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b/_sources/autoapi/dacapo/experiments/architectures/cnnectome_unet/index.rst.txt @@ -193,6 +193,8 @@ Module Contents .. py:property:: eval_shape_increase + :type: funlib.geometry.Coordinate + The increase in shape due to the U-Net. @@ -270,6 +272,8 @@ Module Contents .. py:property:: input_shape + :type: funlib.geometry.Coordinate + Return the input shape of the U-Net. diff --git a/_sources/autoapi/dacapo/experiments/architectures/index.rst.txt b/_sources/autoapi/dacapo/experiments/architectures/index.rst.txt index 787a28c88..ba86becca 100644 --- a/_sources/autoapi/dacapo/experiments/architectures/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/architectures/index.rst.txt @@ -749,6 +749,8 @@ Package Contents .. py:property:: eval_shape_increase + :type: funlib.geometry.Coordinate + The increase in shape due to the U-Net. @@ -826,6 +828,8 @@ Package Contents .. py:property:: input_shape + :type: funlib.geometry.Coordinate + Return the input shape of the U-Net. diff --git a/_sources/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.rst.txt index c941e008d..7fc0e48cc 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.rst.txt @@ -91,3 +91,7 @@ Module Contents :type: bool + .. py:attribute:: kernel_size + :type: int | None + + diff --git a/_sources/autoapi/dacapo/experiments/tasks/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/index.rst.txt index b3f245bff..a949fd193 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/index.rst.txt @@ -413,6 +413,10 @@ Package Contents :type: List[str] + .. py:attribute:: kernel_size + :type: int | None + + .. py:class:: OneHotTask(task_config) @@ -863,6 +867,10 @@ Package Contents :type: bool + .. py:attribute:: kernel_size + :type: int | None + + .. py:class:: HotDistanceTask(task_config) diff --git a/_sources/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.rst.txt index 85c35f49d..567588f44 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.rst.txt @@ -44,3 +44,7 @@ Module Contents :type: List[str] + .. py:attribute:: kernel_size + :type: int | None + + diff --git a/_sources/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.rst.txt index e660a48ee..a466352f6 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.rst.txt @@ -4,6 +4,14 @@ dacapo.experiments.tasks.post_processors.threshold_post_processor .. py:module:: dacapo.experiments.tasks.post_processors.threshold_post_processor +Attributes +---------- + +.. autoapisummary:: + + dacapo.experiments.tasks.post_processors.threshold_post_processor.logger + + Classes ------- @@ -15,6 +23,8 @@ Classes Module Contents --------------- +.. py:data:: logger + .. py:class:: ThresholdPostProcessor diff --git a/_sources/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.rst.txt index c4ce65f13..bc954cdb6 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.rst.txt @@ -25,7 +25,7 @@ Module Contents .. py:data:: logger -.. py:class:: HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool) +.. py:class:: HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool, kernel_size: int) @@ -106,6 +106,9 @@ Module Contents This is a subclass of Predictor. + .. py:attribute:: kernel_size + + .. py:attribute:: channels diff --git a/_sources/autoapi/dacapo/experiments/tasks/predictors/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/predictors/index.rst.txt index 26fe0b1a0..fa9efd5ad 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/predictors/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/predictors/index.rst.txt @@ -422,7 +422,7 @@ Package Contents -.. py:class:: OneHotPredictor(classes: List[str]) +.. py:class:: OneHotPredictor(classes: List[str], kernel_size: int) @@ -466,6 +466,9 @@ Package Contents .. py:attribute:: classes + .. py:attribute:: kernel_size + + .. py:property:: embedding_dims Get the number of embedding dimensions. @@ -1244,7 +1247,7 @@ Package Contents -.. py:class:: HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool) +.. py:class:: HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool, kernel_size: int) @@ -1325,6 +1328,9 @@ Package Contents This is a subclass of Predictor. + .. py:attribute:: kernel_size + + .. py:attribute:: channels diff --git a/_sources/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.rst.txt b/_sources/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.rst.txt index 433a64dbf..636d8cda3 100644 --- a/_sources/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.rst.txt +++ b/_sources/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.rst.txt @@ -25,7 +25,7 @@ Module Contents .. py:data:: logger -.. py:class:: OneHotPredictor(classes: List[str]) +.. py:class:: OneHotPredictor(classes: List[str], kernel_size: int) @@ -69,6 +69,9 @@ Module Contents .. py:attribute:: classes + .. py:attribute:: kernel_size + + .. py:property:: embedding_dims Get the number of embedding dimensions. diff --git a/_sources/notebooks/minimal_tutorial.ipynb.txt b/_sources/notebooks/minimal_tutorial.ipynb.txt index f495947e6..772b2b91b 100644 --- a/_sources/notebooks/minimal_tutorial.ipynb.txt +++ b/_sources/notebooks/minimal_tutorial.ipynb.txt @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "markdown", - "id": "0e9fc2f1", + "id": "09d746ef", "metadata": { "lines_to_next_cell": 2 }, @@ -14,7 +14,7 @@ }, { "cell_type": "markdown", - "id": "169e661a", + "id": "36a59892", "metadata": {}, "source": [ "## Needed Libraries for this Tutorial\n", @@ -28,7 +28,7 @@ }, { "cell_type": "markdown", - "id": "58b04814", + "id": "158c3282", "metadata": {}, "source": [ "## Introduction and overview\n", @@ -53,7 +53,7 @@ }, { "cell_type": "markdown", - "id": "ac805d0e", + "id": "69041e02", "metadata": {}, "source": [ "## Environment setup\n", @@ -79,7 +79,7 @@ }, { "cell_type": "markdown", - "id": "b9f8cfe7", + "id": "6e9bba7e", "metadata": {}, "source": [ "## Config Store\n", @@ -108,13 +108,13 @@ { "cell_type": "code", "execution_count": 1, - "id": "6dd56ef3", + "id": "802f3ac8", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:39.305775Z", - "iopub.status.busy": "2024-11-13T16:49:39.305582Z", - "iopub.status.idle": "2024-11-13T16:49:47.435475Z", - "shell.execute_reply": "2024-11-13T16:49:47.434762Z" + "iopub.execute_input": "2024-11-19T16:12:49.735097Z", + "iopub.status.busy": "2024-11-19T16:12:49.734485Z", + "iopub.status.idle": "2024-11-19T16:12:58.125078Z", + "shell.execute_reply": "2024-11-19T16:12:58.124478Z" } }, "outputs": [ @@ -148,7 +148,7 @@ }, { "cell_type": "markdown", - "id": "3c11c26c", + "id": "9b602c20", "metadata": { "lines_to_next_cell": 0 }, @@ -160,13 +160,13 @@ { "cell_type": "code", "execution_count": 2, - "id": "c0679cf1", + "id": "47fc9f55", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:47.438037Z", - "iopub.status.busy": "2024-11-13T16:49:47.437482Z", - "iopub.status.idle": "2024-11-13T16:49:48.179511Z", - "shell.execute_reply": "2024-11-13T16:49:48.178671Z" + "iopub.execute_input": "2024-11-19T16:12:58.127823Z", + "iopub.status.busy": "2024-11-19T16:12:58.126924Z", + "iopub.status.idle": "2024-11-19T16:12:58.912439Z", + "shell.execute_reply": "2024-11-19T16:12:58.911632Z" }, "lines_to_next_cell": 0, "title": "Create some data" @@ -259,7 +259,7 @@ }, { "cell_type": "markdown", - "id": "f61cc1d8", + "id": "04856a29", "metadata": { "lines_to_next_cell": 0 }, @@ -270,13 +270,13 @@ { "cell_type": "code", "execution_count": 3, - "id": "7cf596f1", + "id": "bcf6b8e4", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.182754Z", - "iopub.status.busy": "2024-11-13T16:49:48.181698Z", - "iopub.status.idle": "2024-11-13T16:49:48.497333Z", - "shell.execute_reply": "2024-11-13T16:49:48.496452Z" + "iopub.execute_input": "2024-11-19T16:12:58.915867Z", + "iopub.status.busy": "2024-11-19T16:12:58.914568Z", + "iopub.status.idle": "2024-11-19T16:12:59.252922Z", + "shell.execute_reply": "2024-11-19T16:12:59.252052Z" }, "lines_to_next_cell": 2 }, @@ -311,7 +311,7 @@ }, { "cell_type": "markdown", - "id": "25e56de5", + "id": "d9080507", "metadata": {}, "source": [ "## Datasplit\n", @@ -327,13 +327,13 @@ { "cell_type": "code", "execution_count": 4, - "id": "84040c4c", + "id": "35f29306", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.500741Z", - "iopub.status.busy": "2024-11-13T16:49:48.500011Z", - "iopub.status.idle": "2024-11-13T16:49:48.506077Z", - "shell.execute_reply": "2024-11-13T16:49:48.505399Z" + "iopub.execute_input": "2024-11-19T16:12:59.256369Z", + "iopub.status.busy": "2024-11-19T16:12:59.256103Z", + "iopub.status.idle": "2024-11-19T16:12:59.262157Z", + "shell.execute_reply": "2024-11-19T16:12:59.261477Z" }, "lines_to_next_cell": 2 }, @@ -350,13 +350,13 @@ { "cell_type": "code", "execution_count": 5, - "id": "21a7fb1c", + "id": "3848fc04", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.508828Z", - "iopub.status.busy": "2024-11-13T16:49:48.508363Z", - "iopub.status.idle": "2024-11-13T16:49:48.511730Z", - "shell.execute_reply": "2024-11-13T16:49:48.511054Z" + "iopub.execute_input": "2024-11-19T16:12:59.265284Z", + "iopub.status.busy": "2024-11-19T16:12:59.264815Z", + "iopub.status.idle": "2024-11-19T16:12:59.268820Z", + "shell.execute_reply": "2024-11-19T16:12:59.268091Z" } }, "outputs": [], @@ -368,13 +368,13 @@ { "cell_type": "code", "execution_count": 6, - "id": "a50331d8", + "id": "e37ac2b5", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.514032Z", - "iopub.status.busy": "2024-11-13T16:49:48.513809Z", - "iopub.status.idle": "2024-11-13T16:49:48.518615Z", - "shell.execute_reply": "2024-11-13T16:49:48.517930Z" + "iopub.execute_input": "2024-11-19T16:12:59.271809Z", + "iopub.status.busy": "2024-11-19T16:12:59.271178Z", + "iopub.status.idle": "2024-11-19T16:12:59.277258Z", + "shell.execute_reply": "2024-11-19T16:12:59.276515Z" } }, "outputs": [], @@ -384,7 +384,7 @@ }, { "cell_type": "markdown", - "id": "010ea4cc", + "id": "b17e5fb9", "metadata": {}, "source": [ "## Task\n", @@ -402,13 +402,13 @@ { "cell_type": "code", "execution_count": 7, - "id": "85c8cff0", + "id": "67aab543", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.521318Z", - "iopub.status.busy": "2024-11-13T16:49:48.520756Z", - "iopub.status.idle": "2024-11-13T16:49:48.531157Z", - "shell.execute_reply": "2024-11-13T16:49:48.530409Z" + "iopub.execute_input": "2024-11-19T16:12:59.279847Z", + "iopub.status.busy": "2024-11-19T16:12:59.279347Z", + "iopub.status.idle": "2024-11-19T16:12:59.292227Z", + "shell.execute_reply": "2024-11-19T16:12:59.291512Z" } }, "outputs": [], @@ -440,7 +440,7 @@ }, { "cell_type": "markdown", - "id": "08b47ee4", + "id": "4b71a1b5", "metadata": {}, "source": [ "## Architecture\n", @@ -454,13 +454,13 @@ { "cell_type": "code", "execution_count": 8, - "id": "a210f14d", + "id": "87e30201", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.533977Z", - "iopub.status.busy": "2024-11-13T16:49:48.533379Z", - "iopub.status.idle": "2024-11-13T16:49:48.542213Z", - "shell.execute_reply": "2024-11-13T16:49:48.541504Z" + "iopub.execute_input": "2024-11-19T16:12:59.294805Z", + "iopub.status.busy": "2024-11-19T16:12:59.294311Z", + "iopub.status.idle": "2024-11-19T16:12:59.304030Z", + "shell.execute_reply": "2024-11-19T16:12:59.303309Z" } }, "outputs": [], @@ -488,7 +488,7 @@ }, { "cell_type": "markdown", - "id": "e9745b9e", + "id": "1796f9c0", "metadata": {}, "source": [ "## Trainer\n", @@ -502,13 +502,13 @@ { "cell_type": "code", "execution_count": 9, - "id": "e554db86", + "id": "f27a40e9", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.544834Z", - "iopub.status.busy": "2024-11-13T16:49:48.544393Z", - "iopub.status.idle": "2024-11-13T16:49:48.549496Z", - "shell.execute_reply": "2024-11-13T16:49:48.548954Z" + "iopub.execute_input": "2024-11-19T16:12:59.306662Z", + "iopub.status.busy": "2024-11-19T16:12:59.306066Z", + "iopub.status.idle": "2024-11-19T16:12:59.311920Z", + "shell.execute_reply": "2024-11-19T16:12:59.311215Z" } }, "outputs": [], @@ -529,7 +529,7 @@ }, { "cell_type": "markdown", - "id": "7e82c042", + "id": "77a383ac", "metadata": {}, "source": [ "## Run\n", @@ -541,13 +541,13 @@ { "cell_type": "code", "execution_count": 10, - "id": "936c9c2d", + "id": "a081ec1a", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.551507Z", - "iopub.status.busy": "2024-11-13T16:49:48.551132Z", - "iopub.status.idle": "2024-11-13T16:49:48.561162Z", - "shell.execute_reply": "2024-11-13T16:49:48.560558Z" + "iopub.execute_input": "2024-11-19T16:12:59.314342Z", + "iopub.status.busy": "2024-11-19T16:12:59.313868Z", + "iopub.status.idle": "2024-11-19T16:12:59.324989Z", + "shell.execute_reply": "2024-11-19T16:12:59.324229Z" } }, "outputs": [], @@ -572,7 +572,7 @@ }, { "cell_type": "markdown", - "id": "d5acdeb8", + "id": "592dd447", "metadata": {}, "source": [ "## Retrieve Configurations\n", @@ -606,7 +606,7 @@ }, { "cell_type": "markdown", - "id": "58f9cd86", + "id": "cbf2245c", "metadata": {}, "source": [ "## Train\n", @@ -620,13 +620,13 @@ { "cell_type": "code", "execution_count": 11, - "id": "f7cda287", + "id": "8963d41e", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T16:49:48.563266Z", - "iopub.status.busy": "2024-11-13T16:49:48.562953Z", - "iopub.status.idle": "2024-11-13T17:18:06.993038Z", - "shell.execute_reply": "2024-11-13T17:18:06.992381Z" + "iopub.execute_input": "2024-11-19T16:12:59.327930Z", + "iopub.status.busy": "2024-11-19T16:12:59.327478Z", + "iopub.status.idle": "2024-11-19T16:48:11.237598Z", + "shell.execute_reply": "2024-11-19T16:48:11.236844Z" } }, "outputs": [ @@ -661,7 +661,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "WARNING:dacapo.experiments.trainers.gunpowder_trainer:Saving Snapshot. Iteration: 0, Loss: 0.8100334405899048!\n" + "WARNING:dacapo.experiments.trainers.gunpowder_trainer:Saving Snapshot. Iteration: 0, Loss: 0.6903617978096008!\n" ] }, { @@ -669,7 +669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 1/2000 [00:00<28:37, 1.16it/s]" + "training until 2000: 0%| | 1/2000 [00:00<32:13, 1.03it/s]" ] }, { @@ -677,7 +677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 1/2000 [00:00<28:37, 1.16it/s, loss=0.81]" + "training until 2000: 0%| | 1/2000 [00:00<32:13, 1.03it/s, loss=0.69]" ] }, { @@ -685,7 +685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 2/2000 [00:02<36:17, 1.09s/it, loss=0.81]" + "training until 2000: 0%| | 2/2000 [00:02<33:56, 1.02s/it, loss=0.69]" ] }, { @@ -693,7 +693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 2/2000 [00:02<36:17, 1.09s/it, loss=0.781]" + "training until 2000: 0%| | 2/2000 [00:02<33:56, 1.02s/it, loss=0.672]" ] }, { @@ -701,7 +701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 3/2000 [00:03<34:08, 1.03s/it, loss=0.781]" + "training until 2000: 0%| | 3/2000 [00:02<30:45, 1.08it/s, loss=0.672]" ] }, { @@ -709,7 +709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 3/2000 [00:03<34:08, 1.03s/it, loss=0.834]" + "training until 2000: 0%| | 3/2000 [00:02<30:45, 1.08it/s, loss=0.679]" ] }, { @@ -717,7 +717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 4/2000 [00:03<27:46, 1.20it/s, loss=0.834]" + "training until 2000: 0%| | 4/2000 [00:03<32:40, 1.02it/s, loss=0.679]" ] }, { @@ -725,7 +725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 4/2000 [00:03<27:46, 1.20it/s, loss=0.813]" + "training until 2000: 0%| | 4/2000 [00:03<32:40, 1.02it/s, loss=0.682]" ] }, { @@ -733,7 +733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 5/2000 [00:04<28:12, 1.18it/s, loss=0.813]" + "training until 2000: 0%| | 5/2000 [00:04<33:21, 1.00s/it, loss=0.682]" ] }, { @@ -741,7 +741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 5/2000 [00:04<28:12, 1.18it/s, loss=0.791]" + "training until 2000: 0%| | 5/2000 [00:04<33:21, 1.00s/it, loss=0.683]" ] }, { @@ -749,7 +749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 6/2000 [00:05<27:42, 1.20it/s, loss=0.791]" + "training until 2000: 0%| | 6/2000 [00:06<34:15, 1.03s/it, loss=0.683]" ] }, { @@ -757,7 +757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 6/2000 [00:05<27:42, 1.20it/s, loss=0.817]" + "training until 2000: 0%| | 6/2000 [00:06<34:15, 1.03s/it, loss=0.675]" ] }, { @@ -765,7 +765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 7/2000 [00:06<28:07, 1.18it/s, loss=0.817]" + "training until 2000: 0%| | 7/2000 [00:06<31:11, 1.07it/s, loss=0.675]" ] }, { @@ -773,7 +773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 7/2000 [00:06<28:07, 1.18it/s, loss=0.807]" + "training until 2000: 0%| | 7/2000 [00:06<31:11, 1.07it/s, loss=0.679]" ] }, { @@ -781,7 +781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 8/2000 [00:06<26:35, 1.25it/s, loss=0.807]" + "training until 2000: 0%| | 8/2000 [00:08<37:07, 1.12s/it, loss=0.679]" ] }, { @@ -789,7 +789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 8/2000 [00:06<26:35, 1.25it/s, loss=0.803]" + "training until 2000: 0%| | 8/2000 [00:08<37:07, 1.12s/it, loss=0.679]" ] }, { @@ -797,7 +797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 9/2000 [00:07<26:57, 1.23it/s, loss=0.803]" + "training until 2000: 0%| | 9/2000 [00:09<37:08, 1.12s/it, loss=0.679]" ] }, { @@ -805,7 +805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 9/2000 [00:07<26:57, 1.23it/s, loss=0.82] " + "training until 2000: 0%| | 9/2000 [00:09<37:08, 1.12s/it, loss=0.691]" ] }, { @@ -813,7 +813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 10/2000 [00:08<30:29, 1.09it/s, loss=0.82]" + "training until 2000: 0%| | 10/2000 [00:09<30:14, 1.10it/s, loss=0.691]" ] }, { @@ -821,7 +821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 0%| | 10/2000 [00:08<30:29, 1.09it/s, loss=0.813]" + "training until 2000: 0%| | 10/2000 [00:09<30:14, 1.10it/s, loss=0.683]" ] }, { @@ -829,7 +829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 11/2000 [00:09<30:39, 1.08it/s, loss=0.813]" + "training until 2000: 1%| | 11/2000 [00:10<31:24, 1.06it/s, loss=0.683]" ] }, { @@ -837,7 +837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 11/2000 [00:09<30:39, 1.08it/s, loss=0.79] " + "training until 2000: 1%| | 11/2000 [00:10<31:24, 1.06it/s, loss=0.687]" ] }, { @@ -845,7 +845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 12/2000 [00:10<28:55, 1.15it/s, loss=0.79]" + "training until 2000: 1%| | 12/2000 [00:11<31:02, 1.07it/s, loss=0.687]" ] }, { @@ -853,7 +853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 12/2000 [00:10<28:55, 1.15it/s, loss=0.816]" + "training until 2000: 1%| | 12/2000 [00:11<31:02, 1.07it/s, loss=0.68] " ] }, { @@ -861,7 +861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 13/2000 [00:11<30:25, 1.09it/s, loss=0.816]" + "training until 2000: 1%| | 13/2000 [00:13<35:15, 1.06s/it, loss=0.68]" ] }, { @@ -869,7 +869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 13/2000 [00:11<30:25, 1.09it/s, loss=0.825]" + "training until 2000: 1%| | 13/2000 [00:13<35:15, 1.06s/it, loss=0.68]" ] }, { @@ -877,7 +877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 14/2000 [00:12<26:46, 1.24it/s, loss=0.825]" + "training until 2000: 1%| | 14/2000 [00:14<38:21, 1.16s/it, loss=0.68]" ] }, { @@ -885,7 +885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 14/2000 [00:12<26:46, 1.24it/s, loss=0.782]" + "training until 2000: 1%| | 14/2000 [00:14<38:21, 1.16s/it, loss=0.678]" ] }, { @@ -893,7 +893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 15/2000 [00:12<25:44, 1.28it/s, loss=0.782]" + "training until 2000: 1%| | 15/2000 [00:15<40:22, 1.22s/it, loss=0.678]" ] }, { @@ -901,7 +901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 15/2000 [00:12<25:44, 1.28it/s, loss=0.804]" + "training until 2000: 1%| | 15/2000 [00:15<40:22, 1.22s/it, loss=0.693]" ] }, { @@ -909,7 +909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 16/2000 [00:13<24:51, 1.33it/s, loss=0.804]" + "training until 2000: 1%| | 16/2000 [00:16<37:31, 1.13s/it, loss=0.693]" ] }, { @@ -917,7 +917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 16/2000 [00:13<24:51, 1.33it/s, loss=0.808]" + "training until 2000: 1%| | 16/2000 [00:16<37:31, 1.13s/it, loss=0.676]" ] }, { @@ -925,7 +925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 17/2000 [00:14<25:28, 1.30it/s, loss=0.808]" + "training until 2000: 1%| | 17/2000 [00:17<37:09, 1.12s/it, loss=0.676]" ] }, { @@ -933,7 +933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 17/2000 [00:14<25:28, 1.30it/s, loss=0.82] " + "training until 2000: 1%| | 17/2000 [00:17<37:09, 1.12s/it, loss=0.678]" ] }, { @@ -941,7 +941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 18/2000 [00:15<25:58, 1.27it/s, loss=0.82]" + "training until 2000: 1%| | 18/2000 [00:19<43:12, 1.31s/it, loss=0.678]" ] }, { @@ -949,7 +949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 18/2000 [00:15<25:58, 1.27it/s, loss=0.858]" + "training until 2000: 1%| | 18/2000 [00:19<43:12, 1.31s/it, loss=0.675]" ] }, { @@ -957,7 +957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 19/2000 [00:16<29:46, 1.11it/s, loss=0.858]" + "training until 2000: 1%| | 19/2000 [00:20<40:33, 1.23s/it, loss=0.675]" ] }, { @@ -965,7 +965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 19/2000 [00:16<29:46, 1.11it/s, loss=0.794]" + "training until 2000: 1%| | 19/2000 [00:20<40:33, 1.23s/it, loss=0.678]" ] }, { @@ -973,7 +973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 20/2000 [00:17<28:34, 1.16it/s, loss=0.794]" + "training until 2000: 1%| | 20/2000 [00:21<36:25, 1.10s/it, loss=0.678]" ] }, { @@ -981,7 +981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 20/2000 [00:17<28:34, 1.16it/s, loss=0.833]" + "training until 2000: 1%| | 20/2000 [00:21<36:25, 1.10s/it, loss=0.684]" ] }, { @@ -989,7 +989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 21/2000 [00:17<27:57, 1.18it/s, loss=0.833]" + "training until 2000: 1%| | 21/2000 [00:22<38:25, 1.17s/it, loss=0.684]" ] }, { @@ -997,7 +997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 21/2000 [00:17<27:57, 1.18it/s, loss=0.815]" + "training until 2000: 1%| | 21/2000 [00:22<38:25, 1.17s/it, loss=0.676]" ] }, { @@ -1005,7 +1005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 22/2000 [00:18<25:13, 1.31it/s, loss=0.815]" + "training until 2000: 1%| | 22/2000 [00:23<34:55, 1.06s/it, loss=0.676]" ] }, { @@ -1013,7 +1013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 22/2000 [00:18<25:13, 1.31it/s, loss=0.801]" + "training until 2000: 1%| | 22/2000 [00:23<34:55, 1.06s/it, loss=0.692]" ] }, { @@ -1021,7 +1021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 23/2000 [00:19<23:10, 1.42it/s, loss=0.801]" + "training until 2000: 1%| | 23/2000 [00:24<34:16, 1.04s/it, loss=0.692]" ] }, { @@ -1029,7 +1029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 23/2000 [00:19<23:10, 1.42it/s, loss=0.735]" + "training until 2000: 1%| | 23/2000 [00:24<34:16, 1.04s/it, loss=0.697]" ] }, { @@ -1037,7 +1037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 24/2000 [00:19<24:37, 1.34it/s, loss=0.735]" + "training until 2000: 1%| | 24/2000 [00:25<34:19, 1.04s/it, loss=0.697]" ] }, { @@ -1045,7 +1045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%| | 24/2000 [00:19<24:37, 1.34it/s, loss=0.804]" + "training until 2000: 1%| | 24/2000 [00:25<34:19, 1.04s/it, loss=0.693]" ] }, { @@ -1053,7 +1053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 25/2000 [00:21<28:15, 1.16it/s, loss=0.804]" + "training until 2000: 1%|▏ | 25/2000 [00:26<30:05, 1.09it/s, loss=0.693]" ] }, { @@ -1061,7 +1061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 25/2000 [00:21<28:15, 1.16it/s, loss=0.769]" + "training until 2000: 1%|▏ | 25/2000 [00:26<30:05, 1.09it/s, loss=0.689]" ] }, { @@ -1069,7 +1069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 26/2000 [00:21<26:57, 1.22it/s, loss=0.769]" + "training until 2000: 1%|▏ | 26/2000 [00:27<30:04, 1.09it/s, loss=0.689]" ] }, { @@ -1077,7 +1077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 26/2000 [00:21<26:57, 1.22it/s, loss=0.815]" + "training until 2000: 1%|▏ | 26/2000 [00:27<30:04, 1.09it/s, loss=0.672]" ] }, { @@ -1085,7 +1085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 27/2000 [00:22<28:27, 1.16it/s, loss=0.815]" + "training until 2000: 1%|▏ | 27/2000 [00:28<29:36, 1.11it/s, loss=0.672]" ] }, { @@ -1093,7 +1093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 27/2000 [00:22<28:27, 1.16it/s, loss=0.825]" + "training until 2000: 1%|▏ | 27/2000 [00:28<29:36, 1.11it/s, loss=0.678]" ] }, { @@ -1101,7 +1101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 28/2000 [00:23<28:11, 1.17it/s, loss=0.825]" + "training until 2000: 1%|▏ | 28/2000 [00:28<27:56, 1.18it/s, loss=0.678]" ] }, { @@ -1109,7 +1109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 28/2000 [00:23<28:11, 1.17it/s, loss=0.777]" + "training until 2000: 1%|▏ | 28/2000 [00:28<27:56, 1.18it/s, loss=0.689]" ] }, { @@ -1117,7 +1117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 29/2000 [00:24<25:23, 1.29it/s, loss=0.777]" + "training until 2000: 1%|▏ | 29/2000 [00:29<30:32, 1.08it/s, loss=0.689]" ] }, { @@ -1125,7 +1125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 1%|▏ | 29/2000 [00:24<25:23, 1.29it/s, loss=0.829]" + "training until 2000: 1%|▏ | 29/2000 [00:29<30:32, 1.08it/s, loss=0.692]" ] }, { @@ -1133,7 +1133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 30/2000 [00:24<24:26, 1.34it/s, loss=0.829]" + "training until 2000: 2%|▏ | 30/2000 [00:30<31:23, 1.05it/s, loss=0.692]" ] }, { @@ -1141,7 +1141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 30/2000 [00:24<24:26, 1.34it/s, loss=0.81] " + "training until 2000: 2%|▏ | 30/2000 [00:30<31:23, 1.05it/s, loss=0.69] " ] }, { @@ -1149,7 +1149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 31/2000 [00:25<24:40, 1.33it/s, loss=0.81]" + "training until 2000: 2%|▏ | 31/2000 [00:32<33:57, 1.03s/it, loss=0.69]" ] }, { @@ -1157,7 +1157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 31/2000 [00:25<24:40, 1.33it/s, loss=0.837]" + "training until 2000: 2%|▏ | 31/2000 [00:32<33:57, 1.03s/it, loss=0.673]" ] }, { @@ -1165,7 +1165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 32/2000 [00:26<24:04, 1.36it/s, loss=0.837]" + "training until 2000: 2%|▏ | 32/2000 [00:32<31:10, 1.05it/s, loss=0.673]" ] }, { @@ -1173,7 +1173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 32/2000 [00:26<24:04, 1.36it/s, loss=0.783]" + "training until 2000: 2%|▏ | 32/2000 [00:32<31:10, 1.05it/s, loss=0.687]" ] }, { @@ -1181,7 +1181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 33/2000 [00:26<23:22, 1.40it/s, loss=0.783]" + "training until 2000: 2%|▏ | 33/2000 [00:33<30:31, 1.07it/s, loss=0.687]" ] }, { @@ -1189,7 +1189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 33/2000 [00:26<23:22, 1.40it/s, loss=0.809]" + "training until 2000: 2%|▏ | 33/2000 [00:33<30:31, 1.07it/s, loss=0.689]" ] }, { @@ -1197,7 +1197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 34/2000 [00:27<24:09, 1.36it/s, loss=0.809]" + "training until 2000: 2%|▏ | 34/2000 [00:34<31:21, 1.05it/s, loss=0.689]" ] }, { @@ -1205,7 +1205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 34/2000 [00:27<24:09, 1.36it/s, loss=0.789]" + "training until 2000: 2%|▏ | 34/2000 [00:34<31:21, 1.05it/s, loss=0.67] " ] }, { @@ -1213,7 +1213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 35/2000 [00:28<25:02, 1.31it/s, loss=0.789]" + "training until 2000: 2%|▏ | 35/2000 [00:36<34:50, 1.06s/it, loss=0.67]" ] }, { @@ -1221,7 +1221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 35/2000 [00:28<25:02, 1.31it/s, loss=0.799]" + "training until 2000: 2%|▏ | 35/2000 [00:36<34:50, 1.06s/it, loss=0.689]" ] }, { @@ -1229,7 +1229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 36/2000 [00:29<27:51, 1.17it/s, loss=0.799]" + "training until 2000: 2%|▏ | 36/2000 [00:37<34:12, 1.05s/it, loss=0.689]" ] }, { @@ -1237,7 +1237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 36/2000 [00:29<27:51, 1.17it/s, loss=0.792]" + "training until 2000: 2%|▏ | 36/2000 [00:37<34:12, 1.05s/it, loss=0.677]" ] }, { @@ -1245,7 +1245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 37/2000 [00:30<31:16, 1.05it/s, loss=0.792]" + "training until 2000: 2%|▏ | 37/2000 [00:37<30:48, 1.06it/s, loss=0.677]" ] }, { @@ -1253,7 +1253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 37/2000 [00:30<31:16, 1.05it/s, loss=0.773]" + "training until 2000: 2%|▏ | 37/2000 [00:37<30:48, 1.06it/s, loss=0.689]" ] }, { @@ -1261,7 +1261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 38/2000 [00:31<28:38, 1.14it/s, loss=0.773]" + "training until 2000: 2%|▏ | 38/2000 [00:38<28:41, 1.14it/s, loss=0.689]" ] }, { @@ -1269,7 +1269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 38/2000 [00:31<28:38, 1.14it/s, loss=0.81] " + "training until 2000: 2%|▏ | 38/2000 [00:38<28:41, 1.14it/s, loss=0.693]" ] }, { @@ -1277,7 +1277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 39/2000 [00:32<26:31, 1.23it/s, loss=0.81]" + "training until 2000: 2%|▏ | 39/2000 [00:39<32:52, 1.01s/it, loss=0.693]" ] }, { @@ -1285,7 +1285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 39/2000 [00:32<26:31, 1.23it/s, loss=0.8] " + "training until 2000: 2%|▏ | 39/2000 [00:39<32:52, 1.01s/it, loss=0.68] " ] }, { @@ -1293,7 +1293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 40/2000 [00:32<25:28, 1.28it/s, loss=0.8]" + "training until 2000: 2%|▏ | 40/2000 [00:40<33:37, 1.03s/it, loss=0.68]" ] }, { @@ -1301,7 +1301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 40/2000 [00:32<25:28, 1.28it/s, loss=0.809]" + "training until 2000: 2%|▏ | 40/2000 [00:40<33:37, 1.03s/it, loss=0.678]" ] }, { @@ -1309,7 +1309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 41/2000 [00:34<29:41, 1.10it/s, loss=0.809]" + "training until 2000: 2%|▏ | 41/2000 [00:42<34:20, 1.05s/it, loss=0.678]" ] }, { @@ -1317,7 +1317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 41/2000 [00:34<29:41, 1.10it/s, loss=0.838]" + "training until 2000: 2%|▏ | 41/2000 [00:42<34:20, 1.05s/it, loss=0.682]" ] }, { @@ -1325,7 +1325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 42/2000 [00:34<29:19, 1.11it/s, loss=0.838]" + "training until 2000: 2%|▏ | 42/2000 [00:42<31:23, 1.04it/s, loss=0.682]" ] }, { @@ -1333,7 +1333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 42/2000 [00:34<29:19, 1.11it/s, loss=0.82] " + "training until 2000: 2%|▏ | 42/2000 [00:42<31:23, 1.04it/s, loss=0.67] " ] }, { @@ -1341,7 +1341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 43/2000 [00:35<26:54, 1.21it/s, loss=0.82]" + "training until 2000: 2%|▏ | 43/2000 [00:43<31:02, 1.05it/s, loss=0.67]" ] }, { @@ -1349,7 +1349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 43/2000 [00:35<26:54, 1.21it/s, loss=0.776]" + "training until 2000: 2%|▏ | 43/2000 [00:43<31:02, 1.05it/s, loss=0.678]" ] }, { @@ -1357,7 +1357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 44/2000 [00:36<28:57, 1.13it/s, loss=0.776]" + "training until 2000: 2%|▏ | 44/2000 [00:45<34:07, 1.05s/it, loss=0.678]" ] }, { @@ -1365,7 +1365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 44/2000 [00:36<28:57, 1.13it/s, loss=0.839]" + "training until 2000: 2%|▏ | 44/2000 [00:45<34:07, 1.05s/it, loss=0.676]" ] }, { @@ -1373,7 +1373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 45/2000 [00:37<30:31, 1.07it/s, loss=0.839]" + "training until 2000: 2%|▏ | 45/2000 [00:46<36:29, 1.12s/it, loss=0.676]" ] }, { @@ -1381,7 +1381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 45/2000 [00:37<30:31, 1.07it/s, loss=0.779]" + "training until 2000: 2%|▏ | 45/2000 [00:46<36:29, 1.12s/it, loss=0.688]" ] }, { @@ -1389,7 +1389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 46/2000 [00:38<28:40, 1.14it/s, loss=0.779]" + "training until 2000: 2%|▏ | 46/2000 [00:47<38:17, 1.18s/it, loss=0.688]" ] }, { @@ -1397,7 +1397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 46/2000 [00:38<28:40, 1.14it/s, loss=0.805]" + "training until 2000: 2%|▏ | 46/2000 [00:47<38:17, 1.18s/it, loss=0.677]" ] }, { @@ -1405,7 +1405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 47/2000 [00:39<27:29, 1.18it/s, loss=0.805]" + "training until 2000: 2%|▏ | 47/2000 [00:48<37:40, 1.16s/it, loss=0.677]" ] }, { @@ -1413,7 +1413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 47/2000 [00:39<27:29, 1.18it/s, loss=0.82] " + "training until 2000: 2%|▏ | 47/2000 [00:48<37:40, 1.16s/it, loss=0.681]" ] }, { @@ -1421,7 +1421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 48/2000 [00:40<30:40, 1.06it/s, loss=0.82]" + "training until 2000: 2%|▏ | 48/2000 [00:49<32:54, 1.01s/it, loss=0.681]" ] }, { @@ -1429,7 +1429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 48/2000 [00:40<30:40, 1.06it/s, loss=0.8] " + "training until 2000: 2%|▏ | 48/2000 [00:49<32:54, 1.01s/it, loss=0.691]" ] }, { @@ -1437,7 +1437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 49/2000 [00:41<29:08, 1.12it/s, loss=0.8]" + "training until 2000: 2%|▏ | 49/2000 [00:50<30:12, 1.08it/s, loss=0.691]" ] }, { @@ -1445,7 +1445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▏ | 49/2000 [00:41<29:08, 1.12it/s, loss=0.838]" + "training until 2000: 2%|▏ | 49/2000 [00:50<30:12, 1.08it/s, loss=0.682]" ] }, { @@ -1453,7 +1453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▎ | 50/2000 [00:42<29:37, 1.10it/s, loss=0.838]" + "training until 2000: 2%|▎ | 50/2000 [00:51<31:59, 1.02it/s, loss=0.682]" ] }, { @@ -1461,7 +1461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 2%|▎ | 50/2000 [00:42<29:37, 1.10it/s, loss=0.831]" + "training until 2000: 2%|▎ | 50/2000 [00:51<31:59, 1.02it/s, loss=0.69] " ] }, { @@ -1469,7 +1469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 51/2000 [00:43<35:07, 1.08s/it, loss=0.831]" + "training until 2000: 3%|▎ | 51/2000 [00:52<33:37, 1.03s/it, loss=0.69]" ] }, { @@ -1477,7 +1477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 51/2000 [00:43<35:07, 1.08s/it, loss=0.768]" + "training until 2000: 3%|▎ | 51/2000 [00:52<33:37, 1.03s/it, loss=0.679]" ] }, { @@ -1485,7 +1485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 52/2000 [00:44<31:04, 1.04it/s, loss=0.768]" + "training until 2000: 3%|▎ | 52/2000 [00:53<31:17, 1.04it/s, loss=0.679]" ] }, { @@ -1493,7 +1493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 52/2000 [00:44<31:04, 1.04it/s, loss=0.804]" + "training until 2000: 3%|▎ | 52/2000 [00:53<31:17, 1.04it/s, loss=0.68] " ] }, { @@ -1501,7 +1501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 53/2000 [00:44<27:19, 1.19it/s, loss=0.804]" + "training until 2000: 3%|▎ | 53/2000 [00:54<36:15, 1.12s/it, loss=0.68]" ] }, { @@ -1509,7 +1509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 53/2000 [00:44<27:19, 1.19it/s, loss=0.826]" + "training until 2000: 3%|▎ | 53/2000 [00:54<36:15, 1.12s/it, loss=0.696]" ] }, { @@ -1517,7 +1517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 54/2000 [00:45<30:09, 1.08it/s, loss=0.826]" + "training until 2000: 3%|▎ | 54/2000 [00:55<32:59, 1.02s/it, loss=0.696]" ] }, { @@ -1525,7 +1525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 54/2000 [00:45<30:09, 1.08it/s, loss=0.79] " + "training until 2000: 3%|▎ | 54/2000 [00:55<32:59, 1.02s/it, loss=0.678]" ] }, { @@ -1533,7 +1533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 55/2000 [00:47<31:46, 1.02it/s, loss=0.79]" + "training until 2000: 3%|▎ | 55/2000 [00:56<31:30, 1.03it/s, loss=0.678]" ] }, { @@ -1541,7 +1541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 55/2000 [00:47<31:46, 1.02it/s, loss=0.793]" + "training until 2000: 3%|▎ | 55/2000 [00:56<31:30, 1.03it/s, loss=0.673]" ] }, { @@ -1549,7 +1549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 56/2000 [00:47<28:54, 1.12it/s, loss=0.793]" + "training until 2000: 3%|▎ | 56/2000 [00:57<32:11, 1.01it/s, loss=0.673]" ] }, { @@ -1557,7 +1557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 56/2000 [00:47<28:54, 1.12it/s, loss=0.831]" + "training until 2000: 3%|▎ | 56/2000 [00:57<32:11, 1.01it/s, loss=0.673]" ] }, { @@ -1565,7 +1565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 57/2000 [00:48<26:45, 1.21it/s, loss=0.831]" + "training until 2000: 3%|▎ | 57/2000 [00:58<31:08, 1.04it/s, loss=0.673]" ] }, { @@ -1573,7 +1573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 57/2000 [00:48<26:45, 1.21it/s, loss=0.836]" + "training until 2000: 3%|▎ | 57/2000 [00:58<31:08, 1.04it/s, loss=0.696]" ] }, { @@ -1581,7 +1581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 58/2000 [00:49<25:44, 1.26it/s, loss=0.836]" + "training until 2000: 3%|▎ | 58/2000 [00:59<37:26, 1.16s/it, loss=0.696]" ] }, { @@ -1589,7 +1589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 58/2000 [00:49<25:44, 1.26it/s, loss=0.838]" + "training until 2000: 3%|▎ | 58/2000 [00:59<37:26, 1.16s/it, loss=0.678]" ] }, { @@ -1597,7 +1597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 59/2000 [00:49<24:08, 1.34it/s, loss=0.838]" + "training until 2000: 3%|▎ | 59/2000 [01:00<35:13, 1.09s/it, loss=0.678]" ] }, { @@ -1605,7 +1605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 59/2000 [00:49<24:08, 1.34it/s, loss=0.799]" + "training until 2000: 3%|▎ | 59/2000 [01:00<35:13, 1.09s/it, loss=0.677]" ] }, { @@ -1613,7 +1613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 60/2000 [00:50<25:52, 1.25it/s, loss=0.799]" + "training until 2000: 3%|▎ | 60/2000 [01:01<35:46, 1.11s/it, loss=0.677]" ] }, { @@ -1621,7 +1621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 60/2000 [00:50<25:52, 1.25it/s, loss=0.832]" + "training until 2000: 3%|▎ | 60/2000 [01:01<35:46, 1.11s/it, loss=0.682]" ] }, { @@ -1629,7 +1629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 61/2000 [00:51<25:46, 1.25it/s, loss=0.832]" + "training until 2000: 3%|▎ | 61/2000 [01:02<34:22, 1.06s/it, loss=0.682]" ] }, { @@ -1637,7 +1637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 61/2000 [00:51<25:46, 1.25it/s, loss=0.802]" + "training until 2000: 3%|▎ | 61/2000 [01:02<34:22, 1.06s/it, loss=0.673]" ] }, { @@ -1645,7 +1645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 62/2000 [00:52<29:22, 1.10it/s, loss=0.802]" + "training until 2000: 3%|▎ | 62/2000 [01:03<29:15, 1.10it/s, loss=0.673]" ] }, { @@ -1653,7 +1653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 62/2000 [00:52<29:22, 1.10it/s, loss=0.804]" + "training until 2000: 3%|▎ | 62/2000 [01:03<29:15, 1.10it/s, loss=0.675]" ] }, { @@ -1661,7 +1661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 63/2000 [00:53<29:19, 1.10it/s, loss=0.804]" + "training until 2000: 3%|▎ | 63/2000 [01:04<30:41, 1.05it/s, loss=0.675]" ] }, { @@ -1669,7 +1669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 63/2000 [00:53<29:19, 1.10it/s, loss=0.819]" + "training until 2000: 3%|▎ | 63/2000 [01:04<30:41, 1.05it/s, loss=0.682]" ] }, { @@ -1677,7 +1677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 64/2000 [00:54<27:44, 1.16it/s, loss=0.819]" + "training until 2000: 3%|▎ | 64/2000 [01:05<30:33, 1.06it/s, loss=0.682]" ] }, { @@ -1685,7 +1685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 64/2000 [00:54<27:44, 1.16it/s, loss=0.774]" + "training until 2000: 3%|▎ | 64/2000 [01:05<30:33, 1.06it/s, loss=0.705]" ] }, { @@ -1693,7 +1693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 65/2000 [00:54<25:56, 1.24it/s, loss=0.774]" + "training until 2000: 3%|▎ | 65/2000 [01:06<29:17, 1.10it/s, loss=0.705]" ] }, { @@ -1701,7 +1701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 65/2000 [00:54<25:56, 1.24it/s, loss=0.83] " + "training until 2000: 3%|▎ | 65/2000 [01:06<29:17, 1.10it/s, loss=0.678]" ] }, { @@ -1709,7 +1709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 66/2000 [00:55<27:16, 1.18it/s, loss=0.83]" + "training until 2000: 3%|▎ | 66/2000 [01:07<27:55, 1.15it/s, loss=0.678]" ] }, { @@ -1717,7 +1717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 66/2000 [00:55<27:16, 1.18it/s, loss=0.783]" + "training until 2000: 3%|▎ | 66/2000 [01:07<27:55, 1.15it/s, loss=0.681]" ] }, { @@ -1725,7 +1725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 67/2000 [00:56<28:52, 1.12it/s, loss=0.783]" + "training until 2000: 3%|▎ | 67/2000 [01:07<28:09, 1.14it/s, loss=0.681]" ] }, { @@ -1733,7 +1733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 67/2000 [00:56<28:52, 1.12it/s, loss=0.821]" + "training until 2000: 3%|▎ | 67/2000 [01:07<28:09, 1.14it/s, loss=0.673]" ] }, { @@ -1741,7 +1741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 68/2000 [00:57<27:50, 1.16it/s, loss=0.821]" + "training until 2000: 3%|▎ | 68/2000 [01:08<27:40, 1.16it/s, loss=0.673]" ] }, { @@ -1749,7 +1749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 68/2000 [00:57<27:50, 1.16it/s, loss=0.844]" + "training until 2000: 3%|▎ | 68/2000 [01:08<27:40, 1.16it/s, loss=0.676]" ] }, { @@ -1757,7 +1757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 69/2000 [00:58<25:21, 1.27it/s, loss=0.844]" + "training until 2000: 3%|▎ | 69/2000 [01:10<33:21, 1.04s/it, loss=0.676]" ] }, { @@ -1765,7 +1765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 3%|▎ | 69/2000 [00:58<25:21, 1.27it/s, loss=0.821]" + "training until 2000: 3%|▎ | 69/2000 [01:10<33:21, 1.04s/it, loss=0.689]" ] }, { @@ -1773,7 +1773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 70/2000 [00:59<25:37, 1.26it/s, loss=0.821]" + "training until 2000: 4%|▎ | 70/2000 [01:11<33:04, 1.03s/it, loss=0.689]" ] }, { @@ -1781,7 +1781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 70/2000 [00:59<25:37, 1.26it/s, loss=0.846]" + "training until 2000: 4%|▎ | 70/2000 [01:11<33:04, 1.03s/it, loss=0.693]" ] }, { @@ -1789,7 +1789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 71/2000 [00:59<24:35, 1.31it/s, loss=0.846]" + "training until 2000: 4%|▎ | 71/2000 [01:12<38:13, 1.19s/it, loss=0.693]" ] }, { @@ -1797,7 +1797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 71/2000 [00:59<24:35, 1.31it/s, loss=0.764]" + "training until 2000: 4%|▎ | 71/2000 [01:12<38:13, 1.19s/it, loss=0.687]" ] }, { @@ -1805,7 +1805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 72/2000 [01:00<22:58, 1.40it/s, loss=0.764]" + "training until 2000: 4%|▎ | 72/2000 [01:13<38:05, 1.19s/it, loss=0.687]" ] }, { @@ -1813,7 +1813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 72/2000 [01:00<22:58, 1.40it/s, loss=0.772]" + "training until 2000: 4%|▎ | 72/2000 [01:13<38:05, 1.19s/it, loss=0.676]" ] }, { @@ -1821,7 +1821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 73/2000 [01:01<21:35, 1.49it/s, loss=0.772]" + "training until 2000: 4%|▎ | 73/2000 [01:15<38:03, 1.18s/it, loss=0.676]" ] }, { @@ -1829,7 +1829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 73/2000 [01:01<21:35, 1.49it/s, loss=0.807]" + "training until 2000: 4%|▎ | 73/2000 [01:15<38:03, 1.18s/it, loss=0.692]" ] }, { @@ -1837,7 +1837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 74/2000 [01:01<22:57, 1.40it/s, loss=0.807]" + "training until 2000: 4%|▎ | 74/2000 [01:16<35:24, 1.10s/it, loss=0.692]" ] }, { @@ -1845,7 +1845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▎ | 74/2000 [01:01<22:57, 1.40it/s, loss=0.839]" + "training until 2000: 4%|▎ | 74/2000 [01:16<35:24, 1.10s/it, loss=0.668]" ] }, { @@ -1853,7 +1853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 75/2000 [01:02<22:08, 1.45it/s, loss=0.839]" + "training until 2000: 4%|▍ | 75/2000 [01:16<33:09, 1.03s/it, loss=0.668]" ] }, { @@ -1861,7 +1861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 75/2000 [01:02<22:08, 1.45it/s, loss=0.811]" + "training until 2000: 4%|▍ | 75/2000 [01:16<33:09, 1.03s/it, loss=0.677]" ] }, { @@ -1869,7 +1869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 76/2000 [01:03<24:51, 1.29it/s, loss=0.811]" + "training until 2000: 4%|▍ | 76/2000 [01:17<30:50, 1.04it/s, loss=0.677]" ] }, { @@ -1877,7 +1877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 76/2000 [01:03<24:51, 1.29it/s, loss=0.813]" + "training until 2000: 4%|▍ | 76/2000 [01:17<30:50, 1.04it/s, loss=0.684]" ] }, { @@ -1885,7 +1885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 77/2000 [01:04<25:40, 1.25it/s, loss=0.813]" + "training until 2000: 4%|▍ | 77/2000 [01:18<28:22, 1.13it/s, loss=0.684]" ] }, { @@ -1893,7 +1893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 77/2000 [01:04<25:40, 1.25it/s, loss=0.786]" + "training until 2000: 4%|▍ | 77/2000 [01:18<28:22, 1.13it/s, loss=0.687]" ] }, { @@ -1901,7 +1901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 78/2000 [01:05<25:49, 1.24it/s, loss=0.786]" + "training until 2000: 4%|▍ | 78/2000 [01:19<27:38, 1.16it/s, loss=0.687]" ] }, { @@ -1909,7 +1909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 78/2000 [01:05<25:49, 1.24it/s, loss=0.818]" + "training until 2000: 4%|▍ | 78/2000 [01:19<27:38, 1.16it/s, loss=0.688]" ] }, { @@ -1917,7 +1917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 79/2000 [01:06<27:50, 1.15it/s, loss=0.818]" + "training until 2000: 4%|▍ | 79/2000 [01:19<26:31, 1.21it/s, loss=0.688]" ] }, { @@ -1925,7 +1925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 79/2000 [01:06<27:50, 1.15it/s, loss=0.805]" + "training until 2000: 4%|▍ | 79/2000 [01:19<26:31, 1.21it/s, loss=0.69] " ] }, { @@ -1933,7 +1933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 80/2000 [01:07<28:11, 1.14it/s, loss=0.805]" + "training until 2000: 4%|▍ | 80/2000 [01:20<25:44, 1.24it/s, loss=0.69]" ] }, { @@ -1941,7 +1941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 80/2000 [01:07<28:11, 1.14it/s, loss=0.836]" + "training until 2000: 4%|▍ | 80/2000 [01:20<25:44, 1.24it/s, loss=0.691]" ] }, { @@ -1949,7 +1949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 81/2000 [01:07<27:41, 1.15it/s, loss=0.836]" + "training until 2000: 4%|▍ | 81/2000 [01:21<27:17, 1.17it/s, loss=0.691]" ] }, { @@ -1957,7 +1957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 81/2000 [01:07<27:41, 1.15it/s, loss=0.804]" + "training until 2000: 4%|▍ | 81/2000 [01:21<27:17, 1.17it/s, loss=0.689]" ] }, { @@ -1965,7 +1965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 82/2000 [01:08<26:58, 1.19it/s, loss=0.804]" + "training until 2000: 4%|▍ | 82/2000 [01:22<30:48, 1.04it/s, loss=0.689]" ] }, { @@ -1973,7 +1973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 82/2000 [01:08<26:58, 1.19it/s, loss=0.822]" + "training until 2000: 4%|▍ | 82/2000 [01:22<30:48, 1.04it/s, loss=0.691]" ] }, { @@ -1981,7 +1981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 83/2000 [01:09<28:11, 1.13it/s, loss=0.822]" + "training until 2000: 4%|▍ | 83/2000 [01:23<32:01, 1.00s/it, loss=0.691]" ] }, { @@ -1989,7 +1989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 83/2000 [01:09<28:11, 1.13it/s, loss=0.829]" + "training until 2000: 4%|▍ | 83/2000 [01:23<32:01, 1.00s/it, loss=0.684]" ] }, { @@ -1997,7 +1997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 84/2000 [01:10<25:27, 1.25it/s, loss=0.829]" + "training until 2000: 4%|▍ | 84/2000 [01:24<30:43, 1.04it/s, loss=0.684]" ] }, { @@ -2005,7 +2005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 84/2000 [01:10<25:27, 1.25it/s, loss=0.829]" + "training until 2000: 4%|▍ | 84/2000 [01:24<30:43, 1.04it/s, loss=0.676]" ] }, { @@ -2013,7 +2013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 85/2000 [01:10<24:53, 1.28it/s, loss=0.829]" + "training until 2000: 4%|▍ | 85/2000 [01:25<28:22, 1.13it/s, loss=0.676]" ] }, { @@ -2021,7 +2021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 85/2000 [01:10<24:53, 1.28it/s, loss=0.789]" + "training until 2000: 4%|▍ | 85/2000 [01:25<28:22, 1.13it/s, loss=0.67] " ] }, { @@ -2029,7 +2029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 86/2000 [01:11<24:59, 1.28it/s, loss=0.789]" + "training until 2000: 4%|▍ | 86/2000 [01:26<26:30, 1.20it/s, loss=0.67]" ] }, { @@ -2037,7 +2037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 86/2000 [01:11<24:59, 1.28it/s, loss=0.786]" + "training until 2000: 4%|▍ | 86/2000 [01:26<26:30, 1.20it/s, loss=0.68]" ] }, { @@ -2045,7 +2045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 87/2000 [01:12<24:59, 1.28it/s, loss=0.786]" + "training until 2000: 4%|▍ | 87/2000 [01:27<26:08, 1.22it/s, loss=0.68]" ] }, { @@ -2053,7 +2053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 87/2000 [01:12<24:59, 1.28it/s, loss=0.793]" + "training until 2000: 4%|▍ | 87/2000 [01:27<26:08, 1.22it/s, loss=0.684]" ] }, { @@ -2061,7 +2061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 88/2000 [01:13<22:41, 1.40it/s, loss=0.793]" + "training until 2000: 4%|▍ | 88/2000 [01:27<26:24, 1.21it/s, loss=0.684]" ] }, { @@ -2069,7 +2069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 88/2000 [01:13<22:41, 1.40it/s, loss=0.817]" + "training until 2000: 4%|▍ | 88/2000 [01:27<26:24, 1.21it/s, loss=0.702]" ] }, { @@ -2077,7 +2077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 89/2000 [01:13<22:05, 1.44it/s, loss=0.817]" + "training until 2000: 4%|▍ | 89/2000 [01:28<26:27, 1.20it/s, loss=0.702]" ] }, { @@ -2085,7 +2085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 89/2000 [01:13<22:05, 1.44it/s, loss=0.831]" + "training until 2000: 4%|▍ | 89/2000 [01:28<26:27, 1.20it/s, loss=0.676]" ] }, { @@ -2093,7 +2093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 90/2000 [01:14<24:43, 1.29it/s, loss=0.831]" + "training until 2000: 4%|▍ | 90/2000 [01:29<27:03, 1.18it/s, loss=0.676]" ] }, { @@ -2101,7 +2101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 4%|▍ | 90/2000 [01:14<24:43, 1.29it/s, loss=0.782]" + "training until 2000: 4%|▍ | 90/2000 [01:29<27:03, 1.18it/s, loss=0.693]" ] }, { @@ -2109,7 +2109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 91/2000 [01:15<24:48, 1.28it/s, loss=0.782]" + "training until 2000: 5%|▍ | 91/2000 [01:30<26:56, 1.18it/s, loss=0.693]" ] }, { @@ -2117,7 +2117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 91/2000 [01:15<24:48, 1.28it/s, loss=0.832]" + "training until 2000: 5%|▍ | 91/2000 [01:30<26:56, 1.18it/s, loss=0.684]" ] }, { @@ -2125,7 +2125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 92/2000 [01:16<24:54, 1.28it/s, loss=0.832]" + "training until 2000: 5%|▍ | 92/2000 [01:31<30:10, 1.05it/s, loss=0.684]" ] }, { @@ -2133,7 +2133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 92/2000 [01:16<24:54, 1.28it/s, loss=0.796]" + "training until 2000: 5%|▍ | 92/2000 [01:31<30:10, 1.05it/s, loss=0.672]" ] }, { @@ -2141,7 +2141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 93/2000 [01:17<24:37, 1.29it/s, loss=0.796]" + "training until 2000: 5%|▍ | 93/2000 [01:32<30:24, 1.05it/s, loss=0.672]" ] }, { @@ -2149,7 +2149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 93/2000 [01:17<24:37, 1.29it/s, loss=0.812]" + "training until 2000: 5%|▍ | 93/2000 [01:32<30:24, 1.05it/s, loss=0.682]" ] }, { @@ -2157,7 +2157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 94/2000 [01:17<23:36, 1.35it/s, loss=0.812]" + "training until 2000: 5%|▍ | 94/2000 [01:33<28:15, 1.12it/s, loss=0.682]" ] }, { @@ -2165,7 +2165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 94/2000 [01:17<23:36, 1.35it/s, loss=0.812]" + "training until 2000: 5%|▍ | 94/2000 [01:33<28:15, 1.12it/s, loss=0.682]" ] }, { @@ -2173,7 +2173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 95/2000 [01:18<24:14, 1.31it/s, loss=0.812]" + "training until 2000: 5%|▍ | 95/2000 [01:34<30:06, 1.05it/s, loss=0.682]" ] }, { @@ -2181,7 +2181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 95/2000 [01:18<24:14, 1.31it/s, loss=0.853]" + "training until 2000: 5%|▍ | 95/2000 [01:34<30:06, 1.05it/s, loss=0.688]" ] }, { @@ -2189,7 +2189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 96/2000 [01:19<24:21, 1.30it/s, loss=0.853]" + "training until 2000: 5%|▍ | 96/2000 [01:35<32:23, 1.02s/it, loss=0.688]" ] }, { @@ -2197,7 +2197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 96/2000 [01:19<24:21, 1.30it/s, loss=0.794]" + "training until 2000: 5%|▍ | 96/2000 [01:35<32:23, 1.02s/it, loss=0.682]" ] }, { @@ -2205,7 +2205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 97/2000 [01:19<23:16, 1.36it/s, loss=0.794]" + "training until 2000: 5%|▍ | 97/2000 [01:36<34:27, 1.09s/it, loss=0.682]" ] }, { @@ -2213,7 +2213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 97/2000 [01:19<23:16, 1.36it/s, loss=0.825]" + "training until 2000: 5%|▍ | 97/2000 [01:36<34:27, 1.09s/it, loss=0.684]" ] }, { @@ -2221,7 +2221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 98/2000 [01:20<21:19, 1.49it/s, loss=0.825]" + "training until 2000: 5%|▍ | 98/2000 [01:37<30:46, 1.03it/s, loss=0.684]" ] }, { @@ -2229,7 +2229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 98/2000 [01:20<21:19, 1.49it/s, loss=0.792]" + "training until 2000: 5%|▍ | 98/2000 [01:37<30:46, 1.03it/s, loss=0.683]" ] }, { @@ -2237,7 +2237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 99/2000 [01:21<20:49, 1.52it/s, loss=0.792]" + "training until 2000: 5%|▍ | 99/2000 [01:38<34:34, 1.09s/it, loss=0.683]" ] }, { @@ -2245,7 +2245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▍ | 99/2000 [01:21<20:49, 1.52it/s, loss=0.795]" + "training until 2000: 5%|▍ | 99/2000 [01:38<34:34, 1.09s/it, loss=0.687]" ] }, { @@ -2253,7 +2253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 100/2000 [01:22<23:23, 1.35it/s, loss=0.795]" + "training until 2000: 5%|▌ | 100/2000 [01:39<32:01, 1.01s/it, loss=0.687]" ] }, { @@ -2261,7 +2261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 100/2000 [01:22<23:23, 1.35it/s, loss=0.825]" + "training until 2000: 5%|▌ | 100/2000 [01:39<32:01, 1.01s/it, loss=0.68] " ] }, { @@ -2269,7 +2269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 101/2000 [01:22<24:16, 1.30it/s, loss=0.825]" + "training until 2000: 5%|▌ | 101/2000 [01:41<34:05, 1.08s/it, loss=0.68]" ] }, { @@ -2277,7 +2277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 101/2000 [01:22<24:16, 1.30it/s, loss=0.793]" + "training until 2000: 5%|▌ | 101/2000 [01:41<34:05, 1.08s/it, loss=0.675]" ] }, { @@ -2285,7 +2285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 102/2000 [01:23<25:29, 1.24it/s, loss=0.793]" + "training until 2000: 5%|▌ | 102/2000 [01:41<31:34, 1.00it/s, loss=0.675]" ] }, { @@ -2293,7 +2293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 102/2000 [01:23<25:29, 1.24it/s, loss=0.767]" + "training until 2000: 5%|▌ | 102/2000 [01:41<31:34, 1.00it/s, loss=0.682]" ] }, { @@ -2301,7 +2301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 103/2000 [01:24<24:28, 1.29it/s, loss=0.767]" + "training until 2000: 5%|▌ | 103/2000 [01:42<31:23, 1.01it/s, loss=0.682]" ] }, { @@ -2309,7 +2309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 103/2000 [01:24<24:28, 1.29it/s, loss=0.827]" + "training until 2000: 5%|▌ | 103/2000 [01:42<31:23, 1.01it/s, loss=0.668]" ] }, { @@ -2317,7 +2317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 104/2000 [01:25<25:00, 1.26it/s, loss=0.827]" + "training until 2000: 5%|▌ | 104/2000 [01:44<33:20, 1.06s/it, loss=0.668]" ] }, { @@ -2325,7 +2325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 104/2000 [01:25<25:00, 1.26it/s, loss=0.797]" + "training until 2000: 5%|▌ | 104/2000 [01:44<33:20, 1.06s/it, loss=0.686]" ] }, { @@ -2333,7 +2333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 105/2000 [01:26<24:23, 1.29it/s, loss=0.797]" + "training until 2000: 5%|▌ | 105/2000 [01:45<33:39, 1.07s/it, loss=0.686]" ] }, { @@ -2341,7 +2341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 105/2000 [01:26<24:23, 1.29it/s, loss=0.79] " + "training until 2000: 5%|▌ | 105/2000 [01:45<33:39, 1.07s/it, loss=0.681]" ] }, { @@ -2349,7 +2349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 106/2000 [01:26<22:33, 1.40it/s, loss=0.79]" + "training until 2000: 5%|▌ | 106/2000 [01:46<36:52, 1.17s/it, loss=0.681]" ] }, { @@ -2357,7 +2357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 106/2000 [01:26<22:33, 1.40it/s, loss=0.816]" + "training until 2000: 5%|▌ | 106/2000 [01:46<36:52, 1.17s/it, loss=0.674]" ] }, { @@ -2365,7 +2365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 107/2000 [01:27<21:33, 1.46it/s, loss=0.816]" + "training until 2000: 5%|▌ | 107/2000 [01:47<38:11, 1.21s/it, loss=0.674]" ] }, { @@ -2373,7 +2373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 107/2000 [01:27<21:33, 1.46it/s, loss=0.785]" + "training until 2000: 5%|▌ | 107/2000 [01:47<38:11, 1.21s/it, loss=0.683]" ] }, { @@ -2381,7 +2381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 108/2000 [01:27<22:10, 1.42it/s, loss=0.785]" + "training until 2000: 5%|▌ | 108/2000 [01:48<32:06, 1.02s/it, loss=0.683]" ] }, { @@ -2389,7 +2389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 108/2000 [01:27<22:10, 1.42it/s, loss=0.822]" + "training until 2000: 5%|▌ | 108/2000 [01:48<32:06, 1.02s/it, loss=0.688]" ] }, { @@ -2397,7 +2397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 109/2000 [01:28<21:02, 1.50it/s, loss=0.822]" + "training until 2000: 5%|▌ | 109/2000 [01:49<29:15, 1.08it/s, loss=0.688]" ] }, { @@ -2405,7 +2405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 5%|▌ | 109/2000 [01:28<21:02, 1.50it/s, loss=0.825]" + "training until 2000: 5%|▌ | 109/2000 [01:49<29:15, 1.08it/s, loss=0.677]" ] }, { @@ -2413,7 +2413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 110/2000 [01:29<23:16, 1.35it/s, loss=0.825]" + "training until 2000: 6%|▌ | 110/2000 [01:50<29:38, 1.06it/s, loss=0.677]" ] }, { @@ -2421,7 +2421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 110/2000 [01:29<23:16, 1.35it/s, loss=0.83] " + "training until 2000: 6%|▌ | 110/2000 [01:50<29:38, 1.06it/s, loss=0.686]" ] }, { @@ -2429,7 +2429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 111/2000 [01:30<22:56, 1.37it/s, loss=0.83]" + "training until 2000: 6%|▌ | 111/2000 [01:50<29:19, 1.07it/s, loss=0.686]" ] }, { @@ -2437,7 +2437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 111/2000 [01:30<22:56, 1.37it/s, loss=0.815]" + "training until 2000: 6%|▌ | 111/2000 [01:50<29:19, 1.07it/s, loss=0.667]" ] }, { @@ -2445,7 +2445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 112/2000 [01:30<21:01, 1.50it/s, loss=0.815]" + "training until 2000: 6%|▌ | 112/2000 [01:51<29:26, 1.07it/s, loss=0.667]" ] }, { @@ -2453,7 +2453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 112/2000 [01:30<21:01, 1.50it/s, loss=0.822]" + "training until 2000: 6%|▌ | 112/2000 [01:51<29:26, 1.07it/s, loss=0.682]" ] }, { @@ -2461,7 +2461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 113/2000 [01:31<22:20, 1.41it/s, loss=0.822]" + "training until 2000: 6%|▌ | 113/2000 [01:52<28:46, 1.09it/s, loss=0.682]" ] }, { @@ -2469,7 +2469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 113/2000 [01:31<22:20, 1.41it/s, loss=0.835]" + "training until 2000: 6%|▌ | 113/2000 [01:52<28:46, 1.09it/s, loss=0.692]" ] }, { @@ -2477,7 +2477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 114/2000 [01:32<21:30, 1.46it/s, loss=0.835]" + "training until 2000: 6%|▌ | 114/2000 [01:53<30:16, 1.04it/s, loss=0.692]" ] }, { @@ -2485,7 +2485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 114/2000 [01:32<21:30, 1.46it/s, loss=0.781]" + "training until 2000: 6%|▌ | 114/2000 [01:53<30:16, 1.04it/s, loss=0.697]" ] }, { @@ -2493,7 +2493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 115/2000 [01:32<22:16, 1.41it/s, loss=0.781]" + "training until 2000: 6%|▌ | 115/2000 [01:54<28:27, 1.10it/s, loss=0.697]" ] }, { @@ -2501,7 +2501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 115/2000 [01:32<22:16, 1.41it/s, loss=0.831]" + "training until 2000: 6%|▌ | 115/2000 [01:54<28:27, 1.10it/s, loss=0.679]" ] }, { @@ -2509,7 +2509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 116/2000 [01:33<21:22, 1.47it/s, loss=0.831]" + "training until 2000: 6%|▌ | 116/2000 [01:55<30:41, 1.02it/s, loss=0.679]" ] }, { @@ -2517,7 +2517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 116/2000 [01:33<21:22, 1.47it/s, loss=0.818]" + "training until 2000: 6%|▌ | 116/2000 [01:55<30:41, 1.02it/s, loss=0.669]" ] }, { @@ -2525,7 +2525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 117/2000 [01:34<24:17, 1.29it/s, loss=0.818]" + "training until 2000: 6%|▌ | 117/2000 [01:57<33:53, 1.08s/it, loss=0.669]" ] }, { @@ -2533,7 +2533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 117/2000 [01:34<24:17, 1.29it/s, loss=0.839]" + "training until 2000: 6%|▌ | 117/2000 [01:57<33:53, 1.08s/it, loss=0.69] " ] }, { @@ -2541,7 +2541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 118/2000 [01:35<22:56, 1.37it/s, loss=0.839]" + "training until 2000: 6%|▌ | 118/2000 [01:58<33:53, 1.08s/it, loss=0.69]" ] }, { @@ -2549,7 +2549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 118/2000 [01:35<22:56, 1.37it/s, loss=0.795]" + "training until 2000: 6%|▌ | 118/2000 [01:58<33:53, 1.08s/it, loss=0.681]" ] }, { @@ -2557,7 +2557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 119/2000 [01:36<26:21, 1.19it/s, loss=0.795]" + "training until 2000: 6%|▌ | 119/2000 [01:59<38:14, 1.22s/it, loss=0.681]" ] }, { @@ -2565,7 +2565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 119/2000 [01:36<26:21, 1.19it/s, loss=0.793]" + "training until 2000: 6%|▌ | 119/2000 [01:59<38:14, 1.22s/it, loss=0.669]" ] }, { @@ -2573,7 +2573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 120/2000 [01:37<26:07, 1.20it/s, loss=0.793]" + "training until 2000: 6%|▌ | 120/2000 [02:00<37:29, 1.20s/it, loss=0.669]" ] }, { @@ -2581,7 +2581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 120/2000 [01:37<26:07, 1.20it/s, loss=0.8] " + "training until 2000: 6%|▌ | 120/2000 [02:00<37:29, 1.20s/it, loss=0.676]" ] }, { @@ -2589,7 +2589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 121/2000 [01:37<23:46, 1.32it/s, loss=0.8]" + "training until 2000: 6%|▌ | 121/2000 [02:01<35:47, 1.14s/it, loss=0.676]" ] }, { @@ -2597,7 +2597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 121/2000 [01:37<23:46, 1.32it/s, loss=0.791]" + "training until 2000: 6%|▌ | 121/2000 [02:01<35:47, 1.14s/it, loss=0.684]" ] }, { @@ -2605,7 +2605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 122/2000 [01:38<23:02, 1.36it/s, loss=0.791]" + "training until 2000: 6%|▌ | 122/2000 [02:02<33:26, 1.07s/it, loss=0.684]" ] }, { @@ -2613,7 +2613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 122/2000 [01:38<23:02, 1.36it/s, loss=0.789]" + "training until 2000: 6%|▌ | 122/2000 [02:02<33:26, 1.07s/it, loss=0.68] " ] }, { @@ -2621,7 +2621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 123/2000 [01:38<20:04, 1.56it/s, loss=0.789]" + "training until 2000: 6%|▌ | 123/2000 [02:03<29:58, 1.04it/s, loss=0.68]" ] }, { @@ -2629,7 +2629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 123/2000 [01:38<20:04, 1.56it/s, loss=0.807]" + "training until 2000: 6%|▌ | 123/2000 [02:03<29:58, 1.04it/s, loss=0.682]" ] }, { @@ -2637,7 +2637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 124/2000 [01:39<20:13, 1.55it/s, loss=0.807]" + "training until 2000: 6%|▌ | 124/2000 [02:05<36:04, 1.15s/it, loss=0.682]" ] }, { @@ -2645,7 +2645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▌ | 124/2000 [01:39<20:13, 1.55it/s, loss=0.817]" + "training until 2000: 6%|▌ | 124/2000 [02:05<36:04, 1.15s/it, loss=0.692]" ] }, { @@ -2653,7 +2653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 125/2000 [01:39<18:41, 1.67it/s, loss=0.817]" + "training until 2000: 6%|▋ | 125/2000 [02:05<32:33, 1.04s/it, loss=0.692]" ] }, { @@ -2661,7 +2661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 125/2000 [01:39<18:41, 1.67it/s, loss=0.819]" + "training until 2000: 6%|▋ | 125/2000 [02:05<32:33, 1.04s/it, loss=0.685]" ] }, { @@ -2669,7 +2669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 126/2000 [01:40<19:48, 1.58it/s, loss=0.819]" + "training until 2000: 6%|▋ | 126/2000 [02:07<35:46, 1.15s/it, loss=0.685]" ] }, { @@ -2677,7 +2677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 126/2000 [01:40<19:48, 1.58it/s, loss=0.828]" + "training until 2000: 6%|▋ | 126/2000 [02:07<35:46, 1.15s/it, loss=0.669]" ] }, { @@ -2685,7 +2685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 127/2000 [01:41<22:17, 1.40it/s, loss=0.828]" + "training until 2000: 6%|▋ | 127/2000 [02:08<37:42, 1.21s/it, loss=0.669]" ] }, { @@ -2693,7 +2693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 127/2000 [01:41<22:17, 1.40it/s, loss=0.811]" + "training until 2000: 6%|▋ | 127/2000 [02:08<37:42, 1.21s/it, loss=0.68] " ] }, { @@ -2701,7 +2701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 128/2000 [01:42<23:07, 1.35it/s, loss=0.811]" + "training until 2000: 6%|▋ | 128/2000 [02:09<35:01, 1.12s/it, loss=0.68]" ] }, { @@ -2709,7 +2709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 128/2000 [01:42<23:07, 1.35it/s, loss=0.811]" + "training until 2000: 6%|▋ | 128/2000 [02:09<35:01, 1.12s/it, loss=0.682]" ] }, { @@ -2717,7 +2717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 129/2000 [01:43<23:18, 1.34it/s, loss=0.811]" + "training until 2000: 6%|▋ | 129/2000 [02:10<30:26, 1.02it/s, loss=0.682]" ] }, { @@ -2725,7 +2725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 129/2000 [01:43<23:18, 1.34it/s, loss=0.782]" + "training until 2000: 6%|▋ | 129/2000 [02:10<30:26, 1.02it/s, loss=0.679]" ] }, { @@ -2733,7 +2733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 130/2000 [01:43<22:06, 1.41it/s, loss=0.782]" + "training until 2000: 6%|▋ | 130/2000 [02:10<27:39, 1.13it/s, loss=0.679]" ] }, { @@ -2741,7 +2741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 6%|▋ | 130/2000 [01:43<22:06, 1.41it/s, loss=0.79] " + "training until 2000: 6%|▋ | 130/2000 [02:10<27:39, 1.13it/s, loss=0.68] " ] }, { @@ -2749,7 +2749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 131/2000 [01:44<23:06, 1.35it/s, loss=0.79]" + "training until 2000: 7%|▋ | 131/2000 [02:11<27:00, 1.15it/s, loss=0.68]" ] }, { @@ -2757,7 +2757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 131/2000 [01:44<23:06, 1.35it/s, loss=0.794]" + "training until 2000: 7%|▋ | 131/2000 [02:11<27:00, 1.15it/s, loss=0.676]" ] }, { @@ -2765,7 +2765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 132/2000 [01:45<22:17, 1.40it/s, loss=0.794]" + "training until 2000: 7%|▋ | 132/2000 [02:12<26:29, 1.18it/s, loss=0.676]" ] }, { @@ -2773,7 +2773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 132/2000 [01:45<22:17, 1.40it/s, loss=0.815]" + "training until 2000: 7%|▋ | 132/2000 [02:12<26:29, 1.18it/s, loss=0.673]" ] }, { @@ -2781,7 +2781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 133/2000 [01:45<21:28, 1.45it/s, loss=0.815]" + "training until 2000: 7%|▋ | 133/2000 [02:13<27:37, 1.13it/s, loss=0.673]" ] }, { @@ -2789,7 +2789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 133/2000 [01:45<21:28, 1.45it/s, loss=0.849]" + "training until 2000: 7%|▋ | 133/2000 [02:13<27:37, 1.13it/s, loss=0.678]" ] }, { @@ -2797,7 +2797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 134/2000 [01:46<20:03, 1.55it/s, loss=0.849]" + "training until 2000: 7%|▋ | 134/2000 [02:14<28:30, 1.09it/s, loss=0.678]" ] }, { @@ -2805,7 +2805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 134/2000 [01:46<20:03, 1.55it/s, loss=0.803]" + "training until 2000: 7%|▋ | 134/2000 [02:14<28:30, 1.09it/s, loss=0.673]" ] }, { @@ -2813,7 +2813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 135/2000 [01:46<19:31, 1.59it/s, loss=0.803]" + "training until 2000: 7%|▋ | 135/2000 [02:15<26:19, 1.18it/s, loss=0.673]" ] }, { @@ -2821,7 +2821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 135/2000 [01:46<19:31, 1.59it/s, loss=0.828]" + "training until 2000: 7%|▋ | 135/2000 [02:15<26:19, 1.18it/s, loss=0.671]" ] }, { @@ -2829,7 +2829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 136/2000 [01:47<23:16, 1.33it/s, loss=0.828]" + "training until 2000: 7%|▋ | 136/2000 [02:16<30:57, 1.00it/s, loss=0.671]" ] }, { @@ -2837,7 +2837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 136/2000 [01:47<23:16, 1.33it/s, loss=0.829]" + "training until 2000: 7%|▋ | 136/2000 [02:16<30:57, 1.00it/s, loss=0.681]" ] }, { @@ -2845,7 +2845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 137/2000 [01:48<23:51, 1.30it/s, loss=0.829]" + "training until 2000: 7%|▋ | 137/2000 [02:17<28:28, 1.09it/s, loss=0.681]" ] }, { @@ -2853,7 +2853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 137/2000 [01:48<23:51, 1.30it/s, loss=0.826]" + "training until 2000: 7%|▋ | 137/2000 [02:17<28:28, 1.09it/s, loss=0.681]" ] }, { @@ -2861,7 +2861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 138/2000 [01:49<23:36, 1.31it/s, loss=0.826]" + "training until 2000: 7%|▋ | 138/2000 [02:18<33:03, 1.07s/it, loss=0.681]" ] }, { @@ -2869,7 +2869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 138/2000 [01:49<23:36, 1.31it/s, loss=0.811]" + "training until 2000: 7%|▋ | 138/2000 [02:18<33:03, 1.07s/it, loss=0.681]" ] }, { @@ -2877,7 +2877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 139/2000 [01:50<24:41, 1.26it/s, loss=0.811]" + "training until 2000: 7%|▋ | 139/2000 [02:19<34:27, 1.11s/it, loss=0.681]" ] }, { @@ -2885,7 +2885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 139/2000 [01:50<24:41, 1.26it/s, loss=0.8] " + "training until 2000: 7%|▋ | 139/2000 [02:19<34:27, 1.11s/it, loss=0.658]" ] }, { @@ -2893,7 +2893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 140/2000 [01:51<23:39, 1.31it/s, loss=0.8]" + "training until 2000: 7%|▋ | 140/2000 [02:21<38:38, 1.25s/it, loss=0.658]" ] }, { @@ -2901,7 +2901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 140/2000 [01:51<23:39, 1.31it/s, loss=0.779]" + "training until 2000: 7%|▋ | 140/2000 [02:21<38:38, 1.25s/it, loss=0.673]" ] }, { @@ -2909,7 +2909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 141/2000 [01:51<21:45, 1.42it/s, loss=0.779]" + "training until 2000: 7%|▋ | 141/2000 [02:22<34:51, 1.13s/it, loss=0.673]" ] }, { @@ -2917,7 +2917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 141/2000 [01:51<21:45, 1.42it/s, loss=0.771]" + "training until 2000: 7%|▋ | 141/2000 [02:22<34:51, 1.13s/it, loss=0.675]" ] }, { @@ -2925,7 +2925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 142/2000 [01:52<24:07, 1.28it/s, loss=0.771]" + "training until 2000: 7%|▋ | 142/2000 [02:23<32:58, 1.06s/it, loss=0.675]" ] }, { @@ -2933,7 +2933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 142/2000 [01:52<24:07, 1.28it/s, loss=0.805]" + "training until 2000: 7%|▋ | 142/2000 [02:23<32:58, 1.06s/it, loss=0.683]" ] }, { @@ -2941,7 +2941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 143/2000 [01:53<24:50, 1.25it/s, loss=0.805]" + "training until 2000: 7%|▋ | 143/2000 [02:24<30:46, 1.01it/s, loss=0.683]" ] }, { @@ -2949,7 +2949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 143/2000 [01:53<24:50, 1.25it/s, loss=0.825]" + "training until 2000: 7%|▋ | 143/2000 [02:24<30:46, 1.01it/s, loss=0.673]" ] }, { @@ -2957,7 +2957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 144/2000 [01:54<26:34, 1.16it/s, loss=0.825]" + "training until 2000: 7%|▋ | 144/2000 [02:25<33:43, 1.09s/it, loss=0.673]" ] }, { @@ -2965,7 +2965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 144/2000 [01:54<26:34, 1.16it/s, loss=0.803]" + "training until 2000: 7%|▋ | 144/2000 [02:25<33:43, 1.09s/it, loss=0.663]" ] }, { @@ -2973,7 +2973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 145/2000 [01:55<28:05, 1.10it/s, loss=0.803]" + "training until 2000: 7%|▋ | 145/2000 [02:26<32:35, 1.05s/it, loss=0.663]" ] }, { @@ -2981,7 +2981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 145/2000 [01:55<28:05, 1.10it/s, loss=0.805]" + "training until 2000: 7%|▋ | 145/2000 [02:26<32:35, 1.05s/it, loss=0.662]" ] }, { @@ -2989,7 +2989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 146/2000 [01:56<30:29, 1.01it/s, loss=0.805]" + "training until 2000: 7%|▋ | 146/2000 [02:27<35:57, 1.16s/it, loss=0.662]" ] }, { @@ -2997,7 +2997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 146/2000 [01:56<30:29, 1.01it/s, loss=0.832]" + "training until 2000: 7%|▋ | 146/2000 [02:27<35:57, 1.16s/it, loss=0.689]" ] }, { @@ -3005,7 +3005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 147/2000 [01:57<29:21, 1.05it/s, loss=0.832]" + "training until 2000: 7%|▋ | 147/2000 [02:28<34:01, 1.10s/it, loss=0.689]" ] }, { @@ -3013,7 +3013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 147/2000 [01:57<29:21, 1.05it/s, loss=0.843]" + "training until 2000: 7%|▋ | 147/2000 [02:28<34:01, 1.10s/it, loss=0.693]" ] }, { @@ -3021,7 +3021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 148/2000 [01:58<31:51, 1.03s/it, loss=0.843]" + "training until 2000: 7%|▋ | 148/2000 [02:29<32:44, 1.06s/it, loss=0.693]" ] }, { @@ -3029,7 +3029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 148/2000 [01:58<31:51, 1.03s/it, loss=0.829]" + "training until 2000: 7%|▋ | 148/2000 [02:29<32:44, 1.06s/it, loss=0.678]" ] }, { @@ -3037,7 +3037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 149/2000 [01:59<28:04, 1.10it/s, loss=0.829]" + "training until 2000: 7%|▋ | 149/2000 [02:30<31:24, 1.02s/it, loss=0.678]" ] }, { @@ -3045,7 +3045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 7%|▋ | 149/2000 [01:59<28:04, 1.10it/s, loss=0.802]" + "training until 2000: 7%|▋ | 149/2000 [02:30<31:24, 1.02s/it, loss=0.67] " ] }, { @@ -3053,7 +3053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 150/2000 [02:00<26:41, 1.16it/s, loss=0.802]" + "training until 2000: 8%|▊ | 150/2000 [02:32<36:09, 1.17s/it, loss=0.67]" ] }, { @@ -3061,7 +3061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 150/2000 [02:00<26:41, 1.16it/s, loss=0.783]" + "training until 2000: 8%|▊ | 150/2000 [02:32<36:09, 1.17s/it, loss=0.677]" ] }, { @@ -3069,7 +3069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 151/2000 [02:01<28:54, 1.07it/s, loss=0.783]" + "training until 2000: 8%|▊ | 151/2000 [02:33<34:13, 1.11s/it, loss=0.677]" ] }, { @@ -3077,7 +3077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 151/2000 [02:01<28:54, 1.07it/s, loss=0.818]" + "training until 2000: 8%|▊ | 151/2000 [02:33<34:13, 1.11s/it, loss=0.676]" ] }, { @@ -3085,7 +3085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 152/2000 [02:01<26:04, 1.18it/s, loss=0.818]" + "training until 2000: 8%|▊ | 152/2000 [02:33<29:34, 1.04it/s, loss=0.676]" ] }, { @@ -3093,7 +3093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 152/2000 [02:01<26:04, 1.18it/s, loss=0.816]" + "training until 2000: 8%|▊ | 152/2000 [02:33<29:34, 1.04it/s, loss=0.671]" ] }, { @@ -3101,7 +3101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 153/2000 [02:02<27:50, 1.11it/s, loss=0.816]" + "training until 2000: 8%|▊ | 153/2000 [02:34<31:12, 1.01s/it, loss=0.671]" ] }, { @@ -3109,7 +3109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 153/2000 [02:02<27:50, 1.11it/s, loss=0.783]" + "training until 2000: 8%|▊ | 153/2000 [02:34<31:12, 1.01s/it, loss=0.676]" ] }, { @@ -3117,7 +3117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 154/2000 [02:03<28:24, 1.08it/s, loss=0.783]" + "training until 2000: 8%|▊ | 154/2000 [02:35<30:44, 1.00it/s, loss=0.676]" ] }, { @@ -3125,7 +3125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 154/2000 [02:03<28:24, 1.08it/s, loss=0.818]" + "training until 2000: 8%|▊ | 154/2000 [02:35<30:44, 1.00it/s, loss=0.684]" ] }, { @@ -3133,7 +3133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 155/2000 [02:04<24:07, 1.27it/s, loss=0.818]" + "training until 2000: 8%|▊ | 155/2000 [02:36<30:01, 1.02it/s, loss=0.684]" ] }, { @@ -3141,7 +3141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 155/2000 [02:04<24:07, 1.27it/s, loss=0.789]" + "training until 2000: 8%|▊ | 155/2000 [02:36<30:01, 1.02it/s, loss=0.685]" ] }, { @@ -3149,7 +3149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 156/2000 [02:04<22:14, 1.38it/s, loss=0.789]" + "training until 2000: 8%|▊ | 156/2000 [02:37<27:15, 1.13it/s, loss=0.685]" ] }, { @@ -3157,7 +3157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 156/2000 [02:04<22:14, 1.38it/s, loss=0.792]" + "training until 2000: 8%|▊ | 156/2000 [02:37<27:15, 1.13it/s, loss=0.687]" ] }, { @@ -3165,7 +3165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 157/2000 [02:06<25:54, 1.19it/s, loss=0.792]" + "training until 2000: 8%|▊ | 157/2000 [02:38<26:43, 1.15it/s, loss=0.687]" ] }, { @@ -3173,7 +3173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 157/2000 [02:06<25:54, 1.19it/s, loss=0.803]" + "training until 2000: 8%|▊ | 157/2000 [02:38<26:43, 1.15it/s, loss=0.684]" ] }, { @@ -3181,7 +3181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 158/2000 [02:07<27:29, 1.12it/s, loss=0.803]" + "training until 2000: 8%|▊ | 158/2000 [02:39<27:36, 1.11it/s, loss=0.684]" ] }, { @@ -3189,7 +3189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 158/2000 [02:07<27:29, 1.12it/s, loss=0.811]" + "training until 2000: 8%|▊ | 158/2000 [02:39<27:36, 1.11it/s, loss=0.682]" ] }, { @@ -3197,7 +3197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 159/2000 [02:07<25:03, 1.22it/s, loss=0.811]" + "training until 2000: 8%|▊ | 159/2000 [02:40<32:52, 1.07s/it, loss=0.682]" ] }, { @@ -3205,7 +3205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 159/2000 [02:07<25:03, 1.22it/s, loss=0.804]" + "training until 2000: 8%|▊ | 159/2000 [02:40<32:52, 1.07s/it, loss=0.674]" ] }, { @@ -3213,7 +3213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 160/2000 [02:08<26:25, 1.16it/s, loss=0.804]" + "training until 2000: 8%|▊ | 160/2000 [02:41<32:47, 1.07s/it, loss=0.674]" ] }, { @@ -3221,7 +3221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 160/2000 [02:08<26:25, 1.16it/s, loss=0.814]" + "training until 2000: 8%|▊ | 160/2000 [02:41<32:47, 1.07s/it, loss=0.677]" ] }, { @@ -3229,7 +3229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 161/2000 [02:09<26:09, 1.17it/s, loss=0.814]" + "training until 2000: 8%|▊ | 161/2000 [02:42<28:25, 1.08it/s, loss=0.677]" ] }, { @@ -3237,7 +3237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 161/2000 [02:09<26:09, 1.17it/s, loss=0.792]" + "training until 2000: 8%|▊ | 161/2000 [02:42<28:25, 1.08it/s, loss=0.676]" ] }, { @@ -3245,7 +3245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 162/2000 [02:10<24:28, 1.25it/s, loss=0.792]" + "training until 2000: 8%|▊ | 162/2000 [02:43<29:32, 1.04it/s, loss=0.676]" ] }, { @@ -3253,7 +3253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 162/2000 [02:10<24:28, 1.25it/s, loss=0.786]" + "training until 2000: 8%|▊ | 162/2000 [02:43<29:32, 1.04it/s, loss=0.676]" ] }, { @@ -3261,7 +3261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 163/2000 [02:11<28:28, 1.08it/s, loss=0.786]" + "training until 2000: 8%|▊ | 163/2000 [02:44<33:06, 1.08s/it, loss=0.676]" ] }, { @@ -3269,7 +3269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 163/2000 [02:11<28:28, 1.08it/s, loss=0.795]" + "training until 2000: 8%|▊ | 163/2000 [02:44<33:06, 1.08s/it, loss=0.662]" ] }, { @@ -3277,7 +3277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 164/2000 [02:12<27:11, 1.13it/s, loss=0.795]" + "training until 2000: 8%|▊ | 164/2000 [02:45<30:28, 1.00it/s, loss=0.662]" ] }, { @@ -3285,7 +3285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 164/2000 [02:12<27:11, 1.13it/s, loss=0.821]" + "training until 2000: 8%|▊ | 164/2000 [02:45<30:28, 1.00it/s, loss=0.685]" ] }, { @@ -3293,7 +3293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 165/2000 [02:12<26:01, 1.18it/s, loss=0.821]" + "training until 2000: 8%|▊ | 165/2000 [02:46<31:33, 1.03s/it, loss=0.685]" ] }, { @@ -3301,7 +3301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 165/2000 [02:12<26:01, 1.18it/s, loss=0.821]" + "training until 2000: 8%|▊ | 165/2000 [02:46<31:33, 1.03s/it, loss=0.668]" ] }, { @@ -3309,7 +3309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 166/2000 [02:13<23:04, 1.32it/s, loss=0.821]" + "training until 2000: 8%|▊ | 166/2000 [02:47<28:07, 1.09it/s, loss=0.668]" ] }, { @@ -3317,7 +3317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 166/2000 [02:13<23:04, 1.32it/s, loss=0.845]" + "training until 2000: 8%|▊ | 166/2000 [02:47<28:07, 1.09it/s, loss=0.682]" ] }, { @@ -3325,7 +3325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 167/2000 [02:14<23:28, 1.30it/s, loss=0.845]" + "training until 2000: 8%|▊ | 167/2000 [02:48<27:25, 1.11it/s, loss=0.682]" ] }, { @@ -3333,7 +3333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 167/2000 [02:14<23:28, 1.30it/s, loss=0.848]" + "training until 2000: 8%|▊ | 167/2000 [02:48<27:25, 1.11it/s, loss=0.681]" ] }, { @@ -3341,7 +3341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 168/2000 [02:15<23:57, 1.27it/s, loss=0.848]" + "training until 2000: 8%|▊ | 168/2000 [02:48<24:20, 1.25it/s, loss=0.681]" ] }, { @@ -3349,7 +3349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 168/2000 [02:15<23:57, 1.27it/s, loss=0.754]" + "training until 2000: 8%|▊ | 168/2000 [02:48<24:20, 1.25it/s, loss=0.681]" ] }, { @@ -3357,7 +3357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 169/2000 [02:15<24:22, 1.25it/s, loss=0.754]" + "training until 2000: 8%|▊ | 169/2000 [02:49<25:51, 1.18it/s, loss=0.681]" ] }, { @@ -3365,7 +3365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 169/2000 [02:15<24:22, 1.25it/s, loss=0.801]" + "training until 2000: 8%|▊ | 169/2000 [02:49<25:51, 1.18it/s, loss=0.681]" ] }, { @@ -3373,7 +3373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 170/2000 [02:16<21:05, 1.45it/s, loss=0.801]" + "training until 2000: 8%|▊ | 170/2000 [02:50<23:29, 1.30it/s, loss=0.681]" ] }, { @@ -3381,7 +3381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 8%|▊ | 170/2000 [02:16<21:05, 1.45it/s, loss=0.804]" + "training until 2000: 8%|▊ | 170/2000 [02:50<23:29, 1.30it/s, loss=0.677]" ] }, { @@ -3389,7 +3389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 171/2000 [02:16<18:56, 1.61it/s, loss=0.804]" + "training until 2000: 9%|▊ | 171/2000 [02:50<23:10, 1.32it/s, loss=0.677]" ] }, { @@ -3397,7 +3397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 171/2000 [02:16<18:56, 1.61it/s, loss=0.815]" + "training until 2000: 9%|▊ | 171/2000 [02:50<23:10, 1.32it/s, loss=0.683]" ] }, { @@ -3405,7 +3405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 172/2000 [02:17<20:14, 1.51it/s, loss=0.815]" + "training until 2000: 9%|▊ | 172/2000 [02:51<24:20, 1.25it/s, loss=0.683]" ] }, { @@ -3413,7 +3413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 172/2000 [02:17<20:14, 1.51it/s, loss=0.807]" + "training until 2000: 9%|▊ | 172/2000 [02:51<24:20, 1.25it/s, loss=0.674]" ] }, { @@ -3421,7 +3421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 173/2000 [02:18<21:16, 1.43it/s, loss=0.807]" + "training until 2000: 9%|▊ | 173/2000 [02:52<22:39, 1.34it/s, loss=0.674]" ] }, { @@ -3429,7 +3429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 173/2000 [02:18<21:16, 1.43it/s, loss=0.788]" + "training until 2000: 9%|▊ | 173/2000 [02:52<22:39, 1.34it/s, loss=0.665]" ] }, { @@ -3437,7 +3437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 174/2000 [02:19<23:22, 1.30it/s, loss=0.788]" + "training until 2000: 9%|▊ | 174/2000 [02:53<25:32, 1.19it/s, loss=0.665]" ] }, { @@ -3445,7 +3445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▊ | 174/2000 [02:19<23:22, 1.30it/s, loss=0.799]" + "training until 2000: 9%|▊ | 174/2000 [02:53<25:32, 1.19it/s, loss=0.692]" ] }, { @@ -3453,7 +3453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 175/2000 [02:20<28:12, 1.08it/s, loss=0.799]" + "training until 2000: 9%|▉ | 175/2000 [02:54<27:51, 1.09it/s, loss=0.692]" ] }, { @@ -3461,7 +3461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 175/2000 [02:20<28:12, 1.08it/s, loss=0.821]" + "training until 2000: 9%|▉ | 175/2000 [02:54<27:51, 1.09it/s, loss=0.676]" ] }, { @@ -3469,7 +3469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 176/2000 [02:21<26:36, 1.14it/s, loss=0.821]" + "training until 2000: 9%|▉ | 176/2000 [02:55<27:27, 1.11it/s, loss=0.676]" ] }, { @@ -3477,7 +3477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 176/2000 [02:21<26:36, 1.14it/s, loss=0.759]" + "training until 2000: 9%|▉ | 176/2000 [02:55<27:27, 1.11it/s, loss=0.66] " ] }, { @@ -3485,7 +3485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 177/2000 [02:22<24:35, 1.24it/s, loss=0.759]" + "training until 2000: 9%|▉ | 177/2000 [02:56<28:12, 1.08it/s, loss=0.66]" ] }, { @@ -3493,7 +3493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 177/2000 [02:22<24:35, 1.24it/s, loss=0.819]" + "training until 2000: 9%|▉ | 177/2000 [02:56<28:12, 1.08it/s, loss=0.682]" ] }, { @@ -3501,7 +3501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 178/2000 [02:22<22:05, 1.37it/s, loss=0.819]" + "training until 2000: 9%|▉ | 178/2000 [02:57<28:34, 1.06it/s, loss=0.682]" ] }, { @@ -3509,7 +3509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 178/2000 [02:22<22:05, 1.37it/s, loss=0.81] " + "training until 2000: 9%|▉ | 178/2000 [02:57<28:34, 1.06it/s, loss=0.668]" ] }, { @@ -3517,7 +3517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 179/2000 [02:23<22:16, 1.36it/s, loss=0.81]" + "training until 2000: 9%|▉ | 179/2000 [02:58<27:04, 1.12it/s, loss=0.668]" ] }, { @@ -3525,7 +3525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 179/2000 [02:23<22:16, 1.36it/s, loss=0.771]" + "training until 2000: 9%|▉ | 179/2000 [02:58<27:04, 1.12it/s, loss=0.665]" ] }, { @@ -3533,7 +3533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 180/2000 [02:24<22:35, 1.34it/s, loss=0.771]" + "training until 2000: 9%|▉ | 180/2000 [02:59<29:20, 1.03it/s, loss=0.665]" ] }, { @@ -3541,7 +3541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 180/2000 [02:24<22:35, 1.34it/s, loss=0.825]" + "training until 2000: 9%|▉ | 180/2000 [02:59<29:20, 1.03it/s, loss=0.665]" ] }, { @@ -3549,7 +3549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 181/2000 [02:24<20:33, 1.47it/s, loss=0.825]" + "training until 2000: 9%|▉ | 181/2000 [03:00<28:01, 1.08it/s, loss=0.665]" ] }, { @@ -3557,7 +3557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 181/2000 [02:24<20:33, 1.47it/s, loss=0.8] " + "training until 2000: 9%|▉ | 181/2000 [03:00<28:01, 1.08it/s, loss=0.664]" ] }, { @@ -3565,7 +3565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 182/2000 [02:25<20:54, 1.45it/s, loss=0.8]" + "training until 2000: 9%|▉ | 182/2000 [03:00<26:01, 1.16it/s, loss=0.664]" ] }, { @@ -3573,7 +3573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 182/2000 [02:25<20:54, 1.45it/s, loss=0.803]" + "training until 2000: 9%|▉ | 182/2000 [03:00<26:01, 1.16it/s, loss=0.684]" ] }, { @@ -3581,7 +3581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 183/2000 [02:26<21:12, 1.43it/s, loss=0.803]" + "training until 2000: 9%|▉ | 183/2000 [03:02<28:59, 1.04it/s, loss=0.684]" ] }, { @@ -3589,7 +3589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 183/2000 [02:26<21:12, 1.43it/s, loss=0.818]" + "training until 2000: 9%|▉ | 183/2000 [03:02<28:59, 1.04it/s, loss=0.678]" ] }, { @@ -3597,7 +3597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 184/2000 [02:26<22:26, 1.35it/s, loss=0.818]" + "training until 2000: 9%|▉ | 184/2000 [03:03<29:03, 1.04it/s, loss=0.678]" ] }, { @@ -3605,7 +3605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 184/2000 [02:26<22:26, 1.35it/s, loss=0.825]" + "training until 2000: 9%|▉ | 184/2000 [03:03<29:03, 1.04it/s, loss=0.68] " ] }, { @@ -3613,7 +3613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 185/2000 [02:27<23:14, 1.30it/s, loss=0.825]" + "training until 2000: 9%|▉ | 185/2000 [03:04<32:10, 1.06s/it, loss=0.68]" ] }, { @@ -3621,7 +3621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 185/2000 [02:27<23:14, 1.30it/s, loss=0.798]" + "training until 2000: 9%|▉ | 185/2000 [03:04<32:10, 1.06s/it, loss=0.675]" ] }, { @@ -3629,7 +3629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 186/2000 [02:28<23:50, 1.27it/s, loss=0.798]" + "training until 2000: 9%|▉ | 186/2000 [03:05<28:26, 1.06it/s, loss=0.675]" ] }, { @@ -3637,7 +3637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 186/2000 [02:28<23:50, 1.27it/s, loss=0.815]" + "training until 2000: 9%|▉ | 186/2000 [03:05<28:26, 1.06it/s, loss=0.671]" ] }, { @@ -3645,7 +3645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 187/2000 [02:29<23:00, 1.31it/s, loss=0.815]" + "training until 2000: 9%|▉ | 187/2000 [03:06<30:09, 1.00it/s, loss=0.671]" ] }, { @@ -3653,7 +3653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 187/2000 [02:29<23:00, 1.31it/s, loss=0.772]" + "training until 2000: 9%|▉ | 187/2000 [03:06<30:09, 1.00it/s, loss=0.68] " ] }, { @@ -3661,7 +3661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 188/2000 [02:29<22:18, 1.35it/s, loss=0.772]" + "training until 2000: 9%|▉ | 188/2000 [03:07<29:36, 1.02it/s, loss=0.68]" ] }, { @@ -3669,7 +3669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 188/2000 [02:29<22:18, 1.35it/s, loss=0.794]" + "training until 2000: 9%|▉ | 188/2000 [03:07<29:36, 1.02it/s, loss=0.695]" ] }, { @@ -3677,7 +3677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 189/2000 [02:30<24:15, 1.24it/s, loss=0.794]" + "training until 2000: 9%|▉ | 189/2000 [03:08<29:17, 1.03it/s, loss=0.695]" ] }, { @@ -3685,7 +3685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 9%|▉ | 189/2000 [02:30<24:15, 1.24it/s, loss=0.834]" + "training until 2000: 9%|▉ | 189/2000 [03:08<29:17, 1.03it/s, loss=0.681]" ] }, { @@ -3693,7 +3693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 190/2000 [02:31<21:42, 1.39it/s, loss=0.834]" + "training until 2000: 10%|▉ | 190/2000 [03:09<30:18, 1.00s/it, loss=0.681]" ] }, { @@ -3701,7 +3701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 190/2000 [02:31<21:42, 1.39it/s, loss=0.795]" + "training until 2000: 10%|▉ | 190/2000 [03:09<30:18, 1.00s/it, loss=0.662]" ] }, { @@ -3709,7 +3709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 191/2000 [02:32<22:11, 1.36it/s, loss=0.795]" + "training until 2000: 10%|▉ | 191/2000 [03:09<27:28, 1.10it/s, loss=0.662]" ] }, { @@ -3717,7 +3717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 191/2000 [02:32<22:11, 1.36it/s, loss=0.793]" + "training until 2000: 10%|▉ | 191/2000 [03:09<27:28, 1.10it/s, loss=0.679]" ] }, { @@ -3725,7 +3725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 192/2000 [02:32<21:07, 1.43it/s, loss=0.793]" + "training until 2000: 10%|▉ | 192/2000 [03:10<28:32, 1.06it/s, loss=0.679]" ] }, { @@ -3733,7 +3733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 192/2000 [02:32<21:07, 1.43it/s, loss=0.798]" + "training until 2000: 10%|▉ | 192/2000 [03:10<28:32, 1.06it/s, loss=0.679]" ] }, { @@ -3741,7 +3741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 193/2000 [02:33<21:24, 1.41it/s, loss=0.798]" + "training until 2000: 10%|▉ | 193/2000 [03:11<26:12, 1.15it/s, loss=0.679]" ] }, { @@ -3749,7 +3749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 193/2000 [02:33<21:24, 1.41it/s, loss=0.824]" + "training until 2000: 10%|▉ | 193/2000 [03:11<26:12, 1.15it/s, loss=0.67] " ] }, { @@ -3757,7 +3757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 194/2000 [02:34<26:18, 1.14it/s, loss=0.824]" + "training until 2000: 10%|▉ | 194/2000 [03:12<26:12, 1.15it/s, loss=0.67]" ] }, { @@ -3765,7 +3765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 194/2000 [02:34<26:18, 1.14it/s, loss=0.798]" + "training until 2000: 10%|▉ | 194/2000 [03:12<26:12, 1.15it/s, loss=0.663]" ] }, { @@ -3773,7 +3773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 195/2000 [02:35<25:52, 1.16it/s, loss=0.798]" + "training until 2000: 10%|▉ | 195/2000 [03:13<25:09, 1.20it/s, loss=0.663]" ] }, { @@ -3781,7 +3781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 195/2000 [02:35<25:52, 1.16it/s, loss=0.741]" + "training until 2000: 10%|▉ | 195/2000 [03:13<25:09, 1.20it/s, loss=0.68] " ] }, { @@ -3789,7 +3789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 196/2000 [02:36<26:30, 1.13it/s, loss=0.741]" + "training until 2000: 10%|▉ | 196/2000 [03:14<25:15, 1.19it/s, loss=0.68]" ] }, { @@ -3797,7 +3797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 196/2000 [02:36<26:30, 1.13it/s, loss=0.77] " + "training until 2000: 10%|▉ | 196/2000 [03:14<25:15, 1.19it/s, loss=0.664]" ] }, { @@ -3805,7 +3805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 197/2000 [02:37<27:32, 1.09it/s, loss=0.77]" + "training until 2000: 10%|▉ | 197/2000 [03:14<23:54, 1.26it/s, loss=0.664]" ] }, { @@ -3813,7 +3813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 197/2000 [02:37<27:32, 1.09it/s, loss=0.813]" + "training until 2000: 10%|▉ | 197/2000 [03:14<23:54, 1.26it/s, loss=0.678]" ] }, { @@ -3821,7 +3821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 198/2000 [02:38<27:41, 1.08it/s, loss=0.813]" + "training until 2000: 10%|▉ | 198/2000 [03:15<25:34, 1.17it/s, loss=0.678]" ] }, { @@ -3829,7 +3829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 198/2000 [02:38<27:41, 1.08it/s, loss=0.794]" + "training until 2000: 10%|▉ | 198/2000 [03:15<25:34, 1.17it/s, loss=0.678]" ] }, { @@ -3837,7 +3837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 199/2000 [02:39<26:10, 1.15it/s, loss=0.794]" + "training until 2000: 10%|▉ | 199/2000 [03:17<34:01, 1.13s/it, loss=0.678]" ] }, { @@ -3845,7 +3845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|▉ | 199/2000 [02:39<26:10, 1.15it/s, loss=0.778]" + "training until 2000: 10%|▉ | 199/2000 [03:17<34:01, 1.13s/it, loss=0.653]" ] }, { @@ -3853,7 +3853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 200/2000 [02:40<26:42, 1.12it/s, loss=0.778]" + "training until 2000: 10%|█ | 200/2000 [03:18<32:04, 1.07s/it, loss=0.653]" ] }, { @@ -3861,7 +3861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 200/2000 [02:40<26:42, 1.12it/s, loss=0.775]" + "training until 2000: 10%|█ | 200/2000 [03:18<32:04, 1.07s/it, loss=0.682]" ] }, { @@ -3869,7 +3869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 201/2000 [02:40<25:05, 1.19it/s, loss=0.775]" + "training until 2000: 10%|█ | 201/2000 [03:19<31:25, 1.05s/it, loss=0.682]" ] }, { @@ -3877,7 +3877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 201/2000 [02:40<25:05, 1.19it/s, loss=0.782]" + "training until 2000: 10%|█ | 201/2000 [03:19<31:25, 1.05s/it, loss=0.67] " ] }, { @@ -3885,7 +3885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 202/2000 [02:41<22:40, 1.32it/s, loss=0.782]" + "training until 2000: 10%|█ | 202/2000 [03:20<31:54, 1.06s/it, loss=0.67]" ] }, { @@ -3893,7 +3893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 202/2000 [02:41<22:40, 1.32it/s, loss=0.797]" + "training until 2000: 10%|█ | 202/2000 [03:20<31:54, 1.06s/it, loss=0.68]" ] }, { @@ -3901,7 +3901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 203/2000 [02:42<24:16, 1.23it/s, loss=0.797]" + "training until 2000: 10%|█ | 203/2000 [03:21<28:49, 1.04it/s, loss=0.68]" ] }, { @@ -3909,7 +3909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 203/2000 [02:42<24:16, 1.23it/s, loss=0.793]" + "training until 2000: 10%|█ | 203/2000 [03:21<28:49, 1.04it/s, loss=0.663]" ] }, { @@ -3917,7 +3917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 204/2000 [02:43<27:30, 1.09it/s, loss=0.793]" + "training until 2000: 10%|█ | 204/2000 [03:22<28:45, 1.04it/s, loss=0.663]" ] }, { @@ -3925,7 +3925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 204/2000 [02:43<27:30, 1.09it/s, loss=0.795]" + "training until 2000: 10%|█ | 204/2000 [03:22<28:45, 1.04it/s, loss=0.674]" ] }, { @@ -3933,7 +3933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 205/2000 [02:44<24:40, 1.21it/s, loss=0.795]" + "training until 2000: 10%|█ | 205/2000 [03:23<29:32, 1.01it/s, loss=0.674]" ] }, { @@ -3941,7 +3941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 205/2000 [02:44<24:40, 1.21it/s, loss=0.815]" + "training until 2000: 10%|█ | 205/2000 [03:23<29:32, 1.01it/s, loss=0.675]" ] }, { @@ -3949,7 +3949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 206/2000 [02:45<26:16, 1.14it/s, loss=0.815]" + "training until 2000: 10%|█ | 206/2000 [03:24<29:01, 1.03it/s, loss=0.675]" ] }, { @@ -3957,7 +3957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 206/2000 [02:45<26:16, 1.14it/s, loss=0.808]" + "training until 2000: 10%|█ | 206/2000 [03:24<29:01, 1.03it/s, loss=0.676]" ] }, { @@ -3965,7 +3965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 207/2000 [02:45<25:11, 1.19it/s, loss=0.808]" + "training until 2000: 10%|█ | 207/2000 [03:24<27:35, 1.08it/s, loss=0.676]" ] }, { @@ -3973,7 +3973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 207/2000 [02:45<25:11, 1.19it/s, loss=0.782]" + "training until 2000: 10%|█ | 207/2000 [03:24<27:35, 1.08it/s, loss=0.669]" ] }, { @@ -3981,7 +3981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 208/2000 [02:46<22:40, 1.32it/s, loss=0.782]" + "training until 2000: 10%|█ | 208/2000 [03:25<27:20, 1.09it/s, loss=0.669]" ] }, { @@ -3989,7 +3989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 208/2000 [02:46<22:40, 1.32it/s, loss=0.79] " + "training until 2000: 10%|█ | 208/2000 [03:25<27:20, 1.09it/s, loss=0.682]" ] }, { @@ -3997,7 +3997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 209/2000 [02:47<23:04, 1.29it/s, loss=0.79]" + "training until 2000: 10%|█ | 209/2000 [03:26<26:02, 1.15it/s, loss=0.682]" ] }, { @@ -4005,7 +4005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 209/2000 [02:47<23:04, 1.29it/s, loss=0.797]" + "training until 2000: 10%|█ | 209/2000 [03:26<26:02, 1.15it/s, loss=0.685]" ] }, { @@ -4013,7 +4013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 210/2000 [02:48<22:39, 1.32it/s, loss=0.797]" + "training until 2000: 10%|█ | 210/2000 [03:27<29:24, 1.01it/s, loss=0.685]" ] }, { @@ -4021,7 +4021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 10%|█ | 210/2000 [02:48<22:39, 1.32it/s, loss=0.817]" + "training until 2000: 10%|█ | 210/2000 [03:27<29:24, 1.01it/s, loss=0.68] " ] }, { @@ -4029,7 +4029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 211/2000 [02:48<23:21, 1.28it/s, loss=0.817]" + "training until 2000: 11%|█ | 211/2000 [03:29<33:46, 1.13s/it, loss=0.68]" ] }, { @@ -4037,7 +4037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 211/2000 [02:48<23:21, 1.28it/s, loss=0.796]" + "training until 2000: 11%|█ | 211/2000 [03:29<33:46, 1.13s/it, loss=0.689]" ] }, { @@ -4045,7 +4045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 212/2000 [02:49<22:59, 1.30it/s, loss=0.796]" + "training until 2000: 11%|█ | 212/2000 [03:30<33:39, 1.13s/it, loss=0.689]" ] }, { @@ -4053,7 +4053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 212/2000 [02:49<22:59, 1.30it/s, loss=0.842]" + "training until 2000: 11%|█ | 212/2000 [03:30<33:39, 1.13s/it, loss=0.661]" ] }, { @@ -4061,7 +4061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 213/2000 [02:50<23:31, 1.27it/s, loss=0.842]" + "training until 2000: 11%|█ | 213/2000 [03:31<32:27, 1.09s/it, loss=0.661]" ] }, { @@ -4069,7 +4069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 213/2000 [02:50<23:31, 1.27it/s, loss=0.768]" + "training until 2000: 11%|█ | 213/2000 [03:31<32:27, 1.09s/it, loss=0.679]" ] }, { @@ -4077,7 +4077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 214/2000 [02:51<27:07, 1.10it/s, loss=0.768]" + "training until 2000: 11%|█ | 214/2000 [03:32<30:44, 1.03s/it, loss=0.679]" ] }, { @@ -4085,7 +4085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 214/2000 [02:51<27:07, 1.10it/s, loss=0.773]" + "training until 2000: 11%|█ | 214/2000 [03:32<30:44, 1.03s/it, loss=0.673]" ] }, { @@ -4093,7 +4093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 215/2000 [02:52<26:53, 1.11it/s, loss=0.773]" + "training until 2000: 11%|█ | 215/2000 [03:33<29:18, 1.01it/s, loss=0.673]" ] }, { @@ -4101,7 +4101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 215/2000 [02:52<26:53, 1.11it/s, loss=0.803]" + "training until 2000: 11%|█ | 215/2000 [03:33<29:18, 1.01it/s, loss=0.696]" ] }, { @@ -4109,7 +4109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 216/2000 [02:53<24:55, 1.19it/s, loss=0.803]" + "training until 2000: 11%|█ | 216/2000 [03:34<29:19, 1.01it/s, loss=0.696]" ] }, { @@ -4117,7 +4117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 216/2000 [02:53<24:55, 1.19it/s, loss=0.813]" + "training until 2000: 11%|█ | 216/2000 [03:34<29:19, 1.01it/s, loss=0.667]" ] }, { @@ -4125,7 +4125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 217/2000 [02:53<22:31, 1.32it/s, loss=0.813]" + "training until 2000: 11%|█ | 217/2000 [03:35<28:47, 1.03it/s, loss=0.667]" ] }, { @@ -4133,7 +4133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 217/2000 [02:53<22:31, 1.32it/s, loss=0.761]" + "training until 2000: 11%|█ | 217/2000 [03:35<28:47, 1.03it/s, loss=0.658]" ] }, { @@ -4141,7 +4141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 218/2000 [02:54<23:28, 1.27it/s, loss=0.761]" + "training until 2000: 11%|█ | 218/2000 [03:36<29:03, 1.02it/s, loss=0.658]" ] }, { @@ -4149,7 +4149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 218/2000 [02:54<23:28, 1.27it/s, loss=0.789]" + "training until 2000: 11%|█ | 218/2000 [03:36<29:03, 1.02it/s, loss=0.665]" ] }, { @@ -4157,7 +4157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 219/2000 [02:55<22:47, 1.30it/s, loss=0.789]" + "training until 2000: 11%|█ | 219/2000 [03:37<30:21, 1.02s/it, loss=0.665]" ] }, { @@ -4165,7 +4165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 219/2000 [02:55<22:47, 1.30it/s, loss=0.782]" + "training until 2000: 11%|█ | 219/2000 [03:37<30:21, 1.02s/it, loss=0.677]" ] }, { @@ -4173,7 +4173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 220/2000 [02:56<22:20, 1.33it/s, loss=0.782]" + "training until 2000: 11%|█ | 220/2000 [03:38<30:58, 1.04s/it, loss=0.677]" ] }, { @@ -4181,7 +4181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 220/2000 [02:56<22:20, 1.33it/s, loss=0.786]" + "training until 2000: 11%|█ | 220/2000 [03:38<30:58, 1.04s/it, loss=0.687]" ] }, { @@ -4189,7 +4189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 221/2000 [02:57<24:32, 1.21it/s, loss=0.786]" + "training until 2000: 11%|█ | 221/2000 [03:39<29:10, 1.02it/s, loss=0.687]" ] }, { @@ -4197,7 +4197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 221/2000 [02:57<24:32, 1.21it/s, loss=0.8] " + "training until 2000: 11%|█ | 221/2000 [03:39<29:10, 1.02it/s, loss=0.657]" ] }, { @@ -4205,7 +4205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 222/2000 [02:58<26:46, 1.11it/s, loss=0.8]" + "training until 2000: 11%|█ | 222/2000 [03:40<27:32, 1.08it/s, loss=0.657]" ] }, { @@ -4213,7 +4213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 222/2000 [02:58<26:46, 1.11it/s, loss=0.831]" + "training until 2000: 11%|█ | 222/2000 [03:40<27:32, 1.08it/s, loss=0.679]" ] }, { @@ -4221,7 +4221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 223/2000 [02:59<26:35, 1.11it/s, loss=0.831]" + "training until 2000: 11%|█ | 223/2000 [03:40<24:52, 1.19it/s, loss=0.679]" ] }, { @@ -4229,7 +4229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 223/2000 [02:59<26:35, 1.11it/s, loss=0.776]" + "training until 2000: 11%|█ | 223/2000 [03:40<24:52, 1.19it/s, loss=0.679]" ] }, { @@ -4237,7 +4237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 224/2000 [02:59<24:40, 1.20it/s, loss=0.776]" + "training until 2000: 11%|█ | 224/2000 [03:41<24:41, 1.20it/s, loss=0.679]" ] }, { @@ -4245,7 +4245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█ | 224/2000 [02:59<24:40, 1.20it/s, loss=0.803]" + "training until 2000: 11%|█ | 224/2000 [03:41<24:41, 1.20it/s, loss=0.676]" ] }, { @@ -4253,7 +4253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 225/2000 [03:00<24:59, 1.18it/s, loss=0.803]" + "training until 2000: 11%|█▏ | 225/2000 [03:42<30:05, 1.02s/it, loss=0.676]" ] }, { @@ -4261,7 +4261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 225/2000 [03:00<24:59, 1.18it/s, loss=0.83] " + "training until 2000: 11%|█▏ | 225/2000 [03:42<30:05, 1.02s/it, loss=0.674]" ] }, { @@ -4269,7 +4269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 226/2000 [03:01<23:48, 1.24it/s, loss=0.83]" + "training until 2000: 11%|█▏ | 226/2000 [03:44<32:40, 1.10s/it, loss=0.674]" ] }, { @@ -4277,7 +4277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 226/2000 [03:01<23:48, 1.24it/s, loss=0.782]" + "training until 2000: 11%|█▏ | 226/2000 [03:44<32:40, 1.10s/it, loss=0.694]" ] }, { @@ -4285,7 +4285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 227/2000 [03:02<22:53, 1.29it/s, loss=0.782]" + "training until 2000: 11%|█▏ | 227/2000 [03:45<33:47, 1.14s/it, loss=0.694]" ] }, { @@ -4293,7 +4293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 227/2000 [03:02<22:53, 1.29it/s, loss=0.783]" + "training until 2000: 11%|█▏ | 227/2000 [03:45<33:47, 1.14s/it, loss=0.683]" ] }, { @@ -4301,7 +4301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 228/2000 [03:02<24:10, 1.22it/s, loss=0.783]" + "training until 2000: 11%|█▏ | 228/2000 [03:46<36:05, 1.22s/it, loss=0.683]" ] }, { @@ -4309,7 +4309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 228/2000 [03:02<24:10, 1.22it/s, loss=0.749]" + "training until 2000: 11%|█▏ | 228/2000 [03:46<36:05, 1.22s/it, loss=0.679]" ] }, { @@ -4317,7 +4317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 229/2000 [03:03<21:24, 1.38it/s, loss=0.749]" + "training until 2000: 11%|█▏ | 229/2000 [03:47<33:39, 1.14s/it, loss=0.679]" ] }, { @@ -4325,7 +4325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 11%|█▏ | 229/2000 [03:03<21:24, 1.38it/s, loss=0.802]" + "training until 2000: 11%|█▏ | 229/2000 [03:47<33:39, 1.14s/it, loss=0.682]" ] }, { @@ -4333,7 +4333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 230/2000 [03:04<23:07, 1.28it/s, loss=0.802]" + "training until 2000: 12%|█▏ | 230/2000 [03:49<37:05, 1.26s/it, loss=0.682]" ] }, { @@ -4341,7 +4341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 230/2000 [03:04<23:07, 1.28it/s, loss=0.777]" + "training until 2000: 12%|█▏ | 230/2000 [03:49<37:05, 1.26s/it, loss=0.655]" ] }, { @@ -4349,7 +4349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 231/2000 [03:05<26:36, 1.11it/s, loss=0.777]" + "training until 2000: 12%|█▏ | 231/2000 [03:50<33:22, 1.13s/it, loss=0.655]" ] }, { @@ -4357,7 +4357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 231/2000 [03:05<26:36, 1.11it/s, loss=0.783]" + "training until 2000: 12%|█▏ | 231/2000 [03:50<33:22, 1.13s/it, loss=0.67] " ] }, { @@ -4365,7 +4365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 232/2000 [03:06<25:13, 1.17it/s, loss=0.783]" + "training until 2000: 12%|█▏ | 232/2000 [03:52<40:53, 1.39s/it, loss=0.67]" ] }, { @@ -4373,7 +4373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 232/2000 [03:06<25:13, 1.17it/s, loss=0.767]" + "training until 2000: 12%|█▏ | 232/2000 [03:52<40:53, 1.39s/it, loss=0.666]" ] }, { @@ -4381,7 +4381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 233/2000 [03:06<23:57, 1.23it/s, loss=0.767]" + "training until 2000: 12%|█▏ | 233/2000 [03:53<37:35, 1.28s/it, loss=0.666]" ] }, { @@ -4389,7 +4389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 233/2000 [03:06<23:57, 1.23it/s, loss=0.766]" + "training until 2000: 12%|█▏ | 233/2000 [03:53<37:35, 1.28s/it, loss=0.68] " ] }, { @@ -4397,7 +4397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 234/2000 [03:07<22:44, 1.29it/s, loss=0.766]" + "training until 2000: 12%|█▏ | 234/2000 [03:54<33:36, 1.14s/it, loss=0.68]" ] }, { @@ -4405,7 +4405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 234/2000 [03:07<22:44, 1.29it/s, loss=0.846]" + "training until 2000: 12%|█▏ | 234/2000 [03:54<33:36, 1.14s/it, loss=0.679]" ] }, { @@ -4413,7 +4413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 235/2000 [03:08<25:03, 1.17it/s, loss=0.846]" + "training until 2000: 12%|█▏ | 235/2000 [03:55<33:02, 1.12s/it, loss=0.679]" ] }, { @@ -4421,7 +4421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 235/2000 [03:08<25:03, 1.17it/s, loss=0.784]" + "training until 2000: 12%|█▏ | 235/2000 [03:55<33:02, 1.12s/it, loss=0.644]" ] }, { @@ -4429,7 +4429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 236/2000 [03:09<25:42, 1.14it/s, loss=0.784]" + "training until 2000: 12%|█▏ | 236/2000 [03:55<30:24, 1.03s/it, loss=0.644]" ] }, { @@ -4437,7 +4437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 236/2000 [03:09<25:42, 1.14it/s, loss=0.796]" + "training until 2000: 12%|█▏ | 236/2000 [03:55<30:24, 1.03s/it, loss=0.669]" ] }, { @@ -4445,7 +4445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 237/2000 [03:10<27:17, 1.08it/s, loss=0.796]" + "training until 2000: 12%|█▏ | 237/2000 [03:56<30:08, 1.03s/it, loss=0.669]" ] }, { @@ -4453,7 +4453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 237/2000 [03:10<27:17, 1.08it/s, loss=0.811]" + "training until 2000: 12%|█▏ | 237/2000 [03:56<30:08, 1.03s/it, loss=0.661]" ] }, { @@ -4461,7 +4461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 238/2000 [03:11<26:29, 1.11it/s, loss=0.811]" + "training until 2000: 12%|█▏ | 238/2000 [03:58<32:25, 1.10s/it, loss=0.661]" ] }, { @@ -4469,7 +4469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 238/2000 [03:11<26:29, 1.11it/s, loss=0.769]" + "training until 2000: 12%|█▏ | 238/2000 [03:58<32:25, 1.10s/it, loss=0.673]" ] }, { @@ -4477,7 +4477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 239/2000 [03:12<25:20, 1.16it/s, loss=0.769]" + "training until 2000: 12%|█▏ | 239/2000 [03:59<32:39, 1.11s/it, loss=0.673]" ] }, { @@ -4485,7 +4485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 239/2000 [03:12<25:20, 1.16it/s, loss=0.816]" + "training until 2000: 12%|█▏ | 239/2000 [03:59<32:39, 1.11s/it, loss=0.688]" ] }, { @@ -4493,7 +4493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 240/2000 [03:13<24:07, 1.22it/s, loss=0.816]" + "training until 2000: 12%|█▏ | 240/2000 [04:00<32:23, 1.10s/it, loss=0.688]" ] }, { @@ -4501,7 +4501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 240/2000 [03:13<24:07, 1.22it/s, loss=0.796]" + "training until 2000: 12%|█▏ | 240/2000 [04:00<32:23, 1.10s/it, loss=0.665]" ] }, { @@ -4509,7 +4509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 241/2000 [03:13<21:59, 1.33it/s, loss=0.796]" + "training until 2000: 12%|█▏ | 241/2000 [04:01<30:18, 1.03s/it, loss=0.665]" ] }, { @@ -4517,7 +4517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 241/2000 [03:13<21:59, 1.33it/s, loss=0.851]" + "training until 2000: 12%|█▏ | 241/2000 [04:01<30:18, 1.03s/it, loss=0.667]" ] }, { @@ -4525,7 +4525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 242/2000 [03:14<23:24, 1.25it/s, loss=0.851]" + "training until 2000: 12%|█▏ | 242/2000 [04:02<27:54, 1.05it/s, loss=0.667]" ] }, { @@ -4533,7 +4533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 242/2000 [03:14<23:24, 1.25it/s, loss=0.78] " + "training until 2000: 12%|█▏ | 242/2000 [04:02<27:54, 1.05it/s, loss=0.664]" ] }, { @@ -4541,7 +4541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 243/2000 [03:15<21:15, 1.38it/s, loss=0.78]" + "training until 2000: 12%|█▏ | 243/2000 [04:02<25:30, 1.15it/s, loss=0.664]" ] }, { @@ -4549,7 +4549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 243/2000 [03:15<21:15, 1.38it/s, loss=0.783]" + "training until 2000: 12%|█▏ | 243/2000 [04:02<25:30, 1.15it/s, loss=0.669]" ] }, { @@ -4557,7 +4557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 244/2000 [03:16<26:12, 1.12it/s, loss=0.783]" + "training until 2000: 12%|█▏ | 244/2000 [04:03<26:18, 1.11it/s, loss=0.669]" ] }, { @@ -4565,7 +4565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 244/2000 [03:16<26:12, 1.12it/s, loss=0.804]" + "training until 2000: 12%|█▏ | 244/2000 [04:03<26:18, 1.11it/s, loss=0.681]" ] }, { @@ -4573,7 +4573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 245/2000 [03:17<25:34, 1.14it/s, loss=0.804]" + "training until 2000: 12%|█▏ | 245/2000 [04:04<26:54, 1.09it/s, loss=0.681]" ] }, { @@ -4581,7 +4581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 245/2000 [03:17<25:34, 1.14it/s, loss=0.8] " + "training until 2000: 12%|█▏ | 245/2000 [04:04<26:54, 1.09it/s, loss=0.684]" ] }, { @@ -4589,7 +4589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 246/2000 [03:18<27:36, 1.06it/s, loss=0.8]" + "training until 2000: 12%|█▏ | 246/2000 [04:05<28:36, 1.02it/s, loss=0.684]" ] }, { @@ -4597,7 +4597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 246/2000 [03:18<27:36, 1.06it/s, loss=0.833]" + "training until 2000: 12%|█▏ | 246/2000 [04:05<28:36, 1.02it/s, loss=0.672]" ] }, { @@ -4605,7 +4605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 247/2000 [03:18<24:53, 1.17it/s, loss=0.833]" + "training until 2000: 12%|█▏ | 247/2000 [04:06<30:07, 1.03s/it, loss=0.672]" ] }, { @@ -4613,7 +4613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 247/2000 [03:18<24:53, 1.17it/s, loss=0.798]" + "training until 2000: 12%|█▏ | 247/2000 [04:06<30:07, 1.03s/it, loss=0.675]" ] }, { @@ -4621,7 +4621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 248/2000 [03:19<21:54, 1.33it/s, loss=0.798]" + "training until 2000: 12%|█▏ | 248/2000 [04:08<31:02, 1.06s/it, loss=0.675]" ] }, { @@ -4629,7 +4629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 248/2000 [03:19<21:54, 1.33it/s, loss=0.82] " + "training until 2000: 12%|█▏ | 248/2000 [04:08<31:02, 1.06s/it, loss=0.669]" ] }, { @@ -4637,7 +4637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 249/2000 [03:20<23:28, 1.24it/s, loss=0.82]" + "training until 2000: 12%|█▏ | 249/2000 [04:09<33:23, 1.14s/it, loss=0.669]" ] }, { @@ -4645,7 +4645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▏ | 249/2000 [03:20<23:28, 1.24it/s, loss=0.783]" + "training until 2000: 12%|█▏ | 249/2000 [04:09<33:23, 1.14s/it, loss=0.661]" ] }, { @@ -4653,7 +4653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▎ | 250/2000 [03:21<24:23, 1.20it/s, loss=0.783]" + "training until 2000: 12%|█▎ | 250/2000 [04:10<35:09, 1.21s/it, loss=0.661]" ] }, { @@ -4661,7 +4661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 12%|█▎ | 250/2000 [03:21<24:23, 1.20it/s, loss=0.784]" + "training until 2000: 12%|█▎ | 250/2000 [04:10<35:09, 1.21s/it, loss=0.668]" ] }, { @@ -4669,7 +4669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 251/2000 [03:21<22:54, 1.27it/s, loss=0.784]" + "training until 2000: 13%|█▎ | 251/2000 [04:11<31:12, 1.07s/it, loss=0.668]" ] }, { @@ -4677,7 +4677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 251/2000 [03:21<22:54, 1.27it/s, loss=0.778]" + "training until 2000: 13%|█▎ | 251/2000 [04:11<31:12, 1.07s/it, loss=0.678]" ] }, { @@ -4685,7 +4685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 252/2000 [03:22<23:47, 1.22it/s, loss=0.778]" + "training until 2000: 13%|█▎ | 252/2000 [04:12<30:05, 1.03s/it, loss=0.678]" ] }, { @@ -4693,7 +4693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 252/2000 [03:22<23:47, 1.22it/s, loss=0.775]" + "training until 2000: 13%|█▎ | 252/2000 [04:12<30:05, 1.03s/it, loss=0.676]" ] }, { @@ -4701,7 +4701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 253/2000 [03:23<24:37, 1.18it/s, loss=0.775]" + "training until 2000: 13%|█▎ | 253/2000 [04:13<32:53, 1.13s/it, loss=0.676]" ] }, { @@ -4709,7 +4709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 253/2000 [03:23<24:37, 1.18it/s, loss=0.825]" + "training until 2000: 13%|█▎ | 253/2000 [04:13<32:53, 1.13s/it, loss=0.684]" ] }, { @@ -4717,7 +4717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 254/2000 [03:24<24:19, 1.20it/s, loss=0.825]" + "training until 2000: 13%|█▎ | 254/2000 [04:15<33:59, 1.17s/it, loss=0.684]" ] }, { @@ -4725,7 +4725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 254/2000 [03:24<24:19, 1.20it/s, loss=0.759]" + "training until 2000: 13%|█▎ | 254/2000 [04:15<33:59, 1.17s/it, loss=0.67] " ] }, { @@ -4733,7 +4733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 255/2000 [03:25<21:27, 1.35it/s, loss=0.759]" + "training until 2000: 13%|█▎ | 255/2000 [04:15<30:53, 1.06s/it, loss=0.67]" ] }, { @@ -4741,7 +4741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 255/2000 [03:25<21:27, 1.35it/s, loss=0.793]" + "training until 2000: 13%|█▎ | 255/2000 [04:15<30:53, 1.06s/it, loss=0.68]" ] }, { @@ -4749,7 +4749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 256/2000 [03:26<23:23, 1.24it/s, loss=0.793]" + "training until 2000: 13%|█▎ | 256/2000 [04:16<27:28, 1.06it/s, loss=0.68]" ] }, { @@ -4757,7 +4757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 256/2000 [03:26<23:23, 1.24it/s, loss=0.777]" + "training until 2000: 13%|█▎ | 256/2000 [04:16<27:28, 1.06it/s, loss=0.688]" ] }, { @@ -4765,7 +4765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 257/2000 [03:27<24:43, 1.17it/s, loss=0.777]" + "training until 2000: 13%|█▎ | 257/2000 [04:17<26:00, 1.12it/s, loss=0.688]" ] }, { @@ -4773,7 +4773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 257/2000 [03:27<24:43, 1.17it/s, loss=0.828]" + "training until 2000: 13%|█▎ | 257/2000 [04:17<26:00, 1.12it/s, loss=0.676]" ] }, { @@ -4781,7 +4781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 258/2000 [03:27<23:16, 1.25it/s, loss=0.828]" + "training until 2000: 13%|█▎ | 258/2000 [04:18<31:37, 1.09s/it, loss=0.676]" ] }, { @@ -4789,7 +4789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 258/2000 [03:27<23:16, 1.25it/s, loss=0.826]" + "training until 2000: 13%|█▎ | 258/2000 [04:18<31:37, 1.09s/it, loss=0.683]" ] }, { @@ -4797,7 +4797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 259/2000 [03:28<23:26, 1.24it/s, loss=0.826]" + "training until 2000: 13%|█▎ | 259/2000 [04:20<35:08, 1.21s/it, loss=0.683]" ] }, { @@ -4805,7 +4805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 259/2000 [03:28<23:26, 1.24it/s, loss=0.786]" + "training until 2000: 13%|█▎ | 259/2000 [04:20<35:08, 1.21s/it, loss=0.666]" ] }, { @@ -4813,7 +4813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 260/2000 [03:29<22:46, 1.27it/s, loss=0.786]" + "training until 2000: 13%|█▎ | 260/2000 [04:21<30:33, 1.05s/it, loss=0.666]" ] }, { @@ -4821,7 +4821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 260/2000 [03:29<22:46, 1.27it/s, loss=0.774]" + "training until 2000: 13%|█▎ | 260/2000 [04:21<30:33, 1.05s/it, loss=0.656]" ] }, { @@ -4829,7 +4829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 261/2000 [03:30<23:14, 1.25it/s, loss=0.774]" + "training until 2000: 13%|█▎ | 261/2000 [04:22<31:44, 1.09s/it, loss=0.656]" ] }, { @@ -4837,7 +4837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 261/2000 [03:30<23:14, 1.25it/s, loss=0.808]" + "training until 2000: 13%|█▎ | 261/2000 [04:22<31:44, 1.09s/it, loss=0.654]" ] }, { @@ -4845,7 +4845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 262/2000 [03:30<22:59, 1.26it/s, loss=0.808]" + "training until 2000: 13%|█▎ | 262/2000 [04:23<31:01, 1.07s/it, loss=0.654]" ] }, { @@ -4853,7 +4853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 262/2000 [03:30<22:59, 1.26it/s, loss=0.78] " + "training until 2000: 13%|█▎ | 262/2000 [04:23<31:01, 1.07s/it, loss=0.681]" ] }, { @@ -4861,7 +4861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 263/2000 [03:31<24:29, 1.18it/s, loss=0.78]" + "training until 2000: 13%|█▎ | 263/2000 [04:24<28:06, 1.03it/s, loss=0.681]" ] }, { @@ -4869,7 +4869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 263/2000 [03:31<24:29, 1.18it/s, loss=0.781]" + "training until 2000: 13%|█▎ | 263/2000 [04:24<28:06, 1.03it/s, loss=0.655]" ] }, { @@ -4877,7 +4877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 264/2000 [03:32<23:55, 1.21it/s, loss=0.781]" + "training until 2000: 13%|█▎ | 264/2000 [04:25<28:14, 1.02it/s, loss=0.655]" ] }, { @@ -4885,7 +4885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 264/2000 [03:32<23:55, 1.21it/s, loss=0.786]" + "training until 2000: 13%|█▎ | 264/2000 [04:25<28:14, 1.02it/s, loss=0.697]" ] }, { @@ -4893,7 +4893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 265/2000 [03:33<26:48, 1.08it/s, loss=0.786]" + "training until 2000: 13%|█▎ | 265/2000 [04:26<30:32, 1.06s/it, loss=0.697]" ] }, { @@ -4901,7 +4901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 265/2000 [03:33<26:48, 1.08it/s, loss=0.789]" + "training until 2000: 13%|█▎ | 265/2000 [04:26<30:32, 1.06s/it, loss=0.677]" ] }, { @@ -4909,7 +4909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 266/2000 [03:34<24:17, 1.19it/s, loss=0.789]" + "training until 2000: 13%|█▎ | 266/2000 [04:27<27:55, 1.03it/s, loss=0.677]" ] }, { @@ -4917,7 +4917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 266/2000 [03:34<24:17, 1.19it/s, loss=0.784]" + "training until 2000: 13%|█▎ | 266/2000 [04:27<27:55, 1.03it/s, loss=0.677]" ] }, { @@ -4925,7 +4925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 267/2000 [03:34<21:26, 1.35it/s, loss=0.784]" + "training until 2000: 13%|█▎ | 267/2000 [04:28<31:59, 1.11s/it, loss=0.677]" ] }, { @@ -4933,7 +4933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 267/2000 [03:34<21:26, 1.35it/s, loss=0.81] " + "training until 2000: 13%|█▎ | 267/2000 [04:28<31:59, 1.11s/it, loss=0.668]" ] }, { @@ -4941,7 +4941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 268/2000 [03:35<20:39, 1.40it/s, loss=0.81]" + "training until 2000: 13%|█▎ | 268/2000 [04:29<31:34, 1.09s/it, loss=0.668]" ] }, { @@ -4949,7 +4949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 268/2000 [03:35<20:39, 1.40it/s, loss=0.79]" + "training until 2000: 13%|█▎ | 268/2000 [04:29<31:34, 1.09s/it, loss=0.649]" ] }, { @@ -4957,7 +4957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 269/2000 [03:36<24:24, 1.18it/s, loss=0.79]" + "training until 2000: 13%|█▎ | 269/2000 [04:30<29:33, 1.02s/it, loss=0.649]" ] }, { @@ -4965,7 +4965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 13%|█▎ | 269/2000 [03:36<24:24, 1.18it/s, loss=0.825]" + "training until 2000: 13%|█▎ | 269/2000 [04:30<29:33, 1.02s/it, loss=0.672]" ] }, { @@ -4973,7 +4973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 270/2000 [03:37<22:59, 1.25it/s, loss=0.825]" + "training until 2000: 14%|█▎ | 270/2000 [04:31<28:40, 1.01it/s, loss=0.672]" ] }, { @@ -4981,7 +4981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 270/2000 [03:37<22:59, 1.25it/s, loss=0.802]" + "training until 2000: 14%|█▎ | 270/2000 [04:31<28:40, 1.01it/s, loss=0.677]" ] }, { @@ -4989,7 +4989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 271/2000 [03:38<24:41, 1.17it/s, loss=0.802]" + "training until 2000: 14%|█▎ | 271/2000 [04:32<27:21, 1.05it/s, loss=0.677]" ] }, { @@ -4997,7 +4997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 271/2000 [03:38<24:41, 1.17it/s, loss=0.802]" + "training until 2000: 14%|█▎ | 271/2000 [04:32<27:21, 1.05it/s, loss=0.652]" ] }, { @@ -5005,7 +5005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 272/2000 [03:39<24:38, 1.17it/s, loss=0.802]" + "training until 2000: 14%|█▎ | 272/2000 [04:32<25:09, 1.14it/s, loss=0.652]" ] }, { @@ -5013,7 +5013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 272/2000 [03:39<24:38, 1.17it/s, loss=0.745]" + "training until 2000: 14%|█▎ | 272/2000 [04:32<25:09, 1.14it/s, loss=0.688]" ] }, { @@ -5021,7 +5021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 273/2000 [03:40<24:38, 1.17it/s, loss=0.745]" + "training until 2000: 14%|█▎ | 273/2000 [04:34<28:42, 1.00it/s, loss=0.688]" ] }, { @@ -5029,7 +5029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 273/2000 [03:40<24:38, 1.17it/s, loss=0.775]" + "training until 2000: 14%|█▎ | 273/2000 [04:34<28:42, 1.00it/s, loss=0.678]" ] }, { @@ -5037,7 +5037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 274/2000 [03:41<25:08, 1.14it/s, loss=0.775]" + "training until 2000: 14%|█▎ | 274/2000 [04:34<26:39, 1.08it/s, loss=0.678]" ] }, { @@ -5045,7 +5045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▎ | 274/2000 [03:41<25:08, 1.14it/s, loss=0.762]" + "training until 2000: 14%|█▎ | 274/2000 [04:34<26:39, 1.08it/s, loss=0.66] " ] }, { @@ -5053,7 +5053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 275/2000 [03:41<22:26, 1.28it/s, loss=0.762]" + "training until 2000: 14%|█▍ | 275/2000 [04:35<26:22, 1.09it/s, loss=0.66]" ] }, { @@ -5061,7 +5061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 275/2000 [03:41<22:26, 1.28it/s, loss=0.792]" + "training until 2000: 14%|█▍ | 275/2000 [04:35<26:22, 1.09it/s, loss=0.682]" ] }, { @@ -5069,7 +5069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 276/2000 [03:42<24:21, 1.18it/s, loss=0.792]" + "training until 2000: 14%|█▍ | 276/2000 [04:37<29:26, 1.02s/it, loss=0.682]" ] }, { @@ -5077,7 +5077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 276/2000 [03:42<24:21, 1.18it/s, loss=0.822]" + "training until 2000: 14%|█▍ | 276/2000 [04:37<29:26, 1.02s/it, loss=0.672]" ] }, { @@ -5085,7 +5085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 277/2000 [03:43<23:12, 1.24it/s, loss=0.822]" + "training until 2000: 14%|█▍ | 277/2000 [04:38<30:08, 1.05s/it, loss=0.672]" ] }, { @@ -5093,7 +5093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 277/2000 [03:43<23:12, 1.24it/s, loss=0.825]" + "training until 2000: 14%|█▍ | 277/2000 [04:38<30:08, 1.05s/it, loss=0.684]" ] }, { @@ -5101,7 +5101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 278/2000 [03:43<21:45, 1.32it/s, loss=0.825]" + "training until 2000: 14%|█▍ | 278/2000 [04:38<27:30, 1.04it/s, loss=0.684]" ] }, { @@ -5109,7 +5109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 278/2000 [03:43<21:45, 1.32it/s, loss=0.8] " + "training until 2000: 14%|█▍ | 278/2000 [04:38<27:30, 1.04it/s, loss=0.659]" ] }, { @@ -5117,7 +5117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 279/2000 [03:44<22:35, 1.27it/s, loss=0.8]" + "training until 2000: 14%|█▍ | 279/2000 [04:39<27:39, 1.04it/s, loss=0.659]" ] }, { @@ -5125,7 +5125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 279/2000 [03:44<22:35, 1.27it/s, loss=0.79]" + "training until 2000: 14%|█▍ | 279/2000 [04:39<27:39, 1.04it/s, loss=0.7] " ] }, { @@ -5133,7 +5133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 280/2000 [03:45<22:31, 1.27it/s, loss=0.79]" + "training until 2000: 14%|█▍ | 280/2000 [04:40<27:28, 1.04it/s, loss=0.7]" ] }, { @@ -5141,7 +5141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 280/2000 [03:45<22:31, 1.27it/s, loss=0.809]" + "training until 2000: 14%|█▍ | 280/2000 [04:40<27:28, 1.04it/s, loss=0.686]" ] }, { @@ -5149,7 +5149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 281/2000 [03:46<21:50, 1.31it/s, loss=0.809]" + "training until 2000: 14%|█▍ | 281/2000 [04:41<25:49, 1.11it/s, loss=0.686]" ] }, { @@ -5157,7 +5157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 281/2000 [03:46<21:50, 1.31it/s, loss=0.788]" + "training until 2000: 14%|█▍ | 281/2000 [04:41<25:49, 1.11it/s, loss=0.671]" ] }, { @@ -5165,7 +5165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 282/2000 [03:47<23:14, 1.23it/s, loss=0.788]" + "training until 2000: 14%|█▍ | 282/2000 [04:42<26:14, 1.09it/s, loss=0.671]" ] }, { @@ -5173,7 +5173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 282/2000 [03:47<23:14, 1.23it/s, loss=0.816]" + "training until 2000: 14%|█▍ | 282/2000 [04:42<26:14, 1.09it/s, loss=0.678]" ] }, { @@ -5181,7 +5181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 283/2000 [03:48<23:16, 1.23it/s, loss=0.816]" + "training until 2000: 14%|█▍ | 283/2000 [04:43<27:25, 1.04it/s, loss=0.678]" ] }, { @@ -5189,7 +5189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 283/2000 [03:48<23:16, 1.23it/s, loss=0.798]" + "training until 2000: 14%|█▍ | 283/2000 [04:43<27:25, 1.04it/s, loss=0.677]" ] }, { @@ -5197,7 +5197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 284/2000 [03:49<26:03, 1.10it/s, loss=0.798]" + "training until 2000: 14%|█▍ | 284/2000 [04:44<27:42, 1.03it/s, loss=0.677]" ] }, { @@ -5205,7 +5205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 284/2000 [03:49<26:03, 1.10it/s, loss=0.787]" + "training until 2000: 14%|█▍ | 284/2000 [04:44<27:42, 1.03it/s, loss=0.675]" ] }, { @@ -5213,7 +5213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 285/2000 [03:49<24:37, 1.16it/s, loss=0.787]" + "training until 2000: 14%|█▍ | 285/2000 [04:45<26:15, 1.09it/s, loss=0.675]" ] }, { @@ -5221,7 +5221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 285/2000 [03:49<24:37, 1.16it/s, loss=0.807]" + "training until 2000: 14%|█▍ | 285/2000 [04:45<26:15, 1.09it/s, loss=0.653]" ] }, { @@ -5229,7 +5229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 286/2000 [03:50<22:54, 1.25it/s, loss=0.807]" + "training until 2000: 14%|█▍ | 286/2000 [04:46<28:34, 1.00s/it, loss=0.653]" ] }, { @@ -5237,7 +5237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 286/2000 [03:50<22:54, 1.25it/s, loss=0.765]" + "training until 2000: 14%|█▍ | 286/2000 [04:46<28:34, 1.00s/it, loss=0.697]" ] }, { @@ -5245,7 +5245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 287/2000 [03:51<20:46, 1.37it/s, loss=0.765]" + "training until 2000: 14%|█▍ | 287/2000 [04:47<28:05, 1.02it/s, loss=0.697]" ] }, { @@ -5253,7 +5253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 287/2000 [03:51<20:46, 1.37it/s, loss=0.789]" + "training until 2000: 14%|█▍ | 287/2000 [04:47<28:05, 1.02it/s, loss=0.689]" ] }, { @@ -5261,7 +5261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 288/2000 [03:51<20:40, 1.38it/s, loss=0.789]" + "training until 2000: 14%|█▍ | 288/2000 [04:48<25:47, 1.11it/s, loss=0.689]" ] }, { @@ -5269,7 +5269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 288/2000 [03:51<20:40, 1.38it/s, loss=0.802]" + "training until 2000: 14%|█▍ | 288/2000 [04:48<25:47, 1.11it/s, loss=0.656]" ] }, { @@ -5277,7 +5277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 289/2000 [03:52<19:55, 1.43it/s, loss=0.802]" + "training until 2000: 14%|█▍ | 289/2000 [04:48<22:54, 1.24it/s, loss=0.656]" ] }, { @@ -5285,7 +5285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 289/2000 [03:52<19:55, 1.43it/s, loss=0.821]" + "training until 2000: 14%|█▍ | 289/2000 [04:48<22:54, 1.24it/s, loss=0.68] " ] }, { @@ -5293,7 +5293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 290/2000 [03:53<19:51, 1.44it/s, loss=0.821]" + "training until 2000: 14%|█▍ | 290/2000 [04:50<28:37, 1.00s/it, loss=0.68]" ] }, { @@ -5301,7 +5301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 14%|█▍ | 290/2000 [03:53<19:51, 1.44it/s, loss=0.792]" + "training until 2000: 14%|█▍ | 290/2000 [04:50<28:37, 1.00s/it, loss=0.656]" ] }, { @@ -5309,7 +5309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 291/2000 [03:53<19:06, 1.49it/s, loss=0.792]" + "training until 2000: 15%|█▍ | 291/2000 [04:51<27:44, 1.03it/s, loss=0.656]" ] }, { @@ -5317,7 +5317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 291/2000 [03:53<19:06, 1.49it/s, loss=0.784]" + "training until 2000: 15%|█▍ | 291/2000 [04:51<27:44, 1.03it/s, loss=0.667]" ] }, { @@ -5325,7 +5325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 292/2000 [03:54<20:26, 1.39it/s, loss=0.784]" + "training until 2000: 15%|█▍ | 292/2000 [04:51<25:58, 1.10it/s, loss=0.667]" ] }, { @@ -5333,7 +5333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 292/2000 [03:54<20:26, 1.39it/s, loss=0.796]" + "training until 2000: 15%|█▍ | 292/2000 [04:51<25:58, 1.10it/s, loss=0.675]" ] }, { @@ -5341,7 +5341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 293/2000 [03:55<22:18, 1.28it/s, loss=0.796]" + "training until 2000: 15%|█▍ | 293/2000 [04:52<25:26, 1.12it/s, loss=0.675]" ] }, { @@ -5349,7 +5349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 293/2000 [03:55<22:18, 1.28it/s, loss=0.782]" + "training until 2000: 15%|█▍ | 293/2000 [04:52<25:26, 1.12it/s, loss=0.671]" ] }, { @@ -5357,7 +5357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 294/2000 [03:56<23:41, 1.20it/s, loss=0.782]" + "training until 2000: 15%|█▍ | 294/2000 [04:53<24:38, 1.15it/s, loss=0.671]" ] }, { @@ -5365,7 +5365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 294/2000 [03:56<23:41, 1.20it/s, loss=0.805]" + "training until 2000: 15%|█▍ | 294/2000 [04:53<24:38, 1.15it/s, loss=0.682]" ] }, { @@ -5373,7 +5373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 295/2000 [03:57<23:05, 1.23it/s, loss=0.805]" + "training until 2000: 15%|█▍ | 295/2000 [04:54<25:57, 1.09it/s, loss=0.682]" ] }, { @@ -5381,7 +5381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 295/2000 [03:57<23:05, 1.23it/s, loss=0.762]" + "training until 2000: 15%|█▍ | 295/2000 [04:54<25:57, 1.09it/s, loss=0.657]" ] }, { @@ -5389,7 +5389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 296/2000 [03:58<23:20, 1.22it/s, loss=0.762]" + "training until 2000: 15%|█▍ | 296/2000 [04:55<25:43, 1.10it/s, loss=0.657]" ] }, { @@ -5397,7 +5397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 296/2000 [03:58<23:20, 1.22it/s, loss=0.758]" + "training until 2000: 15%|█▍ | 296/2000 [04:55<25:43, 1.10it/s, loss=0.66] " ] }, { @@ -5405,7 +5405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 297/2000 [03:58<22:40, 1.25it/s, loss=0.758]" + "training until 2000: 15%|█▍ | 297/2000 [04:56<25:31, 1.11it/s, loss=0.66]" ] }, { @@ -5413,7 +5413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 297/2000 [03:58<22:40, 1.25it/s, loss=0.773]" + "training until 2000: 15%|█▍ | 297/2000 [04:56<25:31, 1.11it/s, loss=0.649]" ] }, { @@ -5421,7 +5421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 298/2000 [03:59<22:02, 1.29it/s, loss=0.773]" + "training until 2000: 15%|█▍ | 298/2000 [04:57<25:00, 1.13it/s, loss=0.649]" ] }, { @@ -5429,7 +5429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 298/2000 [03:59<22:02, 1.29it/s, loss=0.818]" + "training until 2000: 15%|█▍ | 298/2000 [04:57<25:00, 1.13it/s, loss=0.67] " ] }, { @@ -5437,7 +5437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 299/2000 [04:00<21:24, 1.32it/s, loss=0.818]" + "training until 2000: 15%|█▍ | 299/2000 [04:58<25:59, 1.09it/s, loss=0.67]" ] }, { @@ -5445,7 +5445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▍ | 299/2000 [04:00<21:24, 1.32it/s, loss=0.794]" + "training until 2000: 15%|█▍ | 299/2000 [04:58<25:59, 1.09it/s, loss=0.655]" ] }, { @@ -5453,7 +5453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 300/2000 [04:00<20:46, 1.36it/s, loss=0.794]" + "training until 2000: 15%|█▌ | 300/2000 [05:00<35:33, 1.25s/it, loss=0.655]" ] }, { @@ -5461,7 +5461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 300/2000 [04:00<20:46, 1.36it/s, loss=0.82] " + "training until 2000: 15%|█▌ | 300/2000 [05:00<35:33, 1.25s/it, loss=0.685]" ] }, { @@ -5469,7 +5469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 301/2000 [04:01<22:12, 1.28it/s, loss=0.82]" + "training until 2000: 15%|█▌ | 301/2000 [05:01<33:33, 1.18s/it, loss=0.685]" ] }, { @@ -5477,7 +5477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 301/2000 [04:01<22:12, 1.28it/s, loss=0.798]" + "training until 2000: 15%|█▌ | 301/2000 [05:01<33:33, 1.18s/it, loss=0.666]" ] }, { @@ -5485,7 +5485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 302/2000 [04:02<23:06, 1.22it/s, loss=0.798]" + "training until 2000: 15%|█▌ | 302/2000 [05:02<32:58, 1.16s/it, loss=0.666]" ] }, { @@ -5493,7 +5493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 302/2000 [04:02<23:06, 1.22it/s, loss=0.778]" + "training until 2000: 15%|█▌ | 302/2000 [05:02<32:58, 1.16s/it, loss=0.656]" ] }, { @@ -5501,7 +5501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 303/2000 [04:03<21:47, 1.30it/s, loss=0.778]" + "training until 2000: 15%|█▌ | 303/2000 [05:03<31:07, 1.10s/it, loss=0.656]" ] }, { @@ -5509,7 +5509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 303/2000 [04:03<21:47, 1.30it/s, loss=0.801]" + "training until 2000: 15%|█▌ | 303/2000 [05:03<31:07, 1.10s/it, loss=0.686]" ] }, { @@ -5517,7 +5517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 304/2000 [04:04<23:44, 1.19it/s, loss=0.801]" + "training until 2000: 15%|█▌ | 304/2000 [05:04<33:34, 1.19s/it, loss=0.686]" ] }, { @@ -5525,7 +5525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 304/2000 [04:04<23:44, 1.19it/s, loss=0.788]" + "training until 2000: 15%|█▌ | 304/2000 [05:04<33:34, 1.19s/it, loss=0.668]" ] }, { @@ -5533,7 +5533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 305/2000 [04:05<25:50, 1.09it/s, loss=0.788]" + "training until 2000: 15%|█▌ | 305/2000 [05:06<33:38, 1.19s/it, loss=0.668]" ] }, { @@ -5541,7 +5541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 305/2000 [04:05<25:50, 1.09it/s, loss=0.835]" + "training until 2000: 15%|█▌ | 305/2000 [05:06<33:38, 1.19s/it, loss=0.68] " ] }, { @@ -5549,7 +5549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 306/2000 [04:06<25:14, 1.12it/s, loss=0.835]" + "training until 2000: 15%|█▌ | 306/2000 [05:06<31:36, 1.12s/it, loss=0.68]" ] }, { @@ -5557,7 +5557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 306/2000 [04:06<25:14, 1.12it/s, loss=0.781]" + "training until 2000: 15%|█▌ | 306/2000 [05:06<31:36, 1.12s/it, loss=0.663]" ] }, { @@ -5565,7 +5565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 307/2000 [04:07<24:37, 1.15it/s, loss=0.781]" + "training until 2000: 15%|█▌ | 307/2000 [05:08<31:59, 1.13s/it, loss=0.663]" ] }, { @@ -5573,7 +5573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 307/2000 [04:07<24:37, 1.15it/s, loss=0.779]" + "training until 2000: 15%|█▌ | 307/2000 [05:08<31:59, 1.13s/it, loss=0.666]" ] }, { @@ -5581,7 +5581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 308/2000 [04:07<21:45, 1.30it/s, loss=0.779]" + "training until 2000: 15%|█▌ | 308/2000 [05:08<29:03, 1.03s/it, loss=0.666]" ] }, { @@ -5589,7 +5589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 308/2000 [04:07<21:45, 1.30it/s, loss=0.782]" + "training until 2000: 15%|█▌ | 308/2000 [05:08<29:03, 1.03s/it, loss=0.694]" ] }, { @@ -5597,7 +5597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 309/2000 [04:08<20:34, 1.37it/s, loss=0.782]" + "training until 2000: 15%|█▌ | 309/2000 [05:09<28:52, 1.02s/it, loss=0.694]" ] }, { @@ -5605,7 +5605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 15%|█▌ | 309/2000 [04:08<20:34, 1.37it/s, loss=0.819]" + "training until 2000: 15%|█▌ | 309/2000 [05:09<28:52, 1.02s/it, loss=0.681]" ] }, { @@ -5613,7 +5613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 310/2000 [04:09<22:05, 1.27it/s, loss=0.819]" + "training until 2000: 16%|█▌ | 310/2000 [05:11<31:35, 1.12s/it, loss=0.681]" ] }, { @@ -5621,7 +5621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 310/2000 [04:09<22:05, 1.27it/s, loss=0.792]" + "training until 2000: 16%|█▌ | 310/2000 [05:11<31:35, 1.12s/it, loss=0.658]" ] }, { @@ -5629,7 +5629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 311/2000 [04:09<19:57, 1.41it/s, loss=0.792]" + "training until 2000: 16%|█▌ | 311/2000 [05:12<36:19, 1.29s/it, loss=0.658]" ] }, { @@ -5637,7 +5637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 311/2000 [04:09<19:57, 1.41it/s, loss=0.789]" + "training until 2000: 16%|█▌ | 311/2000 [05:12<36:19, 1.29s/it, loss=0.667]" ] }, { @@ -5645,7 +5645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 312/2000 [04:10<23:30, 1.20it/s, loss=0.789]" + "training until 2000: 16%|█▌ | 312/2000 [05:13<31:25, 1.12s/it, loss=0.667]" ] }, { @@ -5653,7 +5653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 312/2000 [04:10<23:30, 1.20it/s, loss=0.801]" + "training until 2000: 16%|█▌ | 312/2000 [05:13<31:25, 1.12s/it, loss=0.694]" ] }, { @@ -5661,7 +5661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 313/2000 [04:11<22:37, 1.24it/s, loss=0.801]" + "training until 2000: 16%|█▌ | 313/2000 [05:14<26:41, 1.05it/s, loss=0.694]" ] }, { @@ -5669,7 +5669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 313/2000 [04:11<22:37, 1.24it/s, loss=0.761]" + "training until 2000: 16%|█▌ | 313/2000 [05:14<26:41, 1.05it/s, loss=0.669]" ] }, { @@ -5677,7 +5677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 314/2000 [04:12<23:59, 1.17it/s, loss=0.761]" + "training until 2000: 16%|█▌ | 314/2000 [05:15<28:43, 1.02s/it, loss=0.669]" ] }, { @@ -5685,7 +5685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 314/2000 [04:12<23:59, 1.17it/s, loss=0.792]" + "training until 2000: 16%|█▌ | 314/2000 [05:15<28:43, 1.02s/it, loss=0.679]" ] }, { @@ -5693,7 +5693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 315/2000 [04:13<23:39, 1.19it/s, loss=0.792]" + "training until 2000: 16%|█▌ | 315/2000 [05:16<31:30, 1.12s/it, loss=0.679]" ] }, { @@ -5701,7 +5701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 315/2000 [04:13<23:39, 1.19it/s, loss=0.77] " + "training until 2000: 16%|█▌ | 315/2000 [05:16<31:30, 1.12s/it, loss=0.682]" ] }, { @@ -5709,7 +5709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 316/2000 [04:14<22:40, 1.24it/s, loss=0.77]" + "training until 2000: 16%|█▌ | 316/2000 [05:18<33:18, 1.19s/it, loss=0.682]" ] }, { @@ -5717,7 +5717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 316/2000 [04:14<22:40, 1.24it/s, loss=0.812]" + "training until 2000: 16%|█▌ | 316/2000 [05:18<33:18, 1.19s/it, loss=0.659]" ] }, { @@ -5725,7 +5725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 317/2000 [04:15<25:58, 1.08it/s, loss=0.812]" + "training until 2000: 16%|█▌ | 317/2000 [05:18<28:02, 1.00it/s, loss=0.659]" ] }, { @@ -5733,7 +5733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 317/2000 [04:15<25:58, 1.08it/s, loss=0.781]" + "training until 2000: 16%|█▌ | 317/2000 [05:18<28:02, 1.00it/s, loss=0.674]" ] }, { @@ -5741,7 +5741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 318/2000 [04:16<26:21, 1.06it/s, loss=0.781]" + "training until 2000: 16%|█▌ | 318/2000 [05:19<27:34, 1.02it/s, loss=0.674]" ] }, { @@ -5749,7 +5749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 318/2000 [04:16<26:21, 1.06it/s, loss=0.822]" + "training until 2000: 16%|█▌ | 318/2000 [05:19<27:34, 1.02it/s, loss=0.661]" ] }, { @@ -5757,7 +5757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 319/2000 [04:17<24:58, 1.12it/s, loss=0.822]" + "training until 2000: 16%|█▌ | 319/2000 [05:20<24:33, 1.14it/s, loss=0.661]" ] }, { @@ -5765,7 +5765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 319/2000 [04:17<24:58, 1.12it/s, loss=0.756]" + "training until 2000: 16%|█▌ | 319/2000 [05:20<24:33, 1.14it/s, loss=0.668]" ] }, { @@ -5773,7 +5773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 320/2000 [04:17<23:53, 1.17it/s, loss=0.756]" + "training until 2000: 16%|█▌ | 320/2000 [05:21<26:50, 1.04it/s, loss=0.668]" ] }, { @@ -5781,7 +5781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 320/2000 [04:17<23:53, 1.17it/s, loss=0.8] " + "training until 2000: 16%|█▌ | 320/2000 [05:21<26:50, 1.04it/s, loss=0.653]" ] }, { @@ -5789,7 +5789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 321/2000 [04:18<24:30, 1.14it/s, loss=0.8]" + "training until 2000: 16%|█▌ | 321/2000 [05:22<31:20, 1.12s/it, loss=0.653]" ] }, { @@ -5797,7 +5797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 321/2000 [04:18<24:30, 1.14it/s, loss=0.814]" + "training until 2000: 16%|█▌ | 321/2000 [05:22<31:20, 1.12s/it, loss=0.678]" ] }, { @@ -5805,7 +5805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 322/2000 [04:19<23:31, 1.19it/s, loss=0.814]" + "training until 2000: 16%|█▌ | 322/2000 [05:24<32:03, 1.15s/it, loss=0.678]" ] }, { @@ -5813,7 +5813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 322/2000 [04:19<23:31, 1.19it/s, loss=0.77] " + "training until 2000: 16%|█▌ | 322/2000 [05:24<32:03, 1.15s/it, loss=0.663]" ] }, { @@ -5821,7 +5821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 323/2000 [04:20<22:32, 1.24it/s, loss=0.77]" + "training until 2000: 16%|█▌ | 323/2000 [05:25<33:11, 1.19s/it, loss=0.663]" ] }, { @@ -5829,7 +5829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 323/2000 [04:20<22:32, 1.24it/s, loss=0.821]" + "training until 2000: 16%|█▌ | 323/2000 [05:25<33:11, 1.19s/it, loss=0.676]" ] }, { @@ -5837,7 +5837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 324/2000 [04:21<21:56, 1.27it/s, loss=0.821]" + "training until 2000: 16%|█▌ | 324/2000 [05:26<30:11, 1.08s/it, loss=0.676]" ] }, { @@ -5845,7 +5845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▌ | 324/2000 [04:21<21:56, 1.27it/s, loss=0.813]" + "training until 2000: 16%|█▌ | 324/2000 [05:26<30:11, 1.08s/it, loss=0.666]" ] }, { @@ -5853,7 +5853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 325/2000 [04:21<19:31, 1.43it/s, loss=0.813]" + "training until 2000: 16%|█▋ | 325/2000 [05:27<30:25, 1.09s/it, loss=0.666]" ] }, { @@ -5861,7 +5861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 325/2000 [04:21<19:31, 1.43it/s, loss=0.757]" + "training until 2000: 16%|█▋ | 325/2000 [05:27<30:25, 1.09s/it, loss=0.634]" ] }, { @@ -5869,7 +5869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 326/2000 [04:22<20:01, 1.39it/s, loss=0.757]" + "training until 2000: 16%|█▋ | 326/2000 [05:28<33:03, 1.19s/it, loss=0.634]" ] }, { @@ -5877,7 +5877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 326/2000 [04:22<20:01, 1.39it/s, loss=0.749]" + "training until 2000: 16%|█▋ | 326/2000 [05:28<33:03, 1.19s/it, loss=0.66] " ] }, { @@ -5885,7 +5885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 327/2000 [04:23<24:01, 1.16it/s, loss=0.749]" + "training until 2000: 16%|█▋ | 327/2000 [05:29<29:46, 1.07s/it, loss=0.66]" ] }, { @@ -5893,7 +5893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 327/2000 [04:23<24:01, 1.16it/s, loss=0.788]" + "training until 2000: 16%|█▋ | 327/2000 [05:29<29:46, 1.07s/it, loss=0.688]" ] }, { @@ -5901,7 +5901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 328/2000 [04:24<23:23, 1.19it/s, loss=0.788]" + "training until 2000: 16%|█▋ | 328/2000 [05:30<29:27, 1.06s/it, loss=0.688]" ] }, { @@ -5909,7 +5909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 328/2000 [04:24<23:23, 1.19it/s, loss=0.778]" + "training until 2000: 16%|█▋ | 328/2000 [05:30<29:27, 1.06s/it, loss=0.676]" ] }, { @@ -5917,7 +5917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 329/2000 [04:25<22:37, 1.23it/s, loss=0.778]" + "training until 2000: 16%|█▋ | 329/2000 [05:31<25:27, 1.09it/s, loss=0.676]" ] }, { @@ -5925,7 +5925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 329/2000 [04:25<22:37, 1.23it/s, loss=0.763]" + "training until 2000: 16%|█▋ | 329/2000 [05:31<25:27, 1.09it/s, loss=0.674]" ] }, { @@ -5933,7 +5933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 330/2000 [04:25<23:02, 1.21it/s, loss=0.763]" + "training until 2000: 16%|█▋ | 330/2000 [05:32<28:40, 1.03s/it, loss=0.674]" ] }, { @@ -5941,7 +5941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 16%|█▋ | 330/2000 [04:25<23:02, 1.21it/s, loss=0.781]" + "training until 2000: 16%|█▋ | 330/2000 [05:32<28:40, 1.03s/it, loss=0.685]" ] }, { @@ -5949,7 +5949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 331/2000 [04:26<23:10, 1.20it/s, loss=0.781]" + "training until 2000: 17%|█▋ | 331/2000 [05:33<28:02, 1.01s/it, loss=0.685]" ] }, { @@ -5957,7 +5957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 331/2000 [04:26<23:10, 1.20it/s, loss=0.796]" + "training until 2000: 17%|█▋ | 331/2000 [05:33<28:02, 1.01s/it, loss=0.665]" ] }, { @@ -5965,7 +5965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 332/2000 [04:27<20:54, 1.33it/s, loss=0.796]" + "training until 2000: 17%|█▋ | 332/2000 [05:34<28:47, 1.04s/it, loss=0.665]" ] }, { @@ -5973,7 +5973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 332/2000 [04:27<20:54, 1.33it/s, loss=0.731]" + "training until 2000: 17%|█▋ | 332/2000 [05:34<28:47, 1.04s/it, loss=0.692]" ] }, { @@ -5981,7 +5981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 333/2000 [04:28<20:24, 1.36it/s, loss=0.731]" + "training until 2000: 17%|█▋ | 333/2000 [05:35<29:11, 1.05s/it, loss=0.692]" ] }, { @@ -5989,7 +5989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 333/2000 [04:28<20:24, 1.36it/s, loss=0.766]" + "training until 2000: 17%|█▋ | 333/2000 [05:35<29:11, 1.05s/it, loss=0.667]" ] }, { @@ -5997,7 +5997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 334/2000 [04:28<21:21, 1.30it/s, loss=0.766]" + "training until 2000: 17%|█▋ | 334/2000 [05:36<28:48, 1.04s/it, loss=0.667]" ] }, { @@ -6005,7 +6005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 334/2000 [04:28<21:21, 1.30it/s, loss=0.786]" + "training until 2000: 17%|█▋ | 334/2000 [05:36<28:48, 1.04s/it, loss=0.674]" ] }, { @@ -6013,7 +6013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 335/2000 [04:29<22:01, 1.26it/s, loss=0.786]" + "training until 2000: 17%|█▋ | 335/2000 [05:37<30:13, 1.09s/it, loss=0.674]" ] }, { @@ -6021,7 +6021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 335/2000 [04:29<22:01, 1.26it/s, loss=0.788]" + "training until 2000: 17%|█▋ | 335/2000 [05:37<30:13, 1.09s/it, loss=0.647]" ] }, { @@ -6029,7 +6029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 336/2000 [04:30<21:06, 1.31it/s, loss=0.788]" + "training until 2000: 17%|█▋ | 336/2000 [05:38<29:44, 1.07s/it, loss=0.647]" ] }, { @@ -6037,7 +6037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 336/2000 [04:30<21:06, 1.31it/s, loss=0.825]" + "training until 2000: 17%|█▋ | 336/2000 [05:38<29:44, 1.07s/it, loss=0.69] " ] }, { @@ -6045,7 +6045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 337/2000 [04:31<26:16, 1.05it/s, loss=0.825]" + "training until 2000: 17%|█▋ | 337/2000 [05:39<28:26, 1.03s/it, loss=0.69]" ] }, { @@ -6053,7 +6053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 337/2000 [04:31<26:16, 1.05it/s, loss=0.825]" + "training until 2000: 17%|█▋ | 337/2000 [05:39<28:26, 1.03s/it, loss=0.673]" ] }, { @@ -6061,7 +6061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 338/2000 [04:32<26:36, 1.04it/s, loss=0.825]" + "training until 2000: 17%|█▋ | 338/2000 [05:40<27:01, 1.02it/s, loss=0.673]" ] }, { @@ -6069,7 +6069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 338/2000 [04:32<26:36, 1.04it/s, loss=0.798]" + "training until 2000: 17%|█▋ | 338/2000 [05:40<27:01, 1.02it/s, loss=0.672]" ] }, { @@ -6077,7 +6077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 339/2000 [04:33<27:24, 1.01it/s, loss=0.798]" + "training until 2000: 17%|█▋ | 339/2000 [05:41<28:35, 1.03s/it, loss=0.672]" ] }, { @@ -6085,7 +6085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 339/2000 [04:33<27:24, 1.01it/s, loss=0.767]" + "training until 2000: 17%|█▋ | 339/2000 [05:41<28:35, 1.03s/it, loss=0.674]" ] }, { @@ -6093,7 +6093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 340/2000 [04:34<25:18, 1.09it/s, loss=0.767]" + "training until 2000: 17%|█▋ | 340/2000 [05:42<29:07, 1.05s/it, loss=0.674]" ] }, { @@ -6101,7 +6101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 340/2000 [04:34<25:18, 1.09it/s, loss=0.791]" + "training until 2000: 17%|█▋ | 340/2000 [05:42<29:07, 1.05s/it, loss=0.671]" ] }, { @@ -6109,7 +6109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 341/2000 [04:35<25:07, 1.10it/s, loss=0.791]" + "training until 2000: 17%|█▋ | 341/2000 [05:43<29:36, 1.07s/it, loss=0.671]" ] }, { @@ -6117,7 +6117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 341/2000 [04:35<25:07, 1.10it/s, loss=0.778]" + "training until 2000: 17%|█▋ | 341/2000 [05:43<29:36, 1.07s/it, loss=0.655]" ] }, { @@ -6125,7 +6125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 342/2000 [04:36<23:29, 1.18it/s, loss=0.778]" + "training until 2000: 17%|█▋ | 342/2000 [05:45<30:49, 1.12s/it, loss=0.655]" ] }, { @@ -6133,7 +6133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 342/2000 [04:36<23:29, 1.18it/s, loss=0.77] " + "training until 2000: 17%|█▋ | 342/2000 [05:45<30:49, 1.12s/it, loss=0.674]" ] }, { @@ -6141,7 +6141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 343/2000 [04:36<22:16, 1.24it/s, loss=0.77]" + "training until 2000: 17%|█▋ | 343/2000 [05:46<30:18, 1.10s/it, loss=0.674]" ] }, { @@ -6149,7 +6149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 343/2000 [04:36<22:16, 1.24it/s, loss=0.769]" + "training until 2000: 17%|█▋ | 343/2000 [05:46<30:18, 1.10s/it, loss=0.659]" ] }, { @@ -6157,7 +6157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 344/2000 [04:37<21:47, 1.27it/s, loss=0.769]" + "training until 2000: 17%|█▋ | 344/2000 [05:46<26:20, 1.05it/s, loss=0.659]" ] }, { @@ -6165,7 +6165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 344/2000 [04:37<21:47, 1.27it/s, loss=0.799]" + "training until 2000: 17%|█▋ | 344/2000 [05:46<26:20, 1.05it/s, loss=0.651]" ] }, { @@ -6173,7 +6173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 345/2000 [04:38<22:07, 1.25it/s, loss=0.799]" + "training until 2000: 17%|█▋ | 345/2000 [05:47<24:31, 1.12it/s, loss=0.651]" ] }, { @@ -6181,7 +6181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 345/2000 [04:38<22:07, 1.25it/s, loss=0.788]" + "training until 2000: 17%|█▋ | 345/2000 [05:47<24:31, 1.12it/s, loss=0.664]" ] }, { @@ -6189,7 +6189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 346/2000 [04:39<20:20, 1.36it/s, loss=0.788]" + "training until 2000: 17%|█▋ | 346/2000 [05:48<24:34, 1.12it/s, loss=0.664]" ] }, { @@ -6197,7 +6197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 346/2000 [04:39<20:20, 1.36it/s, loss=0.753]" + "training until 2000: 17%|█▋ | 346/2000 [05:48<24:34, 1.12it/s, loss=0.657]" ] }, { @@ -6205,7 +6205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 347/2000 [04:39<21:07, 1.30it/s, loss=0.753]" + "training until 2000: 17%|█▋ | 347/2000 [05:49<28:13, 1.02s/it, loss=0.657]" ] }, { @@ -6213,7 +6213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 347/2000 [04:39<21:07, 1.30it/s, loss=0.782]" + "training until 2000: 17%|█▋ | 347/2000 [05:49<28:13, 1.02s/it, loss=0.67] " ] }, { @@ -6221,7 +6221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 348/2000 [04:40<21:18, 1.29it/s, loss=0.782]" + "training until 2000: 17%|█▋ | 348/2000 [05:51<30:04, 1.09s/it, loss=0.67]" ] }, { @@ -6229,7 +6229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 348/2000 [04:40<21:18, 1.29it/s, loss=0.761]" + "training until 2000: 17%|█▋ | 348/2000 [05:51<30:04, 1.09s/it, loss=0.671]" ] }, { @@ -6237,7 +6237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 349/2000 [04:41<22:21, 1.23it/s, loss=0.761]" + "training until 2000: 17%|█▋ | 349/2000 [05:52<29:26, 1.07s/it, loss=0.671]" ] }, { @@ -6245,7 +6245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 17%|█▋ | 349/2000 [04:41<22:21, 1.23it/s, loss=0.794]" + "training until 2000: 17%|█▋ | 349/2000 [05:52<29:26, 1.07s/it, loss=0.66] " ] }, { @@ -6253,7 +6253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 350/2000 [04:42<21:15, 1.29it/s, loss=0.794]" + "training until 2000: 18%|█▊ | 350/2000 [05:53<30:43, 1.12s/it, loss=0.66]" ] }, { @@ -6261,7 +6261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 350/2000 [04:42<21:15, 1.29it/s, loss=0.814]" + "training until 2000: 18%|█▊ | 350/2000 [05:53<30:43, 1.12s/it, loss=0.689]" ] }, { @@ -6269,7 +6269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 351/2000 [04:43<24:29, 1.12it/s, loss=0.814]" + "training until 2000: 18%|█▊ | 351/2000 [05:54<28:58, 1.05s/it, loss=0.689]" ] }, { @@ -6277,7 +6277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 351/2000 [04:43<24:29, 1.12it/s, loss=0.797]" + "training until 2000: 18%|█▊ | 351/2000 [05:54<28:58, 1.05s/it, loss=0.649]" ] }, { @@ -6285,7 +6285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 352/2000 [04:44<25:24, 1.08it/s, loss=0.797]" + "training until 2000: 18%|█▊ | 352/2000 [05:55<28:22, 1.03s/it, loss=0.649]" ] }, { @@ -6293,7 +6293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 352/2000 [04:44<25:24, 1.08it/s, loss=0.735]" + "training until 2000: 18%|█▊ | 352/2000 [05:55<28:22, 1.03s/it, loss=0.635]" ] }, { @@ -6301,7 +6301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 353/2000 [04:45<24:39, 1.11it/s, loss=0.735]" + "training until 2000: 18%|█▊ | 353/2000 [05:56<26:20, 1.04it/s, loss=0.635]" ] }, { @@ -6309,7 +6309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 353/2000 [04:45<24:39, 1.11it/s, loss=0.781]" + "training until 2000: 18%|█▊ | 353/2000 [05:56<26:20, 1.04it/s, loss=0.663]" ] }, { @@ -6317,7 +6317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 354/2000 [04:46<23:14, 1.18it/s, loss=0.781]" + "training until 2000: 18%|█▊ | 354/2000 [05:57<30:40, 1.12s/it, loss=0.663]" ] }, { @@ -6325,7 +6325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 354/2000 [04:46<23:14, 1.18it/s, loss=0.782]" + "training until 2000: 18%|█▊ | 354/2000 [05:57<30:40, 1.12s/it, loss=0.654]" ] }, { @@ -6333,7 +6333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 355/2000 [04:47<24:33, 1.12it/s, loss=0.782]" + "training until 2000: 18%|█▊ | 355/2000 [05:58<28:24, 1.04s/it, loss=0.654]" ] }, { @@ -6341,7 +6341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 355/2000 [04:47<24:33, 1.12it/s, loss=0.77] " + "training until 2000: 18%|█▊ | 355/2000 [05:58<28:24, 1.04s/it, loss=0.682]" ] }, { @@ -6349,7 +6349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 356/2000 [04:47<23:06, 1.19it/s, loss=0.77]" + "training until 2000: 18%|█▊ | 356/2000 [05:59<26:22, 1.04it/s, loss=0.682]" ] }, { @@ -6357,7 +6357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 356/2000 [04:47<23:06, 1.19it/s, loss=0.822]" + "training until 2000: 18%|█▊ | 356/2000 [05:59<26:22, 1.04it/s, loss=0.654]" ] }, { @@ -6365,7 +6365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 357/2000 [04:48<21:59, 1.25it/s, loss=0.822]" + "training until 2000: 18%|█▊ | 357/2000 [06:00<25:33, 1.07it/s, loss=0.654]" ] }, { @@ -6373,7 +6373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 357/2000 [04:48<21:59, 1.25it/s, loss=0.745]" + "training until 2000: 18%|█▊ | 357/2000 [06:00<25:33, 1.07it/s, loss=0.677]" ] }, { @@ -6381,7 +6381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 358/2000 [04:49<20:28, 1.34it/s, loss=0.745]" + "training until 2000: 18%|█▊ | 358/2000 [06:01<28:19, 1.03s/it, loss=0.677]" ] }, { @@ -6389,7 +6389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 358/2000 [04:49<20:28, 1.34it/s, loss=0.775]" + "training until 2000: 18%|█▊ | 358/2000 [06:01<28:19, 1.03s/it, loss=0.679]" ] }, { @@ -6397,7 +6397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 359/2000 [04:50<22:53, 1.19it/s, loss=0.775]" + "training until 2000: 18%|█▊ | 359/2000 [06:02<26:10, 1.04it/s, loss=0.679]" ] }, { @@ -6405,7 +6405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 359/2000 [04:50<22:53, 1.19it/s, loss=0.794]" + "training until 2000: 18%|█▊ | 359/2000 [06:02<26:10, 1.04it/s, loss=0.662]" ] }, { @@ -6413,7 +6413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 360/2000 [04:50<22:25, 1.22it/s, loss=0.794]" + "training until 2000: 18%|█▊ | 360/2000 [06:02<23:58, 1.14it/s, loss=0.662]" ] }, { @@ -6421,7 +6421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 360/2000 [04:50<22:25, 1.22it/s, loss=0.772]" + "training until 2000: 18%|█▊ | 360/2000 [06:02<23:58, 1.14it/s, loss=0.681]" ] }, { @@ -6429,7 +6429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 361/2000 [04:51<21:48, 1.25it/s, loss=0.772]" + "training until 2000: 18%|█▊ | 361/2000 [06:03<25:49, 1.06it/s, loss=0.681]" ] }, { @@ -6437,7 +6437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 361/2000 [04:51<21:48, 1.25it/s, loss=0.772]" + "training until 2000: 18%|█▊ | 361/2000 [06:03<25:49, 1.06it/s, loss=0.656]" ] }, { @@ -6445,7 +6445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 362/2000 [04:52<19:20, 1.41it/s, loss=0.772]" + "training until 2000: 18%|█▊ | 362/2000 [06:04<24:02, 1.14it/s, loss=0.656]" ] }, { @@ -6453,7 +6453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 362/2000 [04:52<19:20, 1.41it/s, loss=0.797]" + "training until 2000: 18%|█▊ | 362/2000 [06:04<24:02, 1.14it/s, loss=0.66] " ] }, { @@ -6461,7 +6461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 363/2000 [04:53<22:29, 1.21it/s, loss=0.797]" + "training until 2000: 18%|█▊ | 363/2000 [06:05<26:41, 1.02it/s, loss=0.66]" ] }, { @@ -6469,7 +6469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 363/2000 [04:53<22:29, 1.21it/s, loss=0.778]" + "training until 2000: 18%|█▊ | 363/2000 [06:05<26:41, 1.02it/s, loss=0.661]" ] }, { @@ -6477,7 +6477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 364/2000 [04:53<21:23, 1.28it/s, loss=0.778]" + "training until 2000: 18%|█▊ | 364/2000 [06:06<27:10, 1.00it/s, loss=0.661]" ] }, { @@ -6485,7 +6485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 364/2000 [04:53<21:23, 1.28it/s, loss=0.785]" + "training until 2000: 18%|█▊ | 364/2000 [06:06<27:10, 1.00it/s, loss=0.654]" ] }, { @@ -6493,7 +6493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 365/2000 [04:54<21:23, 1.27it/s, loss=0.785]" + "training until 2000: 18%|█▊ | 365/2000 [06:07<27:28, 1.01s/it, loss=0.654]" ] }, { @@ -6501,7 +6501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 365/2000 [04:54<21:23, 1.27it/s, loss=0.793]" + "training until 2000: 18%|█▊ | 365/2000 [06:07<27:28, 1.01s/it, loss=0.696]" ] }, { @@ -6509,7 +6509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 366/2000 [04:55<24:36, 1.11it/s, loss=0.793]" + "training until 2000: 18%|█▊ | 366/2000 [06:08<24:31, 1.11it/s, loss=0.696]" ] }, { @@ -6517,7 +6517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 366/2000 [04:55<24:36, 1.11it/s, loss=0.769]" + "training until 2000: 18%|█▊ | 366/2000 [06:08<24:31, 1.11it/s, loss=0.657]" ] }, { @@ -6525,7 +6525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 367/2000 [04:56<23:41, 1.15it/s, loss=0.769]" + "training until 2000: 18%|█▊ | 367/2000 [06:09<27:36, 1.01s/it, loss=0.657]" ] }, { @@ -6533,7 +6533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 367/2000 [04:56<23:41, 1.15it/s, loss=0.798]" + "training until 2000: 18%|█▊ | 367/2000 [06:09<27:36, 1.01s/it, loss=0.676]" ] }, { @@ -6541,7 +6541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 368/2000 [04:57<22:58, 1.18it/s, loss=0.798]" + "training until 2000: 18%|█▊ | 368/2000 [06:11<30:34, 1.12s/it, loss=0.676]" ] }, { @@ -6549,7 +6549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 368/2000 [04:57<22:58, 1.18it/s, loss=0.776]" + "training until 2000: 18%|█▊ | 368/2000 [06:11<30:34, 1.12s/it, loss=0.657]" ] }, { @@ -6557,7 +6557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 369/2000 [04:58<24:21, 1.12it/s, loss=0.776]" + "training until 2000: 18%|█▊ | 369/2000 [06:11<27:33, 1.01s/it, loss=0.657]" ] }, { @@ -6565,7 +6565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 369/2000 [04:58<24:21, 1.12it/s, loss=0.786]" + "training until 2000: 18%|█▊ | 369/2000 [06:11<27:33, 1.01s/it, loss=0.675]" ] }, { @@ -6573,7 +6573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 370/2000 [04:59<23:10, 1.17it/s, loss=0.786]" + "training until 2000: 18%|█▊ | 370/2000 [06:12<25:29, 1.07it/s, loss=0.675]" ] }, { @@ -6581,7 +6581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 18%|█▊ | 370/2000 [04:59<23:10, 1.17it/s, loss=0.759]" + "training until 2000: 18%|█▊ | 370/2000 [06:12<25:29, 1.07it/s, loss=0.668]" ] }, { @@ -6589,7 +6589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 371/2000 [05:00<23:10, 1.17it/s, loss=0.759]" + "training until 2000: 19%|█▊ | 371/2000 [06:13<24:25, 1.11it/s, loss=0.668]" ] }, { @@ -6597,7 +6597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 371/2000 [05:00<23:10, 1.17it/s, loss=0.756]" + "training until 2000: 19%|█▊ | 371/2000 [06:13<24:25, 1.11it/s, loss=0.666]" ] }, { @@ -6605,7 +6605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 372/2000 [05:01<24:15, 1.12it/s, loss=0.756]" + "training until 2000: 19%|█▊ | 372/2000 [06:14<25:18, 1.07it/s, loss=0.666]" ] }, { @@ -6613,7 +6613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 372/2000 [05:01<24:15, 1.12it/s, loss=0.764]" + "training until 2000: 19%|█▊ | 372/2000 [06:14<25:18, 1.07it/s, loss=0.667]" ] }, { @@ -6621,7 +6621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 373/2000 [05:01<23:33, 1.15it/s, loss=0.764]" + "training until 2000: 19%|█▊ | 373/2000 [06:15<25:24, 1.07it/s, loss=0.667]" ] }, { @@ -6629,7 +6629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 373/2000 [05:01<23:33, 1.15it/s, loss=0.801]" + "training until 2000: 19%|█▊ | 373/2000 [06:15<25:24, 1.07it/s, loss=0.675]" ] }, { @@ -6637,7 +6637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 374/2000 [05:02<24:00, 1.13it/s, loss=0.801]" + "training until 2000: 19%|█▊ | 374/2000 [06:16<29:41, 1.10s/it, loss=0.675]" ] }, { @@ -6645,7 +6645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▊ | 374/2000 [05:02<24:00, 1.13it/s, loss=0.773]" + "training until 2000: 19%|█▊ | 374/2000 [06:16<29:41, 1.10s/it, loss=0.673]" ] }, { @@ -6653,7 +6653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 375/2000 [05:03<22:55, 1.18it/s, loss=0.773]" + "training until 2000: 19%|█▉ | 375/2000 [06:18<29:55, 1.11s/it, loss=0.673]" ] }, { @@ -6661,7 +6661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 375/2000 [05:03<22:55, 1.18it/s, loss=0.763]" + "training until 2000: 19%|█▉ | 375/2000 [06:18<29:55, 1.11s/it, loss=0.676]" ] }, { @@ -6669,7 +6669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 376/2000 [05:04<20:18, 1.33it/s, loss=0.763]" + "training until 2000: 19%|█▉ | 376/2000 [06:19<31:52, 1.18s/it, loss=0.676]" ] }, { @@ -6677,7 +6677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 376/2000 [05:04<20:18, 1.33it/s, loss=0.797]" + "training until 2000: 19%|█▉ | 376/2000 [06:19<31:52, 1.18s/it, loss=0.684]" ] }, { @@ -6685,7 +6685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 377/2000 [05:05<23:45, 1.14it/s, loss=0.797]" + "training until 2000: 19%|█▉ | 377/2000 [06:19<26:54, 1.01it/s, loss=0.684]" ] }, { @@ -6693,7 +6693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 377/2000 [05:05<23:45, 1.14it/s, loss=0.769]" + "training until 2000: 19%|█▉ | 377/2000 [06:19<26:54, 1.01it/s, loss=0.666]" ] }, { @@ -6701,7 +6701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 378/2000 [05:05<22:05, 1.22it/s, loss=0.769]" + "training until 2000: 19%|█▉ | 378/2000 [06:20<27:00, 1.00it/s, loss=0.666]" ] }, { @@ -6709,7 +6709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 378/2000 [05:05<22:05, 1.22it/s, loss=0.76] " + "training until 2000: 19%|█▉ | 378/2000 [06:20<27:00, 1.00it/s, loss=0.689]" ] }, { @@ -6717,7 +6717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 379/2000 [05:06<21:17, 1.27it/s, loss=0.76]" + "training until 2000: 19%|█▉ | 379/2000 [06:21<24:06, 1.12it/s, loss=0.689]" ] }, { @@ -6725,7 +6725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 379/2000 [05:06<21:17, 1.27it/s, loss=0.75]" + "training until 2000: 19%|█▉ | 379/2000 [06:21<24:06, 1.12it/s, loss=0.676]" ] }, { @@ -6733,7 +6733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 380/2000 [05:07<21:32, 1.25it/s, loss=0.75]" + "training until 2000: 19%|█▉ | 380/2000 [06:22<26:35, 1.02it/s, loss=0.676]" ] }, { @@ -6741,7 +6741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 380/2000 [05:07<21:32, 1.25it/s, loss=0.748]" + "training until 2000: 19%|█▉ | 380/2000 [06:22<26:35, 1.02it/s, loss=0.673]" ] }, { @@ -6749,7 +6749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 381/2000 [05:08<21:26, 1.26it/s, loss=0.748]" + "training until 2000: 19%|█▉ | 381/2000 [06:23<27:21, 1.01s/it, loss=0.673]" ] }, { @@ -6757,7 +6757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 381/2000 [05:08<21:26, 1.26it/s, loss=0.779]" + "training until 2000: 19%|█▉ | 381/2000 [06:23<27:21, 1.01s/it, loss=0.667]" ] }, { @@ -6765,7 +6765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 382/2000 [05:09<22:26, 1.20it/s, loss=0.779]" + "training until 2000: 19%|█▉ | 382/2000 [06:24<23:59, 1.12it/s, loss=0.667]" ] }, { @@ -6773,7 +6773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 382/2000 [05:09<22:26, 1.20it/s, loss=0.793]" + "training until 2000: 19%|█▉ | 382/2000 [06:24<23:59, 1.12it/s, loss=0.649]" ] }, { @@ -6781,7 +6781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 383/2000 [05:10<23:08, 1.16it/s, loss=0.793]" + "training until 2000: 19%|█▉ | 383/2000 [06:25<25:24, 1.06it/s, loss=0.649]" ] }, { @@ -6789,7 +6789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 383/2000 [05:10<23:08, 1.16it/s, loss=0.789]" + "training until 2000: 19%|█▉ | 383/2000 [06:25<25:24, 1.06it/s, loss=0.654]" ] }, { @@ -6797,7 +6797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 384/2000 [05:10<21:14, 1.27it/s, loss=0.789]" + "training until 2000: 19%|█▉ | 384/2000 [06:26<26:08, 1.03it/s, loss=0.654]" ] }, { @@ -6805,7 +6805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 384/2000 [05:10<21:14, 1.27it/s, loss=0.804]" + "training until 2000: 19%|█▉ | 384/2000 [06:26<26:08, 1.03it/s, loss=0.667]" ] }, { @@ -6813,7 +6813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 385/2000 [05:11<22:20, 1.20it/s, loss=0.804]" + "training until 2000: 19%|█▉ | 385/2000 [06:27<26:01, 1.03it/s, loss=0.667]" ] }, { @@ -6821,7 +6821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 385/2000 [05:11<22:20, 1.20it/s, loss=0.76] " + "training until 2000: 19%|█▉ | 385/2000 [06:27<26:01, 1.03it/s, loss=0.673]" ] }, { @@ -6829,7 +6829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 386/2000 [05:12<20:54, 1.29it/s, loss=0.76]" + "training until 2000: 19%|█▉ | 386/2000 [06:28<25:32, 1.05it/s, loss=0.673]" ] }, { @@ -6837,7 +6837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 386/2000 [05:12<20:54, 1.29it/s, loss=0.768]" + "training until 2000: 19%|█▉ | 386/2000 [06:28<25:32, 1.05it/s, loss=0.642]" ] }, { @@ -6845,7 +6845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 387/2000 [05:13<22:03, 1.22it/s, loss=0.768]" + "training until 2000: 19%|█▉ | 387/2000 [06:29<24:56, 1.08it/s, loss=0.642]" ] }, { @@ -6853,7 +6853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 387/2000 [05:13<22:03, 1.22it/s, loss=0.814]" + "training until 2000: 19%|█▉ | 387/2000 [06:29<24:56, 1.08it/s, loss=0.64] " ] }, { @@ -6861,7 +6861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 388/2000 [05:14<24:57, 1.08it/s, loss=0.814]" + "training until 2000: 19%|█▉ | 388/2000 [06:30<25:31, 1.05it/s, loss=0.64]" ] }, { @@ -6869,7 +6869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 388/2000 [05:14<24:57, 1.08it/s, loss=0.766]" + "training until 2000: 19%|█▉ | 388/2000 [06:30<25:31, 1.05it/s, loss=0.673]" ] }, { @@ -6877,7 +6877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 389/2000 [05:15<23:43, 1.13it/s, loss=0.766]" + "training until 2000: 19%|█▉ | 389/2000 [06:31<28:20, 1.06s/it, loss=0.673]" ] }, { @@ -6885,7 +6885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 19%|█▉ | 389/2000 [05:15<23:43, 1.13it/s, loss=0.737]" + "training until 2000: 19%|█▉ | 389/2000 [06:31<28:20, 1.06s/it, loss=0.631]" ] }, { @@ -6893,7 +6893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 390/2000 [05:16<24:47, 1.08it/s, loss=0.737]" + "training until 2000: 20%|█▉ | 390/2000 [06:32<29:01, 1.08s/it, loss=0.631]" ] }, { @@ -6901,7 +6901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 390/2000 [05:16<24:47, 1.08it/s, loss=0.778]" + "training until 2000: 20%|█▉ | 390/2000 [06:32<29:01, 1.08s/it, loss=0.678]" ] }, { @@ -6909,7 +6909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 391/2000 [05:17<24:54, 1.08it/s, loss=0.778]" + "training until 2000: 20%|█▉ | 391/2000 [06:33<29:18, 1.09s/it, loss=0.678]" ] }, { @@ -6917,7 +6917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 391/2000 [05:17<24:54, 1.08it/s, loss=0.732]" + "training until 2000: 20%|█▉ | 391/2000 [06:33<29:18, 1.09s/it, loss=0.652]" ] }, { @@ -6925,7 +6925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 392/2000 [05:17<22:35, 1.19it/s, loss=0.732]" + "training until 2000: 20%|█▉ | 392/2000 [06:34<26:19, 1.02it/s, loss=0.652]" ] }, { @@ -6933,7 +6933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 392/2000 [05:17<22:35, 1.19it/s, loss=0.751]" + "training until 2000: 20%|█▉ | 392/2000 [06:34<26:19, 1.02it/s, loss=0.666]" ] }, { @@ -6941,7 +6941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 393/2000 [05:18<20:27, 1.31it/s, loss=0.751]" + "training until 2000: 20%|█▉ | 393/2000 [06:35<28:52, 1.08s/it, loss=0.666]" ] }, { @@ -6949,7 +6949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 393/2000 [05:18<20:27, 1.31it/s, loss=0.754]" + "training until 2000: 20%|█▉ | 393/2000 [06:35<28:52, 1.08s/it, loss=0.689]" ] }, { @@ -6957,7 +6957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 394/2000 [05:19<20:24, 1.31it/s, loss=0.754]" + "training until 2000: 20%|█▉ | 394/2000 [06:37<28:39, 1.07s/it, loss=0.689]" ] }, { @@ -6965,7 +6965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 394/2000 [05:19<20:24, 1.31it/s, loss=0.741]" + "training until 2000: 20%|█▉ | 394/2000 [06:37<28:39, 1.07s/it, loss=0.671]" ] }, { @@ -6973,7 +6973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 395/2000 [05:19<21:05, 1.27it/s, loss=0.741]" + "training until 2000: 20%|█▉ | 395/2000 [06:38<30:03, 1.12s/it, loss=0.671]" ] }, { @@ -6981,7 +6981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 395/2000 [05:19<21:05, 1.27it/s, loss=0.753]" + "training until 2000: 20%|█▉ | 395/2000 [06:38<30:03, 1.12s/it, loss=0.662]" ] }, { @@ -6989,7 +6989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 396/2000 [05:21<22:55, 1.17it/s, loss=0.753]" + "training until 2000: 20%|█▉ | 396/2000 [06:39<28:10, 1.05s/it, loss=0.662]" ] }, { @@ -6997,7 +6997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 396/2000 [05:21<22:55, 1.17it/s, loss=0.748]" + "training until 2000: 20%|█▉ | 396/2000 [06:39<28:10, 1.05s/it, loss=0.681]" ] }, { @@ -7005,7 +7005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 397/2000 [05:21<22:34, 1.18it/s, loss=0.748]" + "training until 2000: 20%|█▉ | 397/2000 [06:40<27:59, 1.05s/it, loss=0.681]" ] }, { @@ -7013,7 +7013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 397/2000 [05:21<22:34, 1.18it/s, loss=0.766]" + "training until 2000: 20%|█▉ | 397/2000 [06:40<27:59, 1.05s/it, loss=0.653]" ] }, { @@ -7021,7 +7021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 398/2000 [05:22<21:59, 1.21it/s, loss=0.766]" + "training until 2000: 20%|█▉ | 398/2000 [06:41<26:57, 1.01s/it, loss=0.653]" ] }, { @@ -7029,7 +7029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 398/2000 [05:22<21:59, 1.21it/s, loss=0.769]" + "training until 2000: 20%|█▉ | 398/2000 [06:41<26:57, 1.01s/it, loss=0.642]" ] }, { @@ -7037,7 +7037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 399/2000 [05:23<20:19, 1.31it/s, loss=0.769]" + "training until 2000: 20%|█▉ | 399/2000 [06:42<30:21, 1.14s/it, loss=0.642]" ] }, { @@ -7045,7 +7045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|█▉ | 399/2000 [05:23<20:19, 1.31it/s, loss=0.751]" + "training until 2000: 20%|█▉ | 399/2000 [06:42<30:21, 1.14s/it, loss=0.668]" ] }, { @@ -7053,7 +7053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 400/2000 [05:24<20:40, 1.29it/s, loss=0.751]" + "training until 2000: 20%|██ | 400/2000 [06:43<27:41, 1.04s/it, loss=0.668]" ] }, { @@ -7061,7 +7061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 400/2000 [05:24<20:40, 1.29it/s, loss=0.822]" + "training until 2000: 20%|██ | 400/2000 [06:43<27:41, 1.04s/it, loss=0.642]" ] }, { @@ -7069,7 +7069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 401/2000 [05:24<20:25, 1.30it/s, loss=0.822]" + "training until 2000: 20%|██ | 401/2000 [06:44<25:10, 1.06it/s, loss=0.642]" ] }, { @@ -7077,7 +7077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 401/2000 [05:24<20:25, 1.30it/s, loss=0.786]" + "training until 2000: 20%|██ | 401/2000 [06:44<25:10, 1.06it/s, loss=0.639]" ] }, { @@ -7085,7 +7085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 402/2000 [05:25<23:22, 1.14it/s, loss=0.786]" + "training until 2000: 20%|██ | 402/2000 [06:44<25:04, 1.06it/s, loss=0.639]" ] }, { @@ -7093,7 +7093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 402/2000 [05:25<23:22, 1.14it/s, loss=0.781]" + "training until 2000: 20%|██ | 402/2000 [06:44<25:04, 1.06it/s, loss=0.654]" ] }, { @@ -7101,7 +7101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 403/2000 [05:26<24:36, 1.08it/s, loss=0.781]" + "training until 2000: 20%|██ | 403/2000 [06:46<26:10, 1.02it/s, loss=0.654]" ] }, { @@ -7109,7 +7109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 403/2000 [05:26<24:36, 1.08it/s, loss=0.757]" + "training until 2000: 20%|██ | 403/2000 [06:46<26:10, 1.02it/s, loss=0.68] " ] }, { @@ -7117,7 +7117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 404/2000 [05:27<20:26, 1.30it/s, loss=0.757]" + "training until 2000: 20%|██ | 404/2000 [06:46<23:30, 1.13it/s, loss=0.68]" ] }, { @@ -7125,7 +7125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 404/2000 [05:27<20:26, 1.30it/s, loss=0.747]" + "training until 2000: 20%|██ | 404/2000 [06:46<23:30, 1.13it/s, loss=0.693]" ] }, { @@ -7133,7 +7133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 405/2000 [05:27<19:19, 1.38it/s, loss=0.747]" + "training until 2000: 20%|██ | 405/2000 [06:47<24:15, 1.10it/s, loss=0.693]" ] }, { @@ -7141,7 +7141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 405/2000 [05:27<19:19, 1.38it/s, loss=0.743]" + "training until 2000: 20%|██ | 405/2000 [06:47<24:15, 1.10it/s, loss=0.674]" ] }, { @@ -7149,7 +7149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 406/2000 [05:28<21:17, 1.25it/s, loss=0.743]" + "training until 2000: 20%|██ | 406/2000 [06:48<24:14, 1.10it/s, loss=0.674]" ] }, { @@ -7157,7 +7157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 406/2000 [05:28<21:17, 1.25it/s, loss=0.771]" + "training until 2000: 20%|██ | 406/2000 [06:48<24:14, 1.10it/s, loss=0.692]" ] }, { @@ -7165,7 +7165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 407/2000 [05:30<23:21, 1.14it/s, loss=0.771]" + "training until 2000: 20%|██ | 407/2000 [06:49<25:44, 1.03it/s, loss=0.692]" ] }, { @@ -7173,7 +7173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 407/2000 [05:30<23:21, 1.14it/s, loss=0.771]" + "training until 2000: 20%|██ | 407/2000 [06:49<25:44, 1.03it/s, loss=0.661]" ] }, { @@ -7181,7 +7181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 408/2000 [05:30<22:44, 1.17it/s, loss=0.771]" + "training until 2000: 20%|██ | 408/2000 [06:50<26:16, 1.01it/s, loss=0.661]" ] }, { @@ -7189,7 +7189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 408/2000 [05:30<22:44, 1.17it/s, loss=0.735]" + "training until 2000: 20%|██ | 408/2000 [06:50<26:16, 1.01it/s, loss=0.645]" ] }, { @@ -7197,7 +7197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 409/2000 [05:31<20:06, 1.32it/s, loss=0.735]" + "training until 2000: 20%|██ | 409/2000 [06:51<25:06, 1.06it/s, loss=0.645]" ] }, { @@ -7205,7 +7205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 409/2000 [05:31<20:06, 1.32it/s, loss=0.752]" + "training until 2000: 20%|██ | 409/2000 [06:51<25:06, 1.06it/s, loss=0.651]" ] }, { @@ -7213,7 +7213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 410/2000 [05:32<19:28, 1.36it/s, loss=0.752]" + "training until 2000: 20%|██ | 410/2000 [06:52<23:28, 1.13it/s, loss=0.651]" ] }, { @@ -7221,7 +7221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 20%|██ | 410/2000 [05:32<19:28, 1.36it/s, loss=0.781]" + "training until 2000: 20%|██ | 410/2000 [06:52<23:28, 1.13it/s, loss=0.668]" ] }, { @@ -7229,7 +7229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 411/2000 [05:32<18:57, 1.40it/s, loss=0.781]" + "training until 2000: 21%|██ | 411/2000 [06:53<25:46, 1.03it/s, loss=0.668]" ] }, { @@ -7237,7 +7237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 411/2000 [05:32<18:57, 1.40it/s, loss=0.79] " + "training until 2000: 21%|██ | 411/2000 [06:53<25:46, 1.03it/s, loss=0.683]" ] }, { @@ -7245,7 +7245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 412/2000 [05:33<18:13, 1.45it/s, loss=0.79]" + "training until 2000: 21%|██ | 412/2000 [06:54<27:25, 1.04s/it, loss=0.683]" ] }, { @@ -7253,7 +7253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 412/2000 [05:33<18:13, 1.45it/s, loss=0.724]" + "training until 2000: 21%|██ | 412/2000 [06:54<27:25, 1.04s/it, loss=0.673]" ] }, { @@ -7261,7 +7261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 413/2000 [05:33<16:31, 1.60it/s, loss=0.724]" + "training until 2000: 21%|██ | 413/2000 [06:55<28:16, 1.07s/it, loss=0.673]" ] }, { @@ -7269,7 +7269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 413/2000 [05:33<16:31, 1.60it/s, loss=0.79] " + "training until 2000: 21%|██ | 413/2000 [06:55<28:16, 1.07s/it, loss=0.682]" ] }, { @@ -7277,7 +7277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 414/2000 [05:34<20:00, 1.32it/s, loss=0.79]" + "training until 2000: 21%|██ | 414/2000 [06:56<25:34, 1.03it/s, loss=0.682]" ] }, { @@ -7285,7 +7285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 414/2000 [05:34<20:00, 1.32it/s, loss=0.762]" + "training until 2000: 21%|██ | 414/2000 [06:56<25:34, 1.03it/s, loss=0.666]" ] }, { @@ -7293,7 +7293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 415/2000 [05:35<20:34, 1.28it/s, loss=0.762]" + "training until 2000: 21%|██ | 415/2000 [06:57<25:21, 1.04it/s, loss=0.666]" ] }, { @@ -7301,7 +7301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 415/2000 [05:35<20:34, 1.28it/s, loss=0.768]" + "training until 2000: 21%|██ | 415/2000 [06:57<25:21, 1.04it/s, loss=0.668]" ] }, { @@ -7309,7 +7309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 416/2000 [05:36<18:49, 1.40it/s, loss=0.768]" + "training until 2000: 21%|██ | 416/2000 [06:58<26:56, 1.02s/it, loss=0.668]" ] }, { @@ -7317,7 +7317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 416/2000 [05:36<18:49, 1.40it/s, loss=0.802]" + "training until 2000: 21%|██ | 416/2000 [06:58<26:56, 1.02s/it, loss=0.67] " ] }, { @@ -7325,7 +7325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 417/2000 [05:36<17:38, 1.50it/s, loss=0.802]" + "training until 2000: 21%|██ | 417/2000 [06:59<27:08, 1.03s/it, loss=0.67]" ] }, { @@ -7333,7 +7333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 417/2000 [05:36<17:38, 1.50it/s, loss=0.777]" + "training until 2000: 21%|██ | 417/2000 [06:59<27:08, 1.03s/it, loss=0.655]" ] }, { @@ -7341,7 +7341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 418/2000 [05:37<19:36, 1.34it/s, loss=0.777]" + "training until 2000: 21%|██ | 418/2000 [07:00<25:08, 1.05it/s, loss=0.655]" ] }, { @@ -7349,7 +7349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 418/2000 [05:37<19:36, 1.34it/s, loss=0.754]" + "training until 2000: 21%|██ | 418/2000 [07:00<25:08, 1.05it/s, loss=0.622]" ] }, { @@ -7357,7 +7357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 419/2000 [05:38<21:35, 1.22it/s, loss=0.754]" + "training until 2000: 21%|██ | 419/2000 [07:01<24:06, 1.09it/s, loss=0.622]" ] }, { @@ -7365,7 +7365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 419/2000 [05:38<21:35, 1.22it/s, loss=0.778]" + "training until 2000: 21%|██ | 419/2000 [07:01<24:06, 1.09it/s, loss=0.684]" ] }, { @@ -7373,7 +7373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 420/2000 [05:39<21:43, 1.21it/s, loss=0.778]" + "training until 2000: 21%|██ | 420/2000 [07:02<26:25, 1.00s/it, loss=0.684]" ] }, { @@ -7381,7 +7381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 420/2000 [05:39<21:43, 1.21it/s, loss=0.772]" + "training until 2000: 21%|██ | 420/2000 [07:02<26:25, 1.00s/it, loss=0.661]" ] }, { @@ -7389,7 +7389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 421/2000 [05:40<22:22, 1.18it/s, loss=0.772]" + "training until 2000: 21%|██ | 421/2000 [07:03<25:07, 1.05it/s, loss=0.661]" ] }, { @@ -7397,7 +7397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 421/2000 [05:40<22:22, 1.18it/s, loss=0.8] " + "training until 2000: 21%|██ | 421/2000 [07:03<25:07, 1.05it/s, loss=0.638]" ] }, { @@ -7405,7 +7405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 422/2000 [05:41<21:26, 1.23it/s, loss=0.8]" + "training until 2000: 21%|██ | 422/2000 [07:04<22:49, 1.15it/s, loss=0.638]" ] }, { @@ -7413,7 +7413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 422/2000 [05:41<21:26, 1.23it/s, loss=0.742]" + "training until 2000: 21%|██ | 422/2000 [07:04<22:49, 1.15it/s, loss=0.649]" ] }, { @@ -7421,7 +7421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 423/2000 [05:42<21:20, 1.23it/s, loss=0.742]" + "training until 2000: 21%|██ | 423/2000 [07:05<24:04, 1.09it/s, loss=0.649]" ] }, { @@ -7429,7 +7429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 423/2000 [05:42<21:20, 1.23it/s, loss=0.774]" + "training until 2000: 21%|██ | 423/2000 [07:05<24:04, 1.09it/s, loss=0.682]" ] }, { @@ -7437,7 +7437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 424/2000 [05:42<21:46, 1.21it/s, loss=0.774]" + "training until 2000: 21%|██ | 424/2000 [07:05<23:11, 1.13it/s, loss=0.682]" ] }, { @@ -7445,7 +7445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██ | 424/2000 [05:42<21:46, 1.21it/s, loss=0.736]" + "training until 2000: 21%|██ | 424/2000 [07:05<23:11, 1.13it/s, loss=0.658]" ] }, { @@ -7453,7 +7453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 425/2000 [05:43<20:10, 1.30it/s, loss=0.736]" + "training until 2000: 21%|██▏ | 425/2000 [07:06<23:39, 1.11it/s, loss=0.658]" ] }, { @@ -7461,7 +7461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 425/2000 [05:43<20:10, 1.30it/s, loss=0.762]" + "training until 2000: 21%|██▏ | 425/2000 [07:06<23:39, 1.11it/s, loss=0.629]" ] }, { @@ -7469,7 +7469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 426/2000 [05:44<20:56, 1.25it/s, loss=0.762]" + "training until 2000: 21%|██▏ | 426/2000 [07:08<26:22, 1.01s/it, loss=0.629]" ] }, { @@ -7477,7 +7477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 426/2000 [05:44<20:56, 1.25it/s, loss=0.759]" + "training until 2000: 21%|██▏ | 426/2000 [07:08<26:22, 1.01s/it, loss=0.653]" ] }, { @@ -7485,7 +7485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 427/2000 [05:45<20:47, 1.26it/s, loss=0.759]" + "training until 2000: 21%|██▏ | 427/2000 [07:09<26:27, 1.01s/it, loss=0.653]" ] }, { @@ -7493,7 +7493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 427/2000 [05:45<20:47, 1.26it/s, loss=0.745]" + "training until 2000: 21%|██▏ | 427/2000 [07:09<26:27, 1.01s/it, loss=0.645]" ] }, { @@ -7501,7 +7501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 428/2000 [05:45<18:00, 1.46it/s, loss=0.745]" + "training until 2000: 21%|██▏ | 428/2000 [07:09<24:15, 1.08it/s, loss=0.645]" ] }, { @@ -7509,7 +7509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 428/2000 [05:45<18:00, 1.46it/s, loss=0.738]" + "training until 2000: 21%|██▏ | 428/2000 [07:09<24:15, 1.08it/s, loss=0.647]" ] }, { @@ -7517,7 +7517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 429/2000 [05:46<19:05, 1.37it/s, loss=0.738]" + "training until 2000: 21%|██▏ | 429/2000 [07:10<24:41, 1.06it/s, loss=0.647]" ] }, { @@ -7525,7 +7525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 21%|██▏ | 429/2000 [05:46<19:05, 1.37it/s, loss=0.76] " + "training until 2000: 21%|██▏ | 429/2000 [07:10<24:41, 1.06it/s, loss=0.637]" ] }, { @@ -7533,7 +7533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 430/2000 [05:47<19:57, 1.31it/s, loss=0.76]" + "training until 2000: 22%|██▏ | 430/2000 [07:11<24:08, 1.08it/s, loss=0.637]" ] }, { @@ -7541,7 +7541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 430/2000 [05:47<19:57, 1.31it/s, loss=0.746]" + "training until 2000: 22%|██▏ | 430/2000 [07:11<24:08, 1.08it/s, loss=0.654]" ] }, { @@ -7549,7 +7549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 431/2000 [05:48<20:18, 1.29it/s, loss=0.746]" + "training until 2000: 22%|██▏ | 431/2000 [07:12<25:48, 1.01it/s, loss=0.654]" ] }, { @@ -7557,7 +7557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 431/2000 [05:48<20:18, 1.29it/s, loss=0.781]" + "training until 2000: 22%|██▏ | 431/2000 [07:12<25:48, 1.01it/s, loss=0.675]" ] }, { @@ -7565,7 +7565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 432/2000 [05:49<21:35, 1.21it/s, loss=0.781]" + "training until 2000: 22%|██▏ | 432/2000 [07:13<27:10, 1.04s/it, loss=0.675]" ] }, { @@ -7573,7 +7573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 432/2000 [05:49<21:35, 1.21it/s, loss=0.795]" + "training until 2000: 22%|██▏ | 432/2000 [07:13<27:10, 1.04s/it, loss=0.657]" ] }, { @@ -7581,7 +7581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 433/2000 [05:49<18:49, 1.39it/s, loss=0.795]" + "training until 2000: 22%|██▏ | 433/2000 [07:14<25:54, 1.01it/s, loss=0.657]" ] }, { @@ -7589,7 +7589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 433/2000 [05:49<18:49, 1.39it/s, loss=0.771]" + "training until 2000: 22%|██▏ | 433/2000 [07:14<25:54, 1.01it/s, loss=0.648]" ] }, { @@ -7597,7 +7597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 434/2000 [05:50<19:09, 1.36it/s, loss=0.771]" + "training until 2000: 22%|██▏ | 434/2000 [07:16<29:34, 1.13s/it, loss=0.648]" ] }, { @@ -7605,7 +7605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 434/2000 [05:50<19:09, 1.36it/s, loss=0.747]" + "training until 2000: 22%|██▏ | 434/2000 [07:16<29:34, 1.13s/it, loss=0.648]" ] }, { @@ -7613,7 +7613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 435/2000 [05:50<17:33, 1.49it/s, loss=0.747]" + "training until 2000: 22%|██▏ | 435/2000 [07:17<27:25, 1.05s/it, loss=0.648]" ] }, { @@ -7621,7 +7621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 435/2000 [05:50<17:33, 1.49it/s, loss=0.746]" + "training until 2000: 22%|██▏ | 435/2000 [07:17<27:25, 1.05s/it, loss=0.672]" ] }, { @@ -7629,7 +7629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 436/2000 [05:51<19:21, 1.35it/s, loss=0.746]" + "training until 2000: 22%|██▏ | 436/2000 [07:17<24:43, 1.05it/s, loss=0.672]" ] }, { @@ -7637,7 +7637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 436/2000 [05:51<19:21, 1.35it/s, loss=0.759]" + "training until 2000: 22%|██▏ | 436/2000 [07:17<24:43, 1.05it/s, loss=0.685]" ] }, { @@ -7645,7 +7645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 437/2000 [05:52<20:13, 1.29it/s, loss=0.759]" + "training until 2000: 22%|██▏ | 437/2000 [07:18<22:40, 1.15it/s, loss=0.685]" ] }, { @@ -7653,7 +7653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 437/2000 [05:52<20:13, 1.29it/s, loss=0.778]" + "training until 2000: 22%|██▏ | 437/2000 [07:18<22:40, 1.15it/s, loss=0.652]" ] }, { @@ -7661,7 +7661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 438/2000 [05:53<21:58, 1.18it/s, loss=0.778]" + "training until 2000: 22%|██▏ | 438/2000 [07:19<22:36, 1.15it/s, loss=0.652]" ] }, { @@ -7669,7 +7669,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 438/2000 [05:53<21:58, 1.18it/s, loss=0.753]" + "training until 2000: 22%|██▏ | 438/2000 [07:19<22:36, 1.15it/s, loss=0.631]" ] }, { @@ -7677,7 +7677,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 439/2000 [05:54<20:20, 1.28it/s, loss=0.753]" + "training until 2000: 22%|██▏ | 439/2000 [07:20<23:30, 1.11it/s, loss=0.631]" ] }, { @@ -7685,7 +7685,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 439/2000 [05:54<20:20, 1.28it/s, loss=0.779]" + "training until 2000: 22%|██▏ | 439/2000 [07:20<23:30, 1.11it/s, loss=0.641]" ] }, { @@ -7693,7 +7693,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 440/2000 [05:54<20:33, 1.26it/s, loss=0.779]" + "training until 2000: 22%|██▏ | 440/2000 [07:21<22:24, 1.16it/s, loss=0.641]" ] }, { @@ -7701,7 +7701,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 440/2000 [05:55<20:33, 1.26it/s, loss=0.765]" + "training until 2000: 22%|██▏ | 440/2000 [07:21<22:24, 1.16it/s, loss=0.677]" ] }, { @@ -7709,7 +7709,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 441/2000 [05:55<20:13, 1.29it/s, loss=0.765]" + "training until 2000: 22%|██▏ | 441/2000 [07:22<25:07, 1.03it/s, loss=0.677]" ] }, { @@ -7717,7 +7717,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 441/2000 [05:55<20:13, 1.29it/s, loss=0.756]" + "training until 2000: 22%|██▏ | 441/2000 [07:22<25:07, 1.03it/s, loss=0.655]" ] }, { @@ -7725,7 +7725,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 442/2000 [05:56<20:56, 1.24it/s, loss=0.756]" + "training until 2000: 22%|██▏ | 442/2000 [07:23<22:37, 1.15it/s, loss=0.655]" ] }, { @@ -7733,7 +7733,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 442/2000 [05:56<20:56, 1.24it/s, loss=0.761]" + "training until 2000: 22%|██▏ | 442/2000 [07:23<22:37, 1.15it/s, loss=0.681]" ] }, { @@ -7741,7 +7741,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 443/2000 [05:57<20:04, 1.29it/s, loss=0.761]" + "training until 2000: 22%|██▏ | 443/2000 [07:24<24:52, 1.04it/s, loss=0.681]" ] }, { @@ -7749,7 +7749,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 443/2000 [05:57<20:04, 1.29it/s, loss=0.746]" + "training until 2000: 22%|██▏ | 443/2000 [07:24<24:52, 1.04it/s, loss=0.659]" ] }, { @@ -7757,7 +7757,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 444/2000 [05:58<25:38, 1.01it/s, loss=0.746]" + "training until 2000: 22%|██▏ | 444/2000 [07:25<24:41, 1.05it/s, loss=0.659]" ] }, { @@ -7765,7 +7765,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 444/2000 [05:58<25:38, 1.01it/s, loss=0.733]" + "training until 2000: 22%|██▏ | 444/2000 [07:25<24:41, 1.05it/s, loss=0.695]" ] }, { @@ -7773,7 +7773,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 445/2000 [05:59<26:44, 1.03s/it, loss=0.733]" + "training until 2000: 22%|██▏ | 445/2000 [07:26<24:09, 1.07it/s, loss=0.695]" ] }, { @@ -7781,7 +7781,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 445/2000 [05:59<26:44, 1.03s/it, loss=0.752]" + "training until 2000: 22%|██▏ | 445/2000 [07:26<24:09, 1.07it/s, loss=0.693]" ] }, { @@ -7789,7 +7789,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 446/2000 [06:01<27:49, 1.07s/it, loss=0.752]" + "training until 2000: 22%|██▏ | 446/2000 [07:27<26:09, 1.01s/it, loss=0.693]" ] }, { @@ -7797,7 +7797,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 446/2000 [06:01<27:49, 1.07s/it, loss=0.711]" + "training until 2000: 22%|██▏ | 446/2000 [07:27<26:09, 1.01s/it, loss=0.664]" ] }, { @@ -7805,7 +7805,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 447/2000 [06:01<23:49, 1.09it/s, loss=0.711]" + "training until 2000: 22%|██▏ | 447/2000 [07:28<24:46, 1.04it/s, loss=0.664]" ] }, { @@ -7813,7 +7813,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 447/2000 [06:01<23:49, 1.09it/s, loss=0.745]" + "training until 2000: 22%|██▏ | 447/2000 [07:28<24:46, 1.04it/s, loss=0.683]" ] }, { @@ -7821,7 +7821,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 448/2000 [06:02<21:56, 1.18it/s, loss=0.745]" + "training until 2000: 22%|██▏ | 448/2000 [07:28<22:26, 1.15it/s, loss=0.683]" ] }, { @@ -7829,7 +7829,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 448/2000 [06:02<21:56, 1.18it/s, loss=0.735]" + "training until 2000: 22%|██▏ | 448/2000 [07:28<22:26, 1.15it/s, loss=0.686]" ] }, { @@ -7837,7 +7837,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 449/2000 [06:03<21:34, 1.20it/s, loss=0.735]" + "training until 2000: 22%|██▏ | 449/2000 [07:29<24:45, 1.04it/s, loss=0.686]" ] }, { @@ -7845,7 +7845,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▏ | 449/2000 [06:03<21:34, 1.20it/s, loss=0.755]" + "training until 2000: 22%|██▏ | 449/2000 [07:29<24:45, 1.04it/s, loss=0.675]" ] }, { @@ -7853,7 +7853,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▎ | 450/2000 [06:03<20:50, 1.24it/s, loss=0.755]" + "training until 2000: 22%|██▎ | 450/2000 [07:30<22:42, 1.14it/s, loss=0.675]" ] }, { @@ -7861,7 +7861,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 22%|██▎ | 450/2000 [06:03<20:50, 1.24it/s, loss=0.796]" + "training until 2000: 22%|██▎ | 450/2000 [07:30<22:42, 1.14it/s, loss=0.666]" ] }, { @@ -7869,7 +7869,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 451/2000 [06:04<19:20, 1.33it/s, loss=0.796]" + "training until 2000: 23%|██▎ | 451/2000 [07:31<24:21, 1.06it/s, loss=0.666]" ] }, { @@ -7877,7 +7877,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 451/2000 [06:04<19:20, 1.33it/s, loss=0.76] " + "training until 2000: 23%|██▎ | 451/2000 [07:31<24:21, 1.06it/s, loss=0.632]" ] }, { @@ -7885,7 +7885,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 452/2000 [06:05<19:24, 1.33it/s, loss=0.76]" + "training until 2000: 23%|██▎ | 452/2000 [07:33<28:08, 1.09s/it, loss=0.632]" ] }, { @@ -7893,7 +7893,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 452/2000 [06:05<19:24, 1.33it/s, loss=0.756]" + "training until 2000: 23%|██▎ | 452/2000 [07:33<28:08, 1.09s/it, loss=0.654]" ] }, { @@ -7901,7 +7901,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 453/2000 [06:06<20:43, 1.24it/s, loss=0.756]" + "training until 2000: 23%|██▎ | 453/2000 [07:33<25:59, 1.01s/it, loss=0.654]" ] }, { @@ -7909,7 +7909,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 453/2000 [06:06<20:43, 1.24it/s, loss=0.737]" + "training until 2000: 23%|██▎ | 453/2000 [07:33<25:59, 1.01s/it, loss=0.656]" ] }, { @@ -7917,7 +7917,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 454/2000 [06:07<23:41, 1.09it/s, loss=0.737]" + "training until 2000: 23%|██▎ | 454/2000 [07:35<28:33, 1.11s/it, loss=0.656]" ] }, { @@ -7925,7 +7925,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 454/2000 [06:07<23:41, 1.09it/s, loss=0.744]" + "training until 2000: 23%|██▎ | 454/2000 [07:35<28:33, 1.11s/it, loss=0.652]" ] }, { @@ -7933,7 +7933,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 455/2000 [06:08<23:36, 1.09it/s, loss=0.744]" + "training until 2000: 23%|██▎ | 455/2000 [07:35<25:05, 1.03it/s, loss=0.652]" ] }, { @@ -7941,7 +7941,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 455/2000 [06:08<23:36, 1.09it/s, loss=0.767]" + "training until 2000: 23%|██▎ | 455/2000 [07:35<25:05, 1.03it/s, loss=0.646]" ] }, { @@ -7949,7 +7949,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 456/2000 [06:09<23:38, 1.09it/s, loss=0.767]" + "training until 2000: 23%|██▎ | 456/2000 [07:36<24:46, 1.04it/s, loss=0.646]" ] }, { @@ -7957,7 +7957,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 456/2000 [06:09<23:38, 1.09it/s, loss=0.758]" + "training until 2000: 23%|██▎ | 456/2000 [07:36<24:46, 1.04it/s, loss=0.656]" ] }, { @@ -7965,7 +7965,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 457/2000 [06:09<22:13, 1.16it/s, loss=0.758]" + "training until 2000: 23%|██▎ | 457/2000 [07:37<24:29, 1.05it/s, loss=0.656]" ] }, { @@ -7973,7 +7973,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 457/2000 [06:09<22:13, 1.16it/s, loss=0.764]" + "training until 2000: 23%|██▎ | 457/2000 [07:37<24:29, 1.05it/s, loss=0.629]" ] }, { @@ -7981,7 +7981,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 458/2000 [06:10<21:27, 1.20it/s, loss=0.764]" + "training until 2000: 23%|██▎ | 458/2000 [07:39<28:41, 1.12s/it, loss=0.629]" ] }, { @@ -7989,7 +7989,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 458/2000 [06:10<21:27, 1.20it/s, loss=0.774]" + "training until 2000: 23%|██▎ | 458/2000 [07:39<28:41, 1.12s/it, loss=0.666]" ] }, { @@ -7997,7 +7997,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 459/2000 [06:11<19:17, 1.33it/s, loss=0.774]" + "training until 2000: 23%|██▎ | 459/2000 [07:40<30:37, 1.19s/it, loss=0.666]" ] }, { @@ -8005,7 +8005,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 459/2000 [06:11<19:17, 1.33it/s, loss=0.719]" + "training until 2000: 23%|██▎ | 459/2000 [07:40<30:37, 1.19s/it, loss=0.649]" ] }, { @@ -8013,7 +8013,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 460/2000 [06:12<20:51, 1.23it/s, loss=0.719]" + "training until 2000: 23%|██▎ | 460/2000 [07:41<26:57, 1.05s/it, loss=0.649]" ] }, { @@ -8021,7 +8021,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 460/2000 [06:12<20:51, 1.23it/s, loss=0.733]" + "training until 2000: 23%|██▎ | 460/2000 [07:41<26:57, 1.05s/it, loss=0.618]" ] }, { @@ -8029,7 +8029,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 461/2000 [06:12<18:40, 1.37it/s, loss=0.733]" + "training until 2000: 23%|██▎ | 461/2000 [07:42<27:59, 1.09s/it, loss=0.618]" ] }, { @@ -8037,7 +8037,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 461/2000 [06:12<18:40, 1.37it/s, loss=0.751]" + "training until 2000: 23%|██▎ | 461/2000 [07:42<27:59, 1.09s/it, loss=0.625]" ] }, { @@ -8045,7 +8045,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 462/2000 [06:13<18:48, 1.36it/s, loss=0.751]" + "training until 2000: 23%|██▎ | 462/2000 [07:43<29:18, 1.14s/it, loss=0.625]" ] }, { @@ -8053,7 +8053,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 462/2000 [06:13<18:48, 1.36it/s, loss=0.725]" + "training until 2000: 23%|██▎ | 462/2000 [07:43<29:18, 1.14s/it, loss=0.666]" ] }, { @@ -8061,7 +8061,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 463/2000 [06:14<20:13, 1.27it/s, loss=0.725]" + "training until 2000: 23%|██▎ | 463/2000 [07:45<30:33, 1.19s/it, loss=0.666]" ] }, { @@ -8069,7 +8069,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 463/2000 [06:14<20:13, 1.27it/s, loss=0.761]" + "training until 2000: 23%|██▎ | 463/2000 [07:45<30:33, 1.19s/it, loss=0.678]" ] }, { @@ -8077,7 +8077,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 464/2000 [06:15<20:12, 1.27it/s, loss=0.761]" + "training until 2000: 23%|██▎ | 464/2000 [07:46<31:02, 1.21s/it, loss=0.678]" ] }, { @@ -8085,7 +8085,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 464/2000 [06:15<20:12, 1.27it/s, loss=0.754]" + "training until 2000: 23%|██▎ | 464/2000 [07:46<31:02, 1.21s/it, loss=0.657]" ] }, { @@ -8093,7 +8093,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 465/2000 [06:16<20:39, 1.24it/s, loss=0.754]" + "training until 2000: 23%|██▎ | 465/2000 [07:47<28:52, 1.13s/it, loss=0.657]" ] }, { @@ -8101,7 +8101,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 465/2000 [06:16<20:39, 1.24it/s, loss=0.721]" + "training until 2000: 23%|██▎ | 465/2000 [07:47<28:52, 1.13s/it, loss=0.644]" ] }, { @@ -8109,7 +8109,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 466/2000 [06:17<24:19, 1.05it/s, loss=0.721]" + "training until 2000: 23%|██▎ | 466/2000 [07:48<31:59, 1.25s/it, loss=0.644]" ] }, { @@ -8117,7 +8117,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 466/2000 [06:17<24:19, 1.05it/s, loss=0.773]" + "training until 2000: 23%|██▎ | 466/2000 [07:48<31:59, 1.25s/it, loss=0.629]" ] }, { @@ -8125,7 +8125,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 467/2000 [06:18<23:03, 1.11it/s, loss=0.773]" + "training until 2000: 23%|██▎ | 467/2000 [07:49<29:52, 1.17s/it, loss=0.629]" ] }, { @@ -8133,7 +8133,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 467/2000 [06:18<23:03, 1.11it/s, loss=0.715]" + "training until 2000: 23%|██▎ | 467/2000 [07:49<29:52, 1.17s/it, loss=0.659]" ] }, { @@ -8141,7 +8141,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 468/2000 [06:18<19:49, 1.29it/s, loss=0.715]" + "training until 2000: 23%|██▎ | 468/2000 [07:50<27:56, 1.09s/it, loss=0.659]" ] }, { @@ -8149,7 +8149,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 468/2000 [06:18<19:49, 1.29it/s, loss=0.781]" + "training until 2000: 23%|██▎ | 468/2000 [07:50<27:56, 1.09s/it, loss=0.637]" ] }, { @@ -8157,7 +8157,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 469/2000 [06:19<19:14, 1.33it/s, loss=0.781]" + "training until 2000: 23%|██▎ | 469/2000 [07:52<29:10, 1.14s/it, loss=0.637]" ] }, { @@ -8165,7 +8165,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 23%|██▎ | 469/2000 [06:19<19:14, 1.33it/s, loss=0.781]" + "training until 2000: 23%|██▎ | 469/2000 [07:52<29:10, 1.14s/it, loss=0.661]" ] }, { @@ -8173,7 +8173,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 470/2000 [06:19<18:11, 1.40it/s, loss=0.781]" + "training until 2000: 24%|██▎ | 470/2000 [07:52<26:51, 1.05s/it, loss=0.661]" ] }, { @@ -8181,7 +8181,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 470/2000 [06:19<18:11, 1.40it/s, loss=0.786]" + "training until 2000: 24%|██▎ | 470/2000 [07:52<26:51, 1.05s/it, loss=0.642]" ] }, { @@ -8189,7 +8189,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 471/2000 [06:20<18:14, 1.40it/s, loss=0.786]" + "training until 2000: 24%|██▎ | 471/2000 [07:53<26:26, 1.04s/it, loss=0.642]" ] }, { @@ -8197,7 +8197,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 471/2000 [06:20<18:14, 1.40it/s, loss=0.744]" + "training until 2000: 24%|██▎ | 471/2000 [07:53<26:26, 1.04s/it, loss=0.651]" ] }, { @@ -8205,7 +8205,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 472/2000 [06:21<17:46, 1.43it/s, loss=0.744]" + "training until 2000: 24%|██▎ | 472/2000 [07:55<27:13, 1.07s/it, loss=0.651]" ] }, { @@ -8213,7 +8213,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 472/2000 [06:21<17:46, 1.43it/s, loss=0.734]" + "training until 2000: 24%|██▎ | 472/2000 [07:55<27:13, 1.07s/it, loss=0.647]" ] }, { @@ -8221,7 +8221,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 473/2000 [06:21<17:27, 1.46it/s, loss=0.734]" + "training until 2000: 24%|██▎ | 473/2000 [07:56<26:57, 1.06s/it, loss=0.647]" ] }, { @@ -8229,7 +8229,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 473/2000 [06:21<17:27, 1.46it/s, loss=0.778]" + "training until 2000: 24%|██▎ | 473/2000 [07:56<26:57, 1.06s/it, loss=0.637]" ] }, { @@ -8237,7 +8237,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 474/2000 [06:23<20:56, 1.21it/s, loss=0.778]" + "training until 2000: 24%|██▎ | 474/2000 [07:57<31:39, 1.24s/it, loss=0.637]" ] }, { @@ -8245,7 +8245,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▎ | 474/2000 [06:23<20:56, 1.21it/s, loss=0.741]" + "training until 2000: 24%|██▎ | 474/2000 [07:57<31:39, 1.24s/it, loss=0.656]" ] }, { @@ -8253,7 +8253,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 475/2000 [06:24<22:06, 1.15it/s, loss=0.741]" + "training until 2000: 24%|██▍ | 475/2000 [07:58<28:00, 1.10s/it, loss=0.656]" ] }, { @@ -8261,7 +8261,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 475/2000 [06:24<22:06, 1.15it/s, loss=0.768]" + "training until 2000: 24%|██▍ | 475/2000 [07:58<28:00, 1.10s/it, loss=0.628]" ] }, { @@ -8269,7 +8269,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 476/2000 [06:24<20:56, 1.21it/s, loss=0.768]" + "training until 2000: 24%|██▍ | 476/2000 [07:59<27:12, 1.07s/it, loss=0.628]" ] }, { @@ -8277,7 +8277,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 476/2000 [06:24<20:56, 1.21it/s, loss=0.784]" + "training until 2000: 24%|██▍ | 476/2000 [07:59<27:12, 1.07s/it, loss=0.656]" ] }, { @@ -8285,7 +8285,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 477/2000 [06:25<20:04, 1.26it/s, loss=0.784]" + "training until 2000: 24%|██▍ | 477/2000 [08:00<28:21, 1.12s/it, loss=0.656]" ] }, { @@ -8293,7 +8293,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 477/2000 [06:25<20:04, 1.26it/s, loss=0.758]" + "training until 2000: 24%|██▍ | 477/2000 [08:00<28:21, 1.12s/it, loss=0.635]" ] }, { @@ -8301,7 +8301,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 478/2000 [06:26<19:51, 1.28it/s, loss=0.758]" + "training until 2000: 24%|██▍ | 478/2000 [08:02<32:06, 1.27s/it, loss=0.635]" ] }, { @@ -8309,7 +8309,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 478/2000 [06:26<19:51, 1.28it/s, loss=0.736]" + "training until 2000: 24%|██▍ | 478/2000 [08:02<32:06, 1.27s/it, loss=0.653]" ] }, { @@ -8317,7 +8317,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 479/2000 [06:26<18:57, 1.34it/s, loss=0.736]" + "training until 2000: 24%|██▍ | 479/2000 [08:03<31:07, 1.23s/it, loss=0.653]" ] }, { @@ -8325,7 +8325,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 479/2000 [06:26<18:57, 1.34it/s, loss=0.752]" + "training until 2000: 24%|██▍ | 479/2000 [08:03<31:07, 1.23s/it, loss=0.65] " ] }, { @@ -8333,7 +8333,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 480/2000 [06:27<18:43, 1.35it/s, loss=0.752]" + "training until 2000: 24%|██▍ | 480/2000 [08:04<29:00, 1.15s/it, loss=0.65]" ] }, { @@ -8341,7 +8341,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 480/2000 [06:27<18:43, 1.35it/s, loss=0.722]" + "training until 2000: 24%|██▍ | 480/2000 [08:04<29:00, 1.15s/it, loss=0.68]" ] }, { @@ -8349,7 +8349,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 481/2000 [06:28<19:30, 1.30it/s, loss=0.722]" + "training until 2000: 24%|██▍ | 481/2000 [08:05<28:26, 1.12s/it, loss=0.68]" ] }, { @@ -8357,7 +8357,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 481/2000 [06:28<19:30, 1.30it/s, loss=0.73] " + "training until 2000: 24%|██▍ | 481/2000 [08:05<28:26, 1.12s/it, loss=0.644]" ] }, { @@ -8365,7 +8365,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 482/2000 [06:29<19:38, 1.29it/s, loss=0.73]" + "training until 2000: 24%|██▍ | 482/2000 [08:06<29:31, 1.17s/it, loss=0.644]" ] }, { @@ -8373,7 +8373,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 482/2000 [06:29<19:38, 1.29it/s, loss=0.702]" + "training until 2000: 24%|██▍ | 482/2000 [08:06<29:31, 1.17s/it, loss=0.667]" ] }, { @@ -8381,7 +8381,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 483/2000 [06:30<20:17, 1.25it/s, loss=0.702]" + "training until 2000: 24%|██▍ | 483/2000 [08:07<27:41, 1.10s/it, loss=0.667]" ] }, { @@ -8389,7 +8389,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 483/2000 [06:30<20:17, 1.25it/s, loss=0.744]" + "training until 2000: 24%|██▍ | 483/2000 [08:07<27:41, 1.10s/it, loss=0.664]" ] }, { @@ -8397,7 +8397,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 484/2000 [06:31<20:27, 1.23it/s, loss=0.744]" + "training until 2000: 24%|██▍ | 484/2000 [08:08<28:54, 1.14s/it, loss=0.664]" ] }, { @@ -8405,7 +8405,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 484/2000 [06:31<20:27, 1.23it/s, loss=0.757]" + "training until 2000: 24%|██▍ | 484/2000 [08:08<28:54, 1.14s/it, loss=0.639]" ] }, { @@ -8413,7 +8413,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 485/2000 [06:31<19:35, 1.29it/s, loss=0.757]" + "training until 2000: 24%|██▍ | 485/2000 [08:09<25:46, 1.02s/it, loss=0.639]" ] }, { @@ -8421,7 +8421,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 485/2000 [06:31<19:35, 1.29it/s, loss=0.741]" + "training until 2000: 24%|██▍ | 485/2000 [08:09<25:46, 1.02s/it, loss=0.634]" ] }, { @@ -8429,7 +8429,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 486/2000 [06:32<21:35, 1.17it/s, loss=0.741]" + "training until 2000: 24%|██▍ | 486/2000 [08:10<25:37, 1.02s/it, loss=0.634]" ] }, { @@ -8437,7 +8437,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 486/2000 [06:32<21:35, 1.17it/s, loss=0.773]" + "training until 2000: 24%|██▍ | 486/2000 [08:10<25:37, 1.02s/it, loss=0.645]" ] }, { @@ -8445,7 +8445,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 487/2000 [06:33<19:51, 1.27it/s, loss=0.773]" + "training until 2000: 24%|██▍ | 487/2000 [08:11<26:13, 1.04s/it, loss=0.645]" ] }, { @@ -8453,7 +8453,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 487/2000 [06:33<19:51, 1.27it/s, loss=0.747]" + "training until 2000: 24%|██▍ | 487/2000 [08:11<26:13, 1.04s/it, loss=0.641]" ] }, { @@ -8461,7 +8461,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 488/2000 [06:34<20:47, 1.21it/s, loss=0.747]" + "training until 2000: 24%|██▍ | 488/2000 [08:12<24:39, 1.02it/s, loss=0.641]" ] }, { @@ -8469,7 +8469,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 488/2000 [06:34<20:47, 1.21it/s, loss=0.736]" + "training until 2000: 24%|██▍ | 488/2000 [08:12<24:39, 1.02it/s, loss=0.664]" ] }, { @@ -8477,7 +8477,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 489/2000 [06:35<20:00, 1.26it/s, loss=0.736]" + "training until 2000: 24%|██▍ | 489/2000 [08:13<21:44, 1.16it/s, loss=0.664]" ] }, { @@ -8485,7 +8485,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 489/2000 [06:35<20:00, 1.26it/s, loss=0.739]" + "training until 2000: 24%|██▍ | 489/2000 [08:13<21:44, 1.16it/s, loss=0.666]" ] }, { @@ -8493,7 +8493,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 490/2000 [06:35<20:12, 1.25it/s, loss=0.739]" + "training until 2000: 24%|██▍ | 490/2000 [08:14<25:52, 1.03s/it, loss=0.666]" ] }, { @@ -8501,7 +8501,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 24%|██▍ | 490/2000 [06:35<20:12, 1.25it/s, loss=0.737]" + "training until 2000: 24%|██▍ | 490/2000 [08:14<25:52, 1.03s/it, loss=0.633]" ] }, { @@ -8509,7 +8509,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 491/2000 [06:36<19:55, 1.26it/s, loss=0.737]" + "training until 2000: 25%|██▍ | 491/2000 [08:15<25:35, 1.02s/it, loss=0.633]" ] }, { @@ -8517,7 +8517,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 491/2000 [06:36<19:55, 1.26it/s, loss=0.752]" + "training until 2000: 25%|██▍ | 491/2000 [08:15<25:35, 1.02s/it, loss=0.654]" ] }, { @@ -8525,7 +8525,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 492/2000 [06:37<20:14, 1.24it/s, loss=0.752]" + "training until 2000: 25%|██▍ | 492/2000 [08:16<25:22, 1.01s/it, loss=0.654]" ] }, { @@ -8533,7 +8533,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 492/2000 [06:37<20:14, 1.24it/s, loss=0.72] " + "training until 2000: 25%|██▍ | 492/2000 [08:16<25:22, 1.01s/it, loss=0.664]" ] }, { @@ -8541,7 +8541,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 493/2000 [06:38<20:55, 1.20it/s, loss=0.72]" + "training until 2000: 25%|██▍ | 493/2000 [08:17<26:03, 1.04s/it, loss=0.664]" ] }, { @@ -8549,7 +8549,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 493/2000 [06:38<20:55, 1.20it/s, loss=0.757]" + "training until 2000: 25%|██▍ | 493/2000 [08:17<26:03, 1.04s/it, loss=0.647]" ] }, { @@ -8557,7 +8557,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 494/2000 [06:38<19:26, 1.29it/s, loss=0.757]" + "training until 2000: 25%|██▍ | 494/2000 [08:18<24:05, 1.04it/s, loss=0.647]" ] }, { @@ -8565,7 +8565,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 494/2000 [06:38<19:26, 1.29it/s, loss=0.734]" + "training until 2000: 25%|██▍ | 494/2000 [08:18<24:05, 1.04it/s, loss=0.649]" ] }, { @@ -8573,7 +8573,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 495/2000 [06:39<20:01, 1.25it/s, loss=0.734]" + "training until 2000: 25%|██▍ | 495/2000 [08:19<22:31, 1.11it/s, loss=0.649]" ] }, { @@ -8581,7 +8581,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 495/2000 [06:39<20:01, 1.25it/s, loss=0.75] " + "training until 2000: 25%|██▍ | 495/2000 [08:19<22:31, 1.11it/s, loss=0.651]" ] }, { @@ -8589,7 +8589,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 496/2000 [06:40<20:27, 1.23it/s, loss=0.75]" + "training until 2000: 25%|██▍ | 496/2000 [08:20<22:44, 1.10it/s, loss=0.651]" ] }, { @@ -8597,7 +8597,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 496/2000 [06:40<20:27, 1.23it/s, loss=0.733]" + "training until 2000: 25%|██▍ | 496/2000 [08:20<22:44, 1.10it/s, loss=0.636]" ] }, { @@ -8605,7 +8605,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 497/2000 [06:41<19:18, 1.30it/s, loss=0.733]" + "training until 2000: 25%|██▍ | 497/2000 [08:21<23:33, 1.06it/s, loss=0.636]" ] }, { @@ -8613,7 +8613,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 497/2000 [06:41<19:18, 1.30it/s, loss=0.719]" + "training until 2000: 25%|██▍ | 497/2000 [08:21<23:33, 1.06it/s, loss=0.667]" ] }, { @@ -8621,7 +8621,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 498/2000 [06:42<19:44, 1.27it/s, loss=0.719]" + "training until 2000: 25%|██▍ | 498/2000 [08:21<21:38, 1.16it/s, loss=0.667]" ] }, { @@ -8629,7 +8629,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 498/2000 [06:42<19:44, 1.27it/s, loss=0.734]" + "training until 2000: 25%|██▍ | 498/2000 [08:21<21:38, 1.16it/s, loss=0.652]" ] }, { @@ -8637,7 +8637,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 499/2000 [06:42<18:05, 1.38it/s, loss=0.734]" + "training until 2000: 25%|██▍ | 499/2000 [08:22<22:50, 1.09it/s, loss=0.652]" ] }, { @@ -8645,7 +8645,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▍ | 499/2000 [06:42<18:05, 1.38it/s, loss=0.795]" + "training until 2000: 25%|██▍ | 499/2000 [08:22<22:50, 1.09it/s, loss=0.638]" ] }, { @@ -8653,7 +8653,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 500/2000 [06:44<22:16, 1.12it/s, loss=0.795]" + "training until 2000: 25%|██▌ | 500/2000 [08:23<22:37, 1.10it/s, loss=0.638]" ] }, { @@ -8661,7 +8661,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 500/2000 [06:44<22:16, 1.12it/s, loss=0.754]" + "training until 2000: 25%|██▌ | 500/2000 [08:23<22:37, 1.10it/s, loss=0.65] " ] }, { @@ -8749,7 +8749,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:10, 21.48blocks/s, ⧗=0, ▶=1, ✔=1, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:10, 21.47blocks/s, ⧗=0, ▶=1, ✔=1, ✗=0, ∅=0]" ] }, { @@ -8771,7 +8771,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:19, 10.97blocks/s, ⧗=0, ▶=0, ✔=2, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:19, 11.15blocks/s, ⧗=0, ▶=0, ✔=2, ✗=0, ∅=0]" ] }, { @@ -8793,7 +8793,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:09, 21.54blocks/s, ⧗=0, ▶=1, ✔=2, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:09, 21.91blocks/s, ⧗=0, ▶=1, ✔=2, ✗=0, ∅=0]" ] }, { @@ -8815,7 +8815,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:14, 14.29blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:14, 14.63blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" ] }, { @@ -8837,7 +8837,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:10, 21.29blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" ] }, { @@ -8859,7 +8859,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:10, 21.29blocks/s, ⧗=0, ▶=1, ✔=3, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=1, ✔=3, ✗=0, ∅=0]" ] }, { @@ -8881,7 +8881,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:10, 21.29blocks/s, ⧗=0, ▶=0, ✔=4, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=0, ✔=4, ✗=0, ∅=0]" ] }, { @@ -8903,7 +8903,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:09, 21.29blocks/s, ⧗=0, ▶=1, ✔=4, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=1, ✔=4, ✗=0, ∅=0]" ] }, { @@ -8925,7 +8925,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:09, 21.29blocks/s, ⧗=0, ▶=0, ✔=5, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=0, ✔=5, ✗=0, ∅=0]" ] }, { @@ -8947,7 +8947,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:09, 21.29blocks/s, ⧗=0, ▶=1, ✔=5, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=1, ✔=5, ✗=0, ∅=0]" ] }, { @@ -8969,7 +8969,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:09, 21.29blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:09, 21.78blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" ] }, { @@ -8991,7 +8991,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" ] }, { @@ -9013,7 +9013,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=1, ✔=6, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=1, ✔=6, ✗=0, ∅=0]" ] }, { @@ -9035,7 +9035,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=0, ✔=7, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=0, ✔=7, ✗=0, ∅=0]" ] }, { @@ -9057,7 +9057,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=1, ✔=7, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=1, ✔=7, ✗=0, ∅=0]" ] }, { @@ -9079,7 +9079,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=0, ✔=8, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=0, ✔=8, ✗=0, ∅=0]" ] }, { @@ -9101,7 +9101,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=1, ✔=8, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=1, ✔=8, ✗=0, ∅=0]" ] }, { @@ -9123,7 +9123,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:09, 21.26blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:10, 20.18blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" ] }, { @@ -9145,7 +9145,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:10, 19.04blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" ] }, { @@ -9167,7 +9167,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:10, 19.04blocks/s, ⧗=0, ▶=1, ✔=9, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=1, ✔=9, ✗=0, ∅=0]" ] }, { @@ -9189,7 +9189,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:10, 19.04blocks/s, ⧗=0, ▶=0, ✔=10, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=0, ✔=10, ✗=0, ∅=0]" ] }, { @@ -9211,7 +9211,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:10, 19.04blocks/s, ⧗=0, ▶=1, ✔=10, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=1, ✔=10, ✗=0, ∅=0]" ] }, { @@ -9233,7 +9233,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:10, 19.04blocks/s, ⧗=0, ▶=0, ✔=11, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=0, ✔=11, ✗=0, ∅=0]" ] }, { @@ -9255,7 +9255,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:10, 19.04blocks/s, ⧗=0, ▶=1, ✔=11, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=1, ✔=11, ✗=0, ∅=0]" ] }, { @@ -9277,7 +9277,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:10, 19.32blocks/s, ⧗=0, ▶=1, ✔=11, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:10, 20.40blocks/s, ⧗=0, ▶=0, ✔=12, ✗=0, ∅=0]" ] }, { @@ -9299,7 +9299,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:10, 19.32blocks/s, ⧗=0, ▶=0, ✔=12, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 18.84blocks/s, ⧗=0, ▶=0, ✔=12, ✗=0, ∅=0]" ] }, { @@ -9321,7 +9321,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 19.32blocks/s, ⧗=0, ▶=1, ✔=12, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 18.84blocks/s, ⧗=0, ▶=1, ✔=12, ✗=0, ∅=0]" ] }, { @@ -9343,7 +9343,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 19.32blocks/s, ⧗=0, ▶=0, ✔=13, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 18.84blocks/s, ⧗=0, ▶=0, ✔=13, ✗=0, ∅=0]" ] }, { @@ -9365,7 +9365,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:10, 19.32blocks/s, ⧗=0, ▶=1, ✔=13, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:10, 18.84blocks/s, ⧗=0, ▶=1, ✔=13, ✗=0, ∅=0]" ] }, { @@ -9387,7 +9387,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:10, 19.32blocks/s, ⧗=0, ▶=0, ✔=14, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:10, 18.84blocks/s, ⧗=0, ▶=0, ✔=14, ✗=0, ∅=0]" ] }, { @@ -9409,7 +9409,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:10, 19.60blocks/s, ⧗=0, ▶=0, ✔=14, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:10, 18.95blocks/s, ⧗=0, ▶=0, ✔=14, ✗=0, ∅=0]" ] }, { @@ -9431,7 +9431,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:10, 19.60blocks/s, ⧗=0, ▶=1, ✔=14, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:10, 18.95blocks/s, ⧗=0, ▶=1, ✔=14, ✗=0, ∅=0]" ] }, { @@ -9453,7 +9453,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:10, 19.60blocks/s, ⧗=0, ▶=0, ✔=15, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:10, 18.95blocks/s, ⧗=0, ▶=0, ✔=15, ✗=0, ∅=0]" ] }, { @@ -9475,7 +9475,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 19.60blocks/s, ⧗=0, ▶=1, ✔=15, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 18.95blocks/s, ⧗=0, ▶=1, ✔=15, ✗=0, ∅=0]" ] }, { @@ -9497,7 +9497,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 19.60blocks/s, ⧗=0, ▶=0, ✔=16, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 18.95blocks/s, ⧗=0, ▶=0, ✔=16, ✗=0, ∅=0]" ] }, { @@ -9519,7 +9519,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 18.40blocks/s, ⧗=0, ▶=0, ✔=16, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 18.44blocks/s, ⧗=0, ▶=0, ✔=16, ✗=0, ∅=0]" ] }, { @@ -9541,7 +9541,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 18.40blocks/s, ⧗=0, ▶=1, ✔=16, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 18.44blocks/s, ⧗=0, ▶=1, ✔=16, ✗=0, ∅=0]" ] }, { @@ -9563,7 +9563,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 18.40blocks/s, ⧗=0, ▶=0, ✔=17, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 18.44blocks/s, ⧗=0, ▶=0, ✔=17, ✗=0, ∅=0]" ] }, { @@ -9585,7 +9585,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.40blocks/s, ⧗=0, ▶=1, ✔=17, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.44blocks/s, ⧗=0, ▶=1, ✔=17, ✗=0, ∅=0]" ] }, { @@ -9607,7 +9607,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.40blocks/s, ⧗=0, ▶=0, ✔=18, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.44blocks/s, ⧗=0, ▶=0, ✔=18, ✗=0, ∅=0]" ] }, { @@ -9629,7 +9629,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:11, 17.68blocks/s, ⧗=0, ▶=0, ✔=18, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:10, 18.04blocks/s, ⧗=0, ▶=0, ✔=18, ✗=0, ∅=0]" ] }, { @@ -9651,7 +9651,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:11, 17.68blocks/s, ⧗=0, ▶=1, ✔=18, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:10, 18.04blocks/s, ⧗=0, ▶=1, ✔=18, ✗=0, ∅=0]" ] }, { @@ -9673,7 +9673,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 18/216 [00:01<00:11, 17.68blocks/s, ⧗=0, ▶=0, ✔=19, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:10, 18.04blocks/s, ⧗=0, ▶=0, ✔=19, ✗=0, ∅=0]" ] }, { @@ -9695,7 +9695,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:11, 17.68blocks/s, ⧗=0, ▶=1, ✔=19, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:10, 18.04blocks/s, ⧗=0, ▶=1, ✔=19, ✗=0, ∅=0]" ] }, { @@ -9717,7 +9717,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:11, 17.68blocks/s, ⧗=0, ▶=0, ✔=20, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:10, 18.04blocks/s, ⧗=0, ▶=0, ✔=20, ✗=0, ∅=0]" ] }, { @@ -9739,7 +9739,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.13blocks/s, ⧗=0, ▶=0, ✔=20, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.04blocks/s, ⧗=0, ▶=1, ✔=20, ✗=0, ∅=0]" ] }, { @@ -9761,7 +9761,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.13blocks/s, ⧗=0, ▶=1, ✔=20, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.04blocks/s, ⧗=0, ▶=0, ✔=21, ✗=0, ∅=0]" ] }, { @@ -9783,7 +9783,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.13blocks/s, ⧗=0, ▶=0, ✔=21, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.34blocks/s, ⧗=0, ▶=0, ✔=21, ✗=0, ∅=0]" ] }, { @@ -9805,7 +9805,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.13blocks/s, ⧗=0, ▶=1, ✔=21, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.34blocks/s, ⧗=0, ▶=1, ✔=21, ✗=0, ∅=0]" ] }, { @@ -9827,29 +9827,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.13blocks/s, ⧗=0, ▶=0, ✔=22, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 10%|█ | 22/216 [00:01<00:10, 18.34blocks/s, ⧗=0, ▶=0, ✔=22, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.34blocks/s, ⧗=0, ▶=0, ✔=22, ✗=0, ∅=0]" ] }, { @@ -9937,7 +9915,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:10, 18.34blocks/s, ⧗=0, ▶=0, ✔=24, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:10, 18.73blocks/s, ⧗=0, ▶=1, ✔=23, ✗=0, ∅=0]" ] }, { @@ -9959,7 +9937,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 11%|█ | 24/216 [00:01<00:10, 18.34blocks/s, ⧗=0, ▶=1, ✔=24, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:10, 18.73blocks/s, ⧗=0, ▶=0, ✔=24, ✗=0, ∅=0]" ] }, { @@ -10025,7 +10003,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:10, 18.73blocks/s, ⧗=0, ▶=1, ✔=25, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=0, ✔=25, ✗=0, ∅=0]" ] }, { @@ -10047,7 +10025,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:10, 18.73blocks/s, ⧗=0, ▶=0, ✔=26, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=1, ✔=25, ✗=0, ∅=0]" ] }, { @@ -10069,7 +10047,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:10, 18.73blocks/s, ⧗=0, ▶=1, ✔=26, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=0, ✔=26, ✗=0, ∅=0]" ] }, { @@ -10091,7 +10069,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:10, 18.73blocks/s, ⧗=0, ▶=0, ✔=27, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=1, ✔=26, ✗=0, ∅=0]" ] }, { @@ -10113,7 +10091,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:10, 18.76blocks/s, ⧗=0, ▶=0, ✔=27, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=0, ✔=27, ✗=0, ∅=0]" ] }, { @@ -10135,7 +10113,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:10, 18.76blocks/s, ⧗=0, ▶=1, ✔=27, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:10, 17.45blocks/s, ⧗=0, ▶=0, ✔=27, ✗=0, ∅=0]" ] }, { @@ -10157,7 +10135,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:10, 18.76blocks/s, ⧗=0, ▶=0, ✔=28, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:10, 17.45blocks/s, ⧗=0, ▶=1, ✔=27, ✗=0, ∅=0]" ] }, { @@ -10179,7 +10157,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:10, 18.76blocks/s, ⧗=0, ▶=1, ✔=28, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:10, 17.45blocks/s, ⧗=0, ▶=0, ✔=28, ✗=0, ∅=0]" ] }, { @@ -10201,7 +10179,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:10, 18.76blocks/s, ⧗=0, ▶=0, ✔=29, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:10, 17.45blocks/s, ⧗=0, ▶=1, ✔=28, ✗=0, ∅=0]" ] }, { @@ -10223,7 +10201,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:10, 18.36blocks/s, ⧗=0, ▶=0, ✔=29, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:10, 17.45blocks/s, ⧗=0, ▶=0, ✔=29, ✗=0, ∅=0]" ] }, { @@ -10245,7 +10223,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:10, 18.36blocks/s, ⧗=0, ▶=1, ✔=29, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=0, ✔=29, ✗=0, ∅=0]" ] }, { @@ -10267,7 +10245,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:10, 18.36blocks/s, ⧗=0, ▶=0, ✔=30, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=1, ✔=29, ✗=0, ∅=0]" ] }, { @@ -10289,7 +10267,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:10, 18.36blocks/s, ⧗=0, ▶=1, ✔=30, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=0, ✔=30, ✗=0, ∅=0]" ] }, { @@ -10311,7 +10289,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:10, 18.36blocks/s, ⧗=0, ▶=0, ✔=31, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=1, ✔=30, ✗=0, ∅=0]" ] }, { @@ -10333,7 +10311,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:10, 18.36blocks/s, ⧗=0, ▶=1, ✔=31, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=0, ✔=31, ✗=0, ∅=0]" ] }, { @@ -10355,7 +10333,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:09, 18.69blocks/s, ⧗=0, ▶=1, ✔=31, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:10, 17.98blocks/s, ⧗=0, ▶=1, ✔=31, ✗=0, ∅=0]" ] }, { @@ -10377,7 +10355,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:09, 18.69blocks/s, ⧗=0, ▶=0, ✔=32, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:09, 18.51blocks/s, ⧗=0, ▶=1, ✔=31, ✗=0, ∅=0]" ] }, { @@ -10399,7 +10377,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.69blocks/s, ⧗=0, ▶=1, ✔=32, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:09, 18.51blocks/s, ⧗=0, ▶=0, ✔=32, ✗=0, ∅=0]" ] }, { @@ -10421,7 +10399,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.69blocks/s, ⧗=0, ▶=0, ✔=33, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.51blocks/s, ⧗=0, ▶=1, ✔=32, ✗=0, ∅=0]" ] }, { @@ -10443,7 +10421,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.90blocks/s, ⧗=0, ▶=0, ✔=33, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.51blocks/s, ⧗=0, ▶=0, ✔=33, ✗=0, ∅=0]" ] }, { @@ -10465,7 +10443,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.90blocks/s, ⧗=0, ▶=1, ✔=33, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.78blocks/s, ⧗=0, ▶=0, ✔=33, ✗=0, ∅=0]" ] }, { @@ -10487,7 +10465,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.90blocks/s, ⧗=0, ▶=0, ✔=34, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.78blocks/s, ⧗=0, ▶=1, ✔=33, ✗=0, ∅=0]" ] }, { @@ -10509,7 +10487,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.90blocks/s, ⧗=0, ▶=1, ✔=34, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.78blocks/s, ⧗=0, ▶=0, ✔=34, ✗=0, ∅=0]" ] }, { @@ -10531,7 +10509,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.90blocks/s, ⧗=0, ▶=0, ✔=35, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.78blocks/s, ⧗=0, ▶=1, ✔=34, ✗=0, ∅=0]" ] }, { @@ -10553,7 +10531,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 19.12blocks/s, ⧗=0, ▶=0, ✔=35, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.78blocks/s, ⧗=0, ▶=0, ✔=35, ✗=0, ∅=0]" ] }, { @@ -10575,7 +10553,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 19.12blocks/s, ⧗=0, ▶=1, ✔=35, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 18.86blocks/s, ⧗=0, ▶=0, ✔=35, ✗=0, ∅=0]" ] }, { @@ -10597,7 +10575,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 19.12blocks/s, ⧗=0, ▶=0, ✔=36, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 18.86blocks/s, ⧗=0, ▶=1, ✔=35, ✗=0, ∅=0]" ] }, { @@ -10619,7 +10597,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:09, 19.12blocks/s, ⧗=0, ▶=1, ✔=36, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 18.86blocks/s, ⧗=0, ▶=0, ✔=36, ✗=0, ∅=0]" ] }, { @@ -10641,7 +10619,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:09, 19.12blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:09, 18.86blocks/s, ⧗=0, ▶=1, ✔=36, ✗=0, ∅=0]" ] }, { @@ -10663,7 +10641,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:09, 19.15blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:09, 18.86blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" ] }, { @@ -10685,7 +10663,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:09, 19.15blocks/s, ⧗=0, ▶=1, ✔=37, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:09, 19.15blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" ] }, { @@ -10707,7 +10685,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:02<00:09, 19.15blocks/s, ⧗=0, ▶=0, ✔=38, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:09, 19.15blocks/s, ⧗=0, ▶=1, ✔=37, ✗=0, ∅=0]" ] }, { @@ -10729,7 +10707,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:02<00:09, 19.15blocks/s, ⧗=0, ▶=1, ✔=38, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:02<00:09, 19.15blocks/s, ⧗=0, ▶=0, ✔=38, ✗=0, ∅=0]" ] }, { @@ -10751,7 +10729,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:02<00:09, 19.15blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:02<00:09, 19.15blocks/s, ⧗=0, ▶=1, ✔=38, ✗=0, ∅=0]" ] }, { @@ -10773,7 +10751,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 18.10blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:02<00:09, 19.15blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" ] }, { @@ -10795,7 +10773,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 18.10blocks/s, ⧗=0, ▶=1, ✔=39, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 18.71blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" ] }, { @@ -10817,7 +10795,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 18.10blocks/s, ⧗=0, ▶=0, ✔=40, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 18.71blocks/s, ⧗=0, ▶=1, ✔=39, ✗=0, ∅=0]" ] }, { @@ -10839,7 +10817,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:09, 18.10blocks/s, ⧗=0, ▶=1, ✔=40, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 18.71blocks/s, ⧗=0, ▶=0, ✔=40, ✗=0, ∅=0]" ] }, { @@ -10861,7 +10839,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:09, 18.10blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:09, 18.71blocks/s, ⧗=0, ▶=1, ✔=40, ✗=0, ∅=0]" ] }, { @@ -10883,7 +10861,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.36blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:09, 18.71blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" ] }, { @@ -10905,7 +10883,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.36blocks/s, ⧗=0, ▶=1, ✔=41, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" ] }, { @@ -10927,7 +10905,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.36blocks/s, ⧗=0, ▶=0, ✔=42, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=1, ✔=41, ✗=0, ∅=0]" ] }, { @@ -10949,7 +10927,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:09, 18.36blocks/s, ⧗=0, ▶=1, ✔=42, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=0, ✔=42, ✗=0, ∅=0]" ] }, { @@ -10971,7 +10949,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:09, 18.36blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=1, ✔=42, ✗=0, ∅=0]" ] }, { @@ -10993,7 +10971,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:10, 17.15blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" ] }, { @@ -11015,7 +10993,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:10, 17.15blocks/s, ⧗=0, ▶=1, ✔=43, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:09, 18.90blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" ] }, { @@ -11037,7 +11015,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:10, 17.15blocks/s, ⧗=0, ▶=0, ✔=44, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:09, 18.90blocks/s, ⧗=0, ▶=1, ✔=43, ✗=0, ∅=0]" ] }, { @@ -11059,7 +11037,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:10, 17.15blocks/s, ⧗=0, ▶=1, ✔=44, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:09, 18.90blocks/s, ⧗=0, ▶=0, ✔=44, ✗=0, ∅=0]" ] }, { @@ -11081,7 +11059,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:10, 17.15blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:09, 18.90blocks/s, ⧗=0, ▶=1, ✔=44, ✗=0, ∅=0]" ] }, { @@ -11103,7 +11081,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:10, 17.03blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:09, 18.90blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" ] }, { @@ -11125,7 +11103,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:10, 17.03blocks/s, ⧗=0, ▶=1, ✔=45, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:09, 18.41blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" ] }, { @@ -11147,7 +11125,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:10, 17.03blocks/s, ⧗=0, ▶=0, ✔=46, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:09, 18.41blocks/s, ⧗=0, ▶=1, ✔=45, ✗=0, ∅=0]" ] }, { @@ -11169,7 +11147,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:09, 17.03blocks/s, ⧗=0, ▶=1, ✔=46, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:09, 18.41blocks/s, ⧗=0, ▶=0, ✔=46, ✗=0, ∅=0]" ] }, { @@ -11191,7 +11169,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:09, 17.03blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:09, 18.41blocks/s, ⧗=0, ▶=1, ✔=46, ✗=0, ∅=0]" ] }, { @@ -11213,7 +11191,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 17.37blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:09, 18.41blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" ] }, { @@ -11235,7 +11213,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 17.37blocks/s, ⧗=0, ▶=1, ✔=47, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 17.95blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" ] }, { @@ -11257,7 +11235,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 17.37blocks/s, ⧗=0, ▶=0, ✔=48, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 17.95blocks/s, ⧗=0, ▶=1, ✔=47, ✗=0, ∅=0]" ] }, { @@ -11279,7 +11257,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:09, 17.37blocks/s, ⧗=0, ▶=1, ✔=48, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 17.95blocks/s, ⧗=0, ▶=0, ✔=48, ✗=0, ∅=0]" ] }, { @@ -11301,7 +11279,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:09, 17.37blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:09, 17.95blocks/s, ⧗=0, ▶=1, ✔=48, ✗=0, ∅=0]" ] }, { @@ -11323,7 +11301,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 17.46blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:09, 17.95blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" ] }, { @@ -11345,7 +11323,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 17.46blocks/s, ⧗=0, ▶=1, ✔=49, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 17.48blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" ] }, { @@ -11367,7 +11345,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 17.46blocks/s, ⧗=0, ▶=0, ✔=50, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 17.48blocks/s, ⧗=0, ▶=1, ✔=49, ✗=0, ∅=0]" ] }, { @@ -11389,7 +11367,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:09, 17.46blocks/s, ⧗=0, ▶=1, ✔=50, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 17.48blocks/s, ⧗=0, ▶=0, ✔=50, ✗=0, ∅=0]" ] }, { @@ -11411,7 +11389,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:09, 17.46blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:09, 17.48blocks/s, ⧗=0, ▶=1, ✔=50, ✗=0, ∅=0]" ] }, { @@ -11433,7 +11411,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:10, 15.75blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:09, 17.48blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" ] }, { @@ -11455,7 +11433,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:10, 15.75blocks/s, ⧗=0, ▶=1, ✔=51, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:10, 16.10blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" ] }, { @@ -11477,7 +11455,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:10, 15.75blocks/s, ⧗=0, ▶=0, ✔=52, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:10, 16.10blocks/s, ⧗=0, ▶=1, ✔=51, ✗=0, ∅=0]" ] }, { @@ -11499,7 +11477,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:10, 15.75blocks/s, ⧗=0, ▶=1, ✔=52, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:10, 16.10blocks/s, ⧗=0, ▶=0, ✔=52, ✗=0, ∅=0]" ] }, { @@ -11521,7 +11499,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:10, 15.75blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:10, 16.10blocks/s, ⧗=0, ▶=1, ✔=52, ✗=0, ∅=0]" ] }, { @@ -11543,7 +11521,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 15.60blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:10, 16.10blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" ] }, { @@ -11565,7 +11543,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 15.60blocks/s, ⧗=0, ▶=1, ✔=53, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 15.35blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" ] }, { @@ -11587,7 +11565,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:03<00:10, 15.60blocks/s, ⧗=0, ▶=0, ✔=54, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 15.35blocks/s, ⧗=0, ▶=1, ✔=53, ✗=0, ∅=0]" ] }, { @@ -11609,7 +11587,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:03<00:10, 15.60blocks/s, ⧗=0, ▶=1, ✔=54, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:03<00:10, 15.35blocks/s, ⧗=0, ▶=0, ✔=54, ✗=0, ∅=0]" ] }, { @@ -11631,7 +11609,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:03<00:10, 15.60blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:03<00:10, 15.35blocks/s, ⧗=0, ▶=1, ✔=54, ✗=0, ∅=0]" ] }, { @@ -11653,7 +11631,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 16.08blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:03<00:10, 15.35blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" ] }, { @@ -11675,7 +11653,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 16.08blocks/s, ⧗=0, ▶=1, ✔=55, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 15.92blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" ] }, { @@ -11697,7 +11675,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 16.08blocks/s, ⧗=0, ▶=0, ✔=56, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 15.92blocks/s, ⧗=0, ▶=1, ✔=55, ✗=0, ∅=0]" ] }, { @@ -11719,7 +11697,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:03<00:09, 16.08blocks/s, ⧗=0, ▶=1, ✔=56, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 15.92blocks/s, ⧗=0, ▶=0, ✔=56, ✗=0, ∅=0]" ] }, { @@ -11741,7 +11719,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:03<00:09, 16.08blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:03<00:10, 15.92blocks/s, ⧗=0, ▶=1, ✔=56, ✗=0, ∅=0]" ] }, { @@ -11763,7 +11741,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.40blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:03<00:10, 15.92blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" ] }, { @@ -11785,7 +11763,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.40blocks/s, ⧗=0, ▶=1, ✔=57, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.17blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" ] }, { @@ -11807,7 +11785,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.40blocks/s, ⧗=0, ▶=0, ✔=58, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.17blocks/s, ⧗=0, ▶=1, ✔=57, ✗=0, ∅=0]" ] }, { @@ -11829,7 +11807,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:09, 16.40blocks/s, ⧗=0, ▶=1, ✔=58, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.17blocks/s, ⧗=0, ▶=0, ✔=58, ✗=0, ∅=0]" ] }, { @@ -11851,7 +11829,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:09, 16.40blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:09, 16.17blocks/s, ⧗=0, ▶=1, ✔=58, ✗=0, ∅=0]" ] }, { @@ -11873,7 +11851,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.25blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:09, 16.17blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" ] }, { @@ -11895,7 +11873,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.25blocks/s, ⧗=0, ▶=1, ✔=59, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.73blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" ] }, { @@ -11917,7 +11895,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.25blocks/s, ⧗=0, ▶=0, ✔=60, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.73blocks/s, ⧗=0, ▶=1, ✔=59, ✗=0, ∅=0]" ] }, { @@ -11939,7 +11917,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:09, 16.25blocks/s, ⧗=0, ▶=1, ✔=60, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.73blocks/s, ⧗=0, ▶=0, ✔=60, ✗=0, ∅=0]" ] }, { @@ -11961,7 +11939,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:09, 16.25blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:09, 16.73blocks/s, ⧗=0, ▶=1, ✔=60, ✗=0, ∅=0]" ] }, { @@ -11983,7 +11961,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:09, 16.77blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:09, 16.73blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" ] }, { @@ -12005,7 +11983,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:09, 16.77blocks/s, ⧗=0, ▶=1, ✔=61, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:09, 16.93blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" ] }, { @@ -12027,7 +12005,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:09, 16.77blocks/s, ⧗=0, ▶=0, ✔=62, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:09, 16.93blocks/s, ⧗=0, ▶=1, ✔=61, ✗=0, ∅=0]" ] }, { @@ -12049,7 +12027,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:09, 16.77blocks/s, ⧗=0, ▶=1, ✔=62, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:09, 16.93blocks/s, ⧗=0, ▶=0, ✔=62, ✗=0, ∅=0]" ] }, { @@ -12071,7 +12049,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:09, 16.77blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:09, 16.93blocks/s, ⧗=0, ▶=1, ✔=62, ✗=0, ∅=0]" ] }, { @@ -12093,7 +12071,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:09, 16.44blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:09, 16.93blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" ] }, { @@ -12115,7 +12093,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:09, 16.44blocks/s, ⧗=0, ▶=1, ✔=63, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:09, 16.54blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" ] }, { @@ -12137,7 +12115,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:09, 16.44blocks/s, ⧗=0, ▶=0, ✔=64, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:09, 16.54blocks/s, ⧗=0, ▶=1, ✔=63, ✗=0, ∅=0]" ] }, { @@ -12159,7 +12137,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:09, 16.44blocks/s, ⧗=0, ▶=1, ✔=64, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:09, 16.54blocks/s, ⧗=0, ▶=0, ✔=64, ✗=0, ∅=0]" ] }, { @@ -12181,7 +12159,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:09, 16.44blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:09, 16.54blocks/s, ⧗=0, ▶=1, ✔=64, ✗=0, ∅=0]" ] }, { @@ -12203,7 +12181,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 16.88blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:09, 16.54blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" ] }, { @@ -12225,7 +12203,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 16.88blocks/s, ⧗=0, ▶=1, ✔=65, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 16.87blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" ] }, { @@ -12247,7 +12225,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 16.88blocks/s, ⧗=0, ▶=0, ✔=66, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 16.87blocks/s, ⧗=0, ▶=1, ✔=65, ✗=0, ∅=0]" ] }, { @@ -12269,7 +12247,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 16.88blocks/s, ⧗=0, ▶=1, ✔=66, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 16.87blocks/s, ⧗=0, ▶=0, ✔=66, ✗=0, ∅=0]" ] }, { @@ -12291,7 +12269,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 16.88blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 16.87blocks/s, ⧗=0, ▶=1, ✔=66, ✗=0, ∅=0]" ] }, { @@ -12313,7 +12291,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 17.39blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 16.87blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" ] }, { @@ -12335,7 +12313,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 17.39blocks/s, ⧗=0, ▶=1, ✔=67, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 16.73blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" ] }, { @@ -12357,7 +12335,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 17.39blocks/s, ⧗=0, ▶=0, ✔=68, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 16.73blocks/s, ⧗=0, ▶=1, ✔=67, ✗=0, ∅=0]" ] }, { @@ -12379,7 +12357,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 17.39blocks/s, ⧗=0, ▶=1, ✔=68, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 16.73blocks/s, ⧗=0, ▶=0, ✔=68, ✗=0, ∅=0]" ] }, { @@ -12401,7 +12379,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 17.39blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 16.73blocks/s, ⧗=0, ▶=1, ✔=68, ✗=0, ∅=0]" ] }, { @@ -12423,7 +12401,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.25blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 16.73blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" ] }, { @@ -12445,7 +12423,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.25blocks/s, ⧗=0, ▶=1, ✔=69, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 16.54blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" ] }, { @@ -12467,7 +12445,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.25blocks/s, ⧗=0, ▶=0, ✔=70, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 16.54blocks/s, ⧗=0, ▶=1, ✔=69, ✗=0, ∅=0]" ] }, { @@ -12489,7 +12467,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 17.25blocks/s, ⧗=0, ▶=1, ✔=70, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 16.54blocks/s, ⧗=0, ▶=0, ✔=70, ✗=0, ∅=0]" ] }, { @@ -12511,7 +12489,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 17.25blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 16.54blocks/s, ⧗=0, ▶=1, ✔=70, ✗=0, ∅=0]" ] }, { @@ -12533,7 +12511,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.32blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 16.54blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" ] }, { @@ -12555,7 +12533,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.32blocks/s, ⧗=0, ▶=1, ✔=71, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.07blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" ] }, { @@ -12577,7 +12555,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:04<00:08, 17.32blocks/s, ⧗=0, ▶=0, ✔=72, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.07blocks/s, ⧗=0, ▶=1, ✔=71, ✗=0, ∅=0]" ] }, { @@ -12599,7 +12577,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:04<00:08, 17.32blocks/s, ⧗=0, ▶=1, ✔=72, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:04<00:08, 17.07blocks/s, ⧗=0, ▶=0, ✔=72, ✗=0, ∅=0]" ] }, { @@ -12621,7 +12599,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:04<00:08, 17.32blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:04<00:08, 17.07blocks/s, ⧗=0, ▶=1, ✔=72, ✗=0, ∅=0]" ] }, { @@ -12643,7 +12621,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.87blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:04<00:08, 17.07blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" ] }, { @@ -12665,7 +12643,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.87blocks/s, ⧗=0, ▶=1, ✔=73, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.83blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" ] }, { @@ -12687,7 +12665,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.87blocks/s, ⧗=0, ▶=0, ✔=74, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.83blocks/s, ⧗=0, ▶=1, ✔=73, ✗=0, ∅=0]" ] }, { @@ -12709,7 +12687,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:04<00:07, 17.87blocks/s, ⧗=0, ▶=1, ✔=74, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.83blocks/s, ⧗=0, ▶=0, ✔=74, ✗=0, ∅=0]" ] }, { @@ -12731,7 +12709,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:04<00:07, 17.87blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:04<00:07, 17.83blocks/s, ⧗=0, ▶=1, ✔=74, ✗=0, ∅=0]" ] }, { @@ -12753,7 +12731,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 17.87blocks/s, ⧗=0, ▶=1, ✔=75, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:04<00:07, 17.83blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" ] }, { @@ -12775,7 +12753,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.38blocks/s, ⧗=0, ▶=1, ✔=75, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" ] }, { @@ -12797,7 +12775,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.38blocks/s, ⧗=0, ▶=0, ✔=76, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=1, ✔=75, ✗=0, ∅=0]" ] }, { @@ -12819,7 +12797,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:07, 18.38blocks/s, ⧗=0, ▶=1, ✔=76, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=0, ✔=76, ✗=0, ∅=0]" ] }, { @@ -12841,7 +12819,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:07, 18.38blocks/s, ⧗=0, ▶=0, ✔=77, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=1, ✔=76, ✗=0, ∅=0]" ] }, { @@ -12863,7 +12841,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:07, 18.38blocks/s, ⧗=0, ▶=1, ✔=77, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=0, ✔=77, ✗=0, ∅=0]" ] }, { @@ -12885,7 +12863,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:07, 18.38blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=1, ✔=77, ✗=0, ∅=0]" ] }, { @@ -12907,7 +12885,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 19.14blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:07, 18.42blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" ] }, { @@ -12929,7 +12907,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 19.14blocks/s, ⧗=0, ▶=1, ✔=78, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 18.36blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" ] }, { @@ -12951,7 +12929,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 19.14blocks/s, ⧗=0, ▶=0, ✔=79, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 18.36blocks/s, ⧗=0, ▶=1, ✔=78, ✗=0, ∅=0]" ] }, { @@ -12973,7 +12951,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 19.14blocks/s, ⧗=0, ▶=1, ✔=79, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 18.36blocks/s, ⧗=0, ▶=0, ✔=79, ✗=0, ∅=0]" ] }, { @@ -12995,7 +12973,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 19.14blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 18.36blocks/s, ⧗=0, ▶=1, ✔=79, ✗=0, ∅=0]" ] }, { @@ -13017,7 +12995,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 19.27blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 18.36blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" ] }, { @@ -13039,7 +13017,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 19.27blocks/s, ⧗=0, ▶=1, ✔=80, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.21blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" ] }, { @@ -13061,7 +13039,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 19.27blocks/s, ⧗=0, ▶=0, ✔=81, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.21blocks/s, ⧗=0, ▶=1, ✔=80, ✗=0, ∅=0]" ] }, { @@ -13083,7 +13061,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 19.27blocks/s, ⧗=0, ▶=1, ✔=81, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.21blocks/s, ⧗=0, ▶=0, ✔=81, ✗=0, ∅=0]" ] }, { @@ -13105,7 +13083,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 19.27blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.21blocks/s, ⧗=0, ▶=1, ✔=81, ✗=0, ∅=0]" ] }, { @@ -13127,7 +13105,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 19.00blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.21blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" ] }, { @@ -13149,7 +13127,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 19.00blocks/s, ⧗=0, ▶=1, ✔=82, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.40blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" ] }, { @@ -13171,7 +13149,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 19.00blocks/s, ⧗=0, ▶=0, ✔=83, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.40blocks/s, ⧗=0, ▶=1, ✔=82, ✗=0, ∅=0]" ] }, { @@ -13193,7 +13171,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:06, 19.00blocks/s, ⧗=0, ▶=1, ✔=83, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.40blocks/s, ⧗=0, ▶=0, ✔=83, ✗=0, ∅=0]" ] }, { @@ -13215,7 +13193,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:06, 19.00blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.40blocks/s, ⧗=0, ▶=1, ✔=83, ✗=0, ∅=0]" ] }, { @@ -13237,7 +13215,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:06, 19.06blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.40blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" ] }, { @@ -13259,7 +13237,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:06, 19.06blocks/s, ⧗=0, ▶=1, ✔=84, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:07, 18.44blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" ] }, { @@ -13281,7 +13259,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:06, 19.06blocks/s, ⧗=0, ▶=0, ✔=85, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:07, 18.44blocks/s, ⧗=0, ▶=1, ✔=84, ✗=0, ∅=0]" ] }, { @@ -13303,7 +13281,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:06, 19.06blocks/s, ⧗=0, ▶=1, ✔=85, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:07, 18.44blocks/s, ⧗=0, ▶=0, ✔=85, ✗=0, ∅=0]" ] }, { @@ -13325,7 +13303,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:06, 19.06blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:07, 18.44blocks/s, ⧗=0, ▶=1, ✔=85, ✗=0, ∅=0]" ] }, { @@ -13347,7 +13325,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:06, 18.64blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:07, 18.44blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" ] }, { @@ -13369,7 +13347,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:06, 18.64blocks/s, ⧗=0, ▶=1, ✔=86, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:07, 18.28blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" ] }, { @@ -13391,7 +13369,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:06, 18.64blocks/s, ⧗=0, ▶=0, ✔=87, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:07, 18.28blocks/s, ⧗=0, ▶=1, ✔=86, ✗=0, ∅=0]" ] }, { @@ -13413,7 +13391,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:06, 18.64blocks/s, ⧗=0, ▶=1, ✔=87, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:07, 18.28blocks/s, ⧗=0, ▶=0, ✔=87, ✗=0, ∅=0]" ] }, { @@ -13435,7 +13413,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:06, 18.64blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:07, 18.28blocks/s, ⧗=0, ▶=1, ✔=87, ✗=0, ∅=0]" ] }, { @@ -13457,7 +13435,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.07blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:07, 18.28blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" ] }, { @@ -13479,7 +13457,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.07blocks/s, ⧗=0, ▶=1, ✔=88, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.69blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" ] }, { @@ -13501,7 +13479,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.07blocks/s, ⧗=0, ▶=0, ✔=89, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.69blocks/s, ⧗=0, ▶=1, ✔=88, ✗=0, ∅=0]" ] }, { @@ -13523,7 +13501,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.07blocks/s, ⧗=0, ▶=1, ✔=89, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.69blocks/s, ⧗=0, ▶=0, ✔=89, ✗=0, ∅=0]" ] }, { @@ -13545,7 +13523,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 89/216 [00:05<00:07, 17.07blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.69blocks/s, ⧗=0, ▶=1, ✔=89, ✗=0, ∅=0]" ] }, { @@ -13567,7 +13545,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 16.61blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 41%|████ | 89/216 [00:05<00:07, 17.69blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" ] }, { @@ -13589,7 +13567,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 16.61blocks/s, ⧗=0, ▶=1, ✔=90, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 17.75blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" ] }, { @@ -13611,7 +13589,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 16.61blocks/s, ⧗=0, ▶=0, ✔=91, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 17.75blocks/s, ⧗=0, ▶=1, ✔=90, ✗=0, ∅=0]" ] }, { @@ -13633,7 +13611,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:05<00:07, 16.61blocks/s, ⧗=0, ▶=1, ✔=91, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 17.75blocks/s, ⧗=0, ▶=0, ✔=91, ✗=0, ∅=0]" ] }, { @@ -13655,7 +13633,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:05<00:07, 16.61blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:05<00:07, 17.75blocks/s, ⧗=0, ▶=1, ✔=91, ✗=0, ∅=0]" ] }, { @@ -13677,7 +13655,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:07, 17.42blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:05<00:07, 17.75blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" ] }, { @@ -13699,7 +13677,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:07, 17.42blocks/s, ⧗=0, ▶=1, ✔=92, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:06, 17.79blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" ] }, { @@ -13721,7 +13699,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:07, 17.42blocks/s, ⧗=0, ▶=0, ✔=93, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:06, 17.79blocks/s, ⧗=0, ▶=1, ✔=92, ✗=0, ∅=0]" ] }, { @@ -13743,7 +13721,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:05<00:07, 17.42blocks/s, ⧗=0, ▶=1, ✔=93, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:06, 17.79blocks/s, ⧗=0, ▶=0, ✔=93, ✗=0, ∅=0]" ] }, { @@ -13765,7 +13743,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:05<00:07, 17.42blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:05<00:06, 17.79blocks/s, ⧗=0, ▶=1, ✔=93, ✗=0, ∅=0]" ] }, { @@ -13787,7 +13765,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.69blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:05<00:06, 17.79blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" ] }, { @@ -13809,7 +13787,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.69blocks/s, ⧗=0, ▶=1, ✔=94, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.71blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" ] }, { @@ -13831,7 +13809,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.69blocks/s, ⧗=0, ▶=0, ✔=95, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.71blocks/s, ⧗=0, ▶=1, ✔=94, ✗=0, ∅=0]" ] }, { @@ -13853,7 +13831,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 17.69blocks/s, ⧗=0, ▶=1, ✔=95, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.71blocks/s, ⧗=0, ▶=0, ✔=95, ✗=0, ∅=0]" ] }, { @@ -13875,7 +13853,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 17.69blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 17.71blocks/s, ⧗=0, ▶=1, ✔=95, ✗=0, ∅=0]" ] }, { @@ -13897,7 +13875,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.17blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 17.71blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" ] }, { @@ -13919,7 +13897,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.17blocks/s, ⧗=0, ▶=1, ✔=96, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.33blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" ] }, { @@ -13941,7 +13919,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.17blocks/s, ⧗=0, ▶=0, ✔=97, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.33blocks/s, ⧗=0, ▶=1, ✔=96, ✗=0, ∅=0]" ] }, { @@ -13963,7 +13941,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.17blocks/s, ⧗=0, ▶=1, ✔=97, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.33blocks/s, ⧗=0, ▶=0, ✔=97, ✗=0, ∅=0]" ] }, { @@ -13985,7 +13963,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.17blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.33blocks/s, ⧗=0, ▶=1, ✔=97, ✗=0, ∅=0]" ] }, { @@ -14007,7 +13985,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.51blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.33blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" ] }, { @@ -14029,7 +14007,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.51blocks/s, ⧗=0, ▶=1, ✔=98, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.65blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" ] }, { @@ -14051,7 +14029,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.51blocks/s, ⧗=0, ▶=0, ✔=99, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.65blocks/s, ⧗=0, ▶=1, ✔=98, ✗=0, ∅=0]" ] }, { @@ -14073,7 +14051,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 18.51blocks/s, ⧗=0, ▶=1, ✔=99, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.65blocks/s, ⧗=0, ▶=0, ✔=99, ✗=0, ∅=0]" ] }, { @@ -14095,7 +14073,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 18.51blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 18.65blocks/s, ⧗=0, ▶=1, ✔=99, ✗=0, ∅=0]" ] }, { @@ -14117,7 +14095,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 18.03blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 18.65blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" ] }, { @@ -14139,7 +14117,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 18.03blocks/s, ⧗=0, ▶=1, ✔=100, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 17.99blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" ] }, { @@ -14161,7 +14139,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 18.03blocks/s, ⧗=0, ▶=0, ✔=101, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 17.99blocks/s, ⧗=0, ▶=1, ✔=100, ✗=0, ∅=0]" ] }, { @@ -14183,7 +14161,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 18.03blocks/s, ⧗=0, ▶=1, ✔=101, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 17.99blocks/s, ⧗=0, ▶=0, ✔=101, ✗=0, ∅=0]" ] }, { @@ -14205,7 +14183,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 18.03blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 17.99blocks/s, ⧗=0, ▶=1, ✔=101, ✗=0, ∅=0]" ] }, { @@ -14227,7 +14205,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 17.99blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" ] }, { @@ -14249,7 +14227,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=1, ✔=102, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 18.42blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" ] }, { @@ -14271,7 +14249,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=103, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 18.42blocks/s, ⧗=0, ▶=1, ✔=102, ✗=0, ∅=0]" ] }, { @@ -14293,7 +14271,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=1, ✔=103, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 18.42blocks/s, ⧗=0, ▶=0, ✔=103, ✗=0, ∅=0]" ] }, { @@ -14315,7 +14293,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:06, 18.42blocks/s, ⧗=0, ▶=1, ✔=103, ✗=0, ∅=0]" ] }, { @@ -14337,7 +14315,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:06, 18.60blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:06, 18.42blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" ] }, { @@ -14359,7 +14337,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:06, 18.60blocks/s, ⧗=0, ▶=1, ✔=104, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:05, 18.76blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" ] }, { @@ -14381,7 +14359,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:06, 18.60blocks/s, ⧗=0, ▶=0, ✔=105, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:05, 18.76blocks/s, ⧗=0, ▶=1, ✔=104, ✗=0, ∅=0]" ] }, { @@ -14403,7 +14381,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 18.60blocks/s, ⧗=0, ▶=1, ✔=105, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:05, 18.76blocks/s, ⧗=0, ▶=0, ✔=105, ✗=0, ∅=0]" ] }, { @@ -14425,7 +14403,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 18.60blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 18.76blocks/s, ⧗=0, ▶=1, ✔=105, ✗=0, ∅=0]" ] }, { @@ -14447,7 +14425,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 18.49blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 18.76blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" ] }, { @@ -14469,7 +14447,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 18.49blocks/s, ⧗=0, ▶=1, ✔=106, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 18.84blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" ] }, { @@ -14491,7 +14469,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 18.49blocks/s, ⧗=0, ▶=0, ✔=107, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 18.84blocks/s, ⧗=0, ▶=1, ✔=106, ✗=0, ∅=0]" ] }, { @@ -14513,7 +14491,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:05, 18.49blocks/s, ⧗=0, ▶=1, ✔=107, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 18.84blocks/s, ⧗=0, ▶=0, ✔=107, ✗=0, ∅=0]" ] }, { @@ -14535,7 +14513,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:06<00:05, 18.49blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:05, 18.84blocks/s, ⧗=0, ▶=1, ✔=107, ✗=0, ∅=0]" ] }, { @@ -14557,7 +14535,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 108/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:05, 18.84blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" ] }, { @@ -14579,7 +14557,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 108/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=1, ✔=108, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:05, 18.84blocks/s, ⧗=0, ▶=1, ✔=108, ✗=0, ∅=0]" ] }, { @@ -14601,7 +14579,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 108/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=109, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:05, 19.13blocks/s, ⧗=0, ▶=1, ✔=108, ✗=0, ∅=0]" ] }, { @@ -14623,7 +14601,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 109/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=1, ✔=109, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 108/216 [00:06<00:05, 19.13blocks/s, ⧗=0, ▶=0, ✔=109, ✗=0, ∅=0]" ] }, { @@ -14645,7 +14623,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 109/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=110, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 109/216 [00:06<00:05, 19.13blocks/s, ⧗=0, ▶=1, ✔=109, ✗=0, ∅=0]" ] }, { @@ -14667,7 +14645,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=1, ✔=110, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 50%|█████ | 109/216 [00:06<00:05, 19.13blocks/s, ⧗=0, ▶=0, ✔=110, ✗=0, ∅=0]" ] }, { @@ -14689,7 +14667,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:05, 19.13blocks/s, ⧗=0, ▶=1, ✔=110, ✗=0, ∅=0]" ] }, { @@ -14711,7 +14689,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:05, 19.13blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" ] }, { @@ -14733,7 +14711,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=1, ✔=111, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" ] }, { @@ -14755,7 +14733,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=0, ✔=112, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=1, ✔=111, ✗=0, ∅=0]" ] }, { @@ -14777,7 +14755,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=1, ✔=112, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=0, ✔=112, ✗=0, ∅=0]" ] }, { @@ -14799,7 +14777,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=0, ✔=113, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=1, ✔=112, ✗=0, ∅=0]" ] }, { @@ -14821,7 +14799,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=0, ✔=113, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=0, ✔=113, ✗=0, ∅=0]" ] }, { @@ -14843,7 +14821,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=1, ✔=113, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=1, ✔=113, ✗=0, ∅=0]" ] }, { @@ -14865,7 +14843,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 20.21blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" ] }, { @@ -14887,7 +14865,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=1, ✔=114, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 19.63blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" ] }, { @@ -14909,7 +14887,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 19.49blocks/s, ⧗=0, ▶=0, ✔=115, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 19.63blocks/s, ⧗=0, ▶=1, ✔=114, ✗=0, ∅=0]" ] }, { @@ -14931,7 +14909,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 19.33blocks/s, ⧗=0, ▶=0, ✔=115, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 19.63blocks/s, ⧗=0, ▶=0, ✔=115, ✗=0, ∅=0]" ] }, { @@ -14953,7 +14931,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 19.33blocks/s, ⧗=0, ▶=1, ✔=115, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 19.63blocks/s, ⧗=0, ▶=1, ✔=115, ✗=0, ∅=0]" ] }, { @@ -14975,7 +14953,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 19.33blocks/s, ⧗=0, ▶=0, ✔=116, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 19.63blocks/s, ⧗=0, ▶=0, ✔=116, ✗=0, ∅=0]" ] }, { @@ -14997,7 +14975,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 19.33blocks/s, ⧗=0, ▶=1, ✔=116, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=116, ✗=0, ∅=0]" ] }, { @@ -15019,7 +14997,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 19.33blocks/s, ⧗=0, ▶=0, ✔=117, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=1, ✔=116, ✗=0, ∅=0]" ] }, { @@ -15041,7 +15019,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 19.07blocks/s, ⧗=0, ▶=0, ✔=117, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=117, ✗=0, ∅=0]" ] }, { @@ -15063,7 +15041,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 19.07blocks/s, ⧗=0, ▶=1, ✔=117, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=1, ✔=117, ✗=0, ∅=0]" ] }, { @@ -15085,7 +15063,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 19.07blocks/s, ⧗=0, ▶=0, ✔=118, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 18.54blocks/s, ⧗=0, ▶=0, ✔=118, ✗=0, ∅=0]" ] }, { @@ -15107,7 +15085,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 19.07blocks/s, ⧗=0, ▶=1, ✔=118, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 18.59blocks/s, ⧗=0, ▶=0, ✔=118, ✗=0, ∅=0]" ] }, { @@ -15129,7 +15107,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 19.07blocks/s, ⧗=0, ▶=0, ✔=119, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 18.59blocks/s, ⧗=0, ▶=1, ✔=118, ✗=0, ∅=0]" ] }, { @@ -15151,7 +15129,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 19.26blocks/s, ⧗=0, ▶=0, ✔=119, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 18.59blocks/s, ⧗=0, ▶=0, ✔=119, ✗=0, ∅=0]" ] }, { @@ -15173,7 +15151,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 19.26blocks/s, ⧗=0, ▶=1, ✔=119, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 18.59blocks/s, ⧗=0, ▶=1, ✔=119, ✗=0, ∅=0]" ] }, { @@ -15195,7 +15173,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 19.26blocks/s, ⧗=0, ▶=0, ✔=120, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 18.59blocks/s, ⧗=0, ▶=0, ✔=120, ✗=0, ∅=0]" ] }, { @@ -15217,7 +15195,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:04, 19.26blocks/s, ⧗=0, ▶=1, ✔=120, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:05, 18.59blocks/s, ⧗=0, ▶=1, ✔=120, ✗=0, ∅=0]" ] }, { @@ -15239,7 +15217,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:04, 19.26blocks/s, ⧗=0, ▶=0, ✔=121, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:05, 18.93blocks/s, ⧗=0, ▶=1, ✔=120, ✗=0, ∅=0]" ] }, { @@ -15261,7 +15239,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:04, 19.33blocks/s, ⧗=0, ▶=0, ✔=121, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:05, 18.93blocks/s, ⧗=0, ▶=0, ✔=121, ✗=0, ∅=0]" ] }, { @@ -15283,7 +15261,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:04, 19.33blocks/s, ⧗=0, ▶=1, ✔=121, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:05, 18.93blocks/s, ⧗=0, ▶=1, ✔=121, ✗=0, ∅=0]" ] }, { @@ -15305,7 +15283,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:04, 19.33blocks/s, ⧗=0, ▶=0, ✔=122, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:05, 18.93blocks/s, ⧗=0, ▶=0, ✔=122, ✗=0, ∅=0]" ] }, { @@ -15327,7 +15305,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 19.33blocks/s, ⧗=0, ▶=1, ✔=122, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 18.93blocks/s, ⧗=0, ▶=1, ✔=122, ✗=0, ∅=0]" ] }, { @@ -15349,7 +15327,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 19.33blocks/s, ⧗=0, ▶=0, ✔=123, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 19.09blocks/s, ⧗=0, ▶=1, ✔=122, ✗=0, ∅=0]" ] }, { @@ -15371,7 +15349,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 18.71blocks/s, ⧗=0, ▶=0, ✔=123, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 19.09blocks/s, ⧗=0, ▶=0, ✔=123, ✗=0, ∅=0]" ] }, { @@ -15393,7 +15371,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 18.71blocks/s, ⧗=0, ▶=1, ✔=123, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 19.09blocks/s, ⧗=0, ▶=1, ✔=123, ✗=0, ∅=0]" ] }, { @@ -15415,7 +15393,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 18.71blocks/s, ⧗=0, ▶=0, ✔=124, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 19.09blocks/s, ⧗=0, ▶=0, ✔=124, ✗=0, ∅=0]" ] }, { @@ -15437,7 +15415,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:04, 18.71blocks/s, ⧗=0, ▶=1, ✔=124, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:05, 18.14blocks/s, ⧗=0, ▶=0, ✔=124, ✗=0, ∅=0]" ] }, { @@ -15459,7 +15437,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:04, 18.71blocks/s, ⧗=0, ▶=0, ✔=125, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:05, 18.14blocks/s, ⧗=0, ▶=1, ✔=124, ✗=0, ∅=0]" ] }, { @@ -15481,7 +15459,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=0, ✔=125, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:05, 18.14blocks/s, ⧗=0, ▶=0, ✔=125, ✗=0, ∅=0]" ] }, { @@ -15503,7 +15481,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=1, ✔=125, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 18.14blocks/s, ⧗=0, ▶=1, ✔=125, ✗=0, ∅=0]" ] }, { @@ -15525,7 +15503,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=0, ✔=126, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 18.14blocks/s, ⧗=0, ▶=0, ✔=126, ✗=0, ∅=0]" ] }, { @@ -15547,7 +15525,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=1, ✔=126, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:05, 17.62blocks/s, ⧗=0, ▶=0, ✔=126, ✗=0, ∅=0]" ] }, { @@ -15569,7 +15547,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:07<00:05, 17.64blocks/s, ⧗=0, ▶=0, ✔=127, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:05, 17.62blocks/s, ⧗=0, ▶=1, ✔=126, ✗=0, ∅=0]" ] }, { @@ -15591,7 +15569,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:04, 18.02blocks/s, ⧗=0, ▶=0, ✔=127, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:07<00:05, 17.62blocks/s, ⧗=0, ▶=0, ✔=127, ✗=0, ∅=0]" ] }, { @@ -15613,7 +15591,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:04, 18.02blocks/s, ⧗=0, ▶=1, ✔=127, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:05, 17.62blocks/s, ⧗=0, ▶=1, ✔=127, ✗=0, ∅=0]" ] }, { @@ -15635,7 +15613,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:04, 18.02blocks/s, ⧗=0, ▶=0, ✔=128, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:05, 17.62blocks/s, ⧗=0, ▶=0, ✔=128, ✗=0, ∅=0]" ] }, { @@ -15657,7 +15635,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:07<00:04, 18.02blocks/s, ⧗=0, ▶=1, ✔=128, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:07<00:04, 17.62blocks/s, ⧗=0, ▶=1, ✔=128, ✗=0, ∅=0]" ] }, { @@ -15679,7 +15657,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:07<00:04, 18.02blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:07<00:04, 17.62blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" ] }, { @@ -15701,7 +15679,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 17.63blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 18.71blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" ] }, { @@ -15723,7 +15701,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 17.63blocks/s, ⧗=0, ▶=1, ✔=129, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 18.71blocks/s, ⧗=0, ▶=1, ✔=129, ✗=0, ∅=0]" ] }, { @@ -15745,7 +15723,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 17.63blocks/s, ⧗=0, ▶=0, ✔=130, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 18.71blocks/s, ⧗=0, ▶=0, ✔=130, ✗=0, ∅=0]" ] }, { @@ -15767,7 +15745,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|██████ | 130/216 [00:07<00:04, 17.63blocks/s, ⧗=0, ▶=1, ✔=130, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|██████ | 130/216 [00:07<00:04, 18.71blocks/s, ⧗=0, ▶=1, ✔=130, ✗=0, ∅=0]" ] }, { @@ -15789,7 +15767,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|██████ | 130/216 [00:07<00:04, 17.63blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 60%|██████ | 130/216 [00:07<00:04, 18.71blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" ] }, { @@ -15811,7 +15789,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.17blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.71blocks/s, ⧗=0, ▶=1, ✔=131, ✗=0, ∅=0]" ] }, { @@ -15833,7 +15811,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.17blocks/s, ⧗=0, ▶=1, ✔=131, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 19.03blocks/s, ⧗=0, ▶=1, ✔=131, ✗=0, ∅=0]" ] }, { @@ -15855,7 +15833,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.17blocks/s, ⧗=0, ▶=0, ✔=132, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 19.03blocks/s, ⧗=0, ▶=0, ✔=132, ✗=0, ∅=0]" ] }, { @@ -15877,7 +15855,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 132/216 [00:07<00:04, 18.17blocks/s, ⧗=0, ▶=1, ✔=132, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 132/216 [00:07<00:04, 19.03blocks/s, ⧗=0, ▶=1, ✔=132, ✗=0, ∅=0]" ] }, { @@ -15899,7 +15877,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 132/216 [00:07<00:04, 18.17blocks/s, ⧗=0, ▶=0, ✔=133, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 61%|██████ | 132/216 [00:07<00:04, 19.03blocks/s, ⧗=0, ▶=0, ✔=133, ✗=0, ∅=0]" ] }, { @@ -15921,7 +15899,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 18.17blocks/s, ⧗=0, ▶=1, ✔=133, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 19.12blocks/s, ⧗=0, ▶=0, ✔=133, ✗=0, ∅=0]" ] }, { @@ -15943,7 +15921,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=133, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 19.12blocks/s, ⧗=0, ▶=1, ✔=133, ✗=0, ∅=0]" ] }, { @@ -15965,7 +15943,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=134, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 19.12blocks/s, ⧗=0, ▶=0, ✔=134, ✗=0, ∅=0]" ] }, { @@ -15987,7 +15965,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=134, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 19.12blocks/s, ⧗=0, ▶=1, ✔=134, ✗=0, ∅=0]" ] }, { @@ -16009,7 +15987,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=135, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 19.12blocks/s, ⧗=0, ▶=0, ✔=135, ✗=0, ∅=0]" ] }, { @@ -16031,7 +16009,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 18.72blocks/s, ⧗=0, ▶=0, ✔=135, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=135, ✗=0, ∅=0]" ] }, { @@ -16053,7 +16031,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 18.72blocks/s, ⧗=0, ▶=1, ✔=135, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=135, ✗=0, ∅=0]" ] }, { @@ -16075,7 +16053,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 18.72blocks/s, ⧗=0, ▶=0, ✔=136, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=136, ✗=0, ∅=0]" ] }, { @@ -16097,7 +16075,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 18.72blocks/s, ⧗=0, ▶=1, ✔=136, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=136, ✗=0, ∅=0]" ] }, { @@ -16119,7 +16097,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 18.72blocks/s, ⧗=0, ▶=0, ✔=137, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=137, ✗=0, ∅=0]" ] }, { @@ -16141,7 +16119,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.89blocks/s, ⧗=0, ▶=0, ✔=137, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=137, ✗=0, ∅=0]" ] }, { @@ -16163,7 +16141,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.89blocks/s, ⧗=0, ▶=1, ✔=137, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.99blocks/s, ⧗=0, ▶=1, ✔=137, ✗=0, ∅=0]" ] }, { @@ -16185,7 +16163,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.89blocks/s, ⧗=0, ▶=0, ✔=138, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.99blocks/s, ⧗=0, ▶=0, ✔=138, ✗=0, ∅=0]" ] }, { @@ -16207,7 +16185,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 18.89blocks/s, ⧗=0, ▶=1, ✔=138, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 18.99blocks/s, ⧗=0, ▶=1, ✔=138, ✗=0, ∅=0]" ] }, { @@ -16229,7 +16207,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 18.89blocks/s, ⧗=0, ▶=0, ✔=139, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 18.99blocks/s, ⧗=0, ▶=0, ✔=139, ✗=0, ∅=0]" ] }, { @@ -16251,7 +16229,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 18.89blocks/s, ⧗=0, ▶=1, ✔=139, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 18.99blocks/s, ⧗=0, ▶=1, ✔=139, ✗=0, ∅=0]" ] }, { @@ -16273,7 +16251,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 19.20blocks/s, ⧗=0, ▶=1, ✔=139, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:03, 19.27blocks/s, ⧗=0, ▶=1, ✔=139, ✗=0, ∅=0]" ] }, { @@ -16295,7 +16273,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 19.20blocks/s, ⧗=0, ▶=0, ✔=140, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:03, 19.27blocks/s, ⧗=0, ▶=0, ✔=140, ✗=0, ∅=0]" ] }, { @@ -16317,7 +16295,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=1, ✔=140, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:03, 19.27blocks/s, ⧗=0, ▶=1, ✔=140, ✗=0, ∅=0]" ] }, { @@ -16339,7 +16317,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:03, 19.27blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" ] }, { @@ -16361,7 +16339,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 18.86blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.41blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" ] }, { @@ -16383,7 +16361,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 18.86blocks/s, ⧗=0, ▶=1, ✔=141, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.41blocks/s, ⧗=0, ▶=1, ✔=141, ✗=0, ∅=0]" ] }, { @@ -16405,7 +16383,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 18.86blocks/s, ⧗=0, ▶=0, ✔=142, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.41blocks/s, ⧗=0, ▶=0, ✔=142, ✗=0, ∅=0]" ] }, { @@ -16427,7 +16405,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 18.86blocks/s, ⧗=0, ▶=1, ✔=142, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 19.41blocks/s, ⧗=0, ▶=1, ✔=142, ✗=0, ∅=0]" ] }, { @@ -16449,7 +16427,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 18.86blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 19.41blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" ] }, { @@ -16471,7 +16449,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.10blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" ] }, { @@ -16493,7 +16471,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.10blocks/s, ⧗=0, ▶=1, ✔=143, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=1, ✔=143, ✗=0, ∅=0]" ] }, { @@ -16515,7 +16493,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.10blocks/s, ⧗=0, ▶=0, ✔=144, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=0, ✔=144, ✗=0, ∅=0]" ] }, { @@ -16537,7 +16515,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.10blocks/s, ⧗=0, ▶=1, ✔=144, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=1, ✔=144, ✗=0, ∅=0]" ] }, { @@ -16559,7 +16537,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.10blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.20blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" ] }, { @@ -16581,7 +16559,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 18.52blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.33blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" ] }, { @@ -16603,7 +16581,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 18.52blocks/s, ⧗=0, ▶=1, ✔=145, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.33blocks/s, ⧗=0, ▶=1, ✔=145, ✗=0, ∅=0]" ] }, { @@ -16625,7 +16603,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:08<00:03, 18.52blocks/s, ⧗=0, ▶=0, ✔=146, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.33blocks/s, ⧗=0, ▶=0, ✔=146, ✗=0, ∅=0]" ] }, { @@ -16647,7 +16625,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:08<00:03, 18.52blocks/s, ⧗=0, ▶=1, ✔=146, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:07<00:03, 19.33blocks/s, ⧗=0, ▶=1, ✔=146, ✗=0, ∅=0]" ] }, { @@ -16669,7 +16647,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:08<00:03, 18.52blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:08<00:03, 19.33blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" ] }, { @@ -16691,7 +16669,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 17.30blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 18.75blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" ] }, { @@ -16713,7 +16691,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 17.30blocks/s, ⧗=0, ▶=1, ✔=147, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 18.75blocks/s, ⧗=0, ▶=1, ✔=147, ✗=0, ∅=0]" ] }, { @@ -16735,7 +16713,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 17.30blocks/s, ⧗=0, ▶=0, ✔=148, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 18.75blocks/s, ⧗=0, ▶=0, ✔=148, ✗=0, ∅=0]" ] }, { @@ -16757,7 +16735,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:08<00:03, 17.30blocks/s, ⧗=0, ▶=1, ✔=148, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:08<00:03, 18.75blocks/s, ⧗=0, ▶=1, ✔=148, ✗=0, ∅=0]" ] }, { @@ -16779,7 +16757,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:08<00:03, 17.30blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:08<00:03, 18.75blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" ] }, { @@ -16801,7 +16779,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 17.66blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 18.80blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" ] }, { @@ -16823,7 +16801,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 17.66blocks/s, ⧗=0, ▶=1, ✔=149, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 18.80blocks/s, ⧗=0, ▶=1, ✔=149, ✗=0, ∅=0]" ] }, { @@ -16845,7 +16823,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 17.66blocks/s, ⧗=0, ▶=0, ✔=150, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 18.80blocks/s, ⧗=0, ▶=0, ✔=150, ✗=0, ∅=0]" ] }, { @@ -16867,7 +16845,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:08<00:03, 17.66blocks/s, ⧗=0, ▶=1, ✔=150, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:08<00:03, 18.80blocks/s, ⧗=0, ▶=1, ✔=150, ✗=0, ∅=0]" ] }, { @@ -16889,7 +16867,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:08<00:03, 17.66blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:08<00:03, 18.80blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" ] }, { @@ -16911,7 +16889,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 17.91blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 18.88blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" ] }, { @@ -16933,7 +16911,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 17.91blocks/s, ⧗=0, ▶=1, ✔=151, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 18.88blocks/s, ⧗=0, ▶=1, ✔=151, ✗=0, ∅=0]" ] }, { @@ -16955,7 +16933,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 17.91blocks/s, ⧗=0, ▶=0, ✔=152, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 18.88blocks/s, ⧗=0, ▶=0, ✔=152, ✗=0, ∅=0]" ] }, { @@ -16977,7 +16955,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 17.91blocks/s, ⧗=0, ▶=1, ✔=152, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 18.88blocks/s, ⧗=0, ▶=1, ✔=152, ✗=0, ∅=0]" ] }, { @@ -16999,7 +16977,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 17.91blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 18.88blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" ] }, { @@ -17021,7 +16999,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 17.51blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 18.34blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" ] }, { @@ -17043,7 +17021,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 17.51blocks/s, ⧗=0, ▶=1, ✔=153, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 18.34blocks/s, ⧗=0, ▶=1, ✔=153, ✗=0, ∅=0]" ] }, { @@ -17065,7 +17043,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 17.51blocks/s, ⧗=0, ▶=0, ✔=154, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 18.34blocks/s, ⧗=0, ▶=0, ✔=154, ✗=0, ∅=0]" ] }, { @@ -17087,7 +17065,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.51blocks/s, ⧗=0, ▶=1, ✔=154, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 18.34blocks/s, ⧗=0, ▶=1, ✔=154, ✗=0, ∅=0]" ] }, { @@ -17109,7 +17087,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.51blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 18.34blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" ] }, { @@ -17131,7 +17109,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.67blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 18.13blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" ] }, { @@ -17153,7 +17131,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.67blocks/s, ⧗=0, ▶=1, ✔=155, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 18.13blocks/s, ⧗=0, ▶=1, ✔=155, ✗=0, ∅=0]" ] }, { @@ -17175,7 +17153,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.67blocks/s, ⧗=0, ▶=0, ✔=156, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 18.13blocks/s, ⧗=0, ▶=0, ✔=156, ✗=0, ∅=0]" ] }, { @@ -17197,7 +17175,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.67blocks/s, ⧗=0, ▶=1, ✔=156, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 18.13blocks/s, ⧗=0, ▶=1, ✔=156, ✗=0, ∅=0]" ] }, { @@ -17219,7 +17197,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.67blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 18.13blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" ] }, { @@ -17241,7 +17219,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.31blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.53blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" ] }, { @@ -17263,7 +17241,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.31blocks/s, ⧗=0, ▶=1, ✔=157, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.53blocks/s, ⧗=0, ▶=1, ✔=157, ✗=0, ∅=0]" ] }, { @@ -17285,7 +17263,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.31blocks/s, ⧗=0, ▶=0, ✔=158, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.53blocks/s, ⧗=0, ▶=0, ✔=158, ✗=0, ∅=0]" ] }, { @@ -17307,7 +17285,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 17.31blocks/s, ⧗=0, ▶=1, ✔=158, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 17.53blocks/s, ⧗=0, ▶=1, ✔=158, ✗=0, ∅=0]" ] }, { @@ -17329,7 +17307,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 17.31blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 17.53blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" ] }, { @@ -17351,7 +17329,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.03blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.23blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" ] }, { @@ -17373,7 +17351,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.03blocks/s, ⧗=0, ▶=1, ✔=159, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.23blocks/s, ⧗=0, ▶=1, ✔=159, ✗=0, ∅=0]" ] }, { @@ -17395,7 +17373,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.03blocks/s, ⧗=0, ▶=0, ✔=160, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.23blocks/s, ⧗=0, ▶=0, ✔=160, ✗=0, ∅=0]" ] }, { @@ -17417,7 +17395,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.03blocks/s, ⧗=0, ▶=1, ✔=160, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.23blocks/s, ⧗=0, ▶=1, ✔=160, ✗=0, ∅=0]" ] }, { @@ -17439,7 +17417,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.03blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.23blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" ] }, { @@ -17461,7 +17439,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 15.31blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 16.25blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" ] }, { @@ -17483,7 +17461,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 15.31blocks/s, ⧗=0, ▶=1, ✔=161, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 16.25blocks/s, ⧗=0, ▶=1, ✔=161, ✗=0, ∅=0]" ] }, { @@ -17505,7 +17483,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:09<00:03, 15.31blocks/s, ⧗=0, ▶=0, ✔=162, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 16.25blocks/s, ⧗=0, ▶=0, ✔=162, ✗=0, ∅=0]" ] }, { @@ -17527,7 +17505,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:09<00:03, 15.31blocks/s, ⧗=0, ▶=1, ✔=162, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:08<00:03, 16.25blocks/s, ⧗=0, ▶=1, ✔=162, ✗=0, ∅=0]" ] }, { @@ -17549,7 +17527,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:09<00:03, 15.31blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:08<00:03, 16.25blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" ] }, { @@ -17571,7 +17549,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 15.67blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:08<00:03, 16.72blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" ] }, { @@ -17593,7 +17571,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 15.67blocks/s, ⧗=0, ▶=1, ✔=163, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:08<00:03, 16.72blocks/s, ⧗=0, ▶=1, ✔=163, ✗=0, ∅=0]" ] }, { @@ -17615,7 +17593,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 15.67blocks/s, ⧗=0, ▶=0, ✔=164, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 16.72blocks/s, ⧗=0, ▶=0, ✔=164, ✗=0, ∅=0]" ] }, { @@ -17637,7 +17615,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:09<00:03, 15.67blocks/s, ⧗=0, ▶=1, ✔=164, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:09<00:03, 16.72blocks/s, ⧗=0, ▶=1, ✔=164, ✗=0, ∅=0]" ] }, { @@ -17659,7 +17637,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:09<00:03, 15.67blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:09<00:03, 16.72blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" ] }, { @@ -17681,7 +17659,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:02, 17.05blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" ] }, { @@ -17703,7 +17681,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=1, ✔=165, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:02, 17.05blocks/s, ⧗=0, ▶=1, ✔=165, ✗=0, ∅=0]" ] }, { @@ -17725,7 +17703,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=0, ✔=166, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:02, 17.05blocks/s, ⧗=0, ▶=0, ✔=166, ✗=0, ∅=0]" ] }, { @@ -17747,7 +17725,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=1, ✔=166, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:09<00:02, 17.05blocks/s, ⧗=0, ▶=1, ✔=166, ✗=0, ∅=0]" ] }, { @@ -17769,7 +17747,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:09<00:02, 17.05blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" ] }, { @@ -17791,7 +17769,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:02, 17.50blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" ] }, { @@ -17813,7 +17791,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=1, ✔=167, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:02, 17.50blocks/s, ⧗=0, ▶=1, ✔=167, ✗=0, ∅=0]" ] }, { @@ -17835,7 +17813,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=0, ✔=168, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:02, 17.50blocks/s, ⧗=0, ▶=0, ✔=168, ✗=0, ∅=0]" ] }, { @@ -17857,7 +17835,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=1, ✔=168, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 17.50blocks/s, ⧗=0, ▶=1, ✔=168, ✗=0, ∅=0]" ] }, { @@ -17879,7 +17857,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 17.50blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" ] }, { @@ -17901,7 +17879,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 16.96blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 17.96blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" ] }, { @@ -17923,7 +17901,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 16.96blocks/s, ⧗=0, ▶=1, ✔=169, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 17.96blocks/s, ⧗=0, ▶=1, ✔=169, ✗=0, ∅=0]" ] }, { @@ -17945,7 +17923,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 16.96blocks/s, ⧗=0, ▶=0, ✔=170, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 17.96blocks/s, ⧗=0, ▶=0, ✔=170, ✗=0, ∅=0]" ] }, { @@ -17967,7 +17945,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 16.96blocks/s, ⧗=0, ▶=1, ✔=170, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 17.96blocks/s, ⧗=0, ▶=1, ✔=170, ✗=0, ∅=0]" ] }, { @@ -17989,7 +17967,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 16.96blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 17.96blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" ] }, { @@ -18011,7 +17989,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 16.66blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 17.76blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" ] }, { @@ -18033,7 +18011,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 16.66blocks/s, ⧗=0, ▶=1, ✔=171, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 17.76blocks/s, ⧗=0, ▶=1, ✔=171, ✗=0, ∅=0]" ] }, { @@ -18055,7 +18033,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 16.66blocks/s, ⧗=0, ▶=0, ✔=172, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 17.76blocks/s, ⧗=0, ▶=0, ✔=172, ✗=0, ∅=0]" ] }, { @@ -18077,7 +18055,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.66blocks/s, ⧗=0, ▶=1, ✔=172, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 17.76blocks/s, ⧗=0, ▶=1, ✔=172, ✗=0, ∅=0]" ] }, { @@ -18099,7 +18077,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.66blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 17.76blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" ] }, { @@ -18121,7 +18099,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 17.91blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" ] }, { @@ -18143,7 +18121,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=1, ✔=173, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 17.91blocks/s, ⧗=0, ▶=1, ✔=173, ✗=0, ∅=0]" ] }, { @@ -18165,7 +18143,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=0, ✔=174, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 17.91blocks/s, ⧗=0, ▶=0, ✔=174, ✗=0, ∅=0]" ] }, { @@ -18187,7 +18165,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=1, ✔=174, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 17.91blocks/s, ⧗=0, ▶=1, ✔=174, ✗=0, ∅=0]" ] }, { @@ -18209,7 +18187,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 17.91blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" ] }, { @@ -18231,7 +18209,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 17.25blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 18.29blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" ] }, { @@ -18253,7 +18231,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 17.25blocks/s, ⧗=0, ▶=1, ✔=175, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 18.29blocks/s, ⧗=0, ▶=1, ✔=175, ✗=0, ∅=0]" ] }, { @@ -18275,7 +18253,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 17.25blocks/s, ⧗=0, ▶=0, ✔=176, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 18.29blocks/s, ⧗=0, ▶=0, ✔=176, ✗=0, ∅=0]" ] }, { @@ -18297,7 +18275,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 17.25blocks/s, ⧗=0, ▶=1, ✔=176, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 18.29blocks/s, ⧗=0, ▶=1, ✔=176, ✗=0, ∅=0]" ] }, { @@ -18319,7 +18297,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 17.25blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 18.29blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" ] }, { @@ -18341,7 +18319,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 17.85blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" ] }, { @@ -18363,7 +18341,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=1, ✔=177, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 17.85blocks/s, ⧗=0, ▶=1, ✔=177, ✗=0, ∅=0]" ] }, { @@ -18385,7 +18363,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=0, ✔=178, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 17.85blocks/s, ⧗=0, ▶=0, ✔=178, ✗=0, ∅=0]" ] }, { @@ -18407,7 +18385,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 16.93blocks/s, ⧗=0, ▶=1, ✔=178, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 17.85blocks/s, ⧗=0, ▶=1, ✔=178, ✗=0, ∅=0]" ] }, { @@ -18429,7 +18407,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:10<00:02, 16.93blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 17.85blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" ] }, { @@ -18451,7 +18429,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:10<00:02, 17.26blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:09<00:02, 18.05blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" ] }, { @@ -18473,7 +18451,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:10<00:02, 17.26blocks/s, ⧗=0, ▶=1, ✔=179, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:09<00:02, 18.05blocks/s, ⧗=0, ▶=1, ✔=179, ✗=0, ∅=0]" ] }, { @@ -18495,7 +18473,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:10<00:02, 17.26blocks/s, ⧗=0, ▶=0, ✔=180, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:09<00:02, 18.05blocks/s, ⧗=0, ▶=0, ✔=180, ✗=0, ∅=0]" ] }, { @@ -18517,7 +18495,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:10<00:02, 17.26blocks/s, ⧗=0, ▶=1, ✔=180, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:09<00:01, 18.05blocks/s, ⧗=0, ▶=1, ✔=180, ✗=0, ∅=0]" ] }, { @@ -18539,7 +18517,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:10<00:02, 17.26blocks/s, ⧗=0, ▶=0, ✔=181, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:09<00:01, 18.05blocks/s, ⧗=0, ▶=0, ✔=181, ✗=0, ∅=0]" ] }, { @@ -18561,7 +18539,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:01, 17.86blocks/s, ⧗=0, ▶=0, ✔=181, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:09<00:01, 18.05blocks/s, ⧗=0, ▶=1, ✔=181, ✗=0, ∅=0]" ] }, { @@ -18583,7 +18561,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:01, 17.86blocks/s, ⧗=0, ▶=1, ✔=181, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:01, 18.05blocks/s, ⧗=0, ▶=0, ✔=182, ✗=0, ∅=0]" ] }, { @@ -18605,7 +18583,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:01, 17.86blocks/s, ⧗=0, ▶=0, ✔=182, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:01, 19.02blocks/s, ⧗=0, ▶=0, ✔=182, ✗=0, ∅=0]" ] }, { @@ -18627,7 +18605,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:01, 17.86blocks/s, ⧗=0, ▶=1, ✔=182, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:01, 19.02blocks/s, ⧗=0, ▶=1, ✔=182, ✗=0, ∅=0]" ] }, { @@ -18649,7 +18627,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:01, 17.86blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:01, 19.02blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" ] }, { @@ -18671,7 +18649,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 18.31blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 19.02blocks/s, ⧗=0, ▶=1, ✔=183, ✗=0, ∅=0]" ] }, { @@ -18693,7 +18671,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 18.31blocks/s, ⧗=0, ▶=1, ✔=183, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 19.02blocks/s, ⧗=0, ▶=0, ✔=184, ✗=0, ∅=0]" ] }, { @@ -18715,7 +18693,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 18.31blocks/s, ⧗=0, ▶=0, ✔=184, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 17.91blocks/s, ⧗=0, ▶=0, ✔=184, ✗=0, ∅=0]" ] }, { @@ -18737,7 +18715,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 18.31blocks/s, ⧗=0, ▶=1, ✔=184, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 17.91blocks/s, ⧗=0, ▶=1, ✔=184, ✗=0, ∅=0]" ] }, { @@ -18759,7 +18737,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 18.31blocks/s, ⧗=0, ▶=0, ✔=185, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 17.91blocks/s, ⧗=0, ▶=0, ✔=185, ✗=0, ∅=0]" ] }, { @@ -18781,7 +18759,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=185, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 17.91blocks/s, ⧗=0, ▶=1, ✔=185, ✗=0, ∅=0]" ] }, { @@ -18803,7 +18781,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=1, ✔=185, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 17.91blocks/s, ⧗=0, ▶=0, ✔=186, ✗=0, ∅=0]" ] }, { @@ -18825,7 +18803,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=186, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 17.71blocks/s, ⧗=0, ▶=0, ✔=186, ✗=0, ∅=0]" ] }, { @@ -18847,7 +18825,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=1, ✔=186, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 17.71blocks/s, ⧗=0, ▶=1, ✔=186, ✗=0, ∅=0]" ] }, { @@ -18869,7 +18847,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=187, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 17.71blocks/s, ⧗=0, ▶=0, ✔=187, ✗=0, ∅=0]" ] }, { @@ -18891,7 +18869,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=1, ✔=187, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 17.71blocks/s, ⧗=0, ▶=1, ✔=187, ✗=0, ∅=0]" ] }, { @@ -18913,7 +18891,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 17.71blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" ] }, { @@ -18935,7 +18913,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 19.23blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 18.06blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" ] }, { @@ -18957,7 +18935,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 19.23blocks/s, ⧗=0, ▶=1, ✔=188, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 18.06blocks/s, ⧗=0, ▶=1, ✔=188, ✗=0, ∅=0]" ] }, { @@ -18979,7 +18957,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 19.23blocks/s, ⧗=0, ▶=0, ✔=189, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 18.06blocks/s, ⧗=0, ▶=0, ✔=189, ✗=0, ∅=0]" ] }, { @@ -19001,7 +18979,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 19.23blocks/s, ⧗=0, ▶=1, ✔=189, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 18.06blocks/s, ⧗=0, ▶=1, ✔=189, ✗=0, ∅=0]" ] }, { @@ -19023,7 +19001,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 19.23blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 18.06blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" ] }, { @@ -19045,7 +19023,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 18.84blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 17.93blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" ] }, { @@ -19067,7 +19045,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 18.84blocks/s, ⧗=0, ▶=1, ✔=190, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 17.93blocks/s, ⧗=0, ▶=1, ✔=190, ✗=0, ∅=0]" ] }, { @@ -19089,7 +19067,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 18.84blocks/s, ⧗=0, ▶=0, ✔=191, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 17.93blocks/s, ⧗=0, ▶=0, ✔=191, ✗=0, ∅=0]" ] }, { @@ -19111,7 +19089,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 18.84blocks/s, ⧗=0, ▶=1, ✔=191, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 17.93blocks/s, ⧗=0, ▶=1, ✔=191, ✗=0, ∅=0]" ] }, { @@ -19133,7 +19111,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 18.84blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 17.93blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" ] }, { @@ -19155,7 +19133,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.97blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 17.93blocks/s, ⧗=0, ▶=1, ✔=192, ✗=0, ∅=0]" ] }, { @@ -19177,7 +19155,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.97blocks/s, ⧗=0, ▶=1, ✔=192, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.43blocks/s, ⧗=0, ▶=1, ✔=192, ✗=0, ∅=0]" ] }, { @@ -19199,7 +19177,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.97blocks/s, ⧗=0, ▶=0, ✔=193, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.43blocks/s, ⧗=0, ▶=0, ✔=193, ✗=0, ∅=0]" ] }, { @@ -19221,7 +19199,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.97blocks/s, ⧗=0, ▶=1, ✔=193, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.43blocks/s, ⧗=0, ▶=1, ✔=193, ✗=0, ∅=0]" ] }, { @@ -19243,7 +19221,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.97blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.43blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" ] }, { @@ -19265,7 +19243,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.26blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" ] }, { @@ -19287,7 +19265,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.60blocks/s, ⧗=0, ▶=1, ✔=194, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.26blocks/s, ⧗=0, ▶=1, ✔=194, ✗=0, ∅=0]" ] }, { @@ -19309,7 +19287,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:11<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=195, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.26blocks/s, ⧗=0, ▶=0, ✔=195, ✗=0, ∅=0]" ] }, { @@ -19331,7 +19309,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:11<00:01, 18.60blocks/s, ⧗=0, ▶=1, ✔=195, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:10<00:01, 18.26blocks/s, ⧗=0, ▶=1, ✔=195, ✗=0, ∅=0]" ] }, { @@ -19353,7 +19331,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:11<00:01, 18.60blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:10<00:01, 18.26blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" ] }, { @@ -19375,7 +19353,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:11<00:01, 10.48blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 16.28blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" ] }, { @@ -19397,7 +19375,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:11<00:01, 10.48blocks/s, ⧗=0, ▶=1, ✔=196, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 16.28blocks/s, ⧗=0, ▶=1, ✔=196, ✗=0, ∅=0]" ] }, { @@ -19419,7 +19397,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:11<00:01, 10.48blocks/s, ⧗=0, ▶=0, ✔=197, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 16.28blocks/s, ⧗=0, ▶=0, ✔=197, ✗=0, ∅=0]" ] }, { @@ -19441,7 +19419,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:11<00:01, 10.48blocks/s, ⧗=0, ▶=1, ✔=197, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:10<00:01, 16.28blocks/s, ⧗=0, ▶=1, ✔=197, ✗=0, ∅=0]" ] }, { @@ -19463,7 +19441,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:11<00:01, 10.48blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:10<00:01, 16.28blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" ] }, { @@ -19485,7 +19463,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 11.87blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:10<00:01, 16.76blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" ] }, { @@ -19507,7 +19485,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 11.87blocks/s, ⧗=0, ▶=1, ✔=198, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:10<00:01, 16.76blocks/s, ⧗=0, ▶=1, ✔=198, ✗=0, ∅=0]" ] }, { @@ -19529,7 +19507,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 11.87blocks/s, ⧗=0, ▶=0, ✔=199, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 16.76blocks/s, ⧗=0, ▶=0, ✔=199, ✗=0, ∅=0]" ] }, { @@ -19551,7 +19529,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:11<00:01, 11.87blocks/s, ⧗=0, ▶=1, ✔=199, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:11<00:01, 16.76blocks/s, ⧗=0, ▶=1, ✔=199, ✗=0, ∅=0]" ] }, { @@ -19573,7 +19551,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:11<00:01, 11.87blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:11<00:01, 16.76blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" ] }, { @@ -19595,7 +19573,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:01, 12.87blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:00, 17.55blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" ] }, { @@ -19617,7 +19595,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:01, 12.87blocks/s, ⧗=0, ▶=1, ✔=200, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:00, 17.55blocks/s, ⧗=0, ▶=1, ✔=200, ✗=0, ∅=0]" ] }, { @@ -19639,7 +19617,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:01, 12.87blocks/s, ⧗=0, ▶=0, ✔=201, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:00, 17.55blocks/s, ⧗=0, ▶=0, ✔=201, ✗=0, ∅=0]" ] }, { @@ -19661,7 +19639,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:11<00:01, 12.87blocks/s, ⧗=0, ▶=1, ✔=201, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:11<00:00, 17.55blocks/s, ⧗=0, ▶=1, ✔=201, ✗=0, ∅=0]" ] }, { @@ -19683,7 +19661,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:11<00:01, 12.87blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:11<00:00, 17.55blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" ] }, { @@ -19705,7 +19683,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 14.11blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 17.84blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" ] }, { @@ -19727,7 +19705,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 14.11blocks/s, ⧗=0, ▶=1, ✔=202, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 17.84blocks/s, ⧗=0, ▶=1, ✔=202, ✗=0, ∅=0]" ] }, { @@ -19749,7 +19727,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 14.11blocks/s, ⧗=0, ▶=0, ✔=203, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 17.84blocks/s, ⧗=0, ▶=0, ✔=203, ✗=0, ∅=0]" ] }, { @@ -19771,7 +19749,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:11<00:00, 14.11blocks/s, ⧗=0, ▶=1, ✔=203, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:11<00:00, 17.84blocks/s, ⧗=0, ▶=1, ✔=203, ✗=0, ∅=0]" ] }, { @@ -19793,7 +19771,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:11<00:00, 14.11blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:11<00:00, 17.84blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" ] }, { @@ -19815,7 +19793,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 15.32blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 17.38blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" ] }, { @@ -19837,7 +19815,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 15.32blocks/s, ⧗=0, ▶=1, ✔=204, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 17.38blocks/s, ⧗=0, ▶=1, ✔=204, ✗=0, ∅=0]" ] }, { @@ -19859,7 +19837,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 15.32blocks/s, ⧗=0, ▶=0, ✔=205, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 17.38blocks/s, ⧗=0, ▶=0, ✔=205, ✗=0, ∅=0]" ] }, { @@ -19881,7 +19859,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 15.32blocks/s, ⧗=0, ▶=1, ✔=205, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 17.38blocks/s, ⧗=0, ▶=1, ✔=205, ✗=0, ∅=0]" ] }, { @@ -19903,7 +19881,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 15.32blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 17.38blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" ] }, { @@ -19925,7 +19903,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 16.29blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 17.92blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" ] }, { @@ -19947,7 +19925,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 16.29blocks/s, ⧗=0, ▶=1, ✔=206, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 17.92blocks/s, ⧗=0, ▶=1, ✔=206, ✗=0, ∅=0]" ] }, { @@ -19969,7 +19947,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 16.29blocks/s, ⧗=0, ▶=0, ✔=207, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 17.92blocks/s, ⧗=0, ▶=0, ✔=207, ✗=0, ∅=0]" ] }, { @@ -19991,7 +19969,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 16.29blocks/s, ⧗=0, ▶=1, ✔=207, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 17.92blocks/s, ⧗=0, ▶=1, ✔=207, ✗=0, ∅=0]" ] }, { @@ -20013,7 +19991,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 16.29blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 17.92blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" ] }, { @@ -20035,7 +20013,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 16.22blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 17.79blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" ] }, { @@ -20057,7 +20035,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 16.22blocks/s, ⧗=0, ▶=1, ✔=208, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 17.79blocks/s, ⧗=0, ▶=1, ✔=208, ✗=0, ∅=0]" ] }, { @@ -20079,7 +20057,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 16.22blocks/s, ⧗=0, ▶=0, ✔=209, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 17.79blocks/s, ⧗=0, ▶=0, ✔=209, ✗=0, ∅=0]" ] }, { @@ -20101,7 +20079,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 16.22blocks/s, ⧗=0, ▶=1, ✔=209, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 17.79blocks/s, ⧗=0, ▶=1, ✔=209, ✗=0, ∅=0]" ] }, { @@ -20123,7 +20101,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 16.22blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 17.79blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" ] }, { @@ -20145,7 +20123,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 16.50blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 17.28blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" ] }, { @@ -20167,7 +20145,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 16.50blocks/s, ⧗=0, ▶=1, ✔=210, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 17.28blocks/s, ⧗=0, ▶=1, ✔=210, ✗=0, ∅=0]" ] }, { @@ -20189,7 +20167,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:12<00:00, 16.50blocks/s, ⧗=0, ▶=0, ✔=211, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 17.28blocks/s, ⧗=0, ▶=0, ✔=211, ✗=0, ∅=0]" ] }, { @@ -20211,7 +20189,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:12<00:00, 16.50blocks/s, ⧗=0, ▶=1, ✔=211, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 17.28blocks/s, ⧗=0, ▶=1, ✔=211, ✗=0, ∅=0]" ] }, { @@ -20233,7 +20211,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:12<00:00, 16.50blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 17.28blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" ] }, { @@ -20255,7 +20233,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:12<00:00, 17.07blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" ] }, { @@ -20277,7 +20255,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:12<00:00, 17.07blocks/s, ⧗=0, ▶=1, ✔=212, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=1, ✔=212, ✗=0, ∅=0]" ] }, { @@ -20299,7 +20277,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:12<00:00, 17.07blocks/s, ⧗=0, ▶=0, ✔=213, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=0, ✔=213, ✗=0, ∅=0]" ] }, { @@ -20321,7 +20299,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:12<00:00, 17.07blocks/s, ⧗=0, ▶=1, ✔=213, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=1, ✔=213, ✗=0, ∅=0]" ] }, { @@ -20343,7 +20321,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:12<00:00, 17.07blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" ] }, { @@ -20365,7 +20343,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:12<00:00, 17.34blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 17.76blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" ] }, { @@ -20387,7 +20365,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:12<00:00, 17.34blocks/s, ⧗=0, ▶=1, ✔=214, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 17.76blocks/s, ⧗=0, ▶=1, ✔=214, ✗=0, ∅=0]" ] }, { @@ -20409,7 +20387,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:12<00:00, 17.34blocks/s, ⧗=0, ▶=0, ✔=215, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 17.76blocks/s, ⧗=0, ▶=0, ✔=215, ✗=0, ∅=0]" ] }, { @@ -20431,7 +20409,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:12<00:00, 17.34blocks/s, ⧗=0, ▶=1, ✔=215, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:11<00:00, 17.76blocks/s, ⧗=0, ▶=1, ✔=215, ✗=0, ∅=0]" ] }, { @@ -20453,7 +20431,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:12<00:00, 17.34blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:11<00:00, 17.76blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -20475,7 +20453,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 100%|██████████| 216/216 [00:12<00:00, 16.69blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ▶: 100%|██████████| 216/216 [00:11<00:00, 18.36blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -20497,7 +20475,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ✔: 100%|██████████| 216/216 [00:12<00:00, 16.69blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ✔: 100%|██████████| 216/216 [00:11<00:00, 18.36blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -20512,7 +20490,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ✔: 100%|██████████| 216/216 [00:12<00:00, 17.50blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_500/cells3d/prediction ✔: 100%|██████████| 216/216 [00:11<00:00, 18.07blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -20560,7 +20538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 501/2000 [07:20<4:46:20, 11.46s/it, loss=0.754]" + "training until 2000: 25%|██▌ | 501/2000 [08:56<4:18:08, 10.33s/it, loss=0.65]" ] }, { @@ -20568,7 +20546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 501/2000 [07:20<4:46:20, 11.46s/it, loss=0.73] " + "training until 2000: 25%|██▌ | 501/2000 [08:56<4:18:08, 10.33s/it, loss=0.658]" ] }, { @@ -20576,7 +20554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 502/2000 [07:20<3:25:08, 8.22s/it, loss=0.73]" + "training until 2000: 25%|██▌ | 502/2000 [08:57<3:08:02, 7.53s/it, loss=0.658]" ] }, { @@ -20584,7 +20562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 502/2000 [07:20<3:25:08, 8.22s/it, loss=0.772]" + "training until 2000: 25%|██▌ | 502/2000 [08:57<3:08:02, 7.53s/it, loss=0.634]" ] }, { @@ -20592,7 +20570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 503/2000 [07:21<2:29:32, 5.99s/it, loss=0.772]" + "training until 2000: 25%|██▌ | 503/2000 [08:58<2:19:38, 5.60s/it, loss=0.634]" ] }, { @@ -20600,7 +20578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 503/2000 [07:21<2:29:32, 5.99s/it, loss=0.756]" + "training until 2000: 25%|██▌ | 503/2000 [08:58<2:19:38, 5.60s/it, loss=0.669]" ] }, { @@ -20608,7 +20586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 504/2000 [07:22<1:49:16, 4.38s/it, loss=0.756]" + "training until 2000: 25%|██▌ | 504/2000 [08:59<1:43:32, 4.15s/it, loss=0.669]" ] }, { @@ -20616,7 +20594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 504/2000 [07:22<1:49:16, 4.38s/it, loss=0.757]" + "training until 2000: 25%|██▌ | 504/2000 [08:59<1:43:32, 4.15s/it, loss=0.669]" ] }, { @@ -20624,7 +20602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 505/2000 [07:22<1:21:57, 3.29s/it, loss=0.757]" + "training until 2000: 25%|██▌ | 505/2000 [09:00<1:20:44, 3.24s/it, loss=0.669]" ] }, { @@ -20632,7 +20610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 505/2000 [07:22<1:21:57, 3.29s/it, loss=0.721]" + "training until 2000: 25%|██▌ | 505/2000 [09:00<1:20:44, 3.24s/it, loss=0.628]" ] }, { @@ -20640,7 +20618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 506/2000 [07:23<1:03:54, 2.57s/it, loss=0.721]" + "training until 2000: 25%|██▌ | 506/2000 [09:01<1:03:36, 2.55s/it, loss=0.628]" ] }, { @@ -20648,7 +20626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 506/2000 [07:23<1:03:54, 2.57s/it, loss=0.73] " + "training until 2000: 25%|██▌ | 506/2000 [09:01<1:03:36, 2.55s/it, loss=0.674]" ] }, { @@ -20656,7 +20634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 507/2000 [07:24<49:28, 1.99s/it, loss=0.73] " + "training until 2000: 25%|██▌ | 507/2000 [09:01<50:53, 2.05s/it, loss=0.674] " ] }, { @@ -20664,7 +20642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 507/2000 [07:24<49:28, 1.99s/it, loss=0.745]" + "training until 2000: 25%|██▌ | 507/2000 [09:01<50:53, 2.05s/it, loss=0.693]" ] }, { @@ -20672,7 +20650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 508/2000 [07:25<41:39, 1.68s/it, loss=0.745]" + "training until 2000: 25%|██▌ | 508/2000 [09:03<45:49, 1.84s/it, loss=0.693]" ] }, { @@ -20680,7 +20658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 508/2000 [07:25<41:39, 1.68s/it, loss=0.78] " + "training until 2000: 25%|██▌ | 508/2000 [09:03<45:49, 1.84s/it, loss=0.646]" ] }, { @@ -20688,7 +20666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 509/2000 [07:26<34:55, 1.41s/it, loss=0.78]" + "training until 2000: 25%|██▌ | 509/2000 [09:04<39:29, 1.59s/it, loss=0.646]" ] }, { @@ -20696,7 +20674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 25%|██▌ | 509/2000 [07:26<34:55, 1.41s/it, loss=0.769]" + "training until 2000: 25%|██▌ | 509/2000 [09:04<39:29, 1.59s/it, loss=0.649]" ] }, { @@ -20704,7 +20682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 510/2000 [07:26<29:30, 1.19s/it, loss=0.769]" + "training until 2000: 26%|██▌ | 510/2000 [09:05<35:16, 1.42s/it, loss=0.649]" ] }, { @@ -20712,7 +20690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 510/2000 [07:26<29:30, 1.19s/it, loss=0.69] " + "training until 2000: 26%|██▌ | 510/2000 [09:05<35:16, 1.42s/it, loss=0.656]" ] }, { @@ -20720,7 +20698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 511/2000 [07:27<25:48, 1.04s/it, loss=0.69]" + "training until 2000: 26%|██▌ | 511/2000 [09:06<36:38, 1.48s/it, loss=0.656]" ] }, { @@ -20728,7 +20706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 511/2000 [07:27<25:48, 1.04s/it, loss=0.724]" + "training until 2000: 26%|██▌ | 511/2000 [09:06<36:38, 1.48s/it, loss=0.63] " ] }, { @@ -20736,7 +20714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 512/2000 [07:28<23:55, 1.04it/s, loss=0.724]" + "training until 2000: 26%|██▌ | 512/2000 [09:07<32:27, 1.31s/it, loss=0.63]" ] }, { @@ -20744,7 +20722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 512/2000 [07:28<23:55, 1.04it/s, loss=0.773]" + "training until 2000: 26%|██▌ | 512/2000 [09:07<32:27, 1.31s/it, loss=0.659]" ] }, { @@ -20752,7 +20730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 513/2000 [07:29<23:06, 1.07it/s, loss=0.773]" + "training until 2000: 26%|██▌ | 513/2000 [09:09<34:04, 1.37s/it, loss=0.659]" ] }, { @@ -20760,7 +20738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 513/2000 [07:29<23:06, 1.07it/s, loss=0.711]" + "training until 2000: 26%|██▌ | 513/2000 [09:09<34:04, 1.37s/it, loss=0.656]" ] }, { @@ -20768,7 +20746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 514/2000 [07:29<21:36, 1.15it/s, loss=0.711]" + "training until 2000: 26%|██▌ | 514/2000 [09:09<28:13, 1.14s/it, loss=0.656]" ] }, { @@ -20776,7 +20754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 514/2000 [07:29<21:36, 1.15it/s, loss=0.738]" + "training until 2000: 26%|██▌ | 514/2000 [09:09<28:13, 1.14s/it, loss=0.625]" ] }, { @@ -20784,7 +20762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 515/2000 [07:30<19:52, 1.25it/s, loss=0.738]" + "training until 2000: 26%|██▌ | 515/2000 [09:11<27:45, 1.12s/it, loss=0.625]" ] }, { @@ -20792,7 +20770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 515/2000 [07:30<19:52, 1.25it/s, loss=0.771]" + "training until 2000: 26%|██▌ | 515/2000 [09:11<27:45, 1.12s/it, loss=0.65] " ] }, { @@ -20800,7 +20778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 516/2000 [07:31<20:26, 1.21it/s, loss=0.771]" + "training until 2000: 26%|██▌ | 516/2000 [09:12<28:51, 1.17s/it, loss=0.65]" ] }, { @@ -20808,7 +20786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 516/2000 [07:31<20:26, 1.21it/s, loss=0.748]" + "training until 2000: 26%|██▌ | 516/2000 [09:12<28:51, 1.17s/it, loss=0.659]" ] }, { @@ -20816,7 +20794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 517/2000 [07:32<21:18, 1.16it/s, loss=0.748]" + "training until 2000: 26%|██▌ | 517/2000 [09:13<29:43, 1.20s/it, loss=0.659]" ] }, { @@ -20824,7 +20802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 517/2000 [07:32<21:18, 1.16it/s, loss=0.706]" + "training until 2000: 26%|██▌ | 517/2000 [09:13<29:43, 1.20s/it, loss=0.64] " ] }, { @@ -20832,7 +20810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 518/2000 [07:32<17:52, 1.38it/s, loss=0.706]" + "training until 2000: 26%|██▌ | 518/2000 [09:14<28:59, 1.17s/it, loss=0.64]" ] }, { @@ -20840,7 +20818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 518/2000 [07:32<17:52, 1.38it/s, loss=0.746]" + "training until 2000: 26%|██▌ | 518/2000 [09:14<28:59, 1.17s/it, loss=0.668]" ] }, { @@ -20848,7 +20826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 519/2000 [07:33<19:26, 1.27it/s, loss=0.746]" + "training until 2000: 26%|██▌ | 519/2000 [09:15<27:42, 1.12s/it, loss=0.668]" ] }, { @@ -20856,7 +20834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 519/2000 [07:33<19:26, 1.27it/s, loss=0.699]" + "training until 2000: 26%|██▌ | 519/2000 [09:15<27:42, 1.12s/it, loss=0.615]" ] }, { @@ -20864,7 +20842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 520/2000 [07:34<21:57, 1.12it/s, loss=0.699]" + "training until 2000: 26%|██▌ | 520/2000 [09:16<27:22, 1.11s/it, loss=0.615]" ] }, { @@ -20872,7 +20850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 520/2000 [07:34<21:57, 1.12it/s, loss=0.717]" + "training until 2000: 26%|██▌ | 520/2000 [09:16<27:22, 1.11s/it, loss=0.673]" ] }, { @@ -20880,7 +20858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 521/2000 [07:35<22:44, 1.08it/s, loss=0.717]" + "training until 2000: 26%|██▌ | 521/2000 [09:18<29:40, 1.20s/it, loss=0.673]" ] }, { @@ -20888,7 +20866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 521/2000 [07:35<22:44, 1.08it/s, loss=0.72] " + "training until 2000: 26%|██▌ | 521/2000 [09:18<29:40, 1.20s/it, loss=0.65] " ] }, { @@ -20896,7 +20874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 522/2000 [07:36<20:06, 1.23it/s, loss=0.72]" + "training until 2000: 26%|██▌ | 522/2000 [09:19<28:05, 1.14s/it, loss=0.65]" ] }, { @@ -20904,7 +20882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 522/2000 [07:36<20:06, 1.23it/s, loss=0.717]" + "training until 2000: 26%|██▌ | 522/2000 [09:19<28:05, 1.14s/it, loss=0.661]" ] }, { @@ -20912,7 +20890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 523/2000 [07:37<18:52, 1.30it/s, loss=0.717]" + "training until 2000: 26%|██▌ | 523/2000 [09:19<23:48, 1.03it/s, loss=0.661]" ] }, { @@ -20920,7 +20898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 523/2000 [07:37<18:52, 1.30it/s, loss=0.689]" + "training until 2000: 26%|██▌ | 523/2000 [09:19<23:48, 1.03it/s, loss=0.636]" ] }, { @@ -20928,7 +20906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 524/2000 [07:37<18:58, 1.30it/s, loss=0.689]" + "training until 2000: 26%|██▌ | 524/2000 [09:20<24:33, 1.00it/s, loss=0.636]" ] }, { @@ -20936,7 +20914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▌ | 524/2000 [07:37<18:58, 1.30it/s, loss=0.704]" + "training until 2000: 26%|██▌ | 524/2000 [09:20<24:33, 1.00it/s, loss=0.657]" ] }, { @@ -20944,7 +20922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 525/2000 [07:38<18:17, 1.34it/s, loss=0.704]" + "training until 2000: 26%|██▋ | 525/2000 [09:21<20:34, 1.19it/s, loss=0.657]" ] }, { @@ -20952,7 +20930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 525/2000 [07:38<18:17, 1.34it/s, loss=0.722]" + "training until 2000: 26%|██▋ | 525/2000 [09:21<20:34, 1.19it/s, loss=0.649]" ] }, { @@ -20960,7 +20938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 526/2000 [07:39<18:29, 1.33it/s, loss=0.722]" + "training until 2000: 26%|██▋ | 526/2000 [09:22<21:32, 1.14it/s, loss=0.649]" ] }, { @@ -20968,7 +20946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 526/2000 [07:39<18:29, 1.33it/s, loss=0.741]" + "training until 2000: 26%|██▋ | 526/2000 [09:22<21:32, 1.14it/s, loss=0.621]" ] }, { @@ -20976,7 +20954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 527/2000 [07:40<19:22, 1.27it/s, loss=0.741]" + "training until 2000: 26%|██▋ | 527/2000 [09:23<23:48, 1.03it/s, loss=0.621]" ] }, { @@ -20984,7 +20962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 527/2000 [07:40<19:22, 1.27it/s, loss=0.717]" + "training until 2000: 26%|██▋ | 527/2000 [09:23<23:48, 1.03it/s, loss=0.66] " ] }, { @@ -20992,7 +20970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 528/2000 [07:41<19:43, 1.24it/s, loss=0.717]" + "training until 2000: 26%|██▋ | 528/2000 [09:24<21:20, 1.15it/s, loss=0.66]" ] }, { @@ -21000,7 +20978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 528/2000 [07:41<19:43, 1.24it/s, loss=0.724]" + "training until 2000: 26%|██▋ | 528/2000 [09:24<21:20, 1.15it/s, loss=0.651]" ] }, { @@ -21008,7 +20986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 529/2000 [07:42<21:42, 1.13it/s, loss=0.724]" + "training until 2000: 26%|██▋ | 529/2000 [09:25<22:08, 1.11it/s, loss=0.651]" ] }, { @@ -21016,7 +20994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 529/2000 [07:42<21:42, 1.13it/s, loss=0.749]" + "training until 2000: 26%|██▋ | 529/2000 [09:25<22:08, 1.11it/s, loss=0.657]" ] }, { @@ -21024,7 +21002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 530/2000 [07:42<21:08, 1.16it/s, loss=0.749]" + "training until 2000: 26%|██▋ | 530/2000 [09:25<22:09, 1.11it/s, loss=0.657]" ] }, { @@ -21032,7 +21010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 26%|██▋ | 530/2000 [07:42<21:08, 1.16it/s, loss=0.701]" + "training until 2000: 26%|██▋ | 530/2000 [09:25<22:09, 1.11it/s, loss=0.655]" ] }, { @@ -21040,7 +21018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 531/2000 [07:43<19:45, 1.24it/s, loss=0.701]" + "training until 2000: 27%|██▋ | 531/2000 [09:27<23:12, 1.06it/s, loss=0.655]" ] }, { @@ -21048,7 +21026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 531/2000 [07:43<19:45, 1.24it/s, loss=0.686]" + "training until 2000: 27%|██▋ | 531/2000 [09:27<23:12, 1.06it/s, loss=0.643]" ] }, { @@ -21056,7 +21034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 532/2000 [07:44<18:22, 1.33it/s, loss=0.686]" + "training until 2000: 27%|██▋ | 532/2000 [09:27<22:56, 1.07it/s, loss=0.643]" ] }, { @@ -21064,7 +21042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 532/2000 [07:44<18:22, 1.33it/s, loss=0.743]" + "training until 2000: 27%|██▋ | 532/2000 [09:27<22:56, 1.07it/s, loss=0.654]" ] }, { @@ -21072,7 +21050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 533/2000 [07:44<16:27, 1.49it/s, loss=0.743]" + "training until 2000: 27%|██▋ | 533/2000 [09:28<23:05, 1.06it/s, loss=0.654]" ] }, { @@ -21080,7 +21058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 533/2000 [07:44<16:27, 1.49it/s, loss=0.709]" + "training until 2000: 27%|██▋ | 533/2000 [09:28<23:05, 1.06it/s, loss=0.633]" ] }, { @@ -21088,7 +21066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 534/2000 [07:45<18:40, 1.31it/s, loss=0.709]" + "training until 2000: 27%|██▋ | 534/2000 [09:29<22:46, 1.07it/s, loss=0.633]" ] }, { @@ -21096,7 +21074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 534/2000 [07:45<18:40, 1.31it/s, loss=0.765]" + "training until 2000: 27%|██▋ | 534/2000 [09:29<22:46, 1.07it/s, loss=0.628]" ] }, { @@ -21104,7 +21082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 535/2000 [07:46<18:41, 1.31it/s, loss=0.765]" + "training until 2000: 27%|██▋ | 535/2000 [09:30<23:28, 1.04it/s, loss=0.628]" ] }, { @@ -21112,7 +21090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 535/2000 [07:46<18:41, 1.31it/s, loss=0.717]" + "training until 2000: 27%|██▋ | 535/2000 [09:30<23:28, 1.04it/s, loss=0.64] " ] }, { @@ -21120,7 +21098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 536/2000 [07:47<22:06, 1.10it/s, loss=0.717]" + "training until 2000: 27%|██▋ | 536/2000 [09:31<20:36, 1.18it/s, loss=0.64]" ] }, { @@ -21128,7 +21106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 536/2000 [07:47<22:06, 1.10it/s, loss=0.744]" + "training until 2000: 27%|██▋ | 536/2000 [09:31<20:36, 1.18it/s, loss=0.655]" ] }, { @@ -21136,7 +21114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 537/2000 [07:48<20:32, 1.19it/s, loss=0.744]" + "training until 2000: 27%|██▋ | 537/2000 [09:32<21:57, 1.11it/s, loss=0.655]" ] }, { @@ -21144,7 +21122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 537/2000 [07:48<20:32, 1.19it/s, loss=0.703]" + "training until 2000: 27%|██▋ | 537/2000 [09:32<21:57, 1.11it/s, loss=0.626]" ] }, { @@ -21152,7 +21130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 538/2000 [07:49<18:39, 1.31it/s, loss=0.703]" + "training until 2000: 27%|██▋ | 538/2000 [09:33<21:47, 1.12it/s, loss=0.626]" ] }, { @@ -21160,7 +21138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 538/2000 [07:49<18:39, 1.31it/s, loss=0.724]" + "training until 2000: 27%|██▋ | 538/2000 [09:33<21:47, 1.12it/s, loss=0.657]" ] }, { @@ -21168,7 +21146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 539/2000 [07:50<21:27, 1.14it/s, loss=0.724]" + "training until 2000: 27%|██▋ | 539/2000 [09:33<19:38, 1.24it/s, loss=0.657]" ] }, { @@ -21176,7 +21154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 539/2000 [07:50<21:27, 1.14it/s, loss=0.727]" + "training until 2000: 27%|██▋ | 539/2000 [09:33<19:38, 1.24it/s, loss=0.622]" ] }, { @@ -21184,7 +21162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 540/2000 [07:50<20:14, 1.20it/s, loss=0.727]" + "training until 2000: 27%|██▋ | 540/2000 [09:34<20:21, 1.20it/s, loss=0.622]" ] }, { @@ -21192,7 +21170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 540/2000 [07:50<20:14, 1.20it/s, loss=0.732]" + "training until 2000: 27%|██▋ | 540/2000 [09:34<20:21, 1.20it/s, loss=0.63] " ] }, { @@ -21200,7 +21178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 541/2000 [07:51<19:48, 1.23it/s, loss=0.732]" + "training until 2000: 27%|██▋ | 541/2000 [09:35<20:11, 1.20it/s, loss=0.63]" ] }, { @@ -21208,7 +21186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 541/2000 [07:51<19:48, 1.23it/s, loss=0.7] " + "training until 2000: 27%|██▋ | 541/2000 [09:35<20:11, 1.20it/s, loss=0.674]" ] }, { @@ -21216,7 +21194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 542/2000 [07:52<19:53, 1.22it/s, loss=0.7]" + "training until 2000: 27%|██▋ | 542/2000 [09:36<19:54, 1.22it/s, loss=0.674]" ] }, { @@ -21224,7 +21202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 542/2000 [07:52<19:53, 1.22it/s, loss=0.699]" + "training until 2000: 27%|██▋ | 542/2000 [09:36<19:54, 1.22it/s, loss=0.651]" ] }, { @@ -21232,7 +21210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 543/2000 [07:53<20:02, 1.21it/s, loss=0.699]" + "training until 2000: 27%|██▋ | 543/2000 [09:37<22:07, 1.10it/s, loss=0.651]" ] }, { @@ -21240,7 +21218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 543/2000 [07:53<20:02, 1.21it/s, loss=0.728]" + "training until 2000: 27%|██▋ | 543/2000 [09:37<22:07, 1.10it/s, loss=0.658]" ] }, { @@ -21248,7 +21226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 544/2000 [07:53<18:46, 1.29it/s, loss=0.728]" + "training until 2000: 27%|██▋ | 544/2000 [09:38<25:53, 1.07s/it, loss=0.658]" ] }, { @@ -21256,7 +21234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 544/2000 [07:53<18:46, 1.29it/s, loss=0.756]" + "training until 2000: 27%|██▋ | 544/2000 [09:38<25:53, 1.07s/it, loss=0.614]" ] }, { @@ -21264,7 +21242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 545/2000 [07:54<19:15, 1.26it/s, loss=0.756]" + "training until 2000: 27%|██▋ | 545/2000 [09:40<25:28, 1.05s/it, loss=0.614]" ] }, { @@ -21272,7 +21250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 545/2000 [07:54<19:15, 1.26it/s, loss=0.745]" + "training until 2000: 27%|██▋ | 545/2000 [09:40<25:28, 1.05s/it, loss=0.63] " ] }, { @@ -21280,7 +21258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 546/2000 [07:55<20:27, 1.18it/s, loss=0.745]" + "training until 2000: 27%|██▋ | 546/2000 [09:41<28:24, 1.17s/it, loss=0.63]" ] }, { @@ -21288,7 +21266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 546/2000 [07:55<20:27, 1.18it/s, loss=0.683]" + "training until 2000: 27%|██▋ | 546/2000 [09:41<28:24, 1.17s/it, loss=0.632]" ] }, { @@ -21296,7 +21274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 547/2000 [07:56<19:38, 1.23it/s, loss=0.683]" + "training until 2000: 27%|██▋ | 547/2000 [09:42<29:21, 1.21s/it, loss=0.632]" ] }, { @@ -21304,7 +21282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 547/2000 [07:56<19:38, 1.23it/s, loss=0.704]" + "training until 2000: 27%|██▋ | 547/2000 [09:42<29:21, 1.21s/it, loss=0.616]" ] }, { @@ -21312,7 +21290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 548/2000 [07:57<18:29, 1.31it/s, loss=0.704]" + "training until 2000: 27%|██▋ | 548/2000 [09:43<26:55, 1.11s/it, loss=0.616]" ] }, { @@ -21320,7 +21298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 548/2000 [07:57<18:29, 1.31it/s, loss=0.705]" + "training until 2000: 27%|██▋ | 548/2000 [09:43<26:55, 1.11s/it, loss=0.634]" ] }, { @@ -21328,7 +21306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 549/2000 [07:57<17:03, 1.42it/s, loss=0.705]" + "training until 2000: 27%|██▋ | 549/2000 [09:44<24:57, 1.03s/it, loss=0.634]" ] }, { @@ -21336,7 +21314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 27%|██▋ | 549/2000 [07:57<17:03, 1.42it/s, loss=0.753]" + "training until 2000: 27%|██▋ | 549/2000 [09:44<24:57, 1.03s/it, loss=0.582]" ] }, { @@ -21344,7 +21322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 550/2000 [07:58<16:05, 1.50it/s, loss=0.753]" + "training until 2000: 28%|██▊ | 550/2000 [09:45<25:48, 1.07s/it, loss=0.582]" ] }, { @@ -21352,7 +21330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 550/2000 [07:58<16:05, 1.50it/s, loss=0.703]" + "training until 2000: 28%|██▊ | 550/2000 [09:45<25:48, 1.07s/it, loss=0.661]" ] }, { @@ -21360,7 +21338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 551/2000 [07:59<18:21, 1.32it/s, loss=0.703]" + "training until 2000: 28%|██▊ | 551/2000 [09:46<25:38, 1.06s/it, loss=0.661]" ] }, { @@ -21368,7 +21346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 551/2000 [07:59<18:21, 1.32it/s, loss=0.763]" + "training until 2000: 28%|██▊ | 551/2000 [09:46<25:38, 1.06s/it, loss=0.634]" ] }, { @@ -21376,7 +21354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 552/2000 [08:00<20:19, 1.19it/s, loss=0.763]" + "training until 2000: 28%|██▊ | 552/2000 [09:47<24:12, 1.00s/it, loss=0.634]" ] }, { @@ -21384,7 +21362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 552/2000 [08:00<20:19, 1.19it/s, loss=0.731]" + "training until 2000: 28%|██▊ | 552/2000 [09:47<24:12, 1.00s/it, loss=0.629]" ] }, { @@ -21392,7 +21370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 553/2000 [08:00<18:38, 1.29it/s, loss=0.731]" + "training until 2000: 28%|██▊ | 553/2000 [09:48<23:13, 1.04it/s, loss=0.629]" ] }, { @@ -21400,7 +21378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 553/2000 [08:00<18:38, 1.29it/s, loss=0.699]" + "training until 2000: 28%|██▊ | 553/2000 [09:48<23:13, 1.04it/s, loss=0.644]" ] }, { @@ -21408,7 +21386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 554/2000 [08:01<18:34, 1.30it/s, loss=0.699]" + "training until 2000: 28%|██▊ | 554/2000 [09:49<22:01, 1.09it/s, loss=0.644]" ] }, { @@ -21416,7 +21394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 554/2000 [08:01<18:34, 1.30it/s, loss=0.702]" + "training until 2000: 28%|██▊ | 554/2000 [09:49<22:01, 1.09it/s, loss=0.632]" ] }, { @@ -21424,7 +21402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 555/2000 [08:02<17:22, 1.39it/s, loss=0.702]" + "training until 2000: 28%|██▊ | 555/2000 [09:50<21:55, 1.10it/s, loss=0.632]" ] }, { @@ -21432,7 +21410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 555/2000 [08:02<17:22, 1.39it/s, loss=0.751]" + "training until 2000: 28%|██▊ | 555/2000 [09:50<21:55, 1.10it/s, loss=0.628]" ] }, { @@ -21440,7 +21418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 556/2000 [08:02<17:01, 1.41it/s, loss=0.751]" + "training until 2000: 28%|██▊ | 556/2000 [09:50<20:07, 1.20it/s, loss=0.628]" ] }, { @@ -21448,7 +21426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 556/2000 [08:02<17:01, 1.41it/s, loss=0.709]" + "training until 2000: 28%|██▊ | 556/2000 [09:50<20:07, 1.20it/s, loss=0.633]" ] }, { @@ -21456,7 +21434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 557/2000 [08:03<19:16, 1.25it/s, loss=0.709]" + "training until 2000: 28%|██▊ | 557/2000 [09:52<23:17, 1.03it/s, loss=0.633]" ] }, { @@ -21464,7 +21442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 557/2000 [08:03<19:16, 1.25it/s, loss=0.728]" + "training until 2000: 28%|██▊ | 557/2000 [09:52<23:17, 1.03it/s, loss=0.637]" ] }, { @@ -21472,7 +21450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 558/2000 [08:04<19:38, 1.22it/s, loss=0.728]" + "training until 2000: 28%|██▊ | 558/2000 [09:52<20:13, 1.19it/s, loss=0.637]" ] }, { @@ -21480,7 +21458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 558/2000 [08:04<19:38, 1.22it/s, loss=0.727]" + "training until 2000: 28%|██▊ | 558/2000 [09:52<20:13, 1.19it/s, loss=0.611]" ] }, { @@ -21488,7 +21466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 559/2000 [08:05<18:48, 1.28it/s, loss=0.727]" + "training until 2000: 28%|██▊ | 559/2000 [09:53<20:44, 1.16it/s, loss=0.611]" ] }, { @@ -21496,7 +21474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 559/2000 [08:05<18:48, 1.28it/s, loss=0.715]" + "training until 2000: 28%|██▊ | 559/2000 [09:53<20:44, 1.16it/s, loss=0.621]" ] }, { @@ -21504,7 +21482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 560/2000 [08:06<18:12, 1.32it/s, loss=0.715]" + "training until 2000: 28%|██▊ | 560/2000 [09:54<24:18, 1.01s/it, loss=0.621]" ] }, { @@ -21512,7 +21490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 560/2000 [08:06<18:12, 1.32it/s, loss=0.745]" + "training until 2000: 28%|██▊ | 560/2000 [09:54<24:18, 1.01s/it, loss=0.596]" ] }, { @@ -21520,7 +21498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 561/2000 [08:06<17:57, 1.34it/s, loss=0.745]" + "training until 2000: 28%|██▊ | 561/2000 [09:55<23:51, 1.01it/s, loss=0.596]" ] }, { @@ -21528,7 +21506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 561/2000 [08:06<17:57, 1.34it/s, loss=0.76] " + "training until 2000: 28%|██▊ | 561/2000 [09:55<23:51, 1.01it/s, loss=0.627]" ] }, { @@ -21536,7 +21514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 562/2000 [08:07<18:00, 1.33it/s, loss=0.76]" + "training until 2000: 28%|██▊ | 562/2000 [09:57<28:28, 1.19s/it, loss=0.627]" ] }, { @@ -21544,7 +21522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 562/2000 [08:07<18:00, 1.33it/s, loss=0.726]" + "training until 2000: 28%|██▊ | 562/2000 [09:57<28:28, 1.19s/it, loss=0.618]" ] }, { @@ -21552,7 +21530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 563/2000 [08:08<17:13, 1.39it/s, loss=0.726]" + "training until 2000: 28%|██▊ | 563/2000 [09:58<26:53, 1.12s/it, loss=0.618]" ] }, { @@ -21560,7 +21538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 563/2000 [08:08<17:13, 1.39it/s, loss=0.677]" + "training until 2000: 28%|██▊ | 563/2000 [09:58<26:53, 1.12s/it, loss=0.603]" ] }, { @@ -21568,7 +21546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 564/2000 [08:09<18:27, 1.30it/s, loss=0.677]" + "training until 2000: 28%|██▊ | 564/2000 [09:59<26:24, 1.10s/it, loss=0.603]" ] }, { @@ -21576,7 +21554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 564/2000 [08:09<18:27, 1.30it/s, loss=0.707]" + "training until 2000: 28%|██▊ | 564/2000 [09:59<26:24, 1.10s/it, loss=0.587]" ] }, { @@ -21584,7 +21562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 565/2000 [08:09<17:11, 1.39it/s, loss=0.707]" + "training until 2000: 28%|██▊ | 565/2000 [10:00<27:08, 1.13s/it, loss=0.587]" ] }, { @@ -21592,7 +21570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 565/2000 [08:09<17:11, 1.39it/s, loss=0.734]" + "training until 2000: 28%|██▊ | 565/2000 [10:00<27:08, 1.13s/it, loss=0.592]" ] }, { @@ -21600,7 +21578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 566/2000 [08:10<18:23, 1.30it/s, loss=0.734]" + "training until 2000: 28%|██▊ | 566/2000 [10:02<28:12, 1.18s/it, loss=0.592]" ] }, { @@ -21608,7 +21586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 566/2000 [08:10<18:23, 1.30it/s, loss=0.715]" + "training until 2000: 28%|██▊ | 566/2000 [10:02<28:12, 1.18s/it, loss=0.653]" ] }, { @@ -21616,7 +21594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 567/2000 [08:11<19:53, 1.20it/s, loss=0.715]" + "training until 2000: 28%|██▊ | 567/2000 [10:03<31:52, 1.33s/it, loss=0.653]" ] }, { @@ -21624,7 +21602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 567/2000 [08:11<19:53, 1.20it/s, loss=0.722]" + "training until 2000: 28%|██▊ | 567/2000 [10:03<31:52, 1.33s/it, loss=0.614]" ] }, { @@ -21632,7 +21610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 568/2000 [08:12<19:15, 1.24it/s, loss=0.722]" + "training until 2000: 28%|██▊ | 568/2000 [10:04<30:30, 1.28s/it, loss=0.614]" ] }, { @@ -21640,7 +21618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 568/2000 [08:12<19:15, 1.24it/s, loss=0.701]" + "training until 2000: 28%|██▊ | 568/2000 [10:04<30:30, 1.28s/it, loss=0.655]" ] }, { @@ -21648,7 +21626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 569/2000 [08:13<18:54, 1.26it/s, loss=0.701]" + "training until 2000: 28%|██▊ | 569/2000 [10:06<30:31, 1.28s/it, loss=0.655]" ] }, { @@ -21656,7 +21634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 569/2000 [08:13<18:54, 1.26it/s, loss=0.777]" + "training until 2000: 28%|██▊ | 569/2000 [10:06<30:31, 1.28s/it, loss=0.594]" ] }, { @@ -21664,7 +21642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 570/2000 [08:13<16:41, 1.43it/s, loss=0.777]" + "training until 2000: 28%|██▊ | 570/2000 [10:07<28:41, 1.20s/it, loss=0.594]" ] }, { @@ -21672,7 +21650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 28%|██▊ | 570/2000 [08:13<16:41, 1.43it/s, loss=0.712]" + "training until 2000: 28%|██▊ | 570/2000 [10:07<28:41, 1.20s/it, loss=0.615]" ] }, { @@ -21680,7 +21658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 571/2000 [08:14<16:24, 1.45it/s, loss=0.712]" + "training until 2000: 29%|██▊ | 571/2000 [10:07<25:59, 1.09s/it, loss=0.615]" ] }, { @@ -21688,7 +21666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 571/2000 [08:14<16:24, 1.45it/s, loss=0.7] " + "training until 2000: 29%|██▊ | 571/2000 [10:07<25:59, 1.09s/it, loss=0.603]" ] }, { @@ -21696,7 +21674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 572/2000 [08:15<16:58, 1.40it/s, loss=0.7]" + "training until 2000: 29%|██▊ | 572/2000 [10:09<28:16, 1.19s/it, loss=0.603]" ] }, { @@ -21704,7 +21682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 572/2000 [08:15<16:58, 1.40it/s, loss=0.72]" + "training until 2000: 29%|██▊ | 572/2000 [10:09<28:16, 1.19s/it, loss=0.599]" ] }, { @@ -21712,7 +21690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 573/2000 [08:16<19:49, 1.20it/s, loss=0.72]" + "training until 2000: 29%|██▊ | 573/2000 [10:10<28:34, 1.20s/it, loss=0.599]" ] }, { @@ -21720,7 +21698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 573/2000 [08:16<19:49, 1.20it/s, loss=0.725]" + "training until 2000: 29%|██▊ | 573/2000 [10:10<28:34, 1.20s/it, loss=0.628]" ] }, { @@ -21728,7 +21706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 574/2000 [08:16<18:35, 1.28it/s, loss=0.725]" + "training until 2000: 29%|██▊ | 574/2000 [10:11<27:48, 1.17s/it, loss=0.628]" ] }, { @@ -21736,7 +21714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▊ | 574/2000 [08:16<18:35, 1.28it/s, loss=0.675]" + "training until 2000: 29%|██▊ | 574/2000 [10:11<27:48, 1.17s/it, loss=0.629]" ] }, { @@ -21744,7 +21722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 575/2000 [08:17<19:20, 1.23it/s, loss=0.675]" + "training until 2000: 29%|██▉ | 575/2000 [10:12<27:11, 1.14s/it, loss=0.629]" ] }, { @@ -21752,7 +21730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 575/2000 [08:17<19:20, 1.23it/s, loss=0.734]" + "training until 2000: 29%|██▉ | 575/2000 [10:12<27:11, 1.14s/it, loss=0.579]" ] }, { @@ -21760,7 +21738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 576/2000 [08:18<17:53, 1.33it/s, loss=0.734]" + "training until 2000: 29%|██▉ | 576/2000 [10:13<24:42, 1.04s/it, loss=0.579]" ] }, { @@ -21768,7 +21746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 576/2000 [08:18<17:53, 1.33it/s, loss=0.686]" + "training until 2000: 29%|██▉ | 576/2000 [10:13<24:42, 1.04s/it, loss=0.583]" ] }, { @@ -21776,7 +21754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 577/2000 [08:19<18:04, 1.31it/s, loss=0.686]" + "training until 2000: 29%|██▉ | 577/2000 [10:14<21:59, 1.08it/s, loss=0.583]" ] }, { @@ -21784,7 +21762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 577/2000 [08:19<18:04, 1.31it/s, loss=0.697]" + "training until 2000: 29%|██▉ | 577/2000 [10:14<21:59, 1.08it/s, loss=0.585]" ] }, { @@ -21792,7 +21770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 578/2000 [08:19<18:07, 1.31it/s, loss=0.697]" + "training until 2000: 29%|██▉ | 578/2000 [10:14<18:52, 1.26it/s, loss=0.585]" ] }, { @@ -21800,7 +21778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 578/2000 [08:19<18:07, 1.31it/s, loss=0.738]" + "training until 2000: 29%|██▉ | 578/2000 [10:14<18:52, 1.26it/s, loss=0.556]" ] }, { @@ -21808,7 +21786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 579/2000 [08:20<19:15, 1.23it/s, loss=0.738]" + "training until 2000: 29%|██▉ | 579/2000 [10:15<21:16, 1.11it/s, loss=0.556]" ] }, { @@ -21816,7 +21794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 579/2000 [08:20<19:15, 1.23it/s, loss=0.697]" + "training until 2000: 29%|██▉ | 579/2000 [10:15<21:16, 1.11it/s, loss=0.579]" ] }, { @@ -21824,7 +21802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 580/2000 [08:21<19:13, 1.23it/s, loss=0.697]" + "training until 2000: 29%|██▉ | 580/2000 [10:17<23:19, 1.01it/s, loss=0.579]" ] }, { @@ -21832,7 +21810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 580/2000 [08:21<19:13, 1.23it/s, loss=0.707]" + "training until 2000: 29%|██▉ | 580/2000 [10:17<23:19, 1.01it/s, loss=0.616]" ] }, { @@ -21840,7 +21818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 581/2000 [08:22<18:27, 1.28it/s, loss=0.707]" + "training until 2000: 29%|██▉ | 581/2000 [10:18<25:23, 1.07s/it, loss=0.616]" ] }, { @@ -21848,7 +21826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 581/2000 [08:22<18:27, 1.28it/s, loss=0.76] " + "training until 2000: 29%|██▉ | 581/2000 [10:18<25:23, 1.07s/it, loss=0.578]" ] }, { @@ -21856,7 +21834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 582/2000 [08:23<18:19, 1.29it/s, loss=0.76]" + "training until 2000: 29%|██▉ | 582/2000 [10:19<25:11, 1.07s/it, loss=0.578]" ] }, { @@ -21864,7 +21842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 582/2000 [08:23<18:19, 1.29it/s, loss=0.757]" + "training until 2000: 29%|██▉ | 582/2000 [10:19<25:11, 1.07s/it, loss=0.611]" ] }, { @@ -21872,7 +21850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 583/2000 [08:23<16:49, 1.40it/s, loss=0.757]" + "training until 2000: 29%|██▉ | 583/2000 [10:20<24:01, 1.02s/it, loss=0.611]" ] }, { @@ -21880,7 +21858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 583/2000 [08:23<16:49, 1.40it/s, loss=0.713]" + "training until 2000: 29%|██▉ | 583/2000 [10:20<24:01, 1.02s/it, loss=0.611]" ] }, { @@ -21888,7 +21866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 584/2000 [08:24<16:22, 1.44it/s, loss=0.713]" + "training until 2000: 29%|██▉ | 584/2000 [10:21<23:56, 1.01s/it, loss=0.611]" ] }, { @@ -21896,7 +21874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 584/2000 [08:24<16:22, 1.44it/s, loss=0.691]" + "training until 2000: 29%|██▉ | 584/2000 [10:21<23:56, 1.01s/it, loss=0.601]" ] }, { @@ -21904,7 +21882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 585/2000 [08:25<16:53, 1.40it/s, loss=0.691]" + "training until 2000: 29%|██▉ | 585/2000 [10:22<21:52, 1.08it/s, loss=0.601]" ] }, { @@ -21912,7 +21890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 585/2000 [08:25<16:53, 1.40it/s, loss=0.733]" + "training until 2000: 29%|██▉ | 585/2000 [10:22<21:52, 1.08it/s, loss=0.625]" ] }, { @@ -21920,7 +21898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 586/2000 [08:26<18:39, 1.26it/s, loss=0.733]" + "training until 2000: 29%|██▉ | 586/2000 [10:22<21:14, 1.11it/s, loss=0.625]" ] }, { @@ -21928,7 +21906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 586/2000 [08:26<18:39, 1.26it/s, loss=0.698]" + "training until 2000: 29%|██▉ | 586/2000 [10:22<21:14, 1.11it/s, loss=0.619]" ] }, { @@ -21936,7 +21914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 587/2000 [08:26<16:54, 1.39it/s, loss=0.698]" + "training until 2000: 29%|██▉ | 587/2000 [10:24<22:45, 1.03it/s, loss=0.619]" ] }, { @@ -21944,7 +21922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 587/2000 [08:26<16:54, 1.39it/s, loss=0.675]" + "training until 2000: 29%|██▉ | 587/2000 [10:24<22:45, 1.03it/s, loss=0.6] " ] }, { @@ -21952,7 +21930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 588/2000 [08:27<18:24, 1.28it/s, loss=0.675]" + "training until 2000: 29%|██▉ | 588/2000 [10:24<22:19, 1.05it/s, loss=0.6]" ] }, { @@ -21960,7 +21938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 588/2000 [08:27<18:24, 1.28it/s, loss=0.675]" + "training until 2000: 29%|██▉ | 588/2000 [10:24<22:19, 1.05it/s, loss=0.535]" ] }, { @@ -21968,7 +21946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 589/2000 [08:28<18:34, 1.27it/s, loss=0.675]" + "training until 2000: 29%|██▉ | 589/2000 [10:25<22:55, 1.03it/s, loss=0.535]" ] }, { @@ -21976,7 +21954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 29%|██▉ | 589/2000 [08:28<18:34, 1.27it/s, loss=0.661]" + "training until 2000: 29%|██▉ | 589/2000 [10:25<22:55, 1.03it/s, loss=0.549]" ] }, { @@ -21984,7 +21962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 590/2000 [08:29<18:45, 1.25it/s, loss=0.661]" + "training until 2000: 30%|██▉ | 590/2000 [10:26<22:56, 1.02it/s, loss=0.549]" ] }, { @@ -21992,7 +21970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 590/2000 [08:29<18:45, 1.25it/s, loss=0.725]" + "training until 2000: 30%|██▉ | 590/2000 [10:26<22:56, 1.02it/s, loss=0.613]" ] }, { @@ -22000,7 +21978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 591/2000 [08:30<18:45, 1.25it/s, loss=0.725]" + "training until 2000: 30%|██▉ | 591/2000 [10:27<22:37, 1.04it/s, loss=0.613]" ] }, { @@ -22008,7 +21986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 591/2000 [08:30<18:45, 1.25it/s, loss=0.682]" + "training until 2000: 30%|██▉ | 591/2000 [10:27<22:37, 1.04it/s, loss=0.618]" ] }, { @@ -22016,7 +21994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 592/2000 [08:30<19:10, 1.22it/s, loss=0.682]" + "training until 2000: 30%|██▉ | 592/2000 [10:28<21:58, 1.07it/s, loss=0.618]" ] }, { @@ -22024,7 +22002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 592/2000 [08:30<19:10, 1.22it/s, loss=0.671]" + "training until 2000: 30%|██▉ | 592/2000 [10:28<21:58, 1.07it/s, loss=0.628]" ] }, { @@ -22032,7 +22010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 593/2000 [08:31<20:56, 1.12it/s, loss=0.671]" + "training until 2000: 30%|██▉ | 593/2000 [10:29<21:04, 1.11it/s, loss=0.628]" ] }, { @@ -22040,7 +22018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 593/2000 [08:31<20:56, 1.12it/s, loss=0.743]" + "training until 2000: 30%|██▉ | 593/2000 [10:29<21:04, 1.11it/s, loss=0.606]" ] }, { @@ -22048,7 +22026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 594/2000 [08:32<19:24, 1.21it/s, loss=0.743]" + "training until 2000: 30%|██▉ | 594/2000 [10:30<21:06, 1.11it/s, loss=0.606]" ] }, { @@ -22056,7 +22034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 594/2000 [08:32<19:24, 1.21it/s, loss=0.706]" + "training until 2000: 30%|██▉ | 594/2000 [10:30<21:06, 1.11it/s, loss=0.585]" ] }, { @@ -22064,7 +22042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 595/2000 [08:33<18:07, 1.29it/s, loss=0.706]" + "training until 2000: 30%|██▉ | 595/2000 [10:31<21:53, 1.07it/s, loss=0.585]" ] }, { @@ -22072,7 +22050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 595/2000 [08:33<18:07, 1.29it/s, loss=0.734]" + "training until 2000: 30%|██▉ | 595/2000 [10:31<21:53, 1.07it/s, loss=0.566]" ] }, { @@ -22080,7 +22058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 596/2000 [08:34<17:52, 1.31it/s, loss=0.734]" + "training until 2000: 30%|██▉ | 596/2000 [10:32<22:02, 1.06it/s, loss=0.566]" ] }, { @@ -22088,7 +22066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 596/2000 [08:34<17:52, 1.31it/s, loss=0.674]" + "training until 2000: 30%|██▉ | 596/2000 [10:32<22:02, 1.06it/s, loss=0.641]" ] }, { @@ -22096,7 +22074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 597/2000 [08:34<16:01, 1.46it/s, loss=0.674]" + "training until 2000: 30%|██▉ | 597/2000 [10:33<22:30, 1.04it/s, loss=0.641]" ] }, { @@ -22104,7 +22082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 597/2000 [08:34<16:01, 1.46it/s, loss=0.692]" + "training until 2000: 30%|██▉ | 597/2000 [10:33<22:30, 1.04it/s, loss=0.579]" ] }, { @@ -22112,7 +22090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 598/2000 [08:35<16:57, 1.38it/s, loss=0.692]" + "training until 2000: 30%|██▉ | 598/2000 [10:34<21:13, 1.10it/s, loss=0.579]" ] }, { @@ -22120,7 +22098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 598/2000 [08:35<16:57, 1.38it/s, loss=0.757]" + "training until 2000: 30%|██▉ | 598/2000 [10:34<21:13, 1.10it/s, loss=0.613]" ] }, { @@ -22128,7 +22106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 599/2000 [08:36<16:44, 1.39it/s, loss=0.757]" + "training until 2000: 30%|██▉ | 599/2000 [10:35<23:08, 1.01it/s, loss=0.613]" ] }, { @@ -22136,7 +22114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|██▉ | 599/2000 [08:36<16:44, 1.39it/s, loss=0.69] " + "training until 2000: 30%|██▉ | 599/2000 [10:35<23:08, 1.01it/s, loss=0.608]" ] }, { @@ -22144,7 +22122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 600/2000 [08:37<18:28, 1.26it/s, loss=0.69]" + "training until 2000: 30%|███ | 600/2000 [10:36<21:09, 1.10it/s, loss=0.608]" ] }, { @@ -22152,7 +22130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 600/2000 [08:37<18:28, 1.26it/s, loss=0.693]" + "training until 2000: 30%|███ | 600/2000 [10:36<21:09, 1.10it/s, loss=0.551]" ] }, { @@ -22160,7 +22138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 601/2000 [08:38<20:03, 1.16it/s, loss=0.693]" + "training until 2000: 30%|███ | 601/2000 [10:37<23:42, 1.02s/it, loss=0.551]" ] }, { @@ -22168,7 +22146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 601/2000 [08:38<20:03, 1.16it/s, loss=0.716]" + "training until 2000: 30%|███ | 601/2000 [10:37<23:42, 1.02s/it, loss=0.541]" ] }, { @@ -22176,7 +22154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 602/2000 [08:38<18:14, 1.28it/s, loss=0.716]" + "training until 2000: 30%|███ | 602/2000 [10:38<22:34, 1.03it/s, loss=0.541]" ] }, { @@ -22184,7 +22162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 602/2000 [08:38<18:14, 1.28it/s, loss=0.713]" + "training until 2000: 30%|███ | 602/2000 [10:38<22:34, 1.03it/s, loss=0.607]" ] }, { @@ -22192,7 +22170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 603/2000 [08:39<19:27, 1.20it/s, loss=0.713]" + "training until 2000: 30%|███ | 603/2000 [10:39<22:08, 1.05it/s, loss=0.607]" ] }, { @@ -22200,7 +22178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 603/2000 [08:39<19:27, 1.20it/s, loss=0.723]" + "training until 2000: 30%|███ | 603/2000 [10:39<22:08, 1.05it/s, loss=0.64] " ] }, { @@ -22208,7 +22186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 604/2000 [08:40<18:25, 1.26it/s, loss=0.723]" + "training until 2000: 30%|███ | 604/2000 [10:40<22:17, 1.04it/s, loss=0.64]" ] }, { @@ -22216,7 +22194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 604/2000 [08:40<18:25, 1.26it/s, loss=0.709]" + "training until 2000: 30%|███ | 604/2000 [10:40<22:17, 1.04it/s, loss=0.604]" ] }, { @@ -22224,7 +22202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 605/2000 [08:41<21:26, 1.08it/s, loss=0.709]" + "training until 2000: 30%|███ | 605/2000 [10:40<21:20, 1.09it/s, loss=0.604]" ] }, { @@ -22232,7 +22210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 605/2000 [08:41<21:26, 1.08it/s, loss=0.711]" + "training until 2000: 30%|███ | 605/2000 [10:40<21:20, 1.09it/s, loss=0.674]" ] }, { @@ -22240,7 +22218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 606/2000 [08:42<22:03, 1.05it/s, loss=0.711]" + "training until 2000: 30%|███ | 606/2000 [10:41<21:59, 1.06it/s, loss=0.674]" ] }, { @@ -22248,7 +22226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 606/2000 [08:42<22:03, 1.05it/s, loss=0.693]" + "training until 2000: 30%|███ | 606/2000 [10:41<21:59, 1.06it/s, loss=0.615]" ] }, { @@ -22256,7 +22234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 607/2000 [08:43<20:11, 1.15it/s, loss=0.693]" + "training until 2000: 30%|███ | 607/2000 [10:42<20:15, 1.15it/s, loss=0.615]" ] }, { @@ -22264,7 +22242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 607/2000 [08:43<20:11, 1.15it/s, loss=0.717]" + "training until 2000: 30%|███ | 607/2000 [10:42<20:15, 1.15it/s, loss=0.529]" ] }, { @@ -22272,7 +22250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 608/2000 [08:43<18:52, 1.23it/s, loss=0.717]" + "training until 2000: 30%|███ | 608/2000 [10:43<22:02, 1.05it/s, loss=0.529]" ] }, { @@ -22280,7 +22258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 608/2000 [08:43<18:52, 1.23it/s, loss=0.76] " + "training until 2000: 30%|███ | 608/2000 [10:43<22:02, 1.05it/s, loss=0.561]" ] }, { @@ -22288,7 +22266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 609/2000 [08:44<17:54, 1.29it/s, loss=0.76]" + "training until 2000: 30%|███ | 609/2000 [10:44<21:03, 1.10it/s, loss=0.561]" ] }, { @@ -22296,7 +22274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 609/2000 [08:44<17:54, 1.29it/s, loss=0.759]" + "training until 2000: 30%|███ | 609/2000 [10:44<21:03, 1.10it/s, loss=0.608]" ] }, { @@ -22304,7 +22282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 610/2000 [08:45<18:18, 1.27it/s, loss=0.759]" + "training until 2000: 30%|███ | 610/2000 [10:45<19:55, 1.16it/s, loss=0.608]" ] }, { @@ -22312,7 +22290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 30%|███ | 610/2000 [08:45<18:18, 1.27it/s, loss=0.692]" + "training until 2000: 30%|███ | 610/2000 [10:45<19:55, 1.16it/s, loss=0.587]" ] }, { @@ -22320,7 +22298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 611/2000 [08:46<18:19, 1.26it/s, loss=0.692]" + "training until 2000: 31%|███ | 611/2000 [10:45<18:18, 1.26it/s, loss=0.587]" ] }, { @@ -22328,7 +22306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 611/2000 [08:46<18:19, 1.26it/s, loss=0.697]" + "training until 2000: 31%|███ | 611/2000 [10:45<18:18, 1.26it/s, loss=0.564]" ] }, { @@ -22336,7 +22314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 612/2000 [08:47<18:55, 1.22it/s, loss=0.697]" + "training until 2000: 31%|███ | 612/2000 [10:47<21:34, 1.07it/s, loss=0.564]" ] }, { @@ -22344,7 +22322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 612/2000 [08:47<18:55, 1.22it/s, loss=0.725]" + "training until 2000: 31%|███ | 612/2000 [10:47<21:34, 1.07it/s, loss=0.579]" ] }, { @@ -22352,7 +22330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 613/2000 [08:47<18:53, 1.22it/s, loss=0.725]" + "training until 2000: 31%|███ | 613/2000 [10:48<22:33, 1.02it/s, loss=0.579]" ] }, { @@ -22360,7 +22338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 613/2000 [08:47<18:53, 1.22it/s, loss=0.661]" + "training until 2000: 31%|███ | 613/2000 [10:48<22:33, 1.02it/s, loss=0.672]" ] }, { @@ -22368,7 +22346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 614/2000 [08:48<16:19, 1.42it/s, loss=0.661]" + "training until 2000: 31%|███ | 614/2000 [10:49<23:53, 1.03s/it, loss=0.672]" ] }, { @@ -22376,7 +22354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 614/2000 [08:48<16:19, 1.42it/s, loss=0.701]" + "training until 2000: 31%|███ | 614/2000 [10:49<23:53, 1.03s/it, loss=0.543]" ] }, { @@ -22384,7 +22362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 615/2000 [08:48<15:05, 1.53it/s, loss=0.701]" + "training until 2000: 31%|███ | 615/2000 [10:50<23:48, 1.03s/it, loss=0.543]" ] }, { @@ -22392,7 +22370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 615/2000 [08:48<15:05, 1.53it/s, loss=0.683]" + "training until 2000: 31%|███ | 615/2000 [10:50<23:48, 1.03s/it, loss=0.567]" ] }, { @@ -22400,7 +22378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 616/2000 [08:49<16:50, 1.37it/s, loss=0.683]" + "training until 2000: 31%|███ | 616/2000 [10:51<23:00, 1.00it/s, loss=0.567]" ] }, { @@ -22408,7 +22386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 616/2000 [08:49<16:50, 1.37it/s, loss=0.693]" + "training until 2000: 31%|███ | 616/2000 [10:51<23:00, 1.00it/s, loss=0.573]" ] }, { @@ -22416,7 +22394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 617/2000 [08:50<15:55, 1.45it/s, loss=0.693]" + "training until 2000: 31%|███ | 617/2000 [10:52<24:57, 1.08s/it, loss=0.573]" ] }, { @@ -22424,7 +22402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 617/2000 [08:50<15:55, 1.45it/s, loss=0.659]" + "training until 2000: 31%|███ | 617/2000 [10:52<24:57, 1.08s/it, loss=0.689]" ] }, { @@ -22432,7 +22410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 618/2000 [08:51<16:43, 1.38it/s, loss=0.659]" + "training until 2000: 31%|███ | 618/2000 [10:54<29:01, 1.26s/it, loss=0.689]" ] }, { @@ -22440,7 +22418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 618/2000 [08:51<16:43, 1.38it/s, loss=0.669]" + "training until 2000: 31%|███ | 618/2000 [10:54<29:01, 1.26s/it, loss=0.642]" ] }, { @@ -22448,7 +22426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 619/2000 [08:52<17:37, 1.31it/s, loss=0.669]" + "training until 2000: 31%|███ | 619/2000 [10:56<31:31, 1.37s/it, loss=0.642]" ] }, { @@ -22456,7 +22434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 619/2000 [08:52<17:37, 1.31it/s, loss=0.684]" + "training until 2000: 31%|███ | 619/2000 [10:56<31:31, 1.37s/it, loss=0.545]" ] }, { @@ -22464,7 +22442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 620/2000 [08:52<16:24, 1.40it/s, loss=0.684]" + "training until 2000: 31%|███ | 620/2000 [10:56<27:25, 1.19s/it, loss=0.545]" ] }, { @@ -22472,7 +22450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 620/2000 [08:52<16:24, 1.40it/s, loss=0.708]" + "training until 2000: 31%|███ | 620/2000 [10:56<27:25, 1.19s/it, loss=0.558]" ] }, { @@ -22480,7 +22458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 621/2000 [08:53<15:56, 1.44it/s, loss=0.708]" + "training until 2000: 31%|███ | 621/2000 [10:57<26:43, 1.16s/it, loss=0.558]" ] }, { @@ -22488,7 +22466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 621/2000 [08:53<15:56, 1.44it/s, loss=0.665]" + "training until 2000: 31%|███ | 621/2000 [10:57<26:43, 1.16s/it, loss=0.611]" ] }, { @@ -22496,7 +22474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 622/2000 [08:54<20:02, 1.15it/s, loss=0.665]" + "training until 2000: 31%|███ | 622/2000 [10:58<25:09, 1.10s/it, loss=0.611]" ] }, { @@ -22504,7 +22482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 622/2000 [08:54<20:02, 1.15it/s, loss=0.688]" + "training until 2000: 31%|███ | 622/2000 [10:58<25:09, 1.10s/it, loss=0.542]" ] }, { @@ -22512,7 +22490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 623/2000 [08:55<19:02, 1.21it/s, loss=0.688]" + "training until 2000: 31%|███ | 623/2000 [11:00<28:50, 1.26s/it, loss=0.542]" ] }, { @@ -22520,7 +22498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 623/2000 [08:55<19:02, 1.21it/s, loss=0.728]" + "training until 2000: 31%|███ | 623/2000 [11:00<28:50, 1.26s/it, loss=0.637]" ] }, { @@ -22528,7 +22506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 624/2000 [08:56<18:57, 1.21it/s, loss=0.728]" + "training until 2000: 31%|███ | 624/2000 [11:00<23:33, 1.03s/it, loss=0.637]" ] }, { @@ -22536,7 +22514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███ | 624/2000 [08:56<18:57, 1.21it/s, loss=0.668]" + "training until 2000: 31%|███ | 624/2000 [11:00<23:33, 1.03s/it, loss=0.528]" ] }, { @@ -22544,7 +22522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 625/2000 [08:57<19:34, 1.17it/s, loss=0.668]" + "training until 2000: 31%|███▏ | 625/2000 [11:02<24:05, 1.05s/it, loss=0.528]" ] }, { @@ -22552,7 +22530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 625/2000 [08:57<19:34, 1.17it/s, loss=0.684]" + "training until 2000: 31%|███▏ | 625/2000 [11:02<24:05, 1.05s/it, loss=0.574]" ] }, { @@ -22560,7 +22538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 626/2000 [08:57<19:24, 1.18it/s, loss=0.684]" + "training until 2000: 31%|███▏ | 626/2000 [11:03<26:58, 1.18s/it, loss=0.574]" ] }, { @@ -22568,7 +22546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 626/2000 [08:57<19:24, 1.18it/s, loss=0.695]" + "training until 2000: 31%|███▏ | 626/2000 [11:03<26:58, 1.18s/it, loss=0.599]" ] }, { @@ -22576,7 +22554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 627/2000 [08:58<19:10, 1.19it/s, loss=0.695]" + "training until 2000: 31%|███▏ | 627/2000 [11:04<25:38, 1.12s/it, loss=0.599]" ] }, { @@ -22584,7 +22562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 627/2000 [08:58<19:10, 1.19it/s, loss=0.729]" + "training until 2000: 31%|███▏ | 627/2000 [11:04<25:38, 1.12s/it, loss=0.576]" ] }, { @@ -22592,7 +22570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 628/2000 [08:59<17:09, 1.33it/s, loss=0.729]" + "training until 2000: 31%|███▏ | 628/2000 [11:05<25:20, 1.11s/it, loss=0.576]" ] }, { @@ -22600,7 +22578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 628/2000 [08:59<17:09, 1.33it/s, loss=0.685]" + "training until 2000: 31%|███▏ | 628/2000 [11:05<25:20, 1.11s/it, loss=0.608]" ] }, { @@ -22608,7 +22586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 629/2000 [09:00<19:30, 1.17it/s, loss=0.685]" + "training until 2000: 31%|███▏ | 629/2000 [11:06<26:09, 1.14s/it, loss=0.608]" ] }, { @@ -22616,7 +22594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 31%|███▏ | 629/2000 [09:00<19:30, 1.17it/s, loss=0.711]" + "training until 2000: 31%|███▏ | 629/2000 [11:06<26:09, 1.14s/it, loss=0.575]" ] }, { @@ -22624,7 +22602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 630/2000 [09:00<17:50, 1.28it/s, loss=0.711]" + "training until 2000: 32%|███▏ | 630/2000 [11:07<24:48, 1.09s/it, loss=0.575]" ] }, { @@ -22632,7 +22610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 630/2000 [09:00<17:50, 1.28it/s, loss=0.74] " + "training until 2000: 32%|███▏ | 630/2000 [11:07<24:48, 1.09s/it, loss=0.583]" ] }, { @@ -22640,7 +22618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 631/2000 [09:01<16:20, 1.40it/s, loss=0.74]" + "training until 2000: 32%|███▏ | 631/2000 [11:08<23:51, 1.05s/it, loss=0.583]" ] }, { @@ -22648,7 +22626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 631/2000 [09:01<16:20, 1.40it/s, loss=0.686]" + "training until 2000: 32%|███▏ | 631/2000 [11:08<23:51, 1.05s/it, loss=0.563]" ] }, { @@ -22656,7 +22634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 632/2000 [09:02<15:11, 1.50it/s, loss=0.686]" + "training until 2000: 32%|███▏ | 632/2000 [11:10<25:21, 1.11s/it, loss=0.563]" ] }, { @@ -22664,7 +22642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 632/2000 [09:02<15:11, 1.50it/s, loss=0.727]" + "training until 2000: 32%|███▏ | 632/2000 [11:10<25:21, 1.11s/it, loss=0.579]" ] }, { @@ -22672,7 +22650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 633/2000 [09:02<16:14, 1.40it/s, loss=0.727]" + "training until 2000: 32%|███▏ | 633/2000 [11:11<24:39, 1.08s/it, loss=0.579]" ] }, { @@ -22680,7 +22658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 633/2000 [09:02<16:14, 1.40it/s, loss=0.663]" + "training until 2000: 32%|███▏ | 633/2000 [11:11<24:39, 1.08s/it, loss=0.575]" ] }, { @@ -22688,7 +22666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 634/2000 [09:03<18:18, 1.24it/s, loss=0.663]" + "training until 2000: 32%|███▏ | 634/2000 [11:11<22:01, 1.03it/s, loss=0.575]" ] }, { @@ -22696,7 +22674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 634/2000 [09:03<18:18, 1.24it/s, loss=0.686]" + "training until 2000: 32%|███▏ | 634/2000 [11:11<22:01, 1.03it/s, loss=0.615]" ] }, { @@ -22704,7 +22682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 635/2000 [09:04<18:19, 1.24it/s, loss=0.686]" + "training until 2000: 32%|███▏ | 635/2000 [11:12<22:41, 1.00it/s, loss=0.615]" ] }, { @@ -22712,7 +22690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 635/2000 [09:04<18:19, 1.24it/s, loss=0.67] " + "training until 2000: 32%|███▏ | 635/2000 [11:12<22:41, 1.00it/s, loss=0.583]" ] }, { @@ -22720,7 +22698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 636/2000 [09:05<16:05, 1.41it/s, loss=0.67]" + "training until 2000: 32%|███▏ | 636/2000 [11:13<22:48, 1.00s/it, loss=0.583]" ] }, { @@ -22728,7 +22706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 636/2000 [09:05<16:05, 1.41it/s, loss=0.674]" + "training until 2000: 32%|███▏ | 636/2000 [11:13<22:48, 1.00s/it, loss=0.517]" ] }, { @@ -22736,7 +22714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 637/2000 [09:06<17:41, 1.28it/s, loss=0.674]" + "training until 2000: 32%|███▏ | 637/2000 [11:14<21:42, 1.05it/s, loss=0.517]" ] }, { @@ -22744,7 +22722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 637/2000 [09:06<17:41, 1.28it/s, loss=0.665]" + "training until 2000: 32%|███▏ | 637/2000 [11:14<21:42, 1.05it/s, loss=0.535]" ] }, { @@ -22752,7 +22730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 638/2000 [09:06<17:16, 1.31it/s, loss=0.665]" + "training until 2000: 32%|███▏ | 638/2000 [11:15<23:55, 1.05s/it, loss=0.535]" ] }, { @@ -22760,7 +22738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 638/2000 [09:06<17:16, 1.31it/s, loss=0.691]" + "training until 2000: 32%|███▏ | 638/2000 [11:15<23:55, 1.05s/it, loss=0.574]" ] }, { @@ -22768,7 +22746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 639/2000 [09:07<17:54, 1.27it/s, loss=0.691]" + "training until 2000: 32%|███▏ | 639/2000 [11:16<23:51, 1.05s/it, loss=0.574]" ] }, { @@ -22776,7 +22754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 639/2000 [09:07<17:54, 1.27it/s, loss=0.683]" + "training until 2000: 32%|███▏ | 639/2000 [11:16<23:51, 1.05s/it, loss=0.649]" ] }, { @@ -22784,7 +22762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 640/2000 [09:08<18:13, 1.24it/s, loss=0.683]" + "training until 2000: 32%|███▏ | 640/2000 [11:18<24:35, 1.08s/it, loss=0.649]" ] }, { @@ -22792,7 +22770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 640/2000 [09:08<18:13, 1.24it/s, loss=0.715]" + "training until 2000: 32%|███▏ | 640/2000 [11:18<24:35, 1.08s/it, loss=0.538]" ] }, { @@ -22800,7 +22778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 641/2000 [09:09<19:47, 1.14it/s, loss=0.715]" + "training until 2000: 32%|███▏ | 641/2000 [11:18<22:53, 1.01s/it, loss=0.538]" ] }, { @@ -22808,7 +22786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 641/2000 [09:09<19:47, 1.14it/s, loss=0.658]" + "training until 2000: 32%|███▏ | 641/2000 [11:18<22:53, 1.01s/it, loss=0.626]" ] }, { @@ -22816,7 +22794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 642/2000 [09:10<20:03, 1.13it/s, loss=0.658]" + "training until 2000: 32%|███▏ | 642/2000 [11:19<22:26, 1.01it/s, loss=0.626]" ] }, { @@ -22824,7 +22802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 642/2000 [09:10<20:03, 1.13it/s, loss=0.68] " + "training until 2000: 32%|███▏ | 642/2000 [11:19<22:26, 1.01it/s, loss=0.644]" ] }, { @@ -22832,7 +22810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 643/2000 [09:11<18:17, 1.24it/s, loss=0.68]" + "training until 2000: 32%|███▏ | 643/2000 [11:20<20:02, 1.13it/s, loss=0.644]" ] }, { @@ -22840,7 +22818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 643/2000 [09:11<18:17, 1.24it/s, loss=0.661]" + "training until 2000: 32%|███▏ | 643/2000 [11:20<20:02, 1.13it/s, loss=0.535]" ] }, { @@ -22848,7 +22826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 644/2000 [09:11<16:28, 1.37it/s, loss=0.661]" + "training until 2000: 32%|███▏ | 644/2000 [11:21<18:46, 1.20it/s, loss=0.535]" ] }, { @@ -22856,7 +22834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 644/2000 [09:11<16:28, 1.37it/s, loss=0.666]" + "training until 2000: 32%|███▏ | 644/2000 [11:21<18:46, 1.20it/s, loss=0.545]" ] }, { @@ -22864,7 +22842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 645/2000 [09:12<17:42, 1.27it/s, loss=0.666]" + "training until 2000: 32%|███▏ | 645/2000 [11:21<17:48, 1.27it/s, loss=0.545]" ] }, { @@ -22872,7 +22850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 645/2000 [09:12<17:42, 1.27it/s, loss=0.679]" + "training until 2000: 32%|███▏ | 645/2000 [11:21<17:48, 1.27it/s, loss=0.587]" ] }, { @@ -22880,7 +22858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 646/2000 [09:13<16:34, 1.36it/s, loss=0.679]" + "training until 2000: 32%|███▏ | 646/2000 [11:22<18:45, 1.20it/s, loss=0.587]" ] }, { @@ -22888,7 +22866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 646/2000 [09:13<16:34, 1.36it/s, loss=0.692]" + "training until 2000: 32%|███▏ | 646/2000 [11:22<18:45, 1.20it/s, loss=0.561]" ] }, { @@ -22896,7 +22874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 647/2000 [09:13<15:48, 1.43it/s, loss=0.692]" + "training until 2000: 32%|███▏ | 647/2000 [11:23<19:55, 1.13it/s, loss=0.561]" ] }, { @@ -22904,7 +22882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 647/2000 [09:13<15:48, 1.43it/s, loss=0.683]" + "training until 2000: 32%|███▏ | 647/2000 [11:23<19:55, 1.13it/s, loss=0.519]" ] }, { @@ -22912,7 +22890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 648/2000 [09:14<14:49, 1.52it/s, loss=0.683]" + "training until 2000: 32%|███▏ | 648/2000 [11:24<19:49, 1.14it/s, loss=0.519]" ] }, { @@ -22920,7 +22898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 648/2000 [09:14<14:49, 1.52it/s, loss=0.698]" + "training until 2000: 32%|███▏ | 648/2000 [11:24<19:49, 1.14it/s, loss=0.56] " ] }, { @@ -22928,7 +22906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 649/2000 [09:14<13:57, 1.61it/s, loss=0.698]" + "training until 2000: 32%|███▏ | 649/2000 [11:25<20:06, 1.12it/s, loss=0.56]" ] }, { @@ -22936,7 +22914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▏ | 649/2000 [09:14<13:57, 1.61it/s, loss=0.669]" + "training until 2000: 32%|███▏ | 649/2000 [11:25<20:06, 1.12it/s, loss=0.517]" ] }, { @@ -22944,7 +22922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▎ | 650/2000 [09:15<16:51, 1.33it/s, loss=0.669]" + "training until 2000: 32%|███▎ | 650/2000 [11:26<19:56, 1.13it/s, loss=0.517]" ] }, { @@ -22952,7 +22930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 32%|███▎ | 650/2000 [09:15<16:51, 1.33it/s, loss=0.656]" + "training until 2000: 32%|███▎ | 650/2000 [11:26<19:56, 1.13it/s, loss=0.561]" ] }, { @@ -22960,7 +22938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 651/2000 [09:16<15:46, 1.43it/s, loss=0.656]" + "training until 2000: 33%|███▎ | 651/2000 [11:27<22:26, 1.00it/s, loss=0.561]" ] }, { @@ -22968,7 +22946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 651/2000 [09:16<15:46, 1.43it/s, loss=0.649]" + "training until 2000: 33%|███▎ | 651/2000 [11:27<22:26, 1.00it/s, loss=0.579]" ] }, { @@ -22976,7 +22954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 652/2000 [09:17<16:27, 1.37it/s, loss=0.649]" + "training until 2000: 33%|███▎ | 652/2000 [11:29<28:18, 1.26s/it, loss=0.579]" ] }, { @@ -22984,7 +22962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 652/2000 [09:17<16:27, 1.37it/s, loss=0.716]" + "training until 2000: 33%|███▎ | 652/2000 [11:29<28:18, 1.26s/it, loss=0.551]" ] }, { @@ -22992,7 +22970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 653/2000 [09:18<17:20, 1.29it/s, loss=0.716]" + "training until 2000: 33%|███▎ | 653/2000 [11:31<29:58, 1.33s/it, loss=0.551]" ] }, { @@ -23000,7 +22978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 653/2000 [09:18<17:20, 1.29it/s, loss=0.649]" + "training until 2000: 33%|███▎ | 653/2000 [11:31<29:58, 1.33s/it, loss=0.605]" ] }, { @@ -23008,7 +22986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 654/2000 [09:18<16:55, 1.33it/s, loss=0.649]" + "training until 2000: 33%|███▎ | 654/2000 [11:32<32:28, 1.45s/it, loss=0.605]" ] }, { @@ -23016,7 +22994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 654/2000 [09:18<16:55, 1.33it/s, loss=0.693]" + "training until 2000: 33%|███▎ | 654/2000 [11:32<32:28, 1.45s/it, loss=0.521]" ] }, { @@ -23024,7 +23002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 655/2000 [09:19<15:09, 1.48it/s, loss=0.693]" + "training until 2000: 33%|███▎ | 655/2000 [11:33<29:08, 1.30s/it, loss=0.521]" ] }, { @@ -23032,7 +23010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 655/2000 [09:19<15:09, 1.48it/s, loss=0.716]" + "training until 2000: 33%|███▎ | 655/2000 [11:33<29:08, 1.30s/it, loss=0.657]" ] }, { @@ -23040,7 +23018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 656/2000 [09:20<17:10, 1.30it/s, loss=0.716]" + "training until 2000: 33%|███▎ | 656/2000 [11:34<24:48, 1.11s/it, loss=0.657]" ] }, { @@ -23048,7 +23026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 656/2000 [09:20<17:10, 1.30it/s, loss=0.716]" + "training until 2000: 33%|███▎ | 656/2000 [11:34<24:48, 1.11s/it, loss=0.558]" ] }, { @@ -23056,7 +23034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 657/2000 [09:20<15:38, 1.43it/s, loss=0.716]" + "training until 2000: 33%|███▎ | 657/2000 [11:35<24:28, 1.09s/it, loss=0.558]" ] }, { @@ -23064,7 +23042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 657/2000 [09:20<15:38, 1.43it/s, loss=0.656]" + "training until 2000: 33%|███▎ | 657/2000 [11:35<24:28, 1.09s/it, loss=0.473]" ] }, { @@ -23072,7 +23050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 658/2000 [09:21<17:28, 1.28it/s, loss=0.656]" + "training until 2000: 33%|███▎ | 658/2000 [11:36<22:13, 1.01it/s, loss=0.473]" ] }, { @@ -23080,7 +23058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 658/2000 [09:21<17:28, 1.28it/s, loss=0.638]" + "training until 2000: 33%|███▎ | 658/2000 [11:36<22:13, 1.01it/s, loss=0.577]" ] }, { @@ -23088,7 +23066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 659/2000 [09:22<17:56, 1.25it/s, loss=0.638]" + "training until 2000: 33%|███▎ | 659/2000 [11:37<24:02, 1.08s/it, loss=0.577]" ] }, { @@ -23096,7 +23074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 659/2000 [09:22<17:56, 1.25it/s, loss=0.711]" + "training until 2000: 33%|███▎ | 659/2000 [11:37<24:02, 1.08s/it, loss=0.625]" ] }, { @@ -23104,7 +23082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 660/2000 [09:23<17:03, 1.31it/s, loss=0.711]" + "training until 2000: 33%|███▎ | 660/2000 [11:38<25:05, 1.12s/it, loss=0.625]" ] }, { @@ -23112,7 +23090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 660/2000 [09:23<17:03, 1.31it/s, loss=0.663]" + "training until 2000: 33%|███▎ | 660/2000 [11:38<25:05, 1.12s/it, loss=0.59] " ] }, { @@ -23120,7 +23098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 661/2000 [09:23<15:24, 1.45it/s, loss=0.663]" + "training until 2000: 33%|███▎ | 661/2000 [11:39<22:11, 1.01it/s, loss=0.59]" ] }, { @@ -23128,7 +23106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 661/2000 [09:23<15:24, 1.45it/s, loss=0.683]" + "training until 2000: 33%|███▎ | 661/2000 [11:39<22:11, 1.01it/s, loss=0.5] " ] }, { @@ -23136,7 +23114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 662/2000 [09:24<15:35, 1.43it/s, loss=0.683]" + "training until 2000: 33%|███▎ | 662/2000 [11:40<22:00, 1.01it/s, loss=0.5]" ] }, { @@ -23144,7 +23122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 662/2000 [09:24<15:35, 1.43it/s, loss=0.681]" + "training until 2000: 33%|███▎ | 662/2000 [11:40<22:00, 1.01it/s, loss=0.609]" ] }, { @@ -23152,7 +23130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 663/2000 [09:25<16:45, 1.33it/s, loss=0.681]" + "training until 2000: 33%|███▎ | 663/2000 [11:41<19:25, 1.15it/s, loss=0.609]" ] }, { @@ -23160,7 +23138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 663/2000 [09:25<16:45, 1.33it/s, loss=0.657]" + "training until 2000: 33%|███▎ | 663/2000 [11:41<19:25, 1.15it/s, loss=0.537]" ] }, { @@ -23168,7 +23146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 664/2000 [09:26<18:32, 1.20it/s, loss=0.657]" + "training until 2000: 33%|███▎ | 664/2000 [11:41<18:34, 1.20it/s, loss=0.537]" ] }, { @@ -23176,7 +23154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 664/2000 [09:26<18:32, 1.20it/s, loss=0.669]" + "training until 2000: 33%|███▎ | 664/2000 [11:41<18:34, 1.20it/s, loss=0.583]" ] }, { @@ -23184,7 +23162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 665/2000 [09:27<17:00, 1.31it/s, loss=0.669]" + "training until 2000: 33%|███▎ | 665/2000 [11:42<19:00, 1.17it/s, loss=0.583]" ] }, { @@ -23192,7 +23170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 665/2000 [09:27<17:00, 1.31it/s, loss=0.65] " + "training until 2000: 33%|███▎ | 665/2000 [11:42<19:00, 1.17it/s, loss=0.563]" ] }, { @@ -23200,7 +23178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 666/2000 [09:28<17:30, 1.27it/s, loss=0.65]" + "training until 2000: 33%|███▎ | 666/2000 [11:43<21:19, 1.04it/s, loss=0.563]" ] }, { @@ -23208,7 +23186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 666/2000 [09:28<17:30, 1.27it/s, loss=0.694]" + "training until 2000: 33%|███▎ | 666/2000 [11:43<21:19, 1.04it/s, loss=0.645]" ] }, { @@ -23216,7 +23194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 667/2000 [09:28<16:27, 1.35it/s, loss=0.694]" + "training until 2000: 33%|███▎ | 667/2000 [11:45<24:06, 1.09s/it, loss=0.645]" ] }, { @@ -23224,7 +23202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 667/2000 [09:28<16:27, 1.35it/s, loss=0.674]" + "training until 2000: 33%|███▎ | 667/2000 [11:45<24:06, 1.09s/it, loss=0.523]" ] }, { @@ -23232,7 +23210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 668/2000 [09:29<16:40, 1.33it/s, loss=0.674]" + "training until 2000: 33%|███▎ | 668/2000 [11:46<24:11, 1.09s/it, loss=0.523]" ] }, { @@ -23240,7 +23218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 668/2000 [09:29<16:40, 1.33it/s, loss=0.702]" + "training until 2000: 33%|███▎ | 668/2000 [11:46<24:11, 1.09s/it, loss=0.635]" ] }, { @@ -23248,7 +23226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 669/2000 [09:30<15:30, 1.43it/s, loss=0.702]" + "training until 2000: 33%|███▎ | 669/2000 [11:47<23:48, 1.07s/it, loss=0.635]" ] }, { @@ -23256,7 +23234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 33%|███▎ | 669/2000 [09:30<15:30, 1.43it/s, loss=0.678]" + "training until 2000: 33%|███▎ | 669/2000 [11:47<23:48, 1.07s/it, loss=0.536]" ] }, { @@ -23264,7 +23242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 670/2000 [09:31<19:47, 1.12it/s, loss=0.678]" + "training until 2000: 34%|███▎ | 670/2000 [11:48<20:32, 1.08it/s, loss=0.536]" ] }, { @@ -23272,7 +23250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 670/2000 [09:31<19:47, 1.12it/s, loss=0.679]" + "training until 2000: 34%|███▎ | 670/2000 [11:48<20:32, 1.08it/s, loss=0.553]" ] }, { @@ -23280,7 +23258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 671/2000 [09:32<19:30, 1.14it/s, loss=0.679]" + "training until 2000: 34%|███▎ | 671/2000 [11:49<20:44, 1.07it/s, loss=0.553]" ] }, { @@ -23288,7 +23266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 671/2000 [09:32<19:30, 1.14it/s, loss=0.649]" + "training until 2000: 34%|███▎ | 671/2000 [11:49<20:44, 1.07it/s, loss=0.578]" ] }, { @@ -23296,7 +23274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 672/2000 [09:32<17:53, 1.24it/s, loss=0.649]" + "training until 2000: 34%|███▎ | 672/2000 [11:50<23:20, 1.05s/it, loss=0.578]" ] }, { @@ -23304,7 +23282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 672/2000 [09:32<17:53, 1.24it/s, loss=0.71] " + "training until 2000: 34%|███▎ | 672/2000 [11:50<23:20, 1.05s/it, loss=0.554]" ] }, { @@ -23312,7 +23290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 673/2000 [09:33<16:08, 1.37it/s, loss=0.71]" + "training until 2000: 34%|███▎ | 673/2000 [11:51<23:42, 1.07s/it, loss=0.554]" ] }, { @@ -23320,7 +23298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 673/2000 [09:33<16:08, 1.37it/s, loss=0.646]" + "training until 2000: 34%|███▎ | 673/2000 [11:51<23:42, 1.07s/it, loss=0.495]" ] }, { @@ -23328,7 +23306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 674/2000 [09:33<14:31, 1.52it/s, loss=0.646]" + "training until 2000: 34%|███▎ | 674/2000 [11:52<22:37, 1.02s/it, loss=0.495]" ] }, { @@ -23336,7 +23314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▎ | 674/2000 [09:33<14:31, 1.52it/s, loss=0.659]" + "training until 2000: 34%|███▎ | 674/2000 [11:52<22:37, 1.02s/it, loss=0.657]" ] }, { @@ -23344,7 +23322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 675/2000 [09:34<17:02, 1.30it/s, loss=0.659]" + "training until 2000: 34%|███▍ | 675/2000 [11:53<20:44, 1.07it/s, loss=0.657]" ] }, { @@ -23352,7 +23330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 675/2000 [09:34<17:02, 1.30it/s, loss=0.678]" + "training until 2000: 34%|███▍ | 675/2000 [11:53<20:44, 1.07it/s, loss=0.604]" ] }, { @@ -23360,7 +23338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 676/2000 [09:35<17:23, 1.27it/s, loss=0.678]" + "training until 2000: 34%|███▍ | 676/2000 [11:54<20:45, 1.06it/s, loss=0.604]" ] }, { @@ -23368,7 +23346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 676/2000 [09:35<17:23, 1.27it/s, loss=0.699]" + "training until 2000: 34%|███▍ | 676/2000 [11:54<20:45, 1.06it/s, loss=0.582]" ] }, { @@ -23376,7 +23354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 677/2000 [09:36<19:27, 1.13it/s, loss=0.699]" + "training until 2000: 34%|███▍ | 677/2000 [11:54<20:14, 1.09it/s, loss=0.582]" ] }, { @@ -23384,7 +23362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 677/2000 [09:36<19:27, 1.13it/s, loss=0.68] " + "training until 2000: 34%|███▍ | 677/2000 [11:54<20:14, 1.09it/s, loss=0.524]" ] }, { @@ -23392,7 +23370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 678/2000 [09:37<17:25, 1.27it/s, loss=0.68]" + "training until 2000: 34%|███▍ | 678/2000 [11:55<20:30, 1.07it/s, loss=0.524]" ] }, { @@ -23400,7 +23378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 678/2000 [09:37<17:25, 1.27it/s, loss=0.67]" + "training until 2000: 34%|███▍ | 678/2000 [11:55<20:30, 1.07it/s, loss=0.566]" ] }, { @@ -23408,7 +23386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 679/2000 [09:38<17:16, 1.27it/s, loss=0.67]" + "training until 2000: 34%|███▍ | 679/2000 [11:56<20:12, 1.09it/s, loss=0.566]" ] }, { @@ -23416,7 +23394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 679/2000 [09:38<17:16, 1.27it/s, loss=0.704]" + "training until 2000: 34%|███▍ | 679/2000 [11:56<20:12, 1.09it/s, loss=0.609]" ] }, { @@ -23424,7 +23402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 680/2000 [09:38<17:04, 1.29it/s, loss=0.704]" + "training until 2000: 34%|███▍ | 680/2000 [11:58<22:20, 1.02s/it, loss=0.609]" ] }, { @@ -23432,7 +23410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 680/2000 [09:38<17:04, 1.29it/s, loss=0.689]" + "training until 2000: 34%|███▍ | 680/2000 [11:58<22:20, 1.02s/it, loss=0.455]" ] }, { @@ -23440,7 +23418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 681/2000 [09:39<17:00, 1.29it/s, loss=0.689]" + "training until 2000: 34%|███▍ | 681/2000 [11:59<24:35, 1.12s/it, loss=0.455]" ] }, { @@ -23448,7 +23426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 681/2000 [09:39<17:00, 1.29it/s, loss=0.627]" + "training until 2000: 34%|███▍ | 681/2000 [11:59<24:35, 1.12s/it, loss=0.536]" ] }, { @@ -23456,7 +23434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 682/2000 [09:40<18:15, 1.20it/s, loss=0.627]" + "training until 2000: 34%|███▍ | 682/2000 [12:00<24:17, 1.11s/it, loss=0.536]" ] }, { @@ -23464,7 +23442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 682/2000 [09:40<18:15, 1.20it/s, loss=0.641]" + "training until 2000: 34%|███▍ | 682/2000 [12:00<24:17, 1.11s/it, loss=0.505]" ] }, { @@ -23472,7 +23450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 683/2000 [09:41<17:20, 1.27it/s, loss=0.641]" + "training until 2000: 34%|███▍ | 683/2000 [12:01<24:38, 1.12s/it, loss=0.505]" ] }, { @@ -23480,7 +23458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 683/2000 [09:41<17:20, 1.27it/s, loss=0.691]" + "training until 2000: 34%|███▍ | 683/2000 [12:01<24:38, 1.12s/it, loss=0.541]" ] }, { @@ -23488,7 +23466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 684/2000 [09:42<18:28, 1.19it/s, loss=0.691]" + "training until 2000: 34%|███▍ | 684/2000 [12:02<25:00, 1.14s/it, loss=0.541]" ] }, { @@ -23496,7 +23474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 684/2000 [09:42<18:28, 1.19it/s, loss=0.703]" + "training until 2000: 34%|███▍ | 684/2000 [12:02<25:00, 1.14s/it, loss=0.499]" ] }, { @@ -23504,7 +23482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 685/2000 [09:43<17:44, 1.24it/s, loss=0.703]" + "training until 2000: 34%|███▍ | 685/2000 [12:03<21:53, 1.00it/s, loss=0.499]" ] }, { @@ -23512,7 +23490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 685/2000 [09:43<17:44, 1.24it/s, loss=0.631]" + "training until 2000: 34%|███▍ | 685/2000 [12:03<21:53, 1.00it/s, loss=0.622]" ] }, { @@ -23520,7 +23498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 686/2000 [09:43<16:26, 1.33it/s, loss=0.631]" + "training until 2000: 34%|███▍ | 686/2000 [12:04<21:31, 1.02it/s, loss=0.622]" ] }, { @@ -23528,7 +23506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 686/2000 [09:43<16:26, 1.33it/s, loss=0.646]" + "training until 2000: 34%|███▍ | 686/2000 [12:04<21:31, 1.02it/s, loss=0.541]" ] }, { @@ -23536,7 +23514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 687/2000 [09:44<17:09, 1.28it/s, loss=0.646]" + "training until 2000: 34%|███▍ | 687/2000 [12:05<19:29, 1.12it/s, loss=0.541]" ] }, { @@ -23544,7 +23522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 687/2000 [09:44<17:09, 1.28it/s, loss=0.675]" + "training until 2000: 34%|███▍ | 687/2000 [12:05<19:29, 1.12it/s, loss=0.61] " ] }, { @@ -23552,7 +23530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 688/2000 [09:45<16:47, 1.30it/s, loss=0.675]" + "training until 2000: 34%|███▍ | 688/2000 [12:05<18:50, 1.16it/s, loss=0.61]" ] }, { @@ -23560,7 +23538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 688/2000 [09:45<16:47, 1.30it/s, loss=0.646]" + "training until 2000: 34%|███▍ | 688/2000 [12:05<18:50, 1.16it/s, loss=0.498]" ] }, { @@ -23568,7 +23546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 689/2000 [09:46<17:19, 1.26it/s, loss=0.646]" + "training until 2000: 34%|███▍ | 689/2000 [12:06<18:31, 1.18it/s, loss=0.498]" ] }, { @@ -23576,7 +23554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 689/2000 [09:46<17:19, 1.26it/s, loss=0.647]" + "training until 2000: 34%|███▍ | 689/2000 [12:06<18:31, 1.18it/s, loss=0.501]" ] }, { @@ -23584,7 +23562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 690/2000 [09:47<17:58, 1.21it/s, loss=0.647]" + "training until 2000: 34%|███▍ | 690/2000 [12:07<17:11, 1.27it/s, loss=0.501]" ] }, { @@ -23592,7 +23570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 34%|███▍ | 690/2000 [09:47<17:58, 1.21it/s, loss=0.631]" + "training until 2000: 34%|███▍ | 690/2000 [12:07<17:11, 1.27it/s, loss=0.414]" ] }, { @@ -23600,7 +23578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 691/2000 [09:47<18:29, 1.18it/s, loss=0.631]" + "training until 2000: 35%|███▍ | 691/2000 [12:08<18:03, 1.21it/s, loss=0.414]" ] }, { @@ -23608,7 +23586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 691/2000 [09:47<18:29, 1.18it/s, loss=0.686]" + "training until 2000: 35%|███▍ | 691/2000 [12:08<18:03, 1.21it/s, loss=0.557]" ] }, { @@ -23616,7 +23594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 692/2000 [09:48<17:48, 1.22it/s, loss=0.686]" + "training until 2000: 35%|███▍ | 692/2000 [12:09<21:46, 1.00it/s, loss=0.557]" ] }, { @@ -23624,7 +23602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 692/2000 [09:48<17:48, 1.22it/s, loss=0.631]" + "training until 2000: 35%|███▍ | 692/2000 [12:09<21:46, 1.00it/s, loss=0.472]" ] }, { @@ -23632,7 +23610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 693/2000 [09:49<16:48, 1.30it/s, loss=0.631]" + "training until 2000: 35%|███▍ | 693/2000 [12:10<23:10, 1.06s/it, loss=0.472]" ] }, { @@ -23640,7 +23618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 693/2000 [09:49<16:48, 1.30it/s, loss=0.636]" + "training until 2000: 35%|███▍ | 693/2000 [12:10<23:10, 1.06s/it, loss=0.473]" ] }, { @@ -23648,7 +23626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 694/2000 [09:50<18:22, 1.18it/s, loss=0.636]" + "training until 2000: 35%|███▍ | 694/2000 [12:11<21:21, 1.02it/s, loss=0.473]" ] }, { @@ -23656,7 +23634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 694/2000 [09:50<18:22, 1.18it/s, loss=0.686]" + "training until 2000: 35%|███▍ | 694/2000 [12:11<21:21, 1.02it/s, loss=0.501]" ] }, { @@ -23664,7 +23642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 695/2000 [09:51<16:57, 1.28it/s, loss=0.686]" + "training until 2000: 35%|███▍ | 695/2000 [12:12<22:30, 1.03s/it, loss=0.501]" ] }, { @@ -23672,7 +23650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 695/2000 [09:51<16:57, 1.28it/s, loss=0.64] " + "training until 2000: 35%|███▍ | 695/2000 [12:12<22:30, 1.03s/it, loss=0.564]" ] }, { @@ -23680,7 +23658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 696/2000 [09:51<14:39, 1.48it/s, loss=0.64]" + "training until 2000: 35%|███▍ | 696/2000 [12:13<22:03, 1.02s/it, loss=0.564]" ] }, { @@ -23688,7 +23666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 696/2000 [09:51<14:39, 1.48it/s, loss=0.65]" + "training until 2000: 35%|███▍ | 696/2000 [12:13<22:03, 1.02s/it, loss=0.558]" ] }, { @@ -23696,7 +23674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 697/2000 [09:52<15:18, 1.42it/s, loss=0.65]" + "training until 2000: 35%|███▍ | 697/2000 [12:14<22:19, 1.03s/it, loss=0.558]" ] }, { @@ -23704,7 +23682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 697/2000 [09:52<15:18, 1.42it/s, loss=0.681]" + "training until 2000: 35%|███▍ | 697/2000 [12:14<22:19, 1.03s/it, loss=0.447]" ] }, { @@ -23712,7 +23690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 698/2000 [09:52<15:31, 1.40it/s, loss=0.681]" + "training until 2000: 35%|███▍ | 698/2000 [12:15<20:08, 1.08it/s, loss=0.447]" ] }, { @@ -23720,7 +23698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 698/2000 [09:52<15:31, 1.40it/s, loss=0.661]" + "training until 2000: 35%|███▍ | 698/2000 [12:15<20:08, 1.08it/s, loss=0.592]" ] }, { @@ -23728,7 +23706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 699/2000 [09:53<16:40, 1.30it/s, loss=0.661]" + "training until 2000: 35%|███▍ | 699/2000 [12:16<22:37, 1.04s/it, loss=0.592]" ] }, { @@ -23736,7 +23714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▍ | 699/2000 [09:53<16:40, 1.30it/s, loss=0.648]" + "training until 2000: 35%|███▍ | 699/2000 [12:16<22:37, 1.04s/it, loss=0.528]" ] }, { @@ -23744,7 +23722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 700/2000 [09:54<16:28, 1.31it/s, loss=0.648]" + "training until 2000: 35%|███▌ | 700/2000 [12:17<21:35, 1.00it/s, loss=0.528]" ] }, { @@ -23752,7 +23730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 700/2000 [09:54<16:28, 1.31it/s, loss=0.633]" + "training until 2000: 35%|███▌ | 700/2000 [12:17<21:35, 1.00it/s, loss=0.589]" ] }, { @@ -23760,7 +23738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 701/2000 [09:55<17:40, 1.22it/s, loss=0.633]" + "training until 2000: 35%|███▌ | 701/2000 [12:18<20:59, 1.03it/s, loss=0.589]" ] }, { @@ -23768,7 +23746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 701/2000 [09:55<17:40, 1.22it/s, loss=0.656]" + "training until 2000: 35%|███▌ | 701/2000 [12:18<20:59, 1.03it/s, loss=0.439]" ] }, { @@ -23776,7 +23754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 702/2000 [09:56<17:06, 1.26it/s, loss=0.656]" + "training until 2000: 35%|███▌ | 702/2000 [12:19<20:02, 1.08it/s, loss=0.439]" ] }, { @@ -23784,7 +23762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 702/2000 [09:56<17:06, 1.26it/s, loss=0.682]" + "training until 2000: 35%|███▌ | 702/2000 [12:19<20:02, 1.08it/s, loss=0.567]" ] }, { @@ -23792,7 +23770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 703/2000 [09:56<16:43, 1.29it/s, loss=0.682]" + "training until 2000: 35%|███▌ | 703/2000 [12:20<22:07, 1.02s/it, loss=0.567]" ] }, { @@ -23800,7 +23778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 703/2000 [09:56<16:43, 1.29it/s, loss=0.674]" + "training until 2000: 35%|███▌ | 703/2000 [12:20<22:07, 1.02s/it, loss=0.441]" ] }, { @@ -23808,7 +23786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 704/2000 [09:57<17:26, 1.24it/s, loss=0.674]" + "training until 2000: 35%|███▌ | 704/2000 [12:21<21:30, 1.00it/s, loss=0.441]" ] }, { @@ -23816,7 +23794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 704/2000 [09:57<17:26, 1.24it/s, loss=0.715]" + "training until 2000: 35%|███▌ | 704/2000 [12:21<21:30, 1.00it/s, loss=0.508]" ] }, { @@ -23824,7 +23802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 705/2000 [09:59<19:41, 1.10it/s, loss=0.715]" + "training until 2000: 35%|███▌ | 705/2000 [12:23<23:43, 1.10s/it, loss=0.508]" ] }, { @@ -23832,7 +23810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 705/2000 [09:59<19:41, 1.10it/s, loss=0.633]" + "training until 2000: 35%|███▌ | 705/2000 [12:23<23:43, 1.10s/it, loss=0.446]" ] }, { @@ -23840,7 +23818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 706/2000 [09:59<17:49, 1.21it/s, loss=0.633]" + "training until 2000: 35%|███▌ | 706/2000 [12:23<20:05, 1.07it/s, loss=0.446]" ] }, { @@ -23848,7 +23826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 706/2000 [09:59<17:49, 1.21it/s, loss=0.617]" + "training until 2000: 35%|███▌ | 706/2000 [12:23<20:05, 1.07it/s, loss=0.525]" ] }, { @@ -23856,7 +23834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 707/2000 [10:00<16:49, 1.28it/s, loss=0.617]" + "training until 2000: 35%|███▌ | 707/2000 [12:24<18:24, 1.17it/s, loss=0.525]" ] }, { @@ -23864,7 +23842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 707/2000 [10:00<16:49, 1.28it/s, loss=0.629]" + "training until 2000: 35%|███▌ | 707/2000 [12:24<18:24, 1.17it/s, loss=0.584]" ] }, { @@ -23872,7 +23850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 708/2000 [10:00<15:23, 1.40it/s, loss=0.629]" + "training until 2000: 35%|███▌ | 708/2000 [12:25<19:54, 1.08it/s, loss=0.584]" ] }, { @@ -23880,7 +23858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 708/2000 [10:00<15:23, 1.40it/s, loss=0.672]" + "training until 2000: 35%|███▌ | 708/2000 [12:25<19:54, 1.08it/s, loss=0.693]" ] }, { @@ -23888,7 +23866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 709/2000 [10:01<16:17, 1.32it/s, loss=0.672]" + "training until 2000: 35%|███▌ | 709/2000 [12:26<20:09, 1.07it/s, loss=0.693]" ] }, { @@ -23896,7 +23874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 35%|███▌ | 709/2000 [10:01<16:17, 1.32it/s, loss=0.65] " + "training until 2000: 35%|███▌ | 709/2000 [12:26<20:09, 1.07it/s, loss=0.629]" ] }, { @@ -23904,7 +23882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 710/2000 [10:02<15:44, 1.37it/s, loss=0.65]" + "training until 2000: 36%|███▌ | 710/2000 [12:27<19:44, 1.09it/s, loss=0.629]" ] }, { @@ -23912,7 +23890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 710/2000 [10:02<15:44, 1.37it/s, loss=0.626]" + "training until 2000: 36%|███▌ | 710/2000 [12:27<19:44, 1.09it/s, loss=0.493]" ] }, { @@ -23920,7 +23898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 711/2000 [10:03<16:13, 1.32it/s, loss=0.626]" + "training until 2000: 36%|███▌ | 711/2000 [12:28<23:52, 1.11s/it, loss=0.493]" ] }, { @@ -23928,7 +23906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 711/2000 [10:03<16:13, 1.32it/s, loss=0.648]" + "training until 2000: 36%|███▌ | 711/2000 [12:28<23:52, 1.11s/it, loss=0.617]" ] }, { @@ -23936,7 +23914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 712/2000 [10:03<16:14, 1.32it/s, loss=0.648]" + "training until 2000: 36%|███▌ | 712/2000 [12:29<19:50, 1.08it/s, loss=0.617]" ] }, { @@ -23944,7 +23922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 712/2000 [10:03<16:14, 1.32it/s, loss=0.624]" + "training until 2000: 36%|███▌ | 712/2000 [12:29<19:50, 1.08it/s, loss=0.548]" ] }, { @@ -23952,7 +23930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 713/2000 [10:04<17:28, 1.23it/s, loss=0.624]" + "training until 2000: 36%|███▌ | 713/2000 [12:30<19:25, 1.10it/s, loss=0.548]" ] }, { @@ -23960,7 +23938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 713/2000 [10:04<17:28, 1.23it/s, loss=0.664]" + "training until 2000: 36%|███▌ | 713/2000 [12:30<19:25, 1.10it/s, loss=0.595]" ] }, { @@ -23968,7 +23946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 714/2000 [10:05<16:45, 1.28it/s, loss=0.664]" + "training until 2000: 36%|███▌ | 714/2000 [12:30<19:11, 1.12it/s, loss=0.595]" ] }, { @@ -23976,7 +23954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 714/2000 [10:05<16:45, 1.28it/s, loss=0.68] " + "training until 2000: 36%|███▌ | 714/2000 [12:30<19:11, 1.12it/s, loss=0.566]" ] }, { @@ -23984,7 +23962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 715/2000 [10:06<17:53, 1.20it/s, loss=0.68]" + "training until 2000: 36%|███▌ | 715/2000 [12:32<21:05, 1.02it/s, loss=0.566]" ] }, { @@ -23992,7 +23970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 715/2000 [10:06<17:53, 1.20it/s, loss=0.668]" + "training until 2000: 36%|███▌ | 715/2000 [12:32<21:05, 1.02it/s, loss=0.541]" ] }, { @@ -24000,7 +23978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 716/2000 [10:07<17:08, 1.25it/s, loss=0.668]" + "training until 2000: 36%|███▌ | 716/2000 [12:33<21:42, 1.01s/it, loss=0.541]" ] }, { @@ -24008,7 +23986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 716/2000 [10:07<17:08, 1.25it/s, loss=0.605]" + "training until 2000: 36%|███▌ | 716/2000 [12:33<21:42, 1.01s/it, loss=0.546]" ] }, { @@ -24016,7 +23994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 717/2000 [10:07<15:43, 1.36it/s, loss=0.605]" + "training until 2000: 36%|███▌ | 717/2000 [12:34<20:26, 1.05it/s, loss=0.546]" ] }, { @@ -24024,7 +24002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 717/2000 [10:07<15:43, 1.36it/s, loss=0.629]" + "training until 2000: 36%|███▌ | 717/2000 [12:34<20:26, 1.05it/s, loss=0.501]" ] }, { @@ -24032,7 +24010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 718/2000 [10:08<14:54, 1.43it/s, loss=0.629]" + "training until 2000: 36%|███▌ | 718/2000 [12:35<24:16, 1.14s/it, loss=0.501]" ] }, { @@ -24040,7 +24018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 718/2000 [10:08<14:54, 1.43it/s, loss=0.613]" + "training until 2000: 36%|███▌ | 718/2000 [12:35<24:16, 1.14s/it, loss=0.484]" ] }, { @@ -24048,7 +24026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 719/2000 [10:09<15:41, 1.36it/s, loss=0.613]" + "training until 2000: 36%|███▌ | 719/2000 [12:36<23:43, 1.11s/it, loss=0.484]" ] }, { @@ -24056,7 +24034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 719/2000 [10:09<15:41, 1.36it/s, loss=0.644]" + "training until 2000: 36%|███▌ | 719/2000 [12:36<23:43, 1.11s/it, loss=0.567]" ] }, { @@ -24064,7 +24042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 720/2000 [10:10<15:52, 1.34it/s, loss=0.644]" + "training until 2000: 36%|███▌ | 720/2000 [12:37<20:00, 1.07it/s, loss=0.567]" ] }, { @@ -24072,7 +24050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 720/2000 [10:10<15:52, 1.34it/s, loss=0.66] " + "training until 2000: 36%|███▌ | 720/2000 [12:37<20:00, 1.07it/s, loss=0.577]" ] }, { @@ -24080,7 +24058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 721/2000 [10:10<16:27, 1.30it/s, loss=0.66]" + "training until 2000: 36%|███▌ | 721/2000 [12:38<22:44, 1.07s/it, loss=0.577]" ] }, { @@ -24088,7 +24066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 721/2000 [10:10<16:27, 1.30it/s, loss=0.666]" + "training until 2000: 36%|███▌ | 721/2000 [12:38<22:44, 1.07s/it, loss=0.562]" ] }, { @@ -24096,7 +24074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 722/2000 [10:11<17:33, 1.21it/s, loss=0.666]" + "training until 2000: 36%|███▌ | 722/2000 [12:39<23:33, 1.11s/it, loss=0.562]" ] }, { @@ -24104,7 +24082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 722/2000 [10:11<17:33, 1.21it/s, loss=0.671]" + "training until 2000: 36%|███▌ | 722/2000 [12:39<23:33, 1.11s/it, loss=0.508]" ] }, { @@ -24112,7 +24090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 723/2000 [10:12<16:05, 1.32it/s, loss=0.671]" + "training until 2000: 36%|███▌ | 723/2000 [12:40<22:40, 1.07s/it, loss=0.508]" ] }, { @@ -24120,7 +24098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 723/2000 [10:12<16:05, 1.32it/s, loss=0.649]" + "training until 2000: 36%|███▌ | 723/2000 [12:40<22:40, 1.07s/it, loss=0.524]" ] }, { @@ -24128,7 +24106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 724/2000 [10:13<15:38, 1.36it/s, loss=0.649]" + "training until 2000: 36%|███▌ | 724/2000 [12:41<20:43, 1.03it/s, loss=0.524]" ] }, { @@ -24136,7 +24114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▌ | 724/2000 [10:13<15:38, 1.36it/s, loss=0.613]" + "training until 2000: 36%|███▌ | 724/2000 [12:41<20:43, 1.03it/s, loss=0.581]" ] }, { @@ -24144,7 +24122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 725/2000 [10:13<14:13, 1.49it/s, loss=0.613]" + "training until 2000: 36%|███▋ | 725/2000 [12:42<20:07, 1.06it/s, loss=0.581]" ] }, { @@ -24152,7 +24130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 725/2000 [10:13<14:13, 1.49it/s, loss=0.657]" + "training until 2000: 36%|███▋ | 725/2000 [12:42<20:07, 1.06it/s, loss=0.55] " ] }, { @@ -24160,7 +24138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 726/2000 [10:15<18:52, 1.12it/s, loss=0.657]" + "training until 2000: 36%|███▋ | 726/2000 [12:43<20:13, 1.05it/s, loss=0.55]" ] }, { @@ -24168,7 +24146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 726/2000 [10:15<18:52, 1.12it/s, loss=0.647]" + "training until 2000: 36%|███▋ | 726/2000 [12:43<20:13, 1.05it/s, loss=0.535]" ] }, { @@ -24176,7 +24154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 727/2000 [10:15<17:16, 1.23it/s, loss=0.647]" + "training until 2000: 36%|███▋ | 727/2000 [12:43<17:44, 1.20it/s, loss=0.535]" ] }, { @@ -24184,7 +24162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 727/2000 [10:15<17:16, 1.23it/s, loss=0.689]" + "training until 2000: 36%|███▋ | 727/2000 [12:43<17:44, 1.20it/s, loss=0.452]" ] }, { @@ -24192,7 +24170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 728/2000 [10:16<16:22, 1.29it/s, loss=0.689]" + "training until 2000: 36%|███▋ | 728/2000 [12:44<16:21, 1.30it/s, loss=0.452]" ] }, { @@ -24200,7 +24178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 728/2000 [10:16<16:22, 1.29it/s, loss=0.66] " + "training until 2000: 36%|███▋ | 728/2000 [12:44<16:21, 1.30it/s, loss=0.487]" ] }, { @@ -24208,7 +24186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 729/2000 [10:17<17:05, 1.24it/s, loss=0.66]" + "training until 2000: 36%|███▋ | 729/2000 [12:45<16:52, 1.26it/s, loss=0.487]" ] }, { @@ -24216,7 +24194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 729/2000 [10:17<17:05, 1.24it/s, loss=0.62]" + "training until 2000: 36%|███▋ | 729/2000 [12:45<16:52, 1.26it/s, loss=0.511]" ] }, { @@ -24224,7 +24202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 730/2000 [10:18<16:29, 1.28it/s, loss=0.62]" + "training until 2000: 36%|███▋ | 730/2000 [12:46<19:38, 1.08it/s, loss=0.511]" ] }, { @@ -24232,7 +24210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 36%|███▋ | 730/2000 [10:18<16:29, 1.28it/s, loss=0.64]" + "training until 2000: 36%|███▋ | 730/2000 [12:46<19:38, 1.08it/s, loss=0.517]" ] }, { @@ -24240,7 +24218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 731/2000 [10:19<18:42, 1.13it/s, loss=0.64]" + "training until 2000: 37%|███▋ | 731/2000 [12:47<19:05, 1.11it/s, loss=0.517]" ] }, { @@ -24248,7 +24226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 731/2000 [10:19<18:42, 1.13it/s, loss=0.663]" + "training until 2000: 37%|███▋ | 731/2000 [12:47<19:05, 1.11it/s, loss=0.529]" ] }, { @@ -24256,7 +24234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 732/2000 [10:20<19:14, 1.10it/s, loss=0.663]" + "training until 2000: 37%|███▋ | 732/2000 [12:48<21:09, 1.00s/it, loss=0.529]" ] }, { @@ -24264,7 +24242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 732/2000 [10:20<19:14, 1.10it/s, loss=0.662]" + "training until 2000: 37%|███▋ | 732/2000 [12:48<21:09, 1.00s/it, loss=0.582]" ] }, { @@ -24272,7 +24250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 733/2000 [10:21<19:05, 1.11it/s, loss=0.662]" + "training until 2000: 37%|███▋ | 733/2000 [12:49<21:39, 1.03s/it, loss=0.582]" ] }, { @@ -24280,7 +24258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 733/2000 [10:21<19:05, 1.11it/s, loss=0.638]" + "training until 2000: 37%|███▋ | 733/2000 [12:49<21:39, 1.03s/it, loss=0.542]" ] }, { @@ -24288,7 +24266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 734/2000 [10:21<19:25, 1.09it/s, loss=0.638]" + "training until 2000: 37%|███▋ | 734/2000 [12:50<21:46, 1.03s/it, loss=0.542]" ] }, { @@ -24296,7 +24274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 734/2000 [10:21<19:25, 1.09it/s, loss=0.612]" + "training until 2000: 37%|███▋ | 734/2000 [12:50<21:46, 1.03s/it, loss=0.607]" ] }, { @@ -24304,7 +24282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 735/2000 [10:22<17:29, 1.20it/s, loss=0.612]" + "training until 2000: 37%|███▋ | 735/2000 [12:52<23:11, 1.10s/it, loss=0.607]" ] }, { @@ -24312,7 +24290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 735/2000 [10:22<17:29, 1.20it/s, loss=0.64] " + "training until 2000: 37%|███▋ | 735/2000 [12:52<23:11, 1.10s/it, loss=0.657]" ] }, { @@ -24320,7 +24298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 736/2000 [10:23<16:57, 1.24it/s, loss=0.64]" + "training until 2000: 37%|███▋ | 736/2000 [12:53<23:31, 1.12s/it, loss=0.657]" ] }, { @@ -24328,7 +24306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 736/2000 [10:23<16:57, 1.24it/s, loss=0.734]" + "training until 2000: 37%|███▋ | 736/2000 [12:53<23:31, 1.12s/it, loss=0.558]" ] }, { @@ -24336,7 +24314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 737/2000 [10:24<16:27, 1.28it/s, loss=0.734]" + "training until 2000: 37%|███▋ | 737/2000 [12:54<23:27, 1.11s/it, loss=0.558]" ] }, { @@ -24344,7 +24322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 737/2000 [10:24<16:27, 1.28it/s, loss=0.675]" + "training until 2000: 37%|███▋ | 737/2000 [12:54<23:27, 1.11s/it, loss=0.56] " ] }, { @@ -24352,7 +24330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 738/2000 [10:24<16:00, 1.31it/s, loss=0.675]" + "training until 2000: 37%|███▋ | 738/2000 [12:55<24:41, 1.17s/it, loss=0.56]" ] }, { @@ -24360,7 +24338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 738/2000 [10:24<16:00, 1.31it/s, loss=0.632]" + "training until 2000: 37%|███▋ | 738/2000 [12:55<24:41, 1.17s/it, loss=0.588]" ] }, { @@ -24368,7 +24346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 739/2000 [10:25<16:03, 1.31it/s, loss=0.632]" + "training until 2000: 37%|███▋ | 739/2000 [12:56<23:26, 1.12s/it, loss=0.588]" ] }, { @@ -24376,7 +24354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 739/2000 [10:25<16:03, 1.31it/s, loss=0.627]" + "training until 2000: 37%|███▋ | 739/2000 [12:56<23:26, 1.12s/it, loss=0.466]" ] }, { @@ -24384,7 +24362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 740/2000 [10:26<15:46, 1.33it/s, loss=0.627]" + "training until 2000: 37%|███▋ | 740/2000 [12:57<21:18, 1.01s/it, loss=0.466]" ] }, { @@ -24392,7 +24370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 740/2000 [10:26<15:46, 1.33it/s, loss=0.632]" + "training until 2000: 37%|███▋ | 740/2000 [12:57<21:18, 1.01s/it, loss=0.459]" ] }, { @@ -24400,7 +24378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 741/2000 [10:26<15:33, 1.35it/s, loss=0.632]" + "training until 2000: 37%|███▋ | 741/2000 [12:58<19:19, 1.09it/s, loss=0.459]" ] }, { @@ -24408,7 +24386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 741/2000 [10:26<15:33, 1.35it/s, loss=0.657]" + "training until 2000: 37%|███▋ | 741/2000 [12:58<19:19, 1.09it/s, loss=0.491]" ] }, { @@ -24416,7 +24394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 742/2000 [10:27<15:57, 1.31it/s, loss=0.657]" + "training until 2000: 37%|███▋ | 742/2000 [12:58<17:27, 1.20it/s, loss=0.491]" ] }, { @@ -24424,7 +24402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 742/2000 [10:27<15:57, 1.31it/s, loss=0.613]" + "training until 2000: 37%|███▋ | 742/2000 [12:58<17:27, 1.20it/s, loss=0.474]" ] }, { @@ -24432,7 +24410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 743/2000 [10:28<15:34, 1.34it/s, loss=0.613]" + "training until 2000: 37%|███▋ | 743/2000 [13:00<20:15, 1.03it/s, loss=0.474]" ] }, { @@ -24440,7 +24418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 743/2000 [10:28<15:34, 1.34it/s, loss=0.703]" + "training until 2000: 37%|███▋ | 743/2000 [13:00<20:15, 1.03it/s, loss=0.503]" ] }, { @@ -24448,7 +24426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 744/2000 [10:29<14:33, 1.44it/s, loss=0.703]" + "training until 2000: 37%|███▋ | 744/2000 [13:00<17:46, 1.18it/s, loss=0.503]" ] }, { @@ -24456,7 +24434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 744/2000 [10:29<14:33, 1.44it/s, loss=0.683]" + "training until 2000: 37%|███▋ | 744/2000 [13:00<17:46, 1.18it/s, loss=0.507]" ] }, { @@ -24464,7 +24442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 745/2000 [10:30<17:25, 1.20it/s, loss=0.683]" + "training until 2000: 37%|███▋ | 745/2000 [13:01<16:19, 1.28it/s, loss=0.507]" ] }, { @@ -24472,7 +24450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 745/2000 [10:30<17:25, 1.20it/s, loss=0.666]" + "training until 2000: 37%|███▋ | 745/2000 [13:01<16:19, 1.28it/s, loss=0.425]" ] }, { @@ -24480,7 +24458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 746/2000 [10:30<15:47, 1.32it/s, loss=0.666]" + "training until 2000: 37%|███▋ | 746/2000 [13:02<16:41, 1.25it/s, loss=0.425]" ] }, { @@ -24488,7 +24466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 746/2000 [10:30<15:47, 1.32it/s, loss=0.629]" + "training until 2000: 37%|███▋ | 746/2000 [13:02<16:41, 1.25it/s, loss=0.503]" ] }, { @@ -24496,7 +24474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 747/2000 [10:31<15:11, 1.37it/s, loss=0.629]" + "training until 2000: 37%|███▋ | 747/2000 [13:03<18:31, 1.13it/s, loss=0.503]" ] }, { @@ -24504,7 +24482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 747/2000 [10:31<15:11, 1.37it/s, loss=0.638]" + "training until 2000: 37%|███▋ | 747/2000 [13:03<18:31, 1.13it/s, loss=0.507]" ] }, { @@ -24512,7 +24490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 748/2000 [10:32<15:32, 1.34it/s, loss=0.638]" + "training until 2000: 37%|███▋ | 748/2000 [13:04<20:13, 1.03it/s, loss=0.507]" ] }, { @@ -24520,7 +24498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 748/2000 [10:32<15:32, 1.34it/s, loss=0.632]" + "training until 2000: 37%|███▋ | 748/2000 [13:04<20:13, 1.03it/s, loss=0.448]" ] }, { @@ -24528,7 +24506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 749/2000 [10:32<14:48, 1.41it/s, loss=0.632]" + "training until 2000: 37%|███▋ | 749/2000 [13:05<22:54, 1.10s/it, loss=0.448]" ] }, { @@ -24536,7 +24514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 37%|███▋ | 749/2000 [10:32<14:48, 1.41it/s, loss=0.62] " + "training until 2000: 37%|███▋ | 749/2000 [13:05<22:54, 1.10s/it, loss=0.488]" ] }, { @@ -24544,7 +24522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 750/2000 [10:33<14:42, 1.42it/s, loss=0.62]" + "training until 2000: 38%|███▊ | 750/2000 [13:06<20:02, 1.04it/s, loss=0.488]" ] }, { @@ -24552,7 +24530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 750/2000 [10:33<14:42, 1.42it/s, loss=0.636]" + "training until 2000: 38%|███▊ | 750/2000 [13:06<20:02, 1.04it/s, loss=0.439]" ] }, { @@ -24560,7 +24538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 751/2000 [10:34<13:32, 1.54it/s, loss=0.636]" + "training until 2000: 38%|███▊ | 751/2000 [13:07<20:06, 1.04it/s, loss=0.439]" ] }, { @@ -24568,7 +24546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 751/2000 [10:34<13:32, 1.54it/s, loss=0.607]" + "training until 2000: 38%|███▊ | 751/2000 [13:07<20:06, 1.04it/s, loss=0.428]" ] }, { @@ -24576,7 +24554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 752/2000 [10:35<15:20, 1.36it/s, loss=0.607]" + "training until 2000: 38%|███▊ | 752/2000 [13:08<22:43, 1.09s/it, loss=0.428]" ] }, { @@ -24584,7 +24562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 752/2000 [10:35<15:20, 1.36it/s, loss=0.615]" + "training until 2000: 38%|███▊ | 752/2000 [13:08<22:43, 1.09s/it, loss=0.501]" ] }, { @@ -24592,7 +24570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 753/2000 [10:35<15:55, 1.31it/s, loss=0.615]" + "training until 2000: 38%|███▊ | 753/2000 [13:09<22:30, 1.08s/it, loss=0.501]" ] }, { @@ -24600,7 +24578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 753/2000 [10:35<15:55, 1.31it/s, loss=0.68] " + "training until 2000: 38%|███▊ | 753/2000 [13:09<22:30, 1.08s/it, loss=0.477]" ] }, { @@ -24608,7 +24586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 754/2000 [10:36<16:35, 1.25it/s, loss=0.68]" + "training until 2000: 38%|███▊ | 754/2000 [13:10<20:49, 1.00s/it, loss=0.477]" ] }, { @@ -24616,7 +24594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 754/2000 [10:36<16:35, 1.25it/s, loss=0.605]" + "training until 2000: 38%|███▊ | 754/2000 [13:10<20:49, 1.00s/it, loss=0.455]" ] }, { @@ -24624,7 +24602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 755/2000 [10:37<17:27, 1.19it/s, loss=0.605]" + "training until 2000: 38%|███▊ | 755/2000 [13:12<24:24, 1.18s/it, loss=0.455]" ] }, { @@ -24632,7 +24610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 755/2000 [10:37<17:27, 1.19it/s, loss=0.629]" + "training until 2000: 38%|███▊ | 755/2000 [13:12<24:24, 1.18s/it, loss=0.429]" ] }, { @@ -24640,7 +24618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 756/2000 [10:38<15:31, 1.34it/s, loss=0.629]" + "training until 2000: 38%|███▊ | 756/2000 [13:13<23:08, 1.12s/it, loss=0.429]" ] }, { @@ -24648,7 +24626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 756/2000 [10:38<15:31, 1.34it/s, loss=0.616]" + "training until 2000: 38%|███▊ | 756/2000 [13:13<23:08, 1.12s/it, loss=0.499]" ] }, { @@ -24656,7 +24634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 757/2000 [10:38<14:56, 1.39it/s, loss=0.616]" + "training until 2000: 38%|███▊ | 757/2000 [13:13<20:43, 1.00s/it, loss=0.499]" ] }, { @@ -24664,7 +24642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 757/2000 [10:38<14:56, 1.39it/s, loss=0.637]" + "training until 2000: 38%|███▊ | 757/2000 [13:13<20:43, 1.00s/it, loss=0.455]" ] }, { @@ -24672,7 +24650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 758/2000 [10:39<14:27, 1.43it/s, loss=0.637]" + "training until 2000: 38%|███▊ | 758/2000 [13:14<19:07, 1.08it/s, loss=0.455]" ] }, { @@ -24680,7 +24658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 758/2000 [10:39<14:27, 1.43it/s, loss=0.624]" + "training until 2000: 38%|███▊ | 758/2000 [13:14<19:07, 1.08it/s, loss=0.548]" ] }, { @@ -24688,7 +24666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 759/2000 [10:40<14:29, 1.43it/s, loss=0.624]" + "training until 2000: 38%|███▊ | 759/2000 [13:16<22:07, 1.07s/it, loss=0.548]" ] }, { @@ -24696,7 +24674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 759/2000 [10:40<14:29, 1.43it/s, loss=0.652]" + "training until 2000: 38%|███▊ | 759/2000 [13:16<22:07, 1.07s/it, loss=0.393]" ] }, { @@ -24704,7 +24682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 760/2000 [10:40<14:02, 1.47it/s, loss=0.652]" + "training until 2000: 38%|███▊ | 760/2000 [13:16<20:52, 1.01s/it, loss=0.393]" ] }, { @@ -24712,7 +24690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 760/2000 [10:40<14:02, 1.47it/s, loss=0.646]" + "training until 2000: 38%|███▊ | 760/2000 [13:16<20:52, 1.01s/it, loss=0.594]" ] }, { @@ -24720,7 +24698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 761/2000 [10:41<14:41, 1.41it/s, loss=0.646]" + "training until 2000: 38%|███▊ | 761/2000 [13:18<22:38, 1.10s/it, loss=0.594]" ] }, { @@ -24728,7 +24706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 761/2000 [10:41<14:41, 1.41it/s, loss=0.669]" + "training until 2000: 38%|███▊ | 761/2000 [13:18<22:38, 1.10s/it, loss=0.511]" ] }, { @@ -24736,7 +24714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 762/2000 [10:42<14:25, 1.43it/s, loss=0.669]" + "training until 2000: 38%|███▊ | 762/2000 [13:19<24:01, 1.16s/it, loss=0.511]" ] }, { @@ -24744,7 +24722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 762/2000 [10:42<14:25, 1.43it/s, loss=0.637]" + "training until 2000: 38%|███▊ | 762/2000 [13:19<24:01, 1.16s/it, loss=0.469]" ] }, { @@ -24752,7 +24730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 763/2000 [10:43<14:21, 1.44it/s, loss=0.637]" + "training until 2000: 38%|███▊ | 763/2000 [13:20<24:56, 1.21s/it, loss=0.469]" ] }, { @@ -24760,7 +24738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 763/2000 [10:43<14:21, 1.44it/s, loss=0.662]" + "training until 2000: 38%|███▊ | 763/2000 [13:20<24:56, 1.21s/it, loss=0.461]" ] }, { @@ -24768,7 +24746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 764/2000 [10:43<15:15, 1.35it/s, loss=0.662]" + "training until 2000: 38%|███▊ | 764/2000 [13:21<22:46, 1.11s/it, loss=0.461]" ] }, { @@ -24776,7 +24754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 764/2000 [10:43<15:15, 1.35it/s, loss=0.615]" + "training until 2000: 38%|███▊ | 764/2000 [13:21<22:46, 1.11s/it, loss=0.585]" ] }, { @@ -24784,7 +24762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 765/2000 [10:44<14:48, 1.39it/s, loss=0.615]" + "training until 2000: 38%|███▊ | 765/2000 [13:22<21:11, 1.03s/it, loss=0.585]" ] }, { @@ -24792,7 +24770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 765/2000 [10:44<14:48, 1.39it/s, loss=0.614]" + "training until 2000: 38%|███▊ | 765/2000 [13:22<21:11, 1.03s/it, loss=0.548]" ] }, { @@ -24800,7 +24778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 766/2000 [10:45<15:28, 1.33it/s, loss=0.614]" + "training until 2000: 38%|███▊ | 766/2000 [13:23<20:17, 1.01it/s, loss=0.548]" ] }, { @@ -24808,7 +24786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 766/2000 [10:45<15:28, 1.33it/s, loss=0.655]" + "training until 2000: 38%|███▊ | 766/2000 [13:23<20:17, 1.01it/s, loss=0.583]" ] }, { @@ -24816,7 +24794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 767/2000 [10:45<14:47, 1.39it/s, loss=0.655]" + "training until 2000: 38%|███▊ | 767/2000 [13:24<19:29, 1.05it/s, loss=0.583]" ] }, { @@ -24824,7 +24802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 767/2000 [10:45<14:47, 1.39it/s, loss=0.605]" + "training until 2000: 38%|███▊ | 767/2000 [13:24<19:29, 1.05it/s, loss=0.495]" ] }, { @@ -24832,7 +24810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 768/2000 [10:46<13:34, 1.51it/s, loss=0.605]" + "training until 2000: 38%|███▊ | 768/2000 [13:25<18:20, 1.12it/s, loss=0.495]" ] }, { @@ -24840,7 +24818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 768/2000 [10:46<13:34, 1.51it/s, loss=0.637]" + "training until 2000: 38%|███▊ | 768/2000 [13:25<18:20, 1.12it/s, loss=0.474]" ] }, { @@ -24848,7 +24826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 769/2000 [10:47<13:55, 1.47it/s, loss=0.637]" + "training until 2000: 38%|███▊ | 769/2000 [13:26<19:02, 1.08it/s, loss=0.474]" ] }, { @@ -24856,7 +24834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 769/2000 [10:47<13:55, 1.47it/s, loss=0.638]" + "training until 2000: 38%|███▊ | 769/2000 [13:26<19:02, 1.08it/s, loss=0.509]" ] }, { @@ -24864,7 +24842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 770/2000 [10:48<14:46, 1.39it/s, loss=0.638]" + "training until 2000: 38%|███▊ | 770/2000 [13:27<20:28, 1.00it/s, loss=0.509]" ] }, { @@ -24872,7 +24850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 38%|███▊ | 770/2000 [10:48<14:46, 1.39it/s, loss=0.605]" + "training until 2000: 38%|███▊ | 770/2000 [13:27<20:28, 1.00it/s, loss=0.461]" ] }, { @@ -24880,7 +24858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 771/2000 [10:48<15:10, 1.35it/s, loss=0.605]" + "training until 2000: 39%|███▊ | 771/2000 [13:28<22:34, 1.10s/it, loss=0.461]" ] }, { @@ -24888,7 +24866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 771/2000 [10:48<15:10, 1.35it/s, loss=0.664]" + "training until 2000: 39%|███▊ | 771/2000 [13:28<22:34, 1.10s/it, loss=0.512]" ] }, { @@ -24896,7 +24874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 772/2000 [10:49<16:49, 1.22it/s, loss=0.664]" + "training until 2000: 39%|███▊ | 772/2000 [13:29<21:03, 1.03s/it, loss=0.512]" ] }, { @@ -24904,7 +24882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 772/2000 [10:49<16:49, 1.22it/s, loss=0.703]" + "training until 2000: 39%|███▊ | 772/2000 [13:29<21:03, 1.03s/it, loss=0.576]" ] }, { @@ -24912,7 +24890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 773/2000 [10:50<15:46, 1.30it/s, loss=0.703]" + "training until 2000: 39%|███▊ | 773/2000 [13:30<21:38, 1.06s/it, loss=0.576]" ] }, { @@ -24920,7 +24898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 773/2000 [10:50<15:46, 1.30it/s, loss=0.61] " + "training until 2000: 39%|███▊ | 773/2000 [13:30<21:38, 1.06s/it, loss=0.444]" ] }, { @@ -24928,7 +24906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 774/2000 [10:51<15:36, 1.31it/s, loss=0.61]" + "training until 2000: 39%|███▊ | 774/2000 [13:31<21:02, 1.03s/it, loss=0.444]" ] }, { @@ -24936,7 +24914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▊ | 774/2000 [10:51<15:36, 1.31it/s, loss=0.595]" + "training until 2000: 39%|███▊ | 774/2000 [13:31<21:02, 1.03s/it, loss=0.416]" ] }, { @@ -24944,7 +24922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 775/2000 [10:51<15:02, 1.36it/s, loss=0.595]" + "training until 2000: 39%|███▉ | 775/2000 [13:32<19:18, 1.06it/s, loss=0.416]" ] }, { @@ -24952,7 +24930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 775/2000 [10:51<15:02, 1.36it/s, loss=0.657]" + "training until 2000: 39%|███▉ | 775/2000 [13:32<19:18, 1.06it/s, loss=0.531]" ] }, { @@ -24960,7 +24938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 776/2000 [10:52<15:30, 1.32it/s, loss=0.657]" + "training until 2000: 39%|███▉ | 776/2000 [13:33<20:36, 1.01s/it, loss=0.531]" ] }, { @@ -24968,7 +24946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 776/2000 [10:52<15:30, 1.32it/s, loss=0.594]" + "training until 2000: 39%|███▉ | 776/2000 [13:33<20:36, 1.01s/it, loss=0.37] " ] }, { @@ -24976,7 +24954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 777/2000 [10:53<14:58, 1.36it/s, loss=0.594]" + "training until 2000: 39%|███▉ | 777/2000 [13:34<19:48, 1.03it/s, loss=0.37]" ] }, { @@ -24984,7 +24962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 777/2000 [10:53<14:58, 1.36it/s, loss=0.646]" + "training until 2000: 39%|███▉ | 777/2000 [13:34<19:48, 1.03it/s, loss=0.531]" ] }, { @@ -24992,7 +24970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 778/2000 [10:54<14:13, 1.43it/s, loss=0.646]" + "training until 2000: 39%|███▉ | 778/2000 [13:35<19:39, 1.04it/s, loss=0.531]" ] }, { @@ -25000,7 +24978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 778/2000 [10:54<14:13, 1.43it/s, loss=0.613]" + "training until 2000: 39%|███▉ | 778/2000 [13:35<19:39, 1.04it/s, loss=0.456]" ] }, { @@ -25008,7 +24986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 779/2000 [10:54<15:08, 1.34it/s, loss=0.613]" + "training until 2000: 39%|███▉ | 779/2000 [13:36<21:37, 1.06s/it, loss=0.456]" ] }, { @@ -25016,7 +24994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 779/2000 [10:54<15:08, 1.34it/s, loss=0.619]" + "training until 2000: 39%|███▉ | 779/2000 [13:36<21:37, 1.06s/it, loss=0.44] " ] }, { @@ -25024,7 +25002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 780/2000 [10:55<15:33, 1.31it/s, loss=0.619]" + "training until 2000: 39%|███▉ | 780/2000 [13:37<20:00, 1.02it/s, loss=0.44]" ] }, { @@ -25032,7 +25010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 780/2000 [10:55<15:33, 1.31it/s, loss=0.589]" + "training until 2000: 39%|███▉ | 780/2000 [13:37<20:00, 1.02it/s, loss=0.506]" ] }, { @@ -25040,7 +25018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 781/2000 [10:56<15:16, 1.33it/s, loss=0.589]" + "training until 2000: 39%|███▉ | 781/2000 [13:38<19:48, 1.03it/s, loss=0.506]" ] }, { @@ -25048,7 +25026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 781/2000 [10:56<15:16, 1.33it/s, loss=0.615]" + "training until 2000: 39%|███▉ | 781/2000 [13:38<19:48, 1.03it/s, loss=0.578]" ] }, { @@ -25056,7 +25034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 782/2000 [10:57<15:46, 1.29it/s, loss=0.615]" + "training until 2000: 39%|███▉ | 782/2000 [13:39<18:07, 1.12it/s, loss=0.578]" ] }, { @@ -25064,7 +25042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 782/2000 [10:57<15:46, 1.29it/s, loss=0.61] " + "training until 2000: 39%|███▉ | 782/2000 [13:39<18:07, 1.12it/s, loss=0.416]" ] }, { @@ -25072,7 +25050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 783/2000 [10:57<15:10, 1.34it/s, loss=0.61]" + "training until 2000: 39%|███▉ | 783/2000 [13:40<19:45, 1.03it/s, loss=0.416]" ] }, { @@ -25080,7 +25058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 783/2000 [10:57<15:10, 1.34it/s, loss=0.58]" + "training until 2000: 39%|███▉ | 783/2000 [13:40<19:45, 1.03it/s, loss=0.55] " ] }, { @@ -25088,7 +25066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 784/2000 [10:58<15:50, 1.28it/s, loss=0.58]" + "training until 2000: 39%|███▉ | 784/2000 [13:40<18:28, 1.10it/s, loss=0.55]" ] }, { @@ -25096,7 +25074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 784/2000 [10:58<15:50, 1.28it/s, loss=0.613]" + "training until 2000: 39%|███▉ | 784/2000 [13:40<18:28, 1.10it/s, loss=0.488]" ] }, { @@ -25104,7 +25082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 785/2000 [10:59<16:38, 1.22it/s, loss=0.613]" + "training until 2000: 39%|███▉ | 785/2000 [13:41<17:32, 1.15it/s, loss=0.488]" ] }, { @@ -25112,7 +25090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 785/2000 [10:59<16:38, 1.22it/s, loss=0.623]" + "training until 2000: 39%|███▉ | 785/2000 [13:41<17:32, 1.15it/s, loss=0.491]" ] }, { @@ -25120,7 +25098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 786/2000 [11:00<16:19, 1.24it/s, loss=0.623]" + "training until 2000: 39%|███▉ | 786/2000 [13:42<20:12, 1.00it/s, loss=0.491]" ] }, { @@ -25128,7 +25106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 786/2000 [11:00<16:19, 1.24it/s, loss=0.71] " + "training until 2000: 39%|███▉ | 786/2000 [13:42<20:12, 1.00it/s, loss=0.403]" ] }, { @@ -25136,7 +25114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 787/2000 [11:01<18:35, 1.09it/s, loss=0.71]" + "training until 2000: 39%|███▉ | 787/2000 [13:43<18:23, 1.10it/s, loss=0.403]" ] }, { @@ -25144,7 +25122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 787/2000 [11:01<18:35, 1.09it/s, loss=0.611]" + "training until 2000: 39%|███▉ | 787/2000 [13:43<18:23, 1.10it/s, loss=0.428]" ] }, { @@ -25152,7 +25130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 788/2000 [11:02<19:02, 1.06it/s, loss=0.611]" + "training until 2000: 39%|███▉ | 788/2000 [13:45<20:54, 1.04s/it, loss=0.428]" ] }, { @@ -25160,7 +25138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 788/2000 [11:02<19:02, 1.06it/s, loss=0.637]" + "training until 2000: 39%|███▉ | 788/2000 [13:45<20:54, 1.04s/it, loss=0.481]" ] }, { @@ -25168,7 +25146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 789/2000 [11:03<19:52, 1.02it/s, loss=0.637]" + "training until 2000: 39%|███▉ | 789/2000 [13:46<21:14, 1.05s/it, loss=0.481]" ] }, { @@ -25176,7 +25154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 39%|███▉ | 789/2000 [11:03<19:52, 1.02it/s, loss=0.588]" + "training until 2000: 39%|███▉ | 789/2000 [13:46<21:14, 1.05s/it, loss=0.38] " ] }, { @@ -25184,7 +25162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 790/2000 [11:04<17:54, 1.13it/s, loss=0.588]" + "training until 2000: 40%|███▉ | 790/2000 [13:47<20:22, 1.01s/it, loss=0.38]" ] }, { @@ -25192,7 +25170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 790/2000 [11:04<17:54, 1.13it/s, loss=0.64] " + "training until 2000: 40%|███▉ | 790/2000 [13:47<20:22, 1.01s/it, loss=0.505]" ] }, { @@ -25200,7 +25178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 791/2000 [11:05<16:49, 1.20it/s, loss=0.64]" + "training until 2000: 40%|███▉ | 791/2000 [13:48<20:11, 1.00s/it, loss=0.505]" ] }, { @@ -25208,7 +25186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 791/2000 [11:05<16:49, 1.20it/s, loss=0.633]" + "training until 2000: 40%|███▉ | 791/2000 [13:48<20:11, 1.00s/it, loss=0.561]" ] }, { @@ -25216,7 +25194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 792/2000 [11:05<16:12, 1.24it/s, loss=0.633]" + "training until 2000: 40%|███▉ | 792/2000 [13:48<18:27, 1.09it/s, loss=0.561]" ] }, { @@ -25224,7 +25202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 792/2000 [11:05<16:12, 1.24it/s, loss=0.61] " + "training until 2000: 40%|███▉ | 792/2000 [13:48<18:27, 1.09it/s, loss=0.456]" ] }, { @@ -25232,7 +25210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 793/2000 [11:06<14:11, 1.42it/s, loss=0.61]" + "training until 2000: 40%|███▉ | 793/2000 [13:49<17:37, 1.14it/s, loss=0.456]" ] }, { @@ -25240,7 +25218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 793/2000 [11:06<14:11, 1.42it/s, loss=0.614]" + "training until 2000: 40%|███▉ | 793/2000 [13:49<17:37, 1.14it/s, loss=0.547]" ] }, { @@ -25248,7 +25226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 794/2000 [11:07<14:54, 1.35it/s, loss=0.614]" + "training until 2000: 40%|███▉ | 794/2000 [13:50<16:58, 1.18it/s, loss=0.547]" ] }, { @@ -25256,7 +25234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 794/2000 [11:07<14:54, 1.35it/s, loss=0.619]" + "training until 2000: 40%|███▉ | 794/2000 [13:50<16:58, 1.18it/s, loss=0.365]" ] }, { @@ -25264,7 +25242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 795/2000 [11:07<14:52, 1.35it/s, loss=0.619]" + "training until 2000: 40%|███▉ | 795/2000 [13:51<21:11, 1.06s/it, loss=0.365]" ] }, { @@ -25272,7 +25250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 795/2000 [11:07<14:52, 1.35it/s, loss=0.634]" + "training until 2000: 40%|███▉ | 795/2000 [13:51<21:11, 1.06s/it, loss=0.352]" ] }, { @@ -25280,7 +25258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 796/2000 [11:08<16:31, 1.21it/s, loss=0.634]" + "training until 2000: 40%|███▉ | 796/2000 [13:52<21:06, 1.05s/it, loss=0.352]" ] }, { @@ -25288,7 +25266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 796/2000 [11:08<16:31, 1.21it/s, loss=0.612]" + "training until 2000: 40%|███▉ | 796/2000 [13:52<21:06, 1.05s/it, loss=0.365]" ] }, { @@ -25296,7 +25274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 797/2000 [11:09<14:39, 1.37it/s, loss=0.612]" + "training until 2000: 40%|███▉ | 797/2000 [13:53<20:06, 1.00s/it, loss=0.365]" ] }, { @@ -25304,7 +25282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 797/2000 [11:09<14:39, 1.37it/s, loss=0.627]" + "training until 2000: 40%|███▉ | 797/2000 [13:53<20:06, 1.00s/it, loss=0.495]" ] }, { @@ -25312,7 +25290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 798/2000 [11:10<15:48, 1.27it/s, loss=0.627]" + "training until 2000: 40%|███▉ | 798/2000 [13:54<20:15, 1.01s/it, loss=0.495]" ] }, { @@ -25320,7 +25298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 798/2000 [11:10<15:48, 1.27it/s, loss=0.577]" + "training until 2000: 40%|███▉ | 798/2000 [13:54<20:15, 1.01s/it, loss=0.499]" ] }, { @@ -25328,7 +25306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 799/2000 [11:11<19:00, 1.05it/s, loss=0.577]" + "training until 2000: 40%|███▉ | 799/2000 [13:55<20:21, 1.02s/it, loss=0.499]" ] }, { @@ -25336,7 +25314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|███▉ | 799/2000 [11:11<19:00, 1.05it/s, loss=0.634]" + "training until 2000: 40%|███▉ | 799/2000 [13:55<20:21, 1.02s/it, loss=0.379]" ] }, { @@ -25344,7 +25322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 800/2000 [11:12<16:58, 1.18it/s, loss=0.634]" + "training until 2000: 40%|████ | 800/2000 [13:57<22:48, 1.14s/it, loss=0.379]" ] }, { @@ -25352,7 +25330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 800/2000 [11:12<16:58, 1.18it/s, loss=0.612]" + "training until 2000: 40%|████ | 800/2000 [13:57<22:48, 1.14s/it, loss=0.527]" ] }, { @@ -25360,7 +25338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 801/2000 [11:13<16:27, 1.21it/s, loss=0.612]" + "training until 2000: 40%|████ | 801/2000 [13:58<24:08, 1.21s/it, loss=0.527]" ] }, { @@ -25368,7 +25346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 801/2000 [11:13<16:27, 1.21it/s, loss=0.627]" + "training until 2000: 40%|████ | 801/2000 [13:58<24:08, 1.21s/it, loss=0.57] " ] }, { @@ -25376,7 +25354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 802/2000 [11:13<15:22, 1.30it/s, loss=0.627]" + "training until 2000: 40%|████ | 802/2000 [13:59<22:06, 1.11s/it, loss=0.57]" ] }, { @@ -25384,7 +25362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 802/2000 [11:13<15:22, 1.30it/s, loss=0.639]" + "training until 2000: 40%|████ | 802/2000 [13:59<22:06, 1.11s/it, loss=0.406]" ] }, { @@ -25392,7 +25370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 803/2000 [11:14<15:22, 1.30it/s, loss=0.639]" + "training until 2000: 40%|████ | 803/2000 [14:00<19:14, 1.04it/s, loss=0.406]" ] }, { @@ -25400,7 +25378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 803/2000 [11:14<15:22, 1.30it/s, loss=0.607]" + "training until 2000: 40%|████ | 803/2000 [14:00<19:14, 1.04it/s, loss=0.324]" ] }, { @@ -25408,7 +25386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 804/2000 [11:15<16:05, 1.24it/s, loss=0.607]" + "training until 2000: 40%|████ | 804/2000 [14:00<17:51, 1.12it/s, loss=0.324]" ] }, { @@ -25416,7 +25394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 804/2000 [11:15<16:05, 1.24it/s, loss=0.655]" + "training until 2000: 40%|████ | 804/2000 [14:00<17:51, 1.12it/s, loss=0.521]" ] }, { @@ -25424,7 +25402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 805/2000 [11:16<16:37, 1.20it/s, loss=0.655]" + "training until 2000: 40%|████ | 805/2000 [14:01<18:54, 1.05it/s, loss=0.521]" ] }, { @@ -25432,7 +25410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 805/2000 [11:16<16:37, 1.20it/s, loss=0.616]" + "training until 2000: 40%|████ | 805/2000 [14:01<18:54, 1.05it/s, loss=0.367]" ] }, { @@ -25440,7 +25418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 806/2000 [11:17<17:05, 1.16it/s, loss=0.616]" + "training until 2000: 40%|████ | 806/2000 [14:03<20:23, 1.02s/it, loss=0.367]" ] }, { @@ -25448,7 +25426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 806/2000 [11:17<17:05, 1.16it/s, loss=0.592]" + "training until 2000: 40%|████ | 806/2000 [14:03<20:23, 1.02s/it, loss=0.481]" ] }, { @@ -25456,7 +25434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 807/2000 [11:17<16:16, 1.22it/s, loss=0.592]" + "training until 2000: 40%|████ | 807/2000 [14:04<19:32, 1.02it/s, loss=0.481]" ] }, { @@ -25464,7 +25442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 807/2000 [11:17<16:16, 1.22it/s, loss=0.632]" + "training until 2000: 40%|████ | 807/2000 [14:04<19:32, 1.02it/s, loss=0.42] " ] }, { @@ -25472,7 +25450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 808/2000 [11:18<16:42, 1.19it/s, loss=0.632]" + "training until 2000: 40%|████ | 808/2000 [14:04<18:16, 1.09it/s, loss=0.42]" ] }, { @@ -25480,7 +25458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 808/2000 [11:18<16:42, 1.19it/s, loss=0.598]" + "training until 2000: 40%|████ | 808/2000 [14:04<18:16, 1.09it/s, loss=0.498]" ] }, { @@ -25488,7 +25466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 809/2000 [11:19<16:18, 1.22it/s, loss=0.598]" + "training until 2000: 40%|████ | 809/2000 [14:05<18:52, 1.05it/s, loss=0.498]" ] }, { @@ -25496,7 +25474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 809/2000 [11:19<16:18, 1.22it/s, loss=0.609]" + "training until 2000: 40%|████ | 809/2000 [14:05<18:52, 1.05it/s, loss=0.54] " ] }, { @@ -25504,7 +25482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 810/2000 [11:20<16:05, 1.23it/s, loss=0.609]" + "training until 2000: 40%|████ | 810/2000 [14:06<18:43, 1.06it/s, loss=0.54]" ] }, { @@ -25512,7 +25490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 40%|████ | 810/2000 [11:20<16:05, 1.23it/s, loss=0.609]" + "training until 2000: 40%|████ | 810/2000 [14:06<18:43, 1.06it/s, loss=0.559]" ] }, { @@ -25520,7 +25498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 811/2000 [11:21<15:44, 1.26it/s, loss=0.609]" + "training until 2000: 41%|████ | 811/2000 [14:07<18:24, 1.08it/s, loss=0.559]" ] }, { @@ -25528,7 +25506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 811/2000 [11:21<15:44, 1.26it/s, loss=0.628]" + "training until 2000: 41%|████ | 811/2000 [14:07<18:24, 1.08it/s, loss=0.395]" ] }, { @@ -25536,7 +25514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 812/2000 [11:21<15:59, 1.24it/s, loss=0.628]" + "training until 2000: 41%|████ | 812/2000 [14:08<19:07, 1.04it/s, loss=0.395]" ] }, { @@ -25544,7 +25522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 812/2000 [11:21<15:59, 1.24it/s, loss=0.608]" + "training until 2000: 41%|████ | 812/2000 [14:08<19:07, 1.04it/s, loss=0.556]" ] }, { @@ -25552,7 +25530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 813/2000 [11:22<15:03, 1.31it/s, loss=0.608]" + "training until 2000: 41%|████ | 813/2000 [14:09<16:28, 1.20it/s, loss=0.556]" ] }, { @@ -25560,7 +25538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 813/2000 [11:22<15:03, 1.31it/s, loss=0.601]" + "training until 2000: 41%|████ | 813/2000 [14:09<16:28, 1.20it/s, loss=0.457]" ] }, { @@ -25568,7 +25546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 814/2000 [11:23<14:43, 1.34it/s, loss=0.601]" + "training until 2000: 41%|████ | 814/2000 [14:10<16:16, 1.21it/s, loss=0.457]" ] }, { @@ -25576,7 +25554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 814/2000 [11:23<14:43, 1.34it/s, loss=0.615]" + "training until 2000: 41%|████ | 814/2000 [14:10<16:16, 1.21it/s, loss=0.601]" ] }, { @@ -25584,7 +25562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 815/2000 [11:23<14:11, 1.39it/s, loss=0.615]" + "training until 2000: 41%|████ | 815/2000 [14:10<14:48, 1.33it/s, loss=0.601]" ] }, { @@ -25592,7 +25570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 815/2000 [11:23<14:11, 1.39it/s, loss=0.596]" + "training until 2000: 41%|████ | 815/2000 [14:10<14:48, 1.33it/s, loss=0.525]" ] }, { @@ -25600,7 +25578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 816/2000 [11:24<13:37, 1.45it/s, loss=0.596]" + "training until 2000: 41%|████ | 816/2000 [14:12<18:49, 1.05it/s, loss=0.525]" ] }, { @@ -25608,7 +25586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 816/2000 [11:24<13:37, 1.45it/s, loss=0.581]" + "training until 2000: 41%|████ | 816/2000 [14:12<18:49, 1.05it/s, loss=0.557]" ] }, { @@ -25616,7 +25594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 817/2000 [11:25<13:38, 1.44it/s, loss=0.581]" + "training until 2000: 41%|████ | 817/2000 [14:12<17:25, 1.13it/s, loss=0.557]" ] }, { @@ -25624,7 +25602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 817/2000 [11:25<13:38, 1.44it/s, loss=0.604]" + "training until 2000: 41%|████ | 817/2000 [14:12<17:25, 1.13it/s, loss=0.605]" ] }, { @@ -25632,7 +25610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 818/2000 [11:26<14:12, 1.39it/s, loss=0.604]" + "training until 2000: 41%|████ | 818/2000 [14:13<19:05, 1.03it/s, loss=0.605]" ] }, { @@ -25640,7 +25618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 818/2000 [11:26<14:12, 1.39it/s, loss=0.618]" + "training until 2000: 41%|████ | 818/2000 [14:13<19:05, 1.03it/s, loss=0.354]" ] }, { @@ -25648,7 +25626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 819/2000 [11:26<13:43, 1.43it/s, loss=0.618]" + "training until 2000: 41%|████ | 819/2000 [14:15<21:20, 1.08s/it, loss=0.354]" ] }, { @@ -25656,7 +25634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 819/2000 [11:26<13:43, 1.43it/s, loss=0.643]" + "training until 2000: 41%|████ | 819/2000 [14:15<21:20, 1.08s/it, loss=0.48] " ] }, { @@ -25664,7 +25642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 820/2000 [11:27<12:39, 1.55it/s, loss=0.643]" + "training until 2000: 41%|████ | 820/2000 [14:16<22:25, 1.14s/it, loss=0.48]" ] }, { @@ -25672,7 +25650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 820/2000 [11:27<12:39, 1.55it/s, loss=0.625]" + "training until 2000: 41%|████ | 820/2000 [14:16<22:25, 1.14s/it, loss=0.413]" ] }, { @@ -25680,7 +25658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 821/2000 [11:28<13:40, 1.44it/s, loss=0.625]" + "training until 2000: 41%|████ | 821/2000 [14:17<19:22, 1.01it/s, loss=0.413]" ] }, { @@ -25688,7 +25666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 821/2000 [11:28<13:40, 1.44it/s, loss=0.627]" + "training until 2000: 41%|████ | 821/2000 [14:17<19:22, 1.01it/s, loss=0.448]" ] }, { @@ -25696,7 +25674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 822/2000 [11:29<15:48, 1.24it/s, loss=0.627]" + "training until 2000: 41%|████ | 822/2000 [14:18<21:06, 1.08s/it, loss=0.448]" ] }, { @@ -25704,7 +25682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 822/2000 [11:29<15:48, 1.24it/s, loss=0.636]" + "training until 2000: 41%|████ | 822/2000 [14:18<21:06, 1.08s/it, loss=0.306]" ] }, { @@ -25712,7 +25690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 823/2000 [11:29<14:24, 1.36it/s, loss=0.636]" + "training until 2000: 41%|████ | 823/2000 [14:19<20:50, 1.06s/it, loss=0.306]" ] }, { @@ -25720,7 +25698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 823/2000 [11:29<14:24, 1.36it/s, loss=0.583]" + "training until 2000: 41%|████ | 823/2000 [14:19<20:50, 1.06s/it, loss=0.467]" ] }, { @@ -25728,7 +25706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 824/2000 [11:30<13:24, 1.46it/s, loss=0.583]" + "training until 2000: 41%|████ | 824/2000 [14:20<18:56, 1.04it/s, loss=0.467]" ] }, { @@ -25736,7 +25714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████ | 824/2000 [11:30<13:24, 1.46it/s, loss=0.65] " + "training until 2000: 41%|████ | 824/2000 [14:20<18:56, 1.04it/s, loss=0.422]" ] }, { @@ -25744,7 +25722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 825/2000 [11:30<13:21, 1.47it/s, loss=0.65]" + "training until 2000: 41%|████▏ | 825/2000 [14:21<21:17, 1.09s/it, loss=0.422]" ] }, { @@ -25752,7 +25730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 825/2000 [11:30<13:21, 1.47it/s, loss=0.595]" + "training until 2000: 41%|████▏ | 825/2000 [14:21<21:17, 1.09s/it, loss=0.538]" ] }, { @@ -25760,7 +25738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 826/2000 [11:31<13:55, 1.41it/s, loss=0.595]" + "training until 2000: 41%|████▏ | 826/2000 [14:22<20:04, 1.03s/it, loss=0.538]" ] }, { @@ -25768,7 +25746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 826/2000 [11:31<13:55, 1.41it/s, loss=0.597]" + "training until 2000: 41%|████▏ | 826/2000 [14:22<20:04, 1.03s/it, loss=0.471]" ] }, { @@ -25776,7 +25754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 827/2000 [11:32<14:49, 1.32it/s, loss=0.597]" + "training until 2000: 41%|████▏ | 827/2000 [14:23<20:51, 1.07s/it, loss=0.471]" ] }, { @@ -25784,7 +25762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 827/2000 [11:32<14:49, 1.32it/s, loss=0.588]" + "training until 2000: 41%|████▏ | 827/2000 [14:23<20:51, 1.07s/it, loss=0.438]" ] }, { @@ -25792,7 +25770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 828/2000 [11:33<14:32, 1.34it/s, loss=0.588]" + "training until 2000: 41%|████▏ | 828/2000 [14:24<19:24, 1.01it/s, loss=0.438]" ] }, { @@ -25800,7 +25778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 828/2000 [11:33<14:32, 1.34it/s, loss=0.589]" + "training until 2000: 41%|████▏ | 828/2000 [14:24<19:24, 1.01it/s, loss=0.496]" ] }, { @@ -25808,7 +25786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 829/2000 [11:34<15:00, 1.30it/s, loss=0.589]" + "training until 2000: 41%|████▏ | 829/2000 [14:25<18:49, 1.04it/s, loss=0.496]" ] }, { @@ -25816,7 +25794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 41%|████▏ | 829/2000 [11:34<15:00, 1.30it/s, loss=0.586]" + "training until 2000: 41%|████▏ | 829/2000 [14:25<18:49, 1.04it/s, loss=0.532]" ] }, { @@ -25824,7 +25802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 830/2000 [11:34<15:33, 1.25it/s, loss=0.586]" + "training until 2000: 42%|████▏ | 830/2000 [14:26<19:58, 1.02s/it, loss=0.532]" ] }, { @@ -25832,7 +25810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 830/2000 [11:34<15:33, 1.25it/s, loss=0.604]" + "training until 2000: 42%|████▏ | 830/2000 [14:26<19:58, 1.02s/it, loss=0.547]" ] }, { @@ -25840,7 +25818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 831/2000 [11:35<14:56, 1.30it/s, loss=0.604]" + "training until 2000: 42%|████▏ | 831/2000 [14:27<19:15, 1.01it/s, loss=0.547]" ] }, { @@ -25848,7 +25826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 831/2000 [11:35<14:56, 1.30it/s, loss=0.611]" + "training until 2000: 42%|████▏ | 831/2000 [14:27<19:15, 1.01it/s, loss=0.352]" ] }, { @@ -25856,7 +25834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 832/2000 [11:36<17:14, 1.13it/s, loss=0.611]" + "training until 2000: 42%|████▏ | 832/2000 [14:28<19:29, 1.00s/it, loss=0.352]" ] }, { @@ -25864,7 +25842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 832/2000 [11:36<17:14, 1.13it/s, loss=0.6] " + "training until 2000: 42%|████▏ | 832/2000 [14:28<19:29, 1.00s/it, loss=0.393]" ] }, { @@ -25872,7 +25850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 833/2000 [11:37<16:13, 1.20it/s, loss=0.6]" + "training until 2000: 42%|████▏ | 833/2000 [14:29<17:39, 1.10it/s, loss=0.393]" ] }, { @@ -25880,7 +25858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 833/2000 [11:37<16:13, 1.20it/s, loss=0.581]" + "training until 2000: 42%|████▏ | 833/2000 [14:29<17:39, 1.10it/s, loss=0.448]" ] }, { @@ -25888,7 +25866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 834/2000 [11:38<14:59, 1.30it/s, loss=0.581]" + "training until 2000: 42%|████▏ | 834/2000 [14:30<17:46, 1.09it/s, loss=0.448]" ] }, { @@ -25896,7 +25874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 834/2000 [11:38<14:59, 1.30it/s, loss=0.611]" + "training until 2000: 42%|████▏ | 834/2000 [14:30<17:46, 1.09it/s, loss=0.487]" ] }, { @@ -25904,7 +25882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 835/2000 [11:38<13:47, 1.41it/s, loss=0.611]" + "training until 2000: 42%|████▏ | 835/2000 [14:30<17:09, 1.13it/s, loss=0.487]" ] }, { @@ -25912,7 +25890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 835/2000 [11:38<13:47, 1.41it/s, loss=0.623]" + "training until 2000: 42%|████▏ | 835/2000 [14:30<17:09, 1.13it/s, loss=0.522]" ] }, { @@ -25920,7 +25898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 836/2000 [11:39<13:26, 1.44it/s, loss=0.623]" + "training until 2000: 42%|████▏ | 836/2000 [14:31<16:54, 1.15it/s, loss=0.522]" ] }, { @@ -25928,7 +25906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 836/2000 [11:39<13:26, 1.44it/s, loss=0.61] " + "training until 2000: 42%|████▏ | 836/2000 [14:31<16:54, 1.15it/s, loss=0.435]" ] }, { @@ -25936,7 +25914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 837/2000 [11:40<13:26, 1.44it/s, loss=0.61]" + "training until 2000: 42%|████▏ | 837/2000 [14:33<21:37, 1.12s/it, loss=0.435]" ] }, { @@ -25944,7 +25922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 837/2000 [11:40<13:26, 1.44it/s, loss=0.615]" + "training until 2000: 42%|████▏ | 837/2000 [14:33<21:37, 1.12s/it, loss=0.463]" ] }, { @@ -25952,7 +25930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 838/2000 [11:41<14:53, 1.30it/s, loss=0.615]" + "training until 2000: 42%|████▏ | 838/2000 [14:34<20:48, 1.07s/it, loss=0.463]" ] }, { @@ -25960,7 +25938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 838/2000 [11:41<14:53, 1.30it/s, loss=0.565]" + "training until 2000: 42%|████▏ | 838/2000 [14:34<20:48, 1.07s/it, loss=0.421]" ] }, { @@ -25968,7 +25946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 839/2000 [11:41<15:59, 1.21it/s, loss=0.565]" + "training until 2000: 42%|████▏ | 839/2000 [14:35<18:32, 1.04it/s, loss=0.421]" ] }, { @@ -25976,7 +25954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 839/2000 [11:41<15:59, 1.21it/s, loss=0.617]" + "training until 2000: 42%|████▏ | 839/2000 [14:35<18:32, 1.04it/s, loss=0.397]" ] }, { @@ -25984,7 +25962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 840/2000 [11:42<15:53, 1.22it/s, loss=0.617]" + "training until 2000: 42%|████▏ | 840/2000 [14:36<20:47, 1.08s/it, loss=0.397]" ] }, { @@ -25992,7 +25970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 840/2000 [11:42<15:53, 1.22it/s, loss=0.573]" + "training until 2000: 42%|████▏ | 840/2000 [14:36<20:47, 1.08s/it, loss=0.48] " ] }, { @@ -26000,7 +25978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 841/2000 [11:44<19:33, 1.01s/it, loss=0.573]" + "training until 2000: 42%|████▏ | 841/2000 [14:37<21:31, 1.11s/it, loss=0.48]" ] }, { @@ -26008,7 +25986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 841/2000 [11:44<19:33, 1.01s/it, loss=0.587]" + "training until 2000: 42%|████▏ | 841/2000 [14:37<21:31, 1.11s/it, loss=0.415]" ] }, { @@ -26016,7 +25994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 842/2000 [11:45<18:13, 1.06it/s, loss=0.587]" + "training until 2000: 42%|████▏ | 842/2000 [14:38<21:10, 1.10s/it, loss=0.415]" ] }, { @@ -26024,7 +26002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 842/2000 [11:45<18:13, 1.06it/s, loss=0.586]" + "training until 2000: 42%|████▏ | 842/2000 [14:38<21:10, 1.10s/it, loss=0.418]" ] }, { @@ -26032,7 +26010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 843/2000 [11:45<16:32, 1.17it/s, loss=0.586]" + "training until 2000: 42%|████▏ | 843/2000 [14:39<18:09, 1.06it/s, loss=0.418]" ] }, { @@ -26040,7 +26018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 843/2000 [11:45<16:32, 1.17it/s, loss=0.58] " + "training until 2000: 42%|████▏ | 843/2000 [14:39<18:09, 1.06it/s, loss=0.45] " ] }, { @@ -26048,7 +26026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 844/2000 [11:46<16:13, 1.19it/s, loss=0.58]" + "training until 2000: 42%|████▏ | 844/2000 [14:40<19:03, 1.01it/s, loss=0.45]" ] }, { @@ -26056,7 +26034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 844/2000 [11:46<16:13, 1.19it/s, loss=0.593]" + "training until 2000: 42%|████▏ | 844/2000 [14:40<19:03, 1.01it/s, loss=0.507]" ] }, { @@ -26064,7 +26042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 845/2000 [11:47<14:45, 1.30it/s, loss=0.593]" + "training until 2000: 42%|████▏ | 845/2000 [14:41<17:53, 1.08it/s, loss=0.507]" ] }, { @@ -26072,7 +26050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 845/2000 [11:47<14:45, 1.30it/s, loss=0.598]" + "training until 2000: 42%|████▏ | 845/2000 [14:41<17:53, 1.08it/s, loss=0.507]" ] }, { @@ -26080,7 +26058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 846/2000 [11:47<15:04, 1.28it/s, loss=0.598]" + "training until 2000: 42%|████▏ | 846/2000 [14:41<16:51, 1.14it/s, loss=0.507]" ] }, { @@ -26088,7 +26066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 846/2000 [11:47<15:04, 1.28it/s, loss=0.593]" + "training until 2000: 42%|████▏ | 846/2000 [14:41<16:51, 1.14it/s, loss=0.418]" ] }, { @@ -26096,7 +26074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 847/2000 [11:48<15:18, 1.26it/s, loss=0.593]" + "training until 2000: 42%|████▏ | 847/2000 [14:43<18:20, 1.05it/s, loss=0.418]" ] }, { @@ -26104,7 +26082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 847/2000 [11:48<15:18, 1.26it/s, loss=0.578]" + "training until 2000: 42%|████▏ | 847/2000 [14:43<18:20, 1.05it/s, loss=0.444]" ] }, { @@ -26112,7 +26090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 848/2000 [11:49<15:22, 1.25it/s, loss=0.578]" + "training until 2000: 42%|████▏ | 848/2000 [14:44<18:32, 1.04it/s, loss=0.444]" ] }, { @@ -26120,7 +26098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 848/2000 [11:49<15:22, 1.25it/s, loss=0.591]" + "training until 2000: 42%|████▏ | 848/2000 [14:44<18:32, 1.04it/s, loss=0.509]" ] }, { @@ -26128,7 +26106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 849/2000 [11:50<15:37, 1.23it/s, loss=0.591]" + "training until 2000: 42%|████▏ | 849/2000 [14:44<17:43, 1.08it/s, loss=0.509]" ] }, { @@ -26136,7 +26114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▏ | 849/2000 [11:50<15:37, 1.23it/s, loss=0.609]" + "training until 2000: 42%|████▏ | 849/2000 [14:44<17:43, 1.08it/s, loss=0.547]" ] }, { @@ -26144,7 +26122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▎ | 850/2000 [11:51<16:14, 1.18it/s, loss=0.609]" + "training until 2000: 42%|████▎ | 850/2000 [14:45<17:47, 1.08it/s, loss=0.547]" ] }, { @@ -26152,7 +26130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 42%|████▎ | 850/2000 [11:51<16:14, 1.18it/s, loss=0.584]" + "training until 2000: 42%|████▎ | 850/2000 [14:45<17:47, 1.08it/s, loss=0.426]" ] }, { @@ -26160,7 +26138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 851/2000 [11:52<15:42, 1.22it/s, loss=0.584]" + "training until 2000: 43%|████▎ | 851/2000 [14:46<17:42, 1.08it/s, loss=0.426]" ] }, { @@ -26168,7 +26146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 851/2000 [11:52<15:42, 1.22it/s, loss=0.568]" + "training until 2000: 43%|████▎ | 851/2000 [14:46<17:42, 1.08it/s, loss=0.539]" ] }, { @@ -26176,7 +26154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 852/2000 [11:52<15:35, 1.23it/s, loss=0.568]" + "training until 2000: 43%|████▎ | 852/2000 [14:47<17:47, 1.08it/s, loss=0.539]" ] }, { @@ -26184,7 +26162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 852/2000 [11:52<15:35, 1.23it/s, loss=0.58] " + "training until 2000: 43%|████▎ | 852/2000 [14:47<17:47, 1.08it/s, loss=0.476]" ] }, { @@ -26192,7 +26170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 853/2000 [11:53<16:17, 1.17it/s, loss=0.58]" + "training until 2000: 43%|████▎ | 853/2000 [14:48<17:34, 1.09it/s, loss=0.476]" ] }, { @@ -26200,7 +26178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 853/2000 [11:53<16:17, 1.17it/s, loss=0.603]" + "training until 2000: 43%|████▎ | 853/2000 [14:48<17:34, 1.09it/s, loss=0.463]" ] }, { @@ -26208,7 +26186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 854/2000 [11:54<14:36, 1.31it/s, loss=0.603]" + "training until 2000: 43%|████▎ | 854/2000 [14:49<18:47, 1.02it/s, loss=0.463]" ] }, { @@ -26216,7 +26194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 854/2000 [11:54<14:36, 1.31it/s, loss=0.558]" + "training until 2000: 43%|████▎ | 854/2000 [14:49<18:47, 1.02it/s, loss=0.388]" ] }, { @@ -26224,7 +26202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 855/2000 [11:55<14:18, 1.33it/s, loss=0.558]" + "training until 2000: 43%|████▎ | 855/2000 [14:51<21:22, 1.12s/it, loss=0.388]" ] }, { @@ -26232,7 +26210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 855/2000 [11:55<14:18, 1.33it/s, loss=0.561]" + "training until 2000: 43%|████▎ | 855/2000 [14:51<21:22, 1.12s/it, loss=0.425]" ] }, { @@ -26240,7 +26218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 856/2000 [11:55<14:20, 1.33it/s, loss=0.561]" + "training until 2000: 43%|████▎ | 856/2000 [14:52<23:17, 1.22s/it, loss=0.425]" ] }, { @@ -26248,7 +26226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 856/2000 [11:55<14:20, 1.33it/s, loss=0.562]" + "training until 2000: 43%|████▎ | 856/2000 [14:52<23:17, 1.22s/it, loss=0.557]" ] }, { @@ -26256,7 +26234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 857/2000 [11:56<12:37, 1.51it/s, loss=0.562]" + "training until 2000: 43%|████▎ | 857/2000 [14:53<22:04, 1.16s/it, loss=0.557]" ] }, { @@ -26264,7 +26242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 857/2000 [11:56<12:37, 1.51it/s, loss=0.581]" + "training until 2000: 43%|████▎ | 857/2000 [14:53<22:04, 1.16s/it, loss=0.517]" ] }, { @@ -26272,7 +26250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 858/2000 [11:57<14:29, 1.31it/s, loss=0.581]" + "training until 2000: 43%|████▎ | 858/2000 [14:54<20:32, 1.08s/it, loss=0.517]" ] }, { @@ -26280,7 +26258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 858/2000 [11:57<14:29, 1.31it/s, loss=0.58] " + "training until 2000: 43%|████▎ | 858/2000 [14:54<20:32, 1.08s/it, loss=0.42] " ] }, { @@ -26288,7 +26266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 859/2000 [11:58<14:59, 1.27it/s, loss=0.58]" + "training until 2000: 43%|████▎ | 859/2000 [14:55<18:54, 1.01it/s, loss=0.42]" ] }, { @@ -26296,7 +26274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 859/2000 [11:58<14:59, 1.27it/s, loss=0.571]" + "training until 2000: 43%|████▎ | 859/2000 [14:55<18:54, 1.01it/s, loss=0.453]" ] }, { @@ -26304,7 +26282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 860/2000 [11:59<15:23, 1.23it/s, loss=0.571]" + "training until 2000: 43%|████▎ | 860/2000 [14:55<16:26, 1.16it/s, loss=0.453]" ] }, { @@ -26312,7 +26290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 860/2000 [11:59<15:23, 1.23it/s, loss=0.6] " + "training until 2000: 43%|████▎ | 860/2000 [14:55<16:26, 1.16it/s, loss=0.378]" ] }, { @@ -26320,7 +26298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 861/2000 [11:59<15:05, 1.26it/s, loss=0.6]" + "training until 2000: 43%|████▎ | 861/2000 [14:56<15:07, 1.26it/s, loss=0.378]" ] }, { @@ -26328,7 +26306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 861/2000 [11:59<15:05, 1.26it/s, loss=0.591]" + "training until 2000: 43%|████▎ | 861/2000 [14:56<15:07, 1.26it/s, loss=0.525]" ] }, { @@ -26336,7 +26314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 862/2000 [12:00<15:12, 1.25it/s, loss=0.591]" + "training until 2000: 43%|████▎ | 862/2000 [14:57<16:47, 1.13it/s, loss=0.525]" ] }, { @@ -26344,7 +26322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 862/2000 [12:00<15:12, 1.25it/s, loss=0.545]" + "training until 2000: 43%|████▎ | 862/2000 [14:57<16:47, 1.13it/s, loss=0.439]" ] }, { @@ -26352,7 +26330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 863/2000 [12:01<14:49, 1.28it/s, loss=0.545]" + "training until 2000: 43%|████▎ | 863/2000 [14:59<21:06, 1.11s/it, loss=0.439]" ] }, { @@ -26360,7 +26338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 863/2000 [12:01<14:49, 1.28it/s, loss=0.575]" + "training until 2000: 43%|████▎ | 863/2000 [14:59<21:06, 1.11s/it, loss=0.358]" ] }, { @@ -26368,7 +26346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 864/2000 [12:02<15:23, 1.23it/s, loss=0.575]" + "training until 2000: 43%|████▎ | 864/2000 [15:00<22:08, 1.17s/it, loss=0.358]" ] }, { @@ -26376,7 +26354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 864/2000 [12:02<15:23, 1.23it/s, loss=0.579]" + "training until 2000: 43%|████▎ | 864/2000 [15:00<22:08, 1.17s/it, loss=0.435]" ] }, { @@ -26384,7 +26362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 865/2000 [12:03<15:40, 1.21it/s, loss=0.579]" + "training until 2000: 43%|████▎ | 865/2000 [15:01<18:49, 1.01it/s, loss=0.435]" ] }, { @@ -26392,7 +26370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 865/2000 [12:03<15:40, 1.21it/s, loss=0.55] " + "training until 2000: 43%|████▎ | 865/2000 [15:01<18:49, 1.01it/s, loss=0.46] " ] }, { @@ -26400,7 +26378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 866/2000 [12:03<14:48, 1.28it/s, loss=0.55]" + "training until 2000: 43%|████▎ | 866/2000 [15:01<16:59, 1.11it/s, loss=0.46]" ] }, { @@ -26408,7 +26386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 866/2000 [12:03<14:48, 1.28it/s, loss=0.625]" + "training until 2000: 43%|████▎ | 866/2000 [15:01<16:59, 1.11it/s, loss=0.474]" ] }, { @@ -26416,7 +26394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 867/2000 [12:04<13:01, 1.45it/s, loss=0.625]" + "training until 2000: 43%|████▎ | 867/2000 [15:02<17:43, 1.07it/s, loss=0.474]" ] }, { @@ -26424,7 +26402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 867/2000 [12:04<13:01, 1.45it/s, loss=0.573]" + "training until 2000: 43%|████▎ | 867/2000 [15:02<17:43, 1.07it/s, loss=0.524]" ] }, { @@ -26432,7 +26410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 868/2000 [12:04<12:57, 1.46it/s, loss=0.573]" + "training until 2000: 43%|████▎ | 868/2000 [15:04<20:34, 1.09s/it, loss=0.524]" ] }, { @@ -26440,7 +26418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 868/2000 [12:04<12:57, 1.46it/s, loss=0.578]" + "training until 2000: 43%|████▎ | 868/2000 [15:04<20:34, 1.09s/it, loss=0.528]" ] }, { @@ -26448,7 +26426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 869/2000 [12:05<14:34, 1.29it/s, loss=0.578]" + "training until 2000: 43%|████▎ | 869/2000 [15:05<20:37, 1.09s/it, loss=0.528]" ] }, { @@ -26456,7 +26434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 43%|████▎ | 869/2000 [12:05<14:34, 1.29it/s, loss=0.578]" + "training until 2000: 43%|████▎ | 869/2000 [15:05<20:37, 1.09s/it, loss=0.514]" ] }, { @@ -26464,7 +26442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 870/2000 [12:06<14:54, 1.26it/s, loss=0.578]" + "training until 2000: 44%|████▎ | 870/2000 [15:06<18:47, 1.00it/s, loss=0.514]" ] }, { @@ -26472,7 +26450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 870/2000 [12:06<14:54, 1.26it/s, loss=0.564]" + "training until 2000: 44%|████▎ | 870/2000 [15:06<18:47, 1.00it/s, loss=0.464]" ] }, { @@ -26480,7 +26458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 871/2000 [12:07<15:13, 1.24it/s, loss=0.564]" + "training until 2000: 44%|████▎ | 871/2000 [15:06<17:23, 1.08it/s, loss=0.464]" ] }, { @@ -26488,7 +26466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 871/2000 [12:07<15:13, 1.24it/s, loss=0.556]" + "training until 2000: 44%|████▎ | 871/2000 [15:06<17:23, 1.08it/s, loss=0.428]" ] }, { @@ -26496,7 +26474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 872/2000 [12:08<15:01, 1.25it/s, loss=0.556]" + "training until 2000: 44%|████▎ | 872/2000 [15:07<17:12, 1.09it/s, loss=0.428]" ] }, { @@ -26504,7 +26482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 872/2000 [12:08<15:01, 1.25it/s, loss=0.565]" + "training until 2000: 44%|████▎ | 872/2000 [15:07<17:12, 1.09it/s, loss=0.449]" ] }, { @@ -26512,7 +26490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 873/2000 [12:09<14:29, 1.30it/s, loss=0.565]" + "training until 2000: 44%|████▎ | 873/2000 [15:08<16:30, 1.14it/s, loss=0.449]" ] }, { @@ -26520,7 +26498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 873/2000 [12:09<14:29, 1.30it/s, loss=0.595]" + "training until 2000: 44%|████▎ | 873/2000 [15:08<16:30, 1.14it/s, loss=0.339]" ] }, { @@ -26528,7 +26506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 874/2000 [12:09<15:01, 1.25it/s, loss=0.595]" + "training until 2000: 44%|████▎ | 874/2000 [15:09<15:52, 1.18it/s, loss=0.339]" ] }, { @@ -26536,7 +26514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▎ | 874/2000 [12:09<15:01, 1.25it/s, loss=0.544]" + "training until 2000: 44%|████▎ | 874/2000 [15:09<15:52, 1.18it/s, loss=0.375]" ] }, { @@ -26544,7 +26522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 875/2000 [12:10<14:05, 1.33it/s, loss=0.544]" + "training until 2000: 44%|████▍ | 875/2000 [15:10<17:02, 1.10it/s, loss=0.375]" ] }, { @@ -26552,7 +26530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 875/2000 [12:10<14:05, 1.33it/s, loss=0.527]" + "training until 2000: 44%|████▍ | 875/2000 [15:10<17:02, 1.10it/s, loss=0.383]" ] }, { @@ -26560,7 +26538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 876/2000 [12:11<13:44, 1.36it/s, loss=0.527]" + "training until 2000: 44%|████▍ | 876/2000 [15:11<18:23, 1.02it/s, loss=0.383]" ] }, { @@ -26568,7 +26546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 876/2000 [12:11<13:44, 1.36it/s, loss=0.538]" + "training until 2000: 44%|████▍ | 876/2000 [15:11<18:23, 1.02it/s, loss=0.427]" ] }, { @@ -26576,7 +26554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 877/2000 [12:12<14:37, 1.28it/s, loss=0.538]" + "training until 2000: 44%|████▍ | 877/2000 [15:12<18:07, 1.03it/s, loss=0.427]" ] }, { @@ -26584,7 +26562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 877/2000 [12:12<14:37, 1.28it/s, loss=0.511]" + "training until 2000: 44%|████▍ | 877/2000 [15:12<18:07, 1.03it/s, loss=0.496]" ] }, { @@ -26592,7 +26570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 878/2000 [12:12<14:02, 1.33it/s, loss=0.511]" + "training until 2000: 44%|████▍ | 878/2000 [15:13<16:39, 1.12it/s, loss=0.496]" ] }, { @@ -26600,7 +26578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 878/2000 [12:12<14:02, 1.33it/s, loss=0.585]" + "training until 2000: 44%|████▍ | 878/2000 [15:13<16:39, 1.12it/s, loss=0.461]" ] }, { @@ -26608,7 +26586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 879/2000 [12:13<14:56, 1.25it/s, loss=0.585]" + "training until 2000: 44%|████▍ | 879/2000 [15:13<15:50, 1.18it/s, loss=0.461]" ] }, { @@ -26616,7 +26594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 879/2000 [12:13<14:56, 1.25it/s, loss=0.61] " + "training until 2000: 44%|████▍ | 879/2000 [15:13<15:50, 1.18it/s, loss=0.476]" ] }, { @@ -26624,7 +26602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 880/2000 [12:14<13:29, 1.38it/s, loss=0.61]" + "training until 2000: 44%|████▍ | 880/2000 [15:14<16:28, 1.13it/s, loss=0.476]" ] }, { @@ -26632,7 +26610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 880/2000 [12:14<13:29, 1.38it/s, loss=0.593]" + "training until 2000: 44%|████▍ | 880/2000 [15:14<16:28, 1.13it/s, loss=0.491]" ] }, { @@ -26640,7 +26618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 881/2000 [12:15<14:22, 1.30it/s, loss=0.593]" + "training until 2000: 44%|████▍ | 881/2000 [15:16<17:51, 1.04it/s, loss=0.491]" ] }, { @@ -26648,7 +26626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 881/2000 [12:15<14:22, 1.30it/s, loss=0.562]" + "training until 2000: 44%|████▍ | 881/2000 [15:16<17:51, 1.04it/s, loss=0.442]" ] }, { @@ -26656,7 +26634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 882/2000 [12:15<13:21, 1.39it/s, loss=0.562]" + "training until 2000: 44%|████▍ | 882/2000 [15:16<17:28, 1.07it/s, loss=0.442]" ] }, { @@ -26664,7 +26642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 882/2000 [12:15<13:21, 1.39it/s, loss=0.583]" + "training until 2000: 44%|████▍ | 882/2000 [15:16<17:28, 1.07it/s, loss=0.344]" ] }, { @@ -26672,7 +26650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 883/2000 [12:16<13:56, 1.34it/s, loss=0.583]" + "training until 2000: 44%|████▍ | 883/2000 [15:17<15:53, 1.17it/s, loss=0.344]" ] }, { @@ -26680,7 +26658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 883/2000 [12:16<13:56, 1.34it/s, loss=0.593]" + "training until 2000: 44%|████▍ | 883/2000 [15:17<15:53, 1.17it/s, loss=0.402]" ] }, { @@ -26688,7 +26666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 884/2000 [12:17<15:28, 1.20it/s, loss=0.593]" + "training until 2000: 44%|████▍ | 884/2000 [15:18<15:26, 1.20it/s, loss=0.402]" ] }, { @@ -26696,7 +26674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 884/2000 [12:17<15:28, 1.20it/s, loss=0.579]" + "training until 2000: 44%|████▍ | 884/2000 [15:18<15:26, 1.20it/s, loss=0.46] " ] }, { @@ -26704,7 +26682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 885/2000 [12:18<15:12, 1.22it/s, loss=0.579]" + "training until 2000: 44%|████▍ | 885/2000 [15:19<14:56, 1.24it/s, loss=0.46]" ] }, { @@ -26712,7 +26690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 885/2000 [12:18<15:12, 1.22it/s, loss=0.572]" + "training until 2000: 44%|████▍ | 885/2000 [15:19<14:56, 1.24it/s, loss=0.414]" ] }, { @@ -26720,7 +26698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 886/2000 [12:19<14:24, 1.29it/s, loss=0.572]" + "training until 2000: 44%|████▍ | 886/2000 [15:20<15:47, 1.18it/s, loss=0.414]" ] }, { @@ -26728,7 +26706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 886/2000 [12:19<14:24, 1.29it/s, loss=0.639]" + "training until 2000: 44%|████▍ | 886/2000 [15:20<15:47, 1.18it/s, loss=0.578]" ] }, { @@ -26736,7 +26714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 887/2000 [12:20<15:22, 1.21it/s, loss=0.639]" + "training until 2000: 44%|████▍ | 887/2000 [15:21<16:27, 1.13it/s, loss=0.578]" ] }, { @@ -26744,7 +26722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 887/2000 [12:20<15:22, 1.21it/s, loss=0.559]" + "training until 2000: 44%|████▍ | 887/2000 [15:21<16:27, 1.13it/s, loss=0.312]" ] }, { @@ -26752,7 +26730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 888/2000 [12:21<16:21, 1.13it/s, loss=0.559]" + "training until 2000: 44%|████▍ | 888/2000 [15:22<16:48, 1.10it/s, loss=0.312]" ] }, { @@ -26760,7 +26738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 888/2000 [12:21<16:21, 1.13it/s, loss=0.685]" + "training until 2000: 44%|████▍ | 888/2000 [15:22<16:48, 1.10it/s, loss=0.519]" ] }, { @@ -26768,7 +26746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 889/2000 [12:21<16:21, 1.13it/s, loss=0.685]" + "training until 2000: 44%|████▍ | 889/2000 [15:23<17:37, 1.05it/s, loss=0.519]" ] }, { @@ -26776,7 +26754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 889/2000 [12:21<16:21, 1.13it/s, loss=0.574]" + "training until 2000: 44%|████▍ | 889/2000 [15:23<17:37, 1.05it/s, loss=0.359]" ] }, { @@ -26784,7 +26762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 890/2000 [12:22<15:28, 1.20it/s, loss=0.574]" + "training until 2000: 44%|████▍ | 890/2000 [15:23<17:19, 1.07it/s, loss=0.359]" ] }, { @@ -26792,7 +26770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 44%|████▍ | 890/2000 [12:22<15:28, 1.20it/s, loss=0.565]" + "training until 2000: 44%|████▍ | 890/2000 [15:23<17:19, 1.07it/s, loss=0.404]" ] }, { @@ -26800,7 +26778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 891/2000 [12:23<15:42, 1.18it/s, loss=0.565]" + "training until 2000: 45%|████▍ | 891/2000 [15:25<17:53, 1.03it/s, loss=0.404]" ] }, { @@ -26808,7 +26786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 891/2000 [12:23<15:42, 1.18it/s, loss=0.568]" + "training until 2000: 45%|████▍ | 891/2000 [15:25<17:53, 1.03it/s, loss=0.429]" ] }, { @@ -26816,7 +26794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 892/2000 [12:24<13:57, 1.32it/s, loss=0.568]" + "training until 2000: 45%|████▍ | 892/2000 [15:26<18:41, 1.01s/it, loss=0.429]" ] }, { @@ -26824,7 +26802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 892/2000 [12:24<13:57, 1.32it/s, loss=0.529]" + "training until 2000: 45%|████▍ | 892/2000 [15:26<18:41, 1.01s/it, loss=0.426]" ] }, { @@ -26832,7 +26810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 893/2000 [12:24<13:12, 1.40it/s, loss=0.529]" + "training until 2000: 45%|████▍ | 893/2000 [15:27<18:57, 1.03s/it, loss=0.426]" ] }, { @@ -26840,7 +26818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 893/2000 [12:24<13:12, 1.40it/s, loss=0.538]" + "training until 2000: 45%|████▍ | 893/2000 [15:27<18:57, 1.03s/it, loss=0.293]" ] }, { @@ -26848,7 +26826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 894/2000 [12:25<13:47, 1.34it/s, loss=0.538]" + "training until 2000: 45%|████▍ | 894/2000 [15:28<20:11, 1.10s/it, loss=0.293]" ] }, { @@ -26856,7 +26834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 894/2000 [12:25<13:47, 1.34it/s, loss=0.579]" + "training until 2000: 45%|████▍ | 894/2000 [15:28<20:11, 1.10s/it, loss=0.384]" ] }, { @@ -26864,7 +26842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 895/2000 [12:26<13:29, 1.37it/s, loss=0.579]" + "training until 2000: 45%|████▍ | 895/2000 [15:29<19:12, 1.04s/it, loss=0.384]" ] }, { @@ -26872,7 +26850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 895/2000 [12:26<13:29, 1.37it/s, loss=0.58] " + "training until 2000: 45%|████▍ | 895/2000 [15:29<19:12, 1.04s/it, loss=0.402]" ] }, { @@ -26880,7 +26858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 896/2000 [12:27<14:25, 1.28it/s, loss=0.58]" + "training until 2000: 45%|████▍ | 896/2000 [15:30<18:17, 1.01it/s, loss=0.402]" ] }, { @@ -26888,7 +26866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 896/2000 [12:27<14:25, 1.28it/s, loss=0.547]" + "training until 2000: 45%|████▍ | 896/2000 [15:30<18:17, 1.01it/s, loss=0.408]" ] }, { @@ -26896,7 +26874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 897/2000 [12:28<16:08, 1.14it/s, loss=0.547]" + "training until 2000: 45%|████▍ | 897/2000 [15:31<17:45, 1.04it/s, loss=0.408]" ] }, { @@ -26904,7 +26882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 897/2000 [12:28<16:08, 1.14it/s, loss=0.57] " + "training until 2000: 45%|████▍ | 897/2000 [15:31<17:45, 1.04it/s, loss=0.549]" ] }, { @@ -26912,7 +26890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 898/2000 [12:29<17:09, 1.07it/s, loss=0.57]" + "training until 2000: 45%|████▍ | 898/2000 [15:32<19:05, 1.04s/it, loss=0.549]" ] }, { @@ -26920,7 +26898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 898/2000 [12:29<17:09, 1.07it/s, loss=0.533]" + "training until 2000: 45%|████▍ | 898/2000 [15:32<19:05, 1.04s/it, loss=0.368]" ] }, { @@ -26928,7 +26906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 899/2000 [12:30<17:26, 1.05it/s, loss=0.533]" + "training until 2000: 45%|████▍ | 899/2000 [15:33<18:57, 1.03s/it, loss=0.368]" ] }, { @@ -26936,7 +26914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▍ | 899/2000 [12:30<17:26, 1.05it/s, loss=0.518]" + "training until 2000: 45%|████▍ | 899/2000 [15:33<18:57, 1.03s/it, loss=0.465]" ] }, { @@ -26944,7 +26922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 900/2000 [12:31<16:38, 1.10it/s, loss=0.518]" + "training until 2000: 45%|████▌ | 900/2000 [15:34<17:01, 1.08it/s, loss=0.465]" ] }, { @@ -26952,7 +26930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 900/2000 [12:31<16:38, 1.10it/s, loss=0.586]" + "training until 2000: 45%|████▌ | 900/2000 [15:34<17:01, 1.08it/s, loss=0.393]" ] }, { @@ -26960,7 +26938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 901/2000 [12:31<15:17, 1.20it/s, loss=0.586]" + "training until 2000: 45%|████▌ | 901/2000 [15:35<18:19, 1.00s/it, loss=0.393]" ] }, { @@ -26968,7 +26946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 901/2000 [12:31<15:17, 1.20it/s, loss=0.574]" + "training until 2000: 45%|████▌ | 901/2000 [15:35<18:19, 1.00s/it, loss=0.445]" ] }, { @@ -26976,7 +26954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 902/2000 [12:32<15:15, 1.20it/s, loss=0.574]" + "training until 2000: 45%|████▌ | 902/2000 [15:36<17:59, 1.02it/s, loss=0.445]" ] }, { @@ -26984,7 +26962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 902/2000 [12:32<15:15, 1.20it/s, loss=0.552]" + "training until 2000: 45%|████▌ | 902/2000 [15:36<17:59, 1.02it/s, loss=0.369]" ] }, { @@ -26992,7 +26970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 903/2000 [12:33<15:06, 1.21it/s, loss=0.552]" + "training until 2000: 45%|████▌ | 903/2000 [15:37<20:20, 1.11s/it, loss=0.369]" ] }, { @@ -27000,7 +26978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 903/2000 [12:33<15:06, 1.21it/s, loss=0.551]" + "training until 2000: 45%|████▌ | 903/2000 [15:37<20:20, 1.11s/it, loss=0.404]" ] }, { @@ -27008,7 +26986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 904/2000 [12:34<14:43, 1.24it/s, loss=0.551]" + "training until 2000: 45%|████▌ | 904/2000 [15:38<17:55, 1.02it/s, loss=0.404]" ] }, { @@ -27016,7 +26994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 904/2000 [12:34<14:43, 1.24it/s, loss=0.56] " + "training until 2000: 45%|████▌ | 904/2000 [15:38<17:55, 1.02it/s, loss=0.44] " ] }, { @@ -27024,7 +27002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 905/2000 [12:34<14:35, 1.25it/s, loss=0.56]" + "training until 2000: 45%|████▌ | 905/2000 [15:38<16:18, 1.12it/s, loss=0.44]" ] }, { @@ -27032,7 +27010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 905/2000 [12:34<14:35, 1.25it/s, loss=0.529]" + "training until 2000: 45%|████▌ | 905/2000 [15:38<16:18, 1.12it/s, loss=0.589]" ] }, { @@ -27040,7 +27018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 906/2000 [12:35<14:52, 1.23it/s, loss=0.529]" + "training until 2000: 45%|████▌ | 906/2000 [15:39<15:49, 1.15it/s, loss=0.589]" ] }, { @@ -27048,7 +27026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 906/2000 [12:35<14:52, 1.23it/s, loss=0.586]" + "training until 2000: 45%|████▌ | 906/2000 [15:39<15:49, 1.15it/s, loss=0.389]" ] }, { @@ -27056,7 +27034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 907/2000 [12:36<14:12, 1.28it/s, loss=0.586]" + "training until 2000: 45%|████▌ | 907/2000 [15:40<16:28, 1.11it/s, loss=0.389]" ] }, { @@ -27064,7 +27042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 907/2000 [12:36<14:12, 1.28it/s, loss=0.543]" + "training until 2000: 45%|████▌ | 907/2000 [15:40<16:28, 1.11it/s, loss=0.369]" ] }, { @@ -27072,7 +27050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 908/2000 [12:37<13:16, 1.37it/s, loss=0.543]" + "training until 2000: 45%|████▌ | 908/2000 [15:41<16:51, 1.08it/s, loss=0.369]" ] }, { @@ -27080,7 +27058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 908/2000 [12:37<13:16, 1.37it/s, loss=0.566]" + "training until 2000: 45%|████▌ | 908/2000 [15:41<16:51, 1.08it/s, loss=0.509]" ] }, { @@ -27088,7 +27066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 909/2000 [12:37<12:31, 1.45it/s, loss=0.566]" + "training until 2000: 45%|████▌ | 909/2000 [15:42<17:48, 1.02it/s, loss=0.509]" ] }, { @@ -27096,7 +27074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 45%|████▌ | 909/2000 [12:37<12:31, 1.45it/s, loss=0.54] " + "training until 2000: 45%|████▌ | 909/2000 [15:42<17:48, 1.02it/s, loss=0.442]" ] }, { @@ -27104,7 +27082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 910/2000 [12:38<11:48, 1.54it/s, loss=0.54]" + "training until 2000: 46%|████▌ | 910/2000 [15:43<17:20, 1.05it/s, loss=0.442]" ] }, { @@ -27112,7 +27090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 910/2000 [12:38<11:48, 1.54it/s, loss=0.541]" + "training until 2000: 46%|████▌ | 910/2000 [15:43<17:20, 1.05it/s, loss=0.366]" ] }, { @@ -27120,7 +27098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 911/2000 [12:39<13:16, 1.37it/s, loss=0.541]" + "training until 2000: 46%|████▌ | 911/2000 [15:44<17:38, 1.03it/s, loss=0.366]" ] }, { @@ -27128,7 +27106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 911/2000 [12:39<13:16, 1.37it/s, loss=0.548]" + "training until 2000: 46%|████▌ | 911/2000 [15:44<17:38, 1.03it/s, loss=0.4] " ] }, { @@ -27136,7 +27114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 912/2000 [12:40<14:48, 1.22it/s, loss=0.548]" + "training until 2000: 46%|████▌ | 912/2000 [15:45<15:09, 1.20it/s, loss=0.4]" ] }, { @@ -27144,7 +27122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 912/2000 [12:40<14:48, 1.22it/s, loss=0.54] " + "training until 2000: 46%|████▌ | 912/2000 [15:45<15:09, 1.20it/s, loss=0.411]" ] }, { @@ -27152,7 +27130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 913/2000 [12:40<14:16, 1.27it/s, loss=0.54]" + "training until 2000: 46%|████▌ | 913/2000 [15:45<14:19, 1.26it/s, loss=0.411]" ] }, { @@ -27160,7 +27138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 913/2000 [12:40<14:16, 1.27it/s, loss=0.545]" + "training until 2000: 46%|████▌ | 913/2000 [15:45<14:19, 1.26it/s, loss=0.415]" ] }, { @@ -27168,7 +27146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 914/2000 [12:41<13:52, 1.30it/s, loss=0.545]" + "training until 2000: 46%|████▌ | 914/2000 [15:47<15:59, 1.13it/s, loss=0.415]" ] }, { @@ -27176,7 +27154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 914/2000 [12:41<13:52, 1.30it/s, loss=0.555]" + "training until 2000: 46%|████▌ | 914/2000 [15:47<15:59, 1.13it/s, loss=0.358]" ] }, { @@ -27184,7 +27162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 915/2000 [12:42<13:52, 1.30it/s, loss=0.555]" + "training until 2000: 46%|████▌ | 915/2000 [15:48<17:13, 1.05it/s, loss=0.358]" ] }, { @@ -27192,7 +27170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 915/2000 [12:42<13:52, 1.30it/s, loss=0.56] " + "training until 2000: 46%|████▌ | 915/2000 [15:48<17:13, 1.05it/s, loss=0.42] " ] }, { @@ -27200,7 +27178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 916/2000 [12:42<12:57, 1.39it/s, loss=0.56]" + "training until 2000: 46%|████▌ | 916/2000 [15:49<18:57, 1.05s/it, loss=0.42]" ] }, { @@ -27208,7 +27186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 916/2000 [12:42<12:57, 1.39it/s, loss=0.617]" + "training until 2000: 46%|████▌ | 916/2000 [15:49<18:57, 1.05s/it, loss=0.408]" ] }, { @@ -27216,7 +27194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 917/2000 [12:43<13:23, 1.35it/s, loss=0.617]" + "training until 2000: 46%|████▌ | 917/2000 [15:50<17:20, 1.04it/s, loss=0.408]" ] }, { @@ -27224,7 +27202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 917/2000 [12:43<13:23, 1.35it/s, loss=0.498]" + "training until 2000: 46%|████▌ | 917/2000 [15:50<17:20, 1.04it/s, loss=0.326]" ] }, { @@ -27232,7 +27210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 918/2000 [12:44<12:28, 1.44it/s, loss=0.498]" + "training until 2000: 46%|████▌ | 918/2000 [15:51<17:34, 1.03it/s, loss=0.326]" ] }, { @@ -27240,7 +27218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 918/2000 [12:44<12:28, 1.44it/s, loss=0.653]" + "training until 2000: 46%|████▌ | 918/2000 [15:51<17:34, 1.03it/s, loss=0.3] " ] }, { @@ -27248,7 +27226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 919/2000 [12:45<15:56, 1.13it/s, loss=0.653]" + "training until 2000: 46%|████▌ | 919/2000 [15:52<18:36, 1.03s/it, loss=0.3]" ] }, { @@ -27256,7 +27234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 919/2000 [12:45<15:56, 1.13it/s, loss=0.502]" + "training until 2000: 46%|████▌ | 919/2000 [15:52<18:36, 1.03s/it, loss=0.362]" ] }, { @@ -27264,7 +27242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 920/2000 [12:46<16:38, 1.08it/s, loss=0.502]" + "training until 2000: 46%|████▌ | 920/2000 [15:53<18:49, 1.05s/it, loss=0.362]" ] }, { @@ -27272,7 +27250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 920/2000 [12:46<16:38, 1.08it/s, loss=0.574]" + "training until 2000: 46%|████▌ | 920/2000 [15:53<18:49, 1.05s/it, loss=0.268]" ] }, { @@ -27280,7 +27258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 921/2000 [12:47<16:45, 1.07it/s, loss=0.574]" + "training until 2000: 46%|████▌ | 921/2000 [15:54<20:35, 1.14s/it, loss=0.268]" ] }, { @@ -27288,7 +27266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 921/2000 [12:47<16:45, 1.07it/s, loss=0.553]" + "training until 2000: 46%|████▌ | 921/2000 [15:54<20:35, 1.14s/it, loss=0.32] " ] }, { @@ -27296,7 +27274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 922/2000 [12:48<17:22, 1.03it/s, loss=0.553]" + "training until 2000: 46%|████▌ | 922/2000 [15:55<19:11, 1.07s/it, loss=0.32]" ] }, { @@ -27304,7 +27282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 922/2000 [12:48<17:22, 1.03it/s, loss=0.516]" + "training until 2000: 46%|████▌ | 922/2000 [15:55<19:11, 1.07s/it, loss=0.289]" ] }, { @@ -27312,7 +27290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 923/2000 [12:49<15:35, 1.15it/s, loss=0.516]" + "training until 2000: 46%|████▌ | 923/2000 [15:57<21:49, 1.22s/it, loss=0.289]" ] }, { @@ -27320,7 +27298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 923/2000 [12:49<15:35, 1.15it/s, loss=0.567]" + "training until 2000: 46%|████▌ | 923/2000 [15:57<21:49, 1.22s/it, loss=0.387]" ] }, { @@ -27328,7 +27306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 924/2000 [12:50<16:31, 1.09it/s, loss=0.567]" + "training until 2000: 46%|████▌ | 924/2000 [15:57<18:37, 1.04s/it, loss=0.387]" ] }, { @@ -27336,7 +27314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▌ | 924/2000 [12:50<16:31, 1.09it/s, loss=0.592]" + "training until 2000: 46%|████▌ | 924/2000 [15:57<18:37, 1.04s/it, loss=0.335]" ] }, { @@ -27344,7 +27322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 925/2000 [12:51<17:24, 1.03it/s, loss=0.592]" + "training until 2000: 46%|████▋ | 925/2000 [15:58<17:04, 1.05it/s, loss=0.335]" ] }, { @@ -27352,7 +27330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 925/2000 [12:51<17:24, 1.03it/s, loss=0.52] " + "training until 2000: 46%|████▋ | 925/2000 [15:58<17:04, 1.05it/s, loss=0.412]" ] }, { @@ -27360,7 +27338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 926/2000 [12:52<17:08, 1.04it/s, loss=0.52]" + "training until 2000: 46%|████▋ | 926/2000 [15:59<15:33, 1.15it/s, loss=0.412]" ] }, { @@ -27368,7 +27346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 926/2000 [12:52<17:08, 1.04it/s, loss=0.513]" + "training until 2000: 46%|████▋ | 926/2000 [15:59<15:33, 1.15it/s, loss=0.386]" ] }, { @@ -27376,7 +27354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 927/2000 [12:53<16:05, 1.11it/s, loss=0.513]" + "training until 2000: 46%|████▋ | 927/2000 [16:00<15:04, 1.19it/s, loss=0.386]" ] }, { @@ -27384,7 +27362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 927/2000 [12:53<16:05, 1.11it/s, loss=0.544]" + "training until 2000: 46%|████▋ | 927/2000 [16:00<15:04, 1.19it/s, loss=0.497]" ] }, { @@ -27392,7 +27370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 928/2000 [12:54<17:30, 1.02it/s, loss=0.544]" + "training until 2000: 46%|████▋ | 928/2000 [16:01<17:25, 1.03it/s, loss=0.497]" ] }, { @@ -27400,7 +27378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 928/2000 [12:54<17:30, 1.02it/s, loss=0.582]" + "training until 2000: 46%|████▋ | 928/2000 [16:01<17:25, 1.03it/s, loss=0.38] " ] }, { @@ -27408,7 +27386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 929/2000 [12:55<16:38, 1.07it/s, loss=0.582]" + "training until 2000: 46%|████▋ | 929/2000 [16:02<16:41, 1.07it/s, loss=0.38]" ] }, { @@ -27416,7 +27394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 929/2000 [12:55<16:38, 1.07it/s, loss=0.559]" + "training until 2000: 46%|████▋ | 929/2000 [16:02<16:41, 1.07it/s, loss=0.378]" ] }, { @@ -27424,7 +27402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 930/2000 [12:55<14:59, 1.19it/s, loss=0.559]" + "training until 2000: 46%|████▋ | 930/2000 [16:03<18:38, 1.05s/it, loss=0.378]" ] }, { @@ -27432,7 +27410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 46%|████▋ | 930/2000 [12:55<14:59, 1.19it/s, loss=0.504]" + "training until 2000: 46%|████▋ | 930/2000 [16:03<18:38, 1.05s/it, loss=0.271]" ] }, { @@ -27440,7 +27418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 931/2000 [12:56<14:46, 1.21it/s, loss=0.504]" + "training until 2000: 47%|████▋ | 931/2000 [16:04<18:04, 1.01s/it, loss=0.271]" ] }, { @@ -27448,7 +27426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 931/2000 [12:56<14:46, 1.21it/s, loss=0.508]" + "training until 2000: 47%|████▋ | 931/2000 [16:04<18:04, 1.01s/it, loss=0.307]" ] }, { @@ -27456,7 +27434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 932/2000 [12:57<16:49, 1.06it/s, loss=0.508]" + "training until 2000: 47%|████▋ | 932/2000 [16:05<18:19, 1.03s/it, loss=0.307]" ] }, { @@ -27464,7 +27442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 932/2000 [12:57<16:49, 1.06it/s, loss=0.536]" + "training until 2000: 47%|████▋ | 932/2000 [16:05<18:19, 1.03s/it, loss=0.348]" ] }, { @@ -27472,7 +27450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 933/2000 [12:58<17:26, 1.02it/s, loss=0.536]" + "training until 2000: 47%|████▋ | 933/2000 [16:06<16:11, 1.10it/s, loss=0.348]" ] }, { @@ -27480,7 +27458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 933/2000 [12:58<17:26, 1.02it/s, loss=0.527]" + "training until 2000: 47%|████▋ | 933/2000 [16:06<16:11, 1.10it/s, loss=0.244]" ] }, { @@ -27488,7 +27466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 934/2000 [12:59<15:41, 1.13it/s, loss=0.527]" + "training until 2000: 47%|████▋ | 934/2000 [16:07<16:40, 1.07it/s, loss=0.244]" ] }, { @@ -27496,7 +27474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 934/2000 [12:59<15:41, 1.13it/s, loss=0.553]" + "training until 2000: 47%|████▋ | 934/2000 [16:07<16:40, 1.07it/s, loss=0.323]" ] }, { @@ -27504,7 +27482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 935/2000 [13:00<13:33, 1.31it/s, loss=0.553]" + "training until 2000: 47%|████▋ | 935/2000 [16:07<15:30, 1.14it/s, loss=0.323]" ] }, { @@ -27512,7 +27490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 935/2000 [13:00<13:33, 1.31it/s, loss=0.526]" + "training until 2000: 47%|████▋ | 935/2000 [16:07<15:30, 1.14it/s, loss=0.464]" ] }, { @@ -27520,7 +27498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 936/2000 [13:00<13:38, 1.30it/s, loss=0.526]" + "training until 2000: 47%|████▋ | 936/2000 [16:08<15:08, 1.17it/s, loss=0.464]" ] }, { @@ -27528,7 +27506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 936/2000 [13:00<13:38, 1.30it/s, loss=0.559]" + "training until 2000: 47%|████▋ | 936/2000 [16:08<15:08, 1.17it/s, loss=0.327]" ] }, { @@ -27536,7 +27514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 937/2000 [13:01<13:17, 1.33it/s, loss=0.559]" + "training until 2000: 47%|████▋ | 937/2000 [16:09<16:50, 1.05it/s, loss=0.327]" ] }, { @@ -27544,7 +27522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 937/2000 [13:01<13:17, 1.33it/s, loss=0.564]" + "training until 2000: 47%|████▋ | 937/2000 [16:09<16:50, 1.05it/s, loss=0.397]" ] }, { @@ -27552,7 +27530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 938/2000 [13:02<13:10, 1.34it/s, loss=0.564]" + "training until 2000: 47%|████▋ | 938/2000 [16:10<17:34, 1.01it/s, loss=0.397]" ] }, { @@ -27560,7 +27538,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 938/2000 [13:02<13:10, 1.34it/s, loss=0.492]" + "training until 2000: 47%|████▋ | 938/2000 [16:10<17:34, 1.01it/s, loss=0.335]" ] }, { @@ -27568,7 +27546,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 939/2000 [13:02<12:43, 1.39it/s, loss=0.492]" + "training until 2000: 47%|████▋ | 939/2000 [16:11<16:18, 1.08it/s, loss=0.335]" ] }, { @@ -27576,7 +27554,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 939/2000 [13:02<12:43, 1.39it/s, loss=0.51] " + "training until 2000: 47%|████▋ | 939/2000 [16:11<16:18, 1.08it/s, loss=0.311]" ] }, { @@ -27584,7 +27562,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 940/2000 [13:03<12:44, 1.39it/s, loss=0.51]" + "training until 2000: 47%|████▋ | 940/2000 [16:12<17:25, 1.01it/s, loss=0.311]" ] }, { @@ -27592,7 +27570,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 940/2000 [13:03<12:44, 1.39it/s, loss=0.534]" + "training until 2000: 47%|████▋ | 940/2000 [16:12<17:25, 1.01it/s, loss=0.345]" ] }, { @@ -27600,7 +27578,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 941/2000 [13:04<13:48, 1.28it/s, loss=0.534]" + "training until 2000: 47%|████▋ | 941/2000 [16:14<19:14, 1.09s/it, loss=0.345]" ] }, { @@ -27608,7 +27586,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 941/2000 [13:04<13:48, 1.28it/s, loss=0.537]" + "training until 2000: 47%|████▋ | 941/2000 [16:14<19:14, 1.09s/it, loss=0.272]" ] }, { @@ -27616,7 +27594,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 942/2000 [13:05<13:08, 1.34it/s, loss=0.537]" + "training until 2000: 47%|████▋ | 942/2000 [16:15<19:21, 1.10s/it, loss=0.272]" ] }, { @@ -27624,7 +27602,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 942/2000 [13:05<13:08, 1.34it/s, loss=0.512]" + "training until 2000: 47%|████▋ | 942/2000 [16:15<19:21, 1.10s/it, loss=0.437]" ] }, { @@ -27632,7 +27610,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 943/2000 [13:05<12:52, 1.37it/s, loss=0.512]" + "training until 2000: 47%|████▋ | 943/2000 [16:16<17:16, 1.02it/s, loss=0.437]" ] }, { @@ -27640,7 +27618,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 943/2000 [13:05<12:52, 1.37it/s, loss=0.648]" + "training until 2000: 47%|████▋ | 943/2000 [16:16<17:16, 1.02it/s, loss=0.347]" ] }, { @@ -27648,7 +27626,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 944/2000 [13:06<13:37, 1.29it/s, loss=0.648]" + "training until 2000: 47%|████▋ | 944/2000 [16:17<19:01, 1.08s/it, loss=0.347]" ] }, { @@ -27656,7 +27634,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 944/2000 [13:06<13:37, 1.29it/s, loss=0.542]" + "training until 2000: 47%|████▋ | 944/2000 [16:17<19:01, 1.08s/it, loss=0.275]" ] }, { @@ -27664,7 +27642,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 945/2000 [13:07<14:11, 1.24it/s, loss=0.542]" + "training until 2000: 47%|████▋ | 945/2000 [16:17<16:03, 1.09it/s, loss=0.275]" ] }, { @@ -27672,7 +27650,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 945/2000 [13:07<14:11, 1.24it/s, loss=0.645]" + "training until 2000: 47%|████▋ | 945/2000 [16:17<16:03, 1.09it/s, loss=0.388]" ] }, { @@ -27680,7 +27658,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 946/2000 [13:08<13:58, 1.26it/s, loss=0.645]" + "training until 2000: 47%|████▋ | 946/2000 [16:18<15:52, 1.11it/s, loss=0.388]" ] }, { @@ -27688,7 +27666,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 946/2000 [13:08<13:58, 1.26it/s, loss=0.559]" + "training until 2000: 47%|████▋ | 946/2000 [16:18<15:52, 1.11it/s, loss=0.381]" ] }, { @@ -27696,7 +27674,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 947/2000 [13:09<13:44, 1.28it/s, loss=0.559]" + "training until 2000: 47%|████▋ | 947/2000 [16:19<17:48, 1.02s/it, loss=0.381]" ] }, { @@ -27704,7 +27682,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 947/2000 [13:09<13:44, 1.28it/s, loss=0.506]" + "training until 2000: 47%|████▋ | 947/2000 [16:19<17:48, 1.02s/it, loss=0.425]" ] }, { @@ -27712,7 +27690,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 948/2000 [13:10<14:19, 1.22it/s, loss=0.506]" + "training until 2000: 47%|████▋ | 948/2000 [16:21<17:44, 1.01s/it, loss=0.425]" ] }, { @@ -27720,7 +27698,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 948/2000 [13:10<14:19, 1.22it/s, loss=0.517]" + "training until 2000: 47%|████▋ | 948/2000 [16:21<17:44, 1.01s/it, loss=0.311]" ] }, { @@ -27728,7 +27706,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 949/2000 [13:10<14:08, 1.24it/s, loss=0.517]" + "training until 2000: 47%|████▋ | 949/2000 [16:22<18:19, 1.05s/it, loss=0.311]" ] }, { @@ -27736,7 +27714,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 47%|████▋ | 949/2000 [13:10<14:08, 1.24it/s, loss=0.525]" + "training until 2000: 47%|████▋ | 949/2000 [16:22<18:19, 1.05s/it, loss=0.411]" ] }, { @@ -27744,7 +27722,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 950/2000 [13:11<13:21, 1.31it/s, loss=0.525]" + "training until 2000: 48%|████▊ | 950/2000 [16:22<16:02, 1.09it/s, loss=0.411]" ] }, { @@ -27752,7 +27730,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 950/2000 [13:11<13:21, 1.31it/s, loss=0.559]" + "training until 2000: 48%|████▊ | 950/2000 [16:22<16:02, 1.09it/s, loss=0.349]" ] }, { @@ -27760,7 +27738,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 951/2000 [13:12<12:52, 1.36it/s, loss=0.559]" + "training until 2000: 48%|████▊ | 951/2000 [16:23<17:39, 1.01s/it, loss=0.349]" ] }, { @@ -27768,7 +27746,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 951/2000 [13:12<12:52, 1.36it/s, loss=0.509]" + "training until 2000: 48%|████▊ | 951/2000 [16:23<17:39, 1.01s/it, loss=0.276]" ] }, { @@ -27776,7 +27754,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 952/2000 [13:13<14:16, 1.22it/s, loss=0.509]" + "training until 2000: 48%|████▊ | 952/2000 [16:24<17:27, 1.00it/s, loss=0.276]" ] }, { @@ -27784,7 +27762,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 952/2000 [13:13<14:16, 1.22it/s, loss=0.576]" + "training until 2000: 48%|████▊ | 952/2000 [16:24<17:27, 1.00it/s, loss=0.338]" ] }, { @@ -27792,7 +27770,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 953/2000 [13:13<12:34, 1.39it/s, loss=0.576]" + "training until 2000: 48%|████▊ | 953/2000 [16:25<15:03, 1.16it/s, loss=0.338]" ] }, { @@ -27800,7 +27778,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 953/2000 [13:13<12:34, 1.39it/s, loss=0.534]" + "training until 2000: 48%|████▊ | 953/2000 [16:25<15:03, 1.16it/s, loss=0.442]" ] }, { @@ -27808,7 +27786,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 954/2000 [13:14<12:25, 1.40it/s, loss=0.534]" + "training until 2000: 48%|████▊ | 954/2000 [16:26<16:26, 1.06it/s, loss=0.442]" ] }, { @@ -27816,7 +27794,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 954/2000 [13:14<12:25, 1.40it/s, loss=0.505]" + "training until 2000: 48%|████▊ | 954/2000 [16:26<16:26, 1.06it/s, loss=0.298]" ] }, { @@ -27824,7 +27802,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 955/2000 [13:15<12:53, 1.35it/s, loss=0.505]" + "training until 2000: 48%|████▊ | 955/2000 [16:27<16:36, 1.05it/s, loss=0.298]" ] }, { @@ -27832,7 +27810,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 955/2000 [13:15<12:53, 1.35it/s, loss=0.534]" + "training until 2000: 48%|████▊ | 955/2000 [16:27<16:36, 1.05it/s, loss=0.391]" ] }, { @@ -27840,7 +27818,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 956/2000 [13:16<13:49, 1.26it/s, loss=0.534]" + "training until 2000: 48%|████▊ | 956/2000 [16:28<18:22, 1.06s/it, loss=0.391]" ] }, { @@ -27848,7 +27826,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 956/2000 [13:16<13:49, 1.26it/s, loss=0.541]" + "training until 2000: 48%|████▊ | 956/2000 [16:28<18:22, 1.06s/it, loss=0.499]" ] }, { @@ -27856,7 +27834,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 957/2000 [13:16<12:24, 1.40it/s, loss=0.541]" + "training until 2000: 48%|████▊ | 957/2000 [16:29<17:41, 1.02s/it, loss=0.499]" ] }, { @@ -27864,7 +27842,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 957/2000 [13:16<12:24, 1.40it/s, loss=0.473]" + "training until 2000: 48%|████▊ | 957/2000 [16:29<17:41, 1.02s/it, loss=0.397]" ] }, { @@ -27872,7 +27850,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 958/2000 [13:17<13:16, 1.31it/s, loss=0.473]" + "training until 2000: 48%|████▊ | 958/2000 [16:31<19:03, 1.10s/it, loss=0.397]" ] }, { @@ -27880,7 +27858,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 958/2000 [13:17<13:16, 1.31it/s, loss=0.502]" + "training until 2000: 48%|████▊ | 958/2000 [16:31<19:03, 1.10s/it, loss=0.35] " ] }, { @@ -27888,7 +27866,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 959/2000 [13:18<13:27, 1.29it/s, loss=0.502]" + "training until 2000: 48%|████▊ | 959/2000 [16:32<19:02, 1.10s/it, loss=0.35]" ] }, { @@ -27896,7 +27874,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 959/2000 [13:18<13:27, 1.29it/s, loss=0.514]" + "training until 2000: 48%|████▊ | 959/2000 [16:32<19:02, 1.10s/it, loss=0.303]" ] }, { @@ -27904,7 +27882,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 960/2000 [13:18<12:29, 1.39it/s, loss=0.514]" + "training until 2000: 48%|████▊ | 960/2000 [16:33<18:57, 1.09s/it, loss=0.303]" ] }, { @@ -27912,7 +27890,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 960/2000 [13:18<12:29, 1.39it/s, loss=0.567]" + "training until 2000: 48%|████▊ | 960/2000 [16:33<18:57, 1.09s/it, loss=0.443]" ] }, { @@ -27920,7 +27898,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 961/2000 [13:19<12:50, 1.35it/s, loss=0.567]" + "training until 2000: 48%|████▊ | 961/2000 [16:34<17:39, 1.02s/it, loss=0.443]" ] }, { @@ -27928,7 +27906,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 961/2000 [13:19<12:50, 1.35it/s, loss=0.526]" + "training until 2000: 48%|████▊ | 961/2000 [16:34<17:39, 1.02s/it, loss=0.392]" ] }, { @@ -27936,7 +27914,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 962/2000 [13:20<12:29, 1.39it/s, loss=0.526]" + "training until 2000: 48%|████▊ | 962/2000 [16:35<18:19, 1.06s/it, loss=0.392]" ] }, { @@ -27944,7 +27922,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 962/2000 [13:20<12:29, 1.39it/s, loss=0.521]" + "training until 2000: 48%|████▊ | 962/2000 [16:35<18:19, 1.06s/it, loss=0.407]" ] }, { @@ -27952,7 +27930,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 963/2000 [13:21<13:05, 1.32it/s, loss=0.521]" + "training until 2000: 48%|████▊ | 963/2000 [16:36<16:31, 1.05it/s, loss=0.407]" ] }, { @@ -27960,7 +27938,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 963/2000 [13:21<13:05, 1.32it/s, loss=0.566]" + "training until 2000: 48%|████▊ | 963/2000 [16:36<16:31, 1.05it/s, loss=0.403]" ] }, { @@ -27968,7 +27946,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 964/2000 [13:21<12:50, 1.34it/s, loss=0.566]" + "training until 2000: 48%|████▊ | 964/2000 [16:36<16:40, 1.04it/s, loss=0.403]" ] }, { @@ -27976,7 +27954,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 964/2000 [13:21<12:50, 1.34it/s, loss=0.505]" + "training until 2000: 48%|████▊ | 964/2000 [16:36<16:40, 1.04it/s, loss=0.302]" ] }, { @@ -27984,7 +27962,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 965/2000 [13:22<12:24, 1.39it/s, loss=0.505]" + "training until 2000: 48%|████▊ | 965/2000 [16:38<18:17, 1.06s/it, loss=0.302]" ] }, { @@ -27992,7 +27970,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 965/2000 [13:22<12:24, 1.39it/s, loss=0.481]" + "training until 2000: 48%|████▊ | 965/2000 [16:38<18:17, 1.06s/it, loss=0.405]" ] }, { @@ -28000,7 +27978,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 966/2000 [13:23<13:50, 1.24it/s, loss=0.481]" + "training until 2000: 48%|████▊ | 966/2000 [16:39<18:01, 1.05s/it, loss=0.405]" ] }, { @@ -28008,7 +27986,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 966/2000 [13:23<13:50, 1.24it/s, loss=0.541]" + "training until 2000: 48%|████▊ | 966/2000 [16:39<18:01, 1.05s/it, loss=0.337]" ] }, { @@ -28016,7 +27994,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 967/2000 [13:24<13:34, 1.27it/s, loss=0.541]" + "training until 2000: 48%|████▊ | 967/2000 [16:40<19:39, 1.14s/it, loss=0.337]" ] }, { @@ -28024,7 +28002,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 967/2000 [13:24<13:34, 1.27it/s, loss=0.508]" + "training until 2000: 48%|████▊ | 967/2000 [16:40<19:39, 1.14s/it, loss=0.467]" ] }, { @@ -28032,7 +28010,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 968/2000 [13:25<13:05, 1.31it/s, loss=0.508]" + "training until 2000: 48%|████▊ | 968/2000 [16:41<17:34, 1.02s/it, loss=0.467]" ] }, { @@ -28040,7 +28018,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 968/2000 [13:25<13:05, 1.31it/s, loss=0.487]" + "training until 2000: 48%|████▊ | 968/2000 [16:41<17:34, 1.02s/it, loss=0.213]" ] }, { @@ -28048,7 +28026,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 969/2000 [13:25<11:45, 1.46it/s, loss=0.487]" + "training until 2000: 48%|████▊ | 969/2000 [16:42<15:33, 1.10it/s, loss=0.213]" ] }, { @@ -28056,7 +28034,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 969/2000 [13:25<11:45, 1.46it/s, loss=0.63] " + "training until 2000: 48%|████▊ | 969/2000 [16:42<15:33, 1.10it/s, loss=0.42] " ] }, { @@ -28064,7 +28042,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 970/2000 [13:26<13:31, 1.27it/s, loss=0.63]" + "training until 2000: 48%|████▊ | 970/2000 [16:42<14:50, 1.16it/s, loss=0.42]" ] }, { @@ -28072,7 +28050,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 48%|████▊ | 970/2000 [13:26<13:31, 1.27it/s, loss=0.513]" + "training until 2000: 48%|████▊ | 970/2000 [16:42<14:50, 1.16it/s, loss=0.351]" ] }, { @@ -28080,7 +28058,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 971/2000 [13:27<13:54, 1.23it/s, loss=0.513]" + "training until 2000: 49%|████▊ | 971/2000 [16:43<16:29, 1.04it/s, loss=0.351]" ] }, { @@ -28088,7 +28066,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 971/2000 [13:27<13:54, 1.23it/s, loss=0.496]" + "training until 2000: 49%|████▊ | 971/2000 [16:43<16:29, 1.04it/s, loss=0.295]" ] }, { @@ -28096,7 +28074,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 972/2000 [13:28<14:16, 1.20it/s, loss=0.496]" + "training until 2000: 49%|████▊ | 972/2000 [16:45<18:38, 1.09s/it, loss=0.295]" ] }, { @@ -28104,7 +28082,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 972/2000 [13:28<14:16, 1.20it/s, loss=0.483]" + "training until 2000: 49%|████▊ | 972/2000 [16:45<18:38, 1.09s/it, loss=0.334]" ] }, { @@ -28112,7 +28090,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 973/2000 [13:28<13:24, 1.28it/s, loss=0.483]" + "training until 2000: 49%|████▊ | 973/2000 [16:46<16:31, 1.04it/s, loss=0.334]" ] }, { @@ -28120,7 +28098,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 973/2000 [13:28<13:24, 1.28it/s, loss=0.521]" + "training until 2000: 49%|████▊ | 973/2000 [16:46<16:31, 1.04it/s, loss=0.333]" ] }, { @@ -28128,7 +28106,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 974/2000 [13:29<14:28, 1.18it/s, loss=0.521]" + "training until 2000: 49%|████▊ | 974/2000 [16:47<16:59, 1.01it/s, loss=0.333]" ] }, { @@ -28136,7 +28114,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▊ | 974/2000 [13:29<14:28, 1.18it/s, loss=0.515]" + "training until 2000: 49%|████▊ | 974/2000 [16:47<16:59, 1.01it/s, loss=0.38] " ] }, { @@ -28144,7 +28122,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 975/2000 [13:30<13:55, 1.23it/s, loss=0.515]" + "training until 2000: 49%|████▉ | 975/2000 [16:47<15:53, 1.08it/s, loss=0.38]" ] }, { @@ -28152,7 +28130,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 975/2000 [13:30<13:55, 1.23it/s, loss=0.515]" + "training until 2000: 49%|████▉ | 975/2000 [16:47<15:53, 1.08it/s, loss=0.338]" ] }, { @@ -28160,7 +28138,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 976/2000 [13:31<12:34, 1.36it/s, loss=0.515]" + "training until 2000: 49%|████▉ | 976/2000 [16:48<16:18, 1.05it/s, loss=0.338]" ] }, { @@ -28168,7 +28146,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 976/2000 [13:31<12:34, 1.36it/s, loss=0.561]" + "training until 2000: 49%|████▉ | 976/2000 [16:48<16:18, 1.05it/s, loss=0.253]" ] }, { @@ -28176,7 +28154,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 977/2000 [13:32<13:07, 1.30it/s, loss=0.561]" + "training until 2000: 49%|████▉ | 977/2000 [16:50<17:04, 1.00s/it, loss=0.253]" ] }, { @@ -28184,7 +28162,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 977/2000 [13:32<13:07, 1.30it/s, loss=0.491]" + "training until 2000: 49%|████▉ | 977/2000 [16:50<17:04, 1.00s/it, loss=0.458]" ] }, { @@ -28192,7 +28170,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 978/2000 [13:32<12:37, 1.35it/s, loss=0.491]" + "training until 2000: 49%|████▉ | 978/2000 [16:51<17:11, 1.01s/it, loss=0.458]" ] }, { @@ -28200,7 +28178,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 978/2000 [13:32<12:37, 1.35it/s, loss=0.458]" + "training until 2000: 49%|████▉ | 978/2000 [16:51<17:11, 1.01s/it, loss=0.464]" ] }, { @@ -28208,7 +28186,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 979/2000 [13:33<12:08, 1.40it/s, loss=0.458]" + "training until 2000: 49%|████▉ | 979/2000 [16:52<17:38, 1.04s/it, loss=0.464]" ] }, { @@ -28216,7 +28194,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 979/2000 [13:33<12:08, 1.40it/s, loss=0.485]" + "training until 2000: 49%|████▉ | 979/2000 [16:52<17:38, 1.04s/it, loss=0.52] " ] }, { @@ -28224,7 +28202,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 980/2000 [13:34<11:35, 1.47it/s, loss=0.485]" + "training until 2000: 49%|████▉ | 980/2000 [16:53<17:58, 1.06s/it, loss=0.52]" ] }, { @@ -28232,7 +28210,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 980/2000 [13:34<11:35, 1.47it/s, loss=0.519]" + "training until 2000: 49%|████▉ | 980/2000 [16:53<17:58, 1.06s/it, loss=0.332]" ] }, { @@ -28240,7 +28218,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 981/2000 [13:35<14:51, 1.14it/s, loss=0.519]" + "training until 2000: 49%|████▉ | 981/2000 [16:54<18:16, 1.08s/it, loss=0.332]" ] }, { @@ -28248,7 +28226,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 981/2000 [13:35<14:51, 1.14it/s, loss=0.469]" + "training until 2000: 49%|████▉ | 981/2000 [16:54<18:16, 1.08s/it, loss=0.256]" ] }, { @@ -28256,7 +28234,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 982/2000 [13:36<15:01, 1.13it/s, loss=0.469]" + "training until 2000: 49%|████▉ | 982/2000 [16:55<16:25, 1.03it/s, loss=0.256]" ] }, { @@ -28264,7 +28242,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 982/2000 [13:36<15:01, 1.13it/s, loss=0.486]" + "training until 2000: 49%|████▉ | 982/2000 [16:55<16:25, 1.03it/s, loss=0.299]" ] }, { @@ -28272,7 +28250,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 983/2000 [13:37<15:37, 1.08it/s, loss=0.486]" + "training until 2000: 49%|████▉ | 983/2000 [16:56<17:11, 1.01s/it, loss=0.299]" ] }, { @@ -28280,7 +28258,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 983/2000 [13:37<15:37, 1.08it/s, loss=0.506]" + "training until 2000: 49%|████▉ | 983/2000 [16:56<17:11, 1.01s/it, loss=0.283]" ] }, { @@ -28288,7 +28266,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 984/2000 [13:37<14:23, 1.18it/s, loss=0.506]" + "training until 2000: 49%|████▉ | 984/2000 [16:57<19:24, 1.15s/it, loss=0.283]" ] }, { @@ -28296,7 +28274,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 984/2000 [13:37<14:23, 1.18it/s, loss=0.499]" + "training until 2000: 49%|████▉ | 984/2000 [16:57<19:24, 1.15s/it, loss=0.277]" ] }, { @@ -28304,7 +28282,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 985/2000 [13:38<14:02, 1.20it/s, loss=0.499]" + "training until 2000: 49%|████▉ | 985/2000 [16:58<16:47, 1.01it/s, loss=0.277]" ] }, { @@ -28312,7 +28290,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 985/2000 [13:38<14:02, 1.20it/s, loss=0.51] " + "training until 2000: 49%|████▉ | 985/2000 [16:58<16:47, 1.01it/s, loss=0.348]" ] }, { @@ -28320,7 +28298,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 986/2000 [13:39<14:03, 1.20it/s, loss=0.51]" + "training until 2000: 49%|████▉ | 986/2000 [16:58<14:55, 1.13it/s, loss=0.348]" ] }, { @@ -28328,7 +28306,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 986/2000 [13:39<14:03, 1.20it/s, loss=0.549]" + "training until 2000: 49%|████▉ | 986/2000 [16:58<14:55, 1.13it/s, loss=0.322]" ] }, { @@ -28336,7 +28314,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 987/2000 [13:40<14:32, 1.16it/s, loss=0.549]" + "training until 2000: 49%|████▉ | 987/2000 [16:59<14:28, 1.17it/s, loss=0.322]" ] }, { @@ -28344,7 +28322,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 987/2000 [13:40<14:32, 1.16it/s, loss=0.539]" + "training until 2000: 49%|████▉ | 987/2000 [16:59<14:28, 1.17it/s, loss=0.45] " ] }, { @@ -28352,7 +28330,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 988/2000 [13:41<13:14, 1.27it/s, loss=0.539]" + "training until 2000: 49%|████▉ | 988/2000 [17:01<16:38, 1.01it/s, loss=0.45]" ] }, { @@ -28360,7 +28338,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 988/2000 [13:41<13:14, 1.27it/s, loss=0.538]" + "training until 2000: 49%|████▉ | 988/2000 [17:01<16:38, 1.01it/s, loss=0.348]" ] }, { @@ -28368,7 +28346,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 989/2000 [13:41<12:56, 1.30it/s, loss=0.538]" + "training until 2000: 49%|████▉ | 989/2000 [17:02<17:31, 1.04s/it, loss=0.348]" ] }, { @@ -28376,7 +28354,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 49%|████▉ | 989/2000 [13:41<12:56, 1.30it/s, loss=0.507]" + "training until 2000: 49%|████▉ | 989/2000 [17:02<17:31, 1.04s/it, loss=0.404]" ] }, { @@ -28384,7 +28362,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 990/2000 [13:42<13:26, 1.25it/s, loss=0.507]" + "training until 2000: 50%|████▉ | 990/2000 [17:03<17:38, 1.05s/it, loss=0.404]" ] }, { @@ -28392,7 +28370,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 990/2000 [13:42<13:26, 1.25it/s, loss=0.5] " + "training until 2000: 50%|████▉ | 990/2000 [17:03<17:38, 1.05s/it, loss=0.364]" ] }, { @@ -28400,7 +28378,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 991/2000 [13:43<14:05, 1.19it/s, loss=0.5]" + "training until 2000: 50%|████▉ | 991/2000 [17:04<20:58, 1.25s/it, loss=0.364]" ] }, { @@ -28408,7 +28386,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 991/2000 [13:43<14:05, 1.19it/s, loss=0.538]" + "training until 2000: 50%|████▉ | 991/2000 [17:04<20:58, 1.25s/it, loss=0.328]" ] }, { @@ -28416,7 +28394,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 992/2000 [13:44<13:42, 1.23it/s, loss=0.538]" + "training until 2000: 50%|████▉ | 992/2000 [17:06<21:37, 1.29s/it, loss=0.328]" ] }, { @@ -28424,7 +28402,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 992/2000 [13:44<13:42, 1.23it/s, loss=0.542]" + "training until 2000: 50%|████▉ | 992/2000 [17:06<21:37, 1.29s/it, loss=0.186]" ] }, { @@ -28432,7 +28410,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 993/2000 [13:45<13:21, 1.26it/s, loss=0.542]" + "training until 2000: 50%|████▉ | 993/2000 [17:06<18:24, 1.10s/it, loss=0.186]" ] }, { @@ -28440,7 +28418,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 993/2000 [13:45<13:21, 1.26it/s, loss=0.521]" + "training until 2000: 50%|████▉ | 993/2000 [17:06<18:24, 1.10s/it, loss=0.294]" ] }, { @@ -28448,7 +28426,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 994/2000 [13:45<12:39, 1.32it/s, loss=0.521]" + "training until 2000: 50%|████▉ | 994/2000 [17:07<17:06, 1.02s/it, loss=0.294]" ] }, { @@ -28456,7 +28434,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 994/2000 [13:45<12:39, 1.32it/s, loss=0.498]" + "training until 2000: 50%|████▉ | 994/2000 [17:07<17:06, 1.02s/it, loss=0.297]" ] }, { @@ -28464,7 +28442,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 995/2000 [13:46<11:10, 1.50it/s, loss=0.498]" + "training until 2000: 50%|████▉ | 995/2000 [17:08<17:24, 1.04s/it, loss=0.297]" ] }, { @@ -28472,7 +28450,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 995/2000 [13:46<11:10, 1.50it/s, loss=0.536]" + "training until 2000: 50%|████▉ | 995/2000 [17:08<17:24, 1.04s/it, loss=0.217]" ] }, { @@ -28480,7 +28458,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 996/2000 [13:47<12:32, 1.33it/s, loss=0.536]" + "training until 2000: 50%|████▉ | 996/2000 [17:09<17:22, 1.04s/it, loss=0.217]" ] }, { @@ -28488,7 +28466,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 996/2000 [13:47<12:32, 1.33it/s, loss=0.476]" + "training until 2000: 50%|████▉ | 996/2000 [17:09<17:22, 1.04s/it, loss=0.406]" ] }, { @@ -28496,7 +28474,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 997/2000 [13:48<12:58, 1.29it/s, loss=0.476]" + "training until 2000: 50%|████▉ | 997/2000 [17:11<17:57, 1.07s/it, loss=0.406]" ] }, { @@ -28504,7 +28482,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 997/2000 [13:48<12:58, 1.29it/s, loss=0.497]" + "training until 2000: 50%|████▉ | 997/2000 [17:11<17:57, 1.07s/it, loss=0.362]" ] }, { @@ -28512,7 +28490,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 998/2000 [13:49<14:05, 1.18it/s, loss=0.497]" + "training until 2000: 50%|████▉ | 998/2000 [17:12<18:42, 1.12s/it, loss=0.362]" ] }, { @@ -28520,7 +28498,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 998/2000 [13:49<14:05, 1.18it/s, loss=0.463]" + "training until 2000: 50%|████▉ | 998/2000 [17:12<18:42, 1.12s/it, loss=0.23] " ] }, { @@ -28528,7 +28506,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 999/2000 [13:49<12:55, 1.29it/s, loss=0.463]" + "training until 2000: 50%|████▉ | 999/2000 [17:13<17:03, 1.02s/it, loss=0.23]" ] }, { @@ -28536,7 +28514,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|████▉ | 999/2000 [13:49<12:55, 1.29it/s, loss=0.492]" + "training until 2000: 50%|████▉ | 999/2000 [17:13<17:03, 1.02s/it, loss=0.319]" ] }, { @@ -28544,7 +28522,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1000/2000 [13:50<13:19, 1.25it/s, loss=0.492]" + "training until 2000: 50%|█████ | 1000/2000 [17:14<19:02, 1.14s/it, loss=0.319]" ] }, { @@ -28552,7 +28530,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1000/2000 [13:50<13:19, 1.25it/s, loss=0.555]" + "training until 2000: 50%|█████ | 1000/2000 [17:14<19:02, 1.14s/it, loss=0.353]" ] }, { @@ -28640,7 +28618,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:09, 21.98blocks/s, ⧗=0, ▶=1, ✔=1, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:09, 22.71blocks/s, ⧗=0, ▶=1, ✔=1, ✗=0, ∅=0]" ] }, { @@ -28662,7 +28640,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:20, 10.55blocks/s, ⧗=0, ▶=0, ✔=2, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 0%| | 1/216 [00:00<00:18, 11.63blocks/s, ⧗=0, ▶=0, ✔=2, ✗=0, ∅=0]" ] }, { @@ -28684,7 +28662,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:10, 20.76blocks/s, ⧗=0, ▶=1, ✔=2, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:09, 22.83blocks/s, ⧗=0, ▶=1, ✔=2, ✗=0, ∅=0]" ] }, { @@ -28706,7 +28684,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:15, 14.12blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%| | 2/216 [00:00<00:14, 15.14blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" ] }, { @@ -28728,7 +28706,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=0, ✔=3, ✗=0, ∅=0]" ] }, { @@ -28750,7 +28728,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=1, ✔=3, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=1, ✔=3, ✗=0, ∅=0]" ] }, { @@ -28772,7 +28750,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=0, ✔=4, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 1%|▏ | 3/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=0, ✔=4, ✗=0, ∅=0]" ] }, { @@ -28794,7 +28772,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=1, ✔=4, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=1, ✔=4, ✗=0, ∅=0]" ] }, { @@ -28816,7 +28794,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=0, ✔=5, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 4/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=0, ✔=5, ✗=0, ∅=0]" ] }, { @@ -28838,7 +28816,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=1, ✔=5, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=1, ✔=5, ✗=0, ∅=0]" ] }, { @@ -28860,7 +28838,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:10, 21.02blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 2%|▏ | 5/216 [00:00<00:09, 22.52blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" ] }, { @@ -28882,7 +28860,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=0, ✔=6, ✗=0, ∅=0]" ] }, { @@ -28904,7 +28882,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=1, ✔=6, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=1, ✔=6, ✗=0, ∅=0]" ] }, { @@ -28926,7 +28904,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=0, ✔=7, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 6/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=0, ✔=7, ✗=0, ∅=0]" ] }, { @@ -28948,7 +28926,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=1, ✔=7, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=1, ✔=7, ✗=0, ∅=0]" ] }, { @@ -28970,7 +28948,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=0, ✔=8, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 3%|▎ | 7/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=0, ✔=8, ✗=0, ∅=0]" ] }, { @@ -28992,7 +28970,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=1, ✔=8, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=1, ✔=8, ✗=0, ∅=0]" ] }, { @@ -29014,7 +28992,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:10, 20.02blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▎ | 8/216 [00:00<00:09, 22.25blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" ] }, { @@ -29036,7 +29014,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:11, 18.55blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=0, ✔=9, ✗=0, ∅=0]" ] }, { @@ -29058,7 +29036,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:11, 18.55blocks/s, ⧗=0, ▶=1, ✔=9, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=1, ✔=9, ✗=0, ∅=0]" ] }, { @@ -29080,7 +29058,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:11, 18.55blocks/s, ⧗=0, ▶=0, ✔=10, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 4%|▍ | 9/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=0, ✔=10, ✗=0, ∅=0]" ] }, { @@ -29102,7 +29080,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:11, 18.55blocks/s, ⧗=0, ▶=1, ✔=10, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=1, ✔=10, ✗=0, ∅=0]" ] }, { @@ -29124,7 +29102,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:11, 18.55blocks/s, ⧗=0, ▶=0, ✔=11, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▍ | 10/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=0, ✔=11, ✗=0, ∅=0]" ] }, { @@ -29146,7 +29124,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:11, 17.44blocks/s, ⧗=0, ▶=0, ✔=11, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=1, ✔=11, ✗=0, ∅=0]" ] }, { @@ -29168,7 +29146,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:11, 17.44blocks/s, ⧗=0, ▶=1, ✔=11, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:09, 21.76blocks/s, ⧗=0, ▶=0, ✔=12, ✗=0, ∅=0]" ] }, { @@ -29190,7 +29168,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 5%|▌ | 11/216 [00:00<00:11, 17.44blocks/s, ⧗=0, ▶=0, ✔=12, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 20.23blocks/s, ⧗=0, ▶=0, ✔=12, ✗=0, ∅=0]" ] }, { @@ -29212,7 +29190,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:11, 17.44blocks/s, ⧗=0, ▶=1, ✔=12, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 20.23blocks/s, ⧗=0, ▶=1, ✔=12, ✗=0, ∅=0]" ] }, { @@ -29234,7 +29212,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:11, 17.44blocks/s, ⧗=0, ▶=0, ✔=13, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 12/216 [00:00<00:10, 20.23blocks/s, ⧗=0, ▶=0, ✔=13, ✗=0, ∅=0]" ] }, { @@ -29256,7 +29234,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:11, 17.91blocks/s, ⧗=0, ▶=0, ✔=13, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:10, 20.23blocks/s, ⧗=0, ▶=1, ✔=13, ✗=0, ∅=0]" ] }, { @@ -29278,7 +29256,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:11, 17.91blocks/s, ⧗=0, ▶=1, ✔=13, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:10, 20.23blocks/s, ⧗=0, ▶=0, ✔=14, ✗=0, ∅=0]" ] }, { @@ -29300,7 +29278,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▌ | 13/216 [00:00<00:11, 17.91blocks/s, ⧗=0, ▶=0, ✔=14, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:09, 20.23blocks/s, ⧗=0, ▶=1, ✔=14, ✗=0, ∅=0]" ] }, { @@ -29322,7 +29300,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:11, 17.91blocks/s, ⧗=0, ▶=1, ✔=14, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:09, 20.23blocks/s, ⧗=0, ▶=0, ✔=15, ✗=0, ∅=0]" ] }, { @@ -29344,7 +29322,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 6%|▋ | 14/216 [00:00<00:11, 17.91blocks/s, ⧗=0, ▶=0, ✔=15, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 19.86blocks/s, ⧗=0, ▶=0, ✔=15, ✗=0, ∅=0]" ] }, { @@ -29366,7 +29344,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:11, 17.95blocks/s, ⧗=0, ▶=0, ✔=15, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 19.86blocks/s, ⧗=0, ▶=1, ✔=15, ✗=0, ∅=0]" ] }, { @@ -29388,7 +29366,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:11, 17.95blocks/s, ⧗=0, ▶=1, ✔=15, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:10, 19.86blocks/s, ⧗=0, ▶=0, ✔=16, ✗=0, ∅=0]" ] }, { @@ -29410,7 +29388,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 15/216 [00:00<00:11, 17.95blocks/s, ⧗=0, ▶=0, ✔=16, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 19.86blocks/s, ⧗=0, ▶=1, ✔=16, ✗=0, ∅=0]" ] }, { @@ -29432,7 +29410,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:11, 17.95blocks/s, ⧗=0, ▶=1, ✔=16, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:10, 19.86blocks/s, ⧗=0, ▶=0, ✔=17, ✗=0, ∅=0]" ] }, { @@ -29454,7 +29432,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 7%|▋ | 16/216 [00:00<00:11, 17.95blocks/s, ⧗=0, ▶=0, ✔=17, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 19.74blocks/s, ⧗=0, ▶=0, ✔=17, ✗=0, ∅=0]" ] }, { @@ -29476,7 +29454,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.25blocks/s, ⧗=0, ▶=0, ✔=17, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 19.74blocks/s, ⧗=0, ▶=1, ✔=17, ✗=0, ∅=0]" ] }, { @@ -29498,7 +29476,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.25blocks/s, ⧗=0, ▶=1, ✔=17, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 19.74blocks/s, ⧗=0, ▶=0, ✔=18, ✗=0, ∅=0]" ] }, { @@ -29520,7 +29498,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 17/216 [00:00<00:10, 18.25blocks/s, ⧗=0, ▶=0, ✔=18, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:10, 19.74blocks/s, ⧗=0, ▶=1, ✔=18, ✗=0, ∅=0]" ] }, { @@ -29542,7 +29520,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:10, 18.25blocks/s, ⧗=0, ▶=1, ✔=18, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 18/216 [00:00<00:10, 19.74blocks/s, ⧗=0, ▶=0, ✔=19, ✗=0, ∅=0]" ] }, { @@ -29564,7 +29542,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 8%|▊ | 18/216 [00:01<00:10, 18.25blocks/s, ⧗=0, ▶=0, ✔=19, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 19/216 [00:00<00:09, 19.74blocks/s, ⧗=0, ▶=1, ✔=19, ✗=0, ∅=0]" ] }, { @@ -29586,7 +29564,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:10, 18.25blocks/s, ⧗=0, ▶=1, ✔=19, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 19/216 [00:00<00:09, 19.80blocks/s, ⧗=0, ▶=1, ✔=19, ✗=0, ∅=0]" ] }, { @@ -29608,7 +29586,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:10, 18.67blocks/s, ⧗=0, ▶=1, ✔=19, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 19/216 [00:00<00:09, 19.80blocks/s, ⧗=0, ▶=0, ✔=20, ✗=0, ∅=0]" ] }, { @@ -29630,7 +29608,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 19/216 [00:01<00:10, 18.67blocks/s, ⧗=0, ▶=0, ✔=20, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 20/216 [00:00<00:09, 19.80blocks/s, ⧗=0, ▶=1, ✔=20, ✗=0, ∅=0]" ] }, { @@ -29652,7 +29630,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.67blocks/s, ⧗=0, ▶=1, ✔=20, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:09, 19.80blocks/s, ⧗=0, ▶=0, ✔=21, ✗=0, ∅=0]" ] }, { @@ -29674,7 +29652,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 9%|▉ | 20/216 [00:01<00:10, 18.67blocks/s, ⧗=0, ▶=0, ✔=21, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:09, 19.80blocks/s, ⧗=0, ▶=1, ✔=21, ✗=0, ∅=0]" ] }, { @@ -29696,7 +29674,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.89blocks/s, ⧗=0, ▶=0, ✔=21, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:09, 19.80blocks/s, ⧗=0, ▶=0, ✔=22, ✗=0, ∅=0]" ] }, { @@ -29718,7 +29696,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.89blocks/s, ⧗=0, ▶=1, ✔=21, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|█ | 22/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=0, ✔=22, ✗=0, ∅=0]" ] }, { @@ -29740,7 +29718,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|▉ | 21/216 [00:01<00:10, 18.89blocks/s, ⧗=0, ▶=0, ✔=22, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|█ | 22/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=1, ✔=22, ✗=0, ∅=0]" ] }, { @@ -29762,7 +29740,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|█ | 22/216 [00:01<00:10, 18.89blocks/s, ⧗=0, ▶=1, ✔=22, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|█ | 22/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=0, ✔=23, ✗=0, ∅=0]" ] }, { @@ -29784,7 +29762,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 10%|█ | 22/216 [00:01<00:10, 18.89blocks/s, ⧗=0, ▶=0, ✔=23, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=1, ✔=23, ✗=0, ∅=0]" ] }, { @@ -29806,7 +29784,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:10, 19.17blocks/s, ⧗=0, ▶=0, ✔=23, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=0, ✔=24, ✗=0, ∅=0]" ] }, { @@ -29828,7 +29806,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:10, 19.17blocks/s, ⧗=0, ▶=1, ✔=23, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 24/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=1, ✔=24, ✗=0, ∅=0]" ] }, { @@ -29850,7 +29828,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 23/216 [00:01<00:10, 19.17blocks/s, ⧗=0, ▶=0, ✔=24, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 24/216 [00:01<00:09, 20.18blocks/s, ⧗=0, ▶=0, ✔=25, ✗=0, ∅=0]" ] }, { @@ -29872,7 +29850,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 24/216 [00:01<00:10, 19.17blocks/s, ⧗=0, ▶=1, ✔=24, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=0, ✔=25, ✗=0, ∅=0]" ] }, { @@ -29894,7 +29872,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 11%|█ | 24/216 [00:01<00:10, 19.17blocks/s, ⧗=0, ▶=0, ✔=25, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=1, ✔=25, ✗=0, ∅=0]" ] }, { @@ -29916,7 +29894,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:09, 19.17blocks/s, ⧗=0, ▶=1, ✔=25, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=0, ✔=26, ✗=0, ∅=0]" ] }, { @@ -29938,7 +29916,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 25/216 [00:01<00:09, 19.17blocks/s, ⧗=0, ▶=0, ✔=26, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=1, ✔=26, ✗=0, ∅=0]" ] }, { @@ -29960,7 +29938,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:09, 19.74blocks/s, ⧗=0, ▶=0, ✔=26, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=0, ✔=27, ✗=0, ∅=0]" ] }, { @@ -29982,7 +29960,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:09, 19.74blocks/s, ⧗=0, ▶=1, ✔=26, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=1, ✔=27, ✗=0, ∅=0]" ] }, { @@ -30004,7 +29982,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▏ | 26/216 [00:01<00:09, 19.74blocks/s, ⧗=0, ▶=0, ✔=27, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:09, 20.57blocks/s, ⧗=0, ▶=0, ✔=28, ✗=0, ∅=0]" ] }, { @@ -30026,7 +30004,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:09, 19.74blocks/s, ⧗=0, ▶=1, ✔=27, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=0, ✔=28, ✗=0, ∅=0]" ] }, { @@ -30048,7 +30026,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 12%|█▎ | 27/216 [00:01<00:09, 19.74blocks/s, ⧗=0, ▶=0, ✔=28, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=1, ✔=28, ✗=0, ∅=0]" ] }, { @@ -30070,7 +30048,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:09, 19.19blocks/s, ⧗=0, ▶=0, ✔=28, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=0, ✔=29, ✗=0, ∅=0]" ] }, { @@ -30092,7 +30070,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:09, 19.19blocks/s, ⧗=0, ▶=1, ✔=28, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=1, ✔=29, ✗=0, ∅=0]" ] }, { @@ -30114,7 +30092,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 28/216 [00:01<00:09, 19.19blocks/s, ⧗=0, ▶=0, ✔=29, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=0, ✔=30, ✗=0, ∅=0]" ] }, { @@ -30136,7 +30114,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:09, 19.19blocks/s, ⧗=0, ▶=1, ✔=29, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=1, ✔=30, ✗=0, ∅=0]" ] }, { @@ -30158,7 +30136,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 13%|█▎ | 29/216 [00:01<00:09, 19.19blocks/s, ⧗=0, ▶=0, ✔=30, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:09, 20.49blocks/s, ⧗=0, ▶=0, ✔=31, ✗=0, ∅=0]" ] }, { @@ -30180,7 +30158,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:09, 19.31blocks/s, ⧗=0, ▶=0, ✔=30, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=0, ✔=31, ✗=0, ∅=0]" ] }, { @@ -30202,7 +30180,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:09, 19.31blocks/s, ⧗=0, ▶=1, ✔=30, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=1, ✔=31, ✗=0, ∅=0]" ] }, { @@ -30224,7 +30202,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 30/216 [00:01<00:09, 19.31blocks/s, ⧗=0, ▶=0, ✔=31, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=0, ✔=32, ✗=0, ∅=0]" ] }, { @@ -30246,7 +30224,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:09, 19.31blocks/s, ⧗=0, ▶=1, ✔=31, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=1, ✔=32, ✗=0, ∅=0]" ] }, { @@ -30268,7 +30246,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 14%|█▍ | 31/216 [00:01<00:09, 19.31blocks/s, ⧗=0, ▶=0, ✔=32, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=0, ✔=33, ✗=0, ∅=0]" ] }, { @@ -30290,7 +30268,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.50blocks/s, ⧗=0, ▶=0, ✔=32, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=1, ✔=33, ✗=0, ∅=0]" ] }, { @@ -30312,7 +30290,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.50blocks/s, ⧗=0, ▶=1, ✔=32, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:08, 20.63blocks/s, ⧗=0, ▶=0, ✔=34, ✗=0, ∅=0]" ] }, { @@ -30334,7 +30312,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▍ | 32/216 [00:01<00:09, 18.50blocks/s, ⧗=0, ▶=0, ✔=33, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=0, ✔=34, ✗=0, ∅=0]" ] }, { @@ -30356,7 +30334,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.50blocks/s, ⧗=0, ▶=1, ✔=33, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=1, ✔=34, ✗=0, ∅=0]" ] }, { @@ -30378,7 +30356,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 15%|█▌ | 33/216 [00:01<00:09, 18.50blocks/s, ⧗=0, ▶=0, ✔=34, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=0, ✔=35, ✗=0, ∅=0]" ] }, { @@ -30400,7 +30378,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=0, ✔=34, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=1, ✔=35, ✗=0, ∅=0]" ] }, { @@ -30422,7 +30400,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=1, ✔=34, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=0, ✔=36, ✗=0, ∅=0]" ] }, { @@ -30444,7 +30422,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 34/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=0, ✔=35, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=1, ✔=36, ✗=0, ∅=0]" ] }, { @@ -30466,7 +30444,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=1, ✔=35, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:08, 20.56blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" ] }, { @@ -30488,7 +30466,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 16%|█▌ | 35/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=0, ✔=36, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" ] }, { @@ -30510,7 +30488,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=1, ✔=36, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=1, ✔=37, ✗=0, ∅=0]" ] }, { @@ -30532,7 +30510,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 36/216 [00:01<00:09, 18.56blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=0, ✔=38, ✗=0, ∅=0]" ] }, { @@ -30554,7 +30532,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:09, 19.35blocks/s, ⧗=0, ▶=0, ✔=37, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=1, ✔=38, ✗=0, ∅=0]" ] }, { @@ -30576,7 +30554,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:01<00:09, 19.35blocks/s, ⧗=0, ▶=1, ✔=37, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" ] }, { @@ -30598,7 +30576,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 17%|█▋ | 37/216 [00:02<00:09, 19.35blocks/s, ⧗=0, ▶=0, ✔=38, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=1, ✔=39, ✗=0, ∅=0]" ] }, { @@ -30620,7 +30598,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:02<00:09, 19.35blocks/s, ⧗=0, ▶=1, ✔=38, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:01<00:08, 20.64blocks/s, ⧗=0, ▶=0, ✔=40, ✗=0, ∅=0]" ] }, { @@ -30642,7 +30620,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 38/216 [00:02<00:09, 19.35blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:01<00:08, 20.18blocks/s, ⧗=0, ▶=0, ✔=40, ✗=0, ∅=0]" ] }, { @@ -30664,7 +30642,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 19.08blocks/s, ⧗=0, ▶=0, ✔=39, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:01<00:08, 20.18blocks/s, ⧗=0, ▶=1, ✔=40, ✗=0, ∅=0]" ] }, { @@ -30686,7 +30664,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 19.08blocks/s, ⧗=0, ▶=1, ✔=39, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:08, 20.18blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" ] }, { @@ -30708,7 +30686,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 18%|█▊ | 39/216 [00:02<00:09, 19.08blocks/s, ⧗=0, ▶=0, ✔=40, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:08, 20.18blocks/s, ⧗=0, ▶=1, ✔=41, ✗=0, ∅=0]" ] }, { @@ -30730,7 +30708,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:09, 19.08blocks/s, ⧗=0, ▶=1, ✔=40, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:08, 20.18blocks/s, ⧗=0, ▶=0, ✔=42, ✗=0, ∅=0]" ] }, { @@ -30752,7 +30730,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▊ | 40/216 [00:02<00:09, 19.08blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:08, 20.18blocks/s, ⧗=0, ▶=1, ✔=42, ✗=0, ∅=0]" ] }, { @@ -30774,7 +30752,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.93blocks/s, ⧗=0, ▶=0, ✔=41, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:08, 20.18blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" ] }, { @@ -30796,7 +30774,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.93blocks/s, ⧗=0, ▶=1, ✔=41, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:08, 19.68blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" ] }, { @@ -30818,7 +30796,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 41/216 [00:02<00:09, 18.93blocks/s, ⧗=0, ▶=0, ✔=42, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:08, 19.68blocks/s, ⧗=0, ▶=1, ✔=43, ✗=0, ∅=0]" ] }, { @@ -30840,7 +30818,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:09, 18.93blocks/s, ⧗=0, ▶=1, ✔=42, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:08, 19.68blocks/s, ⧗=0, ▶=0, ✔=44, ✗=0, ∅=0]" ] }, { @@ -30862,7 +30840,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 19%|█▉ | 42/216 [00:02<00:09, 18.93blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:08, 19.68blocks/s, ⧗=0, ▶=1, ✔=44, ✗=0, ∅=0]" ] }, { @@ -30884,7 +30862,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=0, ✔=43, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:08, 19.68blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" ] }, { @@ -30906,7 +30884,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=1, ✔=43, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:08, 19.13blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" ] }, { @@ -30928,7 +30906,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|█▉ | 43/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=0, ✔=44, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:08, 19.13blocks/s, ⧗=0, ▶=1, ✔=45, ✗=0, ∅=0]" ] }, { @@ -30950,7 +30928,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=1, ✔=44, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:08, 19.13blocks/s, ⧗=0, ▶=0, ✔=46, ✗=0, ∅=0]" ] }, { @@ -30972,7 +30950,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 20%|██ | 44/216 [00:02<00:09, 18.92blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:08, 19.13blocks/s, ⧗=0, ▶=1, ✔=46, ✗=0, ∅=0]" ] }, { @@ -30994,7 +30972,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:09, 18.33blocks/s, ⧗=0, ▶=0, ✔=45, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:08, 19.13blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" ] }, { @@ -31016,7 +30994,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:09, 18.33blocks/s, ⧗=0, ▶=1, ✔=45, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:08, 19.12blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" ] }, { @@ -31038,7 +31016,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██ | 45/216 [00:02<00:09, 18.33blocks/s, ⧗=0, ▶=0, ✔=46, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:08, 19.12blocks/s, ⧗=0, ▶=1, ✔=47, ✗=0, ∅=0]" ] }, { @@ -31060,7 +31038,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:09, 18.33blocks/s, ⧗=0, ▶=1, ✔=46, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:08, 19.12blocks/s, ⧗=0, ▶=0, ✔=48, ✗=0, ∅=0]" ] }, { @@ -31082,7 +31060,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 21%|██▏ | 46/216 [00:02<00:09, 18.33blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:08, 19.12blocks/s, ⧗=0, ▶=1, ✔=48, ✗=0, ∅=0]" ] }, { @@ -31104,7 +31082,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 18.40blocks/s, ⧗=0, ▶=0, ✔=47, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:08, 19.12blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" ] }, { @@ -31126,7 +31104,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 18.40blocks/s, ⧗=0, ▶=1, ✔=47, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:08, 18.91blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" ] }, { @@ -31148,7 +31126,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 47/216 [00:02<00:09, 18.40blocks/s, ⧗=0, ▶=0, ✔=48, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:08, 18.91blocks/s, ⧗=0, ▶=1, ✔=49, ✗=0, ∅=0]" ] }, { @@ -31170,7 +31148,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:09, 18.40blocks/s, ⧗=0, ▶=1, ✔=48, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:08, 18.91blocks/s, ⧗=0, ▶=0, ✔=50, ✗=0, ∅=0]" ] }, { @@ -31192,7 +31170,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 22%|██▏ | 48/216 [00:02<00:09, 18.40blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:08, 18.91blocks/s, ⧗=0, ▶=1, ✔=50, ✗=0, ∅=0]" ] }, { @@ -31214,7 +31192,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 18.31blocks/s, ⧗=0, ▶=0, ✔=49, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:08, 18.91blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" ] }, { @@ -31236,7 +31214,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 18.31blocks/s, ⧗=0, ▶=1, ✔=49, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:09, 17.75blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" ] }, { @@ -31258,7 +31236,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 49/216 [00:02<00:09, 18.31blocks/s, ⧗=0, ▶=0, ✔=50, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:09, 17.75blocks/s, ⧗=0, ▶=1, ✔=51, ✗=0, ∅=0]" ] }, { @@ -31280,7 +31258,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:09, 18.31blocks/s, ⧗=0, ▶=1, ✔=50, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:09, 17.75blocks/s, ⧗=0, ▶=0, ✔=52, ✗=0, ∅=0]" ] }, { @@ -31302,7 +31280,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 23%|██▎ | 50/216 [00:02<00:09, 18.31blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:09, 17.75blocks/s, ⧗=0, ▶=1, ✔=52, ✗=0, ∅=0]" ] }, { @@ -31324,7 +31302,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:09, 17.08blocks/s, ⧗=0, ▶=0, ✔=51, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:09, 17.75blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" ] }, { @@ -31346,7 +31324,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:09, 17.08blocks/s, ⧗=0, ▶=1, ✔=51, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:09, 17.00blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" ] }, { @@ -31368,7 +31346,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▎ | 51/216 [00:02<00:09, 17.08blocks/s, ⧗=0, ▶=0, ✔=52, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:09, 17.00blocks/s, ⧗=0, ▶=1, ✔=53, ✗=0, ∅=0]" ] }, { @@ -31390,7 +31368,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:09, 17.08blocks/s, ⧗=0, ▶=1, ✔=52, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:09, 17.00blocks/s, ⧗=0, ▶=0, ✔=54, ✗=0, ∅=0]" ] }, { @@ -31412,7 +31390,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 24%|██▍ | 52/216 [00:02<00:09, 17.08blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:02<00:09, 17.00blocks/s, ⧗=0, ▶=1, ✔=54, ✗=0, ∅=0]" ] }, { @@ -31434,7 +31412,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 16.00blocks/s, ⧗=0, ▶=0, ✔=53, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:02<00:09, 17.00blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" ] }, { @@ -31456,7 +31434,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 16.00blocks/s, ⧗=0, ▶=1, ✔=53, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:02<00:09, 17.40blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" ] }, { @@ -31478,7 +31456,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▍ | 53/216 [00:02<00:10, 16.00blocks/s, ⧗=0, ▶=0, ✔=54, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:02<00:09, 17.40blocks/s, ⧗=0, ▶=1, ✔=55, ✗=0, ∅=0]" ] }, { @@ -31500,7 +31478,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:02<00:10, 16.00blocks/s, ⧗=0, ▶=1, ✔=54, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:02<00:09, 17.40blocks/s, ⧗=0, ▶=0, ✔=56, ✗=0, ∅=0]" ] }, { @@ -31522,7 +31500,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 54/216 [00:03<00:10, 16.00blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:02<00:09, 17.40blocks/s, ⧗=0, ▶=1, ✔=56, ✗=0, ∅=0]" ] }, { @@ -31544,7 +31522,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 15.70blocks/s, ⧗=0, ▶=0, ✔=55, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:02<00:09, 17.40blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" ] }, { @@ -31566,7 +31544,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 15.70blocks/s, ⧗=0, ▶=1, ✔=55, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:02<00:09, 17.61blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" ] }, { @@ -31588,7 +31566,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 25%|██▌ | 55/216 [00:03<00:10, 15.70blocks/s, ⧗=0, ▶=0, ✔=56, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:02<00:09, 17.61blocks/s, ⧗=0, ▶=1, ✔=57, ✗=0, ∅=0]" ] }, { @@ -31610,7 +31588,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:03<00:10, 15.70blocks/s, ⧗=0, ▶=1, ✔=56, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:02<00:09, 17.61blocks/s, ⧗=0, ▶=0, ✔=58, ✗=0, ∅=0]" ] }, { @@ -31632,7 +31610,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▌ | 56/216 [00:03<00:10, 15.70blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:02<00:08, 17.61blocks/s, ⧗=0, ▶=1, ✔=58, ✗=0, ∅=0]" ] }, { @@ -31654,7 +31632,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.14blocks/s, ⧗=0, ▶=0, ✔=57, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:08, 17.61blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" ] }, { @@ -31676,7 +31654,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.14blocks/s, ⧗=0, ▶=1, ✔=57, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 17.44blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" ] }, { @@ -31698,7 +31676,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 26%|██▋ | 57/216 [00:03<00:09, 16.14blocks/s, ⧗=0, ▶=0, ✔=58, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 17.44blocks/s, ⧗=0, ▶=1, ✔=59, ✗=0, ∅=0]" ] }, { @@ -31720,7 +31698,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:09, 16.14blocks/s, ⧗=0, ▶=1, ✔=58, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 17.44blocks/s, ⧗=0, ▶=0, ✔=60, ✗=0, ∅=0]" ] }, { @@ -31742,7 +31720,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 58/216 [00:03<00:09, 16.14blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:08, 17.44blocks/s, ⧗=0, ▶=1, ✔=60, ✗=0, ∅=0]" ] }, { @@ -31764,7 +31742,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.79blocks/s, ⧗=0, ▶=0, ✔=59, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:08, 17.44blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" ] }, { @@ -31786,7 +31764,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.79blocks/s, ⧗=0, ▶=1, ✔=59, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:08, 18.02blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" ] }, { @@ -31808,7 +31786,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 27%|██▋ | 59/216 [00:03<00:09, 16.79blocks/s, ⧗=0, ▶=0, ✔=60, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:08, 18.02blocks/s, ⧗=0, ▶=1, ✔=61, ✗=0, ∅=0]" ] }, { @@ -31830,7 +31808,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:09, 16.79blocks/s, ⧗=0, ▶=1, ✔=60, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:08, 18.02blocks/s, ⧗=0, ▶=0, ✔=62, ✗=0, ∅=0]" ] }, { @@ -31852,7 +31830,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 60/216 [00:03<00:09, 16.79blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:08, 18.02blocks/s, ⧗=0, ▶=1, ✔=62, ✗=0, ∅=0]" ] }, { @@ -31874,7 +31852,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:08, 17.42blocks/s, ⧗=0, ▶=0, ✔=61, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:08, 18.02blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" ] }, { @@ -31896,7 +31874,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:08, 17.42blocks/s, ⧗=0, ▶=1, ✔=61, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:08, 17.41blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" ] }, { @@ -31918,7 +31896,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 28%|██▊ | 61/216 [00:03<00:08, 17.42blocks/s, ⧗=0, ▶=0, ✔=62, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:08, 17.41blocks/s, ⧗=0, ▶=1, ✔=63, ✗=0, ∅=0]" ] }, { @@ -31940,7 +31918,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:08, 17.42blocks/s, ⧗=0, ▶=1, ✔=62, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:08, 17.41blocks/s, ⧗=0, ▶=0, ✔=64, ✗=0, ∅=0]" ] }, { @@ -31962,7 +31940,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▊ | 62/216 [00:03<00:08, 17.42blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:08, 17.41blocks/s, ⧗=0, ▶=1, ✔=64, ✗=0, ∅=0]" ] }, { @@ -31984,7 +31962,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:08, 17.09blocks/s, ⧗=0, ▶=0, ✔=63, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:08, 17.41blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" ] }, { @@ -32006,7 +31984,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:08, 17.09blocks/s, ⧗=0, ▶=1, ✔=63, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 17.23blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" ] }, { @@ -32028,7 +32006,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 29%|██▉ | 63/216 [00:03<00:08, 17.09blocks/s, ⧗=0, ▶=0, ✔=64, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 17.23blocks/s, ⧗=0, ▶=1, ✔=65, ✗=0, ∅=0]" ] }, { @@ -32050,7 +32028,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:08, 17.09blocks/s, ⧗=0, ▶=1, ✔=64, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:08, 17.23blocks/s, ⧗=0, ▶=0, ✔=66, ✗=0, ∅=0]" ] }, { @@ -32072,7 +32050,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|██▉ | 64/216 [00:03<00:08, 17.09blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 17.23blocks/s, ⧗=0, ▶=1, ✔=66, ✗=0, ∅=0]" ] }, { @@ -32094,7 +32072,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:09, 16.76blocks/s, ⧗=0, ▶=0, ✔=65, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 17.23blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" ] }, { @@ -32116,7 +32094,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:09, 16.76blocks/s, ⧗=0, ▶=1, ✔=65, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 17.58blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" ] }, { @@ -32138,7 +32116,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 30%|███ | 65/216 [00:03<00:09, 16.76blocks/s, ⧗=0, ▶=0, ✔=66, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 17.58blocks/s, ⧗=0, ▶=1, ✔=67, ✗=0, ∅=0]" ] }, { @@ -32160,7 +32138,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 16.76blocks/s, ⧗=0, ▶=1, ✔=66, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 17.58blocks/s, ⧗=0, ▶=0, ✔=68, ✗=0, ∅=0]" ] }, { @@ -32182,7 +32160,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 66/216 [00:03<00:08, 16.76blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 17.58blocks/s, ⧗=0, ▶=1, ✔=68, ✗=0, ∅=0]" ] }, { @@ -32204,7 +32182,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 16.98blocks/s, ⧗=0, ▶=0, ✔=67, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 17.58blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" ] }, { @@ -32226,7 +32204,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 16.98blocks/s, ⧗=0, ▶=1, ✔=67, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.61blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" ] }, { @@ -32248,7 +32226,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███ | 67/216 [00:03<00:08, 16.98blocks/s, ⧗=0, ▶=0, ✔=68, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.61blocks/s, ⧗=0, ▶=1, ✔=69, ✗=0, ∅=0]" ] }, { @@ -32270,7 +32248,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 16.98blocks/s, ⧗=0, ▶=1, ✔=68, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.61blocks/s, ⧗=0, ▶=0, ✔=70, ✗=0, ∅=0]" ] }, { @@ -32292,7 +32270,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 31%|███▏ | 68/216 [00:03<00:08, 16.98blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 17.61blocks/s, ⧗=0, ▶=1, ✔=70, ✗=0, ∅=0]" ] }, { @@ -32314,7 +32292,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.04blocks/s, ⧗=0, ▶=0, ✔=69, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 17.61blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" ] }, { @@ -32336,7 +32314,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.04blocks/s, ⧗=0, ▶=1, ✔=69, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.70blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" ] }, { @@ -32358,7 +32336,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 69/216 [00:03<00:08, 17.04blocks/s, ⧗=0, ▶=0, ✔=70, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.70blocks/s, ⧗=0, ▶=1, ✔=71, ✗=0, ∅=0]" ] }, { @@ -32380,7 +32358,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 17.04blocks/s, ⧗=0, ▶=1, ✔=70, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.70blocks/s, ⧗=0, ▶=0, ✔=72, ✗=0, ∅=0]" ] }, { @@ -32402,7 +32380,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 32%|███▏ | 70/216 [00:03<00:08, 17.04blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:03<00:08, 17.70blocks/s, ⧗=0, ▶=1, ✔=72, ✗=0, ∅=0]" ] }, { @@ -32424,7 +32402,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.43blocks/s, ⧗=0, ▶=0, ✔=71, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:03<00:08, 17.70blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" ] }, { @@ -32446,7 +32424,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:03<00:08, 17.43blocks/s, ⧗=0, ▶=1, ✔=71, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:03<00:08, 17.38blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" ] }, { @@ -32468,7 +32446,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 71/216 [00:04<00:08, 17.43blocks/s, ⧗=0, ▶=0, ✔=72, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:03<00:08, 17.38blocks/s, ⧗=0, ▶=1, ✔=73, ✗=0, ∅=0]" ] }, { @@ -32490,7 +32468,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:04<00:08, 17.43blocks/s, ⧗=0, ▶=1, ✔=72, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:03<00:08, 17.38blocks/s, ⧗=0, ▶=0, ✔=74, ✗=0, ∅=0]" ] }, { @@ -32512,7 +32490,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 33%|███▎ | 72/216 [00:04<00:08, 17.43blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:03<00:08, 17.38blocks/s, ⧗=0, ▶=1, ✔=74, ✗=0, ∅=0]" ] }, { @@ -32534,7 +32512,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.78blocks/s, ⧗=0, ▶=0, ✔=73, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:03<00:08, 17.38blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" ] }, { @@ -32556,7 +32534,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.78blocks/s, ⧗=0, ▶=1, ✔=73, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:03<00:08, 16.83blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" ] }, { @@ -32578,7 +32556,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 73/216 [00:04<00:08, 17.78blocks/s, ⧗=0, ▶=0, ✔=74, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:03<00:08, 16.83blocks/s, ⧗=0, ▶=1, ✔=75, ✗=0, ∅=0]" ] }, { @@ -32600,7 +32578,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:04<00:07, 17.78blocks/s, ⧗=0, ▶=1, ✔=74, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:08, 16.83blocks/s, ⧗=0, ▶=0, ✔=76, ✗=0, ∅=0]" ] }, { @@ -32622,7 +32600,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 34%|███▍ | 74/216 [00:04<00:07, 17.78blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:08, 16.83blocks/s, ⧗=0, ▶=1, ✔=76, ✗=0, ∅=0]" ] }, { @@ -32644,7 +32622,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=0, ✔=75, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:08, 16.83blocks/s, ⧗=0, ▶=0, ✔=77, ✗=0, ∅=0]" ] }, { @@ -32666,7 +32644,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=1, ✔=75, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:08, 16.83blocks/s, ⧗=0, ▶=1, ✔=77, ✗=0, ∅=0]" ] }, { @@ -32688,7 +32666,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▍ | 75/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=0, ✔=76, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:08, 16.83blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" ] }, { @@ -32710,7 +32688,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=1, ✔=76, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" ] }, { @@ -32732,7 +32710,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 35%|███▌ | 76/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=0, ✔=77, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=1, ✔=78, ✗=0, ∅=0]" ] }, { @@ -32754,7 +32732,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=1, ✔=77, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=0, ✔=79, ✗=0, ∅=0]" ] }, { @@ -32776,7 +32754,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 77/216 [00:04<00:07, 18.18blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=1, ✔=79, ✗=0, ∅=0]" ] }, { @@ -32798,7 +32776,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 19.05blocks/s, ⧗=0, ▶=0, ✔=78, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" ] }, { @@ -32820,7 +32798,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 19.05blocks/s, ⧗=0, ▶=1, ✔=78, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=1, ✔=80, ✗=0, ∅=0]" ] }, { @@ -32842,7 +32820,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 36%|███▌ | 78/216 [00:04<00:07, 19.05blocks/s, ⧗=0, ▶=0, ✔=79, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.31blocks/s, ⧗=0, ▶=0, ✔=81, ✗=0, ∅=0]" ] }, { @@ -32864,7 +32842,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 19.05blocks/s, ⧗=0, ▶=1, ✔=79, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.61blocks/s, ⧗=0, ▶=0, ✔=81, ✗=0, ∅=0]" ] }, { @@ -32886,7 +32864,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 79/216 [00:04<00:07, 19.05blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.61blocks/s, ⧗=0, ▶=1, ✔=81, ✗=0, ∅=0]" ] }, { @@ -32908,7 +32886,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.93blocks/s, ⧗=0, ▶=0, ✔=80, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.61blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" ] }, { @@ -32930,7 +32908,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.93blocks/s, ⧗=0, ▶=1, ✔=80, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.61blocks/s, ⧗=0, ▶=1, ✔=82, ✗=0, ∅=0]" ] }, { @@ -32952,7 +32930,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 37%|███▋ | 80/216 [00:04<00:07, 18.93blocks/s, ⧗=0, ▶=0, ✔=81, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.61blocks/s, ⧗=0, ▶=0, ✔=83, ✗=0, ∅=0]" ] }, { @@ -32974,7 +32952,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.93blocks/s, ⧗=0, ▶=1, ✔=81, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.79blocks/s, ⧗=0, ▶=0, ✔=83, ✗=0, ∅=0]" ] }, { @@ -32996,7 +32974,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 81/216 [00:04<00:07, 18.93blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.79blocks/s, ⧗=0, ▶=1, ✔=83, ✗=0, ∅=0]" ] }, { @@ -33018,7 +32996,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.88blocks/s, ⧗=0, ▶=0, ✔=82, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.79blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" ] }, { @@ -33040,7 +33018,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.88blocks/s, ⧗=0, ▶=1, ✔=82, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:07, 18.79blocks/s, ⧗=0, ▶=1, ✔=84, ✗=0, ∅=0]" ] }, { @@ -33062,7 +33040,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 82/216 [00:04<00:07, 18.88blocks/s, ⧗=0, ▶=0, ✔=83, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:07, 18.79blocks/s, ⧗=0, ▶=0, ✔=85, ✗=0, ∅=0]" ] }, { @@ -33084,7 +33062,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.88blocks/s, ⧗=0, ▶=1, ✔=83, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:07, 18.51blocks/s, ⧗=0, ▶=0, ✔=85, ✗=0, ∅=0]" ] }, { @@ -33106,7 +33084,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 38%|███▊ | 83/216 [00:04<00:07, 18.88blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:07, 18.51blocks/s, ⧗=0, ▶=1, ✔=85, ✗=0, ∅=0]" ] }, { @@ -33128,7 +33106,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:06, 19.05blocks/s, ⧗=0, ▶=0, ✔=84, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:07, 18.51blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" ] }, { @@ -33150,7 +33128,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:06, 19.05blocks/s, ⧗=0, ▶=1, ✔=84, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:07, 18.51blocks/s, ⧗=0, ▶=1, ✔=86, ✗=0, ∅=0]" ] }, { @@ -33172,7 +33150,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 84/216 [00:04<00:06, 19.05blocks/s, ⧗=0, ▶=0, ✔=85, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:07, 18.51blocks/s, ⧗=0, ▶=0, ✔=87, ✗=0, ∅=0]" ] }, { @@ -33194,7 +33172,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:06, 19.05blocks/s, ⧗=0, ▶=1, ✔=85, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:07, 17.97blocks/s, ⧗=0, ▶=0, ✔=87, ✗=0, ∅=0]" ] }, { @@ -33216,7 +33194,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 39%|███▉ | 85/216 [00:04<00:06, 19.05blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:07, 17.97blocks/s, ⧗=0, ▶=1, ✔=87, ✗=0, ∅=0]" ] }, { @@ -33238,7 +33216,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:06, 18.76blocks/s, ⧗=0, ▶=0, ✔=86, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:07, 17.97blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" ] }, { @@ -33260,7 +33238,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:06, 18.76blocks/s, ⧗=0, ▶=1, ✔=86, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.97blocks/s, ⧗=0, ▶=1, ✔=88, ✗=0, ∅=0]" ] }, { @@ -33282,7 +33260,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|███▉ | 86/216 [00:04<00:06, 18.76blocks/s, ⧗=0, ▶=0, ✔=87, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.97blocks/s, ⧗=0, ▶=0, ✔=89, ✗=0, ∅=0]" ] }, { @@ -33304,7 +33282,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:06, 18.76blocks/s, ⧗=0, ▶=1, ✔=87, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.47blocks/s, ⧗=0, ▶=0, ✔=89, ✗=0, ∅=0]" ] }, { @@ -33326,7 +33304,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 40%|████ | 87/216 [00:04<00:06, 18.76blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.47blocks/s, ⧗=0, ▶=1, ✔=89, ✗=0, ∅=0]" ] }, { @@ -33348,7 +33326,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.35blocks/s, ⧗=0, ▶=0, ✔=88, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.47blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" ] }, { @@ -33370,7 +33348,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.35blocks/s, ⧗=0, ▶=1, ✔=88, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:04<00:07, 17.47blocks/s, ⧗=0, ▶=1, ✔=90, ✗=0, ∅=0]" ] }, { @@ -33392,7 +33370,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 88/216 [00:04<00:07, 17.35blocks/s, ⧗=0, ▶=0, ✔=89, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:04<00:07, 17.47blocks/s, ⧗=0, ▶=0, ✔=91, ✗=0, ∅=0]" ] }, { @@ -33414,7 +33392,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.35blocks/s, ⧗=0, ▶=1, ✔=89, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:04<00:06, 18.04blocks/s, ⧗=0, ▶=0, ✔=91, ✗=0, ∅=0]" ] }, { @@ -33436,7 +33414,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 41%|████ | 89/216 [00:04<00:07, 17.35blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:04<00:06, 18.04blocks/s, ⧗=0, ▶=1, ✔=91, ✗=0, ∅=0]" ] }, { @@ -33458,7 +33436,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:04<00:07, 17.60blocks/s, ⧗=0, ▶=0, ✔=90, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:04<00:06, 18.04blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" ] }, { @@ -33480,7 +33458,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:04<00:07, 17.60blocks/s, ⧗=0, ▶=1, ✔=90, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:04<00:06, 18.04blocks/s, ⧗=0, ▶=1, ✔=92, ✗=0, ∅=0]" ] }, { @@ -33502,7 +33480,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 90/216 [00:05<00:07, 17.60blocks/s, ⧗=0, ▶=0, ✔=91, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:04<00:06, 18.04blocks/s, ⧗=0, ▶=0, ✔=93, ✗=0, ∅=0]" ] }, { @@ -33524,7 +33502,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:05<00:07, 17.60blocks/s, ⧗=0, ▶=1, ✔=91, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:04<00:06, 17.76blocks/s, ⧗=0, ▶=0, ✔=93, ✗=0, ∅=0]" ] }, { @@ -33546,7 +33524,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 42%|████▏ | 91/216 [00:05<00:07, 17.60blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:04<00:06, 17.76blocks/s, ⧗=0, ▶=1, ✔=93, ✗=0, ∅=0]" ] }, { @@ -33568,7 +33546,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:06, 18.10blocks/s, ⧗=0, ▶=0, ✔=92, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:04<00:06, 17.76blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" ] }, { @@ -33590,7 +33568,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:06, 18.10blocks/s, ⧗=0, ▶=1, ✔=92, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:04<00:06, 17.76blocks/s, ⧗=0, ▶=1, ✔=94, ✗=0, ∅=0]" ] }, { @@ -33612,7 +33590,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 92/216 [00:05<00:06, 18.10blocks/s, ⧗=0, ▶=0, ✔=93, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.76blocks/s, ⧗=0, ▶=0, ✔=95, ✗=0, ∅=0]" ] }, { @@ -33634,7 +33612,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:05<00:06, 18.10blocks/s, ⧗=0, ▶=1, ✔=93, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=95, ✗=0, ∅=0]" ] }, { @@ -33656,7 +33634,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 43%|████▎ | 93/216 [00:05<00:06, 18.10blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=1, ✔=95, ✗=0, ∅=0]" ] }, { @@ -33678,7 +33656,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.91blocks/s, ⧗=0, ▶=0, ✔=94, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" ] }, { @@ -33700,7 +33678,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.91blocks/s, ⧗=0, ▶=1, ✔=94, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=1, ✔=96, ✗=0, ∅=0]" ] }, { @@ -33722,7 +33700,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▎ | 94/216 [00:05<00:06, 17.91blocks/s, ⧗=0, ▶=0, ✔=95, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=97, ✗=0, ∅=0]" ] }, { @@ -33744,7 +33722,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 17.91blocks/s, ⧗=0, ▶=1, ✔=95, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=1, ✔=97, ✗=0, ∅=0]" ] }, { @@ -33766,7 +33744,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 95/216 [00:05<00:06, 17.91blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.27blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" ] }, { @@ -33788,7 +33766,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.46blocks/s, ⧗=0, ▶=0, ✔=96, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 19.22blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" ] }, { @@ -33810,7 +33788,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.46blocks/s, ⧗=0, ▶=1, ✔=96, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 19.22blocks/s, ⧗=0, ▶=1, ✔=98, ✗=0, ∅=0]" ] }, { @@ -33832,7 +33810,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 44%|████▍ | 96/216 [00:05<00:06, 18.46blocks/s, ⧗=0, ▶=0, ✔=97, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 19.22blocks/s, ⧗=0, ▶=0, ✔=99, ✗=0, ∅=0]" ] }, { @@ -33854,7 +33832,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.46blocks/s, ⧗=0, ▶=1, ✔=97, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 19.22blocks/s, ⧗=0, ▶=1, ✔=99, ✗=0, ∅=0]" ] }, { @@ -33876,7 +33854,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▍ | 97/216 [00:05<00:06, 18.46blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 19.22blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" ] }, { @@ -33898,7 +33876,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.45blocks/s, ⧗=0, ▶=0, ✔=98, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 19.07blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" ] }, { @@ -33920,7 +33898,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.45blocks/s, ⧗=0, ▶=1, ✔=98, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 19.07blocks/s, ⧗=0, ▶=1, ✔=100, ✗=0, ∅=0]" ] }, { @@ -33942,7 +33920,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 45%|████▌ | 98/216 [00:05<00:06, 18.45blocks/s, ⧗=0, ▶=0, ✔=99, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 19.07blocks/s, ⧗=0, ▶=0, ✔=101, ✗=0, ∅=0]" ] }, { @@ -33964,7 +33942,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 18.45blocks/s, ⧗=0, ▶=1, ✔=99, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 19.07blocks/s, ⧗=0, ▶=1, ✔=101, ✗=0, ∅=0]" ] }, { @@ -33986,7 +33964,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▌ | 99/216 [00:05<00:06, 18.45blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 19.07blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" ] }, { @@ -34008,7 +33986,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 16.97blocks/s, ⧗=0, ▶=0, ✔=100, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:05, 19.07blocks/s, ⧗=0, ▶=1, ✔=102, ✗=0, ∅=0]" ] }, { @@ -34030,7 +34008,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 16.97blocks/s, ⧗=0, ▶=1, ✔=100, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:05, 19.07blocks/s, ⧗=0, ▶=0, ✔=103, ✗=0, ∅=0]" ] }, { @@ -34052,7 +34030,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 46%|████▋ | 100/216 [00:05<00:06, 16.97blocks/s, ⧗=0, ▶=0, ✔=101, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:05, 19.64blocks/s, ⧗=0, ▶=0, ✔=103, ✗=0, ∅=0]" ] }, { @@ -34074,7 +34052,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 16.97blocks/s, ⧗=0, ▶=1, ✔=101, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:05, 19.64blocks/s, ⧗=0, ▶=1, ✔=103, ✗=0, ∅=0]" ] }, { @@ -34096,7 +34074,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 101/216 [00:05<00:06, 16.97blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:05, 19.64blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" ] }, { @@ -34118,7 +34096,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 17.54blocks/s, ⧗=0, ▶=0, ✔=102, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:05, 19.64blocks/s, ⧗=0, ▶=1, ✔=104, ✗=0, ∅=0]" ] }, { @@ -34140,7 +34118,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 17.54blocks/s, ⧗=0, ▶=1, ✔=102, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:05, 19.64blocks/s, ⧗=0, ▶=0, ✔=105, ✗=0, ∅=0]" ] }, { @@ -34162,7 +34140,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 47%|████▋ | 102/216 [00:05<00:06, 17.54blocks/s, ⧗=0, ▶=0, ✔=103, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=0, ✔=105, ✗=0, ∅=0]" ] }, { @@ -34184,7 +34162,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:06, 17.54blocks/s, ⧗=0, ▶=1, ✔=103, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=1, ✔=105, ✗=0, ∅=0]" ] }, { @@ -34206,7 +34184,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 103/216 [00:05<00:06, 17.54blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" ] }, { @@ -34228,7 +34206,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:06, 17.83blocks/s, ⧗=0, ▶=0, ✔=104, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=1, ✔=106, ✗=0, ∅=0]" ] }, { @@ -34250,7 +34228,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:06, 17.83blocks/s, ⧗=0, ▶=1, ✔=104, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=0, ✔=107, ✗=0, ∅=0]" ] }, { @@ -34272,7 +34250,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 48%|████▊ | 104/216 [00:05<00:06, 17.83blocks/s, ⧗=0, ▶=0, ✔=105, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=1, ✔=107, ✗=0, ∅=0]" ] }, { @@ -34294,7 +34272,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:06, 17.83blocks/s, ⧗=0, ▶=1, ✔=105, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:05, 19.51blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" ] }, { @@ -34316,7 +34294,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▊ | 105/216 [00:05<00:06, 17.83blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" ] }, { @@ -34338,7 +34316,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:06, 18.06blocks/s, ⧗=0, ▶=0, ✔=106, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=1, ✔=108, ✗=0, ∅=0]" ] }, { @@ -34360,7 +34338,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:06, 18.06blocks/s, ⧗=0, ▶=1, ✔=106, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=0, ✔=109, ✗=0, ∅=0]" ] }, { @@ -34382,7 +34360,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 49%|████▉ | 106/216 [00:05<00:06, 18.06blocks/s, ⧗=0, ▶=0, ✔=107, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 109/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=1, ✔=109, ✗=0, ∅=0]" ] }, { @@ -34404,7 +34382,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:06, 18.06blocks/s, ⧗=0, ▶=1, ✔=107, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 109/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=0, ✔=110, ✗=0, ∅=0]" ] }, { @@ -34426,7 +34404,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|████▉ | 107/216 [00:05<00:06, 18.06blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████ | 110/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=1, ✔=110, ✗=0, ∅=0]" ] }, { @@ -34448,7 +34426,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:06, 17.32blocks/s, ⧗=0, ▶=0, ✔=108, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████ | 110/216 [00:05<00:05, 20.00blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" ] }, { @@ -34470,7 +34448,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 108/216 [00:05<00:06, 17.32blocks/s, ⧗=0, ▶=1, ✔=108, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" ] }, { @@ -34492,7 +34470,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 108/216 [00:06<00:06, 17.32blocks/s, ⧗=0, ▶=0, ✔=109, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=1, ✔=111, ✗=0, ∅=0]" ] }, { @@ -34514,7 +34492,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 109/216 [00:06<00:06, 17.32blocks/s, ⧗=0, ▶=1, ✔=109, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=0, ✔=112, ✗=0, ∅=0]" ] }, { @@ -34536,7 +34514,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 50%|█████ | 109/216 [00:06<00:06, 17.32blocks/s, ⧗=0, ▶=0, ✔=110, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=1, ✔=112, ✗=0, ∅=0]" ] }, { @@ -34558,7 +34536,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:06, 17.58blocks/s, ⧗=0, ▶=0, ✔=110, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=0, ✔=113, ✗=0, ∅=0]" ] }, { @@ -34580,7 +34558,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:06, 17.58blocks/s, ⧗=0, ▶=1, ✔=110, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=1, ✔=113, ✗=0, ∅=0]" ] }, { @@ -34602,7 +34580,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████ | 110/216 [00:06<00:06, 17.58blocks/s, ⧗=0, ▶=0, ✔=111, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:05<00:05, 19.85blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" ] }, { @@ -34624,7 +34602,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 17.58blocks/s, ⧗=0, ▶=1, ✔=111, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:05<00:04, 20.65blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" ] }, { @@ -34646,7 +34624,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 51%|█████▏ | 111/216 [00:06<00:05, 17.58blocks/s, ⧗=0, ▶=0, ✔=112, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:05<00:04, 20.65blocks/s, ⧗=0, ▶=1, ✔=114, ✗=0, ∅=0]" ] }, { @@ -34668,7 +34646,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 17.53blocks/s, ⧗=0, ▶=0, ✔=112, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:04, 20.65blocks/s, ⧗=0, ▶=0, ✔=115, ✗=0, ∅=0]" ] }, { @@ -34690,7 +34668,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 17.53blocks/s, ⧗=0, ▶=1, ✔=112, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:04, 20.65blocks/s, ⧗=0, ▶=1, ✔=115, ✗=0, ∅=0]" ] }, { @@ -34712,7 +34690,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 112/216 [00:06<00:05, 17.53blocks/s, ⧗=0, ▶=0, ✔=113, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:04, 20.65blocks/s, ⧗=0, ▶=0, ✔=116, ✗=0, ∅=0]" ] }, { @@ -34734,7 +34712,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 17.53blocks/s, ⧗=0, ▶=1, ✔=113, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:04, 20.65blocks/s, ⧗=0, ▶=1, ✔=116, ✗=0, ∅=0]" ] }, { @@ -34756,7 +34734,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 52%|█████▏ | 113/216 [00:06<00:05, 17.53blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:04, 20.65blocks/s, ⧗=0, ▶=0, ✔=117, ✗=0, ∅=0]" ] }, { @@ -34778,7 +34756,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 17.01blocks/s, ⧗=0, ▶=0, ✔=114, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=0, ✔=117, ✗=0, ∅=0]" ] }, { @@ -34800,7 +34778,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 17.01blocks/s, ⧗=0, ▶=1, ✔=114, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=1, ✔=117, ✗=0, ∅=0]" ] }, { @@ -34822,7 +34800,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 114/216 [00:06<00:05, 17.01blocks/s, ⧗=0, ▶=0, ✔=115, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=0, ✔=118, ✗=0, ∅=0]" ] }, { @@ -34844,7 +34822,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 17.01blocks/s, ⧗=0, ▶=1, ✔=115, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=1, ✔=118, ✗=0, ∅=0]" ] }, { @@ -34866,7 +34844,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 53%|█████▎ | 115/216 [00:06<00:05, 17.01blocks/s, ⧗=0, ▶=0, ✔=116, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=0, ✔=119, ✗=0, ∅=0]" ] }, { @@ -34888,7 +34866,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 17.41blocks/s, ⧗=0, ▶=0, ✔=116, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=1, ✔=119, ✗=0, ∅=0]" ] }, { @@ -34910,7 +34888,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 17.41blocks/s, ⧗=0, ▶=1, ✔=116, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:04, 20.22blocks/s, ⧗=0, ▶=0, ✔=120, ✗=0, ∅=0]" ] }, { @@ -34932,7 +34910,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▎ | 116/216 [00:06<00:05, 17.41blocks/s, ⧗=0, ▶=0, ✔=117, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=0, ✔=120, ✗=0, ∅=0]" ] }, { @@ -34954,7 +34932,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 17.41blocks/s, ⧗=0, ▶=1, ✔=117, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=1, ✔=120, ✗=0, ∅=0]" ] }, { @@ -34976,7 +34954,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 54%|█████▍ | 117/216 [00:06<00:05, 17.41blocks/s, ⧗=0, ▶=0, ✔=118, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=0, ✔=121, ✗=0, ∅=0]" ] }, { @@ -34998,7 +34976,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 17.96blocks/s, ⧗=0, ▶=0, ✔=118, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=1, ✔=121, ✗=0, ∅=0]" ] }, { @@ -35020,7 +34998,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 17.96blocks/s, ⧗=0, ▶=1, ✔=118, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=0, ✔=122, ✗=0, ∅=0]" ] }, { @@ -35042,7 +35020,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▍ | 118/216 [00:06<00:05, 17.96blocks/s, ⧗=0, ▶=0, ✔=119, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=1, ✔=122, ✗=0, ∅=0]" ] }, { @@ -35064,7 +35042,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 17.96blocks/s, ⧗=0, ▶=1, ✔=119, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:04, 20.20blocks/s, ⧗=0, ▶=0, ✔=123, ✗=0, ∅=0]" ] }, { @@ -35086,7 +35064,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 55%|█████▌ | 119/216 [00:06<00:05, 17.96blocks/s, ⧗=0, ▶=0, ✔=120, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 19.78blocks/s, ⧗=0, ▶=0, ✔=123, ✗=0, ∅=0]" ] }, { @@ -35108,7 +35086,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:05, 17.96blocks/s, ⧗=0, ▶=1, ✔=120, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 19.78blocks/s, ⧗=0, ▶=1, ✔=123, ✗=0, ∅=0]" ] }, { @@ -35130,7 +35108,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:05, 18.51blocks/s, ⧗=0, ▶=1, ✔=120, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 19.78blocks/s, ⧗=0, ▶=0, ✔=124, ✗=0, ∅=0]" ] }, { @@ -35152,7 +35130,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 120/216 [00:06<00:05, 18.51blocks/s, ⧗=0, ▶=0, ✔=121, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:04, 19.78blocks/s, ⧗=0, ▶=1, ✔=124, ✗=0, ∅=0]" ] }, { @@ -35174,7 +35152,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:05, 18.51blocks/s, ⧗=0, ▶=1, ✔=121, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:04, 19.78blocks/s, ⧗=0, ▶=0, ✔=125, ✗=0, ∅=0]" ] }, { @@ -35196,7 +35174,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▌ | 121/216 [00:06<00:05, 18.51blocks/s, ⧗=0, ▶=0, ✔=122, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=0, ✔=125, ✗=0, ∅=0]" ] }, { @@ -35218,7 +35196,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:05, 18.75blocks/s, ⧗=0, ▶=0, ✔=122, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=1, ✔=125, ✗=0, ∅=0]" ] }, { @@ -35240,7 +35218,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:05, 18.75blocks/s, ⧗=0, ▶=1, ✔=122, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=0, ✔=126, ✗=0, ∅=0]" ] }, { @@ -35262,7 +35240,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 56%|█████▋ | 122/216 [00:06<00:05, 18.75blocks/s, ⧗=0, ▶=0, ✔=123, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=1, ✔=126, ✗=0, ∅=0]" ] }, { @@ -35284,7 +35262,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 18.75blocks/s, ⧗=0, ▶=1, ✔=123, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=0, ✔=127, ✗=0, ∅=0]" ] }, { @@ -35306,7 +35284,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 123/216 [00:06<00:04, 18.75blocks/s, ⧗=0, ▶=0, ✔=124, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=1, ✔=127, ✗=0, ∅=0]" ] }, { @@ -35328,7 +35306,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=0, ✔=124, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:06<00:04, 19.75blocks/s, ⧗=0, ▶=0, ✔=128, ✗=0, ∅=0]" ] }, { @@ -35350,7 +35328,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=1, ✔=124, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=0, ✔=128, ✗=0, ∅=0]" ] }, { @@ -35372,7 +35350,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 57%|█████▋ | 124/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=0, ✔=125, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=1, ✔=128, ✗=0, ∅=0]" ] }, { @@ -35394,7 +35372,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=1, ✔=125, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" ] }, { @@ -35416,7 +35394,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 125/216 [00:06<00:05, 17.64blocks/s, ⧗=0, ▶=0, ✔=126, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=1, ✔=129, ✗=0, ∅=0]" ] }, { @@ -35438,7 +35416,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:04, 18.09blocks/s, ⧗=0, ▶=0, ✔=126, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=0, ✔=130, ✗=0, ∅=0]" ] }, { @@ -35460,7 +35438,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:06<00:04, 18.09blocks/s, ⧗=0, ▶=1, ✔=126, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|██████ | 130/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=1, ✔=130, ✗=0, ∅=0]" ] }, { @@ -35482,7 +35460,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 58%|█████▊ | 126/216 [00:07<00:04, 18.09blocks/s, ⧗=0, ▶=0, ✔=127, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|██████ | 130/216 [00:06<00:04, 20.15blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" ] }, { @@ -35504,7 +35482,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:04, 18.09blocks/s, ⧗=0, ▶=1, ✔=127, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 131/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" ] }, { @@ -35526,7 +35504,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 127/216 [00:07<00:04, 18.09blocks/s, ⧗=0, ▶=0, ✔=128, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 131/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=1, ✔=131, ✗=0, ∅=0]" ] }, { @@ -35548,7 +35526,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:07<00:04, 18.09blocks/s, ⧗=0, ▶=1, ✔=128, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 131/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=0, ✔=132, ✗=0, ∅=0]" ] }, { @@ -35570,7 +35548,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 59%|█████▉ | 128/216 [00:07<00:04, 18.09blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 132/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=1, ✔=132, ✗=0, ∅=0]" ] }, { @@ -35592,7 +35570,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 18.88blocks/s, ⧗=0, ▶=0, ✔=129, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 132/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=0, ✔=133, ✗=0, ∅=0]" ] }, { @@ -35614,7 +35592,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 18.88blocks/s, ⧗=0, ▶=1, ✔=129, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=1, ✔=133, ✗=0, ∅=0]" ] }, { @@ -35636,7 +35614,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|█████▉ | 129/216 [00:07<00:04, 18.88blocks/s, ⧗=0, ▶=0, ✔=130, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:06<00:04, 19.35blocks/s, ⧗=0, ▶=0, ✔=134, ✗=0, ∅=0]" ] }, { @@ -35658,7 +35636,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|██████ | 130/216 [00:07<00:04, 18.88blocks/s, ⧗=0, ▶=1, ✔=130, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:06<00:04, 19.97blocks/s, ⧗=0, ▶=0, ✔=134, ✗=0, ∅=0]" ] }, { @@ -35680,7 +35658,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 60%|██████ | 130/216 [00:07<00:04, 18.88blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:06<00:04, 19.97blocks/s, ⧗=0, ▶=1, ✔=134, ✗=0, ∅=0]" ] }, { @@ -35702,7 +35680,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=0, ✔=131, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 19.97blocks/s, ⧗=0, ▶=0, ✔=135, ✗=0, ∅=0]" ] }, { @@ -35724,7 +35702,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=1, ✔=131, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 19.97blocks/s, ⧗=0, ▶=1, ✔=135, ✗=0, ∅=0]" ] }, { @@ -35746,7 +35724,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 131/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=0, ✔=132, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 19.97blocks/s, ⧗=0, ▶=0, ✔=136, ✗=0, ∅=0]" ] }, { @@ -35768,7 +35746,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 132/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=1, ✔=132, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 19.97blocks/s, ⧗=0, ▶=1, ✔=136, ✗=0, ∅=0]" ] }, { @@ -35790,7 +35768,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 61%|██████ | 132/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=0, ✔=133, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 19.97blocks/s, ⧗=0, ▶=0, ✔=137, ✗=0, ∅=0]" ] }, { @@ -35812,7 +35790,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=1, ✔=133, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=137, ✗=0, ∅=0]" ] }, { @@ -35834,7 +35812,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 133/216 [00:07<00:04, 18.96blocks/s, ⧗=0, ▶=0, ✔=134, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=137, ✗=0, ∅=0]" ] }, { @@ -35856,7 +35834,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 19.43blocks/s, ⧗=0, ▶=0, ✔=134, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=138, ✗=0, ∅=0]" ] }, { @@ -35878,7 +35856,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 19.43blocks/s, ⧗=0, ▶=1, ✔=134, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=1, ✔=138, ✗=0, ∅=0]" ] }, { @@ -35900,7 +35878,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▏ | 134/216 [00:07<00:04, 19.43blocks/s, ⧗=0, ▶=0, ✔=135, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 18.65blocks/s, ⧗=0, ▶=0, ✔=139, ✗=0, ∅=0]" ] }, { @@ -35922,7 +35900,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 19.43blocks/s, ⧗=0, ▶=1, ✔=135, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 18.80blocks/s, ⧗=0, ▶=0, ✔=139, ✗=0, ∅=0]" ] }, { @@ -35944,7 +35922,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 62%|██████▎ | 135/216 [00:07<00:04, 19.43blocks/s, ⧗=0, ▶=0, ✔=136, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 18.80blocks/s, ⧗=0, ▶=1, ✔=139, ✗=0, ∅=0]" ] }, { @@ -35966,7 +35944,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 19.14blocks/s, ⧗=0, ▶=0, ✔=136, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 18.80blocks/s, ⧗=0, ▶=0, ✔=140, ✗=0, ∅=0]" ] }, { @@ -35988,7 +35966,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 19.14blocks/s, ⧗=0, ▶=1, ✔=136, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:04, 18.80blocks/s, ⧗=0, ▶=1, ✔=140, ✗=0, ∅=0]" ] }, { @@ -36010,7 +35988,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 136/216 [00:07<00:04, 19.14blocks/s, ⧗=0, ▶=0, ✔=137, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:04, 18.80blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" ] }, { @@ -36032,7 +36010,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 19.14blocks/s, ⧗=0, ▶=1, ✔=137, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" ] }, { @@ -36054,7 +36032,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 63%|██████▎ | 137/216 [00:07<00:04, 19.14blocks/s, ⧗=0, ▶=0, ✔=138, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=1, ✔=141, ✗=0, ∅=0]" ] }, { @@ -36076,7 +36054,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 19.04blocks/s, ⧗=0, ▶=0, ✔=138, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=0, ✔=142, ✗=0, ∅=0]" ] }, { @@ -36098,7 +36076,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 19.04blocks/s, ⧗=0, ▶=1, ✔=138, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=1, ✔=142, ✗=0, ∅=0]" ] }, { @@ -36120,7 +36098,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 138/216 [00:07<00:04, 19.04blocks/s, ⧗=0, ▶=0, ✔=139, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" ] }, { @@ -36142,7 +36120,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 19.04blocks/s, ⧗=0, ▶=1, ✔=139, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=1, ✔=143, ✗=0, ∅=0]" ] }, { @@ -36164,7 +36142,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 64%|██████▍ | 139/216 [00:07<00:04, 19.04blocks/s, ⧗=0, ▶=0, ✔=140, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.03blocks/s, ⧗=0, ▶=0, ✔=144, ✗=0, ∅=0]" ] }, { @@ -36186,7 +36164,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:03, 19.04blocks/s, ⧗=0, ▶=1, ✔=140, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.69blocks/s, ⧗=0, ▶=0, ✔=144, ✗=0, ∅=0]" ] }, { @@ -36208,7 +36186,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▍ | 140/216 [00:07<00:03, 19.04blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.69blocks/s, ⧗=0, ▶=1, ✔=144, ✗=0, ∅=0]" ] }, { @@ -36230,7 +36208,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.36blocks/s, ⧗=0, ▶=0, ✔=141, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.69blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" ] }, { @@ -36252,7 +36230,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.36blocks/s, ⧗=0, ▶=1, ✔=141, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.69blocks/s, ⧗=0, ▶=1, ✔=145, ✗=0, ∅=0]" ] }, { @@ -36274,7 +36252,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 65%|██████▌ | 141/216 [00:07<00:03, 19.36blocks/s, ⧗=0, ▶=0, ✔=142, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.69blocks/s, ⧗=0, ▶=0, ✔=146, ✗=0, ∅=0]" ] }, { @@ -36296,7 +36274,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 19.36blocks/s, ⧗=0, ▶=1, ✔=142, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:07<00:03, 19.70blocks/s, ⧗=0, ▶=0, ✔=146, ✗=0, ∅=0]" ] }, { @@ -36318,7 +36296,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 142/216 [00:07<00:03, 19.36blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:07<00:03, 19.70blocks/s, ⧗=0, ▶=1, ✔=146, ✗=0, ∅=0]" ] }, { @@ -36340,7 +36318,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.51blocks/s, ⧗=0, ▶=0, ✔=143, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:07<00:03, 19.70blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" ] }, { @@ -36362,7 +36340,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.51blocks/s, ⧗=0, ▶=1, ✔=143, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:07<00:03, 19.70blocks/s, ⧗=0, ▶=1, ✔=147, ✗=0, ∅=0]" ] }, { @@ -36384,7 +36362,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 66%|██████▌ | 143/216 [00:07<00:03, 19.51blocks/s, ⧗=0, ▶=0, ✔=144, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:07<00:03, 19.70blocks/s, ⧗=0, ▶=0, ✔=148, ✗=0, ∅=0]" ] }, { @@ -36406,7 +36384,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.51blocks/s, ⧗=0, ▶=1, ✔=144, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:07<00:03, 19.28blocks/s, ⧗=0, ▶=0, ✔=148, ✗=0, ∅=0]" ] }, { @@ -36428,7 +36406,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 144/216 [00:07<00:03, 19.51blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:07<00:03, 19.28blocks/s, ⧗=0, ▶=1, ✔=148, ✗=0, ∅=0]" ] }, { @@ -36450,7 +36428,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.57blocks/s, ⧗=0, ▶=0, ✔=145, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:07<00:03, 19.28blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" ] }, { @@ -36472,7 +36450,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:07<00:03, 19.57blocks/s, ⧗=0, ▶=1, ✔=145, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:07<00:03, 19.28blocks/s, ⧗=0, ▶=1, ✔=149, ✗=0, ∅=0]" ] }, { @@ -36494,7 +36472,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 67%|██████▋ | 145/216 [00:08<00:03, 19.57blocks/s, ⧗=0, ▶=0, ✔=146, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:07<00:03, 19.28blocks/s, ⧗=0, ▶=0, ✔=150, ✗=0, ∅=0]" ] }, { @@ -36516,7 +36494,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:08<00:03, 19.57blocks/s, ⧗=0, ▶=1, ✔=146, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:07<00:03, 18.09blocks/s, ⧗=0, ▶=0, ✔=150, ✗=0, ∅=0]" ] }, { @@ -36538,7 +36516,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 146/216 [00:08<00:03, 19.57blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:07<00:03, 18.09blocks/s, ⧗=0, ▶=1, ✔=150, ✗=0, ∅=0]" ] }, { @@ -36560,7 +36538,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 18.95blocks/s, ⧗=0, ▶=0, ✔=147, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:07<00:03, 18.09blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" ] }, { @@ -36582,7 +36560,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 18.95blocks/s, ⧗=0, ▶=1, ✔=147, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:07<00:03, 18.09blocks/s, ⧗=0, ▶=1, ✔=151, ✗=0, ∅=0]" ] }, { @@ -36604,7 +36582,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 68%|██████▊ | 147/216 [00:08<00:03, 18.95blocks/s, ⧗=0, ▶=0, ✔=148, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:07<00:03, 18.09blocks/s, ⧗=0, ▶=0, ✔=152, ✗=0, ∅=0]" ] }, { @@ -36626,7 +36604,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:08<00:03, 18.95blocks/s, ⧗=0, ▶=1, ✔=148, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|███████ | 152/216 [00:07<00:03, 18.12blocks/s, ⧗=0, ▶=0, ✔=152, ✗=0, ∅=0]" ] }, { @@ -36648,7 +36626,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▊ | 148/216 [00:08<00:03, 18.95blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|███████ | 152/216 [00:07<00:03, 18.12blocks/s, ⧗=0, ▶=1, ✔=152, ✗=0, ∅=0]" ] }, { @@ -36670,7 +36648,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 18.79blocks/s, ⧗=0, ▶=0, ✔=149, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 18.12blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" ] }, { @@ -36692,7 +36670,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 18.79blocks/s, ⧗=0, ▶=1, ✔=149, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 18.12blocks/s, ⧗=0, ▶=1, ✔=153, ✗=0, ∅=0]" ] }, { @@ -36714,7 +36692,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 149/216 [00:08<00:03, 18.79blocks/s, ⧗=0, ▶=0, ✔=150, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 18.12blocks/s, ⧗=0, ▶=0, ✔=154, ✗=0, ∅=0]" ] }, { @@ -36736,7 +36714,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:08<00:03, 18.79blocks/s, ⧗=0, ▶=1, ✔=150, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.18blocks/s, ⧗=0, ▶=0, ✔=154, ✗=0, ∅=0]" ] }, { @@ -36758,7 +36736,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 69%|██████▉ | 150/216 [00:08<00:03, 18.79blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.18blocks/s, ⧗=0, ▶=1, ✔=154, ✗=0, ∅=0]" ] }, { @@ -36780,7 +36758,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 18.56blocks/s, ⧗=0, ▶=0, ✔=151, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.18blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" ] }, { @@ -36802,7 +36780,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 18.56blocks/s, ⧗=0, ▶=1, ✔=151, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.18blocks/s, ⧗=0, ▶=1, ✔=155, ✗=0, ∅=0]" ] }, { @@ -36824,7 +36802,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|██████▉ | 151/216 [00:08<00:03, 18.56blocks/s, ⧗=0, ▶=0, ✔=152, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.18blocks/s, ⧗=0, ▶=0, ✔=156, ✗=0, ∅=0]" ] }, { @@ -36846,7 +36824,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 18.56blocks/s, ⧗=0, ▶=1, ✔=152, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.26blocks/s, ⧗=0, ▶=0, ✔=156, ✗=0, ∅=0]" ] }, { @@ -36868,7 +36846,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 70%|███████ | 152/216 [00:08<00:03, 18.56blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.26blocks/s, ⧗=0, ▶=1, ✔=156, ✗=0, ∅=0]" ] }, { @@ -36890,7 +36868,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 17.98blocks/s, ⧗=0, ▶=0, ✔=153, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.26blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" ] }, { @@ -36912,7 +36890,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 17.98blocks/s, ⧗=0, ▶=1, ✔=153, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.26blocks/s, ⧗=0, ▶=1, ✔=157, ✗=0, ∅=0]" ] }, { @@ -36934,7 +36912,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████ | 153/216 [00:08<00:03, 17.98blocks/s, ⧗=0, ▶=0, ✔=154, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.26blocks/s, ⧗=0, ▶=0, ✔=158, ✗=0, ∅=0]" ] }, { @@ -36956,7 +36934,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.98blocks/s, ⧗=0, ▶=1, ✔=154, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 16.96blocks/s, ⧗=0, ▶=0, ✔=158, ✗=0, ∅=0]" ] }, { @@ -36978,7 +36956,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 71%|███████▏ | 154/216 [00:08<00:03, 17.98blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 16.96blocks/s, ⧗=0, ▶=1, ✔=158, ✗=0, ∅=0]" ] }, { @@ -37000,7 +36978,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.04blocks/s, ⧗=0, ▶=0, ✔=155, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 16.96blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" ] }, { @@ -37022,7 +37000,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.04blocks/s, ⧗=0, ▶=1, ✔=155, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.96blocks/s, ⧗=0, ▶=1, ✔=159, ✗=0, ∅=0]" ] }, { @@ -37044,7 +37022,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 155/216 [00:08<00:03, 17.04blocks/s, ⧗=0, ▶=0, ✔=156, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.96blocks/s, ⧗=0, ▶=0, ✔=160, ✗=0, ∅=0]" ] }, { @@ -37066,7 +37044,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.04blocks/s, ⧗=0, ▶=1, ✔=156, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.09blocks/s, ⧗=0, ▶=0, ✔=160, ✗=0, ∅=0]" ] }, { @@ -37088,7 +37066,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 72%|███████▏ | 156/216 [00:08<00:03, 17.04blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.09blocks/s, ⧗=0, ▶=1, ✔=160, ✗=0, ∅=0]" ] }, { @@ -37110,7 +37088,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.09blocks/s, ⧗=0, ▶=0, ✔=157, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.09blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" ] }, { @@ -37132,7 +37110,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.09blocks/s, ⧗=0, ▶=1, ✔=157, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 16.09blocks/s, ⧗=0, ▶=1, ✔=161, ✗=0, ∅=0]" ] }, { @@ -37154,7 +37132,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 157/216 [00:08<00:03, 17.09blocks/s, ⧗=0, ▶=0, ✔=158, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 16.09blocks/s, ⧗=0, ▶=0, ✔=162, ✗=0, ∅=0]" ] }, { @@ -37176,7 +37154,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 17.09blocks/s, ⧗=0, ▶=1, ✔=158, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:08<00:03, 15.55blocks/s, ⧗=0, ▶=0, ✔=162, ✗=0, ∅=0]" ] }, { @@ -37198,7 +37176,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 73%|███████▎ | 158/216 [00:08<00:03, 17.09blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:08<00:03, 15.55blocks/s, ⧗=0, ▶=1, ✔=162, ✗=0, ∅=0]" ] }, { @@ -37220,7 +37198,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.05blocks/s, ⧗=0, ▶=0, ✔=159, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:08<00:03, 15.55blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" ] }, { @@ -37242,7 +37220,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.05blocks/s, ⧗=0, ▶=1, ✔=159, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:08<00:03, 15.55blocks/s, ⧗=0, ▶=1, ✔=163, ✗=0, ∅=0]" ] }, { @@ -37264,7 +37242,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▎ | 159/216 [00:08<00:03, 16.05blocks/s, ⧗=0, ▶=0, ✔=160, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:08<00:03, 15.55blocks/s, ⧗=0, ▶=0, ✔=164, ✗=0, ∅=0]" ] }, { @@ -37286,7 +37264,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.05blocks/s, ⧗=0, ▶=1, ✔=160, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:08<00:03, 15.87blocks/s, ⧗=0, ▶=0, ✔=164, ✗=0, ∅=0]" ] }, { @@ -37308,7 +37286,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 74%|███████▍ | 160/216 [00:08<00:03, 16.05blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:08<00:03, 15.87blocks/s, ⧗=0, ▶=1, ✔=164, ✗=0, ∅=0]" ] }, { @@ -37330,7 +37308,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 15.78blocks/s, ⧗=0, ▶=0, ✔=161, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:08<00:03, 15.87blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" ] }, { @@ -37352,7 +37330,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 15.78blocks/s, ⧗=0, ▶=1, ✔=161, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:08<00:03, 15.87blocks/s, ⧗=0, ▶=1, ✔=165, ✗=0, ∅=0]" ] }, { @@ -37374,7 +37352,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▍ | 161/216 [00:08<00:03, 15.78blocks/s, ⧗=0, ▶=0, ✔=162, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:08<00:03, 15.87blocks/s, ⧗=0, ▶=0, ✔=166, ✗=0, ∅=0]" ] }, { @@ -37396,7 +37374,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:09<00:03, 15.78blocks/s, ⧗=0, ▶=1, ✔=162, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:08<00:03, 16.35blocks/s, ⧗=0, ▶=0, ✔=166, ✗=0, ∅=0]" ] }, { @@ -37418,7 +37396,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 162/216 [00:09<00:03, 15.78blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:08<00:03, 16.35blocks/s, ⧗=0, ▶=1, ✔=166, ✗=0, ∅=0]" ] }, { @@ -37440,7 +37418,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=0, ✔=163, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:08<00:03, 16.35blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" ] }, { @@ -37462,7 +37440,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=1, ✔=163, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:08<00:02, 16.35blocks/s, ⧗=0, ▶=1, ✔=167, ✗=0, ∅=0]" ] }, { @@ -37484,7 +37462,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 75%|███████▌ | 163/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=0, ✔=164, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:08<00:02, 16.35blocks/s, ⧗=0, ▶=0, ✔=168, ✗=0, ∅=0]" ] }, { @@ -37506,7 +37484,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=1, ✔=164, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:08<00:02, 17.09blocks/s, ⧗=0, ▶=0, ✔=168, ✗=0, ∅=0]" ] }, { @@ -37528,7 +37506,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▌ | 164/216 [00:09<00:03, 15.96blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:08<00:02, 17.09blocks/s, ⧗=0, ▶=1, ✔=168, ✗=0, ∅=0]" ] }, { @@ -37550,7 +37528,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:03, 15.68blocks/s, ⧗=0, ▶=0, ✔=165, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 17.09blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" ] }, { @@ -37572,7 +37550,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:03, 15.68blocks/s, ⧗=0, ▶=1, ✔=165, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 17.09blocks/s, ⧗=0, ▶=1, ✔=169, ✗=0, ∅=0]" ] }, { @@ -37594,7 +37572,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 76%|███████▋ | 165/216 [00:09<00:03, 15.68blocks/s, ⧗=0, ▶=0, ✔=166, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 17.09blocks/s, ⧗=0, ▶=0, ✔=170, ✗=0, ∅=0]" ] }, { @@ -37616,7 +37594,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:09<00:03, 15.68blocks/s, ⧗=0, ▶=1, ✔=166, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 17.51blocks/s, ⧗=0, ▶=0, ✔=170, ✗=0, ∅=0]" ] }, { @@ -37638,7 +37616,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 166/216 [00:09<00:03, 15.68blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 17.51blocks/s, ⧗=0, ▶=1, ✔=170, ✗=0, ∅=0]" ] }, { @@ -37660,7 +37638,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:03, 16.16blocks/s, ⧗=0, ▶=0, ✔=167, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 17.51blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" ] }, { @@ -37682,7 +37660,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:03, 16.16blocks/s, ⧗=0, ▶=1, ✔=167, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 17.51blocks/s, ⧗=0, ▶=1, ✔=171, ✗=0, ∅=0]" ] }, { @@ -37704,7 +37682,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 77%|███████▋ | 167/216 [00:09<00:03, 16.16blocks/s, ⧗=0, ▶=0, ✔=168, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 17.51blocks/s, ⧗=0, ▶=0, ✔=172, ✗=0, ∅=0]" ] }, { @@ -37726,7 +37704,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 16.16blocks/s, ⧗=0, ▶=1, ✔=168, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.78blocks/s, ⧗=0, ▶=0, ✔=172, ✗=0, ∅=0]" ] }, { @@ -37748,7 +37726,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 168/216 [00:09<00:02, 16.16blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.78blocks/s, ⧗=0, ▶=1, ✔=172, ✗=0, ∅=0]" ] }, { @@ -37770,7 +37748,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 16.81blocks/s, ⧗=0, ▶=0, ✔=169, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.78blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" ] }, { @@ -37792,7 +37770,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 16.81blocks/s, ⧗=0, ▶=1, ✔=169, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.78blocks/s, ⧗=0, ▶=1, ✔=173, ✗=0, ∅=0]" ] }, { @@ -37814,7 +37792,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 78%|███████▊ | 169/216 [00:09<00:02, 16.81blocks/s, ⧗=0, ▶=0, ✔=170, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.78blocks/s, ⧗=0, ▶=0, ✔=174, ✗=0, ∅=0]" ] }, { @@ -37836,7 +37814,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 16.81blocks/s, ⧗=0, ▶=1, ✔=170, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.67blocks/s, ⧗=0, ▶=0, ✔=174, ✗=0, ∅=0]" ] }, { @@ -37858,7 +37836,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▊ | 170/216 [00:09<00:02, 16.81blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.67blocks/s, ⧗=0, ▶=1, ✔=174, ✗=0, ∅=0]" ] }, { @@ -37880,7 +37858,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 16.12blocks/s, ⧗=0, ▶=0, ✔=171, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.67blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" ] }, { @@ -37902,7 +37880,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 16.12blocks/s, ⧗=0, ▶=1, ✔=171, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 16.67blocks/s, ⧗=0, ▶=1, ✔=175, ✗=0, ∅=0]" ] }, { @@ -37924,7 +37902,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 79%|███████▉ | 171/216 [00:09<00:02, 16.12blocks/s, ⧗=0, ▶=0, ✔=172, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 16.67blocks/s, ⧗=0, ▶=0, ✔=176, ✗=0, ∅=0]" ] }, { @@ -37946,7 +37924,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.12blocks/s, ⧗=0, ▶=1, ✔=172, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 17.24blocks/s, ⧗=0, ▶=0, ✔=176, ✗=0, ∅=0]" ] }, { @@ -37968,7 +37946,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|███████▉ | 172/216 [00:09<00:02, 16.12blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 17.24blocks/s, ⧗=0, ▶=1, ✔=176, ✗=0, ∅=0]" ] }, { @@ -37990,7 +37968,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.01blocks/s, ⧗=0, ▶=0, ✔=173, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 17.24blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" ] }, { @@ -38012,7 +37990,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.01blocks/s, ⧗=0, ▶=1, ✔=173, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 17.24blocks/s, ⧗=0, ▶=1, ✔=177, ✗=0, ∅=0]" ] }, { @@ -38034,7 +38012,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 80%|████████ | 173/216 [00:09<00:02, 16.01blocks/s, ⧗=0, ▶=0, ✔=174, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 17.24blocks/s, ⧗=0, ▶=0, ✔=178, ✗=0, ∅=0]" ] }, { @@ -38056,7 +38034,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.01blocks/s, ⧗=0, ▶=1, ✔=174, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 17.19blocks/s, ⧗=0, ▶=0, ✔=178, ✗=0, ∅=0]" ] }, { @@ -38078,7 +38056,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 174/216 [00:09<00:02, 16.01blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 17.19blocks/s, ⧗=0, ▶=1, ✔=178, ✗=0, ∅=0]" ] }, { @@ -38100,7 +38078,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=0, ✔=175, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 17.19blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" ] }, { @@ -38122,7 +38100,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=1, ✔=175, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:09<00:02, 17.19blocks/s, ⧗=0, ▶=1, ✔=179, ✗=0, ∅=0]" ] }, { @@ -38144,7 +38122,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████ | 175/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=0, ✔=176, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:09<00:02, 17.19blocks/s, ⧗=0, ▶=0, ✔=180, ✗=0, ∅=0]" ] }, { @@ -38166,7 +38144,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=1, ✔=176, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:09<00:02, 17.62blocks/s, ⧗=0, ▶=0, ✔=180, ✗=0, ∅=0]" ] }, { @@ -38188,7 +38166,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 81%|████████▏ | 176/216 [00:09<00:02, 16.43blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:09<00:02, 17.62blocks/s, ⧗=0, ▶=1, ✔=180, ✗=0, ∅=0]" ] }, { @@ -38210,7 +38188,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 15.95blocks/s, ⧗=0, ▶=0, ✔=177, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:09<00:02, 17.62blocks/s, ⧗=0, ▶=0, ✔=181, ✗=0, ∅=0]" ] }, { @@ -38232,7 +38210,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 15.95blocks/s, ⧗=0, ▶=1, ✔=177, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:09<00:01, 17.62blocks/s, ⧗=0, ▶=1, ✔=181, ✗=0, ∅=0]" ] }, { @@ -38254,7 +38232,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 177/216 [00:09<00:02, 15.95blocks/s, ⧗=0, ▶=0, ✔=178, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:09<00:01, 17.62blocks/s, ⧗=0, ▶=0, ✔=182, ✗=0, ∅=0]" ] }, { @@ -38276,7 +38254,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:09<00:02, 15.95blocks/s, ⧗=0, ▶=1, ✔=178, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:09<00:01, 17.62blocks/s, ⧗=0, ▶=1, ✔=182, ✗=0, ∅=0]" ] }, { @@ -38298,7 +38276,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 82%|████████▏ | 178/216 [00:10<00:02, 15.95blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:09<00:01, 17.62blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" ] }, { @@ -38320,7 +38298,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:10<00:02, 16.44blocks/s, ⧗=0, ▶=0, ✔=179, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" ] }, { @@ -38342,7 +38320,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:10<00:02, 16.44blocks/s, ⧗=0, ▶=1, ✔=179, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=1, ✔=183, ✗=0, ∅=0]" ] }, { @@ -38364,7 +38342,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 179/216 [00:10<00:02, 16.44blocks/s, ⧗=0, ▶=0, ✔=180, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=0, ✔=184, ✗=0, ∅=0]" ] }, { @@ -38386,7 +38364,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:10<00:02, 16.44blocks/s, ⧗=0, ▶=1, ✔=180, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=1, ✔=184, ✗=0, ∅=0]" ] }, { @@ -38408,7 +38386,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 83%|████████▎ | 180/216 [00:10<00:02, 16.44blocks/s, ⧗=0, ▶=0, ✔=181, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=0, ✔=185, ✗=0, ∅=0]" ] }, { @@ -38430,7 +38408,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:02, 16.37blocks/s, ⧗=0, ▶=0, ✔=181, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=1, ✔=185, ✗=0, ∅=0]" ] }, { @@ -38452,7 +38430,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:02, 16.37blocks/s, ⧗=0, ▶=1, ✔=181, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:09<00:01, 18.56blocks/s, ⧗=0, ▶=0, ✔=186, ✗=0, ∅=0]" ] }, { @@ -38474,7 +38452,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 181/216 [00:10<00:02, 16.37blocks/s, ⧗=0, ▶=0, ✔=182, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:09<00:01, 19.46blocks/s, ⧗=0, ▶=0, ✔=186, ✗=0, ∅=0]" ] }, { @@ -38496,7 +38474,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:02, 16.37blocks/s, ⧗=0, ▶=1, ✔=182, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:09<00:01, 19.46blocks/s, ⧗=0, ▶=1, ✔=186, ✗=0, ∅=0]" ] }, { @@ -38518,7 +38496,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 84%|████████▍ | 182/216 [00:10<00:02, 16.37blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:09<00:01, 19.46blocks/s, ⧗=0, ▶=0, ✔=187, ✗=0, ∅=0]" ] }, { @@ -38540,7 +38518,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 17.17blocks/s, ⧗=0, ▶=0, ✔=183, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:09<00:01, 19.46blocks/s, ⧗=0, ▶=1, ✔=187, ✗=0, ∅=0]" ] }, { @@ -38562,7 +38540,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 17.17blocks/s, ⧗=0, ▶=1, ✔=183, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 19.46blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" ] }, { @@ -38584,7 +38562,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▍ | 183/216 [00:10<00:01, 17.17blocks/s, ⧗=0, ▶=0, ✔=184, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 19.20blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" ] }, { @@ -38606,7 +38584,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 17.17blocks/s, ⧗=0, ▶=1, ✔=184, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 19.20blocks/s, ⧗=0, ▶=1, ✔=188, ✗=0, ∅=0]" ] }, { @@ -38628,7 +38606,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 85%|████████▌ | 184/216 [00:10<00:01, 17.17blocks/s, ⧗=0, ▶=0, ✔=185, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 19.20blocks/s, ⧗=0, ▶=0, ✔=189, ✗=0, ∅=0]" ] }, { @@ -38650,7 +38628,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=0, ✔=185, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 19.20blocks/s, ⧗=0, ▶=1, ✔=189, ✗=0, ∅=0]" ] }, { @@ -38672,7 +38650,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=1, ✔=185, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 19.20blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" ] }, { @@ -38694,7 +38672,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 185/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=0, ✔=186, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 18.96blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" ] }, { @@ -38716,7 +38694,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=1, ✔=186, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 18.96blocks/s, ⧗=0, ▶=1, ✔=190, ✗=0, ∅=0]" ] }, { @@ -38738,7 +38716,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 86%|████████▌ | 186/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=0, ✔=187, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 18.96blocks/s, ⧗=0, ▶=0, ✔=191, ✗=0, ∅=0]" ] }, { @@ -38760,7 +38738,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=1, ✔=187, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 18.96blocks/s, ⧗=0, ▶=1, ✔=191, ✗=0, ∅=0]" ] }, { @@ -38782,7 +38760,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 187/216 [00:10<00:01, 17.31blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 18.96blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" ] }, { @@ -38804,7 +38782,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=0, ✔=188, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.76blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" ] }, { @@ -38826,7 +38804,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=1, ✔=188, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.76blocks/s, ⧗=0, ▶=1, ✔=192, ✗=0, ∅=0]" ] }, { @@ -38848,7 +38826,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 87%|████████▋ | 188/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=0, ✔=189, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.76blocks/s, ⧗=0, ▶=0, ✔=193, ✗=0, ∅=0]" ] }, { @@ -38870,7 +38848,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=1, ✔=189, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.76blocks/s, ⧗=0, ▶=1, ✔=193, ✗=0, ∅=0]" ] }, { @@ -38892,7 +38870,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 189/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.76blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" ] }, { @@ -38914,7 +38892,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 17.96blocks/s, ⧗=0, ▶=0, ✔=190, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.67blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" ] }, { @@ -38936,7 +38914,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 17.96blocks/s, ⧗=0, ▶=1, ✔=190, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.67blocks/s, ⧗=0, ▶=1, ✔=194, ✗=0, ∅=0]" ] }, { @@ -38958,7 +38936,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 190/216 [00:10<00:01, 17.96blocks/s, ⧗=0, ▶=0, ✔=191, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.67blocks/s, ⧗=0, ▶=0, ✔=195, ✗=0, ∅=0]" ] }, { @@ -38980,7 +38958,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 17.96blocks/s, ⧗=0, ▶=1, ✔=191, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:10<00:01, 18.67blocks/s, ⧗=0, ▶=1, ✔=195, ✗=0, ∅=0]" ] }, { @@ -39002,7 +38980,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 88%|████████▊ | 191/216 [00:10<00:01, 17.96blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:10<00:01, 18.67blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" ] }, { @@ -39024,7 +39002,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=0, ✔=192, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 18.03blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" ] }, { @@ -39046,7 +39024,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=1, ✔=192, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 18.03blocks/s, ⧗=0, ▶=1, ✔=196, ✗=0, ∅=0]" ] }, { @@ -39068,7 +39046,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 192/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=0, ✔=193, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 18.03blocks/s, ⧗=0, ▶=0, ✔=197, ✗=0, ∅=0]" ] }, { @@ -39090,7 +39068,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=1, ✔=193, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:10<00:01, 18.03blocks/s, ⧗=0, ▶=1, ✔=197, ✗=0, ∅=0]" ] }, { @@ -39112,7 +39090,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 89%|████████▉ | 193/216 [00:10<00:01, 18.39blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:10<00:01, 18.03blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" ] }, { @@ -39134,7 +39112,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.18blocks/s, ⧗=0, ▶=0, ✔=194, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:10<00:01, 17.57blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" ] }, { @@ -39156,7 +39134,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.18blocks/s, ⧗=0, ▶=1, ✔=194, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:10<00:01, 17.57blocks/s, ⧗=0, ▶=1, ✔=198, ✗=0, ∅=0]" ] }, { @@ -39178,7 +39156,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|████████▉ | 194/216 [00:10<00:01, 18.18blocks/s, ⧗=0, ▶=0, ✔=195, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:10<00:01, 17.57blocks/s, ⧗=0, ▶=0, ✔=199, ✗=0, ∅=0]" ] }, { @@ -39200,7 +39178,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:10<00:01, 18.18blocks/s, ⧗=0, ▶=1, ✔=195, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:10<00:00, 17.57blocks/s, ⧗=0, ▶=1, ✔=199, ✗=0, ∅=0]" ] }, { @@ -39222,7 +39200,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 90%|█████████ | 195/216 [00:10<00:01, 18.18blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:10<00:00, 17.57blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" ] }, { @@ -39244,7 +39222,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 16.94blocks/s, ⧗=0, ▶=0, ✔=196, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:10<00:00, 18.14blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" ] }, { @@ -39266,7 +39244,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:10<00:01, 16.94blocks/s, ⧗=0, ▶=1, ✔=196, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:10<00:00, 18.14blocks/s, ⧗=0, ▶=1, ✔=200, ✗=0, ∅=0]" ] }, { @@ -39288,7 +39266,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 196/216 [00:11<00:01, 16.94blocks/s, ⧗=0, ▶=0, ✔=197, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:10<00:00, 18.14blocks/s, ⧗=0, ▶=0, ✔=201, ✗=0, ∅=0]" ] }, { @@ -39310,7 +39288,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:11<00:01, 16.94blocks/s, ⧗=0, ▶=1, ✔=197, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:10<00:00, 18.14blocks/s, ⧗=0, ▶=1, ✔=201, ✗=0, ∅=0]" ] }, { @@ -39332,7 +39310,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 91%|█████████ | 197/216 [00:11<00:01, 16.94blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:10<00:00, 18.14blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" ] }, { @@ -39354,7 +39332,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 17.18blocks/s, ⧗=0, ▶=0, ✔=198, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:10<00:00, 17.82blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" ] }, { @@ -39376,7 +39354,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 17.18blocks/s, ⧗=0, ▶=1, ✔=198, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:10<00:00, 17.82blocks/s, ⧗=0, ▶=1, ✔=202, ✗=0, ∅=0]" ] }, { @@ -39398,7 +39376,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 198/216 [00:11<00:01, 17.18blocks/s, ⧗=0, ▶=0, ✔=199, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:10<00:00, 17.82blocks/s, ⧗=0, ▶=0, ✔=203, ✗=0, ∅=0]" ] }, { @@ -39420,7 +39398,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:11<00:00, 17.18blocks/s, ⧗=0, ▶=1, ✔=199, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:10<00:00, 17.82blocks/s, ⧗=0, ▶=1, ✔=203, ✗=0, ∅=0]" ] }, { @@ -39442,7 +39420,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 92%|█████████▏| 199/216 [00:11<00:00, 17.18blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:10<00:00, 17.82blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" ] }, { @@ -39464,7 +39442,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:00, 16.80blocks/s, ⧗=0, ▶=0, ✔=200, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:10<00:00, 17.82blocks/s, ⧗=0, ▶=1, ✔=204, ✗=0, ∅=0]" ] }, { @@ -39486,7 +39464,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:00, 16.80blocks/s, ⧗=0, ▶=1, ✔=200, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:10<00:00, 18.36blocks/s, ⧗=0, ▶=1, ✔=204, ✗=0, ∅=0]" ] }, { @@ -39508,7 +39486,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 200/216 [00:11<00:00, 16.80blocks/s, ⧗=0, ▶=0, ✔=201, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:10<00:00, 18.36blocks/s, ⧗=0, ▶=0, ✔=205, ✗=0, ∅=0]" ] }, { @@ -39530,7 +39508,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:11<00:00, 16.80blocks/s, ⧗=0, ▶=1, ✔=201, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:10<00:00, 18.36blocks/s, ⧗=0, ▶=1, ✔=205, ✗=0, ∅=0]" ] }, { @@ -39552,7 +39530,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 93%|█████████▎| 201/216 [00:11<00:00, 16.80blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 18.36blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" ] }, { @@ -39574,7 +39552,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 16.51blocks/s, ⧗=0, ▶=0, ✔=202, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 18.36blocks/s, ⧗=0, ▶=1, ✔=206, ✗=0, ∅=0]" ] }, { @@ -39596,7 +39574,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 16.51blocks/s, ⧗=0, ▶=1, ✔=202, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 18.36blocks/s, ⧗=0, ▶=0, ✔=207, ✗=0, ∅=0]" ] }, { @@ -39618,7 +39596,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▎| 202/216 [00:11<00:00, 16.51blocks/s, ⧗=0, ▶=0, ✔=203, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 18.77blocks/s, ⧗=0, ▶=0, ✔=207, ✗=0, ∅=0]" ] }, { @@ -39640,7 +39618,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:11<00:00, 16.51blocks/s, ⧗=0, ▶=1, ✔=203, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 18.77blocks/s, ⧗=0, ▶=1, ✔=207, ✗=0, ∅=0]" ] }, { @@ -39662,7 +39640,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 203/216 [00:11<00:00, 16.51blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 18.77blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" ] }, { @@ -39684,7 +39662,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 17.31blocks/s, ⧗=0, ▶=0, ✔=204, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 18.77blocks/s, ⧗=0, ▶=1, ✔=208, ✗=0, ∅=0]" ] }, { @@ -39706,7 +39684,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 17.31blocks/s, ⧗=0, ▶=1, ✔=204, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 18.77blocks/s, ⧗=0, ▶=0, ✔=209, ✗=0, ∅=0]" ] }, { @@ -39728,7 +39706,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 94%|█████████▍| 204/216 [00:11<00:00, 17.31blocks/s, ⧗=0, ▶=0, ✔=205, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 18.64blocks/s, ⧗=0, ▶=0, ✔=209, ✗=0, ∅=0]" ] }, { @@ -39750,7 +39728,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 17.31blocks/s, ⧗=0, ▶=1, ✔=205, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 18.64blocks/s, ⧗=0, ▶=1, ✔=209, ✗=0, ∅=0]" ] }, { @@ -39772,7 +39750,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▍| 205/216 [00:11<00:00, 17.31blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 18.64blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" ] }, { @@ -39794,7 +39772,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=0, ✔=206, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 18.64blocks/s, ⧗=0, ▶=1, ✔=210, ✗=0, ∅=0]" ] }, { @@ -39816,7 +39794,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=1, ✔=206, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 18.64blocks/s, ⧗=0, ▶=0, ✔=211, ✗=0, ∅=0]" ] }, { @@ -39838,7 +39816,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 95%|█████████▌| 206/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=0, ✔=207, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 17.65blocks/s, ⧗=0, ▶=0, ✔=211, ✗=0, ∅=0]" ] }, { @@ -39860,7 +39838,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=1, ✔=207, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 17.65blocks/s, ⧗=0, ▶=1, ✔=211, ✗=0, ∅=0]" ] }, { @@ -39882,7 +39860,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▌| 207/216 [00:11<00:00, 17.87blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 17.65blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" ] }, { @@ -39904,7 +39882,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 17.96blocks/s, ⧗=0, ▶=0, ✔=208, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 17.65blocks/s, ⧗=0, ▶=1, ✔=212, ✗=0, ∅=0]" ] }, { @@ -39926,7 +39904,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 17.96blocks/s, ⧗=0, ▶=1, ✔=208, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 17.65blocks/s, ⧗=0, ▶=0, ✔=213, ✗=0, ∅=0]" ] }, { @@ -39948,7 +39926,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 96%|█████████▋| 208/216 [00:11<00:00, 17.96blocks/s, ⧗=0, ▶=0, ✔=209, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=0, ✔=213, ✗=0, ∅=0]" ] }, { @@ -39970,7 +39948,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 17.96blocks/s, ⧗=0, ▶=1, ✔=209, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=1, ✔=213, ✗=0, ∅=0]" ] }, { @@ -39992,7 +39970,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 209/216 [00:11<00:00, 17.96blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" ] }, { @@ -40014,7 +39992,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 18.29blocks/s, ⧗=0, ▶=0, ✔=210, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=1, ✔=214, ✗=0, ∅=0]" ] }, { @@ -40036,7 +40014,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 18.29blocks/s, ⧗=0, ▶=1, ✔=210, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=0, ✔=215, ✗=0, ∅=0]" ] }, { @@ -40058,7 +40036,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 97%|█████████▋| 210/216 [00:11<00:00, 18.29blocks/s, ⧗=0, ▶=0, ✔=211, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=1, ✔=215, ✗=0, ∅=0]" ] }, { @@ -40080,7 +40058,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 18.29blocks/s, ⧗=0, ▶=1, ✔=211, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:11<00:00, 17.26blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -40102,7 +40080,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 211/216 [00:11<00:00, 18.29blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 100%|██████████| 216/216 [00:11<00:00, 17.88blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -40124,7 +40102,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 18.66blocks/s, ⧗=0, ▶=0, ✔=212, ✗=0, ∅=0]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ✔: 100%|██████████| 216/216 [00:11<00:00, 17.88blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -40134,26 +40112,12 @@ "\u001b[A" ] }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - }, { "name": "stderr", "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 18.66blocks/s, ⧗=0, ▶=1, ✔=212, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" + "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ✔: 100%|██████████| 216/216 [00:11<00:00, 18.60blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" ] }, { @@ -40164,47 +40128,50 @@ ] }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 98%|█████████▊| 212/216 [00:11<00:00, 18.66blocks/s, ⧗=0, ▶=0, ✔=213, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "\u001b[A" + "\n", + "Execution Summary\n", + "-----------------\n", + "\n", + " Task predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction:\n", + "\n", + " num blocks : 216\n", + " completed ✔: 216 (skipped 0)\n", + " failed ✗: 0\n", + " orphaned ∅: 0\n", + "\n", + " all blocks processed successfully\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\n" + "WARNING:dacapo.store.file_stats_store:Overwriting previous validation scores for run example_run\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 18.66blocks/s, ⧗=0, ▶=1, ✔=213, ✗=0, ∅=0]" + "WARNING:dacapo.store.file_stats_store:Overwriting previous validation scores for run example_run\n" ] }, { - "name": "stderr", + "name": "stdout", "output_type": "stream", "text": [ - "\u001b[A" + "Creating FileStatsStore:\n", + "\tpath : /home/runner/dacapo/stats\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\n" + "WARNING:dacapo.experiments.trainers.gunpowder_trainer:Saving Snapshot. Iteration: 1000, Loss: 0.5637715458869934!\n" ] }, { @@ -40212,21 +40179,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▊| 213/216 [00:11<00:00, 18.66blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" + "training until 2000: 50%|█████ | 1001/2000 [17:49<3:09:13, 11.36s/it, loss=0.353]" ] }, { @@ -40234,21 +40187,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 18.48blocks/s, ⧗=0, ▶=0, ✔=214, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" + "training until 2000: 50%|█████ | 1001/2000 [17:49<3:09:13, 11.36s/it, loss=0.564]" ] }, { @@ -40256,21 +40195,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:11<00:00, 18.48blocks/s, ⧗=0, ▶=1, ✔=214, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" + "training until 2000: 50%|█████ | 1002/2000 [17:50<2:17:14, 8.25s/it, loss=0.564]" ] }, { @@ -40278,21 +40203,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 99%|█████████▉| 214/216 [00:12<00:00, 18.48blocks/s, ⧗=0, ▶=0, ✔=215, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" + "training until 2000: 50%|█████ | 1002/2000 [17:50<2:17:14, 8.25s/it, loss=0.355]" ] }, { @@ -40300,21 +40211,7 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:12<00:00, 18.48blocks/s, ⧗=0, ▶=1, ✔=215, ✗=0, ∅=0]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\u001b[A" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" + "training until 2000: 50%|█████ | 1003/2000 [17:51<1:40:25, 6.04s/it, loss=0.355]" ] }, { @@ -40322,21 +40219,23 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 100%|█████████▉| 215/216 [00:12<00:00, 18.48blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "training until 2000: 50%|█████ | 1003/2000 [17:51<1:40:25, 6.04s/it, loss=0.286]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[A" + "\r", + "training until 2000: 50%|█████ | 1004/2000 [17:52<1:15:59, 4.58s/it, loss=0.286]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\n" + "\r", + "training until 2000: 50%|█████ | 1004/2000 [17:52<1:15:59, 4.58s/it, loss=0.315]" ] }, { @@ -40344,21 +40243,23 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ▶: 100%|██████████| 216/216 [00:12<00:00, 18.76blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "training until 2000: 50%|█████ | 1005/2000 [17:53<58:08, 3.51s/it, loss=0.315] " ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[A" + "\r", + "training until 2000: 50%|█████ | 1005/2000 [17:53<58:08, 3.51s/it, loss=0.298]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\n" + "\r", + "training until 2000: 50%|█████ | 1006/2000 [17:55<47:09, 2.85s/it, loss=0.298]" ] }, { @@ -40366,14 +40267,15 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ✔: 100%|██████████| 216/216 [00:12<00:00, 18.76blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "training until 2000: 50%|█████ | 1006/2000 [17:55<47:09, 2.85s/it, loss=0.276]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\u001b[A" + "\r", + "training until 2000: 50%|█████ | 1007/2000 [17:55<36:44, 2.22s/it, loss=0.276]" ] }, { @@ -40381,61 +40283,39 @@ "output_type": "stream", "text": [ "\r", - "predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction ✔: 100%|██████████| 216/216 [00:12<00:00, 17.86blocks/s, ⧗=0, ▶=0, ✔=216, ✗=0, ∅=0]" + "training until 2000: 50%|█████ | 1007/2000 [17:55<36:44, 2.22s/it, loss=0.305]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Execution Summary\n", - "-----------------\n", - "\n", - " Task predict_/home/runner/dacapo/example_run/validation.zarr_1000/cells3d/prediction:\n", - "\n", - " num blocks : 216\n", - " completed ✔: 216 (skipped 0)\n", - " failed ✗: 0\n", - " orphaned ∅: 0\n", - "\n", - " all blocks processed successfully\n" + "\r", + "training until 2000: 50%|█████ | 1008/2000 [17:56<31:13, 1.89s/it, loss=0.305]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "WARNING:dacapo.store.file_stats_store:Overwriting previous validation scores for run example_run\n" + "\r", + "training until 2000: 50%|█████ | 1008/2000 [17:56<31:13, 1.89s/it, loss=0.342]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "WARNING:dacapo.store.file_stats_store:Overwriting previous validation scores for run example_run\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Creating FileStatsStore:\n", - "\tpath : /home/runner/dacapo/stats\n" + "\r", + "training until 2000: 50%|█████ | 1009/2000 [17:58<27:41, 1.68s/it, loss=0.342]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "WARNING:dacapo.experiments.trainers.gunpowder_trainer:Saving Snapshot. Iteration: 1000, Loss: 0.4614645540714264!\n" + "\r", + "training until 2000: 50%|█████ | 1009/2000 [17:58<27:41, 1.68s/it, loss=0.293]" ] }, { @@ -40443,7 +40323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1001/2000 [14:26<3:07:50, 11.28s/it, loss=0.555]" + "training until 2000: 50%|█████ | 1010/2000 [17:58<23:24, 1.42s/it, loss=0.293]" ] }, { @@ -40451,7 +40331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1001/2000 [14:26<3:07:50, 11.28s/it, loss=0.461]" + "training until 2000: 50%|█████ | 1010/2000 [17:58<23:24, 1.42s/it, loss=0.269]" ] }, { @@ -40459,7 +40339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1002/2000 [14:26<2:14:36, 8.09s/it, loss=0.461]" + "training until 2000: 51%|█████ | 1011/2000 [18:00<22:53, 1.39s/it, loss=0.269]" ] }, { @@ -40467,7 +40347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1002/2000 [14:26<2:14:36, 8.09s/it, loss=0.474]" + "training until 2000: 51%|█████ | 1011/2000 [18:00<22:53, 1.39s/it, loss=0.363]" ] }, { @@ -40475,7 +40355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1003/2000 [14:27<1:37:27, 5.87s/it, loss=0.474]" + "training until 2000: 51%|█████ | 1012/2000 [18:01<20:46, 1.26s/it, loss=0.363]" ] }, { @@ -40483,7 +40363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1003/2000 [14:27<1:37:27, 5.87s/it, loss=0.468]" + "training until 2000: 51%|█████ | 1012/2000 [18:01<20:46, 1.26s/it, loss=0.342]" ] }, { @@ -40491,7 +40371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1004/2000 [14:28<1:12:17, 4.35s/it, loss=0.468]" + "training until 2000: 51%|█████ | 1013/2000 [18:02<19:52, 1.21s/it, loss=0.342]" ] }, { @@ -40499,7 +40379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1004/2000 [14:28<1:12:17, 4.35s/it, loss=0.45] " + "training until 2000: 51%|█████ | 1013/2000 [18:02<19:52, 1.21s/it, loss=0.313]" ] }, { @@ -40507,7 +40387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1005/2000 [14:29<56:45, 3.42s/it, loss=0.45] " + "training until 2000: 51%|█████ | 1014/2000 [18:03<17:37, 1.07s/it, loss=0.313]" ] }, { @@ -40515,7 +40395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1005/2000 [14:29<56:45, 3.42s/it, loss=0.568]" + "training until 2000: 51%|█████ | 1014/2000 [18:03<17:37, 1.07s/it, loss=0.163]" ] }, { @@ -40523,7 +40403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1006/2000 [14:30<45:06, 2.72s/it, loss=0.568]" + "training until 2000: 51%|█████ | 1015/2000 [18:04<17:36, 1.07s/it, loss=0.163]" ] }, { @@ -40531,7 +40411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1006/2000 [14:30<45:06, 2.72s/it, loss=0.513]" + "training until 2000: 51%|█████ | 1015/2000 [18:04<17:36, 1.07s/it, loss=0.259]" ] }, { @@ -40539,7 +40419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1007/2000 [14:31<36:23, 2.20s/it, loss=0.513]" + "training until 2000: 51%|█████ | 1016/2000 [18:05<18:37, 1.14s/it, loss=0.259]" ] }, { @@ -40547,7 +40427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1007/2000 [14:31<36:23, 2.20s/it, loss=0.507]" + "training until 2000: 51%|█████ | 1016/2000 [18:05<18:37, 1.14s/it, loss=0.356]" ] }, { @@ -40555,7 +40435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1008/2000 [14:32<30:50, 1.87s/it, loss=0.507]" + "training until 2000: 51%|█████ | 1017/2000 [18:06<17:31, 1.07s/it, loss=0.356]" ] }, { @@ -40563,7 +40443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1008/2000 [14:32<30:50, 1.87s/it, loss=0.511]" + "training until 2000: 51%|█████ | 1017/2000 [18:06<17:31, 1.07s/it, loss=0.31] " ] }, { @@ -40571,7 +40451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1009/2000 [14:33<25:56, 1.57s/it, loss=0.511]" + "training until 2000: 51%|█████ | 1018/2000 [18:07<16:26, 1.00s/it, loss=0.31]" ] }, { @@ -40579,7 +40459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1009/2000 [14:33<25:56, 1.57s/it, loss=0.496]" + "training until 2000: 51%|█████ | 1018/2000 [18:07<16:26, 1.00s/it, loss=0.401]" ] }, { @@ -40587,7 +40467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1010/2000 [14:34<22:42, 1.38s/it, loss=0.496]" + "training until 2000: 51%|█████ | 1019/2000 [18:08<15:44, 1.04it/s, loss=0.401]" ] }, { @@ -40595,7 +40475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 50%|█████ | 1010/2000 [14:34<22:42, 1.38s/it, loss=0.518]" + "training until 2000: 51%|█████ | 1019/2000 [18:08<15:44, 1.04it/s, loss=0.331]" ] }, { @@ -40603,7 +40483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1011/2000 [14:35<18:52, 1.15s/it, loss=0.518]" + "training until 2000: 51%|█████ | 1020/2000 [18:09<16:24, 1.00s/it, loss=0.331]" ] }, { @@ -40611,7 +40491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1011/2000 [14:35<18:52, 1.15s/it, loss=0.504]" + "training until 2000: 51%|█████ | 1020/2000 [18:09<16:24, 1.00s/it, loss=0.355]" ] }, { @@ -40619,7 +40499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1012/2000 [14:36<17:45, 1.08s/it, loss=0.504]" + "training until 2000: 51%|█████ | 1021/2000 [18:10<15:27, 1.05it/s, loss=0.355]" ] }, { @@ -40627,7 +40507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1012/2000 [14:36<17:45, 1.08s/it, loss=0.479]" + "training until 2000: 51%|█████ | 1021/2000 [18:10<15:27, 1.05it/s, loss=0.347]" ] }, { @@ -40635,7 +40515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1013/2000 [14:37<16:48, 1.02s/it, loss=0.479]" + "training until 2000: 51%|█████ | 1022/2000 [18:11<17:23, 1.07s/it, loss=0.347]" ] }, { @@ -40643,7 +40523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1013/2000 [14:37<16:48, 1.02s/it, loss=0.503]" + "training until 2000: 51%|█████ | 1022/2000 [18:11<17:23, 1.07s/it, loss=0.276]" ] }, { @@ -40651,7 +40531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1014/2000 [14:37<14:46, 1.11it/s, loss=0.503]" + "training until 2000: 51%|█████ | 1023/2000 [18:12<17:27, 1.07s/it, loss=0.276]" ] }, { @@ -40659,7 +40539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1014/2000 [14:37<14:46, 1.11it/s, loss=0.506]" + "training until 2000: 51%|█████ | 1023/2000 [18:12<17:27, 1.07s/it, loss=0.24] " ] }, { @@ -40667,7 +40547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1015/2000 [14:38<15:04, 1.09it/s, loss=0.506]" + "training until 2000: 51%|█████ | 1024/2000 [18:13<15:42, 1.04it/s, loss=0.24]" ] }, { @@ -40675,7 +40555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1015/2000 [14:38<15:04, 1.09it/s, loss=0.439]" + "training until 2000: 51%|█████ | 1024/2000 [18:13<15:42, 1.04it/s, loss=0.382]" ] }, { @@ -40683,7 +40563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1016/2000 [14:39<14:08, 1.16it/s, loss=0.439]" + "training until 2000: 51%|█████▏ | 1025/2000 [18:13<14:32, 1.12it/s, loss=0.382]" ] }, { @@ -40691,7 +40571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1016/2000 [14:39<14:08, 1.16it/s, loss=0.473]" + "training until 2000: 51%|█████▏ | 1025/2000 [18:13<14:32, 1.12it/s, loss=0.3] " ] }, { @@ -40699,7 +40579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1017/2000 [14:40<15:17, 1.07it/s, loss=0.473]" + "training until 2000: 51%|█████▏ | 1026/2000 [18:14<15:24, 1.05it/s, loss=0.3]" ] }, { @@ -40707,7 +40587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1017/2000 [14:40<15:17, 1.07it/s, loss=0.491]" + "training until 2000: 51%|█████▏ | 1026/2000 [18:14<15:24, 1.05it/s, loss=0.361]" ] }, { @@ -40715,7 +40595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1018/2000 [14:41<13:35, 1.20it/s, loss=0.491]" + "training until 2000: 51%|█████▏ | 1027/2000 [18:15<15:44, 1.03it/s, loss=0.361]" ] }, { @@ -40723,7 +40603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1018/2000 [14:41<13:35, 1.20it/s, loss=0.497]" + "training until 2000: 51%|█████▏ | 1027/2000 [18:15<15:44, 1.03it/s, loss=0.473]" ] }, { @@ -40731,7 +40611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1019/2000 [14:42<15:50, 1.03it/s, loss=0.497]" + "training until 2000: 51%|█████▏ | 1028/2000 [18:16<14:48, 1.09it/s, loss=0.473]" ] }, { @@ -40739,7 +40619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1019/2000 [14:42<15:50, 1.03it/s, loss=0.463]" + "training until 2000: 51%|█████▏ | 1028/2000 [18:16<14:48, 1.09it/s, loss=0.369]" ] }, { @@ -40747,7 +40627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1020/2000 [14:43<15:26, 1.06it/s, loss=0.463]" + "training until 2000: 51%|█████▏ | 1029/2000 [18:17<15:32, 1.04it/s, loss=0.369]" ] }, { @@ -40755,7 +40635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1020/2000 [14:43<15:26, 1.06it/s, loss=0.512]" + "training until 2000: 51%|█████▏ | 1029/2000 [18:17<15:32, 1.04it/s, loss=0.273]" ] }, { @@ -40763,7 +40643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1021/2000 [14:43<13:48, 1.18it/s, loss=0.512]" + "training until 2000: 52%|█████▏ | 1030/2000 [18:18<14:59, 1.08it/s, loss=0.273]" ] }, { @@ -40771,7 +40651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1021/2000 [14:43<13:48, 1.18it/s, loss=0.517]" + "training until 2000: 52%|█████▏ | 1030/2000 [18:18<14:59, 1.08it/s, loss=0.208]" ] }, { @@ -40779,7 +40659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1022/2000 [14:44<13:33, 1.20it/s, loss=0.517]" + "training until 2000: 52%|█████▏ | 1031/2000 [18:19<14:26, 1.12it/s, loss=0.208]" ] }, { @@ -40787,7 +40667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1022/2000 [14:44<13:33, 1.20it/s, loss=0.527]" + "training until 2000: 52%|█████▏ | 1031/2000 [18:19<14:26, 1.12it/s, loss=0.21] " ] }, { @@ -40795,7 +40675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1023/2000 [14:45<13:06, 1.24it/s, loss=0.527]" + "training until 2000: 52%|█████▏ | 1032/2000 [18:20<16:30, 1.02s/it, loss=0.21]" ] }, { @@ -40803,7 +40683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1023/2000 [14:45<13:06, 1.24it/s, loss=0.476]" + "training until 2000: 52%|█████▏ | 1032/2000 [18:20<16:30, 1.02s/it, loss=0.286]" ] }, { @@ -40811,7 +40691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1024/2000 [14:46<12:55, 1.26it/s, loss=0.476]" + "training until 2000: 52%|█████▏ | 1033/2000 [18:22<18:07, 1.12s/it, loss=0.286]" ] }, { @@ -40819,7 +40699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████ | 1024/2000 [14:46<12:55, 1.26it/s, loss=0.555]" + "training until 2000: 52%|█████▏ | 1033/2000 [18:22<18:07, 1.12s/it, loss=0.304]" ] }, { @@ -40827,7 +40707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1025/2000 [14:47<13:24, 1.21it/s, loss=0.555]" + "training until 2000: 52%|█████▏ | 1034/2000 [18:23<16:41, 1.04s/it, loss=0.304]" ] }, { @@ -40835,7 +40715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1025/2000 [14:47<13:24, 1.21it/s, loss=0.554]" + "training until 2000: 52%|█████▏ | 1034/2000 [18:23<16:41, 1.04s/it, loss=0.267]" ] }, { @@ -40843,7 +40723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1026/2000 [14:47<12:25, 1.31it/s, loss=0.554]" + "training until 2000: 52%|█████▏ | 1035/2000 [18:24<17:46, 1.11s/it, loss=0.267]" ] }, { @@ -40851,7 +40731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1026/2000 [14:47<12:25, 1.31it/s, loss=0.478]" + "training until 2000: 52%|█████▏ | 1035/2000 [18:24<17:46, 1.11s/it, loss=0.234]" ] }, { @@ -40859,7 +40739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1027/2000 [14:48<13:53, 1.17it/s, loss=0.478]" + "training until 2000: 52%|█████▏ | 1036/2000 [18:25<17:49, 1.11s/it, loss=0.234]" ] }, { @@ -40867,7 +40747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1027/2000 [14:48<13:53, 1.17it/s, loss=0.469]" + "training until 2000: 52%|█████▏ | 1036/2000 [18:25<17:49, 1.11s/it, loss=0.296]" ] }, { @@ -40875,7 +40755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1028/2000 [14:49<14:53, 1.09it/s, loss=0.469]" + "training until 2000: 52%|█████▏ | 1037/2000 [18:26<17:42, 1.10s/it, loss=0.296]" ] }, { @@ -40883,7 +40763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1028/2000 [14:49<14:53, 1.09it/s, loss=0.487]" + "training until 2000: 52%|█████▏ | 1037/2000 [18:26<17:42, 1.10s/it, loss=0.267]" ] }, { @@ -40891,7 +40771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1029/2000 [14:50<15:46, 1.03it/s, loss=0.487]" + "training until 2000: 52%|█████▏ | 1038/2000 [18:28<21:13, 1.32s/it, loss=0.267]" ] }, { @@ -40899,7 +40779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 51%|█████▏ | 1029/2000 [14:50<15:46, 1.03it/s, loss=0.505]" + "training until 2000: 52%|█████▏ | 1038/2000 [18:28<21:13, 1.32s/it, loss=0.382]" ] }, { @@ -40907,7 +40787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1030/2000 [14:51<14:09, 1.14it/s, loss=0.505]" + "training until 2000: 52%|█████▏ | 1039/2000 [18:29<20:02, 1.25s/it, loss=0.382]" ] }, { @@ -40915,7 +40795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1030/2000 [14:51<14:09, 1.14it/s, loss=0.47] " + "training until 2000: 52%|█████▏ | 1039/2000 [18:29<20:02, 1.25s/it, loss=0.417]" ] }, { @@ -40923,7 +40803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1031/2000 [14:52<13:12, 1.22it/s, loss=0.47]" + "training until 2000: 52%|█████▏ | 1040/2000 [18:30<19:36, 1.23s/it, loss=0.417]" ] }, { @@ -40931,7 +40811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1031/2000 [14:52<13:12, 1.22it/s, loss=0.687]" + "training until 2000: 52%|█████▏ | 1040/2000 [18:30<19:36, 1.23s/it, loss=0.309]" ] }, { @@ -40939,7 +40819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1032/2000 [14:53<15:21, 1.05it/s, loss=0.687]" + "training until 2000: 52%|█████▏ | 1041/2000 [18:31<18:34, 1.16s/it, loss=0.309]" ] }, { @@ -40947,7 +40827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1032/2000 [14:53<15:21, 1.05it/s, loss=0.571]" + "training until 2000: 52%|█████▏ | 1041/2000 [18:31<18:34, 1.16s/it, loss=0.396]" ] }, { @@ -40955,7 +40835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1033/2000 [14:54<14:57, 1.08it/s, loss=0.571]" + "training until 2000: 52%|█████▏ | 1042/2000 [18:32<18:06, 1.13s/it, loss=0.396]" ] }, { @@ -40963,7 +40843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1033/2000 [14:54<14:57, 1.08it/s, loss=0.475]" + "training until 2000: 52%|█████▏ | 1042/2000 [18:32<18:06, 1.13s/it, loss=0.218]" ] }, { @@ -40971,7 +40851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1034/2000 [14:54<13:04, 1.23it/s, loss=0.475]" + "training until 2000: 52%|█████▏ | 1043/2000 [18:34<21:13, 1.33s/it, loss=0.218]" ] }, { @@ -40979,7 +40859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1034/2000 [14:54<13:04, 1.23it/s, loss=0.465]" + "training until 2000: 52%|█████▏ | 1043/2000 [18:34<21:13, 1.33s/it, loss=0.349]" ] }, { @@ -40987,7 +40867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1035/2000 [14:55<12:39, 1.27it/s, loss=0.465]" + "training until 2000: 52%|█████▏ | 1044/2000 [18:35<19:24, 1.22s/it, loss=0.349]" ] }, { @@ -40995,7 +40875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1035/2000 [14:55<12:39, 1.27it/s, loss=0.486]" + "training until 2000: 52%|█████▏ | 1044/2000 [18:35<19:24, 1.22s/it, loss=0.324]" ] }, { @@ -41003,7 +40883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1036/2000 [14:56<13:20, 1.20it/s, loss=0.486]" + "training until 2000: 52%|█████▏ | 1045/2000 [18:36<17:49, 1.12s/it, loss=0.324]" ] }, { @@ -41011,7 +40891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1036/2000 [14:56<13:20, 1.20it/s, loss=0.566]" + "training until 2000: 52%|█████▏ | 1045/2000 [18:36<17:49, 1.12s/it, loss=0.427]" ] }, { @@ -41019,7 +40899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1037/2000 [14:57<13:55, 1.15it/s, loss=0.566]" + "training until 2000: 52%|█████▏ | 1046/2000 [18:37<16:01, 1.01s/it, loss=0.427]" ] }, { @@ -41027,7 +40907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1037/2000 [14:57<13:55, 1.15it/s, loss=0.487]" + "training until 2000: 52%|█████▏ | 1046/2000 [18:37<16:01, 1.01s/it, loss=0.271]" ] }, { @@ -41035,7 +40915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1038/2000 [14:58<14:38, 1.10it/s, loss=0.487]" + "training until 2000: 52%|█████▏ | 1047/2000 [18:37<14:39, 1.08it/s, loss=0.271]" ] }, { @@ -41043,7 +40923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1038/2000 [14:58<14:38, 1.10it/s, loss=0.529]" + "training until 2000: 52%|█████▏ | 1047/2000 [18:37<14:39, 1.08it/s, loss=0.39] " ] }, { @@ -41051,7 +40931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1039/2000 [14:59<13:35, 1.18it/s, loss=0.529]" + "training until 2000: 52%|█████▏ | 1048/2000 [18:38<13:48, 1.15it/s, loss=0.39]" ] }, { @@ -41059,7 +40939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1039/2000 [14:59<13:35, 1.18it/s, loss=0.562]" + "training until 2000: 52%|█████▏ | 1048/2000 [18:38<13:48, 1.15it/s, loss=0.248]" ] }, { @@ -41067,7 +40947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1040/2000 [14:59<12:17, 1.30it/s, loss=0.562]" + "training until 2000: 52%|█████▏ | 1049/2000 [18:39<15:25, 1.03it/s, loss=0.248]" ] }, { @@ -41075,7 +40955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1040/2000 [14:59<12:17, 1.30it/s, loss=0.51] " + "training until 2000: 52%|█████▏ | 1049/2000 [18:39<15:25, 1.03it/s, loss=0.217]" ] }, { @@ -41083,7 +40963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1041/2000 [15:00<11:44, 1.36it/s, loss=0.51]" + "training until 2000: 52%|█████▎ | 1050/2000 [18:40<13:21, 1.18it/s, loss=0.217]" ] }, { @@ -41091,7 +40971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1041/2000 [15:00<11:44, 1.36it/s, loss=0.529]" + "training until 2000: 52%|█████▎ | 1050/2000 [18:40<13:21, 1.18it/s, loss=0.291]" ] }, { @@ -41099,7 +40979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1042/2000 [15:01<11:13, 1.42it/s, loss=0.529]" + "training until 2000: 53%|█████▎ | 1051/2000 [18:41<16:20, 1.03s/it, loss=0.291]" ] }, { @@ -41107,7 +40987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1042/2000 [15:01<11:13, 1.42it/s, loss=0.57] " + "training until 2000: 53%|█████▎ | 1051/2000 [18:41<16:20, 1.03s/it, loss=0.198]" ] }, { @@ -41115,7 +40995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1043/2000 [15:01<10:36, 1.50it/s, loss=0.57]" + "training until 2000: 53%|█████▎ | 1052/2000 [18:42<14:02, 1.13it/s, loss=0.198]" ] }, { @@ -41123,7 +41003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1043/2000 [15:01<10:36, 1.50it/s, loss=0.522]" + "training until 2000: 53%|█████▎ | 1052/2000 [18:42<14:02, 1.13it/s, loss=0.3] " ] }, { @@ -41131,7 +41011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1044/2000 [15:02<09:51, 1.62it/s, loss=0.522]" + "training until 2000: 53%|█████▎ | 1053/2000 [18:43<15:04, 1.05it/s, loss=0.3]" ] }, { @@ -41139,7 +41019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1044/2000 [15:02<09:51, 1.62it/s, loss=0.483]" + "training until 2000: 53%|█████▎ | 1053/2000 [18:43<15:04, 1.05it/s, loss=0.266]" ] }, { @@ -41147,7 +41027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1045/2000 [15:03<10:57, 1.45it/s, loss=0.483]" + "training until 2000: 53%|█████▎ | 1054/2000 [18:44<16:33, 1.05s/it, loss=0.266]" ] }, { @@ -41155,7 +41035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1045/2000 [15:03<10:57, 1.45it/s, loss=0.457]" + "training until 2000: 53%|█████▎ | 1054/2000 [18:44<16:33, 1.05s/it, loss=0.295]" ] }, { @@ -41163,7 +41043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1046/2000 [15:04<12:16, 1.30it/s, loss=0.457]" + "training until 2000: 53%|█████▎ | 1055/2000 [18:45<16:41, 1.06s/it, loss=0.295]" ] }, { @@ -41171,7 +41051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1046/2000 [15:04<12:16, 1.30it/s, loss=0.517]" + "training until 2000: 53%|█████▎ | 1055/2000 [18:45<16:41, 1.06s/it, loss=0.178]" ] }, { @@ -41179,7 +41059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1047/2000 [15:05<14:25, 1.10it/s, loss=0.517]" + "training until 2000: 53%|█████▎ | 1056/2000 [18:46<14:38, 1.07it/s, loss=0.178]" ] }, { @@ -41187,7 +41067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1047/2000 [15:05<14:25, 1.10it/s, loss=0.482]" + "training until 2000: 53%|█████▎ | 1056/2000 [18:46<14:38, 1.07it/s, loss=0.475]" ] }, { @@ -41195,7 +41075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1048/2000 [15:05<13:13, 1.20it/s, loss=0.482]" + "training until 2000: 53%|█████▎ | 1057/2000 [18:47<13:29, 1.16it/s, loss=0.475]" ] }, { @@ -41203,7 +41083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1048/2000 [15:05<13:13, 1.20it/s, loss=0.512]" + "training until 2000: 53%|█████▎ | 1057/2000 [18:47<13:29, 1.16it/s, loss=0.273]" ] }, { @@ -41211,7 +41091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1049/2000 [15:06<12:56, 1.23it/s, loss=0.512]" + "training until 2000: 53%|█████▎ | 1058/2000 [18:48<15:28, 1.01it/s, loss=0.273]" ] }, { @@ -41219,7 +41099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▏ | 1049/2000 [15:06<12:56, 1.23it/s, loss=0.486]" + "training until 2000: 53%|█████▎ | 1058/2000 [18:48<15:28, 1.01it/s, loss=0.253]" ] }, { @@ -41227,7 +41107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▎ | 1050/2000 [15:07<14:00, 1.13it/s, loss=0.486]" + "training until 2000: 53%|█████▎ | 1059/2000 [18:49<16:48, 1.07s/it, loss=0.253]" ] }, { @@ -41235,7 +41115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 52%|█████▎ | 1050/2000 [15:07<14:00, 1.13it/s, loss=0.453]" + "training until 2000: 53%|█████▎ | 1059/2000 [18:49<16:48, 1.07s/it, loss=0.383]" ] }, { @@ -41243,7 +41123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1051/2000 [15:08<12:39, 1.25it/s, loss=0.453]" + "training until 2000: 53%|█████▎ | 1060/2000 [18:50<16:38, 1.06s/it, loss=0.383]" ] }, { @@ -41251,7 +41131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1051/2000 [15:08<12:39, 1.25it/s, loss=0.472]" + "training until 2000: 53%|█████▎ | 1060/2000 [18:50<16:38, 1.06s/it, loss=0.249]" ] }, { @@ -41259,7 +41139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1052/2000 [15:09<13:15, 1.19it/s, loss=0.472]" + "training until 2000: 53%|█████▎ | 1061/2000 [18:52<19:41, 1.26s/it, loss=0.249]" ] }, { @@ -41267,7 +41147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1052/2000 [15:09<13:15, 1.19it/s, loss=0.444]" + "training until 2000: 53%|█████▎ | 1061/2000 [18:52<19:41, 1.26s/it, loss=0.301]" ] }, { @@ -41275,7 +41155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1053/2000 [15:10<12:42, 1.24it/s, loss=0.444]" + "training until 2000: 53%|█████▎ | 1062/2000 [18:53<17:13, 1.10s/it, loss=0.301]" ] }, { @@ -41283,7 +41163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1053/2000 [15:10<12:42, 1.24it/s, loss=0.498]" + "training until 2000: 53%|█████▎ | 1062/2000 [18:53<17:13, 1.10s/it, loss=0.245]" ] }, { @@ -41291,7 +41171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1054/2000 [15:10<12:46, 1.23it/s, loss=0.498]" + "training until 2000: 53%|█████▎ | 1063/2000 [18:54<17:04, 1.09s/it, loss=0.245]" ] }, { @@ -41299,7 +41179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1054/2000 [15:10<12:46, 1.23it/s, loss=0.444]" + "training until 2000: 53%|█████▎ | 1063/2000 [18:54<17:04, 1.09s/it, loss=0.282]" ] }, { @@ -41307,7 +41187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1055/2000 [15:11<12:00, 1.31it/s, loss=0.444]" + "training until 2000: 53%|█████▎ | 1064/2000 [18:55<17:10, 1.10s/it, loss=0.282]" ] }, { @@ -41315,7 +41195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1055/2000 [15:11<12:00, 1.31it/s, loss=0.444]" + "training until 2000: 53%|█████▎ | 1064/2000 [18:55<17:10, 1.10s/it, loss=0.317]" ] }, { @@ -41323,7 +41203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1056/2000 [15:12<12:06, 1.30it/s, loss=0.444]" + "training until 2000: 53%|█████▎ | 1065/2000 [18:56<16:05, 1.03s/it, loss=0.317]" ] }, { @@ -41331,7 +41211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1056/2000 [15:12<12:06, 1.30it/s, loss=0.539]" + "training until 2000: 53%|█████▎ | 1065/2000 [18:56<16:05, 1.03s/it, loss=0.236]" ] }, { @@ -41339,7 +41219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1057/2000 [15:12<10:24, 1.51it/s, loss=0.539]" + "training until 2000: 53%|█████▎ | 1066/2000 [18:57<16:34, 1.06s/it, loss=0.236]" ] }, { @@ -41347,7 +41227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1057/2000 [15:12<10:24, 1.51it/s, loss=0.491]" + "training until 2000: 53%|█████▎ | 1066/2000 [18:57<16:34, 1.06s/it, loss=0.42] " ] }, { @@ -41355,7 +41235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1058/2000 [15:13<10:16, 1.53it/s, loss=0.491]" + "training until 2000: 53%|█████▎ | 1067/2000 [18:58<18:33, 1.19s/it, loss=0.42]" ] }, { @@ -41363,7 +41243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1058/2000 [15:13<10:16, 1.53it/s, loss=0.478]" + "training until 2000: 53%|█████▎ | 1067/2000 [18:58<18:33, 1.19s/it, loss=0.303]" ] }, { @@ -41371,7 +41251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1059/2000 [15:14<10:42, 1.47it/s, loss=0.478]" + "training until 2000: 53%|█████▎ | 1068/2000 [18:59<16:25, 1.06s/it, loss=0.303]" ] }, { @@ -41379,7 +41259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1059/2000 [15:14<10:42, 1.47it/s, loss=0.486]" + "training until 2000: 53%|█████▎ | 1068/2000 [18:59<16:25, 1.06s/it, loss=0.288]" ] }, { @@ -41387,7 +41267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1060/2000 [15:15<12:47, 1.23it/s, loss=0.486]" + "training until 2000: 53%|█████▎ | 1069/2000 [19:00<16:09, 1.04s/it, loss=0.288]" ] }, { @@ -41395,7 +41275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1060/2000 [15:15<12:47, 1.23it/s, loss=0.437]" + "training until 2000: 53%|█████▎ | 1069/2000 [19:00<16:09, 1.04s/it, loss=0.335]" ] }, { @@ -41403,7 +41283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1061/2000 [15:16<14:11, 1.10it/s, loss=0.437]" + "training until 2000: 54%|█████▎ | 1070/2000 [19:01<15:33, 1.00s/it, loss=0.335]" ] }, { @@ -41411,7 +41291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1061/2000 [15:16<14:11, 1.10it/s, loss=0.454]" + "training until 2000: 54%|█████▎ | 1070/2000 [19:01<15:33, 1.00s/it, loss=0.238]" ] }, { @@ -41419,7 +41299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1062/2000 [15:17<14:00, 1.12it/s, loss=0.454]" + "training until 2000: 54%|█████▎ | 1071/2000 [19:02<13:17, 1.16it/s, loss=0.238]" ] }, { @@ -41427,7 +41307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1062/2000 [15:17<14:00, 1.12it/s, loss=0.449]" + "training until 2000: 54%|█████▎ | 1071/2000 [19:02<13:17, 1.16it/s, loss=0.318]" ] }, { @@ -41435,7 +41315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1063/2000 [15:17<12:08, 1.29it/s, loss=0.449]" + "training until 2000: 54%|█████▎ | 1072/2000 [19:02<13:04, 1.18it/s, loss=0.318]" ] }, { @@ -41443,7 +41323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1063/2000 [15:17<12:08, 1.29it/s, loss=0.456]" + "training until 2000: 54%|█████▎ | 1072/2000 [19:02<13:04, 1.18it/s, loss=0.273]" ] }, { @@ -41451,7 +41331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1064/2000 [15:18<12:51, 1.21it/s, loss=0.456]" + "training until 2000: 54%|█████▎ | 1073/2000 [19:03<13:49, 1.12it/s, loss=0.273]" ] }, { @@ -41459,7 +41339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1064/2000 [15:18<12:51, 1.21it/s, loss=0.475]" + "training until 2000: 54%|█████▎ | 1073/2000 [19:03<13:49, 1.12it/s, loss=0.227]" ] }, { @@ -41467,7 +41347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1065/2000 [15:19<12:58, 1.20it/s, loss=0.475]" + "training until 2000: 54%|█████▎ | 1074/2000 [19:04<14:42, 1.05it/s, loss=0.227]" ] }, { @@ -41475,7 +41355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1065/2000 [15:19<12:58, 1.20it/s, loss=0.477]" + "training until 2000: 54%|█████▎ | 1074/2000 [19:04<14:42, 1.05it/s, loss=0.222]" ] }, { @@ -41483,7 +41363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1066/2000 [15:20<13:27, 1.16it/s, loss=0.477]" + "training until 2000: 54%|█████▍ | 1075/2000 [19:05<14:41, 1.05it/s, loss=0.222]" ] }, { @@ -41491,7 +41371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1066/2000 [15:20<13:27, 1.16it/s, loss=0.499]" + "training until 2000: 54%|█████▍ | 1075/2000 [19:05<14:41, 1.05it/s, loss=0.301]" ] }, { @@ -41499,7 +41379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1067/2000 [15:21<13:39, 1.14it/s, loss=0.499]" + "training until 2000: 54%|█████▍ | 1076/2000 [19:06<13:36, 1.13it/s, loss=0.301]" ] }, { @@ -41507,7 +41387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1067/2000 [15:21<13:39, 1.14it/s, loss=0.482]" + "training until 2000: 54%|█████▍ | 1076/2000 [19:06<13:36, 1.13it/s, loss=0.319]" ] }, { @@ -41515,7 +41395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1068/2000 [15:22<13:23, 1.16it/s, loss=0.482]" + "training until 2000: 54%|█████▍ | 1077/2000 [19:07<12:14, 1.26it/s, loss=0.319]" ] }, { @@ -41523,7 +41403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1068/2000 [15:22<13:23, 1.16it/s, loss=0.459]" + "training until 2000: 54%|█████▍ | 1077/2000 [19:07<12:14, 1.26it/s, loss=0.189]" ] }, { @@ -41531,7 +41411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1069/2000 [15:22<12:29, 1.24it/s, loss=0.459]" + "training until 2000: 54%|█████▍ | 1078/2000 [19:08<13:57, 1.10it/s, loss=0.189]" ] }, { @@ -41539,7 +41419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 53%|█████▎ | 1069/2000 [15:22<12:29, 1.24it/s, loss=0.489]" + "training until 2000: 54%|█████▍ | 1078/2000 [19:08<13:57, 1.10it/s, loss=0.239]" ] }, { @@ -41547,7 +41427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1070/2000 [15:23<11:57, 1.30it/s, loss=0.489]" + "training until 2000: 54%|█████▍ | 1079/2000 [19:09<15:52, 1.03s/it, loss=0.239]" ] }, { @@ -41555,7 +41435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1070/2000 [15:23<11:57, 1.30it/s, loss=0.562]" + "training until 2000: 54%|█████▍ | 1079/2000 [19:09<15:52, 1.03s/it, loss=0.219]" ] }, { @@ -41563,7 +41443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1071/2000 [15:24<11:31, 1.34it/s, loss=0.562]" + "training until 2000: 54%|█████▍ | 1080/2000 [19:10<13:51, 1.11it/s, loss=0.219]" ] }, { @@ -41571,7 +41451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1071/2000 [15:24<11:31, 1.34it/s, loss=0.433]" + "training until 2000: 54%|█████▍ | 1080/2000 [19:10<13:51, 1.11it/s, loss=0.183]" ] }, { @@ -41579,7 +41459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1072/2000 [15:24<11:00, 1.41it/s, loss=0.433]" + "training until 2000: 54%|█████▍ | 1081/2000 [19:11<13:13, 1.16it/s, loss=0.183]" ] }, { @@ -41587,7 +41467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1072/2000 [15:24<11:00, 1.41it/s, loss=0.496]" + "training until 2000: 54%|█████▍ | 1081/2000 [19:11<13:13, 1.16it/s, loss=0.175]" ] }, { @@ -41595,7 +41475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1073/2000 [15:25<10:04, 1.53it/s, loss=0.496]" + "training until 2000: 54%|█████▍ | 1082/2000 [19:11<13:24, 1.14it/s, loss=0.175]" ] }, { @@ -41603,7 +41483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1073/2000 [15:25<10:04, 1.53it/s, loss=0.645]" + "training until 2000: 54%|█████▍ | 1082/2000 [19:11<13:24, 1.14it/s, loss=0.394]" ] }, { @@ -41611,7 +41491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1074/2000 [15:25<09:26, 1.63it/s, loss=0.645]" + "training until 2000: 54%|█████▍ | 1083/2000 [19:12<13:56, 1.10it/s, loss=0.394]" ] }, { @@ -41619,7 +41499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▎ | 1074/2000 [15:25<09:26, 1.63it/s, loss=0.488]" + "training until 2000: 54%|█████▍ | 1083/2000 [19:12<13:56, 1.10it/s, loss=0.228]" ] }, { @@ -41627,7 +41507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1075/2000 [15:26<10:02, 1.54it/s, loss=0.488]" + "training until 2000: 54%|█████▍ | 1084/2000 [19:13<12:42, 1.20it/s, loss=0.228]" ] }, { @@ -41635,7 +41515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1075/2000 [15:26<10:02, 1.54it/s, loss=0.485]" + "training until 2000: 54%|█████▍ | 1084/2000 [19:13<12:42, 1.20it/s, loss=0.176]" ] }, { @@ -41643,7 +41523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1076/2000 [15:27<10:02, 1.53it/s, loss=0.485]" + "training until 2000: 54%|█████▍ | 1085/2000 [19:14<13:50, 1.10it/s, loss=0.176]" ] }, { @@ -41651,7 +41531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1076/2000 [15:27<10:02, 1.53it/s, loss=0.479]" + "training until 2000: 54%|█████▍ | 1085/2000 [19:14<13:50, 1.10it/s, loss=0.376]" ] }, { @@ -41659,7 +41539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1077/2000 [15:28<11:00, 1.40it/s, loss=0.479]" + "training until 2000: 54%|█████▍ | 1086/2000 [19:15<15:33, 1.02s/it, loss=0.376]" ] }, { @@ -41667,7 +41547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1077/2000 [15:28<11:00, 1.40it/s, loss=0.45] " + "training until 2000: 54%|█████▍ | 1086/2000 [19:15<15:33, 1.02s/it, loss=0.35] " ] }, { @@ -41675,7 +41555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1078/2000 [15:28<10:27, 1.47it/s, loss=0.45]" + "training until 2000: 54%|█████▍ | 1087/2000 [19:16<15:23, 1.01s/it, loss=0.35]" ] }, { @@ -41683,7 +41563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1078/2000 [15:28<10:27, 1.47it/s, loss=0.547]" + "training until 2000: 54%|█████▍ | 1087/2000 [19:16<15:23, 1.01s/it, loss=0.204]" ] }, { @@ -41691,7 +41571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1079/2000 [15:29<10:24, 1.47it/s, loss=0.547]" + "training until 2000: 54%|█████▍ | 1088/2000 [19:17<14:19, 1.06it/s, loss=0.204]" ] }, { @@ -41699,7 +41579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1079/2000 [15:29<10:24, 1.47it/s, loss=0.549]" + "training until 2000: 54%|█████▍ | 1088/2000 [19:17<14:19, 1.06it/s, loss=0.32] " ] }, { @@ -41707,7 +41587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1080/2000 [15:30<11:21, 1.35it/s, loss=0.549]" + "training until 2000: 54%|█████▍ | 1089/2000 [19:19<16:16, 1.07s/it, loss=0.32]" ] }, { @@ -41715,7 +41595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1080/2000 [15:30<11:21, 1.35it/s, loss=0.549]" + "training until 2000: 54%|█████▍ | 1089/2000 [19:19<16:16, 1.07s/it, loss=0.311]" ] }, { @@ -41723,7 +41603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1081/2000 [15:31<12:40, 1.21it/s, loss=0.549]" + "training until 2000: 55%|█████▍ | 1090/2000 [19:19<14:15, 1.06it/s, loss=0.311]" ] }, { @@ -41731,7 +41611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1081/2000 [15:31<12:40, 1.21it/s, loss=0.485]" + "training until 2000: 55%|█████▍ | 1090/2000 [19:19<14:15, 1.06it/s, loss=0.281]" ] }, { @@ -41739,7 +41619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1082/2000 [15:31<11:19, 1.35it/s, loss=0.485]" + "training until 2000: 55%|█████▍ | 1091/2000 [19:20<15:20, 1.01s/it, loss=0.281]" ] }, { @@ -41747,7 +41627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1082/2000 [15:31<11:19, 1.35it/s, loss=0.473]" + "training until 2000: 55%|█████▍ | 1091/2000 [19:20<15:20, 1.01s/it, loss=0.282]" ] }, { @@ -41755,7 +41635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1083/2000 [15:32<10:13, 1.49it/s, loss=0.473]" + "training until 2000: 55%|█████▍ | 1092/2000 [19:22<16:30, 1.09s/it, loss=0.282]" ] }, { @@ -41763,7 +41643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1083/2000 [15:32<10:13, 1.49it/s, loss=0.483]" + "training until 2000: 55%|█████▍ | 1092/2000 [19:22<16:30, 1.09s/it, loss=0.31] " ] }, { @@ -41771,7 +41651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1084/2000 [15:33<10:42, 1.43it/s, loss=0.483]" + "training until 2000: 55%|█████▍ | 1093/2000 [19:23<16:29, 1.09s/it, loss=0.31]" ] }, { @@ -41779,7 +41659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1084/2000 [15:33<10:42, 1.43it/s, loss=0.531]" + "training until 2000: 55%|█████▍ | 1093/2000 [19:23<16:29, 1.09s/it, loss=0.241]" ] }, { @@ -41787,7 +41667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1085/2000 [15:33<11:03, 1.38it/s, loss=0.531]" + "training until 2000: 55%|█████▍ | 1094/2000 [19:24<14:52, 1.01it/s, loss=0.241]" ] }, { @@ -41795,7 +41675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1085/2000 [15:33<11:03, 1.38it/s, loss=0.468]" + "training until 2000: 55%|█████▍ | 1094/2000 [19:24<14:52, 1.01it/s, loss=0.25] " ] }, { @@ -41803,7 +41683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1086/2000 [15:34<11:45, 1.30it/s, loss=0.468]" + "training until 2000: 55%|█████▍ | 1095/2000 [19:24<14:14, 1.06it/s, loss=0.25]" ] }, { @@ -41811,7 +41691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1086/2000 [15:34<11:45, 1.30it/s, loss=0.547]" + "training until 2000: 55%|█████▍ | 1095/2000 [19:24<14:14, 1.06it/s, loss=0.231]" ] }, { @@ -41819,7 +41699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1087/2000 [15:35<13:35, 1.12it/s, loss=0.547]" + "training until 2000: 55%|█████▍ | 1096/2000 [19:25<13:50, 1.09it/s, loss=0.231]" ] }, { @@ -41827,7 +41707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1087/2000 [15:35<13:35, 1.12it/s, loss=0.454]" + "training until 2000: 55%|█████▍ | 1096/2000 [19:25<13:50, 1.09it/s, loss=0.318]" ] }, { @@ -41835,7 +41715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1088/2000 [15:37<16:06, 1.06s/it, loss=0.454]" + "training until 2000: 55%|█████▍ | 1097/2000 [19:26<13:05, 1.15it/s, loss=0.318]" ] }, { @@ -41843,7 +41723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1088/2000 [15:37<16:06, 1.06s/it, loss=0.556]" + "training until 2000: 55%|█████▍ | 1097/2000 [19:26<13:05, 1.15it/s, loss=0.257]" ] }, { @@ -41851,7 +41731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1089/2000 [15:38<14:07, 1.07it/s, loss=0.556]" + "training until 2000: 55%|█████▍ | 1098/2000 [19:28<15:57, 1.06s/it, loss=0.257]" ] }, { @@ -41859,7 +41739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 54%|█████▍ | 1089/2000 [15:38<14:07, 1.07it/s, loss=0.47] " + "training until 2000: 55%|█████▍ | 1098/2000 [19:28<15:57, 1.06s/it, loss=0.123]" ] }, { @@ -41867,7 +41747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1090/2000 [15:38<13:46, 1.10it/s, loss=0.47]" + "training until 2000: 55%|█████▍ | 1099/2000 [19:28<15:12, 1.01s/it, loss=0.123]" ] }, { @@ -41875,7 +41755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1090/2000 [15:38<13:46, 1.10it/s, loss=0.504]" + "training until 2000: 55%|█████▍ | 1099/2000 [19:28<15:12, 1.01s/it, loss=0.285]" ] }, { @@ -41883,7 +41763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1091/2000 [15:39<13:38, 1.11it/s, loss=0.504]" + "training until 2000: 55%|█████▌ | 1100/2000 [19:29<14:59, 1.00it/s, loss=0.285]" ] }, { @@ -41891,7 +41771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1091/2000 [15:39<13:38, 1.11it/s, loss=0.492]" + "training until 2000: 55%|█████▌ | 1100/2000 [19:29<14:59, 1.00it/s, loss=0.31] " ] }, { @@ -41899,7 +41779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1092/2000 [15:40<12:37, 1.20it/s, loss=0.492]" + "training until 2000: 55%|█████▌ | 1101/2000 [19:31<15:59, 1.07s/it, loss=0.31]" ] }, { @@ -41907,7 +41787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1092/2000 [15:40<12:37, 1.20it/s, loss=0.488]" + "training until 2000: 55%|█████▌ | 1101/2000 [19:31<15:59, 1.07s/it, loss=0.223]" ] }, { @@ -41915,7 +41795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1093/2000 [15:41<11:55, 1.27it/s, loss=0.488]" + "training until 2000: 55%|█████▌ | 1102/2000 [19:32<16:21, 1.09s/it, loss=0.223]" ] }, { @@ -41923,7 +41803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1093/2000 [15:41<11:55, 1.27it/s, loss=0.463]" + "training until 2000: 55%|█████▌ | 1102/2000 [19:32<16:21, 1.09s/it, loss=0.28] " ] }, { @@ -41931,7 +41811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1094/2000 [15:41<10:56, 1.38it/s, loss=0.463]" + "training until 2000: 55%|█████▌ | 1103/2000 [19:33<16:03, 1.07s/it, loss=0.28]" ] }, { @@ -41939,7 +41819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1094/2000 [15:41<10:56, 1.38it/s, loss=0.45] " + "training until 2000: 55%|█████▌ | 1103/2000 [19:33<16:03, 1.07s/it, loss=0.318]" ] }, { @@ -41947,7 +41827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1095/2000 [15:42<10:15, 1.47it/s, loss=0.45]" + "training until 2000: 55%|█████▌ | 1104/2000 [19:34<15:05, 1.01s/it, loss=0.318]" ] }, { @@ -41955,7 +41835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1095/2000 [15:42<10:15, 1.47it/s, loss=0.483]" + "training until 2000: 55%|█████▌ | 1104/2000 [19:34<15:05, 1.01s/it, loss=0.458]" ] }, { @@ -41963,7 +41843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1096/2000 [15:42<09:26, 1.60it/s, loss=0.483]" + "training until 2000: 55%|█████▌ | 1105/2000 [19:34<14:13, 1.05it/s, loss=0.458]" ] }, { @@ -41971,7 +41851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1096/2000 [15:42<09:26, 1.60it/s, loss=0.491]" + "training until 2000: 55%|█████▌ | 1105/2000 [19:34<14:13, 1.05it/s, loss=0.407]" ] }, { @@ -41979,7 +41859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1097/2000 [15:43<10:37, 1.42it/s, loss=0.491]" + "training until 2000: 55%|█████▌ | 1106/2000 [19:35<13:20, 1.12it/s, loss=0.407]" ] }, { @@ -41987,7 +41867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1097/2000 [15:43<10:37, 1.42it/s, loss=0.458]" + "training until 2000: 55%|█████▌ | 1106/2000 [19:35<13:20, 1.12it/s, loss=0.331]" ] }, { @@ -41995,7 +41875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1098/2000 [15:44<11:40, 1.29it/s, loss=0.458]" + "training until 2000: 55%|█████▌ | 1107/2000 [19:36<14:54, 1.00s/it, loss=0.331]" ] }, { @@ -42003,7 +41883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1098/2000 [15:44<11:40, 1.29it/s, loss=0.498]" + "training until 2000: 55%|█████▌ | 1107/2000 [19:36<14:54, 1.00s/it, loss=0.367]" ] }, { @@ -42011,7 +41891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1099/2000 [15:45<11:25, 1.31it/s, loss=0.498]" + "training until 2000: 55%|█████▌ | 1108/2000 [19:37<13:50, 1.07it/s, loss=0.367]" ] }, { @@ -42019,7 +41899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▍ | 1099/2000 [15:45<11:25, 1.31it/s, loss=0.465]" + "training until 2000: 55%|█████▌ | 1108/2000 [19:37<13:50, 1.07it/s, loss=0.318]" ] }, { @@ -42027,7 +41907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1100/2000 [15:46<12:32, 1.20it/s, loss=0.465]" + "training until 2000: 55%|█████▌ | 1109/2000 [19:38<13:00, 1.14it/s, loss=0.318]" ] }, { @@ -42035,7 +41915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1100/2000 [15:46<12:32, 1.20it/s, loss=0.5] " + "training until 2000: 55%|█████▌ | 1109/2000 [19:38<13:00, 1.14it/s, loss=0.182]" ] }, { @@ -42043,7 +41923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1101/2000 [15:47<11:57, 1.25it/s, loss=0.5]" + "training until 2000: 56%|█████▌ | 1110/2000 [19:39<14:35, 1.02it/s, loss=0.182]" ] }, { @@ -42051,7 +41931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1101/2000 [15:47<11:57, 1.25it/s, loss=0.413]" + "training until 2000: 56%|█████▌ | 1110/2000 [19:39<14:35, 1.02it/s, loss=0.185]" ] }, { @@ -42059,7 +41939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1102/2000 [15:47<11:11, 1.34it/s, loss=0.413]" + "training until 2000: 56%|█████▌ | 1111/2000 [19:40<14:47, 1.00it/s, loss=0.185]" ] }, { @@ -42067,7 +41947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1102/2000 [15:47<11:11, 1.34it/s, loss=0.476]" + "training until 2000: 56%|█████▌ | 1111/2000 [19:40<14:47, 1.00it/s, loss=0.355]" ] }, { @@ -42075,7 +41955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1103/2000 [15:48<09:54, 1.51it/s, loss=0.476]" + "training until 2000: 56%|█████▌ | 1112/2000 [19:41<13:38, 1.09it/s, loss=0.355]" ] }, { @@ -42083,7 +41963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1103/2000 [15:48<09:54, 1.51it/s, loss=0.491]" + "training until 2000: 56%|█████▌ | 1112/2000 [19:41<13:38, 1.09it/s, loss=0.219]" ] }, { @@ -42091,7 +41971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1104/2000 [15:48<10:12, 1.46it/s, loss=0.491]" + "training until 2000: 56%|█████▌ | 1113/2000 [19:42<12:37, 1.17it/s, loss=0.219]" ] }, { @@ -42099,7 +41979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1104/2000 [15:48<10:12, 1.46it/s, loss=0.456]" + "training until 2000: 56%|█████▌ | 1113/2000 [19:42<12:37, 1.17it/s, loss=0.235]" ] }, { @@ -42107,7 +41987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1105/2000 [15:49<10:21, 1.44it/s, loss=0.456]" + "training until 2000: 56%|█████▌ | 1114/2000 [19:43<14:15, 1.04it/s, loss=0.235]" ] }, { @@ -42115,7 +41995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1105/2000 [15:49<10:21, 1.44it/s, loss=0.515]" + "training until 2000: 56%|█████▌ | 1114/2000 [19:43<14:15, 1.04it/s, loss=0.433]" ] }, { @@ -42123,7 +42003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1106/2000 [15:50<11:18, 1.32it/s, loss=0.515]" + "training until 2000: 56%|█████▌ | 1115/2000 [19:44<14:29, 1.02it/s, loss=0.433]" ] }, { @@ -42131,7 +42011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1106/2000 [15:50<11:18, 1.32it/s, loss=0.431]" + "training until 2000: 56%|█████▌ | 1115/2000 [19:44<14:29, 1.02it/s, loss=0.206]" ] }, { @@ -42139,7 +42019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1107/2000 [15:51<13:01, 1.14it/s, loss=0.431]" + "training until 2000: 56%|█████▌ | 1116/2000 [19:45<13:33, 1.09it/s, loss=0.206]" ] }, { @@ -42147,7 +42027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1107/2000 [15:51<13:01, 1.14it/s, loss=0.474]" + "training until 2000: 56%|█████▌ | 1116/2000 [19:45<13:33, 1.09it/s, loss=0.312]" ] }, { @@ -42155,7 +42035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1108/2000 [15:52<12:47, 1.16it/s, loss=0.474]" + "training until 2000: 56%|█████▌ | 1117/2000 [19:46<14:24, 1.02it/s, loss=0.312]" ] }, { @@ -42163,7 +42043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1108/2000 [15:52<12:47, 1.16it/s, loss=0.428]" + "training until 2000: 56%|█████▌ | 1117/2000 [19:46<14:24, 1.02it/s, loss=0.316]" ] }, { @@ -42171,7 +42051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1109/2000 [15:53<12:47, 1.16it/s, loss=0.428]" + "training until 2000: 56%|█████▌ | 1118/2000 [19:47<13:19, 1.10it/s, loss=0.316]" ] }, { @@ -42179,7 +42059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 55%|█████▌ | 1109/2000 [15:53<12:47, 1.16it/s, loss=0.433]" + "training until 2000: 56%|█████▌ | 1118/2000 [19:47<13:19, 1.10it/s, loss=0.242]" ] }, { @@ -42187,7 +42067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1110/2000 [15:54<12:33, 1.18it/s, loss=0.433]" + "training until 2000: 56%|█████▌ | 1119/2000 [19:48<14:54, 1.02s/it, loss=0.242]" ] }, { @@ -42195,7 +42075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1110/2000 [15:54<12:33, 1.18it/s, loss=0.444]" + "training until 2000: 56%|█████▌ | 1119/2000 [19:48<14:54, 1.02s/it, loss=0.267]" ] }, { @@ -42203,7 +42083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1111/2000 [15:55<13:23, 1.11it/s, loss=0.444]" + "training until 2000: 56%|█████▌ | 1120/2000 [19:49<16:50, 1.15s/it, loss=0.267]" ] }, { @@ -42211,7 +42091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1111/2000 [15:55<13:23, 1.11it/s, loss=0.472]" + "training until 2000: 56%|█████▌ | 1120/2000 [19:49<16:50, 1.15s/it, loss=0.268]" ] }, { @@ -42219,7 +42099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1112/2000 [15:55<12:43, 1.16it/s, loss=0.472]" + "training until 2000: 56%|█████▌ | 1121/2000 [19:51<18:01, 1.23s/it, loss=0.268]" ] }, { @@ -42227,7 +42107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1112/2000 [15:55<12:43, 1.16it/s, loss=0.439]" + "training until 2000: 56%|█████▌ | 1121/2000 [19:51<18:01, 1.23s/it, loss=0.452]" ] }, { @@ -42235,7 +42115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1113/2000 [15:56<11:36, 1.27it/s, loss=0.439]" + "training until 2000: 56%|█████▌ | 1122/2000 [19:52<16:49, 1.15s/it, loss=0.452]" ] }, { @@ -42243,7 +42123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1113/2000 [15:56<11:36, 1.27it/s, loss=0.461]" + "training until 2000: 56%|█████▌ | 1122/2000 [19:52<16:49, 1.15s/it, loss=0.194]" ] }, { @@ -42251,7 +42131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1114/2000 [15:57<10:32, 1.40it/s, loss=0.461]" + "training until 2000: 56%|█████▌ | 1123/2000 [19:53<15:26, 1.06s/it, loss=0.194]" ] }, { @@ -42259,7 +42139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1114/2000 [15:57<10:32, 1.40it/s, loss=0.451]" + "training until 2000: 56%|█████▌ | 1123/2000 [19:53<15:26, 1.06s/it, loss=0.27] " ] }, { @@ -42267,7 +42147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1115/2000 [15:57<09:54, 1.49it/s, loss=0.451]" + "training until 2000: 56%|█████▌ | 1124/2000 [19:54<16:45, 1.15s/it, loss=0.27]" ] }, { @@ -42275,7 +42155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1115/2000 [15:57<09:54, 1.49it/s, loss=0.428]" + "training until 2000: 56%|█████▌ | 1124/2000 [19:54<16:45, 1.15s/it, loss=0.22]" ] }, { @@ -42283,7 +42163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1116/2000 [15:58<11:22, 1.29it/s, loss=0.428]" + "training until 2000: 56%|█████▋ | 1125/2000 [19:55<14:44, 1.01s/it, loss=0.22]" ] }, { @@ -42291,7 +42171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1116/2000 [15:58<11:22, 1.29it/s, loss=0.427]" + "training until 2000: 56%|█████▋ | 1125/2000 [19:55<14:44, 1.01s/it, loss=0.178]" ] }, { @@ -42299,7 +42179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1117/2000 [15:59<11:54, 1.24it/s, loss=0.427]" + "training until 2000: 56%|█████▋ | 1126/2000 [19:55<13:37, 1.07it/s, loss=0.178]" ] }, { @@ -42307,7 +42187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1117/2000 [15:59<11:54, 1.24it/s, loss=0.455]" + "training until 2000: 56%|█████▋ | 1126/2000 [19:55<13:37, 1.07it/s, loss=0.297]" ] }, { @@ -42315,7 +42195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1118/2000 [16:00<12:23, 1.19it/s, loss=0.455]" + "training until 2000: 56%|█████▋ | 1127/2000 [19:56<13:30, 1.08it/s, loss=0.297]" ] }, { @@ -42323,7 +42203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1118/2000 [16:00<12:23, 1.19it/s, loss=0.429]" + "training until 2000: 56%|█████▋ | 1127/2000 [19:56<13:30, 1.08it/s, loss=0.264]" ] }, { @@ -42331,7 +42211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1119/2000 [16:01<11:13, 1.31it/s, loss=0.429]" + "training until 2000: 56%|█████▋ | 1128/2000 [19:57<13:27, 1.08it/s, loss=0.264]" ] }, { @@ -42339,7 +42219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1119/2000 [16:01<11:13, 1.31it/s, loss=0.431]" + "training until 2000: 56%|█████▋ | 1128/2000 [19:57<13:27, 1.08it/s, loss=0.403]" ] }, { @@ -42347,7 +42227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1120/2000 [16:01<11:37, 1.26it/s, loss=0.431]" + "training until 2000: 56%|█████▋ | 1129/2000 [19:58<13:07, 1.11it/s, loss=0.403]" ] }, { @@ -42355,7 +42235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1120/2000 [16:01<11:37, 1.26it/s, loss=0.483]" + "training until 2000: 56%|█████▋ | 1129/2000 [19:58<13:07, 1.11it/s, loss=0.185]" ] }, { @@ -42363,7 +42243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1121/2000 [16:02<10:12, 1.44it/s, loss=0.483]" + "training until 2000: 56%|█████▋ | 1130/2000 [19:59<15:25, 1.06s/it, loss=0.185]" ] }, { @@ -42371,7 +42251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1121/2000 [16:02<10:12, 1.44it/s, loss=0.476]" + "training until 2000: 56%|█████▋ | 1130/2000 [19:59<15:25, 1.06s/it, loss=0.282]" ] }, { @@ -42379,7 +42259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1122/2000 [16:03<10:17, 1.42it/s, loss=0.476]" + "training until 2000: 57%|█████▋ | 1131/2000 [20:01<15:34, 1.08s/it, loss=0.282]" ] }, { @@ -42387,7 +42267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1122/2000 [16:03<10:17, 1.42it/s, loss=0.544]" + "training until 2000: 57%|█████▋ | 1131/2000 [20:01<15:34, 1.08s/it, loss=0.41] " ] }, { @@ -42395,7 +42275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1123/2000 [16:03<09:50, 1.48it/s, loss=0.544]" + "training until 2000: 57%|█████▋ | 1132/2000 [20:02<15:39, 1.08s/it, loss=0.41]" ] }, { @@ -42403,7 +42283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1123/2000 [16:03<09:50, 1.48it/s, loss=0.439]" + "training until 2000: 57%|█████▋ | 1132/2000 [20:02<15:39, 1.08s/it, loss=0.353]" ] }, { @@ -42411,7 +42291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1124/2000 [16:04<10:47, 1.35it/s, loss=0.439]" + "training until 2000: 57%|█████▋ | 1133/2000 [20:03<16:39, 1.15s/it, loss=0.353]" ] }, { @@ -42419,7 +42299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▌ | 1124/2000 [16:04<10:47, 1.35it/s, loss=0.474]" + "training until 2000: 57%|█████▋ | 1133/2000 [20:03<16:39, 1.15s/it, loss=0.307]" ] }, { @@ -42427,7 +42307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1125/2000 [16:05<10:29, 1.39it/s, loss=0.474]" + "training until 2000: 57%|█████▋ | 1134/2000 [20:04<15:57, 1.11s/it, loss=0.307]" ] }, { @@ -42435,7 +42315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1125/2000 [16:05<10:29, 1.39it/s, loss=0.47] " + "training until 2000: 57%|█████▋ | 1134/2000 [20:04<15:57, 1.11s/it, loss=0.308]" ] }, { @@ -42443,7 +42323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1126/2000 [16:06<10:31, 1.38it/s, loss=0.47]" + "training until 2000: 57%|█████▋ | 1135/2000 [20:05<16:34, 1.15s/it, loss=0.308]" ] }, { @@ -42451,7 +42331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1126/2000 [16:06<10:31, 1.38it/s, loss=0.537]" + "training until 2000: 57%|█████▋ | 1135/2000 [20:05<16:34, 1.15s/it, loss=0.26] " ] }, { @@ -42459,7 +42339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1127/2000 [16:06<09:35, 1.52it/s, loss=0.537]" + "training until 2000: 57%|█████▋ | 1136/2000 [20:06<15:05, 1.05s/it, loss=0.26]" ] }, { @@ -42467,7 +42347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1127/2000 [16:06<09:35, 1.52it/s, loss=0.458]" + "training until 2000: 57%|█████▋ | 1136/2000 [20:06<15:05, 1.05s/it, loss=0.329]" ] }, { @@ -42475,7 +42355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1128/2000 [16:07<10:41, 1.36it/s, loss=0.458]" + "training until 2000: 57%|█████▋ | 1137/2000 [20:07<14:32, 1.01s/it, loss=0.329]" ] }, { @@ -42483,7 +42363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1128/2000 [16:07<10:41, 1.36it/s, loss=0.491]" + "training until 2000: 57%|█████▋ | 1137/2000 [20:07<14:32, 1.01s/it, loss=0.335]" ] }, { @@ -42491,7 +42371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1129/2000 [16:08<10:19, 1.41it/s, loss=0.491]" + "training until 2000: 57%|█████▋ | 1138/2000 [20:08<15:52, 1.11s/it, loss=0.335]" ] }, { @@ -42499,7 +42379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1129/2000 [16:08<10:19, 1.41it/s, loss=0.47] " + "training until 2000: 57%|█████▋ | 1138/2000 [20:08<15:52, 1.11s/it, loss=0.311]" ] }, { @@ -42507,7 +42387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1130/2000 [16:09<11:37, 1.25it/s, loss=0.47]" + "training until 2000: 57%|█████▋ | 1139/2000 [20:10<16:47, 1.17s/it, loss=0.311]" ] }, { @@ -42515,7 +42395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 56%|█████▋ | 1130/2000 [16:09<11:37, 1.25it/s, loss=0.448]" + "training until 2000: 57%|█████▋ | 1139/2000 [20:10<16:47, 1.17s/it, loss=0.287]" ] }, { @@ -42523,7 +42403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1131/2000 [16:09<10:59, 1.32it/s, loss=0.448]" + "training until 2000: 57%|█████▋ | 1140/2000 [20:11<15:42, 1.10s/it, loss=0.287]" ] }, { @@ -42531,7 +42411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1131/2000 [16:09<10:59, 1.32it/s, loss=0.421]" + "training until 2000: 57%|█████▋ | 1140/2000 [20:11<15:42, 1.10s/it, loss=0.379]" ] }, { @@ -42539,7 +42419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1132/2000 [16:10<11:11, 1.29it/s, loss=0.421]" + "training until 2000: 57%|█████▋ | 1141/2000 [20:12<16:10, 1.13s/it, loss=0.379]" ] }, { @@ -42547,7 +42427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1132/2000 [16:10<11:11, 1.29it/s, loss=0.499]" + "training until 2000: 57%|█████▋ | 1141/2000 [20:12<16:10, 1.13s/it, loss=0.224]" ] }, { @@ -42555,7 +42435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1133/2000 [16:11<11:16, 1.28it/s, loss=0.499]" + "training until 2000: 57%|█████▋ | 1142/2000 [20:13<16:24, 1.15s/it, loss=0.224]" ] }, { @@ -42563,7 +42443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1133/2000 [16:11<11:16, 1.28it/s, loss=0.45] " + "training until 2000: 57%|█████▋ | 1142/2000 [20:13<16:24, 1.15s/it, loss=0.532]" ] }, { @@ -42571,7 +42451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1134/2000 [16:12<11:43, 1.23it/s, loss=0.45]" + "training until 2000: 57%|█████▋ | 1143/2000 [20:14<17:46, 1.24s/it, loss=0.532]" ] }, { @@ -42579,7 +42459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1134/2000 [16:12<11:43, 1.23it/s, loss=0.424]" + "training until 2000: 57%|█████▋ | 1143/2000 [20:14<17:46, 1.24s/it, loss=0.153]" ] }, { @@ -42587,7 +42467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1135/2000 [16:12<11:12, 1.29it/s, loss=0.424]" + "training until 2000: 57%|█████▋ | 1144/2000 [20:15<15:58, 1.12s/it, loss=0.153]" ] }, { @@ -42595,7 +42475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1135/2000 [16:12<11:12, 1.29it/s, loss=0.514]" + "training until 2000: 57%|█████▋ | 1144/2000 [20:15<15:58, 1.12s/it, loss=0.187]" ] }, { @@ -42603,7 +42483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1136/2000 [16:13<11:54, 1.21it/s, loss=0.514]" + "training until 2000: 57%|█████▋ | 1145/2000 [20:16<14:24, 1.01s/it, loss=0.187]" ] }, { @@ -42611,7 +42491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1136/2000 [16:13<11:54, 1.21it/s, loss=0.431]" + "training until 2000: 57%|█████▋ | 1145/2000 [20:16<14:24, 1.01s/it, loss=0.234]" ] }, { @@ -42619,7 +42499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1137/2000 [16:14<10:49, 1.33it/s, loss=0.431]" + "training until 2000: 57%|█████▋ | 1146/2000 [20:17<13:31, 1.05it/s, loss=0.234]" ] }, { @@ -42627,7 +42507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1137/2000 [16:14<10:49, 1.33it/s, loss=0.426]" + "training until 2000: 57%|█████▋ | 1146/2000 [20:17<13:31, 1.05it/s, loss=0.231]" ] }, { @@ -42635,7 +42515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1138/2000 [16:15<11:10, 1.28it/s, loss=0.426]" + "training until 2000: 57%|█████▋ | 1147/2000 [20:18<13:22, 1.06it/s, loss=0.231]" ] }, { @@ -42643,7 +42523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1138/2000 [16:15<11:10, 1.28it/s, loss=0.427]" + "training until 2000: 57%|█████▋ | 1147/2000 [20:18<13:22, 1.06it/s, loss=0.365]" ] }, { @@ -42651,7 +42531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1139/2000 [16:16<11:27, 1.25it/s, loss=0.427]" + "training until 2000: 57%|█████▋ | 1148/2000 [20:19<13:31, 1.05it/s, loss=0.365]" ] }, { @@ -42659,7 +42539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1139/2000 [16:16<11:27, 1.25it/s, loss=0.431]" + "training until 2000: 57%|█████▋ | 1148/2000 [20:19<13:31, 1.05it/s, loss=0.264]" ] }, { @@ -42667,7 +42547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1140/2000 [16:16<10:52, 1.32it/s, loss=0.431]" + "training until 2000: 57%|█████▋ | 1149/2000 [20:20<14:31, 1.02s/it, loss=0.264]" ] }, { @@ -42675,7 +42555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1140/2000 [16:16<10:52, 1.32it/s, loss=0.46] " + "training until 2000: 57%|█████▋ | 1149/2000 [20:20<14:31, 1.02s/it, loss=0.215]" ] }, { @@ -42683,7 +42563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1141/2000 [16:17<11:11, 1.28it/s, loss=0.46]" + "training until 2000: 57%|█████▊ | 1150/2000 [20:21<15:22, 1.08s/it, loss=0.215]" ] }, { @@ -42691,7 +42571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1141/2000 [16:17<11:11, 1.28it/s, loss=0.472]" + "training until 2000: 57%|█████▊ | 1150/2000 [20:21<15:22, 1.08s/it, loss=0.381]" ] }, { @@ -42699,7 +42579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1142/2000 [16:18<11:05, 1.29it/s, loss=0.472]" + "training until 2000: 58%|█████▊ | 1151/2000 [20:22<14:53, 1.05s/it, loss=0.381]" ] }, { @@ -42707,7 +42587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1142/2000 [16:18<11:05, 1.29it/s, loss=0.525]" + "training until 2000: 58%|█████▊ | 1151/2000 [20:22<14:53, 1.05s/it, loss=0.256]" ] }, { @@ -42715,7 +42595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1143/2000 [16:19<11:13, 1.27it/s, loss=0.525]" + "training until 2000: 58%|█████▊ | 1152/2000 [20:23<13:46, 1.03it/s, loss=0.256]" ] }, { @@ -42723,7 +42603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1143/2000 [16:19<11:13, 1.27it/s, loss=0.459]" + "training until 2000: 58%|█████▊ | 1152/2000 [20:23<13:46, 1.03it/s, loss=0.375]" ] }, { @@ -42731,7 +42611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1144/2000 [16:20<11:41, 1.22it/s, loss=0.459]" + "training until 2000: 58%|█████▊ | 1153/2000 [20:24<12:22, 1.14it/s, loss=0.375]" ] }, { @@ -42739,7 +42619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1144/2000 [16:20<11:41, 1.22it/s, loss=0.407]" + "training until 2000: 58%|█████▊ | 1153/2000 [20:24<12:22, 1.14it/s, loss=0.202]" ] }, { @@ -42747,7 +42627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1145/2000 [16:20<11:07, 1.28it/s, loss=0.407]" + "training until 2000: 58%|█████▊ | 1154/2000 [20:25<15:06, 1.07s/it, loss=0.202]" ] }, { @@ -42755,7 +42635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1145/2000 [16:20<11:07, 1.28it/s, loss=0.49] " + "training until 2000: 58%|█████▊ | 1154/2000 [20:25<15:06, 1.07s/it, loss=0.306]" ] }, { @@ -42763,7 +42643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1146/2000 [16:21<12:08, 1.17it/s, loss=0.49]" + "training until 2000: 58%|█████▊ | 1155/2000 [20:26<16:07, 1.15s/it, loss=0.306]" ] }, { @@ -42771,7 +42651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1146/2000 [16:21<12:08, 1.17it/s, loss=0.431]" + "training until 2000: 58%|█████▊ | 1155/2000 [20:26<16:07, 1.15s/it, loss=0.376]" ] }, { @@ -42779,7 +42659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1147/2000 [16:22<12:04, 1.18it/s, loss=0.431]" + "training until 2000: 58%|█████▊ | 1156/2000 [20:28<16:49, 1.20s/it, loss=0.376]" ] }, { @@ -42787,7 +42667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1147/2000 [16:22<12:04, 1.18it/s, loss=0.491]" + "training until 2000: 58%|█████▊ | 1156/2000 [20:28<16:49, 1.20s/it, loss=0.357]" ] }, { @@ -42795,7 +42675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1148/2000 [16:23<10:41, 1.33it/s, loss=0.491]" + "training until 2000: 58%|█████▊ | 1157/2000 [20:29<17:12, 1.22s/it, loss=0.357]" ] }, { @@ -42803,7 +42683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1148/2000 [16:23<10:41, 1.33it/s, loss=0.471]" + "training until 2000: 58%|█████▊ | 1157/2000 [20:29<17:12, 1.22s/it, loss=0.341]" ] }, { @@ -42811,7 +42691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1149/2000 [16:23<10:30, 1.35it/s, loss=0.471]" + "training until 2000: 58%|█████▊ | 1158/2000 [20:30<14:47, 1.05s/it, loss=0.341]" ] }, { @@ -42819,7 +42699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▋ | 1149/2000 [16:23<10:30, 1.35it/s, loss=0.413]" + "training until 2000: 58%|█████▊ | 1158/2000 [20:30<14:47, 1.05s/it, loss=0.355]" ] }, { @@ -42827,7 +42707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▊ | 1150/2000 [16:24<11:13, 1.26it/s, loss=0.413]" + "training until 2000: 58%|█████▊ | 1159/2000 [20:31<14:02, 1.00s/it, loss=0.355]" ] }, { @@ -42835,7 +42715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 57%|█████▊ | 1150/2000 [16:24<11:13, 1.26it/s, loss=0.434]" + "training until 2000: 58%|█████▊ | 1159/2000 [20:31<14:02, 1.00s/it, loss=0.168]" ] }, { @@ -42843,7 +42723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1151/2000 [16:25<11:04, 1.28it/s, loss=0.434]" + "training until 2000: 58%|█████▊ | 1160/2000 [20:31<13:48, 1.01it/s, loss=0.168]" ] }, { @@ -42851,7 +42731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1151/2000 [16:25<11:04, 1.28it/s, loss=0.424]" + "training until 2000: 58%|█████▊ | 1160/2000 [20:31<13:48, 1.01it/s, loss=0.204]" ] }, { @@ -42859,7 +42739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1152/2000 [16:26<10:30, 1.35it/s, loss=0.424]" + "training until 2000: 58%|█████▊ | 1161/2000 [20:32<12:50, 1.09it/s, loss=0.204]" ] }, { @@ -42867,7 +42747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1152/2000 [16:26<10:30, 1.35it/s, loss=0.444]" + "training until 2000: 58%|█████▊ | 1161/2000 [20:32<12:50, 1.09it/s, loss=0.417]" ] }, { @@ -42875,7 +42755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1153/2000 [16:27<10:29, 1.35it/s, loss=0.444]" + "training until 2000: 58%|█████▊ | 1162/2000 [20:33<12:28, 1.12it/s, loss=0.417]" ] }, { @@ -42883,7 +42763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1153/2000 [16:27<10:29, 1.35it/s, loss=0.45] " + "training until 2000: 58%|█████▊ | 1162/2000 [20:33<12:28, 1.12it/s, loss=0.245]" ] }, { @@ -42891,7 +42771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1154/2000 [16:28<11:31, 1.22it/s, loss=0.45]" + "training until 2000: 58%|█████▊ | 1163/2000 [20:34<12:39, 1.10it/s, loss=0.245]" ] }, { @@ -42899,7 +42779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1154/2000 [16:28<11:31, 1.22it/s, loss=0.482]" + "training until 2000: 58%|█████▊ | 1163/2000 [20:34<12:39, 1.10it/s, loss=0.209]" ] }, { @@ -42907,7 +42787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1155/2000 [16:28<10:59, 1.28it/s, loss=0.482]" + "training until 2000: 58%|█████▊ | 1164/2000 [20:35<12:39, 1.10it/s, loss=0.209]" ] }, { @@ -42915,7 +42795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1155/2000 [16:28<10:59, 1.28it/s, loss=0.459]" + "training until 2000: 58%|█████▊ | 1164/2000 [20:35<12:39, 1.10it/s, loss=0.222]" ] }, { @@ -42923,7 +42803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1156/2000 [16:29<09:39, 1.46it/s, loss=0.459]" + "training until 2000: 58%|█████▊ | 1165/2000 [20:36<14:24, 1.04s/it, loss=0.222]" ] }, { @@ -42931,7 +42811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1156/2000 [16:29<09:39, 1.46it/s, loss=0.453]" + "training until 2000: 58%|█████▊ | 1165/2000 [20:36<14:24, 1.04s/it, loss=0.253]" ] }, { @@ -42939,7 +42819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1157/2000 [16:29<09:38, 1.46it/s, loss=0.453]" + "training until 2000: 58%|█████▊ | 1166/2000 [20:37<13:38, 1.02it/s, loss=0.253]" ] }, { @@ -42947,7 +42827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1157/2000 [16:29<09:38, 1.46it/s, loss=0.447]" + "training until 2000: 58%|█████▊ | 1166/2000 [20:37<13:38, 1.02it/s, loss=0.273]" ] }, { @@ -42955,7 +42835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1158/2000 [16:30<10:19, 1.36it/s, loss=0.447]" + "training until 2000: 58%|█████▊ | 1167/2000 [20:38<14:11, 1.02s/it, loss=0.273]" ] }, { @@ -42963,7 +42843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1158/2000 [16:30<10:19, 1.36it/s, loss=0.409]" + "training until 2000: 58%|█████▊ | 1167/2000 [20:38<14:11, 1.02s/it, loss=0.205]" ] }, { @@ -42971,7 +42851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1159/2000 [16:31<10:52, 1.29it/s, loss=0.409]" + "training until 2000: 58%|█████▊ | 1168/2000 [20:39<15:15, 1.10s/it, loss=0.205]" ] }, { @@ -42979,7 +42859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1159/2000 [16:31<10:52, 1.29it/s, loss=0.451]" + "training until 2000: 58%|█████▊ | 1168/2000 [20:39<15:15, 1.10s/it, loss=0.193]" ] }, { @@ -42987,7 +42867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1160/2000 [16:32<11:02, 1.27it/s, loss=0.451]" + "training until 2000: 58%|█████▊ | 1169/2000 [20:40<13:22, 1.04it/s, loss=0.193]" ] }, { @@ -42995,7 +42875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1160/2000 [16:32<11:02, 1.27it/s, loss=0.523]" + "training until 2000: 58%|█████▊ | 1169/2000 [20:40<13:22, 1.04it/s, loss=0.493]" ] }, { @@ -43003,7 +42883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1161/2000 [16:33<11:31, 1.21it/s, loss=0.523]" + "training until 2000: 58%|█████▊ | 1170/2000 [20:41<14:04, 1.02s/it, loss=0.493]" ] }, { @@ -43011,7 +42891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1161/2000 [16:33<11:31, 1.21it/s, loss=0.424]" + "training until 2000: 58%|█████▊ | 1170/2000 [20:41<14:04, 1.02s/it, loss=0.375]" ] }, { @@ -43019,7 +42899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1162/2000 [16:34<11:16, 1.24it/s, loss=0.424]" + "training until 2000: 59%|█████▊ | 1171/2000 [20:42<12:42, 1.09it/s, loss=0.375]" ] }, { @@ -43027,7 +42907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1162/2000 [16:34<11:16, 1.24it/s, loss=0.417]" + "training until 2000: 59%|█████▊ | 1171/2000 [20:42<12:42, 1.09it/s, loss=0.169]" ] }, { @@ -43035,7 +42915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1163/2000 [16:34<10:30, 1.33it/s, loss=0.417]" + "training until 2000: 59%|█████▊ | 1172/2000 [20:43<12:25, 1.11it/s, loss=0.169]" ] }, { @@ -43043,7 +42923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1163/2000 [16:34<10:30, 1.33it/s, loss=0.414]" + "training until 2000: 59%|█████▊ | 1172/2000 [20:43<12:25, 1.11it/s, loss=0.343]" ] }, { @@ -43051,7 +42931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1164/2000 [16:35<10:25, 1.34it/s, loss=0.414]" + "training until 2000: 59%|█████▊ | 1173/2000 [20:44<11:43, 1.18it/s, loss=0.343]" ] }, { @@ -43059,7 +42939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1164/2000 [16:35<10:25, 1.34it/s, loss=0.452]" + "training until 2000: 59%|█████▊ | 1173/2000 [20:44<11:43, 1.18it/s, loss=0.283]" ] }, { @@ -43067,7 +42947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1165/2000 [16:36<10:49, 1.29it/s, loss=0.452]" + "training until 2000: 59%|█████▊ | 1174/2000 [20:44<11:58, 1.15it/s, loss=0.283]" ] }, { @@ -43075,7 +42955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1165/2000 [16:36<10:49, 1.29it/s, loss=0.449]" + "training until 2000: 59%|█████▊ | 1174/2000 [20:44<11:58, 1.15it/s, loss=0.359]" ] }, { @@ -43083,7 +42963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1166/2000 [16:36<10:26, 1.33it/s, loss=0.449]" + "training until 2000: 59%|█████▉ | 1175/2000 [20:46<13:28, 1.02it/s, loss=0.359]" ] }, { @@ -43091,7 +42971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1166/2000 [16:36<10:26, 1.33it/s, loss=0.44] " + "training until 2000: 59%|█████▉ | 1175/2000 [20:46<13:28, 1.02it/s, loss=0.229]" ] }, { @@ -43099,7 +42979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1167/2000 [16:37<10:11, 1.36it/s, loss=0.44]" + "training until 2000: 59%|█████▉ | 1176/2000 [20:47<15:06, 1.10s/it, loss=0.229]" ] }, { @@ -43107,7 +42987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1167/2000 [16:37<10:11, 1.36it/s, loss=0.472]" + "training until 2000: 59%|█████▉ | 1176/2000 [20:47<15:06, 1.10s/it, loss=0.229]" ] }, { @@ -43115,7 +42995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1168/2000 [16:38<09:10, 1.51it/s, loss=0.472]" + "training until 2000: 59%|█████▉ | 1177/2000 [20:48<15:02, 1.10s/it, loss=0.229]" ] }, { @@ -43123,7 +43003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1168/2000 [16:38<09:10, 1.51it/s, loss=0.446]" + "training until 2000: 59%|█████▉ | 1177/2000 [20:48<15:02, 1.10s/it, loss=0.23] " ] }, { @@ -43131,7 +43011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1169/2000 [16:38<09:20, 1.48it/s, loss=0.446]" + "training until 2000: 59%|█████▉ | 1178/2000 [20:49<14:36, 1.07s/it, loss=0.23]" ] }, { @@ -43139,7 +43019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1169/2000 [16:38<09:20, 1.48it/s, loss=0.472]" + "training until 2000: 59%|█████▉ | 1178/2000 [20:49<14:36, 1.07s/it, loss=0.361]" ] }, { @@ -43147,7 +43027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1170/2000 [16:39<09:05, 1.52it/s, loss=0.472]" + "training until 2000: 59%|█████▉ | 1179/2000 [20:50<12:49, 1.07it/s, loss=0.361]" ] }, { @@ -43155,7 +43035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 58%|█████▊ | 1170/2000 [16:39<09:05, 1.52it/s, loss=0.499]" + "training until 2000: 59%|█████▉ | 1179/2000 [20:50<12:49, 1.07it/s, loss=0.295]" ] }, { @@ -43163,7 +43043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1171/2000 [16:40<09:34, 1.44it/s, loss=0.499]" + "training until 2000: 59%|█████▉ | 1180/2000 [20:51<12:32, 1.09it/s, loss=0.295]" ] }, { @@ -43171,7 +43051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1171/2000 [16:40<09:34, 1.44it/s, loss=0.422]" + "training until 2000: 59%|█████▉ | 1180/2000 [20:51<12:32, 1.09it/s, loss=0.184]" ] }, { @@ -43179,7 +43059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1172/2000 [16:41<10:03, 1.37it/s, loss=0.422]" + "training until 2000: 59%|█████▉ | 1181/2000 [20:51<11:08, 1.23it/s, loss=0.184]" ] }, { @@ -43187,7 +43067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1172/2000 [16:41<10:03, 1.37it/s, loss=0.426]" + "training until 2000: 59%|█████▉ | 1181/2000 [20:51<11:08, 1.23it/s, loss=0.361]" ] }, { @@ -43195,7 +43075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1173/2000 [16:42<11:19, 1.22it/s, loss=0.426]" + "training until 2000: 59%|█████▉ | 1182/2000 [20:52<12:06, 1.13it/s, loss=0.361]" ] }, { @@ -43203,7 +43083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1173/2000 [16:42<11:19, 1.22it/s, loss=0.412]" + "training until 2000: 59%|█████▉ | 1182/2000 [20:52<12:06, 1.13it/s, loss=0.179]" ] }, { @@ -43211,7 +43091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1174/2000 [16:42<11:13, 1.23it/s, loss=0.412]" + "training until 2000: 59%|█████▉ | 1183/2000 [20:53<11:40, 1.17it/s, loss=0.179]" ] }, { @@ -43219,7 +43099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▊ | 1174/2000 [16:42<11:13, 1.23it/s, loss=0.524]" + "training until 2000: 59%|█████▉ | 1183/2000 [20:53<11:40, 1.17it/s, loss=0.3] " ] }, { @@ -43227,7 +43107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1175/2000 [16:43<12:08, 1.13it/s, loss=0.524]" + "training until 2000: 59%|█████▉ | 1184/2000 [20:54<12:12, 1.11it/s, loss=0.3]" ] }, { @@ -43235,7 +43115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1175/2000 [16:43<12:08, 1.13it/s, loss=0.399]" + "training until 2000: 59%|█████▉ | 1184/2000 [20:54<12:12, 1.11it/s, loss=0.378]" ] }, { @@ -43243,7 +43123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1176/2000 [16:44<10:50, 1.27it/s, loss=0.399]" + "training until 2000: 59%|█████▉ | 1185/2000 [20:55<12:48, 1.06it/s, loss=0.378]" ] }, { @@ -43251,7 +43131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1176/2000 [16:44<10:50, 1.27it/s, loss=0.456]" + "training until 2000: 59%|█████▉ | 1185/2000 [20:55<12:48, 1.06it/s, loss=0.274]" ] }, { @@ -43259,7 +43139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1177/2000 [16:45<11:06, 1.24it/s, loss=0.456]" + "training until 2000: 59%|█████▉ | 1186/2000 [20:56<14:03, 1.04s/it, loss=0.274]" ] }, { @@ -43267,7 +43147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1177/2000 [16:45<11:06, 1.24it/s, loss=0.456]" + "training until 2000: 59%|█████▉ | 1186/2000 [20:56<14:03, 1.04s/it, loss=0.334]" ] }, { @@ -43275,7 +43155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1178/2000 [16:46<11:03, 1.24it/s, loss=0.456]" + "training until 2000: 59%|█████▉ | 1187/2000 [20:57<14:02, 1.04s/it, loss=0.334]" ] }, { @@ -43283,7 +43163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1178/2000 [16:46<11:03, 1.24it/s, loss=0.43] " + "training until 2000: 59%|█████▉ | 1187/2000 [20:57<14:02, 1.04s/it, loss=0.16] " ] }, { @@ -43291,7 +43171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1179/2000 [16:46<10:55, 1.25it/s, loss=0.43]" + "training until 2000: 59%|█████▉ | 1188/2000 [20:59<15:58, 1.18s/it, loss=0.16]" ] }, { @@ -43299,7 +43179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1179/2000 [16:46<10:55, 1.25it/s, loss=0.442]" + "training until 2000: 59%|█████▉ | 1188/2000 [20:59<15:58, 1.18s/it, loss=0.278]" ] }, { @@ -43307,7 +43187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1180/2000 [16:47<10:23, 1.32it/s, loss=0.442]" + "training until 2000: 59%|█████▉ | 1189/2000 [21:00<14:00, 1.04s/it, loss=0.278]" ] }, { @@ -43315,7 +43195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1180/2000 [16:47<10:23, 1.32it/s, loss=0.472]" + "training until 2000: 59%|█████▉ | 1189/2000 [21:00<14:00, 1.04s/it, loss=0.279]" ] }, { @@ -43323,7 +43203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1181/2000 [16:48<11:32, 1.18it/s, loss=0.472]" + "training until 2000: 60%|█████▉ | 1190/2000 [21:00<12:03, 1.12it/s, loss=0.279]" ] }, { @@ -43331,7 +43211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1181/2000 [16:48<11:32, 1.18it/s, loss=0.41] " + "training until 2000: 60%|█████▉ | 1190/2000 [21:00<12:03, 1.12it/s, loss=0.284]" ] }, { @@ -43339,7 +43219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1182/2000 [16:49<10:52, 1.25it/s, loss=0.41]" + "training until 2000: 60%|█████▉ | 1191/2000 [21:01<11:18, 1.19it/s, loss=0.284]" ] }, { @@ -43347,7 +43227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1182/2000 [16:49<10:52, 1.25it/s, loss=0.422]" + "training until 2000: 60%|█████▉ | 1191/2000 [21:01<11:18, 1.19it/s, loss=0.181]" ] }, { @@ -43355,7 +43235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1183/2000 [16:49<10:06, 1.35it/s, loss=0.422]" + "training until 2000: 60%|█████▉ | 1192/2000 [21:02<13:05, 1.03it/s, loss=0.181]" ] }, { @@ -43363,7 +43243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1183/2000 [16:49<10:06, 1.35it/s, loss=0.417]" + "training until 2000: 60%|█████▉ | 1192/2000 [21:02<13:05, 1.03it/s, loss=0.311]" ] }, { @@ -43371,7 +43251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1184/2000 [16:50<09:59, 1.36it/s, loss=0.417]" + "training until 2000: 60%|█████▉ | 1193/2000 [21:03<12:54, 1.04it/s, loss=0.311]" ] }, { @@ -43379,7 +43259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1184/2000 [16:50<09:59, 1.36it/s, loss=0.462]" + "training until 2000: 60%|█████▉ | 1193/2000 [21:03<12:54, 1.04it/s, loss=0.283]" ] }, { @@ -43387,7 +43267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1185/2000 [16:51<09:55, 1.37it/s, loss=0.462]" + "training until 2000: 60%|█████▉ | 1194/2000 [21:04<11:44, 1.14it/s, loss=0.283]" ] }, { @@ -43395,7 +43275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1185/2000 [16:51<09:55, 1.37it/s, loss=0.406]" + "training until 2000: 60%|█████▉ | 1194/2000 [21:04<11:44, 1.14it/s, loss=0.276]" ] }, { @@ -43403,7 +43283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1186/2000 [16:52<09:27, 1.43it/s, loss=0.406]" + "training until 2000: 60%|█████▉ | 1195/2000 [21:05<12:17, 1.09it/s, loss=0.276]" ] }, { @@ -43411,7 +43291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1186/2000 [16:52<09:27, 1.43it/s, loss=0.467]" + "training until 2000: 60%|█████▉ | 1195/2000 [21:05<12:17, 1.09it/s, loss=0.242]" ] }, { @@ -43419,7 +43299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1187/2000 [16:53<11:36, 1.17it/s, loss=0.467]" + "training until 2000: 60%|█████▉ | 1196/2000 [21:06<12:12, 1.10it/s, loss=0.242]" ] }, { @@ -43427,7 +43307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1187/2000 [16:53<11:36, 1.17it/s, loss=0.433]" + "training until 2000: 60%|█████▉ | 1196/2000 [21:06<12:12, 1.10it/s, loss=0.288]" ] }, { @@ -43435,7 +43315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1188/2000 [16:53<10:49, 1.25it/s, loss=0.433]" + "training until 2000: 60%|█████▉ | 1197/2000 [21:07<12:52, 1.04it/s, loss=0.288]" ] }, { @@ -43443,7 +43323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1188/2000 [16:53<10:49, 1.25it/s, loss=0.429]" + "training until 2000: 60%|█████▉ | 1197/2000 [21:07<12:52, 1.04it/s, loss=0.388]" ] }, { @@ -43451,7 +43331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1189/2000 [16:54<10:38, 1.27it/s, loss=0.429]" + "training until 2000: 60%|█████▉ | 1198/2000 [21:08<12:47, 1.05it/s, loss=0.388]" ] }, { @@ -43459,7 +43339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 59%|█████▉ | 1189/2000 [16:54<10:38, 1.27it/s, loss=0.475]" + "training until 2000: 60%|█████▉ | 1198/2000 [21:08<12:47, 1.05it/s, loss=0.316]" ] }, { @@ -43467,7 +43347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1190/2000 [16:55<09:55, 1.36it/s, loss=0.475]" + "training until 2000: 60%|█████▉ | 1199/2000 [21:09<11:59, 1.11it/s, loss=0.316]" ] }, { @@ -43475,7 +43355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1190/2000 [16:55<09:55, 1.36it/s, loss=0.48] " + "training until 2000: 60%|█████▉ | 1199/2000 [21:09<11:59, 1.11it/s, loss=0.333]" ] }, { @@ -43483,7 +43363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1191/2000 [16:55<09:28, 1.42it/s, loss=0.48]" + "training until 2000: 60%|██████ | 1200/2000 [21:10<14:02, 1.05s/it, loss=0.333]" ] }, { @@ -43491,7 +43371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1191/2000 [16:55<09:28, 1.42it/s, loss=0.421]" + "training until 2000: 60%|██████ | 1200/2000 [21:10<14:02, 1.05s/it, loss=0.172]" ] }, { @@ -43499,7 +43379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1192/2000 [16:56<09:59, 1.35it/s, loss=0.421]" + "training until 2000: 60%|██████ | 1201/2000 [21:11<13:31, 1.02s/it, loss=0.172]" ] }, { @@ -43507,7 +43387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1192/2000 [16:56<09:59, 1.35it/s, loss=0.423]" + "training until 2000: 60%|██████ | 1201/2000 [21:11<13:31, 1.02s/it, loss=0.213]" ] }, { @@ -43515,7 +43395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1193/2000 [16:57<11:00, 1.22it/s, loss=0.423]" + "training until 2000: 60%|██████ | 1202/2000 [21:12<12:20, 1.08it/s, loss=0.213]" ] }, { @@ -43523,7 +43403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1193/2000 [16:57<11:00, 1.22it/s, loss=0.424]" + "training until 2000: 60%|██████ | 1202/2000 [21:12<12:20, 1.08it/s, loss=0.291]" ] }, { @@ -43531,7 +43411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1194/2000 [16:58<10:35, 1.27it/s, loss=0.424]" + "training until 2000: 60%|██████ | 1203/2000 [21:12<11:28, 1.16it/s, loss=0.291]" ] }, { @@ -43539,7 +43419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1194/2000 [16:58<10:35, 1.27it/s, loss=0.455]" + "training until 2000: 60%|██████ | 1203/2000 [21:12<11:28, 1.16it/s, loss=0.208]" ] }, { @@ -43547,7 +43427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1195/2000 [16:59<10:09, 1.32it/s, loss=0.455]" + "training until 2000: 60%|██████ | 1204/2000 [21:13<12:44, 1.04it/s, loss=0.208]" ] }, { @@ -43555,7 +43435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1195/2000 [16:59<10:09, 1.32it/s, loss=0.419]" + "training until 2000: 60%|██████ | 1204/2000 [21:13<12:44, 1.04it/s, loss=0.309]" ] }, { @@ -43563,7 +43443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1196/2000 [17:00<11:08, 1.20it/s, loss=0.419]" + "training until 2000: 60%|██████ | 1205/2000 [21:14<12:11, 1.09it/s, loss=0.309]" ] }, { @@ -43571,7 +43451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1196/2000 [17:00<11:08, 1.20it/s, loss=0.438]" + "training until 2000: 60%|██████ | 1205/2000 [21:14<12:11, 1.09it/s, loss=0.35] " ] }, { @@ -43579,7 +43459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1197/2000 [17:00<10:44, 1.25it/s, loss=0.438]" + "training until 2000: 60%|██████ | 1206/2000 [21:15<10:57, 1.21it/s, loss=0.35]" ] }, { @@ -43587,7 +43467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1197/2000 [17:00<10:44, 1.25it/s, loss=0.45] " + "training until 2000: 60%|██████ | 1206/2000 [21:15<10:57, 1.21it/s, loss=0.245]" ] }, { @@ -43595,7 +43475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1198/2000 [17:01<10:26, 1.28it/s, loss=0.45]" + "training until 2000: 60%|██████ | 1207/2000 [21:16<12:48, 1.03it/s, loss=0.245]" ] }, { @@ -43603,7 +43483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1198/2000 [17:01<10:26, 1.28it/s, loss=0.426]" + "training until 2000: 60%|██████ | 1207/2000 [21:16<12:48, 1.03it/s, loss=0.283]" ] }, { @@ -43611,7 +43491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1199/2000 [17:02<11:42, 1.14it/s, loss=0.426]" + "training until 2000: 60%|██████ | 1208/2000 [21:17<12:51, 1.03it/s, loss=0.283]" ] }, { @@ -43619,7 +43499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|█████▉ | 1199/2000 [17:02<11:42, 1.14it/s, loss=0.462]" + "training until 2000: 60%|██████ | 1208/2000 [21:17<12:51, 1.03it/s, loss=0.322]" ] }, { @@ -43627,7 +43507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1200/2000 [17:03<11:31, 1.16it/s, loss=0.462]" + "training until 2000: 60%|██████ | 1209/2000 [21:18<12:33, 1.05it/s, loss=0.322]" ] }, { @@ -43635,7 +43515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1200/2000 [17:03<11:31, 1.16it/s, loss=0.49] " + "training until 2000: 60%|██████ | 1209/2000 [21:18<12:33, 1.05it/s, loss=0.371]" ] }, { @@ -43643,7 +43523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1201/2000 [17:04<13:01, 1.02it/s, loss=0.49]" + "training until 2000: 60%|██████ | 1210/2000 [21:19<11:44, 1.12it/s, loss=0.371]" ] }, { @@ -43651,7 +43531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1201/2000 [17:04<13:01, 1.02it/s, loss=0.386]" + "training until 2000: 60%|██████ | 1210/2000 [21:19<11:44, 1.12it/s, loss=0.258]" ] }, { @@ -43659,7 +43539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1202/2000 [17:05<12:33, 1.06it/s, loss=0.386]" + "training until 2000: 61%|██████ | 1211/2000 [21:20<11:54, 1.10it/s, loss=0.258]" ] }, { @@ -43667,7 +43547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1202/2000 [17:05<12:33, 1.06it/s, loss=0.433]" + "training until 2000: 61%|██████ | 1211/2000 [21:20<11:54, 1.10it/s, loss=0.408]" ] }, { @@ -43675,7 +43555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1203/2000 [17:06<11:20, 1.17it/s, loss=0.433]" + "training until 2000: 61%|██████ | 1212/2000 [21:21<11:43, 1.12it/s, loss=0.408]" ] }, { @@ -43683,7 +43563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1203/2000 [17:06<11:20, 1.17it/s, loss=0.427]" + "training until 2000: 61%|██████ | 1212/2000 [21:21<11:43, 1.12it/s, loss=0.236]" ] }, { @@ -43691,7 +43571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1204/2000 [17:06<10:30, 1.26it/s, loss=0.427]" + "training until 2000: 61%|██████ | 1213/2000 [21:21<10:59, 1.19it/s, loss=0.236]" ] }, { @@ -43699,7 +43579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1204/2000 [17:06<10:30, 1.26it/s, loss=0.443]" + "training until 2000: 61%|██████ | 1213/2000 [21:21<10:59, 1.19it/s, loss=0.346]" ] }, { @@ -43707,7 +43587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1205/2000 [17:07<10:33, 1.26it/s, loss=0.443]" + "training until 2000: 61%|██████ | 1214/2000 [21:22<11:16, 1.16it/s, loss=0.346]" ] }, { @@ -43715,7 +43595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1205/2000 [17:07<10:33, 1.26it/s, loss=0.454]" + "training until 2000: 61%|██████ | 1214/2000 [21:22<11:16, 1.16it/s, loss=0.293]" ] }, { @@ -43723,7 +43603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1206/2000 [17:08<10:35, 1.25it/s, loss=0.454]" + "training until 2000: 61%|██████ | 1215/2000 [21:23<11:15, 1.16it/s, loss=0.293]" ] }, { @@ -43731,7 +43611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1206/2000 [17:08<10:35, 1.25it/s, loss=0.444]" + "training until 2000: 61%|██████ | 1215/2000 [21:23<11:15, 1.16it/s, loss=0.279]" ] }, { @@ -43739,7 +43619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1207/2000 [17:09<11:08, 1.19it/s, loss=0.444]" + "training until 2000: 61%|██████ | 1216/2000 [21:24<11:04, 1.18it/s, loss=0.279]" ] }, { @@ -43747,7 +43627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1207/2000 [17:09<11:08, 1.19it/s, loss=0.48] " + "training until 2000: 61%|██████ | 1216/2000 [21:24<11:04, 1.18it/s, loss=0.14] " ] }, { @@ -43755,7 +43635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1208/2000 [17:10<11:52, 1.11it/s, loss=0.48]" + "training until 2000: 61%|██████ | 1217/2000 [21:26<14:34, 1.12s/it, loss=0.14]" ] }, { @@ -43763,7 +43643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1208/2000 [17:10<11:52, 1.11it/s, loss=0.414]" + "training until 2000: 61%|██████ | 1217/2000 [21:26<14:34, 1.12s/it, loss=0.34]" ] }, { @@ -43771,7 +43651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1209/2000 [17:11<11:51, 1.11it/s, loss=0.414]" + "training until 2000: 61%|██████ | 1218/2000 [21:27<14:45, 1.13s/it, loss=0.34]" ] }, { @@ -43779,7 +43659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1209/2000 [17:11<11:51, 1.11it/s, loss=0.445]" + "training until 2000: 61%|██████ | 1218/2000 [21:27<14:45, 1.13s/it, loss=0.307]" ] }, { @@ -43787,7 +43667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1210/2000 [17:12<10:59, 1.20it/s, loss=0.445]" + "training until 2000: 61%|██████ | 1219/2000 [21:28<13:36, 1.05s/it, loss=0.307]" ] }, { @@ -43795,7 +43675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 60%|██████ | 1210/2000 [17:12<10:59, 1.20it/s, loss=0.391]" + "training until 2000: 61%|██████ | 1219/2000 [21:28<13:36, 1.05s/it, loss=0.318]" ] }, { @@ -43803,7 +43683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1211/2000 [17:12<10:32, 1.25it/s, loss=0.391]" + "training until 2000: 61%|██████ | 1220/2000 [21:29<13:17, 1.02s/it, loss=0.318]" ] }, { @@ -43811,7 +43691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1211/2000 [17:12<10:32, 1.25it/s, loss=0.401]" + "training until 2000: 61%|██████ | 1220/2000 [21:29<13:17, 1.02s/it, loss=0.331]" ] }, { @@ -43819,7 +43699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1212/2000 [17:13<10:03, 1.31it/s, loss=0.401]" + "training until 2000: 61%|██████ | 1221/2000 [21:30<13:27, 1.04s/it, loss=0.331]" ] }, { @@ -43827,7 +43707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1212/2000 [17:13<10:03, 1.31it/s, loss=0.421]" + "training until 2000: 61%|██████ | 1221/2000 [21:30<13:27, 1.04s/it, loss=0.22] " ] }, { @@ -43835,7 +43715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1213/2000 [17:14<09:32, 1.38it/s, loss=0.421]" + "training until 2000: 61%|██████ | 1222/2000 [21:31<13:33, 1.05s/it, loss=0.22]" ] }, { @@ -43843,7 +43723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1213/2000 [17:14<09:32, 1.38it/s, loss=0.437]" + "training until 2000: 61%|██████ | 1222/2000 [21:31<13:33, 1.05s/it, loss=0.223]" ] }, { @@ -43851,7 +43731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1214/2000 [17:14<08:50, 1.48it/s, loss=0.437]" + "training until 2000: 61%|██████ | 1223/2000 [21:32<13:38, 1.05s/it, loss=0.223]" ] }, { @@ -43859,7 +43739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1214/2000 [17:14<08:50, 1.48it/s, loss=0.447]" + "training until 2000: 61%|██████ | 1223/2000 [21:32<13:38, 1.05s/it, loss=0.254]" ] }, { @@ -43867,7 +43747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1215/2000 [17:15<08:32, 1.53it/s, loss=0.447]" + "training until 2000: 61%|██████ | 1224/2000 [21:33<12:50, 1.01it/s, loss=0.254]" ] }, { @@ -43875,7 +43755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1215/2000 [17:15<08:32, 1.53it/s, loss=0.471]" + "training until 2000: 61%|██████ | 1224/2000 [21:33<12:50, 1.01it/s, loss=0.279]" ] }, { @@ -43883,7 +43763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1216/2000 [17:15<07:43, 1.69it/s, loss=0.471]" + "training until 2000: 61%|██████▏ | 1225/2000 [21:33<11:16, 1.15it/s, loss=0.279]" ] }, { @@ -43891,7 +43771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1216/2000 [17:15<07:43, 1.69it/s, loss=0.41] " + "training until 2000: 61%|██████▏ | 1225/2000 [21:33<11:16, 1.15it/s, loss=0.329]" ] }, { @@ -43899,7 +43779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1217/2000 [17:16<08:50, 1.47it/s, loss=0.41]" + "training until 2000: 61%|██████▏ | 1226/2000 [21:34<11:31, 1.12it/s, loss=0.329]" ] }, { @@ -43907,7 +43787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1217/2000 [17:16<08:50, 1.47it/s, loss=0.397]" + "training until 2000: 61%|██████▏ | 1226/2000 [21:34<11:31, 1.12it/s, loss=0.349]" ] }, { @@ -43915,7 +43795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1218/2000 [17:17<07:51, 1.66it/s, loss=0.397]" + "training until 2000: 61%|██████▏ | 1227/2000 [21:35<12:39, 1.02it/s, loss=0.349]" ] }, { @@ -43923,7 +43803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1218/2000 [17:17<07:51, 1.66it/s, loss=0.432]" + "training until 2000: 61%|██████▏ | 1227/2000 [21:35<12:39, 1.02it/s, loss=0.288]" ] }, { @@ -43931,7 +43811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1219/2000 [17:17<07:51, 1.66it/s, loss=0.432]" + "training until 2000: 61%|██████▏ | 1228/2000 [21:37<13:07, 1.02s/it, loss=0.288]" ] }, { @@ -43939,7 +43819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1219/2000 [17:17<07:51, 1.66it/s, loss=0.481]" + "training until 2000: 61%|██████▏ | 1228/2000 [21:37<13:07, 1.02s/it, loss=0.335]" ] }, { @@ -43947,7 +43827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1220/2000 [17:18<08:14, 1.58it/s, loss=0.481]" + "training until 2000: 61%|██████▏ | 1229/2000 [21:37<11:00, 1.17it/s, loss=0.335]" ] }, { @@ -43955,7 +43835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1220/2000 [17:18<08:14, 1.58it/s, loss=0.436]" + "training until 2000: 61%|██████▏ | 1229/2000 [21:37<11:00, 1.17it/s, loss=0.304]" ] }, { @@ -43963,7 +43843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1221/2000 [17:19<10:01, 1.30it/s, loss=0.436]" + "training until 2000: 62%|██████▏ | 1230/2000 [21:38<10:16, 1.25it/s, loss=0.304]" ] }, { @@ -43971,7 +43851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1221/2000 [17:19<10:01, 1.30it/s, loss=0.431]" + "training until 2000: 62%|██████▏ | 1230/2000 [21:38<10:16, 1.25it/s, loss=0.246]" ] }, { @@ -43979,7 +43859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1222/2000 [17:20<09:46, 1.33it/s, loss=0.431]" + "training until 2000: 62%|██████▏ | 1231/2000 [21:39<11:38, 1.10it/s, loss=0.246]" ] }, { @@ -43987,7 +43867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1222/2000 [17:20<09:46, 1.33it/s, loss=0.474]" + "training until 2000: 62%|██████▏ | 1231/2000 [21:39<11:38, 1.10it/s, loss=0.324]" ] }, { @@ -43995,7 +43875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1223/2000 [17:21<10:22, 1.25it/s, loss=0.474]" + "training until 2000: 62%|██████▏ | 1232/2000 [21:40<12:41, 1.01it/s, loss=0.324]" ] }, { @@ -44003,7 +43883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1223/2000 [17:21<10:22, 1.25it/s, loss=0.42] " + "training until 2000: 62%|██████▏ | 1232/2000 [21:40<12:41, 1.01it/s, loss=0.218]" ] }, { @@ -44011,7 +43891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1224/2000 [17:22<11:54, 1.09it/s, loss=0.42]" + "training until 2000: 62%|██████▏ | 1233/2000 [21:41<12:30, 1.02it/s, loss=0.218]" ] }, { @@ -44019,7 +43899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████ | 1224/2000 [17:22<11:54, 1.09it/s, loss=0.41]" + "training until 2000: 62%|██████▏ | 1233/2000 [21:41<12:30, 1.02it/s, loss=0.225]" ] }, { @@ -44027,7 +43907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1225/2000 [17:22<10:49, 1.19it/s, loss=0.41]" + "training until 2000: 62%|██████▏ | 1234/2000 [21:42<12:18, 1.04it/s, loss=0.225]" ] }, { @@ -44035,7 +43915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1225/2000 [17:22<10:49, 1.19it/s, loss=0.413]" + "training until 2000: 62%|██████▏ | 1234/2000 [21:42<12:18, 1.04it/s, loss=0.2] " ] }, { @@ -44043,7 +43923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1226/2000 [17:23<10:43, 1.20it/s, loss=0.413]" + "training until 2000: 62%|██████▏ | 1235/2000 [21:43<12:21, 1.03it/s, loss=0.2]" ] }, { @@ -44051,7 +43931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1226/2000 [17:23<10:43, 1.20it/s, loss=0.5] " + "training until 2000: 62%|██████▏ | 1235/2000 [21:43<12:21, 1.03it/s, loss=0.126]" ] }, { @@ -44059,7 +43939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1227/2000 [17:24<09:58, 1.29it/s, loss=0.5]" + "training until 2000: 62%|██████▏ | 1236/2000 [21:44<13:14, 1.04s/it, loss=0.126]" ] }, { @@ -44067,7 +43947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1227/2000 [17:24<09:58, 1.29it/s, loss=0.449]" + "training until 2000: 62%|██████▏ | 1236/2000 [21:44<13:14, 1.04s/it, loss=0.186]" ] }, { @@ -44075,7 +43955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1228/2000 [17:25<09:30, 1.35it/s, loss=0.449]" + "training until 2000: 62%|██████▏ | 1237/2000 [21:45<13:14, 1.04s/it, loss=0.186]" ] }, { @@ -44083,7 +43963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1228/2000 [17:25<09:30, 1.35it/s, loss=0.417]" + "training until 2000: 62%|██████▏ | 1237/2000 [21:45<13:14, 1.04s/it, loss=0.302]" ] }, { @@ -44091,7 +43971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1229/2000 [17:26<12:15, 1.05it/s, loss=0.417]" + "training until 2000: 62%|██████▏ | 1238/2000 [21:46<12:51, 1.01s/it, loss=0.302]" ] }, { @@ -44099,7 +43979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 61%|██████▏ | 1229/2000 [17:26<12:15, 1.05it/s, loss=0.456]" + "training until 2000: 62%|██████▏ | 1238/2000 [21:46<12:51, 1.01s/it, loss=0.149]" ] }, { @@ -44107,7 +43987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1230/2000 [17:27<11:30, 1.12it/s, loss=0.456]" + "training until 2000: 62%|██████▏ | 1239/2000 [21:47<12:16, 1.03it/s, loss=0.149]" ] }, { @@ -44115,7 +43995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1230/2000 [17:27<11:30, 1.12it/s, loss=0.598]" + "training until 2000: 62%|██████▏ | 1239/2000 [21:47<12:16, 1.03it/s, loss=0.207]" ] }, { @@ -44123,7 +44003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1231/2000 [17:28<11:12, 1.14it/s, loss=0.598]" + "training until 2000: 62%|██████▏ | 1240/2000 [21:48<12:14, 1.03it/s, loss=0.207]" ] }, { @@ -44131,7 +44011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1231/2000 [17:28<11:12, 1.14it/s, loss=0.409]" + "training until 2000: 62%|██████▏ | 1240/2000 [21:48<12:14, 1.03it/s, loss=0.227]" ] }, { @@ -44139,7 +44019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1232/2000 [17:29<12:06, 1.06it/s, loss=0.409]" + "training until 2000: 62%|██████▏ | 1241/2000 [21:49<12:05, 1.05it/s, loss=0.227]" ] }, { @@ -44147,7 +44027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1232/2000 [17:29<12:06, 1.06it/s, loss=0.44] " + "training until 2000: 62%|██████▏ | 1241/2000 [21:49<12:05, 1.05it/s, loss=0.275]" ] }, { @@ -44155,7 +44035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1233/2000 [17:30<11:31, 1.11it/s, loss=0.44]" + "training until 2000: 62%|██████▏ | 1242/2000 [21:50<12:32, 1.01it/s, loss=0.275]" ] }, { @@ -44163,7 +44043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1233/2000 [17:30<11:31, 1.11it/s, loss=0.43]" + "training until 2000: 62%|██████▏ | 1242/2000 [21:50<12:32, 1.01it/s, loss=0.297]" ] }, { @@ -44171,7 +44051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1234/2000 [17:30<11:06, 1.15it/s, loss=0.43]" + "training until 2000: 62%|██████▏ | 1243/2000 [21:51<10:58, 1.15it/s, loss=0.297]" ] }, { @@ -44179,7 +44059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1234/2000 [17:30<11:06, 1.15it/s, loss=0.404]" + "training until 2000: 62%|██████▏ | 1243/2000 [21:51<10:58, 1.15it/s, loss=0.204]" ] }, { @@ -44187,7 +44067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1235/2000 [17:31<11:09, 1.14it/s, loss=0.404]" + "training until 2000: 62%|██████▏ | 1244/2000 [21:51<10:39, 1.18it/s, loss=0.204]" ] }, { @@ -44195,7 +44075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1235/2000 [17:31<11:09, 1.14it/s, loss=0.472]" + "training until 2000: 62%|██████▏ | 1244/2000 [21:51<10:39, 1.18it/s, loss=0.395]" ] }, { @@ -44203,7 +44083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1236/2000 [17:32<10:26, 1.22it/s, loss=0.472]" + "training until 2000: 62%|██████▏ | 1245/2000 [21:52<10:39, 1.18it/s, loss=0.395]" ] }, { @@ -44211,7 +44091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1236/2000 [17:32<10:26, 1.22it/s, loss=0.431]" + "training until 2000: 62%|██████▏ | 1245/2000 [21:52<10:39, 1.18it/s, loss=0.281]" ] }, { @@ -44219,7 +44099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1237/2000 [17:33<10:44, 1.18it/s, loss=0.431]" + "training until 2000: 62%|██████▏ | 1246/2000 [21:53<10:48, 1.16it/s, loss=0.281]" ] }, { @@ -44227,7 +44107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1237/2000 [17:33<10:44, 1.18it/s, loss=0.397]" + "training until 2000: 62%|██████▏ | 1246/2000 [21:53<10:48, 1.16it/s, loss=0.17] " ] }, { @@ -44235,7 +44115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1238/2000 [17:33<09:57, 1.28it/s, loss=0.397]" + "training until 2000: 62%|██████▏ | 1247/2000 [21:54<11:22, 1.10it/s, loss=0.17]" ] }, { @@ -44243,7 +44123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1238/2000 [17:33<09:57, 1.28it/s, loss=0.413]" + "training until 2000: 62%|██████▏ | 1247/2000 [21:54<11:22, 1.10it/s, loss=0.192]" ] }, { @@ -44251,7 +44131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1239/2000 [17:34<09:47, 1.30it/s, loss=0.413]" + "training until 2000: 62%|██████▏ | 1248/2000 [21:55<10:58, 1.14it/s, loss=0.192]" ] }, { @@ -44259,7 +44139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1239/2000 [17:34<09:47, 1.30it/s, loss=0.372]" + "training until 2000: 62%|██████▏ | 1248/2000 [21:55<10:58, 1.14it/s, loss=0.196]" ] }, { @@ -44267,7 +44147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1240/2000 [17:35<10:30, 1.20it/s, loss=0.372]" + "training until 2000: 62%|██████▏ | 1249/2000 [21:56<12:10, 1.03it/s, loss=0.196]" ] }, { @@ -44275,7 +44155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1240/2000 [17:35<10:30, 1.20it/s, loss=0.446]" + "training until 2000: 62%|██████▏ | 1249/2000 [21:56<12:10, 1.03it/s, loss=0.301]" ] }, { @@ -44283,7 +44163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1241/2000 [17:36<09:40, 1.31it/s, loss=0.446]" + "training until 2000: 62%|██████▎ | 1250/2000 [21:57<13:31, 1.08s/it, loss=0.301]" ] }, { @@ -44291,7 +44171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1241/2000 [17:36<09:40, 1.31it/s, loss=0.423]" + "training until 2000: 62%|██████▎ | 1250/2000 [21:57<13:31, 1.08s/it, loss=0.22] " ] }, { @@ -44299,7 +44179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1242/2000 [17:37<10:07, 1.25it/s, loss=0.423]" + "training until 2000: 63%|██████▎ | 1251/2000 [21:59<13:38, 1.09s/it, loss=0.22]" ] }, { @@ -44307,7 +44187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1242/2000 [17:37<10:07, 1.25it/s, loss=0.509]" + "training until 2000: 63%|██████▎ | 1251/2000 [21:59<13:38, 1.09s/it, loss=0.228]" ] }, { @@ -44315,7 +44195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1243/2000 [17:37<09:36, 1.31it/s, loss=0.509]" + "training until 2000: 63%|██████▎ | 1252/2000 [21:59<12:27, 1.00it/s, loss=0.228]" ] }, { @@ -44323,7 +44203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1243/2000 [17:37<09:36, 1.31it/s, loss=0.493]" + "training until 2000: 63%|██████▎ | 1252/2000 [21:59<12:27, 1.00it/s, loss=0.269]" ] }, { @@ -44331,7 +44211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1244/2000 [17:38<09:28, 1.33it/s, loss=0.493]" + "training until 2000: 63%|██████▎ | 1253/2000 [22:00<11:01, 1.13it/s, loss=0.269]" ] }, { @@ -44339,7 +44219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1244/2000 [17:38<09:28, 1.33it/s, loss=0.469]" + "training until 2000: 63%|██████▎ | 1253/2000 [22:00<11:01, 1.13it/s, loss=0.29] " ] }, { @@ -44347,7 +44227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1245/2000 [17:39<10:02, 1.25it/s, loss=0.469]" + "training until 2000: 63%|██████▎ | 1254/2000 [22:01<11:33, 1.08it/s, loss=0.29]" ] }, { @@ -44355,7 +44235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1245/2000 [17:39<10:02, 1.25it/s, loss=0.423]" + "training until 2000: 63%|██████▎ | 1254/2000 [22:01<11:33, 1.08it/s, loss=0.326]" ] }, { @@ -44363,7 +44243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1246/2000 [17:39<09:01, 1.39it/s, loss=0.423]" + "training until 2000: 63%|██████▎ | 1255/2000 [22:02<11:18, 1.10it/s, loss=0.326]" ] }, { @@ -44371,7 +44251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1246/2000 [17:39<09:01, 1.39it/s, loss=0.491]" + "training until 2000: 63%|██████▎ | 1255/2000 [22:02<11:18, 1.10it/s, loss=0.238]" ] }, { @@ -44379,7 +44259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1247/2000 [17:40<08:46, 1.43it/s, loss=0.491]" + "training until 2000: 63%|██████▎ | 1256/2000 [22:03<11:56, 1.04it/s, loss=0.238]" ] }, { @@ -44387,7 +44267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1247/2000 [17:40<08:46, 1.43it/s, loss=0.426]" + "training until 2000: 63%|██████▎ | 1256/2000 [22:03<11:56, 1.04it/s, loss=0.281]" ] }, { @@ -44395,7 +44275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1248/2000 [17:41<08:24, 1.49it/s, loss=0.426]" + "training until 2000: 63%|██████▎ | 1257/2000 [22:04<12:33, 1.01s/it, loss=0.281]" ] }, { @@ -44403,7 +44283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1248/2000 [17:41<08:24, 1.49it/s, loss=0.412]" + "training until 2000: 63%|██████▎ | 1257/2000 [22:04<12:33, 1.01s/it, loss=0.171]" ] }, { @@ -44411,7 +44291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1249/2000 [17:42<10:05, 1.24it/s, loss=0.412]" + "training until 2000: 63%|██████▎ | 1258/2000 [22:05<13:01, 1.05s/it, loss=0.171]" ] }, { @@ -44419,7 +44299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▏ | 1249/2000 [17:42<10:05, 1.24it/s, loss=0.424]" + "training until 2000: 63%|██████▎ | 1258/2000 [22:05<13:01, 1.05s/it, loss=0.205]" ] }, { @@ -44427,7 +44307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▎ | 1250/2000 [17:43<10:16, 1.22it/s, loss=0.424]" + "training until 2000: 63%|██████▎ | 1259/2000 [22:06<11:50, 1.04it/s, loss=0.205]" ] }, { @@ -44435,7 +44315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 62%|██████▎ | 1250/2000 [17:43<10:16, 1.22it/s, loss=0.411]" + "training until 2000: 63%|██████▎ | 1259/2000 [22:06<11:50, 1.04it/s, loss=0.25] " ] }, { @@ -44443,7 +44323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1251/2000 [17:43<09:55, 1.26it/s, loss=0.411]" + "training until 2000: 63%|██████▎ | 1260/2000 [22:07<11:48, 1.04it/s, loss=0.25]" ] }, { @@ -44451,7 +44331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1251/2000 [17:43<09:55, 1.26it/s, loss=0.41] " + "training until 2000: 63%|██████▎ | 1260/2000 [22:07<11:48, 1.04it/s, loss=0.288]" ] }, { @@ -44459,7 +44339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1252/2000 [17:44<09:43, 1.28it/s, loss=0.41]" + "training until 2000: 63%|██████▎ | 1261/2000 [22:08<11:11, 1.10it/s, loss=0.288]" ] }, { @@ -44467,7 +44347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1252/2000 [17:44<09:43, 1.28it/s, loss=0.458]" + "training until 2000: 63%|██████▎ | 1261/2000 [22:08<11:11, 1.10it/s, loss=0.318]" ] }, { @@ -44475,7 +44355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1253/2000 [17:45<10:11, 1.22it/s, loss=0.458]" + "training until 2000: 63%|██████▎ | 1262/2000 [22:08<09:43, 1.27it/s, loss=0.318]" ] }, { @@ -44483,7 +44363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1253/2000 [17:45<10:11, 1.22it/s, loss=0.427]" + "training until 2000: 63%|██████▎ | 1262/2000 [22:08<09:43, 1.27it/s, loss=0.218]" ] }, { @@ -44491,7 +44371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1254/2000 [17:46<09:35, 1.30it/s, loss=0.427]" + "training until 2000: 63%|██████▎ | 1263/2000 [22:09<10:04, 1.22it/s, loss=0.218]" ] }, { @@ -44499,7 +44379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1254/2000 [17:46<09:35, 1.30it/s, loss=0.426]" + "training until 2000: 63%|██████▎ | 1263/2000 [22:09<10:04, 1.22it/s, loss=0.354]" ] }, { @@ -44507,7 +44387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1255/2000 [17:47<10:17, 1.21it/s, loss=0.426]" + "training until 2000: 63%|██████▎ | 1264/2000 [22:10<10:29, 1.17it/s, loss=0.354]" ] }, { @@ -44515,7 +44395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1255/2000 [17:47<10:17, 1.21it/s, loss=0.488]" + "training until 2000: 63%|██████▎ | 1264/2000 [22:10<10:29, 1.17it/s, loss=0.243]" ] }, { @@ -44523,7 +44403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1256/2000 [17:48<10:15, 1.21it/s, loss=0.488]" + "training until 2000: 63%|██████▎ | 1265/2000 [22:11<09:54, 1.24it/s, loss=0.243]" ] }, { @@ -44531,7 +44411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1256/2000 [17:48<10:15, 1.21it/s, loss=0.378]" + "training until 2000: 63%|██████▎ | 1265/2000 [22:11<09:54, 1.24it/s, loss=0.249]" ] }, { @@ -44539,7 +44419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1257/2000 [17:48<09:07, 1.36it/s, loss=0.378]" + "training until 2000: 63%|██████▎ | 1266/2000 [22:11<09:29, 1.29it/s, loss=0.249]" ] }, { @@ -44547,7 +44427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1257/2000 [17:48<09:07, 1.36it/s, loss=0.4] " + "training until 2000: 63%|██████▎ | 1266/2000 [22:11<09:29, 1.29it/s, loss=0.329]" ] }, { @@ -44555,7 +44435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1258/2000 [17:49<09:08, 1.35it/s, loss=0.4]" + "training until 2000: 63%|██████▎ | 1267/2000 [22:12<08:43, 1.40it/s, loss=0.329]" ] }, { @@ -44563,7 +44443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1258/2000 [17:49<09:08, 1.35it/s, loss=0.383]" + "training until 2000: 63%|██████▎ | 1267/2000 [22:12<08:43, 1.40it/s, loss=0.221]" ] }, { @@ -44571,7 +44451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1259/2000 [17:49<08:32, 1.44it/s, loss=0.383]" + "training until 2000: 63%|██████▎ | 1268/2000 [22:13<08:25, 1.45it/s, loss=0.221]" ] }, { @@ -44579,7 +44459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1259/2000 [17:49<08:32, 1.44it/s, loss=0.465]" + "training until 2000: 63%|██████▎ | 1268/2000 [22:13<08:25, 1.45it/s, loss=0.23] " ] }, { @@ -44587,7 +44467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1260/2000 [17:50<09:24, 1.31it/s, loss=0.465]" + "training until 2000: 63%|██████▎ | 1269/2000 [22:14<09:02, 1.35it/s, loss=0.23]" ] }, { @@ -44595,7 +44475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1260/2000 [17:50<09:24, 1.31it/s, loss=0.435]" + "training until 2000: 63%|██████▎ | 1269/2000 [22:14<09:02, 1.35it/s, loss=0.323]" ] }, { @@ -44603,7 +44483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1261/2000 [17:51<09:05, 1.36it/s, loss=0.435]" + "training until 2000: 64%|██████▎ | 1270/2000 [22:14<09:04, 1.34it/s, loss=0.323]" ] }, { @@ -44611,7 +44491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1261/2000 [17:51<09:05, 1.36it/s, loss=0.407]" + "training until 2000: 64%|██████▎ | 1270/2000 [22:14<09:04, 1.34it/s, loss=0.379]" ] }, { @@ -44619,7 +44499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1262/2000 [17:52<09:18, 1.32it/s, loss=0.407]" + "training until 2000: 64%|██████▎ | 1271/2000 [22:15<09:11, 1.32it/s, loss=0.379]" ] }, { @@ -44627,7 +44507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1262/2000 [17:52<09:18, 1.32it/s, loss=0.406]" + "training until 2000: 64%|██████▎ | 1271/2000 [22:15<09:11, 1.32it/s, loss=0.293]" ] }, { @@ -44635,7 +44515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1263/2000 [17:53<09:44, 1.26it/s, loss=0.406]" + "training until 2000: 64%|██████▎ | 1272/2000 [22:16<11:21, 1.07it/s, loss=0.293]" ] }, { @@ -44643,7 +44523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1263/2000 [17:53<09:44, 1.26it/s, loss=0.409]" + "training until 2000: 64%|██████▎ | 1272/2000 [22:16<11:21, 1.07it/s, loss=0.317]" ] }, { @@ -44651,7 +44531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1264/2000 [17:54<09:44, 1.26it/s, loss=0.409]" + "training until 2000: 64%|██████▎ | 1273/2000 [22:17<10:54, 1.11it/s, loss=0.317]" ] }, { @@ -44659,7 +44539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1264/2000 [17:54<09:44, 1.26it/s, loss=0.393]" + "training until 2000: 64%|██████▎ | 1273/2000 [22:17<10:54, 1.11it/s, loss=0.224]" ] }, { @@ -44667,7 +44547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1265/2000 [17:54<09:52, 1.24it/s, loss=0.393]" + "training until 2000: 64%|██████▎ | 1274/2000 [22:18<10:24, 1.16it/s, loss=0.224]" ] }, { @@ -44675,7 +44555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1265/2000 [17:54<09:52, 1.24it/s, loss=0.473]" + "training until 2000: 64%|██████▎ | 1274/2000 [22:18<10:24, 1.16it/s, loss=0.239]" ] }, { @@ -44683,7 +44563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1266/2000 [17:55<09:38, 1.27it/s, loss=0.473]" + "training until 2000: 64%|██████▍ | 1275/2000 [22:19<10:38, 1.13it/s, loss=0.239]" ] }, { @@ -44691,7 +44571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1266/2000 [17:55<09:38, 1.27it/s, loss=0.391]" + "training until 2000: 64%|██████▍ | 1275/2000 [22:19<10:38, 1.13it/s, loss=0.235]" ] }, { @@ -44699,7 +44579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1267/2000 [17:56<09:07, 1.34it/s, loss=0.391]" + "training until 2000: 64%|██████▍ | 1276/2000 [22:20<11:37, 1.04it/s, loss=0.235]" ] }, { @@ -44707,7 +44587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1267/2000 [17:56<09:07, 1.34it/s, loss=0.423]" + "training until 2000: 64%|██████▍ | 1276/2000 [22:20<11:37, 1.04it/s, loss=0.368]" ] }, { @@ -44715,7 +44595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1268/2000 [17:56<08:44, 1.40it/s, loss=0.423]" + "training until 2000: 64%|██████▍ | 1277/2000 [22:21<10:55, 1.10it/s, loss=0.368]" ] }, { @@ -44723,7 +44603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1268/2000 [17:56<08:44, 1.40it/s, loss=0.419]" + "training until 2000: 64%|██████▍ | 1277/2000 [22:21<10:55, 1.10it/s, loss=0.363]" ] }, { @@ -44731,7 +44611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1269/2000 [17:57<09:41, 1.26it/s, loss=0.419]" + "training until 2000: 64%|██████▍ | 1278/2000 [22:22<10:17, 1.17it/s, loss=0.363]" ] }, { @@ -44739,7 +44619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 63%|██████▎ | 1269/2000 [17:57<09:41, 1.26it/s, loss=0.383]" + "training until 2000: 64%|██████▍ | 1278/2000 [22:22<10:17, 1.17it/s, loss=0.292]" ] }, { @@ -44747,7 +44627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1270/2000 [17:58<09:23, 1.29it/s, loss=0.383]" + "training until 2000: 64%|██████▍ | 1279/2000 [22:23<11:47, 1.02it/s, loss=0.292]" ] }, { @@ -44755,7 +44635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1270/2000 [17:58<09:23, 1.29it/s, loss=0.445]" + "training until 2000: 64%|██████▍ | 1279/2000 [22:23<11:47, 1.02it/s, loss=0.411]" ] }, { @@ -44763,7 +44643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1271/2000 [17:59<08:58, 1.35it/s, loss=0.445]" + "training until 2000: 64%|██████▍ | 1280/2000 [22:24<12:26, 1.04s/it, loss=0.411]" ] }, { @@ -44771,7 +44651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1271/2000 [17:59<08:58, 1.35it/s, loss=0.412]" + "training until 2000: 64%|██████▍ | 1280/2000 [22:24<12:26, 1.04s/it, loss=0.247]" ] }, { @@ -44779,7 +44659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1272/2000 [18:00<09:54, 1.23it/s, loss=0.412]" + "training until 2000: 64%|██████▍ | 1281/2000 [22:25<12:42, 1.06s/it, loss=0.247]" ] }, { @@ -44787,7 +44667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1272/2000 [18:00<09:54, 1.23it/s, loss=0.454]" + "training until 2000: 64%|██████▍ | 1281/2000 [22:25<12:42, 1.06s/it, loss=0.303]" ] }, { @@ -44795,7 +44675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1273/2000 [18:01<09:44, 1.24it/s, loss=0.454]" + "training until 2000: 64%|██████▍ | 1282/2000 [22:26<13:20, 1.12s/it, loss=0.303]" ] }, { @@ -44803,7 +44683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1273/2000 [18:01<09:44, 1.24it/s, loss=0.377]" + "training until 2000: 64%|██████▍ | 1282/2000 [22:26<13:20, 1.12s/it, loss=0.261]" ] }, { @@ -44811,7 +44691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1274/2000 [18:01<09:27, 1.28it/s, loss=0.377]" + "training until 2000: 64%|██████▍ | 1283/2000 [22:27<11:58, 1.00s/it, loss=0.261]" ] }, { @@ -44819,7 +44699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▎ | 1274/2000 [18:01<09:27, 1.28it/s, loss=0.398]" + "training until 2000: 64%|██████▍ | 1283/2000 [22:27<11:58, 1.00s/it, loss=0.344]" ] }, { @@ -44827,7 +44707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1275/2000 [18:02<09:32, 1.27it/s, loss=0.398]" + "training until 2000: 64%|██████▍ | 1284/2000 [22:28<11:15, 1.06it/s, loss=0.344]" ] }, { @@ -44835,7 +44715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1275/2000 [18:02<09:32, 1.27it/s, loss=0.419]" + "training until 2000: 64%|██████▍ | 1284/2000 [22:28<11:15, 1.06it/s, loss=0.229]" ] }, { @@ -44843,7 +44723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1276/2000 [18:03<09:56, 1.21it/s, loss=0.419]" + "training until 2000: 64%|██████▍ | 1285/2000 [22:29<10:59, 1.08it/s, loss=0.229]" ] }, { @@ -44851,7 +44731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1276/2000 [18:03<09:56, 1.21it/s, loss=0.418]" + "training until 2000: 64%|██████▍ | 1285/2000 [22:29<10:59, 1.08it/s, loss=0.24] " ] }, { @@ -44859,7 +44739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1277/2000 [18:03<08:36, 1.40it/s, loss=0.418]" + "training until 2000: 64%|██████▍ | 1286/2000 [22:30<12:23, 1.04s/it, loss=0.24]" ] }, { @@ -44867,7 +44747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1277/2000 [18:03<08:36, 1.40it/s, loss=0.426]" + "training until 2000: 64%|██████▍ | 1286/2000 [22:30<12:23, 1.04s/it, loss=0.404]" ] }, { @@ -44875,7 +44755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1278/2000 [18:04<08:21, 1.44it/s, loss=0.426]" + "training until 2000: 64%|██████▍ | 1287/2000 [22:31<11:40, 1.02it/s, loss=0.404]" ] }, { @@ -44883,7 +44763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1278/2000 [18:04<08:21, 1.44it/s, loss=0.428]" + "training until 2000: 64%|██████▍ | 1287/2000 [22:31<11:40, 1.02it/s, loss=0.234]" ] }, { @@ -44891,7 +44771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1279/2000 [18:05<09:25, 1.27it/s, loss=0.428]" + "training until 2000: 64%|██████▍ | 1288/2000 [22:32<11:53, 1.00s/it, loss=0.234]" ] }, { @@ -44899,7 +44779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1279/2000 [18:05<09:25, 1.27it/s, loss=0.416]" + "training until 2000: 64%|██████▍ | 1288/2000 [22:32<11:53, 1.00s/it, loss=0.239]" ] }, { @@ -44907,7 +44787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1280/2000 [18:06<08:19, 1.44it/s, loss=0.416]" + "training until 2000: 64%|██████▍ | 1289/2000 [22:33<10:21, 1.14it/s, loss=0.239]" ] }, { @@ -44915,7 +44795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1280/2000 [18:06<08:19, 1.44it/s, loss=0.52] " + "training until 2000: 64%|██████▍ | 1289/2000 [22:33<10:21, 1.14it/s, loss=0.404]" ] }, { @@ -44923,7 +44803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1281/2000 [18:06<08:31, 1.41it/s, loss=0.52]" + "training until 2000: 64%|██████▍ | 1290/2000 [22:33<09:45, 1.21it/s, loss=0.404]" ] }, { @@ -44931,7 +44811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1281/2000 [18:06<08:31, 1.41it/s, loss=0.403]" + "training until 2000: 64%|██████▍ | 1290/2000 [22:33<09:45, 1.21it/s, loss=0.241]" ] }, { @@ -44939,7 +44819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1282/2000 [18:07<09:20, 1.28it/s, loss=0.403]" + "training until 2000: 65%|██████▍ | 1291/2000 [22:34<10:22, 1.14it/s, loss=0.241]" ] }, { @@ -44947,7 +44827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1282/2000 [18:07<09:20, 1.28it/s, loss=0.412]" + "training until 2000: 65%|██████▍ | 1291/2000 [22:34<10:22, 1.14it/s, loss=0.362]" ] }, { @@ -44955,7 +44835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1283/2000 [18:08<09:44, 1.23it/s, loss=0.412]" + "training until 2000: 65%|██████▍ | 1292/2000 [22:35<11:19, 1.04it/s, loss=0.362]" ] }, { @@ -44963,7 +44843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1283/2000 [18:08<09:44, 1.23it/s, loss=0.432]" + "training until 2000: 65%|██████▍ | 1292/2000 [22:35<11:19, 1.04it/s, loss=0.283]" ] }, { @@ -44971,7 +44851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1284/2000 [18:09<10:06, 1.18it/s, loss=0.432]" + "training until 2000: 65%|██████▍ | 1293/2000 [22:37<12:39, 1.07s/it, loss=0.283]" ] }, { @@ -44979,7 +44859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1284/2000 [18:09<10:06, 1.18it/s, loss=0.447]" + "training until 2000: 65%|██████▍ | 1293/2000 [22:37<12:39, 1.07s/it, loss=0.246]" ] }, { @@ -44987,7 +44867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1285/2000 [18:10<09:05, 1.31it/s, loss=0.447]" + "training until 2000: 65%|██████▍ | 1294/2000 [22:38<11:52, 1.01s/it, loss=0.246]" ] }, { @@ -44995,7 +44875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1285/2000 [18:10<09:05, 1.31it/s, loss=0.39] " + "training until 2000: 65%|██████▍ | 1294/2000 [22:38<11:52, 1.01s/it, loss=0.19] " ] }, { @@ -45003,7 +44883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1286/2000 [18:10<08:39, 1.37it/s, loss=0.39]" + "training until 2000: 65%|██████▍ | 1295/2000 [22:39<11:25, 1.03it/s, loss=0.19]" ] }, { @@ -45011,7 +44891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1286/2000 [18:10<08:39, 1.37it/s, loss=0.537]" + "training until 2000: 65%|██████▍ | 1295/2000 [22:39<11:25, 1.03it/s, loss=0.219]" ] }, { @@ -45019,7 +44899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1287/2000 [18:11<08:56, 1.33it/s, loss=0.537]" + "training until 2000: 65%|██████▍ | 1296/2000 [22:40<11:28, 1.02it/s, loss=0.219]" ] }, { @@ -45027,7 +44907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1287/2000 [18:11<08:56, 1.33it/s, loss=0.407]" + "training until 2000: 65%|██████▍ | 1296/2000 [22:40<11:28, 1.02it/s, loss=0.319]" ] }, { @@ -45035,7 +44915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1288/2000 [18:12<08:59, 1.32it/s, loss=0.407]" + "training until 2000: 65%|██████▍ | 1297/2000 [22:40<10:10, 1.15it/s, loss=0.319]" ] }, { @@ -45043,7 +44923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1288/2000 [18:12<08:59, 1.32it/s, loss=0.441]" + "training until 2000: 65%|██████▍ | 1297/2000 [22:40<10:10, 1.15it/s, loss=0.236]" ] }, { @@ -45051,7 +44931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1289/2000 [18:12<08:12, 1.44it/s, loss=0.441]" + "training until 2000: 65%|██████▍ | 1298/2000 [22:41<09:25, 1.24it/s, loss=0.236]" ] }, { @@ -45059,7 +44939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1289/2000 [18:12<08:12, 1.44it/s, loss=0.407]" + "training until 2000: 65%|██████▍ | 1298/2000 [22:41<09:25, 1.24it/s, loss=0.299]" ] }, { @@ -45067,7 +44947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1290/2000 [18:13<09:00, 1.31it/s, loss=0.407]" + "training until 2000: 65%|██████▍ | 1299/2000 [22:42<09:09, 1.28it/s, loss=0.299]" ] }, { @@ -45075,7 +44955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 64%|██████▍ | 1290/2000 [18:13<09:00, 1.31it/s, loss=0.434]" + "training until 2000: 65%|██████▍ | 1299/2000 [22:42<09:09, 1.28it/s, loss=0.319]" ] }, { @@ -45083,7 +44963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1291/2000 [18:14<09:05, 1.30it/s, loss=0.434]" + "training until 2000: 65%|██████▌ | 1300/2000 [22:43<10:10, 1.15it/s, loss=0.319]" ] }, { @@ -45091,7 +44971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1291/2000 [18:14<09:05, 1.30it/s, loss=0.429]" + "training until 2000: 65%|██████▌ | 1300/2000 [22:43<10:10, 1.15it/s, loss=0.287]" ] }, { @@ -45099,7 +44979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1292/2000 [18:15<08:53, 1.33it/s, loss=0.429]" + "training until 2000: 65%|██████▌ | 1301/2000 [22:44<10:47, 1.08it/s, loss=0.287]" ] }, { @@ -45107,7 +44987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1292/2000 [18:15<08:53, 1.33it/s, loss=0.384]" + "training until 2000: 65%|██████▌ | 1301/2000 [22:44<10:47, 1.08it/s, loss=0.256]" ] }, { @@ -45115,7 +44995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1293/2000 [18:15<08:03, 1.46it/s, loss=0.384]" + "training until 2000: 65%|██████▌ | 1302/2000 [22:44<10:02, 1.16it/s, loss=0.256]" ] }, { @@ -45123,7 +45003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1293/2000 [18:15<08:03, 1.46it/s, loss=0.446]" + "training until 2000: 65%|██████▌ | 1302/2000 [22:44<10:02, 1.16it/s, loss=0.231]" ] }, { @@ -45131,7 +45011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1294/2000 [18:16<08:56, 1.32it/s, loss=0.446]" + "training until 2000: 65%|██████▌ | 1303/2000 [22:45<10:23, 1.12it/s, loss=0.231]" ] }, { @@ -45139,7 +45019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1294/2000 [18:16<08:56, 1.32it/s, loss=0.394]" + "training until 2000: 65%|██████▌ | 1303/2000 [22:45<10:23, 1.12it/s, loss=0.189]" ] }, { @@ -45147,7 +45027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1295/2000 [18:17<08:33, 1.37it/s, loss=0.394]" + "training until 2000: 65%|██████▌ | 1304/2000 [22:46<09:47, 1.18it/s, loss=0.189]" ] }, { @@ -45155,7 +45035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1295/2000 [18:17<08:33, 1.37it/s, loss=0.38] " + "training until 2000: 65%|██████▌ | 1304/2000 [22:46<09:47, 1.18it/s, loss=0.256]" ] }, { @@ -45163,7 +45043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1296/2000 [18:18<08:50, 1.33it/s, loss=0.38]" + "training until 2000: 65%|██████▌ | 1305/2000 [22:47<08:53, 1.30it/s, loss=0.256]" ] }, { @@ -45171,7 +45051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1296/2000 [18:18<08:50, 1.33it/s, loss=0.406]" + "training until 2000: 65%|██████▌ | 1305/2000 [22:47<08:53, 1.30it/s, loss=0.381]" ] }, { @@ -45179,7 +45059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1297/2000 [18:18<07:59, 1.47it/s, loss=0.406]" + "training until 2000: 65%|██████▌ | 1306/2000 [22:48<09:24, 1.23it/s, loss=0.381]" ] }, { @@ -45187,7 +45067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1297/2000 [18:18<07:59, 1.47it/s, loss=0.429]" + "training until 2000: 65%|██████▌ | 1306/2000 [22:48<09:24, 1.23it/s, loss=0.313]" ] }, { @@ -45195,7 +45075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1298/2000 [18:19<07:48, 1.50it/s, loss=0.429]" + "training until 2000: 65%|██████▌ | 1307/2000 [22:48<09:02, 1.28it/s, loss=0.313]" ] }, { @@ -45203,7 +45083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1298/2000 [18:19<07:48, 1.50it/s, loss=0.395]" + "training until 2000: 65%|██████▌ | 1307/2000 [22:48<09:02, 1.28it/s, loss=0.311]" ] }, { @@ -45211,7 +45091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1299/2000 [18:20<08:47, 1.33it/s, loss=0.395]" + "training until 2000: 65%|██████▌ | 1308/2000 [22:49<09:49, 1.17it/s, loss=0.311]" ] }, { @@ -45219,7 +45099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▍ | 1299/2000 [18:20<08:47, 1.33it/s, loss=0.389]" + "training until 2000: 65%|██████▌ | 1308/2000 [22:49<09:49, 1.17it/s, loss=0.21] " ] }, { @@ -45227,7 +45107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1300/2000 [18:21<08:39, 1.35it/s, loss=0.389]" + "training until 2000: 65%|██████▌ | 1309/2000 [22:50<09:49, 1.17it/s, loss=0.21]" ] }, { @@ -45235,7 +45115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1300/2000 [18:21<08:39, 1.35it/s, loss=0.433]" + "training until 2000: 65%|██████▌ | 1309/2000 [22:50<09:49, 1.17it/s, loss=0.236]" ] }, { @@ -45243,7 +45123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1301/2000 [18:21<07:37, 1.53it/s, loss=0.433]" + "training until 2000: 66%|██████▌ | 1310/2000 [22:51<08:47, 1.31it/s, loss=0.236]" ] }, { @@ -45251,7 +45131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1301/2000 [18:21<07:37, 1.53it/s, loss=0.431]" + "training until 2000: 66%|██████▌ | 1310/2000 [22:51<08:47, 1.31it/s, loss=0.277]" ] }, { @@ -45259,7 +45139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1302/2000 [18:22<07:58, 1.46it/s, loss=0.431]" + "training until 2000: 66%|██████▌ | 1311/2000 [22:52<09:24, 1.22it/s, loss=0.277]" ] }, { @@ -45267,7 +45147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1302/2000 [18:22<07:58, 1.46it/s, loss=0.398]" + "training until 2000: 66%|██████▌ | 1311/2000 [22:52<09:24, 1.22it/s, loss=0.214]" ] }, { @@ -45275,7 +45155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1303/2000 [18:23<08:22, 1.39it/s, loss=0.398]" + "training until 2000: 66%|██████▌ | 1312/2000 [22:53<11:12, 1.02it/s, loss=0.214]" ] }, { @@ -45283,7 +45163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1303/2000 [18:23<08:22, 1.39it/s, loss=0.417]" + "training until 2000: 66%|██████▌ | 1312/2000 [22:53<11:12, 1.02it/s, loss=0.271]" ] }, { @@ -45291,7 +45171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1304/2000 [18:24<10:26, 1.11it/s, loss=0.417]" + "training until 2000: 66%|██████▌ | 1313/2000 [22:54<11:36, 1.01s/it, loss=0.271]" ] }, { @@ -45299,7 +45179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1304/2000 [18:24<10:26, 1.11it/s, loss=0.375]" + "training until 2000: 66%|██████▌ | 1313/2000 [22:54<11:36, 1.01s/it, loss=0.294]" ] }, { @@ -45307,7 +45187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1305/2000 [18:25<09:33, 1.21it/s, loss=0.375]" + "training until 2000: 66%|██████▌ | 1314/2000 [22:55<12:02, 1.05s/it, loss=0.294]" ] }, { @@ -45315,7 +45195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1305/2000 [18:25<09:33, 1.21it/s, loss=0.538]" + "training until 2000: 66%|██████▌ | 1314/2000 [22:55<12:02, 1.05s/it, loss=0.181]" ] }, { @@ -45323,7 +45203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1306/2000 [18:25<09:56, 1.16it/s, loss=0.538]" + "training until 2000: 66%|██████▌ | 1315/2000 [22:56<10:48, 1.06it/s, loss=0.181]" ] }, { @@ -45331,7 +45211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1306/2000 [18:25<09:56, 1.16it/s, loss=0.407]" + "training until 2000: 66%|██████▌ | 1315/2000 [22:56<10:48, 1.06it/s, loss=0.204]" ] }, { @@ -45339,7 +45219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1307/2000 [18:26<09:57, 1.16it/s, loss=0.407]" + "training until 2000: 66%|██████▌ | 1316/2000 [22:57<10:19, 1.10it/s, loss=0.204]" ] }, { @@ -45347,7 +45227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1307/2000 [18:26<09:57, 1.16it/s, loss=0.431]" + "training until 2000: 66%|██████▌ | 1316/2000 [22:57<10:19, 1.10it/s, loss=0.226]" ] }, { @@ -45355,7 +45235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1308/2000 [18:27<09:45, 1.18it/s, loss=0.431]" + "training until 2000: 66%|██████▌ | 1317/2000 [22:58<09:59, 1.14it/s, loss=0.226]" ] }, { @@ -45363,7 +45243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1308/2000 [18:27<09:45, 1.18it/s, loss=0.394]" + "training until 2000: 66%|██████▌ | 1317/2000 [22:58<09:59, 1.14it/s, loss=0.293]" ] }, { @@ -45371,7 +45251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1309/2000 [18:28<09:37, 1.20it/s, loss=0.394]" + "training until 2000: 66%|██████▌ | 1318/2000 [22:58<09:00, 1.26it/s, loss=0.293]" ] }, { @@ -45379,7 +45259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 65%|██████▌ | 1309/2000 [18:28<09:37, 1.20it/s, loss=0.435]" + "training until 2000: 66%|██████▌ | 1318/2000 [22:58<09:00, 1.26it/s, loss=0.242]" ] }, { @@ -45387,7 +45267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1310/2000 [18:29<09:21, 1.23it/s, loss=0.435]" + "training until 2000: 66%|██████▌ | 1319/2000 [22:59<08:39, 1.31it/s, loss=0.242]" ] }, { @@ -45395,7 +45275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1310/2000 [18:29<09:21, 1.23it/s, loss=0.438]" + "training until 2000: 66%|██████▌ | 1319/2000 [22:59<08:39, 1.31it/s, loss=0.362]" ] }, { @@ -45403,7 +45283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1311/2000 [18:30<10:29, 1.09it/s, loss=0.438]" + "training until 2000: 66%|██████▌ | 1320/2000 [23:00<09:59, 1.13it/s, loss=0.362]" ] }, { @@ -45411,7 +45291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1311/2000 [18:30<10:29, 1.09it/s, loss=0.415]" + "training until 2000: 66%|██████▌ | 1320/2000 [23:00<09:59, 1.13it/s, loss=0.232]" ] }, { @@ -45419,7 +45299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1312/2000 [18:31<10:16, 1.12it/s, loss=0.415]" + "training until 2000: 66%|██████▌ | 1321/2000 [23:01<11:43, 1.04s/it, loss=0.232]" ] }, { @@ -45427,7 +45307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1312/2000 [18:31<10:16, 1.12it/s, loss=0.432]" + "training until 2000: 66%|██████▌ | 1321/2000 [23:01<11:43, 1.04s/it, loss=0.186]" ] }, { @@ -45435,7 +45315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1313/2000 [18:32<10:27, 1.10it/s, loss=0.432]" + "training until 2000: 66%|██████▌ | 1322/2000 [23:02<11:19, 1.00s/it, loss=0.186]" ] }, { @@ -45443,7 +45323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1313/2000 [18:32<10:27, 1.10it/s, loss=0.406]" + "training until 2000: 66%|██████▌ | 1322/2000 [23:02<11:19, 1.00s/it, loss=0.281]" ] }, { @@ -45451,7 +45331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1314/2000 [18:32<09:02, 1.26it/s, loss=0.406]" + "training until 2000: 66%|██████▌ | 1323/2000 [23:03<10:48, 1.04it/s, loss=0.281]" ] }, { @@ -45459,7 +45339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1314/2000 [18:32<09:02, 1.26it/s, loss=0.412]" + "training until 2000: 66%|██████▌ | 1323/2000 [23:03<10:48, 1.04it/s, loss=0.226]" ] }, { @@ -45467,7 +45347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1315/2000 [18:33<09:04, 1.26it/s, loss=0.412]" + "training until 2000: 66%|██████▌ | 1324/2000 [23:04<11:26, 1.02s/it, loss=0.226]" ] }, { @@ -45475,7 +45355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1315/2000 [18:33<09:04, 1.26it/s, loss=0.406]" + "training until 2000: 66%|██████▌ | 1324/2000 [23:04<11:26, 1.02s/it, loss=0.295]" ] }, { @@ -45483,7 +45363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1316/2000 [18:34<08:40, 1.31it/s, loss=0.406]" + "training until 2000: 66%|██████▋ | 1325/2000 [23:05<10:31, 1.07it/s, loss=0.295]" ] }, { @@ -45491,7 +45371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1316/2000 [18:34<08:40, 1.31it/s, loss=0.416]" + "training until 2000: 66%|██████▋ | 1325/2000 [23:05<10:31, 1.07it/s, loss=0.318]" ] }, { @@ -45499,7 +45379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1317/2000 [18:34<08:08, 1.40it/s, loss=0.416]" + "training until 2000: 66%|██████▋ | 1326/2000 [23:06<12:04, 1.08s/it, loss=0.318]" ] }, { @@ -45507,7 +45387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1317/2000 [18:34<08:08, 1.40it/s, loss=0.395]" + "training until 2000: 66%|██████▋ | 1326/2000 [23:06<12:04, 1.08s/it, loss=0.309]" ] }, { @@ -45515,7 +45395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1318/2000 [18:35<08:28, 1.34it/s, loss=0.395]" + "training until 2000: 66%|██████▋ | 1327/2000 [23:07<11:33, 1.03s/it, loss=0.309]" ] }, { @@ -45523,7 +45403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1318/2000 [18:35<08:28, 1.34it/s, loss=0.403]" + "training until 2000: 66%|██████▋ | 1327/2000 [23:07<11:33, 1.03s/it, loss=0.283]" ] }, { @@ -45531,7 +45411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1319/2000 [18:36<08:51, 1.28it/s, loss=0.403]" + "training until 2000: 66%|██████▋ | 1328/2000 [23:09<12:24, 1.11s/it, loss=0.283]" ] }, { @@ -45539,7 +45419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1319/2000 [18:36<08:51, 1.28it/s, loss=0.384]" + "training until 2000: 66%|██████▋ | 1328/2000 [23:09<12:24, 1.11s/it, loss=0.193]" ] }, { @@ -45547,7 +45427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1320/2000 [18:37<08:41, 1.30it/s, loss=0.384]" + "training until 2000: 66%|██████▋ | 1329/2000 [23:10<12:59, 1.16s/it, loss=0.193]" ] }, { @@ -45555,7 +45435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1320/2000 [18:37<08:41, 1.30it/s, loss=0.489]" + "training until 2000: 66%|██████▋ | 1329/2000 [23:10<12:59, 1.16s/it, loss=0.2] " ] }, { @@ -45563,7 +45443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1321/2000 [18:37<08:37, 1.31it/s, loss=0.489]" + "training until 2000: 66%|██████▋ | 1330/2000 [23:11<13:46, 1.23s/it, loss=0.2]" ] }, { @@ -45571,7 +45451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1321/2000 [18:37<08:37, 1.31it/s, loss=0.414]" + "training until 2000: 66%|██████▋ | 1330/2000 [23:11<13:46, 1.23s/it, loss=0.242]" ] }, { @@ -45579,7 +45459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1322/2000 [18:38<07:51, 1.44it/s, loss=0.414]" + "training until 2000: 67%|██████▋ | 1331/2000 [23:12<13:08, 1.18s/it, loss=0.242]" ] }, { @@ -45587,7 +45467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1322/2000 [18:38<07:51, 1.44it/s, loss=0.4] " + "training until 2000: 67%|██████▋ | 1331/2000 [23:12<13:08, 1.18s/it, loss=0.264]" ] }, { @@ -45595,7 +45475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1323/2000 [18:39<08:29, 1.33it/s, loss=0.4]" + "training until 2000: 67%|██████▋ | 1332/2000 [23:13<11:14, 1.01s/it, loss=0.264]" ] }, { @@ -45603,7 +45483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1323/2000 [18:39<08:29, 1.33it/s, loss=0.576]" + "training until 2000: 67%|██████▋ | 1332/2000 [23:13<11:14, 1.01s/it, loss=0.244]" ] }, { @@ -45611,7 +45491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1324/2000 [18:40<09:06, 1.24it/s, loss=0.576]" + "training until 2000: 67%|██████▋ | 1333/2000 [23:14<10:44, 1.03it/s, loss=0.244]" ] }, { @@ -45619,7 +45499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▌ | 1324/2000 [18:40<09:06, 1.24it/s, loss=0.444]" + "training until 2000: 67%|██████▋ | 1333/2000 [23:14<10:44, 1.03it/s, loss=0.382]" ] }, { @@ -45627,7 +45507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1325/2000 [18:40<08:25, 1.33it/s, loss=0.444]" + "training until 2000: 67%|██████▋ | 1334/2000 [23:15<09:58, 1.11it/s, loss=0.382]" ] }, { @@ -45635,7 +45515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1325/2000 [18:40<08:25, 1.33it/s, loss=0.466]" + "training until 2000: 67%|██████▋ | 1334/2000 [23:15<09:58, 1.11it/s, loss=0.296]" ] }, { @@ -45643,7 +45523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1326/2000 [18:41<08:17, 1.35it/s, loss=0.466]" + "training until 2000: 67%|██████▋ | 1335/2000 [23:15<09:41, 1.14it/s, loss=0.296]" ] }, { @@ -45651,7 +45531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1326/2000 [18:41<08:17, 1.35it/s, loss=0.448]" + "training until 2000: 67%|██████▋ | 1335/2000 [23:15<09:41, 1.14it/s, loss=0.17] " ] }, { @@ -45659,7 +45539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1327/2000 [18:42<08:33, 1.31it/s, loss=0.448]" + "training until 2000: 67%|██████▋ | 1336/2000 [23:17<10:28, 1.06it/s, loss=0.17]" ] }, { @@ -45667,7 +45547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1327/2000 [18:42<08:33, 1.31it/s, loss=0.393]" + "training until 2000: 67%|██████▋ | 1336/2000 [23:17<10:28, 1.06it/s, loss=0.262]" ] }, { @@ -45675,7 +45555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1328/2000 [18:43<08:18, 1.35it/s, loss=0.393]" + "training until 2000: 67%|██████▋ | 1337/2000 [23:17<09:26, 1.17it/s, loss=0.262]" ] }, { @@ -45683,7 +45563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1328/2000 [18:43<08:18, 1.35it/s, loss=0.396]" + "training until 2000: 67%|██████▋ | 1337/2000 [23:17<09:26, 1.17it/s, loss=0.298]" ] }, { @@ -45691,7 +45571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1329/2000 [18:43<08:12, 1.36it/s, loss=0.396]" + "training until 2000: 67%|██████▋ | 1338/2000 [23:18<08:43, 1.27it/s, loss=0.298]" ] }, { @@ -45699,7 +45579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1329/2000 [18:43<08:12, 1.36it/s, loss=0.4] " + "training until 2000: 67%|██████▋ | 1338/2000 [23:18<08:43, 1.27it/s, loss=0.182]" ] }, { @@ -45707,7 +45587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1330/2000 [18:44<08:16, 1.35it/s, loss=0.4]" + "training until 2000: 67%|██████▋ | 1339/2000 [23:19<08:28, 1.30it/s, loss=0.182]" ] }, { @@ -45715,7 +45595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 66%|██████▋ | 1330/2000 [18:44<08:16, 1.35it/s, loss=0.379]" + "training until 2000: 67%|██████▋ | 1339/2000 [23:19<08:28, 1.30it/s, loss=0.164]" ] }, { @@ -45723,7 +45603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1331/2000 [18:45<08:23, 1.33it/s, loss=0.379]" + "training until 2000: 67%|██████▋ | 1340/2000 [23:20<09:08, 1.20it/s, loss=0.164]" ] }, { @@ -45731,7 +45611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1331/2000 [18:45<08:23, 1.33it/s, loss=0.462]" + "training until 2000: 67%|██████▋ | 1340/2000 [23:20<09:08, 1.20it/s, loss=0.319]" ] }, { @@ -45739,7 +45619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1332/2000 [18:46<08:15, 1.35it/s, loss=0.462]" + "training until 2000: 67%|██████▋ | 1341/2000 [23:21<10:24, 1.06it/s, loss=0.319]" ] }, { @@ -45747,7 +45627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1332/2000 [18:46<08:15, 1.35it/s, loss=0.365]" + "training until 2000: 67%|██████▋ | 1341/2000 [23:21<10:24, 1.06it/s, loss=0.168]" ] }, { @@ -45755,7 +45635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1333/2000 [18:47<09:43, 1.14it/s, loss=0.365]" + "training until 2000: 67%|██████▋ | 1342/2000 [23:21<09:25, 1.16it/s, loss=0.168]" ] }, { @@ -45763,7 +45643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1333/2000 [18:47<09:43, 1.14it/s, loss=0.403]" + "training until 2000: 67%|██████▋ | 1342/2000 [23:21<09:25, 1.16it/s, loss=0.225]" ] }, { @@ -45771,7 +45651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1334/2000 [18:48<10:55, 1.02it/s, loss=0.403]" + "training until 2000: 67%|██████▋ | 1343/2000 [23:22<09:02, 1.21it/s, loss=0.225]" ] }, { @@ -45779,7 +45659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1334/2000 [18:48<10:55, 1.02it/s, loss=0.42] " + "training until 2000: 67%|██████▋ | 1343/2000 [23:22<09:02, 1.21it/s, loss=0.318]" ] }, { @@ -45787,7 +45667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1335/2000 [18:49<11:48, 1.07s/it, loss=0.42]" + "training until 2000: 67%|██████▋ | 1344/2000 [23:24<10:57, 1.00s/it, loss=0.318]" ] }, { @@ -45795,7 +45675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1335/2000 [18:49<11:48, 1.07s/it, loss=0.383]" + "training until 2000: 67%|██████▋ | 1344/2000 [23:24<10:57, 1.00s/it, loss=0.27] " ] }, { @@ -45803,7 +45683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1336/2000 [18:50<11:08, 1.01s/it, loss=0.383]" + "training until 2000: 67%|██████▋ | 1345/2000 [23:24<10:24, 1.05it/s, loss=0.27]" ] }, { @@ -45811,7 +45691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1336/2000 [18:50<11:08, 1.01s/it, loss=0.4] " + "training until 2000: 67%|██████▋ | 1345/2000 [23:24<10:24, 1.05it/s, loss=0.141]" ] }, { @@ -45819,7 +45699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1337/2000 [18:51<11:05, 1.00s/it, loss=0.4]" + "training until 2000: 67%|██████▋ | 1346/2000 [23:26<11:11, 1.03s/it, loss=0.141]" ] }, { @@ -45827,7 +45707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1337/2000 [18:51<11:05, 1.00s/it, loss=0.394]" + "training until 2000: 67%|██████▋ | 1346/2000 [23:26<11:11, 1.03s/it, loss=0.168]" ] }, { @@ -45835,7 +45715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1338/2000 [18:52<09:52, 1.12it/s, loss=0.394]" + "training until 2000: 67%|██████▋ | 1347/2000 [23:27<11:06, 1.02s/it, loss=0.168]" ] }, { @@ -45843,7 +45723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1338/2000 [18:52<09:52, 1.12it/s, loss=0.394]" + "training until 2000: 67%|██████▋ | 1347/2000 [23:27<11:06, 1.02s/it, loss=0.374]" ] }, { @@ -45851,7 +45731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1339/2000 [18:53<09:51, 1.12it/s, loss=0.394]" + "training until 2000: 67%|██████▋ | 1348/2000 [23:28<10:45, 1.01it/s, loss=0.374]" ] }, { @@ -45859,7 +45739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1339/2000 [18:53<09:51, 1.12it/s, loss=0.421]" + "training until 2000: 67%|██████▋ | 1348/2000 [23:28<10:45, 1.01it/s, loss=0.228]" ] }, { @@ -45867,7 +45747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1340/2000 [18:54<10:07, 1.09it/s, loss=0.421]" + "training until 2000: 67%|██████▋ | 1349/2000 [23:29<10:38, 1.02it/s, loss=0.228]" ] }, { @@ -45875,7 +45755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1340/2000 [18:54<10:07, 1.09it/s, loss=0.434]" + "training until 2000: 67%|██████▋ | 1349/2000 [23:29<10:38, 1.02it/s, loss=0.253]" ] }, { @@ -45883,7 +45763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1341/2000 [18:54<09:27, 1.16it/s, loss=0.434]" + "training until 2000: 68%|██████▊ | 1350/2000 [23:29<09:59, 1.08it/s, loss=0.253]" ] }, { @@ -45891,7 +45771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1341/2000 [18:54<09:27, 1.16it/s, loss=0.375]" + "training until 2000: 68%|██████▊ | 1350/2000 [23:29<09:59, 1.08it/s, loss=0.331]" ] }, { @@ -45899,7 +45779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1342/2000 [18:55<09:42, 1.13it/s, loss=0.375]" + "training until 2000: 68%|██████▊ | 1351/2000 [23:30<10:22, 1.04it/s, loss=0.331]" ] }, { @@ -45907,7 +45787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1342/2000 [18:55<09:42, 1.13it/s, loss=0.405]" + "training until 2000: 68%|██████▊ | 1351/2000 [23:30<10:22, 1.04it/s, loss=0.401]" ] }, { @@ -45915,7 +45795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1343/2000 [18:56<09:48, 1.12it/s, loss=0.405]" + "training until 2000: 68%|██████▊ | 1352/2000 [23:31<10:43, 1.01it/s, loss=0.401]" ] }, { @@ -45923,7 +45803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1343/2000 [18:56<09:48, 1.12it/s, loss=0.425]" + "training until 2000: 68%|██████▊ | 1352/2000 [23:31<10:43, 1.01it/s, loss=0.239]" ] }, { @@ -45931,7 +45811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1344/2000 [18:57<10:10, 1.07it/s, loss=0.425]" + "training until 2000: 68%|██████▊ | 1353/2000 [23:33<11:32, 1.07s/it, loss=0.239]" ] }, { @@ -45939,7 +45819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1344/2000 [18:57<10:10, 1.07it/s, loss=0.447]" + "training until 2000: 68%|██████▊ | 1353/2000 [23:33<11:32, 1.07s/it, loss=0.319]" ] }, { @@ -45947,7 +45827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1345/2000 [18:58<10:13, 1.07it/s, loss=0.447]" + "training until 2000: 68%|██████▊ | 1354/2000 [23:34<12:18, 1.14s/it, loss=0.319]" ] }, { @@ -45955,7 +45835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1345/2000 [18:58<10:13, 1.07it/s, loss=0.44] " + "training until 2000: 68%|██████▊ | 1354/2000 [23:34<12:18, 1.14s/it, loss=0.233]" ] }, { @@ -45963,7 +45843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1346/2000 [18:59<09:39, 1.13it/s, loss=0.44]" + "training until 2000: 68%|██████▊ | 1355/2000 [23:35<10:57, 1.02s/it, loss=0.233]" ] }, { @@ -45971,7 +45851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1346/2000 [18:59<09:39, 1.13it/s, loss=0.397]" + "training until 2000: 68%|██████▊ | 1355/2000 [23:35<10:57, 1.02s/it, loss=0.259]" ] }, { @@ -45979,7 +45859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1347/2000 [19:00<09:30, 1.15it/s, loss=0.397]" + "training until 2000: 68%|██████▊ | 1356/2000 [23:35<09:55, 1.08it/s, loss=0.259]" ] }, { @@ -45987,7 +45867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1347/2000 [19:00<09:30, 1.15it/s, loss=0.426]" + "training until 2000: 68%|██████▊ | 1356/2000 [23:35<09:55, 1.08it/s, loss=0.272]" ] }, { @@ -45995,7 +45875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1348/2000 [19:01<09:27, 1.15it/s, loss=0.426]" + "training until 2000: 68%|██████▊ | 1357/2000 [23:37<11:02, 1.03s/it, loss=0.272]" ] }, { @@ -46003,7 +45883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1348/2000 [19:01<09:27, 1.15it/s, loss=0.516]" + "training until 2000: 68%|██████▊ | 1357/2000 [23:37<11:02, 1.03s/it, loss=0.349]" ] }, { @@ -46011,7 +45891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1349/2000 [19:01<08:35, 1.26it/s, loss=0.516]" + "training until 2000: 68%|██████▊ | 1358/2000 [23:38<10:52, 1.02s/it, loss=0.349]" ] }, { @@ -46019,7 +45899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 67%|██████▋ | 1349/2000 [19:01<08:35, 1.26it/s, loss=0.406]" + "training until 2000: 68%|██████▊ | 1358/2000 [23:38<10:52, 1.02s/it, loss=0.261]" ] }, { @@ -46027,7 +45907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1350/2000 [19:02<08:35, 1.26it/s, loss=0.406]" + "training until 2000: 68%|██████▊ | 1359/2000 [23:39<10:35, 1.01it/s, loss=0.261]" ] }, { @@ -46035,7 +45915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1350/2000 [19:02<08:35, 1.26it/s, loss=0.384]" + "training until 2000: 68%|██████▊ | 1359/2000 [23:39<10:35, 1.01it/s, loss=0.236]" ] }, { @@ -46043,7 +45923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1351/2000 [19:03<08:48, 1.23it/s, loss=0.384]" + "training until 2000: 68%|██████▊ | 1360/2000 [23:39<09:57, 1.07it/s, loss=0.236]" ] }, { @@ -46051,7 +45931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1351/2000 [19:03<08:48, 1.23it/s, loss=0.454]" + "training until 2000: 68%|██████▊ | 1360/2000 [23:39<09:57, 1.07it/s, loss=0.323]" ] }, { @@ -46059,7 +45939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1352/2000 [19:04<08:59, 1.20it/s, loss=0.454]" + "training until 2000: 68%|██████▊ | 1361/2000 [23:40<09:53, 1.08it/s, loss=0.323]" ] }, { @@ -46067,7 +45947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1352/2000 [19:04<08:59, 1.20it/s, loss=0.427]" + "training until 2000: 68%|██████▊ | 1361/2000 [23:40<09:53, 1.08it/s, loss=0.197]" ] }, { @@ -46075,7 +45955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1353/2000 [19:05<08:44, 1.23it/s, loss=0.427]" + "training until 2000: 68%|██████▊ | 1362/2000 [23:41<08:58, 1.18it/s, loss=0.197]" ] }, { @@ -46083,7 +45963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1353/2000 [19:05<08:44, 1.23it/s, loss=0.374]" + "training until 2000: 68%|██████▊ | 1362/2000 [23:41<08:58, 1.18it/s, loss=0.207]" ] }, { @@ -46091,7 +45971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1354/2000 [19:05<08:42, 1.24it/s, loss=0.374]" + "training until 2000: 68%|██████▊ | 1363/2000 [23:42<09:34, 1.11it/s, loss=0.207]" ] }, { @@ -46099,7 +45979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1354/2000 [19:05<08:42, 1.24it/s, loss=0.426]" + "training until 2000: 68%|██████▊ | 1363/2000 [23:42<09:34, 1.11it/s, loss=0.311]" ] }, { @@ -46107,7 +45987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1355/2000 [19:06<08:37, 1.25it/s, loss=0.426]" + "training until 2000: 68%|██████▊ | 1364/2000 [23:43<09:21, 1.13it/s, loss=0.311]" ] }, { @@ -46115,7 +45995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1355/2000 [19:06<08:37, 1.25it/s, loss=0.373]" + "training until 2000: 68%|██████▊ | 1364/2000 [23:43<09:21, 1.13it/s, loss=0.224]" ] }, { @@ -46123,7 +46003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1356/2000 [19:07<08:18, 1.29it/s, loss=0.373]" + "training until 2000: 68%|██████▊ | 1365/2000 [23:44<09:44, 1.09it/s, loss=0.224]" ] }, { @@ -46131,7 +46011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1356/2000 [19:07<08:18, 1.29it/s, loss=0.376]" + "training until 2000: 68%|██████▊ | 1365/2000 [23:44<09:44, 1.09it/s, loss=0.335]" ] }, { @@ -46139,7 +46019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1357/2000 [19:08<08:21, 1.28it/s, loss=0.376]" + "training until 2000: 68%|██████▊ | 1366/2000 [23:45<10:15, 1.03it/s, loss=0.335]" ] }, { @@ -46147,7 +46027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1357/2000 [19:08<08:21, 1.28it/s, loss=0.462]" + "training until 2000: 68%|██████▊ | 1366/2000 [23:45<10:15, 1.03it/s, loss=0.183]" ] }, { @@ -46155,7 +46035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1358/2000 [19:08<07:35, 1.41it/s, loss=0.462]" + "training until 2000: 68%|██████▊ | 1367/2000 [23:46<09:55, 1.06it/s, loss=0.183]" ] }, { @@ -46163,7 +46043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1358/2000 [19:08<07:35, 1.41it/s, loss=0.406]" + "training until 2000: 68%|██████▊ | 1367/2000 [23:46<09:55, 1.06it/s, loss=0.306]" ] }, { @@ -46171,7 +46051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1359/2000 [19:09<06:50, 1.56it/s, loss=0.406]" + "training until 2000: 68%|██████▊ | 1368/2000 [23:47<09:42, 1.09it/s, loss=0.306]" ] }, { @@ -46179,7 +46059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1359/2000 [19:09<06:50, 1.56it/s, loss=0.401]" + "training until 2000: 68%|██████▊ | 1368/2000 [23:47<09:42, 1.09it/s, loss=0.348]" ] }, { @@ -46187,7 +46067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1360/2000 [19:09<06:46, 1.57it/s, loss=0.401]" + "training until 2000: 68%|██████▊ | 1369/2000 [23:47<08:53, 1.18it/s, loss=0.348]" ] }, { @@ -46195,7 +46075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1360/2000 [19:09<06:46, 1.57it/s, loss=0.404]" + "training until 2000: 68%|██████▊ | 1369/2000 [23:47<08:53, 1.18it/s, loss=0.286]" ] }, { @@ -46203,7 +46083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1361/2000 [19:10<07:09, 1.49it/s, loss=0.404]" + "training until 2000: 68%|██████▊ | 1370/2000 [23:48<08:49, 1.19it/s, loss=0.286]" ] }, { @@ -46211,7 +46091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1361/2000 [19:10<07:09, 1.49it/s, loss=0.388]" + "training until 2000: 68%|██████▊ | 1370/2000 [23:48<08:49, 1.19it/s, loss=0.297]" ] }, { @@ -46219,7 +46099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1362/2000 [19:11<07:25, 1.43it/s, loss=0.388]" + "training until 2000: 69%|██████▊ | 1371/2000 [23:49<09:00, 1.16it/s, loss=0.297]" ] }, { @@ -46227,7 +46107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1362/2000 [19:11<07:25, 1.43it/s, loss=0.441]" + "training until 2000: 69%|██████▊ | 1371/2000 [23:49<09:00, 1.16it/s, loss=0.316]" ] }, { @@ -46235,7 +46115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1363/2000 [19:12<07:57, 1.33it/s, loss=0.441]" + "training until 2000: 69%|██████▊ | 1372/2000 [23:50<08:37, 1.21it/s, loss=0.316]" ] }, { @@ -46243,7 +46123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1363/2000 [19:12<07:57, 1.33it/s, loss=0.426]" + "training until 2000: 69%|██████▊ | 1372/2000 [23:50<08:37, 1.21it/s, loss=0.169]" ] }, { @@ -46251,7 +46131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1364/2000 [19:13<08:32, 1.24it/s, loss=0.426]" + "training until 2000: 69%|██████▊ | 1373/2000 [23:51<08:09, 1.28it/s, loss=0.169]" ] }, { @@ -46259,7 +46139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1364/2000 [19:13<08:32, 1.24it/s, loss=0.421]" + "training until 2000: 69%|██████▊ | 1373/2000 [23:51<08:09, 1.28it/s, loss=0.258]" ] }, { @@ -46267,7 +46147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1365/2000 [19:13<08:04, 1.31it/s, loss=0.421]" + "training until 2000: 69%|██████▊ | 1374/2000 [23:51<08:03, 1.30it/s, loss=0.258]" ] }, { @@ -46275,7 +46155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1365/2000 [19:13<08:04, 1.31it/s, loss=0.405]" + "training until 2000: 69%|██████▊ | 1374/2000 [23:51<08:03, 1.30it/s, loss=0.202]" ] }, { @@ -46283,7 +46163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1366/2000 [19:14<07:52, 1.34it/s, loss=0.405]" + "training until 2000: 69%|██████▉ | 1375/2000 [23:52<09:13, 1.13it/s, loss=0.202]" ] }, { @@ -46291,7 +46171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1366/2000 [19:14<07:52, 1.34it/s, loss=0.405]" + "training until 2000: 69%|██████▉ | 1375/2000 [23:52<09:13, 1.13it/s, loss=0.139]" ] }, { @@ -46299,7 +46179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1367/2000 [19:15<08:32, 1.24it/s, loss=0.405]" + "training until 2000: 69%|██████▉ | 1376/2000 [23:53<09:34, 1.09it/s, loss=0.139]" ] }, { @@ -46307,7 +46187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1367/2000 [19:15<08:32, 1.24it/s, loss=0.395]" + "training until 2000: 69%|██████▉ | 1376/2000 [23:53<09:34, 1.09it/s, loss=0.187]" ] }, { @@ -46315,7 +46195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1368/2000 [19:16<08:37, 1.22it/s, loss=0.395]" + "training until 2000: 69%|██████▉ | 1377/2000 [23:54<08:32, 1.22it/s, loss=0.187]" ] }, { @@ -46323,7 +46203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1368/2000 [19:16<08:37, 1.22it/s, loss=0.399]" + "training until 2000: 69%|██████▉ | 1377/2000 [23:54<08:32, 1.22it/s, loss=0.264]" ] }, { @@ -46331,7 +46211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1369/2000 [19:17<08:14, 1.28it/s, loss=0.399]" + "training until 2000: 69%|██████▉ | 1378/2000 [23:55<08:25, 1.23it/s, loss=0.264]" ] }, { @@ -46339,7 +46219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1369/2000 [19:17<08:14, 1.28it/s, loss=0.429]" + "training until 2000: 69%|██████▉ | 1378/2000 [23:55<08:25, 1.23it/s, loss=0.232]" ] }, { @@ -46347,7 +46227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1370/2000 [19:17<08:40, 1.21it/s, loss=0.429]" + "training until 2000: 69%|██████▉ | 1379/2000 [23:56<09:35, 1.08it/s, loss=0.232]" ] }, { @@ -46355,7 +46235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 68%|██████▊ | 1370/2000 [19:17<08:40, 1.21it/s, loss=0.427]" + "training until 2000: 69%|██████▉ | 1379/2000 [23:56<09:35, 1.08it/s, loss=0.268]" ] }, { @@ -46363,7 +46243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1371/2000 [19:18<08:19, 1.26it/s, loss=0.427]" + "training until 2000: 69%|██████▉ | 1380/2000 [23:57<09:20, 1.11it/s, loss=0.268]" ] }, { @@ -46371,7 +46251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1371/2000 [19:18<08:19, 1.26it/s, loss=0.38] " + "training until 2000: 69%|██████▉ | 1380/2000 [23:57<09:20, 1.11it/s, loss=0.271]" ] }, { @@ -46379,7 +46259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1372/2000 [19:19<07:52, 1.33it/s, loss=0.38]" + "training until 2000: 69%|██████▉ | 1381/2000 [23:58<08:59, 1.15it/s, loss=0.271]" ] }, { @@ -46387,7 +46267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1372/2000 [19:19<07:52, 1.33it/s, loss=0.454]" + "training until 2000: 69%|██████▉ | 1381/2000 [23:58<08:59, 1.15it/s, loss=0.312]" ] }, { @@ -46395,7 +46275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1373/2000 [19:20<07:53, 1.33it/s, loss=0.454]" + "training until 2000: 69%|██████▉ | 1382/2000 [23:58<08:27, 1.22it/s, loss=0.312]" ] }, { @@ -46403,7 +46283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1373/2000 [19:20<07:53, 1.33it/s, loss=0.444]" + "training until 2000: 69%|██████▉ | 1382/2000 [23:58<08:27, 1.22it/s, loss=0.264]" ] }, { @@ -46411,7 +46291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1374/2000 [19:21<08:55, 1.17it/s, loss=0.444]" + "training until 2000: 69%|██████▉ | 1383/2000 [23:59<08:08, 1.26it/s, loss=0.264]" ] }, { @@ -46419,7 +46299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▊ | 1374/2000 [19:21<08:55, 1.17it/s, loss=0.408]" + "training until 2000: 69%|██████▉ | 1383/2000 [23:59<08:08, 1.26it/s, loss=0.228]" ] }, { @@ -46427,7 +46307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1375/2000 [19:21<08:11, 1.27it/s, loss=0.408]" + "training until 2000: 69%|██████▉ | 1384/2000 [24:00<09:01, 1.14it/s, loss=0.228]" ] }, { @@ -46435,7 +46315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1375/2000 [19:21<08:11, 1.27it/s, loss=0.407]" + "training until 2000: 69%|██████▉ | 1384/2000 [24:00<09:01, 1.14it/s, loss=0.235]" ] }, { @@ -46443,7 +46323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1376/2000 [19:22<08:09, 1.28it/s, loss=0.407]" + "training until 2000: 69%|██████▉ | 1385/2000 [24:01<08:17, 1.24it/s, loss=0.235]" ] }, { @@ -46451,7 +46331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1376/2000 [19:22<08:09, 1.28it/s, loss=0.417]" + "training until 2000: 69%|██████▉ | 1385/2000 [24:01<08:17, 1.24it/s, loss=0.338]" ] }, { @@ -46459,7 +46339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1377/2000 [19:23<08:53, 1.17it/s, loss=0.417]" + "training until 2000: 69%|██████▉ | 1386/2000 [24:02<08:45, 1.17it/s, loss=0.338]" ] }, { @@ -46467,7 +46347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1377/2000 [19:23<08:53, 1.17it/s, loss=0.436]" + "training until 2000: 69%|██████▉ | 1386/2000 [24:02<08:45, 1.17it/s, loss=0.197]" ] }, { @@ -46475,7 +46355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1378/2000 [19:24<09:07, 1.14it/s, loss=0.436]" + "training until 2000: 69%|██████▉ | 1387/2000 [24:03<09:37, 1.06it/s, loss=0.197]" ] }, { @@ -46483,7 +46363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1378/2000 [19:24<09:07, 1.14it/s, loss=0.405]" + "training until 2000: 69%|██████▉ | 1387/2000 [24:03<09:37, 1.06it/s, loss=0.245]" ] }, { @@ -46491,7 +46371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1379/2000 [19:25<09:41, 1.07it/s, loss=0.405]" + "training until 2000: 69%|██████▉ | 1388/2000 [24:04<09:46, 1.04it/s, loss=0.245]" ] }, { @@ -46499,7 +46379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1379/2000 [19:25<09:41, 1.07it/s, loss=0.394]" + "training until 2000: 69%|██████▉ | 1388/2000 [24:04<09:46, 1.04it/s, loss=0.253]" ] }, { @@ -46507,7 +46387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1380/2000 [19:26<08:32, 1.21it/s, loss=0.394]" + "training until 2000: 69%|██████▉ | 1389/2000 [24:05<10:29, 1.03s/it, loss=0.253]" ] }, { @@ -46515,7 +46395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1380/2000 [19:26<08:32, 1.21it/s, loss=0.356]" + "training until 2000: 69%|██████▉ | 1389/2000 [24:05<10:29, 1.03s/it, loss=0.253]" ] }, { @@ -46523,7 +46403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1381/2000 [19:26<08:19, 1.24it/s, loss=0.356]" + "training until 2000: 70%|██████▉ | 1390/2000 [24:06<10:25, 1.03s/it, loss=0.253]" ] }, { @@ -46531,7 +46411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1381/2000 [19:26<08:19, 1.24it/s, loss=0.409]" + "training until 2000: 70%|██████▉ | 1390/2000 [24:06<10:25, 1.03s/it, loss=0.285]" ] }, { @@ -46539,7 +46419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1382/2000 [19:27<07:46, 1.32it/s, loss=0.409]" + "training until 2000: 70%|██████▉ | 1391/2000 [24:08<11:37, 1.15s/it, loss=0.285]" ] }, { @@ -46547,7 +46427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1382/2000 [19:27<07:46, 1.32it/s, loss=0.488]" + "training until 2000: 70%|██████▉ | 1391/2000 [24:08<11:37, 1.15s/it, loss=0.309]" ] }, { @@ -46555,7 +46435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1383/2000 [19:28<07:47, 1.32it/s, loss=0.488]" + "training until 2000: 70%|██████▉ | 1392/2000 [24:09<11:44, 1.16s/it, loss=0.309]" ] }, { @@ -46563,7 +46443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1383/2000 [19:28<07:47, 1.32it/s, loss=0.383]" + "training until 2000: 70%|██████▉ | 1392/2000 [24:09<11:44, 1.16s/it, loss=0.217]" ] }, { @@ -46571,7 +46451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1384/2000 [19:29<07:45, 1.32it/s, loss=0.383]" + "training until 2000: 70%|██████▉ | 1393/2000 [24:10<11:17, 1.12s/it, loss=0.217]" ] }, { @@ -46579,7 +46459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1384/2000 [19:29<07:45, 1.32it/s, loss=0.499]" + "training until 2000: 70%|██████▉ | 1393/2000 [24:10<11:17, 1.12s/it, loss=0.257]" ] }, { @@ -46587,7 +46467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1385/2000 [19:29<07:38, 1.34it/s, loss=0.499]" + "training until 2000: 70%|██████▉ | 1394/2000 [24:11<11:26, 1.13s/it, loss=0.257]" ] }, { @@ -46595,7 +46475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1385/2000 [19:29<07:38, 1.34it/s, loss=0.381]" + "training until 2000: 70%|██████▉ | 1394/2000 [24:11<11:26, 1.13s/it, loss=0.27] " ] }, { @@ -46603,7 +46483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1386/2000 [19:30<07:57, 1.29it/s, loss=0.381]" + "training until 2000: 70%|██████▉ | 1395/2000 [24:12<11:46, 1.17s/it, loss=0.27]" ] }, { @@ -46611,7 +46491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1386/2000 [19:30<07:57, 1.29it/s, loss=0.421]" + "training until 2000: 70%|██████▉ | 1395/2000 [24:12<11:46, 1.17s/it, loss=0.227]" ] }, { @@ -46619,7 +46499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1387/2000 [19:31<08:10, 1.25it/s, loss=0.421]" + "training until 2000: 70%|██████▉ | 1396/2000 [24:13<10:57, 1.09s/it, loss=0.227]" ] }, { @@ -46627,7 +46507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1387/2000 [19:31<08:10, 1.25it/s, loss=0.376]" + "training until 2000: 70%|██████▉ | 1396/2000 [24:13<10:57, 1.09s/it, loss=0.263]" ] }, { @@ -46635,7 +46515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1388/2000 [19:32<07:29, 1.36it/s, loss=0.376]" + "training until 2000: 70%|██████▉ | 1397/2000 [24:14<09:39, 1.04it/s, loss=0.263]" ] }, { @@ -46643,7 +46523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1388/2000 [19:32<07:29, 1.36it/s, loss=0.379]" + "training until 2000: 70%|██████▉ | 1397/2000 [24:14<09:39, 1.04it/s, loss=0.185]" ] }, { @@ -46651,7 +46531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1389/2000 [19:32<07:24, 1.37it/s, loss=0.379]" + "training until 2000: 70%|██████▉ | 1398/2000 [24:15<10:10, 1.01s/it, loss=0.185]" ] }, { @@ -46659,7 +46539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 69%|██████▉ | 1389/2000 [19:32<07:24, 1.37it/s, loss=0.411]" + "training until 2000: 70%|██████▉ | 1398/2000 [24:15<10:10, 1.01s/it, loss=0.194]" ] }, { @@ -46667,7 +46547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1390/2000 [19:33<08:00, 1.27it/s, loss=0.411]" + "training until 2000: 70%|██████▉ | 1399/2000 [24:16<10:06, 1.01s/it, loss=0.194]" ] }, { @@ -46675,7 +46555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1390/2000 [19:33<08:00, 1.27it/s, loss=0.405]" + "training until 2000: 70%|██████▉ | 1399/2000 [24:16<10:06, 1.01s/it, loss=0.172]" ] }, { @@ -46683,7 +46563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1391/2000 [19:34<08:25, 1.20it/s, loss=0.405]" + "training until 2000: 70%|███████ | 1400/2000 [24:17<09:51, 1.01it/s, loss=0.172]" ] }, { @@ -46691,7 +46571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1391/2000 [19:34<08:25, 1.20it/s, loss=0.377]" + "training until 2000: 70%|███████ | 1400/2000 [24:17<09:51, 1.01it/s, loss=0.497]" ] }, { @@ -46699,7 +46579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1392/2000 [19:35<07:59, 1.27it/s, loss=0.377]" + "training until 2000: 70%|███████ | 1401/2000 [24:17<08:22, 1.19it/s, loss=0.497]" ] }, { @@ -46707,7 +46587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1392/2000 [19:35<07:59, 1.27it/s, loss=0.386]" + "training until 2000: 70%|███████ | 1401/2000 [24:17<08:22, 1.19it/s, loss=0.282]" ] }, { @@ -46715,7 +46595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1393/2000 [19:36<07:39, 1.32it/s, loss=0.386]" + "training until 2000: 70%|███████ | 1402/2000 [24:19<09:47, 1.02it/s, loss=0.282]" ] }, { @@ -46723,7 +46603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1393/2000 [19:36<07:39, 1.32it/s, loss=0.474]" + "training until 2000: 70%|███████ | 1402/2000 [24:19<09:47, 1.02it/s, loss=0.196]" ] }, { @@ -46731,7 +46611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1394/2000 [19:36<07:04, 1.43it/s, loss=0.474]" + "training until 2000: 70%|███████ | 1403/2000 [24:20<09:44, 1.02it/s, loss=0.196]" ] }, { @@ -46739,7 +46619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1394/2000 [19:36<07:04, 1.43it/s, loss=0.508]" + "training until 2000: 70%|███████ | 1403/2000 [24:20<09:44, 1.02it/s, loss=0.241]" ] }, { @@ -46747,7 +46627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1395/2000 [19:37<07:04, 1.43it/s, loss=0.508]" + "training until 2000: 70%|███████ | 1404/2000 [24:20<08:47, 1.13it/s, loss=0.241]" ] }, { @@ -46755,7 +46635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1395/2000 [19:37<07:04, 1.43it/s, loss=0.398]" + "training until 2000: 70%|███████ | 1404/2000 [24:20<08:47, 1.13it/s, loss=0.25] " ] }, { @@ -46763,7 +46643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1396/2000 [19:38<07:11, 1.40it/s, loss=0.398]" + "training until 2000: 70%|███████ | 1405/2000 [24:21<08:23, 1.18it/s, loss=0.25]" ] }, { @@ -46771,7 +46651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1396/2000 [19:38<07:11, 1.40it/s, loss=0.518]" + "training until 2000: 70%|███████ | 1405/2000 [24:21<08:23, 1.18it/s, loss=0.197]" ] }, { @@ -46779,7 +46659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1397/2000 [19:38<06:59, 1.44it/s, loss=0.518]" + "training until 2000: 70%|███████ | 1406/2000 [24:22<08:46, 1.13it/s, loss=0.197]" ] }, { @@ -46787,7 +46667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1397/2000 [19:38<06:59, 1.44it/s, loss=0.476]" + "training until 2000: 70%|███████ | 1406/2000 [24:22<08:46, 1.13it/s, loss=0.277]" ] }, { @@ -46795,7 +46675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1398/2000 [19:39<07:07, 1.41it/s, loss=0.476]" + "training until 2000: 70%|███████ | 1407/2000 [24:23<09:07, 1.08it/s, loss=0.277]" ] }, { @@ -46803,7 +46683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1398/2000 [19:39<07:07, 1.41it/s, loss=0.395]" + "training until 2000: 70%|███████ | 1407/2000 [24:23<09:07, 1.08it/s, loss=0.296]" ] }, { @@ -46811,7 +46691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1399/2000 [19:40<07:29, 1.34it/s, loss=0.395]" + "training until 2000: 70%|███████ | 1408/2000 [24:24<09:32, 1.03it/s, loss=0.296]" ] }, { @@ -46819,7 +46699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|██████▉ | 1399/2000 [19:40<07:29, 1.34it/s, loss=0.398]" + "training until 2000: 70%|███████ | 1408/2000 [24:24<09:32, 1.03it/s, loss=0.224]" ] }, { @@ -46827,7 +46707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1400/2000 [19:40<07:18, 1.37it/s, loss=0.398]" + "training until 2000: 70%|███████ | 1409/2000 [24:25<08:29, 1.16it/s, loss=0.224]" ] }, { @@ -46835,7 +46715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1400/2000 [19:40<07:18, 1.37it/s, loss=0.379]" + "training until 2000: 70%|███████ | 1409/2000 [24:25<08:29, 1.16it/s, loss=0.203]" ] }, { @@ -46843,7 +46723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1401/2000 [19:41<07:50, 1.27it/s, loss=0.379]" + "training until 2000: 70%|███████ | 1410/2000 [24:26<08:36, 1.14it/s, loss=0.203]" ] }, { @@ -46851,7 +46731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1401/2000 [19:41<07:50, 1.27it/s, loss=0.392]" + "training until 2000: 70%|███████ | 1410/2000 [24:26<08:36, 1.14it/s, loss=0.221]" ] }, { @@ -46859,7 +46739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1402/2000 [19:42<07:12, 1.38it/s, loss=0.392]" + "training until 2000: 71%|███████ | 1411/2000 [24:27<08:43, 1.13it/s, loss=0.221]" ] }, { @@ -46867,7 +46747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1402/2000 [19:42<07:12, 1.38it/s, loss=0.398]" + "training until 2000: 71%|███████ | 1411/2000 [24:27<08:43, 1.13it/s, loss=0.142]" ] }, { @@ -46875,7 +46755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1403/2000 [19:43<07:43, 1.29it/s, loss=0.398]" + "training until 2000: 71%|███████ | 1412/2000 [24:27<08:20, 1.18it/s, loss=0.142]" ] }, { @@ -46883,7 +46763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1403/2000 [19:43<07:43, 1.29it/s, loss=0.372]" + "training until 2000: 71%|███████ | 1412/2000 [24:27<08:20, 1.18it/s, loss=0.206]" ] }, { @@ -46891,7 +46771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1404/2000 [19:43<07:03, 1.41it/s, loss=0.372]" + "training until 2000: 71%|███████ | 1413/2000 [24:28<08:02, 1.22it/s, loss=0.206]" ] }, { @@ -46899,7 +46779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1404/2000 [19:43<07:03, 1.41it/s, loss=0.411]" + "training until 2000: 71%|███████ | 1413/2000 [24:28<08:02, 1.22it/s, loss=0.261]" ] }, { @@ -46907,7 +46787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1405/2000 [19:44<07:38, 1.30it/s, loss=0.411]" + "training until 2000: 71%|███████ | 1414/2000 [24:29<07:45, 1.26it/s, loss=0.261]" ] }, { @@ -46915,7 +46795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1405/2000 [19:44<07:38, 1.30it/s, loss=0.466]" + "training until 2000: 71%|███████ | 1414/2000 [24:29<07:45, 1.26it/s, loss=0.223]" ] }, { @@ -46923,7 +46803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1406/2000 [19:45<07:59, 1.24it/s, loss=0.466]" + "training until 2000: 71%|███████ | 1415/2000 [24:30<09:48, 1.01s/it, loss=0.223]" ] }, { @@ -46931,7 +46811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1406/2000 [19:45<07:59, 1.24it/s, loss=0.381]" + "training until 2000: 71%|███████ | 1415/2000 [24:30<09:48, 1.01s/it, loss=0.26] " ] }, { @@ -46939,7 +46819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1407/2000 [19:46<07:39, 1.29it/s, loss=0.381]" + "training until 2000: 71%|███████ | 1416/2000 [24:31<09:47, 1.01s/it, loss=0.26]" ] }, { @@ -46947,7 +46827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1407/2000 [19:46<07:39, 1.29it/s, loss=0.409]" + "training until 2000: 71%|███████ | 1416/2000 [24:31<09:47, 1.01s/it, loss=0.291]" ] }, { @@ -46955,7 +46835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1408/2000 [19:47<07:08, 1.38it/s, loss=0.409]" + "training until 2000: 71%|███████ | 1417/2000 [24:32<10:02, 1.03s/it, loss=0.291]" ] }, { @@ -46963,7 +46843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1408/2000 [19:47<07:08, 1.38it/s, loss=0.368]" + "training until 2000: 71%|███████ | 1417/2000 [24:32<10:02, 1.03s/it, loss=0.261]" ] }, { @@ -46971,7 +46851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1409/2000 [19:47<07:04, 1.39it/s, loss=0.368]" + "training until 2000: 71%|███████ | 1418/2000 [24:34<11:03, 1.14s/it, loss=0.261]" ] }, { @@ -46979,7 +46859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1409/2000 [19:47<07:04, 1.39it/s, loss=0.386]" + "training until 2000: 71%|███████ | 1418/2000 [24:34<11:03, 1.14s/it, loss=0.208]" ] }, { @@ -46987,7 +46867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1410/2000 [19:48<07:25, 1.32it/s, loss=0.386]" + "training until 2000: 71%|███████ | 1419/2000 [24:35<11:15, 1.16s/it, loss=0.208]" ] }, { @@ -46995,7 +46875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 70%|███████ | 1410/2000 [19:48<07:25, 1.32it/s, loss=0.397]" + "training until 2000: 71%|███████ | 1419/2000 [24:35<11:15, 1.16s/it, loss=0.254]" ] }, { @@ -47003,7 +46883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1411/2000 [19:49<07:57, 1.23it/s, loss=0.397]" + "training until 2000: 71%|███████ | 1420/2000 [24:36<11:54, 1.23s/it, loss=0.254]" ] }, { @@ -47011,7 +46891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1411/2000 [19:49<07:57, 1.23it/s, loss=0.392]" + "training until 2000: 71%|███████ | 1420/2000 [24:36<11:54, 1.23s/it, loss=0.204]" ] }, { @@ -47019,7 +46899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1412/2000 [19:50<08:06, 1.21it/s, loss=0.392]" + "training until 2000: 71%|███████ | 1421/2000 [24:37<10:57, 1.13s/it, loss=0.204]" ] }, { @@ -47027,7 +46907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1412/2000 [19:50<08:06, 1.21it/s, loss=0.448]" + "training until 2000: 71%|███████ | 1421/2000 [24:37<10:57, 1.13s/it, loss=0.243]" ] }, { @@ -47035,7 +46915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1413/2000 [19:51<08:22, 1.17it/s, loss=0.448]" + "training until 2000: 71%|███████ | 1422/2000 [24:38<10:57, 1.14s/it, loss=0.243]" ] }, { @@ -47043,7 +46923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1413/2000 [19:51<08:22, 1.17it/s, loss=0.492]" + "training until 2000: 71%|███████ | 1422/2000 [24:38<10:57, 1.14s/it, loss=0.293]" ] }, { @@ -47051,7 +46931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1414/2000 [19:51<07:24, 1.32it/s, loss=0.492]" + "training until 2000: 71%|███████ | 1423/2000 [24:40<11:39, 1.21s/it, loss=0.293]" ] }, { @@ -47059,7 +46939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1414/2000 [19:51<07:24, 1.32it/s, loss=0.358]" + "training until 2000: 71%|███████ | 1423/2000 [24:40<11:39, 1.21s/it, loss=0.265]" ] }, { @@ -47067,7 +46947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1415/2000 [19:52<06:57, 1.40it/s, loss=0.358]" + "training until 2000: 71%|███████ | 1424/2000 [24:41<10:30, 1.09s/it, loss=0.265]" ] }, { @@ -47075,7 +46955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1415/2000 [19:52<06:57, 1.40it/s, loss=0.411]" + "training until 2000: 71%|███████ | 1424/2000 [24:41<10:30, 1.09s/it, loss=0.21] " ] }, { @@ -47083,7 +46963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1416/2000 [19:53<06:57, 1.40it/s, loss=0.411]" + "training until 2000: 71%|███████▏ | 1425/2000 [24:41<09:40, 1.01s/it, loss=0.21]" ] }, { @@ -47091,7 +46971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1416/2000 [19:53<06:57, 1.40it/s, loss=0.361]" + "training until 2000: 71%|███████▏ | 1425/2000 [24:41<09:40, 1.01s/it, loss=0.392]" ] }, { @@ -47099,7 +46979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1417/2000 [19:53<06:26, 1.51it/s, loss=0.361]" + "training until 2000: 71%|███████▏ | 1426/2000 [24:43<10:17, 1.08s/it, loss=0.392]" ] }, { @@ -47107,7 +46987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1417/2000 [19:53<06:26, 1.51it/s, loss=0.414]" + "training until 2000: 71%|███████▏ | 1426/2000 [24:43<10:17, 1.08s/it, loss=0.21] " ] }, { @@ -47115,7 +46995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1418/2000 [19:54<06:42, 1.45it/s, loss=0.414]" + "training until 2000: 71%|███████▏ | 1427/2000 [24:43<08:57, 1.07it/s, loss=0.21]" ] }, { @@ -47123,7 +47003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1418/2000 [19:54<06:42, 1.45it/s, loss=0.368]" + "training until 2000: 71%|███████▏ | 1427/2000 [24:43<08:57, 1.07it/s, loss=0.22]" ] }, { @@ -47131,7 +47011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1419/2000 [19:55<06:51, 1.41it/s, loss=0.368]" + "training until 2000: 71%|███████▏ | 1428/2000 [24:44<08:29, 1.12it/s, loss=0.22]" ] }, { @@ -47139,7 +47019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1419/2000 [19:55<06:51, 1.41it/s, loss=0.383]" + "training until 2000: 71%|███████▏ | 1428/2000 [24:44<08:29, 1.12it/s, loss=0.22]" ] }, { @@ -47147,7 +47027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1420/2000 [19:55<06:25, 1.51it/s, loss=0.383]" + "training until 2000: 71%|███████▏ | 1429/2000 [24:45<07:59, 1.19it/s, loss=0.22]" ] }, { @@ -47155,7 +47035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1420/2000 [19:55<06:25, 1.51it/s, loss=0.406]" + "training until 2000: 71%|███████▏ | 1429/2000 [24:45<07:59, 1.19it/s, loss=0.228]" ] }, { @@ -47163,7 +47043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1421/2000 [19:57<08:09, 1.18it/s, loss=0.406]" + "training until 2000: 72%|███████▏ | 1430/2000 [24:46<08:16, 1.15it/s, loss=0.228]" ] }, { @@ -47171,7 +47051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1421/2000 [19:57<08:09, 1.18it/s, loss=0.435]" + "training until 2000: 72%|███████▏ | 1430/2000 [24:46<08:16, 1.15it/s, loss=0.223]" ] }, { @@ -47179,7 +47059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1422/2000 [19:57<07:50, 1.23it/s, loss=0.435]" + "training until 2000: 72%|███████▏ | 1431/2000 [24:47<09:47, 1.03s/it, loss=0.223]" ] }, { @@ -47187,7 +47067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1422/2000 [19:57<07:50, 1.23it/s, loss=0.438]" + "training until 2000: 72%|███████▏ | 1431/2000 [24:47<09:47, 1.03s/it, loss=0.348]" ] }, { @@ -47195,7 +47075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1423/2000 [19:58<08:12, 1.17it/s, loss=0.438]" + "training until 2000: 72%|███████▏ | 1432/2000 [24:49<11:06, 1.17s/it, loss=0.348]" ] }, { @@ -47203,7 +47083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1423/2000 [19:58<08:12, 1.17it/s, loss=0.476]" + "training until 2000: 72%|███████▏ | 1432/2000 [24:49<11:06, 1.17s/it, loss=0.212]" ] }, { @@ -47211,7 +47091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1424/2000 [19:59<07:37, 1.26it/s, loss=0.476]" + "training until 2000: 72%|███████▏ | 1433/2000 [24:49<09:30, 1.01s/it, loss=0.212]" ] }, { @@ -47219,7 +47099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████ | 1424/2000 [19:59<07:37, 1.26it/s, loss=0.414]" + "training until 2000: 72%|███████▏ | 1433/2000 [24:49<09:30, 1.01s/it, loss=0.292]" ] }, { @@ -47227,7 +47107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1425/2000 [19:59<06:55, 1.38it/s, loss=0.414]" + "training until 2000: 72%|███████▏ | 1434/2000 [24:50<08:56, 1.06it/s, loss=0.292]" ] }, { @@ -47235,7 +47115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1425/2000 [19:59<06:55, 1.38it/s, loss=0.433]" + "training until 2000: 72%|███████▏ | 1434/2000 [24:50<08:56, 1.06it/s, loss=0.315]" ] }, { @@ -47243,7 +47123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1426/2000 [20:00<07:01, 1.36it/s, loss=0.433]" + "training until 2000: 72%|███████▏ | 1435/2000 [24:51<08:25, 1.12it/s, loss=0.315]" ] }, { @@ -47251,7 +47131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1426/2000 [20:00<07:01, 1.36it/s, loss=0.368]" + "training until 2000: 72%|███████▏ | 1435/2000 [24:51<08:25, 1.12it/s, loss=0.232]" ] }, { @@ -47259,7 +47139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1427/2000 [20:01<06:43, 1.42it/s, loss=0.368]" + "training until 2000: 72%|███████▏ | 1436/2000 [24:52<08:46, 1.07it/s, loss=0.232]" ] }, { @@ -47267,7 +47147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1427/2000 [20:01<06:43, 1.42it/s, loss=0.389]" + "training until 2000: 72%|███████▏ | 1436/2000 [24:52<08:46, 1.07it/s, loss=0.285]" ] }, { @@ -47275,7 +47155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1428/2000 [20:02<06:40, 1.43it/s, loss=0.389]" + "training until 2000: 72%|███████▏ | 1437/2000 [24:53<08:20, 1.12it/s, loss=0.285]" ] }, { @@ -47283,7 +47163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1428/2000 [20:02<06:40, 1.43it/s, loss=0.385]" + "training until 2000: 72%|███████▏ | 1437/2000 [24:53<08:20, 1.12it/s, loss=0.229]" ] }, { @@ -47291,7 +47171,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1429/2000 [20:02<06:22, 1.49it/s, loss=0.385]" + "training until 2000: 72%|███████▏ | 1438/2000 [24:53<08:07, 1.15it/s, loss=0.229]" ] }, { @@ -47299,7 +47179,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 71%|███████▏ | 1429/2000 [20:02<06:22, 1.49it/s, loss=0.37] " + "training until 2000: 72%|███████▏ | 1438/2000 [24:53<08:07, 1.15it/s, loss=0.245]" ] }, { @@ -47307,7 +47187,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1430/2000 [20:03<06:20, 1.50it/s, loss=0.37]" + "training until 2000: 72%|███████▏ | 1439/2000 [24:54<08:13, 1.14it/s, loss=0.245]" ] }, { @@ -47315,7 +47195,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1430/2000 [20:03<06:20, 1.50it/s, loss=0.421]" + "training until 2000: 72%|███████▏ | 1439/2000 [24:54<08:13, 1.14it/s, loss=0.232]" ] }, { @@ -47323,7 +47203,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1431/2000 [20:04<06:44, 1.41it/s, loss=0.421]" + "training until 2000: 72%|███████▏ | 1440/2000 [24:55<07:27, 1.25it/s, loss=0.232]" ] }, { @@ -47331,7 +47211,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1431/2000 [20:04<06:44, 1.41it/s, loss=0.402]" + "training until 2000: 72%|███████▏ | 1440/2000 [24:55<07:27, 1.25it/s, loss=0.288]" ] }, { @@ -47339,7 +47219,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1432/2000 [20:04<06:24, 1.48it/s, loss=0.402]" + "training until 2000: 72%|███████▏ | 1441/2000 [24:56<08:04, 1.15it/s, loss=0.288]" ] }, { @@ -47347,7 +47227,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1432/2000 [20:04<06:24, 1.48it/s, loss=0.411]" + "training until 2000: 72%|███████▏ | 1441/2000 [24:56<08:04, 1.15it/s, loss=0.226]" ] }, { @@ -47355,7 +47235,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1433/2000 [20:05<05:43, 1.65it/s, loss=0.411]" + "training until 2000: 72%|███████▏ | 1442/2000 [24:57<07:18, 1.27it/s, loss=0.226]" ] }, { @@ -47363,7 +47243,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1433/2000 [20:05<05:43, 1.65it/s, loss=0.408]" + "training until 2000: 72%|███████▏ | 1442/2000 [24:57<07:18, 1.27it/s, loss=0.223]" ] }, { @@ -47371,7 +47251,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1434/2000 [20:05<05:28, 1.73it/s, loss=0.408]" + "training until 2000: 72%|███████▏ | 1443/2000 [24:57<06:38, 1.40it/s, loss=0.223]" ] }, { @@ -47379,7 +47259,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1434/2000 [20:05<05:28, 1.73it/s, loss=0.452]" + "training until 2000: 72%|███████▏ | 1443/2000 [24:57<06:38, 1.40it/s, loss=0.256]" ] }, { @@ -47387,7 +47267,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1435/2000 [20:06<05:30, 1.71it/s, loss=0.452]" + "training until 2000: 72%|███████▏ | 1444/2000 [24:58<06:58, 1.33it/s, loss=0.256]" ] }, { @@ -47395,7 +47275,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1435/2000 [20:06<05:30, 1.71it/s, loss=0.368]" + "training until 2000: 72%|███████▏ | 1444/2000 [24:58<06:58, 1.33it/s, loss=0.309]" ] }, { @@ -47403,7 +47283,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1436/2000 [20:06<05:34, 1.69it/s, loss=0.368]" + "training until 2000: 72%|███████▏ | 1445/2000 [24:59<07:55, 1.17it/s, loss=0.309]" ] }, { @@ -47411,7 +47291,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1436/2000 [20:06<05:34, 1.69it/s, loss=0.38] " + "training until 2000: 72%|███████▏ | 1445/2000 [24:59<07:55, 1.17it/s, loss=0.276]" ] }, { @@ -47419,7 +47299,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1437/2000 [20:07<05:16, 1.78it/s, loss=0.38]" + "training until 2000: 72%|███████▏ | 1446/2000 [25:00<07:08, 1.29it/s, loss=0.276]" ] }, { @@ -47427,7 +47307,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1437/2000 [20:07<05:16, 1.78it/s, loss=0.419]" + "training until 2000: 72%|███████▏ | 1446/2000 [25:00<07:08, 1.29it/s, loss=0.307]" ] }, { @@ -47435,7 +47315,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1438/2000 [20:08<06:23, 1.47it/s, loss=0.419]" + "training until 2000: 72%|███████▏ | 1447/2000 [25:01<08:16, 1.11it/s, loss=0.307]" ] }, { @@ -47443,7 +47323,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1438/2000 [20:08<06:23, 1.47it/s, loss=0.365]" + "training until 2000: 72%|███████▏ | 1447/2000 [25:01<08:16, 1.11it/s, loss=0.239]" ] }, { @@ -47451,7 +47331,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1439/2000 [20:09<07:22, 1.27it/s, loss=0.365]" + "training until 2000: 72%|███████▏ | 1448/2000 [25:02<08:25, 1.09it/s, loss=0.239]" ] }, { @@ -47459,7 +47339,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1439/2000 [20:09<07:22, 1.27it/s, loss=0.385]" + "training until 2000: 72%|███████▏ | 1448/2000 [25:02<08:25, 1.09it/s, loss=0.159]" ] }, { @@ -47467,7 +47347,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1440/2000 [20:10<07:25, 1.26it/s, loss=0.385]" + "training until 2000: 72%|███████▏ | 1449/2000 [25:03<07:55, 1.16it/s, loss=0.159]" ] }, { @@ -47475,7 +47355,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1440/2000 [20:10<07:25, 1.26it/s, loss=0.4] " + "training until 2000: 72%|███████▏ | 1449/2000 [25:03<07:55, 1.16it/s, loss=0.253]" ] }, { @@ -47483,7 +47363,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1441/2000 [20:10<07:07, 1.31it/s, loss=0.4]" + "training until 2000: 72%|███████▎ | 1450/2000 [25:04<08:07, 1.13it/s, loss=0.253]" ] }, { @@ -47491,7 +47371,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1441/2000 [20:10<07:07, 1.31it/s, loss=0.373]" + "training until 2000: 72%|███████▎ | 1450/2000 [25:04<08:07, 1.13it/s, loss=0.267]" ] }, { @@ -47499,7 +47379,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1442/2000 [20:11<07:42, 1.21it/s, loss=0.373]" + "training until 2000: 73%|███████▎ | 1451/2000 [25:04<07:35, 1.20it/s, loss=0.267]" ] }, { @@ -47507,7 +47387,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1442/2000 [20:11<07:42, 1.21it/s, loss=0.361]" + "training until 2000: 73%|███████▎ | 1451/2000 [25:04<07:35, 1.20it/s, loss=0.213]" ] }, { @@ -47515,7 +47395,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1443/2000 [20:12<07:53, 1.18it/s, loss=0.361]" + "training until 2000: 73%|███████▎ | 1452/2000 [25:06<09:13, 1.01s/it, loss=0.213]" ] }, { @@ -47523,7 +47403,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1443/2000 [20:12<07:53, 1.18it/s, loss=0.369]" + "training until 2000: 73%|███████▎ | 1452/2000 [25:06<09:13, 1.01s/it, loss=0.254]" ] }, { @@ -47531,7 +47411,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1444/2000 [20:13<07:07, 1.30it/s, loss=0.369]" + "training until 2000: 73%|███████▎ | 1453/2000 [25:07<09:00, 1.01it/s, loss=0.254]" ] }, { @@ -47539,7 +47419,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1444/2000 [20:13<07:07, 1.30it/s, loss=0.412]" + "training until 2000: 73%|███████▎ | 1453/2000 [25:07<09:00, 1.01it/s, loss=0.253]" ] }, { @@ -47547,7 +47427,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1445/2000 [20:14<07:25, 1.25it/s, loss=0.412]" + "training until 2000: 73%|███████▎ | 1454/2000 [25:08<09:11, 1.01s/it, loss=0.253]" ] }, { @@ -47555,7 +47435,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1445/2000 [20:14<07:25, 1.25it/s, loss=0.396]" + "training until 2000: 73%|███████▎ | 1454/2000 [25:08<09:11, 1.01s/it, loss=0.176]" ] }, { @@ -47563,7 +47443,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1446/2000 [20:14<07:08, 1.29it/s, loss=0.396]" + "training until 2000: 73%|███████▎ | 1455/2000 [25:09<10:22, 1.14s/it, loss=0.176]" ] }, { @@ -47571,7 +47451,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1446/2000 [20:14<07:08, 1.29it/s, loss=0.368]" + "training until 2000: 73%|███████▎ | 1455/2000 [25:09<10:22, 1.14s/it, loss=0.181]" ] }, { @@ -47579,7 +47459,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1447/2000 [20:15<07:00, 1.31it/s, loss=0.368]" + "training until 2000: 73%|███████▎ | 1456/2000 [25:10<09:41, 1.07s/it, loss=0.181]" ] }, { @@ -47587,7 +47467,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1447/2000 [20:15<07:00, 1.31it/s, loss=0.468]" + "training until 2000: 73%|███████▎ | 1456/2000 [25:10<09:41, 1.07s/it, loss=0.256]" ] }, { @@ -47595,7 +47475,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1448/2000 [20:16<06:27, 1.42it/s, loss=0.468]" + "training until 2000: 73%|███████▎ | 1457/2000 [25:11<09:01, 1.00it/s, loss=0.256]" ] }, { @@ -47603,7 +47483,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1448/2000 [20:16<06:27, 1.42it/s, loss=0.444]" + "training until 2000: 73%|███████▎ | 1457/2000 [25:11<09:01, 1.00it/s, loss=0.255]" ] }, { @@ -47611,7 +47491,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1449/2000 [20:16<06:12, 1.48it/s, loss=0.444]" + "training until 2000: 73%|███████▎ | 1458/2000 [25:12<09:00, 1.00it/s, loss=0.255]" ] }, { @@ -47619,7 +47499,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▏ | 1449/2000 [20:16<06:12, 1.48it/s, loss=0.362]" + "training until 2000: 73%|███████▎ | 1458/2000 [25:12<09:00, 1.00it/s, loss=0.251]" ] }, { @@ -47627,7 +47507,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▎ | 1450/2000 [20:17<06:58, 1.31it/s, loss=0.362]" + "training until 2000: 73%|███████▎ | 1459/2000 [25:13<09:14, 1.03s/it, loss=0.251]" ] }, { @@ -47635,7 +47515,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 72%|███████▎ | 1450/2000 [20:17<06:58, 1.31it/s, loss=0.368]" + "training until 2000: 73%|███████▎ | 1459/2000 [25:13<09:14, 1.03s/it, loss=0.28] " ] }, { @@ -47643,7 +47523,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1451/2000 [20:18<06:53, 1.33it/s, loss=0.368]" + "training until 2000: 73%|███████▎ | 1460/2000 [25:14<09:51, 1.09s/it, loss=0.28]" ] }, { @@ -47651,7 +47531,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1451/2000 [20:18<06:53, 1.33it/s, loss=0.378]" + "training until 2000: 73%|███████▎ | 1460/2000 [25:14<09:51, 1.09s/it, loss=0.2] " ] }, { @@ -47659,7 +47539,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1452/2000 [20:19<06:47, 1.34it/s, loss=0.378]" + "training until 2000: 73%|███████▎ | 1461/2000 [25:16<10:30, 1.17s/it, loss=0.2]" ] }, { @@ -47667,7 +47547,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1452/2000 [20:19<06:47, 1.34it/s, loss=0.368]" + "training until 2000: 73%|███████▎ | 1461/2000 [25:16<10:30, 1.17s/it, loss=0.216]" ] }, { @@ -47675,7 +47555,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1453/2000 [20:20<07:08, 1.28it/s, loss=0.368]" + "training until 2000: 73%|███████▎ | 1462/2000 [25:16<09:50, 1.10s/it, loss=0.216]" ] }, { @@ -47683,7 +47563,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1453/2000 [20:20<07:08, 1.28it/s, loss=0.364]" + "training until 2000: 73%|███████▎ | 1462/2000 [25:16<09:50, 1.10s/it, loss=0.195]" ] }, { @@ -47691,7 +47571,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1454/2000 [20:20<06:41, 1.36it/s, loss=0.364]" + "training until 2000: 73%|███████▎ | 1463/2000 [25:17<09:19, 1.04s/it, loss=0.195]" ] }, { @@ -47699,7 +47579,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1454/2000 [20:20<06:41, 1.36it/s, loss=0.456]" + "training until 2000: 73%|███████▎ | 1463/2000 [25:17<09:19, 1.04s/it, loss=0.264]" ] }, { @@ -47707,7 +47587,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1455/2000 [20:21<06:39, 1.36it/s, loss=0.456]" + "training until 2000: 73%|███████▎ | 1464/2000 [25:18<08:17, 1.08it/s, loss=0.264]" ] }, { @@ -47715,7 +47595,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1455/2000 [20:21<06:39, 1.36it/s, loss=0.403]" + "training until 2000: 73%|███████▎ | 1464/2000 [25:18<08:17, 1.08it/s, loss=0.287]" ] }, { @@ -47723,7 +47603,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1456/2000 [20:22<07:18, 1.24it/s, loss=0.403]" + "training until 2000: 73%|███████▎ | 1465/2000 [25:19<07:30, 1.19it/s, loss=0.287]" ] }, { @@ -47731,7 +47611,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1456/2000 [20:22<07:18, 1.24it/s, loss=0.371]" + "training until 2000: 73%|███████▎ | 1465/2000 [25:19<07:30, 1.19it/s, loss=0.173]" ] }, { @@ -47739,7 +47619,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1457/2000 [20:23<07:20, 1.23it/s, loss=0.371]" + "training until 2000: 73%|███████▎ | 1466/2000 [25:20<07:43, 1.15it/s, loss=0.173]" ] }, { @@ -47747,7 +47627,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1457/2000 [20:23<07:20, 1.23it/s, loss=0.394]" + "training until 2000: 73%|███████▎ | 1466/2000 [25:20<07:43, 1.15it/s, loss=0.204]" ] }, { @@ -47755,7 +47635,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1458/2000 [20:24<07:22, 1.22it/s, loss=0.394]" + "training until 2000: 73%|███████▎ | 1467/2000 [25:20<07:45, 1.15it/s, loss=0.204]" ] }, { @@ -47763,7 +47643,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1458/2000 [20:24<07:22, 1.22it/s, loss=0.393]" + "training until 2000: 73%|███████▎ | 1467/2000 [25:20<07:45, 1.15it/s, loss=0.19] " ] }, { @@ -47771,7 +47651,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1459/2000 [20:25<07:52, 1.14it/s, loss=0.393]" + "training until 2000: 73%|███████▎ | 1468/2000 [25:22<08:11, 1.08it/s, loss=0.19]" ] }, { @@ -47779,7 +47659,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1459/2000 [20:25<07:52, 1.14it/s, loss=0.391]" + "training until 2000: 73%|███████▎ | 1468/2000 [25:22<08:11, 1.08it/s, loss=0.203]" ] }, { @@ -47787,7 +47667,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1460/2000 [20:25<07:22, 1.22it/s, loss=0.391]" + "training until 2000: 73%|███████▎ | 1469/2000 [25:22<07:41, 1.15it/s, loss=0.203]" ] }, { @@ -47795,7 +47675,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1460/2000 [20:25<07:22, 1.22it/s, loss=0.411]" + "training until 2000: 73%|███████▎ | 1469/2000 [25:22<07:41, 1.15it/s, loss=0.174]" ] }, { @@ -47803,7 +47683,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1461/2000 [20:26<06:44, 1.33it/s, loss=0.411]" + "training until 2000: 74%|███████▎ | 1470/2000 [25:23<07:08, 1.24it/s, loss=0.174]" ] }, { @@ -47811,7 +47691,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1461/2000 [20:26<06:44, 1.33it/s, loss=0.398]" + "training until 2000: 74%|███████▎ | 1470/2000 [25:23<07:08, 1.24it/s, loss=0.32] " ] }, { @@ -47819,7 +47699,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1462/2000 [20:27<07:23, 1.21it/s, loss=0.398]" + "training until 2000: 74%|███████▎ | 1471/2000 [25:24<08:06, 1.09it/s, loss=0.32]" ] }, { @@ -47827,7 +47707,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1462/2000 [20:27<07:23, 1.21it/s, loss=0.407]" + "training until 2000: 74%|███████▎ | 1471/2000 [25:24<08:06, 1.09it/s, loss=0.257]" ] }, { @@ -47835,7 +47715,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1463/2000 [20:28<08:04, 1.11it/s, loss=0.407]" + "training until 2000: 74%|███████▎ | 1472/2000 [25:25<08:15, 1.07it/s, loss=0.257]" ] }, { @@ -47843,7 +47723,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1463/2000 [20:28<08:04, 1.11it/s, loss=0.393]" + "training until 2000: 74%|███████▎ | 1472/2000 [25:25<08:15, 1.07it/s, loss=0.268]" ] }, { @@ -47851,7 +47731,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1464/2000 [20:29<07:40, 1.16it/s, loss=0.393]" + "training until 2000: 74%|███████▎ | 1473/2000 [25:26<09:25, 1.07s/it, loss=0.268]" ] }, { @@ -47859,7 +47739,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1464/2000 [20:29<07:40, 1.16it/s, loss=0.392]" + "training until 2000: 74%|███████▎ | 1473/2000 [25:26<09:25, 1.07s/it, loss=0.234]" ] }, { @@ -47867,7 +47747,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1465/2000 [20:30<07:35, 1.17it/s, loss=0.392]" + "training until 2000: 74%|███████▎ | 1474/2000 [25:27<09:00, 1.03s/it, loss=0.234]" ] }, { @@ -47875,7 +47755,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1465/2000 [20:30<07:35, 1.17it/s, loss=0.402]" + "training until 2000: 74%|███████▎ | 1474/2000 [25:27<09:00, 1.03s/it, loss=0.336]" ] }, { @@ -47883,7 +47763,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1466/2000 [20:30<07:07, 1.25it/s, loss=0.402]" + "training until 2000: 74%|███████▍ | 1475/2000 [25:28<08:22, 1.04it/s, loss=0.336]" ] }, { @@ -47891,7 +47771,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1466/2000 [20:30<07:07, 1.25it/s, loss=0.375]" + "training until 2000: 74%|███████▍ | 1475/2000 [25:28<08:22, 1.04it/s, loss=0.205]" ] }, { @@ -47899,7 +47779,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1467/2000 [20:31<06:48, 1.31it/s, loss=0.375]" + "training until 2000: 74%|███████▍ | 1476/2000 [25:30<09:24, 1.08s/it, loss=0.205]" ] }, { @@ -47907,7 +47787,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1467/2000 [20:31<06:48, 1.31it/s, loss=0.437]" + "training until 2000: 74%|███████▍ | 1476/2000 [25:30<09:24, 1.08s/it, loss=0.256]" ] }, { @@ -47915,7 +47795,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1468/2000 [20:31<06:14, 1.42it/s, loss=0.437]" + "training until 2000: 74%|███████▍ | 1477/2000 [25:31<09:17, 1.07s/it, loss=0.256]" ] }, { @@ -47923,7 +47803,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1468/2000 [20:31<06:14, 1.42it/s, loss=0.437]" + "training until 2000: 74%|███████▍ | 1477/2000 [25:31<09:17, 1.07s/it, loss=0.362]" ] }, { @@ -47931,7 +47811,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1469/2000 [20:32<06:13, 1.42it/s, loss=0.437]" + "training until 2000: 74%|███████▍ | 1478/2000 [25:32<09:11, 1.06s/it, loss=0.362]" ] }, { @@ -47939,7 +47819,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 73%|███████▎ | 1469/2000 [20:32<06:13, 1.42it/s, loss=0.39] " + "training until 2000: 74%|███████▍ | 1478/2000 [25:32<09:11, 1.06s/it, loss=0.195]" ] }, { @@ -47947,7 +47827,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1470/2000 [20:33<06:38, 1.33it/s, loss=0.39]" + "training until 2000: 74%|███████▍ | 1479/2000 [25:33<09:21, 1.08s/it, loss=0.195]" ] }, { @@ -47955,7 +47835,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1470/2000 [20:33<06:38, 1.33it/s, loss=0.425]" + "training until 2000: 74%|███████▍ | 1479/2000 [25:33<09:21, 1.08s/it, loss=0.147]" ] }, { @@ -47963,7 +47843,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1471/2000 [20:34<06:25, 1.37it/s, loss=0.425]" + "training until 2000: 74%|███████▍ | 1480/2000 [25:34<09:43, 1.12s/it, loss=0.147]" ] }, { @@ -47971,7 +47851,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1471/2000 [20:34<06:25, 1.37it/s, loss=0.4] " + "training until 2000: 74%|███████▍ | 1480/2000 [25:34<09:43, 1.12s/it, loss=0.2] " ] }, { @@ -47979,7 +47859,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1472/2000 [20:35<06:46, 1.30it/s, loss=0.4]" + "training until 2000: 74%|███████▍ | 1481/2000 [25:35<09:01, 1.04s/it, loss=0.2]" ] }, { @@ -47987,7 +47867,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1472/2000 [20:35<06:46, 1.30it/s, loss=0.388]" + "training until 2000: 74%|███████▍ | 1481/2000 [25:35<09:01, 1.04s/it, loss=0.263]" ] }, { @@ -47995,7 +47875,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1473/2000 [20:35<06:50, 1.28it/s, loss=0.388]" + "training until 2000: 74%|███████▍ | 1482/2000 [25:36<08:27, 1.02it/s, loss=0.263]" ] }, { @@ -48003,7 +47883,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1473/2000 [20:35<06:50, 1.28it/s, loss=0.345]" + "training until 2000: 74%|███████▍ | 1482/2000 [25:36<08:27, 1.02it/s, loss=0.239]" ] }, { @@ -48011,7 +47891,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1474/2000 [20:36<06:18, 1.39it/s, loss=0.345]" + "training until 2000: 74%|███████▍ | 1483/2000 [25:37<08:28, 1.02it/s, loss=0.239]" ] }, { @@ -48019,7 +47899,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▎ | 1474/2000 [20:36<06:18, 1.39it/s, loss=0.395]" + "training until 2000: 74%|███████▍ | 1483/2000 [25:37<08:28, 1.02it/s, loss=0.233]" ] }, { @@ -48027,7 +47907,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1475/2000 [20:37<06:20, 1.38it/s, loss=0.395]" + "training until 2000: 74%|███████▍ | 1484/2000 [25:38<08:53, 1.03s/it, loss=0.233]" ] }, { @@ -48035,7 +47915,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1475/2000 [20:37<06:20, 1.38it/s, loss=0.389]" + "training until 2000: 74%|███████▍ | 1484/2000 [25:38<08:53, 1.03s/it, loss=0.293]" ] }, { @@ -48043,7 +47923,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1476/2000 [20:37<05:54, 1.48it/s, loss=0.389]" + "training until 2000: 74%|███████▍ | 1485/2000 [25:39<08:17, 1.04it/s, loss=0.293]" ] }, { @@ -48051,7 +47931,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1476/2000 [20:37<05:54, 1.48it/s, loss=0.385]" + "training until 2000: 74%|███████▍ | 1485/2000 [25:39<08:17, 1.04it/s, loss=0.175]" ] }, { @@ -48059,7 +47939,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1477/2000 [20:38<06:14, 1.40it/s, loss=0.385]" + "training until 2000: 74%|███████▍ | 1486/2000 [25:39<07:56, 1.08it/s, loss=0.175]" ] }, { @@ -48067,7 +47947,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1477/2000 [20:38<06:14, 1.40it/s, loss=0.461]" + "training until 2000: 74%|███████▍ | 1486/2000 [25:39<07:56, 1.08it/s, loss=0.252]" ] }, { @@ -48075,7 +47955,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1478/2000 [20:39<06:58, 1.25it/s, loss=0.461]" + "training until 2000: 74%|███████▍ | 1487/2000 [25:40<07:47, 1.10it/s, loss=0.252]" ] }, { @@ -48083,7 +47963,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1478/2000 [20:39<06:58, 1.25it/s, loss=0.347]" + "training until 2000: 74%|███████▍ | 1487/2000 [25:40<07:47, 1.10it/s, loss=0.238]" ] }, { @@ -48091,7 +47971,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1479/2000 [20:40<06:36, 1.32it/s, loss=0.347]" + "training until 2000: 74%|███████▍ | 1488/2000 [25:42<08:28, 1.01it/s, loss=0.238]" ] }, { @@ -48099,7 +47979,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1479/2000 [20:40<06:36, 1.32it/s, loss=0.386]" + "training until 2000: 74%|███████▍ | 1488/2000 [25:42<08:28, 1.01it/s, loss=0.264]" ] }, { @@ -48107,7 +47987,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1480/2000 [20:40<06:27, 1.34it/s, loss=0.386]" + "training until 2000: 74%|███████▍ | 1489/2000 [25:43<08:39, 1.02s/it, loss=0.264]" ] }, { @@ -48115,7 +47995,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1480/2000 [20:40<06:27, 1.34it/s, loss=0.424]" + "training until 2000: 74%|███████▍ | 1489/2000 [25:43<08:39, 1.02s/it, loss=0.279]" ] }, { @@ -48123,7 +48003,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1481/2000 [20:41<07:03, 1.23it/s, loss=0.424]" + "training until 2000: 74%|███████▍ | 1490/2000 [25:44<09:17, 1.09s/it, loss=0.279]" ] }, { @@ -48131,7 +48011,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1481/2000 [20:41<07:03, 1.23it/s, loss=0.392]" + "training until 2000: 74%|███████▍ | 1490/2000 [25:44<09:17, 1.09s/it, loss=0.183]" ] }, { @@ -48139,7 +48019,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1482/2000 [20:42<06:49, 1.27it/s, loss=0.392]" + "training until 2000: 75%|███████▍ | 1491/2000 [25:45<08:29, 1.00s/it, loss=0.183]" ] }, { @@ -48147,7 +48027,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1482/2000 [20:42<06:49, 1.27it/s, loss=0.385]" + "training until 2000: 75%|███████▍ | 1491/2000 [25:45<08:29, 1.00s/it, loss=0.152]" ] }, { @@ -48155,7 +48035,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1483/2000 [20:43<06:25, 1.34it/s, loss=0.385]" + "training until 2000: 75%|███████▍ | 1492/2000 [25:46<09:41, 1.15s/it, loss=0.152]" ] }, { @@ -48163,7 +48043,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1483/2000 [20:43<06:25, 1.34it/s, loss=0.448]" + "training until 2000: 75%|███████▍ | 1492/2000 [25:46<09:41, 1.15s/it, loss=0.178]" ] }, { @@ -48171,7 +48051,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1484/2000 [20:44<07:02, 1.22it/s, loss=0.448]" + "training until 2000: 75%|███████▍ | 1493/2000 [25:47<09:09, 1.08s/it, loss=0.178]" ] }, { @@ -48179,7 +48059,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1484/2000 [20:44<07:02, 1.22it/s, loss=0.419]" + "training until 2000: 75%|███████▍ | 1493/2000 [25:47<09:09, 1.08s/it, loss=0.421]" ] }, { @@ -48187,7 +48067,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1485/2000 [20:45<07:28, 1.15it/s, loss=0.419]" + "training until 2000: 75%|███████▍ | 1494/2000 [25:48<09:16, 1.10s/it, loss=0.421]" ] }, { @@ -48195,7 +48075,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1485/2000 [20:45<07:28, 1.15it/s, loss=0.408]" + "training until 2000: 75%|███████▍ | 1494/2000 [25:48<09:16, 1.10s/it, loss=0.355]" ] }, { @@ -48203,7 +48083,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1486/2000 [20:46<08:08, 1.05it/s, loss=0.408]" + "training until 2000: 75%|███████▍ | 1495/2000 [25:49<09:26, 1.12s/it, loss=0.355]" ] }, { @@ -48211,7 +48091,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1486/2000 [20:46<08:08, 1.05it/s, loss=0.449]" + "training until 2000: 75%|███████▍ | 1495/2000 [25:49<09:26, 1.12s/it, loss=0.251]" ] }, { @@ -48219,7 +48099,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1487/2000 [20:47<07:26, 1.15it/s, loss=0.449]" + "training until 2000: 75%|███████▍ | 1496/2000 [25:50<09:23, 1.12s/it, loss=0.251]" ] }, { @@ -48227,7 +48107,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1487/2000 [20:47<07:26, 1.15it/s, loss=0.465]" + "training until 2000: 75%|███████▍ | 1496/2000 [25:50<09:23, 1.12s/it, loss=0.244]" ] }, { @@ -48235,7 +48115,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1488/2000 [20:47<07:25, 1.15it/s, loss=0.465]" + "training until 2000: 75%|███████▍ | 1497/2000 [25:51<08:16, 1.01it/s, loss=0.244]" ] }, { @@ -48243,7 +48123,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1488/2000 [20:47<07:25, 1.15it/s, loss=0.364]" + "training until 2000: 75%|███████▍ | 1497/2000 [25:51<08:16, 1.01it/s, loss=0.17] " ] }, { @@ -48251,7 +48131,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1489/2000 [20:48<06:43, 1.27it/s, loss=0.364]" + "training until 2000: 75%|███████▍ | 1498/2000 [25:52<07:30, 1.11it/s, loss=0.17]" ] }, { @@ -48259,7 +48139,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1489/2000 [20:48<06:43, 1.27it/s, loss=0.382]" + "training until 2000: 75%|███████▍ | 1498/2000 [25:52<07:30, 1.11it/s, loss=0.22]" ] }, { @@ -48267,7 +48147,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1490/2000 [20:49<06:27, 1.32it/s, loss=0.382]" + "training until 2000: 75%|███████▍ | 1499/2000 [25:52<06:48, 1.23it/s, loss=0.22]" ] }, { @@ -48275,7 +48155,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 74%|███████▍ | 1490/2000 [20:49<06:27, 1.32it/s, loss=0.428]" + "training until 2000: 75%|███████▍ | 1499/2000 [25:52<06:48, 1.23it/s, loss=0.211]" ] }, { @@ -48283,7 +48163,7 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 75%|███████▍ | 1491/2000 [20:50<06:42, 1.26it/s, loss=0.428]" + "training until 2000: 75%|███████▌ | 1500/2000 [25:54<08:13, 1.01it/s, loss=0.211]" ] }, { @@ -48291,23 +48171,21 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 75%|███████▍ | 1491/2000 [20:50<06:42, 1.26it/s, loss=0.48] " + "training until 2000: 75%|███████▌ | 1500/2000 [25:54<08:13, 1.01it/s, loss=0.197]" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\r", - "training until 2000: 75%|███████▍ | 1492/2000 [20:50<06:02, 1.40it/s, loss=0.48]" + "WARNING:dacapo.store.local_weights_store:Storing weights for run example_run, iteration 1500\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "\r", - "training until 2000: 75%|███████▍ | 1492/2000 [20:50<06:02, 1.40it/s, loss=0.363]" + "\n" ] }, { @@ -48315,23 +48193,21 @@ "output_type": "stream", "text": [ "\r", - "training until 2000: 75%|███████▍ | 1493/2000 [20:51<06:11, 1.36it/s, loss=0.363]" + "predict_/home/runner/dacapo/example_run/validation.zarr_1500/cells3d/prediction ▶: 0%| | 0/216 [00:00\n", - "array([0.81003344, 0.78063643, 0.8337096 , ..., 0.32482904, 0.35309637,\n", - " 0.28647012])\n", + "array([0.6903618 , 0.67242622, 0.67879522, ..., 0.18601137, 0.20407282,\n", + " 0.25669718])\n", "Coordinates:\n", " * iterations (iterations) int64 0 1 2 3 4 5 ... 1994 1995 1996 1997 1998 1999\n" ] }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -80020,13 +79888,13 @@ { "cell_type": "code", "execution_count": 13, - "id": "05755c5e", + "id": "e882b07d", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T17:18:07.115023Z", - "iopub.status.busy": "2024-11-13T17:18:07.114596Z", - "iopub.status.idle": "2024-11-13T17:18:07.783633Z", - "shell.execute_reply": "2024-11-13T17:18:07.782985Z" + "iopub.execute_input": "2024-11-19T16:48:11.395243Z", + "iopub.status.busy": "2024-11-19T16:48:11.394819Z", + "iopub.status.idle": "2024-11-19T16:48:12.447214Z", + "shell.execute_reply": "2024-11-19T16:48:12.446423Z" }, "lines_to_next_cell": 0 }, @@ -80043,7 +79911,7 @@ }, { "data": { - "image/png": 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", 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" ] @@ -80075,19 +79943,19 @@ { "cell_type": "code", "execution_count": 14, - "id": "0d7c0380", + "id": "763519ce", "metadata": { "execution": { - "iopub.execute_input": "2024-11-13T17:18:07.785764Z", - "iopub.status.busy": "2024-11-13T17:18:07.785367Z", - "iopub.status.idle": "2024-11-13T17:18:09.093220Z", - "shell.execute_reply": "2024-11-13T17:18:09.092477Z" + "iopub.execute_input": "2024-11-19T16:48:12.449657Z", + "iopub.status.busy": "2024-11-19T16:48:12.449405Z", + "iopub.status.idle": "2024-11-19T16:48:13.778969Z", + "shell.execute_reply": "2024-11-19T16:48:13.778200Z" } }, "outputs": [ { "data": { - "image/png": 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", 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", 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TBAGffvopffv2jZb/p35dwPaBgQMHMmfOHBzH4Y033mDu3LncdNNNHHXUUbz++uu8//77KKU2u0fzyBOQ/L288847t/reNM1IS/hFfPH+KS0tBWil2cwvD4KA+vp6KioqtrpNeXTp0mUzUt+mTZutLjGwcuVKLr30Up544onN7u36+vqt2sem+L73tQKB+QGjqqoqcqUZOXIk+++/P8cddxzvvvsuqVSKBx98kBNPPJGRI0cyadIk2rdvj2EYTJs2LXrp5LH//vuzcOFCMpkMS5Ys4dJLL6Vfv36UlZXx4osv8s4775BKpdhzzz2/i1Mt4HuM0tJSOnXqxJtvvrnZd/n82bw+64uIxWJf6Uz2Zfiy2d3/JFY3DGOLy9XX0KFsC2w6k5aHEGKL7fi64vsvO8cCtm9s+rzfErbUl4IgoH379vzxj3/c4jZfJLrbK74v/bqA/x62bTNw4EAGDhxIr169GDduHI888ghBECCE4O9///sWf+//poDvl90/X3Vffd02/Tf3qe/7DBs2jJqaGn73u9+x2267UVRUxOrVqznxxBMJguAr97Et8L/sawUC8yNBnpgMGTKE//u//+PCCy/k0UcfZaeddmLOnDmtBnuXXXbZZtsfcMABzJo1iz/96U/4vs++++6LlJL9998/IjD77rtvYXBUwBZx6KGHcs8991BdXU1VVdV/ta/u3buzYMECGhsbW0Vhli9fHn0PLTM/dXV1rbb/byI03bt3JwgCPvzww1azUu++++433ufWok2bNltMJfji+XyTtJwCfpzo2bMnCxYsYL/99tsiac4j36fef//9Vqkk69ev/8qZ1Xy08s0332To0KFfut7W3rft2rUjmUxusc8tX74cKeVmM+MF/DCRJ+yff/45PXv2RClFjx496NWr15duk7+XP/jgA4YMGRIt9zyPjz/++L+uw7UptrZNXwdf1k/+/e9/895773H//fdzwgknRMvnz5+/1fv4Ir7vfa2ggfkRYfDgwVRVVXHzzTeTzWYjsrEpM/7Xv/7Fyy+/vNm2+dSwa665hv79+0ch1AMOOICFCxfy6quvFtLHCvhSXHDBBSSTScaPH7/F6uBfZ3bmkEMOwfd9/u///q/V8ptuugkhBD//+c8BKCkpoW3btpF2K4/bb7/9G5yBRn7ft9xyS6vlN9988zfe59aiZ8+eLF++vJUl5RtvvMGiRYtarZd3l/oicSuggC/imGOOwfd9rrrqqs2+8zwvuoeGDh2KZVnceuutrfrq1tz3P/3pT+nRowc333zzZvfkpvvK16T5qvvWMAyGDx/O448/3ipyu3btWh566CH2339/SkpKvrJdBWw/ePbZZ7f4jshrEnfddVdGjRqFYRhcccUVm62rlGLjxo2AJj0VFRXcfffdkVYF4I9//OM2T3Pa2jZ9HXxZP9nSeE4pFVmVb80+vojve18rRGB+ZJg0aRJHH3009913H7/4xS+YM2cORxxxBIceeigrVqzgjjvuoE+fPpvpFXbeeWc6duzIu+++26rq7YEHHsjvfvc7gAKBKeBLscsuu/DQQw8xZswYdt11V371q1+x++67o5RixYoVPPTQQ0gpt2hh+UUcdthhDBkyhIsvvpiPP/6Y3XffnaeffprHH3+cs88+u5U+5eSTT+b3v/89J598MgMGDOCFF17gvffe+8bnscceezBmzBhuv/126uvr2XfffVm4cCEffPDBN97n1mL8+PHceOONjBgxgpNOOol169Zxxx130Ldv31ZCykQiQZ8+fZg9eza9evWivLycfv36bTMNQgE/HAwaNIjTTjuNadOm8frrrzN8+HAsy+L999/nkUceYfr06Rx11FFRraBp06bxi1/8gkMOOYSlS5fy97//nbZt2/7HY0gpmTFjBocddhh77LEH48aNo1OnTixfvpy33nqLefPmAVBZWQlog4wRI0ZgGAbHHnvsFvd59dVXM3/+fPbff39OP/10TNPkzjvvJJfLtaqbUcAPA2eeeSbpdJojjjiC3XbbDcdx+Oc//8ns2bPZcccdGTduHGVlZVx99dVcdNFFkS1ycXExK1asYO7cuZx66qmcf/752LbN5ZdfzplnnslBBx3EMcccw8cff8x9991Hz549t2kEu2fPnlvVpq+7z7KyMu644w6Ki4spKipir732YrfddqNnz56cf/75rF69mpKSEh577LEtkrIfTF/b5r5mBXznyNvZvfLKK5t95/u+6tmzp+rZs6fyPE9NnTpVde/eXcViMbXnnnuqJ598cjNb1jyOPvpoBajZs2dHyxzHUclkUtm2rTKZzLd5WgX8APDBBx+oCRMmqJ133lnF43GVSCTUbrvtpn7zm9+o119/vdW6Y8eOVUVFRVvcT2NjozrnnHPUDjvsoCzLUrvssou67rrrWtk3KqVtJU866SRVWlqqiouL1THHHKPWrVv3pTbK69evb7V9vi+tWLEiWpbJZNRZZ52lKioqVFFRkTrssMPUp59+uk1tlL/YjjwefPBBtdNOOynbttUee+yh5s2bt8X++s9//lNVVlYq27ZbtevLrmn+uAVsf/hPz/s8/lNfUkqpu+66S1VWVqpEIqGKi4vVT37yE3XBBReozz77LFrH9311xRVXqE6dOqlEIqEGDx6s3nzzTdW9e/f/aKOcx0svvaSGDRumiouLVVFRkerfv7+69dZbo+89z1NnnnmmateunRJCtLoft9S3XnvtNTVixAiVSqVUMplUQ4YMUf/85z+36tp8WRsL+H7i73//uxo/frzabbfdVCqVUrZtq5133lmdeeaZau3ata3Wfeyxx9T++++vioqKVFFRkdptt93UGWecod59991W691yyy3R2KeqqkotWrRIVVZWqp/97GfROvn75JFHHmm17ZfdV1/2/N6aNg0aNEj17dt3s3Pf0vP98ccfV3369FGmabayVH777bfV0KFDVSqVUm3btlWnnHKKeuONNzazXf6h9DURNriAAgoooIACCiiggAJ+dAiCgHbt2jFq1Cjuvvvu77o5BWwFChqYAgoooIACCiiggAJ+FMhms5tpUv7whz9QU1PD4MGDv5tGFfC1UYjAFFBAAQUUUEABBRTwo8Bzzz3HOeecw9FHH01FRQWvvfYa9957L71792bJkiVRge8Cvt8oiPgLKKCAAgoooIACCvhRYMcdd6Rr167ccsst1NTUUF5ezgknnMDvf//7AnnZjvCDSSG77bbb2HHHHYnH4+y1115UV1d/100qoIDvHQr9pIACvhqFflJAAVuH7bGv7LjjjjzxxBOsWbMGx3FYs2YNM2fOpH379t910wr4GvhBEJjZs2dz7rnnctlll/Haa6+x++67M2LECNatW/ddN62AAr43KPSTAgr4ahT6SQEFbB0KfaWA7xI/CA3MXnvtxcCBA6PCdkEQ0LVrV84880wuvPDC77h1BRTw/UChnxRQwFej0E8KKGDrUOgrBXyX2O41MI7jsGTJEi666KJomZSSoUOHbrGi/JYQBAGfffYZxcXF27SIUQHbN5RSNDY2ssMOOyDl9h2sLPSTAr4tFPpJaxT6SQFbwg+pn8B/31cK/aSALeHr9JPtnsBs2LAB3/fp0KFDq+UdOnRg+fLlW9wml8uRy+Wiz6tXr6ZPnz7fajsL2H7x6aefblWF+O8zCv2kgG8bhX6iUegnBfwn/BD6CXz9vlLoJwV8HWxNP9nuCcw3wbRp07jiiis2Wz644zjMWJLsjm3xbYnhBPgxSXNHExGA9CBe42FmfZQQIMBsdgksAz9hYDZ7ACgBbspCGXqdog9qoaYOfA8CBVKAkCAlKIWwLIjbBEVJVMIkMCTKlHhJA+kpjIzeb2AbKCkQSqGkQBkCs9FFKEVgGQg/QAQK4QQYDc2Qc1Ce33JM19UnqgJ9fBXoz4YJSoE0EIYEISARw+lYildkIl1FtsJCuorEuiwAMusjfB/hK4KESWCbBJZESYGXMBBKYWZ8fFsiFPiWpOjDWkRzGuX5CClRQaDblm8HtFwPy9Rt9gNUSYogaRFYRnTeAAjdDgQoSyJcvR8l9fciUJgNOUQ6g8rkwPfBMPR1yM/4hP8Ly0IVJcC2QCnctkmai3yWzJtKcXHxtrr1tit8WT/ZFM+ePeq/Ps6Qm+d8rfXH/vzx//qYedz/98P/6338fsKvt0FL4MIZD26T/QC888zbX7lO74O27eCh0E9ao+ul/w/DTOC18RAZCUoggMAKMJsNfFuhkj5mrX4NSxeMtEB64CVABJCrCJCuwGwWmBlwyhSBqb+TWYF00ctLwOnkEi/LkK1LYBU52HEPpQR7dFzF0s+74HySwqqXCB/cPml2bL+RDz7pgNFgIl2BbyuseondAHajwk0K/Jg+VmDr95pXrPBSAWaT1Mstorb7NhhZsBoFubYKr8xDWAFFpRma1hWBBGEFqLSB8AQiENi1EiXAzOrzEJ7CTQm8BChDIXxBrBayFeCVBBhZgfDBK1IoAarIA0diNhmgwCv2Eb5+pitTYaQlygSZEyhTZ8vLnEC4AiOn2++WBogA/GIfTIW50UK6EBigDLBrBXZDeA0kBCY4bRR+TEGpi1KQKsvgeZKKVJqmXIzSRIYNTSmyK1MkujcihaJhnWD1xGsK/eQL+NvEP1IUS1L30J8BeH1mjHPWdeLZCz/m9ZkxAJ4p6c+Vc3ows6Y7J+1yP1bXCay74Apenxnj8uH3cdgz/Wk+/Vi8++Jc9fwnAFwxqwOXjVsLwHW8wSR254pZHZj7/xoB+Oy6eZyRO4q63f9O2Rs/Z+7/a+SUvdeTWVnNXw9aBsCRh/6ap96eS2ZFM8d8cDJ9PtJjsRfO6kXd7n+PzuGd6tcY+PBV0eeDGpZxzWmPALBwyhJ++/gpvFP9GpkVzRz9VArR61jOeKwIq+sEbq66ngv3eYxp9+vx2UVjLS6b3ZWlM/fl0P+X5v2Ru9Gm59s89rcHef6aiQz63XSev2YiQKu/8+d86S97c+UT73D1paPoG9zPkL++RM+xS+lrHsUe4zWBvPHRgRzUsIwn7v0Q8ekamv/UwEOVDmf/9RJK0/cBUOn9lMuH678vf/pEninpz18/WM8ZlzZQf8+L0TWqf/Aibmr/OZcPvy9qH8Dz10zk2LLPmHGVyUPPFen2HfkaC96ezAmzlvCWHAvA021/zx7jc4yxnmBRk81VTx/G3D3/sFX9ZLsnMG3btsUwDNauXdtq+dq1a+nYseMWt7nooos499xzo88NDQ107doV04xjFJVg2HGkIVBFAhkTGHGDeI1+yFnCwMrlCGyDIGYQVCSw6x0C30AlbcxGBz9h4RdpAmM1+dC+HLMxB8LTg2jQA2kAAfhAJsDINSOSCVQyTpA0wYojDIXpunhJEyOAwBIoU2DkAoQCGTMxMi6i2Uc2hYN0x9XEBQleoA9iWoBC+QFCGHrgLmVIpvKDeYmwbTAN/HalqDZx4mlPEwbXxGryEIkkSgqkFSCzLgQgTYlvGYiYgRLgF5uY6QBLehhKaoKRNJFtFEY2QAVuSFxEeP4emCGJEoAyEL4EYYJQkA00MYrF8JMmItAETgQKEQvJjxBgK4yc38LLGrOI+iwoUMoISZsANFkDdDsAfAGNDsLwwDCw0o1YCRnuevsPb2/LfpLHK78bvU3a9srvRjPwmtlbvX6edJzyywXf6Hh3PzH0G223Jdx89vhtuq+zb565TfZVnPrfD5IK/UQj309UhYVqI7At/awRKxMYGYFjB4iEwDAVgRWgygVWnSSW0c9DI5xfcsoVoszD2mAiYwLTBS+mIKYwmyQGgAXCADMGnmWSapPDqykiaCoi1wjCFWzolCNRYpLraBLYFsKHRHmOrF1MrK2BqEtgeIJAgIiD4YAfB8MHYekBeyytB+9WM3hCk4sgrl8hfiogcAUYCpUTZDsoMKC0cxbflwRBETKewGiWiLTArhcEMZA5MB3wkqCKQcXAN0HZYDngJRTSE1ACtgArrdsiBBiuwi1RBCkXY4Ot56VKAuKNIUFLKYJEgOkYuKU+gQIjIzUBKVEoS2GuMRGWwjTA8CBX5IIrsTAwPAE+mM1gpfV7KVckCOLgJxXCUsSbJTnhYRS77NChgdW1pdgpj326rOGDhna0S/h8JgQyESebtZCOftf8EPoJfP2+8mX95I7Dr2Hw8gAmw7Ad5rG86Ao+2OjTZdw4uryo11122O9Ixa6hz7g7GLTfXSyZHqPrpK4UnayPnTvzRBZObeS1f9Ux6dDdACgbchepl4cBYO9Tz3Re4Lr4MM4Y1sTYgc30bmtgGnGOOas3vz5zLp0ue4f3SnsDMW7sUMFpC6/m0ffWcfx+Yyn3HHb4WEKRtlg2jTh377tPy8ntuw/8a030cf4Am/QNF3DjmkeIrZ/JfWP+xD03XsY9B/6JTrsfyz0H/gn7nyfQO/M05iezufHN47GWPwDA0385mstfLaPywWs5deAFXGTEmTx8ByYPv4DKidcCmriMqt6TJdMv0Nf2Ln29rz26HxeM/hBOaMP/41mG129kx/OaOPWoIyk/rz1Mgpob1nLv4VM4o+3F7Hb7Y/Q3x3Bht7u4/vlizFQCSxqU3zebZSeOZlT1nkw4qj/l77TnhYMTjOv1DyZ4/ZmRMhhVvScA5/wqx8z374vakv//avEaE/vtxJO/PB+vRo8VzDUr2efCEh4ZfwAn7vQEJz7/Mf0+sHl0SZIjGcuFB+1MWbGefNuafrLdExjbtqmsrGThwoWMHDkS0LmVCxcu5Le//e0Wt4nFYsRisc2/UAoVs6IZfiMXAJJ4bYBvC6xMgHQClGUgvQCEwLdNMh3iOlKSDfBSNtINkE44mJbgJ0wsy0J5YYTG9cj/NMoPdNQjHyXJZBGej1HXSKIujkrGULaJMgTSD5AuKF9HN2TWRTblEOksKptDwSZRFQPC46ECyOU0QTHQxzIMTXZ89NsSEHEL5bqQjJOriCPCsb0SArveRbo+gSnDWUSJcCVCgpey8GMGZpOLMiVGVoECAjAzDkHMxMgG+HETw5DgEkZXCElLmOeYJxNmeHXy7fd9hB9g+gHSiRHELfy4gcz5OvLiKQjC8w4CZM5HNoYRqHzUCVDZHMIyWx8rf718wDZQfqCPaxiQbgl3b+/Ypv3kW8DXJTHQmohsDZnZlsTl+44uVV1ZVf3pf/y+gM2xLfuJ0WSgUpJEaYbGdSkSjQIRQKxG4qUUbqmPbDYwMoJYraBoTYBTLMiVCZQBCEh+oqMBytCREKtRkLPAyIH0Qfh6UG9kQWYkNetLwA4o3qGRxvUp8AQfvN8J7IDYZ5aOtMQVzeuKaJZJRFZSsl7oSEoGPdkj9LGEB34KvKTCjwnsen1MmQPQ0R8lQZkC6Qrc0gDlCqwGSWBDc1OckuIMdWuTOuIRkhfpgQfE6hRKCEwFuXLwUgrh56+eQJk6H95LCWIbwU2BDPIES+jnviMx0wLpgJE1MDO6TdIReCmBlwzAUAhHv2OUoVCGoqh9M80UYW8wsOv09ZZxn8AX+HGwGnRUyMgpAiM8XhD+Dh5Ioc8/sdrETRl8uLEzZkbwSVkSb0fJ6pUVCEciM5KMFSOIBZhpd7N7ZHvG1+0rX9ZPzn9lCEVNh1K558ssWfIW/Ewvn3rY73hsld7vv5b35vBd7uNMUtEA+Yg3cuz81N7Q736efutcDu41A3rBdQtXMGWf+QBMOrgH1y1cwcUhkTngltvhFlhXfCUH3RrjpRMu5SCO48Fb9+RS9uSdMTnKz+sADGF4/VKu6QBz9n2IF886vVWbh52qyUrlxGuj9swfUKe/e7WMC/e7i6ffnMHiSR/zs4fnc/HLMPaTcu4Blg/vw8ULp/IOy5ly8GRG/fME9nzsBUbfsxtn3eFRzSsMYxhLpl/ARXd15Om3ziW1jyYLo6r3pModCEA1r3DEGzmGx89g2qn3hOebiNr47msvYl4zgGmnlvHLq1fxRK1u78mnv8ff93ZZfcK5LHn9AiYd3INR1Xty7W9MTvgD1CVP5eJd72FS8lTK0neF1wN2uv1gak68ixmPLqPKHUi19Qrl981mwm/v4Qz0Nchf97rkqZijO1LZ+AYXruzFQafPoCx9F2e0vZhpbRfw0Gs9qH/hD/z5DwYP9BzFkdZf2O9Vl+l7Wfx7cTv+/BX3Xh7bPYEBOPfccxk7diwDBgygqqqKm2++mebmZsaNG/f1diR0epJ0NfmQOQ9KYihTYGYCpKsQXoBTYuEVSaSriK/P4ZbYCC9AGQI/JlHS1A9EX+h0pkCBaUSDZmEYKMdtiYJsApVzogG0aGxGpHXKVnK92aqdZHN62yDQg3SlNCHJRzIcF3wfpZRmspYJgY7AAAjfb0kjC1PKlOsi4nH80iTKAKteP3D9IqkjP1K3wa53MDKeTmUzJb4t8eMCIyuRboCR9QlsqUlOYKAMHTHyikysmK3bHuSJS9DazNs0o/PItxUpwHEQSmHkHGQyjkxYKEPqKEzORwQBwgsQTWkdgXIcvW3+POEL5CVMJ9uUzDmAIcEPdBrbDwzbrJ98D/FjIicFfLvYVv0kiClk2iCXs5BpA6sZjKwmA14K8AR2nU7ZAvAtndZkOGG6kqEH+NIF1wYVppVZzZoE5APYwtfEwmqU+I6Fv0OOdDqGXZLDabIxak2Eb+i0tLhOvRKegEBQ3K0Bu6dHTV0KP21ibTAxwkhQrCYkA66eUHKLddukC0gIAEwwMpoACFcgPYGZFrhSoeps6jImZq0ZRm80KQmEjuT4cZ0qlictwtP7CmKKXFsfmZF4nRzkBguURLpEJEIJ8Ms9yOlnu/R0u6QLfgKUqfcnAgF2ABkDJQFDn7vrGrTtUsfGXDlms77GgSsRcR9rpYWf0PsUPmTL9fn7cf3+NtPh54TCyArMjIhIVGBKPlvTBqPBQPgCu05gOALflriB981vyu8ptkVfuWJWB0zjTebtqUlL07jjqZ71AHXJUzm4F1w7uydPtG0GoHK/a7kQPcs/d/cYz71wG2bfG5l26hoq+02IyERd8lSuW7gCWBFFLQ56cwbcAs3XTWLEJfDrM5cy7KzTmU8dAE89/wxP/Qba7lPMhgWNHMJBURsPuOX2zdp98gvHMmqfPams0iRm2Ktl0brJnqlW695/VA3Lh/fhxbNO56K7YN5Dt3BT0SguuOFdLv/kF8y7bTycMZMqd1+WeQ9zwx4f8NCgxqjdTaMzLTu7aznPnLobqVmvMHf3GHBPFIF5t82LrD7hIX2uQGrWA/DyMPpeM4BJszW5uef2XpzMe3D65cA9XLdwBfMHDOSsO17RhOW+2fzjgn9Qtu4u4pkPmLIPxDMfkA3JCUC19QoANSeOprJqKUumXxCRuSn7zGen2w/mnrd64b05gyULO8DCFcAwOLUlSnXBa/cyZdy9vPZqMxd/OozKiddy3POfcMRpLaYQX4UfBIEZPXo069ev59JLL2XNmjXsscce/OMf/9hMXPaVCPUf0g8Qro+fsBBKYTV6GFkPp9QmsA1EoEh+nosIiXSCaEDvFVkElsSqdVFS4CcMAktoUgHhoNlD2FbLAD1QKKWXaTJhtiIfKpvTbQvTzoQQ+julwDR1NEepUJcjQfl6PzKcNVIK4XrRttGAXQatSIwwbTAkXspC5gLMJgdlGTiGjZeU2A36TZPXmAS2QWAbmGkfPyHxY5LAlhhpD2XqvxH6ZRNYEj+uCZcwTU28gkBHPsLrIkxTR6n8AIX+H0NCEDIc3wfPQ2RzGKapCVeoI8qfk/K8MKojNIkDsCUqo4mgiMdQbg4RD2eC8seXouXaG+gUvE21OT8AbLN+UgCwbdPHNt3ntkojK0RZvhm2VT8x0hKVBKcuhpUVWE0Ku0nhJsEtEYCBH1c0lSqtcWnWg3Pfhmxbrffw4wrpa8JiOECgtRkEoCytlVGyZbBt5ARG3GWPzqt5Z30H3KyJ38bDTHiIlQmsZoHbO01ZKkPzsnIyy8vI7NhMUGcT22AgVEgQTIVbLPBjCmXp4wkF0tPRmiAWTsb5YaREotPackJHcSSgwKwxMXJ6PbMZchUQmIpYrSAw9TpucfgedQVWGmS9QBkSL6FQaU08hEe0X02qQFo+qskAoXBKw2vgaTIifJCBjtKoRq1hFQHgai2MmzMJkkAbBycTw8gJrLV2pHvJw0tqQuXb+piBpdPrhB+SLRuUVHp5TBMma7WNdAVBqLlRUhNM84cT0I+wLfpK0e1/wkoZ3PiqyzUTPmeXtedyUHJG9L1ou4BftlkFwPxuY6PlF93VkamjbuSS7Cim7LNLq31q8qIxqnpPKhv2ZmH+eJOuA2DNqDksGPAoz5y6G9lf3c5NRaOYP6COavTg/Knnn+GSO/bjxfNO56ddiyiadF0Uibnoro7s8PFydmAgVYsGctGpHTnoruU89fwz0XEXHz6Jx90jmcEylg/vQ2rWA1w07ni82QlunH07lZOH836He7kGqD+1Hwt235dq6xXiHmw4/QqG94Wn3zoXMyQv865q5Mguf+F3q0by9OwEVfUDmT+gjiNHPcb1dy7jqXZXwKkD+PnplzNh4T18sCLJvdccz5RZDzB1wzVcwIeoOVdwyoIxra4hwDTgmbuO1wtnjaYHmoD2N8fwu1WdATi4V3uuW7iCSQf3oCx9V7SPk09/j8qJvZiyYAIXTexIt3dnU3PiaKaMmsCS9F3AsGjdKfvMp8odSFn6LqaMG8iwV8vYfUZbzOUXsGT6BfzDbaTnNR/yzFZKU38QdWD+WzQ0NFBaWsrQbqdD5474CROzLoeK6Rl66WjRfpAwUYbETxjYNVn8IgunxEI6AVaDi/B1epmXMLDr9NNKmZIgZmCtaYSa+pAshAPs/KV3vU2E/aIlCgGIWKxFN2OaOpLj+WBIVDym/zfD6TAJwlc6CpFzdDRHBa2jDIahj5E/bl6LY0h9rJhN867tkL7CanBQUuCU2bhFEsNVxDY4GDkfkXNx2hXh2xKr0Y0Ii1NiYDUFmBkPp9jSM3O+nhFzE5Kyt+qQ6+s04VJKi/nzESShRftR+wLVQtzyKXZ50X8+7QwQptFiCCBFS+pZft38uefJmtESDYuubT46I1veXp6fZeHGWdTX11NSUrKtbrftFvl+kse20sDk8XVTyL5LfBvkZVNsKxLzv0Shn2jk+0mPy6cgE3G8ZIBVL0msF5gZRfMOglx7H+GEwvJiD/NzG6tBE5X0DgFBkY9MGxhZgdWgJ6LclCY6fkIhnTDtyQGEjg445YHW8pW6DNntXV5d05Wco59rHcsaWflZBYniLN3La9m34iOeX78LH761AyoeYBU7BKuSeqAfPhrzERHD1ccWgUC4WgPix3VbhC8IbJ36ZTaLaPDvFivcdi7WeisyIJCOTgMzM2BmtFg/V6Zw2wQYTVJHlhww09DUPdAkSIJon8VYkUD4kGvvg1RYNSZB1yx8HtMmB2mhU97y1ybc1iltmYRSEpQVfjYVWPp6iYw2FbAatH4mIjtK/++UtaS2BaFRQWCD1aBJmFui2ypUGNkCrCbRQrRcTXo8N8uH0yYX+kmIfD957oK53HLUlVS2H8dbn1zMhtM3F/qPOEM/D887/U1W/XQg9187gOcnatLizW5JmxpevzT6+3drOzO1ZA1V49NUz0yysGN/htcvpdp6hcl/vYY7Nu7IyuefBOCgu5Zz5KjH+N1fu7FhgY58HDJIR2Ceev6Z6O/8Z4ARVcN4fuIuXD9lNJfv8Iso3e3ILn+hsmFvAJaULGbDgkZGVA1jSclimsYdz9NvncuBU3dmRNUw4u+9yJK+n3DugscAGHDVcA56cwYHr1nGW9aDJGcv4Z7bezG/21iqZyajfaRmPUDTuOOjNh1013KWeQ/T1/11dF1Ssx6Ivq9sP44R9+7GvEFzefXt9xnQZxeqxqe5rnj3aN1N95vfNp75gL7dp7Bk3Szqkqdy7eyeTD3sd6ycmKXk7rMAnVoGOhrTNO54Bk1/nyUli6Njv3rHgZx2nBO166C7WhzqLtzvLqYsmMDFQ2cwZcEElpQspu/nP+Wqw+/dqn6y/ZuRb0v4AUZjDuEGoauV1l4I10cohcx4GE16UO+lbAJThrNfCpEfeAd64C+8AJlxEb7CtyQqZurBsx/oQXOY8qUcVw+ohdTRFMuCQCFiMUSqCFVShCotRlWU4bcrw+tYhtu9HW7nctI7tcHpkMKtSOK2TZLrmMJpX0R25/a4PTtB2zaQzzlVgR6k5/U2vt8SdYgIQ4AKB/JKCtwSGz+hZ68SG1zi6x2MZk02/OI40guw0h7C1yTPqssRq/UQgcItCp11PBW5pgEESbuFuPm+TvXKXxMvNDnw/dbkxfMg8FvOI/9/4CMMqaMlfhgxyROSTd3eoIUcCtliWpC/BnlsQl6Q4geZRratsK3JSwEF/NBg1QtiNdpty8jqyEU+TcyqlcTXSQgE1iqb2EaB1axn+I2sTu+KbZQkV2vtidUYOmaV6BQwr0hFA2kl9P+kPNrsVINKG7y6pitNTXGcjIXrmGxsTpIsyaKUIG64PP15b+qzcVCCVLtmDuv1b4IOOR1tiCuEq1Ol8sTDbBZa+xI+LmVORJERIyuiz3mPFCMjEFkDI6dJGUpHKIwc2PUKu0G3X/o6YmNmBVYjxDfqd0MQVyhb/+1nTK2pVAJiPiIrMdICP2MgAu3QRkQ6BEYW7EYQrj6uMhVBLNBRk+Ywi8EOkLUW5gZLZwlItMbHA7tBi/ehRXskAr2OnwxACcym0L0yjEoJX0QOaXn9UF675Nu6HVbT/+a+294w+NojogH/Q4MaGTT9fQZNf19rP2Y9wNNvncsnh+/NogEWUxZMAGDsBa9G2x+8ZhkHr1lGWfou/IzBo+e/SLX1Ckd2+UtEXkCTm8oxOarcgSz42aOsfP5Jsr+6nW6DfkHlmBwfx37BhKP6A5qcfPDH87nyhIcYUTWMK094iCtPeCgiMyOqdFThoLuWc/bOT1DZsDdi1GWIUZdR2bA3Fw+dwfMTd6GyYW/ifzydedXzOXWHw5g6qh+jqvfkkEEHUTU+TbbXAbyxu043m3rY7wAofeYxLh46g77ur+kx6iamLJjAsJX3R6Rg3lWNEVnKw3rjn/Q3x/D8xF3wZiciAjKnaimVDXtH5AVgQJ9dWDHnnOi6ADSNO56D7lrOY6tGRiSmyh1INrEzS9bNAsAcnWHseWOj3+rgNcs2+y0Pums5S0oWM+Go/sypWsqcqqWcdpxO50/NeoDUrAe4cD/9Oz1zqjZbyJMXINr31uIHkUK2zWAaenAeOl3JrIvwQmteo0WvIjyttzCyAVZDqLUIAgLDRLo+Mu20RBSCIEylEjpFynd0JCVPWLzQgYswvStmg2XiFyfJtU8Q2Fqk7sclQil8S2A3+JhZH6EgMARms07Zko5uF5bESxgEncuwbQs21LZEJSAcyG/y0xuGTsWSEgytY8k/sGXO1/v1A4wmrbvxYxZOmYXwlHZDE5vslzDFTIGZ9lGmIFdq4MUl0lMt0SAh9PlKicrldCqXsQmfVkr/C7bgGCakjrp4fksaXj6qEvihI1kYxcpbLhubRLz8oCUSI4U2DVAtds7CsvRvYmxCaApohYHXzN4uSMxry7Yub+On/f83ZgUF/HigJDTt6IEdENTb+tEUzuwbuZCw1EhiNXp5pj3kOnjIrNSOXvngeE7hlAqUoRX2yobAbpkUcku0FsNYa1OTLSO+1qRRlWA26si8TlMzEM0GKh7werorNFgoO8DwQArF6mwZytWCeLNZIJSONBg68xa3SB8nH21B6JSvKMJugcgRpaBJD2IbDAJToZIQT2sCpwxo6ipC+2IfSjyMtbYmOHH97ghsMJolXhsPmTMw11s45T7ENHmwGiV2PeSazVDnEhINldfWQDalUKYKU9yUjrhsMlcljADpCaxGgfRkSyqcQWQdLQKiNDff1mlghA5sMiO0jbOBtp9u1Bodt1hF2wqlA2LITUhmAZvhksdP0oPzdYt1dCVcPmXBBC6umsHwvjdywh39qNyzK6uvfpKz7tBjmRR6kP58OOs/p2oplQv25pVJx8IqmFqyhuowkD33kuc46voDWPJwjF+fuZQ3n/g5/vT3eX7i6fxm1MdMLt6dQdPfZ8ppD8C9cMggn5enDuJnJ+7C5FUd4c7jeX7iLhw0SEcP3rIepK/7a54u3ZNn+k3g4HAAPrzvjUxuaMRYdCqgtSoH3bUcPzOMuz77KxPu/4TKQXtHmetLShZz3KsjmTdoLlXuQCZ06091nyRzWRARlglH9Wd+t7EMq7qfUdV7IkZdFg74iyOicuPy/uxlvUJq1itMOKQ/J17dm77XDGDKgr15fuIuGHc9yoh/HEXlni+z4OyPYOZNANSU3E15wykMmv4+lWNyHPnoXwDCNhtgQZU7ED9jsGTWAxz/1mFUbxJd2en2g/no9IUcvGYZPRr25umO/Tl4jQGkGVW9J3OqdETsL88OB4YzcsjTzKElSpaHkfDxO/eDD975WvdOgcBsipwLRQrhK7yUhbIkZl1W62Ky2k5YWUboTgaBZWB4bmjpi9akKIWSEuH7qJAUGLkgSpnKi8QxZZjWpKM2wjRQxUUEJQm8Yjt6OZlpfaubWV/bF9vaPEC4AUYY1/aKtEuZ1eCCAJHzMd0AL2WR3rGEhGUgPt+gB/h5IiPRxCAIIx+WpQmMEJgZvd/AlkhHEyU/rv0rA9tAmZqgCKVT1qQbaG2LF2ACypChk42+joGlQ+2JDT5GfSYyH0CpyJkNmSd4oQuYabbWoOQjMEJHjVSej22aTib1TFxEZjY1AchvSwsJ2mL0ZZNlyix0j+8jtpaUfJN9FojM18cTtfvwyzZbV6X+xwRlgnQkga2fQ9kKRdFqTQ58W+HHdY0Tw9HRiFy5AKkQrgBP4BaFxCSXr68iQYFTFuiBd17i54QamaxASYNcO1+THXTURihIlafJxGMgFLGYS26djUib+B1yNDfHed9oi7R9lGnplLGicPCOJmL5wbcyFEFCYTYYyJzAzGpNTiDC9C1Xp4FpJzAAndoVmODFNcEQMb1ufK2B/MyI0uCEp8lHYOmoiVVjEhgh7zC1s6W13gpJmY4QCV8fx8hBYmNAto0k3SkgSAQYJQ7B+jhmWuL72pggSAQ6FW5dDLNJoCzt7GY4+riBpSDQaXN5lzXpCZRUCE9gNOt3jR8DP6YwnFDAH2qQrEYRkhwQ4XkpQzu35VI/+mz9L0XTuOOZOqofZ93xO2AxlQ17M/aCVxn704Ecd9TtzKsaxjzg4tdeYUrDhGi7Ec8fwWTeBDThmXvJc8wNvyu5+yzM0RkGTX+fI64azNOl/TFHZ3h69p50/PAC3rukC1fPa0ftvn9kEjBs6P2s+ulAzrrD45lxu3FzY47ebd9mNU8yFlgyazG//o3JyFgTY47vTraXjkI07NObJSWLGd73RlKzHuBI4LFVIxl43Z8oZ7colW1O1VImdOtP1fg0w1ZqmjYK7S6Wj0LkoyJTFkyA0NwjT8IO6jiDyjXLqFzQEqX413JNVE6f/j407B1FnE4H7tzrEwaF6w39x1EMuGp4y76BhR37c8RVsKTkAZYAVfSP0tIeLbkbgCOuGswy60HGjR8FMzXxqszszUqe4+KhMzj59HN4pt8Engn323DKLazY83FW/AJgNN3GTwQcRg55mskNHZmKNiWYe8otlLNLRHKqrVfY76l/8snhe/P5G1ufSl4YoW0KKRA5F5nz8ZNmRCJAR2CEr0AqAls7b5kZn8AOQ9JuEBEZFTMQWYUIher5bSORuh2mJvnhbL9hoJJxvIoUbok2AZBhUUbflgR2fgAOsVpXF2wUAukGKFMLHo1cgHQ8lKEH5m6JjVNiIpSiuXuKVFMG6psQMVuThLyeZNPilUGghe8qHhXNDBImRrOLkXFx2ia1o1iYNhYYAhK6gKbMBC0REwMdxfIUfkwXPAOwGl19jDxpyeuADKO157dt6XWkEREbAkNrZTYxMgBQSrS2gw5Ui/YlT4Ly0TAhNXHMR2m+KP9SgTYMkOgoWEkhhez7hm+DvHxx/981idme9C8L/QNobvjhuSttEwRaJ+EIE7se7PpwUqoZfFsQGHoux4sLsuVhIctG/XyLrdfpUUYOAltE1sYoHfloHTHQQn/hgl0nyBkCUerg5udvspIgEJiWR67ZJp02MYNwsgcwLY/mTIzAk9hpvTzX2UHkDNxiqQflEGpxJG7CwyvzsBotlCRsI+TaBsQ2hkYAtBCCIAG5ckV8g4wIip8M8DMCkRat3MWE0ulxfplHkDUQrkAFAqPeBKkg0NcxvUNAUOKR+NgOjwNOqY6CBEU+ifIMlunTELMJHJ3K5tsKJRVIkE1a7xIZDhBe25yIrnM+kqRM/T9CITxtKw1aAxQYWnMjHaJolB8HK6e3C2ylyV8g8FI/LFOYbYl5VzUCL2+WQnT/tQMYscnnG27vR9/d2tH2zv0BmDxHk5c8Afh8wp50mrGUI64aTNUhOlJQTUuq1KDp78MagF9Tas3n8eMewv3FUxw1+UFOnvoex3U5hBv/ejuj9vobV+28iF6rnop0MoyD8UC3Ox6AV13mXvJctN+VE7O8+ta5DB93I4Omv6/JS8MpeLMTjBgNg6av0cRhfJqLOldz0FMzWgnh53cbyyzrQbKJnbeYRvX8xF0wyfA8LWYFqVkPsBdQPuhybv/scu77fxZDb96J2493mHObzZLf/IUlwKTGNLX3vxHVbVmCvi4L3+vIkV20pmZS4xvR9VlSsphBDYN5fuIuLCl5gJUTu3BR52qOYHB07COuGgyXwOtLD+fk09+jx6ibqBqfhpmDmXvJ4eyx5+MA7Pav7jz/Lx3pWTI9rp3l1izj+YZTAKIIDcCiARbX/HQub1mH8QgPb3YNtoSCBmZTBApcD7Mhq8mBEPhFto68GAZB3MRtE8ePS6SvCEwdkfDjJoRifWVJTXTyg2Z0+FgL7YModUpIGaWRqeIkXtsUytY/h+EEmM0eZtqPiEwefkhujMasLtToBi0RoZiJV2zjlMU0cVA63K+kwG+rC9upfPqU57VoYCCsSKY1P0ZaR5WUAC9u4JTHyXZIkK2wtH1l0tRtzPjabtrVOqF8G/yYgXQC/JjELZL4tiBR42M25hBZp+V4oYgfQKkWi2f9/SZpY76vRfp5q2jPQ/mBXj+vITI0ERPJBCIe06RHiihdTZMrvyWS4wchqdkkfWwTkX9QnMBPFgjM9wnfNnn5Ovi2SMb2RF4K+M/QM+8iSimyGxV+HBp7BPgx/bdTCpmO2sXKTEN8nRaz2/UCK5yBdYsg00FrX6zmUI/iEE0MBTFwSgKc8oBcRaDf6gJE0seuyBKUeKQbtB5GNJtY6yysBn0MBLQpTpNriCGaTAJL4SfASjmYFaF1q9Bt0xF3kM065OLHFW5K4YaOsSoW4MUVvqXbFIRRE+npyIcK56iUVMisDMsMaNtj6erUK9/S5MfcYCFcQVDs4RX7GCFBiNXpCJaKKfAkytT1Y4KYTt/KlYfHlIqmprjeh63wkgGGI7DqDKwaA4KWujOBrX8HN6VT4XTdG6IUPq9I/1aollowCL2uHw9Jiq4TraNVlsJLhO1p64e1chQqXiAwW8Lrxa9scfn91w5gckNHars+riMrlzxHttcBAGw47SWASC8zZcEEFnbsT6cZekB8+2f1zHh0GdcV787cS3S04KJDFrOwY3+en7gL8fdepP6qtbziWqx8/kna3rk/dw9tGTTvP1Y/hx+a91Neyl7KS9lLmTqqH97sBE3jjufhB/Q44u11n/L2Ol1va3hfTV4AXn35HbK/uj1yELt4qHZVy0deytJ3RfqUt6wHqZ6ZZMPpV1DZsHckdgeY3NCRt6wHo/PM739T1Jw4mr7XDOCiztWtlk84qj+3/Makd9u3Gbby/kiTsnJilsqGvTm4V/voGgJcV7w7VePTPLZqJM9P3KXVsY64anCrdgFMW10V/Z0/v4Ud+0fkpbJhb2pK7m5lJpBfJ78sT6rykZ9bXzuCW1I/2ewcvwyFCMwmULkcSBtZ34xpGARJKyIo0gnTteIG0lWYTbqOi9GUi0hOPjtJmRKUgbJN3BIb6SmUZUSDcOV5WsdhSFTMwi9N4LSxQ8IS2iMLgcx5BLat840dhV3rYKS1tbGyTQJLD86VockGwsC3dQTByAbYtZqkOKUWTqlN0rZQ2awmBypMHRNCF9PM2ysHAaI5iyUE2Y464iICTdasRh/D0cROBAp8hQhCzZCl0xuad4jpWTlHaWvNbEBivU9sTZN2R8uTirz1sZS6xosQYIaC/Hz0JYyeKCk0UcmndDk5sIiE+iIeQ6WSuCVxlC3DSJjCaHaRjVlEc0bvx3FbiJvcJAKTj86A/j+0YnaLCgTmP2F70cF8Wzj75pnb1I2sQF5+WPCTCr9YRwqcMhszo9OkrAZJYCmsJkIhvCCxQWl3rmZwSvVIX3o6VSkfIVCmwinRLmRkBCqci7FrBYGtbXv9hNJCc8eAnEQWOQhTIa0AP2dE1ejdlMKuF7Rp00RzzkbktD7GK3NwHIPiuEsmHcPM6AG5MsLIQqMmHUFxgJEx8RMKp02g7ZsbDfyiQOskk4EmEtnQ2cvXhMdoEHpdJ7SNNvU5OiVC/18WivtdQS6uEGaA8rTWxmwSmGlo7K4jMXn3NelAYLRocxCQzdiwPoaZC62gDS3qF4EIXTEVgalT22Re7C/DWi9CXx/pgpkRkX+A9MCNA20cqLFRaGtrIxfWt7EgVqePoUKra1ns4sUCxDoringV0BonndAXseoyBuzTm27T48ypWho5U604/T0+6tWekrvhgrLP+VmXK/nHqkuBkMQs14NnNecKQM/s15TczV67vRO5afUvrefVXfWxFr63jhEUs2iAxak7nAOPwI0joPb+P7LgfnjVWkPldS+zalEH2g4tZv8/thSw3HDaSzQc/QhHTB/M3Es0efnZw7uwcmKWt9d9Sp/2dzP3EihvOIXhfW+EP+rtpo7qB9xI5W51jKrek6Zxx1OXTDCq+i6WsJiVE7uwoaGFMJw7r46fdZnByae/xynAmtPb03fNMi4eOiNKU9sUm7qRiVGXATDqjIuBLmw8ahEA6v9dwYhLWjQzS1hMWVpHYpaULGbJo8A47Ug2tWQNg6brei11yVPpNv0uaNCWzoPQ6Wd5B7MjrkqypGQ0hGVyGk65hXtensCo6j0ZfVR/qqhi9n0XU3nVTVQdlaZ65jKWlCxmTtVShvfV7dYk5gFNrK6yKP0aNsoFArMp8jqQnINR34xQSYKyeJgDrJNxZaj5UFJgZFyE62M05CCfYgbgK4KYSZAwkV6gPftNqS2D8wNz0OQhlSDXRqesqHwalSJ0PwuwN6QhDIEazbkoquPHw58uJE4CXWvFyNekyadS+RDb4OMV2zo1K5sNow2iRQfi+ygPhKGJkwBkOoeRi+vZt2YXP2FqK2lDaMtkpQt+6vMAr0RPnXlxoa+RpzCbfey6HLI+3eL8BbodrgeWTtMTefG+H9aIcd1NtDGbWij7+rNh6NQ320CVl9K8Y0l03UCTNy9p4KZMZFkM6ZVg1WaQdU26po7jttbFqPAC5qMwYWTGSxYClF+F/xWJ+V9GX76LNLICefnhIbAUsUaJSlukPlHYzTo6IAJBpiPkKhSBpYivk+TaCLy4HtA7pVqsbzWDkQFiRMUklRGmMSUU8RpBYp3CbtLvk3RbSUNPnQJmf66fx35dCtXG12NnRxLEAl2fxlTkysH0DRprk8icgKKAoFlHPprtOIYZkOvkQQBmnYldK/CSmihY6y1EoHU3gRkSiZzQwZ8AVNwHV+IX+9qUQBHaGmudjJfQ55gX1ntJXVvGamqpnxJfJ8kpG1Xi4SUU0oO6Pj6YCtlkQKmLK0E4ApQmRsIDo8hDGj6BpyNVvg1GNj9BpVO6pKfdylT+dSzC5gSa8PjJANnQ0m5lKLwkeGUeUihUmYtfbyGb9Pr57Z2S0InM18cImi2MEgevxEBahVTLLeGKTkuYct+EaGA7ZcEEbj3ueg56sz891txEmfU4y0adz5Lp65myYEKUPgYwAriYGUwt0QPul7KXkn6riZLkDJ55awLDx91Im+nvAzOonplk2FAtgH9+3PH0iz3M+NwYzp1Xx+GDHmvVpsknHMeS5euZfFUjU0vWMLmhI5Oa72HwfTD5rY6s2PNxup04mpUTtctFn/ZdKQ/TouZd1ciCsz+KLIonz3kTb3aC/3e0FsynZj3AhEP6Uz1z701c0jR5ect6kIu7NDK8743UnDianUrXcvCnh7NizjmMql5MZcP7VB3VP9LKzL3kOcrDNnebHqckqSNNoOvmTPvleVx0yGIW8BEvWY/x+FFHcl3x7nQb9AtqTmx5b1c27M1Di67jbOC4V0dSNT7NvPnzaTjxOS3Fmb6Yg96cwZL0XTSNO565ne8Gqpl7CWHEpVe0rwH79AZgxqPLNIk8cTQfJU9lyaMtKXNa+3IuhEGc4X1vZMwZM7nktAfYtXyHrb53CgRmU+QLIQIi5yAbwM65eGXJaGYfQGZbBOXKMhCOh8LQqWKWgQRts2xLzGZPe9m7Og1K2BbK8zSZKS7CbRNHmQLp6JeQdANkTrdBOp5OY4tL3CIDs9lG+CoSyGurZ20IoAy9D5nTbfPjZmT9rAztUKYsc5PULB8IwAm0sYAKtJ7EdTWh8H3sDc0o2wRfoYqsMC84tM8MZ7ucUhOrSTuVSVeR9JVOLUu7GM0OOC7CCwtgWqZ2HYtb+EUxlC21xbSh0wLs2hwy7SCa0ppP5CMknreJA5nWtoh4DLdLBUHMQHhKO54ZQkevAm1A4IWGB4EtyHUowkzaWJ/X6jZ4PrhOa6exMCqmU9VUCyEt4D/ixxyJ+W+jMF+HuGx6nALh2Q4gwS0OsBskufJQp1GiHbh0bRAdGciVK8x0SARiOoqCQtd1kWDVSG1V7Ot0MqtRD779hC5kGVjaNCW9A/hlHuZGEz+mdLFJCRhhJMOQuigloDrkCFwDQ2oXSbtrMx1KG8l6JuvWlxA0W5htsghHYtVIzIwWuvsJbZGc17IgiLQkZkbbC2t3TAu/2EfEfS2LbDLCYo8K6erzNmpCEiHD6Iebn+TSEYzA1qRImQGp7vU01hTRtfNGVr/dATMj8IRCZKVOE0sGKBf8lMIyfWzbo6nMA0xdRLMptHOGKJUNiGreEABWWKMmLciFEXmvSEUTY9IFAk1KrLIsbtpASQMjo8mm8HTqXKZdSzTIrDPwAhvsANP0KWBzdLkmzpKUFu5XLtibW4+7HtDRkkl9NXnpP+d6nh91PsvWnwYPnR+tc+ZD5zNlUIuo/+I7j2fKaQ9Q+owmJIOmv8/CjtoaOZ/mlE+FGp8bQ03J3Rj7VoGlSci01VXMq9K/05KSxUzqupY2nx7OkV3+wsoTSwHo9/c7WDHpOn524i4Mvq+e2w9pCI/9PhcPnYEYpQfk+ePH33uRz60aPpreAXhAp3KxlAGX9GbRyitYd8llvDLpWBac/RFrXx7NlAUWU067lMePOpIZjy6jErjn9l5wO9qlLKwH89iqkYzNpeh8la5bw6qRwDq4eSeO7PIXAJ7pdz8/fXcHhhadzOP7avKiIz03kc58wLjjRzHjUR3dGVW9J+/2WhPpiUYMG0abmUnmXvJcqFXR13nKgr0h1MOsmHMOry89XJOW1UQRtPJxN9L29stYWXI3gxoGQ8MyQNtLH/TmDJ7pNyGKRuWh0wM/5iEnRe+tvHcKBGZTRCLwUOSdziByDmagUAmbIG4SmC2OV37cRMRMPcMkdG0YPyYxszJ0VdGkxCm2SKQ9hBA6jSksVqkSWmiP0PVSpBtgZL2WXGFTF6n0Y5L4Rm054ydNbW2c8VCexE9aBKbeQPhKR3w2sX4WfoBbFiMwBPYqD5W3D855kIiHlsItA3URj2lXtIyO9ggvQNkm0tF20IYTkGtjEV+nZ8STq7SmRea0lbPtK4SjU7BwPV0fJ0RQmiTXLomXkGH4XiA9hZUOyKUM3JSB2RzDaohjrm9oSf2Shn4R522OixJkdm4HgF2bxWzWL3CkwE1Z2rYanVedJz5BTJKriKHsCuyVNYhsDhWE+hg/QDsqCJTSpgEiCJAFArPV+DZJzPdJ+7IlfBWJ2ZRs5NfbWgLybRfMLODbg5ERmDs1k/u8iMDUqb6ZDgFGWj+vAxNEeQ7fl6iNFnad1ANqJQgSATInCCpcgiabWF2LRiMvdjdy4BaLqOq98MGsNcMUYoHqkMO0fZwmLWRHaXMAPw6q3ta1S9orysqb2KGkgUAJPqspQeUM7I0GDnGko+ubtDiLaQKW6+hi1ZhRmpU+JiTXKbJtNDEJEgIr4eJbATQZoSWziAb80tGp0V6RwLe1FsUtDjAyArcsQFkK7IDyNk3UrC+BbP65rg0QgqyJldG6lCABfioAQ+G5Bk69jqD6ZR72mrC2WWh4ENg6HU0EOkomcyHpktqYJrB1xMVolGS6eBhNkuTnkly5LuaJJwhWJzE9gXRE9FsoqaM9ytRObTKrz9XISIKUgyzkkH0pKtuPY+5ETTDODAlKp9+cT0PxdcCl1JzYlbezl0LxpSwaOpN9q/en/L7ZVI1PMzQcsP/zFy+x75P7c3FoeTxlgSYqB69ZxjPhcfLEArQIvmhxZ7geHneP5CKqtY7k6GotUi+BZaPO10U0B1h0mx4H4F2g7aCTgBf4qL4Dpz+l93fxrjOi1LeakrvpNj3Oq4cfwoAHDmDZqF14+q1zUXOuQLA0cgJbUjINJsLA6/5ErwdW0ZbRrO3tsn/8SoZ9qCMUlQv25hD+jNd3FTOiApa7MAKoKWmC6/7U6lp2mx5np9K1APxj1aX8v6MfYbcle7P2qfUM4n3mXvIcqz58lV5nz2fWA3NYObELas4V9Ot1R3SNLh56Lue/uwNtPj2crh+P4u2e06PrumLOL+gx6qboeEdcNZgppz3AjEfjuo5ONcQzl7Hh9Cto/1YX3rJOoq/7a+LvvQhAvF9FZJGd7KkjT+kPm3jpNC2me/tPw6D3a1t13xQIzBcRiryVHyDMTQXgATLtEJQmCOLahSzvBObHDJwyk8YuBk4xlC+XxOo8pK/wEwZmxkc2ZSMLYNAaEGVqgbvVFGBkfYKweKaKm3hFFoahiVBiTRbhBXgpW1sY+woVN0PPfKn1Hhkf6fpaTB8EGI1+qOExIVD4Ka1viSIO+er0eaeuvBOYp7dHSoTjgqftoHVUSNe5KWrIRcQmT5bwFUZjs04J8zZx+Qq1Ll7bYrLtE2TbGMQafaxmpevLBBBYIrJkBsh0jBM3BNZ6A9HQ1GKx7LgI08DpWkEQk9g1DiLno+I6EuaWaK/P/H4JI1W+LVFCYKZ93KRJ0KMtsVV1iAbVEuX5IlyvJUWugK1CIRLz1WRjWxGXr0uEAPrf9d4Wly87tdcWlxfw3yG+XpD5rAjphc5hHiTW6smbXHmAKvZQOSOy2s108hCu1BqLBk1ocoYOmYhAD/jNjB686zQyrRnxigLMJomRE8Q3CDLttP2y60uS8QzOxjjEtSbFj4Hs3oy3MU6sRuIHgobGJK5v0LS+SBcuCcX3ZoOBkrqwpVMGSJ3upgs1yqhwpFekRfKBJVBCkm2nI0cyI3HXJlBJH0Nq22htNaxNAZShDWbcIh1tCop8zFozEskLTyCyJjVOGbF1OoKzen0ZUoHdoJ/5ZrPALVaoWACuQBZ5JJIOzY0WwpGohI9XrDDSWqsiHV0Xxo/rqJfwNPkKBOF3kGvnIR397o1/FhobxAnztAkJmHY1E74mL35MkxevSNefUabCTymMrG6jp2yyMvml98qPGX89aBlW9Sy6TY9HDlxr1hUB0BFdUfSIO8/nlYaOYTrXOxyJFq8PHTqSQ0f15s3xNez7pE4tW1KymNSsxdCwt7buLVkTicXhgajQ5Cj2JHfWqVzXV6dbretdxoDfvMC7vdbw/H67AFqXkuUAKtv3pjb3e72L9zrCb16I2t9pYTl9fzmKNgvWM/eS5zj/3R147kTtsHXg1EZgGE+/dS6jqvdkxLhiBuzTO3Iw6/X7VZQ3XMGkxje47vRT4PbLaLvzaC3YpyWydNaqN1myfD007M2STYpUtpwXlN+n7YfvqerFSZMOpvboGm4cVcZv3r+BOyrPo1tJnKZxx7NuL5t9p+9P+X1P8d6iQ3hl0rFMLVlD5/0msXrRdQCoOVcw9dM1LClZTO7zi6Cnvq7dBp1Dj1E3bSLof5J7bp/Rqh1N444n+1YX5s15h0NHQTaxM7g6wjK/WyXVM58FYNVPB4aW1AaP12VJjK4E4Ib7H9nqe6dAYL6IvJgdogG4yDlgGihLL3dT2iIY8ilV+QgImFlwkxIrDFkLT2lNSkOzFvFHYnEBUmI1BVhNYcqYG2iBvhB4CQMvYSCUTo+SCsy0ixc6YylD4BbrWbX4BpfAlihfRPVYEEJbO5vaMS1W60LOCSvWq01E7EEkXFehQ5ryfF3nMqcJjqxvQjZJlG2hkjF9TRxPH8f1ULaF8DXx0S+11gP/IBUn2z6Bl5RYmQDhoS2oDZ0DHVgSMxO6qQW6OKZbbAEpLN/XzmW+r8X6xUmcUl1bximzydcGU3nraQXS8TGyHm5JDN/Ws5pm2sdMuxg5SbatjdE2hRkEiJyLckJnNMcFITVRCgKSKwszZj9GfFP9S55MfBNysSm+TtTl5rPHb9Vxvoy8bPrdslN7tfp7a3Cw8SJP1O6zVev+2ODFwaqXKEOFTlRhPRdHYeQkbqONU6oF8LJnE07GQuUMpFTgiHBWX+GV+2R8M3IdEwH4jo4UuKW+Fo2bQFZHdfyUj58zoMmk0Upgljl4GRPhSrwKl5Tt4XoCq0ngBxI/a9DsxbHXmrhlAUajoSMLviYZRlYL8P0yD7VBP3FFqYNqiOv3UqPQ+04p0l09ZLGLqrMxGwXSl/ieTo8jHiByQk/CCa17idXqqIaRFhhpE+lqkwKrVmI3aqF/ulNLzpeqtVEScm20lsYpVTpSIxWY0K1jDRuaihBFHso0QOoIi1vmI2oNXVcno88n11ZHe0A7u4kgFPHbAUHCx83amnx6IVkJU9AMJ9TLKP1b5MqU1t+E9svCC4tnxgICy4iInr2xUBj5y5AnLjsu7Mwfp/ViyoL8N+drwfjE3SG0+D0ylLzmq9E/xTHMXzCW6/51fKt9Tg5Tq+ZVz6ftUO3CunJilvI9z2F4313YsOB2Rix4lnnV8wHY7Y+n0/Sv49l11gPsNEenqL1gHsCBK8pZce3P6DHqnUi83j/8vs2nh9P/92mGdjT42Sgtsn/uxLt59eV3mLJgArVdH4dPteajsmFvqhrfYMaseEsjMzCp8Q1mPLqMQe0rGTtqN0bGFlHecApPv3VuS6Rm+Xoqd2vHjSPKMN8aQqzTG4yqbrluK+acE0VFpozS20xe1ZERwNqn/kq3kjiv3nEgzvrT4EngN/vz6XmX0GXVWo5M/AWA1KzFHFd3EfwN+pXdwa7vdaRL50pY/TTx1Zqw5I9RU3I301ZXMePRZUxpmMCdd9jcu6AO0Glza3u/zaGdh7PD6XtQAywaOgSv7yqqeEPbLQPv0Ie3rcf4/OASJhedzKhBN3LA04eSGLUHXPnRVt03BQKzJeRF46CjERhay+EHUBzTOhRTYDZri0Qz52tnlZy2DjZyOt1KVwKG2OdpTRxARxPCive6OCQoU+DZBlaji1usXxBG1o/yc5UQuCWWLmZpCtyEhZMydNqZp/CKTIycH+Y4h85kpsRP6pQ2t8Qk9UF9y/mJTYpGRjbKm5C2LwrcfR+C0JbZbREiKjOsyZLN6WuTj7yYRkRiVMwm1zGFWySx0iHBcANEoJAK/Lgmafg6AqNCUuPHJIFtI50URk2TJhpxG69NMrK3dEoMRNBC6Py41rxYQeji5vgoU1+bwNTRLeErjGxAtn0M226D/Vm91pF6HuRr5KgAFQgd/Snga+HHHIXJ439BXL643X865n8iL1+2Xv+73ttqElMoYvklCAe5kczCBGL6ea6EjqLY9RKrEbIiharwEDmJytoQUzR38enR53NWfNYWoUwCG/xEPj1Yu4nJnNT6Dl9g14P0IRMInLY+9gYDURPHaRNgtcvgSosdu2zg44/bY2Z1StR+HVfxUronXtrEqfDBUgSuThNzSxQqrqMidp0gSNtIPxTcN1iIcFBvp3VEwssIvCKBYwdgB0jf0MUcCd3W0iFJsEEkQyIWE6HTWViU0tX2xs4OHl6DSWKt1NGNtg6iWQ9XgniAVSdxOnjIpEeQNsGRWHUGa9qU4PtCR7ZC4iB8ECosC5BQETEL4tqMx2oMa8LkfzZT6ddeUYByBKIZDEdH0KQXpsIpcJKakMbqBE6J0pGZvAbIMfBTAq/E15EkX7TysSmgNSY3dATgIeBXF73Hr0K9ypQFE7iueHdSsx7g4qqlzO82NtpmAVoon+yZ4nAeg+xj7B+/MiIXgx5riXhtWNBIYnQlr748myOuuokeo2DVlUAVjKgaxqKhQ7jrpzr6MH7c8Xw06wF2Kl2L+uVemggNfZhT5pzDvN8cAmhnr9sPaSD94QzOf3cHDj+kIUy5ep+Lh2ryMrmhI1M/1XZaeaKRF99XNuzN3Eueo9v0naPPz4/zmFvSpGvYjH+Dmn16M7mhY+Qs9o9Vl7ZyINupdC1LWMxzdz7AeWNuioT3H9V3AOBX1gcMmv5rbnj4DM4bA/zmBZovHs+BK8qZt6CRtkPf448bz+dXFfp67dCxmEU76t+hcfwxPCdO4ddX3sxh+7jMeFRHfCoX7B0WsHyP6qtu4p+/eAme3J9+My+Cbn+Lzu+DzsOJV0+jR8PefFZ1kf49pr8P44nsnpOHufxs6C58VA/GsE/AggNXlEdapa3B1yYw1dXVvPzyy6xZo10fOnbsyD777ENVVdVXbLkdIPDBMMM0MgNFaNPr6fooKhFDBCrygvcTYQ0TU2I2udg1fjT4z7Wxdc7xxiyiKaNTlfIV5vOQ4Mdl6Eyj8JKmjpi4gSYnOT8SurvFBrkyva309YyeUGBmdNTCS5g4JQZ2vUFso3bGEF5AUGwSq3GRteFgPE8s3LCMsxAtmh/D0AN4Twv/84U3hWm2EDARiv4B4WwSoXDC/eWjV0IX2AxKEmQqTOK1fmjfaRCYksQ6hdXkIh0ft8TGzHiR4UC2QyzMJ5bk2sVJZF1ETttWuykzchnLQygd6XINCAyBdA2MrKf1QDlfV26OSURxDC+f0ucqvCIDWZHC+iwU8+cNHPK/0aZ1aQr4UeC7KmL5fdS6fN1oTAGtEVgQS4eExaBFsB5qWKxmbU0sAp1uZmQtAlMhfE1AzPYZLOljfRLTKWEdfVTKQzSboRg+HzUAH4USgvhGiK01cHplcHMSq0EQX2eQMeLE2mbYuWQDK+PlEJh4yYD36trhNVuImE+nLjXUNBbhFhl4a+KouI9MeviOxEwbJNcoAkuQbasoWmnix7VmJUgLTE+nhaEEfswkCNOrCHS0wsjqmjjIcJmhzzuwdTQlsEPykgQjLRC+hd/eIW2aCFcgpIISF7neJjDB6eyCo9+dsbIsubo4ZpMg+3kS0cYBTyAzMipGaTborAg/rnSdl5R2B5WuiBzUAkuhTBBGEOaUaRLjF+k2x9eZmGmdLuYlFIGh/waIbwxT93ICmROh3kfitXUhMDAbBEZjgcFsCYc9059DD+rNfgueZUc6A0RaEtAD38odDmMOSxm28n6SPbVWIj54Mf16jmQAHak6Mk2bTw/nhoeHk31Me/pecsd+jB42ib3vfZvFJ/Vh8MbjOYQ/s6RkWuR2lsfik/pw/5gBAHSb8wten3g3Gw5LMnleHYd26cdZq97kveWHkJo8FYBlr+9PfHANI2fq6PPj7pHMY74mYuF+J/W9E9BRmrmXPBdFZfIpbOUnvQkTjwbghofPYO+33uajkx7hhodh8KPH0404Ayf+KboWxr6fwKO6vkv1zCQ33HkGNff2Y8A+RzPltE91aYlD4HF3WEgSuvD+QcPp2VHrTJorenHv0R+x7x4d+eQXx8MqmLjXpyRurqL26BpmXvsAqfF3s//YmewP1A3ajw6X9OemlR2Js4wDp+4c/TY3POwwuGQx+z65P80VvchMncy8I9NUP5bkkjv244aT+sCdD/AckBp/N6cdp2cyqmcmqeihTRX+8UYfFhz1ETMeXQZoA4ZFQ4dwyeMOVx1+71bdO1tNYNatW8eRRx7JokWL6NatGx06aJa3du1azjnnHPbbbz8ee+wx2rdvv7W7/P5Btgy+kWE6VT4CEbMRrofRkNPi/UBEYnsdkZFgaAcsL2lgOAFWXQ5jXR24blT1HohIhMx4KGlHURihwpmoQGBkPKTj4Zt2lKbmJQR2oyY3vqXtk420B4bAlwIvJrDyNscxQ88uNXvYK2u0fbAUUXX7iJDkzzvwW5y+bEs7svlB5EjWCptqXExtc6yCoGXgrxQqZhOUJGjuksRwFGbG0+eQlGHetIEyBHZtThfHtCTCM8ICmkKLXqVOxzPaFhFL5/SxQmMBIxdgNQYYbmhTbQiUNHV6QamB8CwdxXK1+47V7JErs8i2MYjXCmJ1LmTDopxlKWRdk87/lmFdnJgN+dSyAr4WvkkUZuA1s7+l1mw9vgvysq2Iy9amkn0TfJ1oTAEtsJogKA4/qFAE77eIvc2Mtkn246EeJG/eIrUAnI+L+PDjIuINYQpWEK7g6yi1kdPuWk6ZAqEH335cEMQUQYOF4WkSZTjQ5t8GTd1SvF/WDivmgQN+Ebi+gWwyCHzB2poSAleicgZGADJtoBzt8pXXKubKwSvRek3QpET6Ol1OC/rBy+o2KKlJilfs4ycFic8MHY2S4IdV64WRJ3UKX4Jf4mNtNHXaXSBIdGomUxeHjAmWNkDwd3ApKsvQvK4IVRMjF7OIrzGx0hDUSURNIvoN3KIwMtIQXmcZuqiVBbr2jdAkJtvRA4GOWklNYmSjxK3wdBpaYxj9MXQkLf9bGrnQXc4KzyvRcjzpCPyEoS2wA6J6PgW0xh6NA4kveDb6/PHBqyMnrDyWLF8fDpzP4LwxtzGvej5vfghvfvgXzhtzGzdcewaDTzue2fPTXNVTbzPj0WVwpyYn5425TUcdqqdFbmdLSrTz2bzq+fTrOZ95YR3I9NLnAOi16ikenQpP0YumP+jBe593zwag+rEkD51wHP/v6C70vWowF3V+jm71HSI7Z9DEZXJDR47s8hdemXRsFEnJn1tt1+Fc99ZpTC1Zw6973wxXwjn76CjGlDHv87h7JMNW3s+rQ99pOR90BOMIBrPx0MdYMH8so/tMYuTv9yGb2JmVE7PM+v0cXh3UyIB9evPWn3Ra3e61r3HgqJvo8tpsplw7gKnodr5+/3OMGDGMtZ1dau7tx3kf38JHt1Wx0xmHswiYO2YG07pVwVH9GT1sEm2HHk9lw94MPk3vd+XELK++PJtR1Xvy9q5TSQGjT+oDwHljbtO/XYnWIy0aOoRzuv2NKuKMHjYJDn2M6plJXVxznyyDu9az+KQzeOrwY7b63tlqAnP66afj+z7vvPMOu+66a6vv3n33XcaPH88ZZ5zBI49svQDne4eKUkRDTpOWQKGCsKCibepBu2kgsjnsmtD9y9aDcKtei9oD2yBImNj1DrLJQW6o1RGNsNZJFN0wTV3xvtnByCXIlWliI13tyGXk/KhwpjL1YN9q9kMRoi4eaeR0MU3pBQTCQDoBsUafwBJaJyN0Gpq1cgMqk2lxWIOW/8PzxKB1nZZNCEu+/QShHsg0dVpdWGwTP9T/mCbkbZINiV+aoLFHEV5CkFzvIXM+fsLUFppSEzJlCIKEds0JbEngKbykEb74FGZWF9Bs2NGmPF2MbHK041o+dU1BYEgkAdLxidd6eEmJzCn8uIGZ9qJ6PX6RpV+YQVj12VMIoQhsiVORxJISo6YBkXP0i8b3v1zg/yPHmaf9mlvvfPA/rrO1JGZriMtP+8e+dSey7Zm8bLq/Aon5/sApBlGiIqvh2EaBDAe8UqAnoBwd5XeK87VG9Pp2vcRs0oRAGWHalQ9yo4VdK/GKdAFHq1GnNzllmgC5RVqDYdcaOtpQ4hPYEulI/HiAZfgEgcAvVsisRApFkNJR6ti/k+TKFX6xj1/qY68z8ZJE9VvcVBgt+szEj+vq81aTLkApXfDyFs0mCF/XelGGTnOLdW0ibSQpWmkiHF2lXnr63RGrE+TagNvWQ1gBXicH5UqMuKf1QIDRLAliAmWBkfAoTWbIpGwCLLADhN8SyVFh3p7X3gWhyAkLI6edzqxm/Ru4aV24U2YMpENkN+1U+AhXogJtzWyX5Ag+LsLIioiEKkO3yWoQWI3gFmszBVSY4hdIAluEv7uIavgEhbrIW8Trxa9gpcLJ3YP3bvXdoqFDeIpjIpH44NMWswS0puXDlvXyBOWq3+j0rqoj04wYth8bfjOSEVXD+Muzwxk5BHRREw0dydApZAAv9KjhwBXlvDC6BoAybzBtPj080pTUdn28VdtuPPc39Pr9TdR2fBwoZeXELBNWa33H0Jt3YmrJmojQTC1Zw4B9euvBPIQi/lIq+hwZDfQ7vGNxUedFdCuJc/Gdx8P4dETadnr7aOZULWXAPr1JHuZGKXd/fdni19wMjGb6v7py5PS/kGVn5nfrz+HrHuPkF47lsH1cZqN1MlMW6GMPtHTGzIg/nAUfvMMhagden7ozN1x1EEeU6/OMV0+jfdUVjD6pD4NPO57zGm5jUdVFLKmeRtP1fwOgvCsM7wpN10Oq+lCaK3ox4KKWOj3Qkj6334Jnue6uaUxafBGz51/Hgvlw8cr7mbJgQnhd6tnp7aM54/GTtn0EZt68ebzwwgubkReAXXfdlVtuuYXBgwdv7e6+lwjiNiowdMV4Q6ACHwIflQvte30T4bgI10M0aRJCEESEQOYH+p6HCgJdUyZQiE20Fbq4pK/rrWRyGLkAr50W+nkxHWHRmhedrqaEJi0EENvo6JxqU+gBuK9Fgk6ppdOicmF6mITYhgxyY4MWqAsZOY21qqkiQ1c0n9DpS6Jyjl6eTy2TRovwn/BvQzuaKc8Hz28pRCkEqjiGX5qgbpeiqN6B1eCFed8CM6Pzjv2YjjQ5xZbWwzg6LSywBYaj8GO6UKb0FF5CkCuPkazPIL1wZs/XKXYY2pVNOj52jU9g6Nk36SlNmEJDAyPtEc94xGoNrYUJlLYEdQ38mIFbroV1Rm0jZLI6xS4o+Pb/N9iUxHwfIixfhu8qbayAHzbMDGBrUXpg5NOO9Xe6JgoEjq6pgmyZodcidT1lH9g6/crMglgvNTlQLftwSkNyVKN1K0H4RhdZgVPhY7fJ4nsGfkMC4cMH73dCJD3a7FxDWSLLXhUf8/DagQBk2wdYjWHqbyLQz8cKX9dZiQXahewzS6cuNwsMN4wmxfQ/ZajofyMj8EoCZJlDkNWDU6s8S1olkFmdZqUS4XvTFcRqBX7c0KnLviDWRdelqc/EwdN1cMxmXUhTrY2zZm0c6QrMHAhl4KYUXjtX6158gUwbWOssneoV10YBeZG9V6Qw09pcwGqUCE8TjbZdawGoeaeC1CcSI6fwVqR0JkCRLrQp0QUzpUdkLa3ro4XObc26Zo4S+jszraMvZlrgmIUJsS0he9C5+CTZefXTYbX2Fu3Kfgue5amhLYPgfPRiScliNh4aFp8MB/OTd9NRgakla+BTgDRthxazqGoIIxc83eqYS0oWs2jlRezHsxEx+YkHH83rzSs109np7aPhvhZtDsCCYZrozJs/n8knHMeCIwcwYtgo/H92Z2afY9jp7aMZPWwSAydfRfWKlkhMZcPefDTvvciGOe9SNm11FaP7tG7TR30eoRvH80KPGuZ2XsarQ9+h/KQzePVlHYXZY8/HWfl6Cna7G4B7DtQWymNG7cXJrKDL2ZWsWr2Ewy19bR689Gzusfbm8Sd1+tarx5fT7fE4ziM7UPHiDcwdM4ZVH77KQY90BDpQc28/PufP7HTGGn3NFzzL4odbGnlOt78xA0idfyiVDS1RLP077M0LFTW0PSPkCO6veaFHTbTtgSvKGXTqVbBYE68HLz2bKWOS3Hrc9ez75P7UTX+OV1/uRafirWf6W01gYrEYDQ0NX/p9Y2Mjsdh2PhCQEBQnMbJOi0YkGrArVN4GxnFAhuHw/CAfWgTx+ciGDFOSco7WjeQ1FUJHY0TOIfZZE4FZjFskWwptGQI3pUmNXetgu9pZTIaWxUEoqFeGxCsyI1G7mfUxGx2MmqYWx7F8u5TSKXHSAMJ0sbzjmu+Dr3O1AcgL9W2r5fyU1vcopVr0LmHl+nyanTB0ileuIobdHOAUSWINPl7S0C/gQBEInQrnxQSx2gA3ZejzFjJ0DFORoFNbaepK035cEsRtjKyPlzBC0b6h9UfNHoFthFEbXzvEyZbzyTvGyLQLhnZPU6ZESYmKm9r+0xCI0hgy6+goTOiqVsCWcf5Z47n+lq+e7S8Qly3j29K8FKIw3x+IAHxTTz4ZXssylNaLBDYgQnvkdFjcMiYxHIVbFNYXCZ+bytC6CrdYpzGZzSKsAwMqpi2KZUgorCZNbDrvuIHa5gSGERBIXdNFNBj4nqCog8uAipVUpT5iSbdueEqyQrbFMSwo8ZB1FrkKH1nkIg1FsDZOUOqRa+sTW2+AGWay5ed4BLqKfcLHTGvtjdlkkHNjiHIHKRVu2oakhy8MCAykBLfcQ2QM5FrN3qxGqSNHrsGqDWX4zRZYAYFpEGsQODvmoMFCtnHw62yEL3XadomPaNZRFcI0MTMjcEt8kOH3OYmRA6fcx2w0sJpCF8yYQsV89my3itfWddWkA52Ol1wT4CUEKIFj5qNkRC5qRlaTH6tR4pQGKE+bM0gXPFO/e6QK3dzSBQ3Ml+Gcbn9j9pSLuf7ZSzhwRbJV+tgX/867hg1CC9pTk6dSXHXNZvtc8mjAq3ccCOMXwdAh7Bemqd35kA0cyGnh5+fCApUAu+8PNff2Y/y7O/Bv8wB+tvvb0Xc/mf9iq/3PvPZpZg6D85bfxk5vH0236XGmHXUd10/W0ZwXh/+Ni+88PiJdcyc+F5EY0ESoZtf7ufjelur1s1dfB/P7c/2zWT7q8wjlIXf4w46nsmzek8y81oHiGir+diQ3L7yF+MGLmT3/OpitScEtne9hfrexTEDrTGadsA9/eQ5mPTBHHzOp2P/69+iw5kA2HnAeR4wYzKKhf6Nv9yn07Q4jqt4BnoV8Kcmde3PeGB15WQSwSarfDQ+fQc29M5izSV2bA1eUA79m0dAh0bpFG9/juTsf4Jwr/sxNuXd54Vkgm2Xg5KtgRTlnPnQ+taVrefv215myYALZRoe/smwLd8nm2GoCM3r0aMaOHctNN93EwQcfTEmJ9rJraGhg4cKFnHvuuYwZM2Zrd/e9hGzKQXFMD9yz2Rbykh/0e54mItJoSQkLVEuRxTxxMU29/qbIp2L5fsvA3/OQjc3ENlj4sSSGo/cRWC0V5DEEwtHkJbC0aNELGaqR05GR+HoHc0OTtnsOU72QUtdyCQKwQkbr+wjTQLmBTovz865hZmQZnRfo6wOEEZs8MfP9MBUtJDUhsYuukxB4pQlNCCTE63ykE2A2exhZj8AyCGyJ3Rjoega2flnnSrTnvtWsI05GJkAZAi8uidV6CBXgFhm4beJY9VkQMby4Qa7cQvgKN2VjZgLsOlcPDhqyBDEzKuBpAUoKpCmRWQ9MbbyAELq+TZEu1AmgYpYuZKkUBIWk5e8LtlUaWSHa8t+hQGK2HmYGREaQq9BRZ8PUgnKrSeHbYf0RA5StIzPKFHhxCGw9gRNYQFwPkPPGMcIDI9TROKU6shBYIJTCaRsgMwIjJ8l1cllXW4zbYIOhiCmBW+EiEj6qyaSmOcmitTuxIZfik41t6NNxDWbMwyuFioomGpMx2hSnsWRAxrXYkDYxak0dCcno81NGS8QnMFUozNeWxW5J6PxlB5A2SROK45UmA8pQiKzAXm9qHY0DQdLHlQbKCiBrIutM4g2SbDcH4YfRqzDaYb2bCK+fwmnnI3yh7ZQV4Am8HRz43NZa1YSHvVprTd1U+L5Gp9pJD6xGQWBazH+7DypjUFyft/cHp1gTRcPR62c7eWHh6nwqmYw0rcLTbmyBRfR7yTC6Y+TAKS5EYLaEvR9/kZsOP5T4iaOBXpF4v5UGJpzpz5OBi4fOiETlT3EMVLdeH+DiqhnAUs5/dwdmilPYj2e54eEzSNEiKs+ndAEMtFxqnq9jyoIJvGBqApLHzx7ehRFH6QjMiXP2Y2jRKgafdjyn7nAY0I7KR7QYf978e4ADom2nnNbiGjZtdRUzWMbMa5/m5s9v4ZYTX+QPO/6Csw8+i2nzr2PGo8uobkhGNsNAZEAAcP2unwH9GFW9JxsWNHLL2xbjL3iSP5X3ZqcRvWi++T2mLJhA9abHHQ8jZ7YQ55EzBdnEoexzzEHcesDPeb96EiMWwAu+jpTUPHss6pnJHHEVsHNvlqybhTVZEq9eHF7TpZSf9CY7vX00NS/34xD+HBFDgK4n63HvsTsu4OyHzwIg+9zexAfr71+ZegmDTzue5ope0fXP17OJV0+jtnQtuaatnzgWaisT/XO5HGeffTYzZ87E8zxsW9v9Oo6DaZqcdNJJ3HTTTdtlFKahoYHS0lKG9jgTmSoFQyDX1oRpROEA3TJbBvAhAcEPXcfyBABaCIzr6ChLaAQgQmOAiBCFJECYBpgmfttScu0TOj0gXz3elkgv1GsECj+mPyuhv7PrXcyaZkQmh8pktT2zbUX1WpRl4MdNjIwLUiLTDuQc7egVBCjHBddpaX+gWs4tnw6XRz4FLV+5Pm8IsGkRzHgMp3sF6fY2VngTGk6A2ejo6Iuli7b5CZPA1HVslBSYaW2rrKTQERhTp80FtsBq9BFKF6MUviK2Po1fZJNtH8NMa3KUbWfrNIDQIc5s0hGiIGZokwMBbomN8ALMjI9Rr13aVExbbarQ8MCPm0jHx1rbAHWNeG6ahbX3U19fHxH2HzPy/QR0BAbYqijMtsY3ITLfN+LybbuOfTEKs7VWyluLLZGYQj/RyPeT3c6cimnEae4aID2BQgu/4+vDyHAo3Ne6jRZXroisuGHNERkKx41NIh4QVa4PUj5Go4GfDBCuwMhKpANumwCjUeqikjlwywNKu9TT0Jigc7s66jNxMhkbL2fSqWMtFYk0SdOhyHB44aOdtTuZFaAyBnZ5FqfJxv7M0nqQKHVKO3JJlzAKo1O0AktR3K2Bxrokxlobr9jHKs/iZixE2kRmdRHJwNJamNhGnUrnluj3hp8IwFLgC6xaA6tBkOnkU9ytgYbPiyl+38RLaNF8yR4b2fB5KSIjdY1oM0DkpE6Bi+mikvbGsOhlqW5bVA8mphBKF9JUhqL4AxPhgVsCvq2Qvk4Hkw5kO/gYbXMYHyS08L+9rwmaL5C50BGtVurtPBE5hQaGwnAEbpDho6svLvSTEPl+MqpyDyas3x2A65/NRoPcbNVFPMUx0SB57iXPUd51IU//eYeIxBz3fDGrFnXghckfRPvN11zJD47Pf3cHZl77NOMvGE6bTw+ncrd23NKlH+v2uYzkYXqs0Okvpbj/F/DcnXrgP/i04xl5zEB+YzzEnOfPBeCkNV24b9Qirn82+6XnVLHqKf7xh5fZ+963Ww3s86Rk3vz5jAhT0S7qXM1HfVo04zu9fTQf9XlER1RAC92/gPPG3MaioUNYt89lXP3I0Rx32TGRoD5bdRHndGshXZum4m2KJSWL2bCgkUzzdYwc8jTzqueTab6O8vF/IjN7CQCTTzhOr7t8PV1P9vn0nhbX1xd61HD+kDjDVt7PgH16U/Fgf351cEsU65ZOL5I8zOXND/8CwENX/Jm7PvsroEX/3abHaa7oxYEryllSsphs1UX6Wu2si4XmmgJurVyzVf3ka6WQzZgxg2uuuYZXX32VtWvXAtpGubKy8gfRIZUQCMfFq0ghYzbknFDHEpDnsEp5erCO3zLIz6eG2RbkcvofLXa8AlqIQaD0tvn0Jk/rYYz1ikTOJbtDMV7KwGzyQaEH84GKUqQCS2I1uhhrmltMAkxDWx4nYqiiOF5xDAxBYMoo1UoEIFIWwtM3tVWTRqSzqLTQURYRvpQwUNkcwrZbuZVpR7Kwvkv+vAMdkRL51DPP1yQkIEx/8JE5bUHtJ22kq9O79EtF4hRJ/DiYcUPbQQtdZVp6CqvJx673woKWoQjSDtO+DBkJ8WXOI75O4cdNba0sFF7K0hN9pnZzQwjdFjdAZl0Ia8LghwTNC8CUBJaeCVQJG9lkgPtt3WkF/DfIk5GtITJfRlyW/WX1Vh+v/8jOW73ujwUFi+Wvhm+DGUZLjKzWb/iGJh6BqWf4hR/+U0QEQLo6Y1eJcJnSbldChQEMQ4vgAxOCMo+yiiYaEglotFBJHy/lI6RCWgFe3AA3tL33BPUfl6GSPlIoGuuSyA0WqtRnfV0KQyi6ldfyr7XdYVUCEQ908D3u4+ZMzI0W0tVCej+m8EoCVEKnbpHWBYM9WxeWFJ6gvChNU1M8TNUy8HNJRLmDMvQklTAUSirwBLlyPflkZEPHNUMhbB9RY5NYE5oUJH1Mw8csdWjcVUEgMBsN0jkL2agnx6xaSa6bh90mS64pBlntDhrZV/tgeEI7hMUVbmmAigeIjCS10qTo84BMhYwc4XxbvyPcEm1249XZWDm9LYGgqF2a3HslWvcSHkP6mhgpQ/9uygLPUJDewk1SAH0vreTziXqAPO3NLKe+fTQQZ78Fz3LO+LGMHtYHhsIRCwCu4uk/60H4/G5jqXaTPDS5dcRmCYujKI4W/69l9vzr8K84mZt6vMsNl53BQ6v+zHGXPUI/RgLw+ch63rzzLwz791j6T63i4rDmyePjj2T0ZccwcPJV3Dfqk1bkpWjje5H+44UeNST33xm/ay8emvNnbrm3HwCvHl+OePwpusqBdApyVD+WZOawSYy/YDjd6jvARJ16NuGo/kAVrL6Om1Yeyrp9LmP2/OsiEnPzwlv4W/sl3MD99Js6kvaTp7Kg+WzGX3APz51YyhFXDeZijmG/mVr037Pj+wzqekZElubNnx+tB/DC5A84adL/8ZZVzccfjOfqZ/4Ofyzl03v0+gua76FN7EJqu97DDQc/zcAeV1G08T0mHNWfKnQa3PxuY2E1MASqZxrMbfgJPX9/Lz39JB/udhJ7T9bRI02y/srKVafQbfrdzKlaCizlwAUTOG3f53l1we90Gx+6hRFVh3P9/WOB1mYOX4avXQempKSEgw466Otutn1A6nCw8ANULKw4bFs6UgF64O6G0RjQkYtNxfleOLC3zJYoi+uFkQvZso888qTGMHS0Z2MdccclKE7iF1nhgF2nWmnLYRcj62Gsr9fkKh8JsS1UPIZXUYQfNzGbHC3wL43rmT10upkSWvwexAycdkUomcLe0IysadROZSGEbetUssilzECYYfvzESkpdNvD81I5R6deuYF21slHpAQEtklgSfyEgdmsncHytpJWs5698xIyJC9EUSZlhC/FpMS3tLhfBAFGxsUr0mleIuthNueQSRuhYuTKLHxbYDf5GLkAp9RG+goj7WE0hpEX29SEUAFegGzOoWIWQbs4HibCjyE36hS8AraM62+ZGUVhvit8VVrZlsjL1yEuX9ymQGQK+DrwkwovCHUdsVDYXqTTyQJTRxukI7RwPtRiyJyexAliqkWLEWYAS5/ICSufukUAXiCpKG+izkrgOSbKFwgzwDB9fKkH8MIKEHXawcz14LOaElTWwE8FmEUuhqFYU1vMxqadSdclEMkAZQcIR2qNSk63xS1WBLbCzAhIuRAIVMrDs8LCkQlf2z1nDVZvLCXImGR28DBLHdSGGMqTmPUGyTUCpwQCWw/0UZpc+LHwPA2FMDSpQYJTFoCAug/LCeIBMitRlsIvCkjXJjAUCFegpML63CbXXkAgEEpANnwJKk2QpKstld0yHXWRTQZGRmBkwC3S6ybWaTe4XJnQETITyP9WVhg9i/s4ORPpQqw2NGawdQTKcAS+rXQ0ytZpa37So4DN8daVS3ivvUFj9e9Y/EQfdkKnYy0aOoSqbn9j8GnHUzlmbz6ckKDnjIwmKg1QvUmQedP0sbxN8oCfXcOdDALgz3scD6cDN71LYsI/uaVLP2Z3uy6yXAYddXEBGvTg/POTfWY8uozBHA8b4fpne3H+kHgrEtP1ZJ8Oq65n7p8f5JVDDuS8MTUY+37CWasA2sED66H9ONq/tAH2/YRL7tgPuI7qMYez8pLnuDpMPfP/SRSlWDexmm7/n73zjpeqPLf/991t2umcAggIGCxgi2BBRQVRiUYDJiIY2wVBY8RujBI1ipjYYsESFbi2iGICRBODIqASBRENFmxIEVA4hdPPtF3e3x/PnplD1FzMTSLeH8/ncz5nyu4ze/a79nrWWndFOfWBQobN9ImLeOXqTzh++fu03yQOYe/vcSd1cxrY7/A/MLd1H4C8JTSIjXPw+c3MPGAoPYEuj+8L6+ClBx5j6ov3svZ5uQl1+FkzufuDHoyacpS4o10xiVGRveCTD5g5S8wPcqzYqcdckXdN61wHjUvyyuKX2femgzhoXJKrbp3GJb0OggUhI7RgX666Uz6bOfwNgEEjRLf0wBMOA/9SxHvHz+O9NQDbHyD+tQBMQ0MDM2fO/EKQ5aGHHsrZZ59NVVXV11ncjle2BT6Y7eGgyLJAh1kogQZlhEL1sI0sl9rueijbyg/2AWE1ci1jINPnWrVyzEwn6+J8m1lHCtP1MBvBdmzRsWQlxDEnzM/ZPCtTdBw6HsWtLkIrhd2aQWU9dKg38eIG0Xrp9zSyAjzMpAAyP2GT7l6ME3ewNjdJVgx0slkOwVou8yXXHpdjYAxxKtOd2ujMtIcKr7hewsRwRJxveBoz7YuDmi8Xh1iTBEoCpCJW/sLsRQ2MEosgFeT7wXVUbkUqL0B1pDGLBGB6ZVFpkQOUG4S9yZApkeNuZTT21qyI9m0TDAOvyBbNi+tjZkP2yQuIbU6SLYuIPsa2oIDpdlan2h4b5f9UfZ3WsH8GvPz9/N8WEPP3Yv53Ju7+L28j21n/uJSnyFQGcic+pYg0i0FLYBLaEAuLYrcJa21kxNnLyILvi0UvGoyIgJbcHf6ca5kfEUqmvTFOu6Gpqm4l41q0bShBZRXZRIBKeBSXt2MoTbNbjOuDX+xTVdpBixVQFMtQHMlwQMVGnt+wJ6mPy4ikQ5aoVwY/bYk0MmUTOLLNlHhQ7aF8A+0aKEfATrw0RSKapWFdBcpTeA0x7Fa5CRS0x1C2RrVZRLcqnGYxa8k64CUCzDB0MnRABl+hfbEyzhYbOE0GftrGTCmy5RDEAuxmE69I8lz8co+Kqlaa1lagizzIGqisgY76KN/ALfcxXGkjQ0l7npFWWEkDMyVZNm6RZN04bSHrUhRqYSwtups2Az8mIDO+WeG22bglFl6RxmtXRJo0sTRkSxTJbhqvKMi38xlZJar+nfWFGnDtQKIJBxDHqxVLP2Dqoa0cRwmXcBYLKn/KuYeOZhBw1/D5vDfuVc49Lcvk4ffzvNUK3P+luhmAcw99mQWr9sw/77LpOWbstgds2sTyD+PE+gzE3O2HLFkrBlW/3300K+ZfyWZDrisbLiqAlS6Pkwcvb9x0DYfMeJ93PrqYl85eQvXJ1zPqxXt55+rlvNMVTjg8ws+Sd3Bk7yP4rzlVnHbdaPrucgpHPdzCMQM+ZO41BzP1jdehNxjdJ7F8ZpyXZoW6lf4wqvVeBo69F8bCYSzm+eVQMf49Dht7L88vh4ndT+QXg69j7Z+f5qif3cjUAaez4sV3861qm40IF6/5KX0PPBiAtj3u5Ij1W3j5wR9x2cQpAGw6r5Ium2SVOWamoudCGpkHn3wQurP9lFmP9GLBqj15f487uexFAS+Th9+/jf7l+QULKBvbjUFvLSYARs28kuUIM/X8bk/xaO+JTB19engkRce0gisZNOJmqj94gY29Ab6+hn67bzG/8cYb7L777tx9992UlpZyxBFHcMQRR1BaWsrdd9/NnnvuyYoVK772BuxIFTiWZIy4HjomA+RcOjum2cllLCgwKoCKhc4ShhLmonOmSvi6ikbD9qsww0SFVsURByxL2s2Ukrv+ng9ZF9XWgepIQSot1r6eV8gmyYGjaAS3SwLlaayWjOhcAG2bkoniagzXx0i6eZ0JiF7ETHmYGR+3yMarKRPmJX8wwmbrELjlwj3zxyO/vWaneQKM5g7MTIAfM0TnkjDp6GbS0dUi3cUmGxoQ5Nx4tBI2xrfBdAVwuEViKe1HDfxILk1Zh3bSASqVwaltw8j6BBETtzRKEJVcHsOVK6Dpyt07p8WDgBA0iduY1e5K7kzEwi8OAYtV2Ec/ZhZA2876ytoRWJj/dP1vQVCu/l1OYTtrxyltaOiWQdWkw5ajgnuY4YnlbrRB3Ce9IskwsdrJ56oYnsZOasyU/JYFlvwpHbaaeWBEPXAN7C0O9VtKaa0twuowsNsNjCKXPXtuoSiaIeNa2MUZySSxA0yl8TyD+o3lrPusElv5JJMRCHU4aLAsn126hzaooS2wjgTQYVFd3oYT8dilRyPaM4gUZeha2kYqa0MA0VoD5QkAsNsVTqvCapPgTTRkSxVeHLFFDsX3ob5f9i1lQquNSnh4cY3dIcfOj0raPQiAi3VrR8ekB68insKsSuN8bmO3SNu02WqJCULUx3cgXSm/6VZa7Juj9SK610qYk2yZJlOqSNYIQyTZLjrfUuaWBVgpcXmzUpIF47QYaAO8hMKNQ6ZUAKou8kXLE35efnynLf+X1bIfDOGgcUl6nuMzqK2CBb3Owug+ieOZDcDP177JcV5BojD4vb/mwcuK+dJ+NPXFn+R1MYNG3MygETfn3wP40XMH0fvCP+BfIS2vp103mlf6NPLBVLFJHtK3hO8++WtAmIEn1w9n43STtf2fzrMkl+7xEFtPf4cum55j791GctiLiynf+AO4YhJ1cxqY27oPa34+nrblst5b4pdwQt1A6g7fwp0L76Zur2PZ97jvY3SfxIWbhzD2rA2smH8lpx5zRejotTezHunFrEd68evvTs9v+6ARN/PemnkcMuN9bp/1U4476BhU78upXno9fd8/hfKNP8DoPomDxiW5Y8MJee3LZWPv5cLNQwAoPuhm3hn9CAd+t5nkG5NIvjGJrae/w3+dcTID3NMZNOJmVtmP0zhmHgAD96zKLyMHAJeN75+3nD71oIFf+Bx7PrYZAL3+Nl7p08grfRr58dGlPNp74jbT5T6nHGu0+683MfWN19l7t5GM+9mxzHiix3Z9b+BrMDCTJk3ilFNO4be//e02zAEIe3DeeecxadIkli5dut0r39HKSGdDrhi0YWBEI+gc02IaYixmUmgDU4q8C0lO32LQyULZFJ2IYQrDYtsFAGKaYJnoiIMKAUuerQF0mC+jVMi4+EHB+QxE/G8Y+JUl+FETpyktug6t0aaJF5dWKjMVEERMDMCPyr4ZiKVwYJsEtkFgKjKVUZRfirmlSVrmDLMAWAJ/W1DmemCGjmVBeFB0AJgo18NuTBNYYkjgRwxiDUHe6llpjVtkiR7FBSslDI6ZBTsVEJhygTN8uYDnLJWdpI/TlEEl0wJi2pJYfoDXq4wgaojNsq0ILGk1M3yNmRbxf2Ab2C3CwpitaYK4gx8xMbWPSuswfFPAjZnxhcnx/G3B2c7K147Cvnyd+lcBj29LfRlA2snC/GfLcBXZtAEZA8tVWClNEBF7ZLtdBvBoaTsiCEMrLYg0h2YkSfkvwb9gdTbnCW/GZFJRDE/htEC0wSGwoKNflqLqNnokkiRdh7Rrkc1aBI0RKJKFdGQc3KSD2WYSre7gw7Ya/A4bO+dFY2sCz8Q2/byGJoiFTo2mZnN9KTpQbCWBvcUmMGzW1caxqlJQ6pL2JDtG+Ub4myxBkxK6qeU3vUXywIJ44UaR0yqtV8oDUARJS8I4myxpw0vL9cCLGWhH4/sGqt3EyCrWR7rAhhhWUgwBcjks2TKN9bkDhrSp5dgsq0OYL6dVPgeUwk1osuUCWKykfFZOiwjzfUcTqTPJloj7mx8RAGZmZf+8qACz/HY2yM26wNICYKM7bfm/rA754xKu8oUpWPtnAczHbHgEeIQlL03n52vfFL3LzCth+FD2vekgnhoegprhsoycO1nuzn7uNbifqRt/wor5VzL3mpcYddNR/PfJf6av+TRbT4cZn0WZctPVTL72LaZyNRPOvIbRVz5Nf2Bg4hx+WL+FFzumM2rKD1jQc09uTJzDmx/W03y12ATfPuunDGqryO9L45h5XGSNgE0jmHmAbOugETdz+8ntwM1snG6ykTi3zxJmo3ahz9HHXs6JL/SixirElPy+Zit3efNZsvXH/Hw+HDJ8KHVzGujLKwDU9ric9omL4Fmbude8xMDXBGQd9qFs01PBrdx9zXJ2q46zmx+nqfezrChuZN8Dp/HO1ct5avmbTH3xJwQjbmbuNQczCDjr6M9Y8cnDALzpVfL+HncC0P8jAS3HvHsW5Rt/wPPLF3DcTcdw0Lg/83zPBQLiEDvqlw48mF8dehCXvLYHb35YD4gBQK5dbMX8K3nn6uUhiDmfs6rPYpJ7OrU9Lv+nvjvbzcC8/fbbXHLJJV8ALyBswiWXXMLKlSv/qY3YkUr5YmWcAwP5u/Dhf+15YRClJ6DD7/SjlGs1y/0P/MIgP8xdUeFfnm3Jrzh8LZcyb9vSIpZr3YLQtrnTXRzbwktIiKXyQ/CkFH6JQ0d3m0yJOH2lKh1adouT7mLjxUyMjIe2JHNF+TLYt1I+ftxBF4XOFTmQFra74Qeyz4aS9qpO4ZUghgW5YEuzuZ1IXUrc0zyN3eZhtwdY6QCrQ7bfjxqYabk75UcM7FSA1REQbfIo3uRjJQPsdo/452kijVns5gxGUztk3XA9njAxTULpmukAp1XYIRWAmQowXLFjtjq8sBXAwK2IC8gL9UAq64EnOTsqI2DKyHjgugXGbWftrE71TbEw2zv9P5pup+j+P1fp7p7oMAIZCOdcx9JdNL4tzmBmVgbVVkphdeSsiYWVzjnHiBhci7ZQyWMjC8qTAb/VIUGLfkTE5nZRlv6VtSSsLHWtRbS2xfFbHVRWoeM+Pbs3UpFIQtbAaVFkPyrhbx/0xtpq5Q0H7FaDIGuyflMlRtLAaleYbSYq6oMVEGSEIXFdEyupsFsUylcEgVgMByUeRV3b8RPyG+rFNdrReDER1Buuwm7TJDaKlbJX7Avg8cDMyrLQoDIG2BorBdFGhZfQeMWiwdFOQKYhhtVuYHgKNsRwWsLrUagXstoh0mBgZgUEekUBWomWRwXSjpfTuFhJiDSLO5ndpnBaw3yeLEQbJFfGj8l11mnJhXcKc+M7spxMeYDXLQsanCbR2+SAn2rfeUPsy+qe309g6ujTufDSlVw29l7u2HACAM9brfx+99F5ZuH2WT/lsBcXf2W72OTh92/DwOTq1eFDAWmTyr9+xaS8A9k5Dw6jtsflJJ+18c8fwPI/xFn+hzh/OP8IfnjfK+x73PcB0ZSo3pczaMTN+Zazy8bey5ETp7D0/l05cuIURh3gUdvjcmp7XM64t6S9qrbH5Zy+/JfcuKjQk16kJYiyZtNtAMzNVLFi/pUc55Wg19/GXd58LrJG8PO/nQOwjaMZwMbpJscddAw9158MwH+fLFqTgXtWceDVU3hwRK1oXoD/mnMC1uy/csiM93l1+FAW7PMIFePf45U+jXmWKrfuE+ffyyv+q7ziv8qy8f1ZNr4/5Rt/QPnGH7DvTQcBcNxBIvRfPjNO+cYfcF/Zd5nV9ktWLP2AUVOOIvh8GnWHb8lbKufYnNxn9F9zTmDgnlU82nsijzT6vPzgNTx+0C9lv87oxr1vXviPvi7b1HYzMF27dmX58uXsueeeX/r+8uXLqamp2e4V75ClJIUYhCkACmGQgVEY0Ha2F/Z9MKzCdIaSwX7u9VDzopRCB2KrnLcj1tISlRfFg8ybe880BTCBsC/ptDA9lryvIzZe3MRuDUT3YhgECenddNol/CtVodCGgJVos4/d7omuJuOK5aahCBwTP2KAA3Qtxsm66GSqYBvt+6ELmVEAMZ33gQDtI3oYT1gbMwgwOtJi52wZ+FEr76JjpcSdzPAClOujtIPdEWpYAMeVzBsj4+Xtn1V7MmRFDHGv8QMULmZtM07Ewi1xQGsMT2N1+FhJD6/IRoW5OEbKA8sgW+qgbUMydgxCsOoR2JF8+KXRlhawuLOF7EtrR9LAfNsrBzb+VbbK/8nWtJ1g6B+X2WFgZi1xNrRFEC4DZo1rgJVWglNcaWnyY4i5SVS0GF5cidtiDvwY0pLlFotbolsEmcqAIBag4h7K0FR3ER3MwaXrMFRAidOH19b1xWo20bYmWpzB14q44YtQ3odYncJpsfPLRIkBgVHvEGkKHSAtiDQqgrYogS3ZKzruk4hnSBbF8kAlSFoYbRbYGq0VRkrCI7WnsJsNAifUgwSQLRM9EIDdauLFA2GcAtCWAAwjK0xVpgy5RoQBx2ZGYX1qY7eTZ/ezpQXnLzMjeiOM0IraAwKFn4BUb5fI5zZWEryYsP3akGtTpFFjJhTpSkhHASVmCmZWY2wV9zIQwb6VkiBRM0PImIEXU1jds2QTNk6zwi3SklGjwEztNIX5shr02IdMn/hL9h/dRzQTjOaUiSOofeFynlw/nMNmxlk2qz/HvHsWjD1om1YxuP8Ly+vcbgZw2PotvNp7KBdZI0TfsrwFbp3G+r1OoObq+Zw96DJ2e+EWLnxwGNNfuAWAAfMhsf8TzLjhc06k1xfWMfjnx8NEsRx+dfhQhnerYFD9lYw9awNFw9bQriYAG5g14ma63XMgAPue9xHvfLIHK399JO1HT2DF/Ct5dfhQLpo5m99WCbB63mqF3tB+0wHcdTUQgq+6OQ2y4luncXv/p2mcsXcewPXZZ1fWvPspM25YzvhrDyL11JukegNPwSVzTuO060bDeJn9srH35vNwJHQSpr7xOrc/2M4pE9cx5S0oeasFgKPNHCvSh0Ejbs4zSn9fh5//AGvMJN3CMM4V869k8vAH89s3/dEnOKfHFu7utgSWijXzNi2AD16TX9a4txYz5vb3gTlfWM+X1XYDmMsvv5yJEyfy5ptvcvTRR+fBSm1tLQsXLuShhx7itttu297F7Zj19+xSyIbI4P3LZ8kl0yulQjeyMEOFXM+UKkwXaDRajAAMYWCUH+Tdz9Chg1mYAK9TBQGZ9jywHVTEEccwxyGIO1hJX7zmI3YBdAVgtfvEs5psiYnvQLZIkS0ysZI+XsJGxS0Z1GuEfXAMjGyAW2RhVpZgfu6iAx1aLBsoFbbJmYQGBn5BB2SFgZe5YEyt0R0+pDMYyTQ66gjVl2OYghC42RbaMrCa0yhP2BLl+mjblLtwqawYGHg+OpP9onmAFntre10txi6VZLqIFslud9GGIvJ5Ozpmy/4GAV7UIXAMfFNyZpQnfelYpoCaiCUmBG0daDcL/k7XmP8L9e9oH/tXC/r/GXYlB3q+LmjZ2Ur2nykzpTD90IRE6/BufYCVFDYgWxJgZhV2yA4oD1Byx9/wdB6wKD8HYGQaK8yGUYHc3Y9XdZBOOcTiWeK2S9TyKDZT9HO24GqTtRWVNEdd0mmbLsUd9C5p5NV3dhcRfFyLNbIKhfu2aEyMLGhHmBOnRdqwvDIPp84SHU0AZswjnbHz+TNBPEAlBShpOyC9tphoo4GZFqbDSipUm+yjH8lf5oRpCsgHSwZW6ChmhuzHJlucyErEnc2PBdBqEmkU++VMlU+kXq5z2tRkumhhjDIhcMiQdznz2gy0JetBi9YosEMNkiXgUPnC3HT0DLDbVaidUbjFwhhpKwR6Gsy0MFY5Js0vCtCuGdpmg7YDzA5TrLF3Xk6+tA754xKiiT6AJLlfarUy+d2DIQQOt8/6KYfMeJ99Xzwo3yqWH/wO/5+X/2rvrvz6t9ew+YIRvHP1cp64ZzGPHHQTkOXdaW10q/Y4aMsRvHOSx3EHHcPLD17Dmq6wL78A2CYDZeoNBwBw0A+TsPEHrJy9jm5XfMzoO+YCMOuRXsAU7vLmA/CbNVPYx2vjpbNLqRj/HuMeOYVR000uQ8Tw/T+6GAZ8mF/+glV7MvOWFzjk6pvyGTh1cxr4aH+HPVaKvvmysffCWAEHG3vPoQ+7MmrKUbxz9XLe/LCe4w46hpWz1wEw44blHG0up+NBuVYMekSAkvvxbAbtfjNjz9oAZ23gwKunsP+6Pvn59h9dePzq8KHw4pU8NfxN1lyTZNSUo/KsFsBF1s1MHzea/Uf3yU//vHUzjJDjNfnatwAYNf1KRnFU/jNkhEx7mVXE1BsO4LiDjmHqDQfw3Tf+zKL/+WMFvgaA+elPf0plZSV33HEH9913H37IOJimycCBA3n44YcZPXr09i5ux6ysC5G4MDFKiTYFCi5knR+Hon6V4/lzjESuTFXQxhCK9iO2TJMT+mtdADhREdBr20Q7FkZrSsCN54lqE0NE/JksKhYDpfCKIxJ2mfUJYpaAANuUO09A4CicFp9kjUW0KcBplxYpEUoqzECjLfJMhZHxMQ1FqiZGPFWCsbVZNEC5YEulQq1PCFRyNs46/J9jnHIsU2i5rDpSAtJyACbPbhXydfB9AXY5Rzc/1AUZRv5KpwwD3akdD60F2Dg25mcNRLNlZKoTZLpEcJpddMwW5scL0IaBW2KhlcJM+eJKpsAvjoS6HBttGcTWNkqLmmmSB6E7a4er014uBuCJI9u+4S355mqnEcAOXkqE5trSOM0GTqsIvVUIagxXpBdaiQ7G8MIBtQPaCn/DTZVnCHKD8CD0WonVa7yEycD9NjKgaLMI8QOH99u6ETcyVBhyA2yv8lpWG1XUBUWkXIv1rRVYLSZ2i8It0WHrk8bMiGDdS2js9vyVTQBFAGbCw0uI53FFz2YaPy9FNVtEOhSZSgnT1FaY7aJA+aITkeVKpkqkSWGlZODvJmR9gYkwOFra6+w2JfqYaAjmwqycwAIrZZApk1BQt0jYEetTC98B5Ugrl7Y02lREGsHwNW5ChW1rEGlSosMpRgI+QwDjR7T8jwVEGk3sDohtkXa4dGVAkPCxWixh0ELRv5WRljOC3DLAaTQI2mPEaiW7JrHBIghZoXT0P/rt+9bUsh8MwVjzF9646Zq8RW+ffXblyaXD8yn0y8b357nhMr7MaVs6g5dTDxrIU8vf5Hhm8xzbjkOfYzS/Zg8mh45cqw4tZZ/Vv+CV7IH0Bm48aAvjex3C2EeX0fRMhtKycbQ0y2/rrtHuebvhvscJ43zcQcfARsLXbXn9DrjLm4+/5g+ACP4Bao9+Efg+Z/78ZY56g7xVcfxEl8nXvkW3exaxGchs3g9YzDEDPuQY4C7eB6R17NXhQ6lGWJi1/Z9m8vC9ed5q5S5vPtUMZf8pixk04mbeOWBoHhx4zw7k5ePHctnYe7l91k+57MV7mTz8fp7zhOXZ48e3M/nA2+n7fuhAtq4iD1g619MPzgfm89xwadl75+rlvHP1cuoGv0SffXal48FxTB8nx/v2WT/lyOdmUTf4OiZznSx3uSznOK+Eqfwk3042efj9HHGT2D1P5er8a1Nf/AkL39i+7w18DQ0MwKmnnsqyZctIJpN89tlnfPbZZySTSZYtW/btBy+ACgJUOit/Wks2C2zjOJYfzHd+nh+sBwUmRXcCPCCgKOpsYwCg41F01CEojhFEhVHJViVYf1Ixm4fXEJQXybI7gyND5ZdvZH0CU6E8+fEPIhbKlcBGuzWL3erjtLoUb8hS9HkGu9VD+Rqrw5OsGC/AyHgYboCZ8rFaUthtWVDQsVuJOKTlQFQgTFOeaQnBi87pgFRhv5RlbdNmpz1fwJfrQjoT2kEHsrycw1ruddctgJewxU4Hsg3a8wUsudlCm55pyHvZLGrzVmJrtxKpT6MtCfJUfoDyNdkuUXFqS/kYXmjH7ItDW2CJzXP08zZoafuiacHO2qb+0+1jp71c/IW/v3/vm6hvszHA/7b9a2f72P9cVofc6TfTctdeBeRduACcZkWsXgBKLvw3l1eSGyQbYWeyVoRMu4jF/YjY9brFGi8w2S+2gWGJD/he8TskrCxlRpKkttiYrmB9ewVJ1ya9OUFjQzG+VnhVLm6pxmmWnBO/1JPtVKAdjVusQ8AkIMfIKGJ/E4G8rsiSyjjgBPihKYDyRBBvZpRkxpgar4sr4nXAi2oBRzHIFodan4iWLBwX7FYDM20IixGV4yFsSkC6i87n3mRLJFdFrKdVnonSluhrgohk63jFAV4CfCd0GbMEMOWWY2ZEg4QhIEpeFEe0IHQyUCFDE9lqENli5zUtaFlfYJIPXhazBWGZ4p8rElsCnBaZ1nQhU6nJ1uxMRv6yOuSPS/LtTAP3rMrrMg57cTFHm5dz2dh7aQyDIZ/vJHTvXLnWps7gpbNGZlz1RYBkofzmowmAiM6L73yDrHsu/vE/ZtaZh/DSUYNkeV1/wafpz5nZcSnl53xA+Tkf0PRMhujKV/LLnNt4Fwv923h1+FCmjxuNv+YPXLrHQ1y6x0OcVSE3P2s23cbdv9mfZ78zjMvG3svc1n0YNeUozn09ydizNvDz86YICwJ5bU/n7R804mYuskaIMQDQ8eybVIx/L7+vOW3MivlXMu6txfl9zmzeL2SDhLHJMSbPW61MHzdaLJyR9rHJw+9n7jUvse7dTzln5uz8+p9+cP42bmPvXL2cYP+q/LFe9+6nPMdo1o04iXUjTmLWI704r/5KRk05ij777MrK2euoWf8dAS+5kNEP6/PLe+XqT750f79O/VNNmbZt061bN7p164Zt2//MInbI0kqhbQttWzKAzuehSLuTBFT+HXjJPTfDx1YYYhn+5fNdcm5jpom2cn8GflEEvyhCe98imgaU0NLHIVPt076rJtO1CB2PFoT9OS1NqIvRptDhSoOR9fBjJsld4mTLbLxiRxy1/AC7JS0WyxkPM+liJrMFswJf48VM/JiJVxrDLXFQniQl+1WlqGgkH5aJYxcCLM2/++oooyD4J3RJQ9zUlGmgDKOgE8pV7rkWpoYgENCUAy+drYxzTE+n8EzJ49GF9QY+uiOJtaEO+/OWfEudtuSzsdsFwClfY7rizpZzZnPq2jHqmkI9Upj1Y+707f+f6ra7d7IA39Z6Z+Lu/xQQ2QletrO0CLxzFsFePAQqgTALZjZkXlwKtvJGYV4xHpFBcs4AQIljMKmuPh0HpOi1l+SxGQS06ghpbdEn1oCpApalduOtxp6UR5I0tiTQCfm9PbBqA3bMJbEpbG8zNJGydD6AUZuaIO5jtwlqChxhVTIVmmy5D1rhf1hM7JMIOuKT+U4abWu8cg8vLiJ5NJhNoqvxHULhu0G2LMAtFqbEbhezAMMVe2WrI2SdIuIE5sW16HtyMlQ73P9Almem5bVsibAnhgeYAsa0E+SF9SqQY2eGx9mPyLH14iEAcRXRBgOr1ZBWOBsyFQJysqUaP66JbxYrZz8a2iqbBYCT7qJwiyFbLjbMgQXJKgMvdEJzE7L9ZmxnD9mX1ZQfzOCG0w7hmHfP4sWO6bw6fGi+henpB+czefj9nHrQQFqH1udbs563WrcBKLmB74svDd/mdad7PwbNuQ+Aow4cTK9LJnBJZA8AitafwDtrr+InW//Mg683s3f5Qnb79QyZ8aeynktPuyXvslV+kuiLm56RvLy+759C3/dP4bAXF9Px4DiOWFfB9HGjmT5uNENG/jD/eFTJuwB5hiNnHzzrkV4sG9+fcT87dhsgAnCRNYJBI27mLm8+5osn50HOtU8so+/7pzB9nOiEckL5zoJ8AG/04ayYLzkrk4ffz0XWiDz4e2ae5K302WfX/PSjphzFougrDB6S4ekH5zNp6g0APLX8zfw0C/Z5BGNlPbfP+ilr+z/N1DdeZ9Dgvdjt1zPoM/+Z/HSvDh9Kx4Pj8oDo780WTpk4glMPGpi3yQZhtV4dPjS/n9tb2z1Cq6uro7q6Ov985cqV3HHHHXzyySd069aNCy64gKOOOuprrXyHqxCkaFNhNLWHPcid3LZyg2nbESbCsUMWoJDtorUETObskoWNECtmHXUEOCiFdmz8uEOqa5RklVgAZ8oh1SdL7171tM3ujpn0wlwaoxCC6ft5at9MZlHFknKvPLA6PPyIQaqLRaTVx8gGovXwdWgTbGC4PtowRPsB+bwY8fl38CMKKyV6lNbdEpQ3tEI2C5kMKhYTFkSFTJNhopzw2Bihu5ptF4I6QyOCXBuYsix5z/cL4MU0ZZ+i0ZDdCfU/OtQK5c0RTGFGdMi65NrXOjE/udJao9o6sLKuANJ4BIwY6UpHBg9heKaZ8TEzPkZLEtXaKf01b9aw07f/qyqX//LvBjDby66c9nLxN9JO9m0Kt/yq6gxI/pE2Zidw+XrlRyCIBui0idUqA1ltafyIJrLVyLMBfjjIlhYpec3MyuA8B2q0CSorz3OMw27dGjiw4lNqMyV0MTuIKp/mIMJ/lb3JRj/Cqo5d2NoR54JdF7OqtiuuEeBlLDKBRaAVyRppH/OKfVTSQXfxKPrEhsAkiAijYbfLgN4tDcAEM2ngfG4R36IF3ERsvFg42K8OMFwRukfXSJ+bH5M2ZSMDZgpMR8k0nsxjmSoPMqwUoBWZco3XPUskkSWTstFJg+TuWfAMrK2WtOZFBQQpLdksyhUw5LsaL+JjpEy8hEbbCqu9ILT3i0WmqgLR+ICAEJBAUStp4kd03n3MaZb99xICmOT6oTA6wudaY4SOaaKJkRuKmfKQZXI0XresePLsdLX80to0ZC2LNv4a6gZy5h4PUjG+P0v6tvL7mTfzNCLIfyghgOI5Rufbp54bfj+tQ+spWVzFcV4JFePfwx/ei19/LAPjV4cPpaL6NjadBwfU/ZmWk06juettwEGcfWMT+wI37z+Lz350O7uvipM98RrYB/BhHMey0L+N/biFpmcyvH/3ndQNvo61/X/KWZ/Oh2nQZ599mbH6MXrPqmX90BrGz57JOTNn51uqZqx+jPH9ztimNWvRtFMY3+8MJlW+AGdtYP3aGjjvbQDmDn6JycPvp3XoDQyb9DQrTj6f45nN8KNepHVoDcOASVNvYPLSKhZFhQmax2TmXvMSi6KvcGPqM34R24Vh6SNY2/+n/H7qDfQ+awPPPyLHq/9HF/Pp7ftyeqnLXbfGqHv3U0DA4OCpmfw2tg6tz/8vWVxFxfj3ZDvXwgTgkBnvU3zQzQweMp9FvMKw9BHw7qfymTA6P//SJcIarZy9jhmrH2PpkgjTx41moX8bB86awvO7jeb4q2fT/6OLmXTeDRz80lgOun4WI8sat/u7s90Aplu3bmzevJnq6mpee+01jjrqKA499FAOO+wwVq5cyTHHHMPChQs54ogjtnvlO1yFeSDKD8Xr2fCXTYe3cHIVhK1MWTdvmaxCMJOzSN5m8J0rnRNmKnTEJFvhUP9dg2xFgNlugAFnDlrKB21dCbb4WK3pfBsVIMvLMQ6eh9GSJOiRQBsKZSiUH+C0umJdnPSwmlLisFUcBV9jJrMy0A+XF0RtgpiVH9CLN74vtspJSUD2qkqw0hl0EAh4CdurlOMIMPENiEbyAC0ojYfgRtgRlfZQrodKZwoCfqStTMT4YYtaru1Mh8c80OK6livLEtAVhFeKcBoMCuGahpl/rA0TOiSVVrWZOE0OdtQJW/lsVNpFZbJiyxwE6JwpQc622jR25sB8RU069/T/eaJ/Qf2rWsP2HbnLv7Xd6+uCmDEjv9px7Ml53yyjlQMpnYHMTuDyz5Uf06isgVsqWVlaCUugfGkbC0y5o2+GP3OdheW50pY4ZXkJYUCCqEZHAoqr2im207T7ETanStjqJ6j3S3gn2ZO9Yp/zaks/NrSX09aY4LY1Ynt67G4f8UFLDRHDw09bqEhoCtBmQruJV+YRmGLpnIkVHL2spMLrJr+rvjIJOgya95DttdsUZkrAR+BYoYW92B1nqzysJgu7DdAidI/VK7KlkC3TBWMCH1BKEu9Dq2OA9NaY6GjiAfgKlTGEwXJV2MaFWEObGpWVgNBYrYKNDihIVQtz5LSFzI0vutBsqQ41SJI5I+6jhYwZuz1nsiAte1ZH4TNSvmhvDBeUlht3Ofc2bRBqZgT8WSkxYbBjLpGIS+tHsf/E1+5bWb9bKM5Xx3Eq+3jH8gA3MHhIhlbqWbokAhQG2DMPGArLC2xDbqB95HOzGHvWWOZueJLfMJs3ZvTnzmf64b/9fegNHw2+mBPHzAAewHm2DzW9F5PdazoMkOXMPuNi/OFzaDhhT/gZUAlvP1XHrpe9Q90bS9nNj3NU4jfc8X4p1Uuv5yJrBL1zIARY6N/GwrM2gF8ws3pt4smF7T5kDCVeCa3UM2bxYp5jNMMG7wVXTAKg+uTrGTSngTEnL2bF4vN5tPdEajaNYNlZ79GbWg45uRKGCuCoWjWXh+KvAnDj06cw/oYzOPGFXow/dgO7rYxz4cK76X202BGPPWsD69cOZWloFjB4SAaGQsni0QwemmHYpKeZOvp0ef3v6nmrleNmlNB7/Hsc8+5ZrDGTrB3fn/Vr51OyuIrWofV5MFVCFc9brSxdQh5QAuDfRu++tdAXjiZ0N7sZKsa/xzKgP8hnPHwOww48mHkNf2Z7oyy3G8DkAxiBX/7yl5xxxhnMmDEj/9rFF1/M9ddfz8KFC7d3kTtkKS9AdaQK+hcdFDQoOd1FJPLF9qbg7+6u5DJeHLvQDuXYaMcicEy8Iod0mUm2V5Ze3bfiBgZ9Shr5qL2GVc/tQc8tbWIxnOnUypZrw8pZK/sBVirAj5qopBY9S6CJdrgYHRlUWgCLNpQkzYffTwVo00SbBm6RFfYRa4xsYR9UoLFTAZmqKFadI4N9A7QboHJtg5aJLooTxCOku8VxEyLUNzOB9B5bCistFyorGRCtT2NubRNgA/njl/tm5Zmr3P52NgrI6XA6MV7buL4F4a3JXHXWsQQanUxCNhuyQCYqlQHXzbfjAQUgZFnhsncyMP+o/l3syz8DXP437Mu/G+Dk6h8Bly+b5psEMztBy/++FBDEfFTWwMxIwKHyFbGmUNgeIR+qqHLMiglB6NLlRwQEuZUeRswjFs/i+wa7VTUwoHQz+8Y3srKjF7vEW+hptbDFK+Xtpl14tbYvbekIXYvbKK7ooL5R7mJHDJe0JwxMpChDRoPqMDFTBn5UdJTaFOexIBJgZEz8KJLdogFf5dkPbWtUWgbvVgqUr7FbRZMTaRZ9Dr7Ki+RR8j8wIQj1I9rS2G0GbpEmsAO0BUGxh7IDdNbA7DAE5CQCVNpER338rDAc2OKYZvsGypPtyoEGq0NMBMxUqO9xCsfWLRJw4TQbAhY92Qc/RqgjhcCU+bUln42RCVkij7xJAJ7CTQjYdIs0hicOZF6pgCkjq/Ktf0agaG+JYWT1V35X/n+uHkv68s6CPZjyVh9ammfyadk4bP8Qli6J5C2RI6seoX7A8Xmw0jp0KCXSdUXJ4ipGdZuM03M+Rz4H9z53MG/M6M/j5/ai4QSYmZFlXHVND7gG4HIO8P5MrTmUh+KvMm/dq9wSh8/P7gs9LuedW+Da897mb7fst812LtjnEQZtqWDeXT4jLzoW3hCGYVj6CKqXXg99+28z/dIlEWYeMgYQ0DDGm59nJ5aN78+o5ybDeuj/0VFc+UIVp6y5gKl7PAQWPDmknvH9zmDG6gx9T3iFRdNOYanVi2Hpg7mwxxD26baEmlDHctIBc6kfMIneR9cya2YvBg/JsHRThFmPyHacc9EEhqXfodq7nieHFtzDcsfy0XUTgdMpWVzIazme2VxkjeAub760es14n4eGzmfM4sWs7Q+9+9ZS0fc9hr1/xDbLyw8yFwtTA/Dk0KEMm/S0bMvo2fk2sdlnXMznZ/el+xn9+fmBB9Nnn1258IUhLN/obPd3559q8n/vvfe44YYbtnltwoQJ3/oWMq0UKpURQTkUBrJ5N7FOrls5UKKMfLin1lq0HjnwkgM5hiF6FdvEj9nUHpwQ/3kP+vWsZf+KTTS7MQJtsOTTvhTV6Txw0YYSIwA/QHueDMCVQrsuyvOxW7NkykNApUI9TDILridaHttCBVpAghmCGYAwyDLXSkYAZkbyV7y4iRczCkRHURwjkwXTlP0DsC38yhI6eiUwXI0fUdjtAWY2wMj4BBGTwJbWON9QuAmDwIlhVkSIftaO0dIugMEwBFD5QaH/O7eNgYGKWNsGeEYi5INBc9MaJuDnj7myZB5lmWIAkJvW99GBRrW0fwFwKstC50IIwufK2Snk/6rakbQv2wNevgqk/Kvav/4RC7M9wOWr5vumGZmd9c+XmVT4ppb8E1NjhIPvXOZIDjBgAH6oFQkrcIR18Up8zLhHj6omDq1aS22mhAFFn1NptVJmdrBiay8+ayijxEpRmykh7dl8tqkCuyhLixOlSyKJ7xscssun7BJplu1SmrKiFLVtEXSxh29aqKyCjCF6FyWsjJUWtiJwNLG1EcyUtFIBeBoMX8wJvLiwGZAzJgjo6KFQroHhK9HxOBqtFNmyXJsZEDIpZhpQimyFL8AhaWF2yMVA2xoj5mFsjRKUZtGmhfLCY1jsYTRGsFsMcXbTYnCQy2oRbahktXgxjQ4BlNNiiOObF+pgHECHTmUZwFEEjrA0KryP6cZB2xJgaWw2xFUtqvEt0eyYWYXKKHSZj9liC5PUxUNFfBzbx3ND0czO+kJ9v+Zy4FnWvfspi6I2vYtv45AZ73Mce1Mx/r28gL9331rWr63heauVksUl+bv9o7pN5pE9LwYu5sObRjPkyrNZs08pL5+wJw8tP42l/j4MNt+l4YQ9ueOsX8Ct0+izz64kALPL4fzt7Pu22Z53rlnB0iURjhnwIbU9Lmdkn6nM7F/LgVdP4f37oPGtlYDBXd58DpkBcH1+3vVra5jQMYK25VfmncRyoKEzeACYu3mqDPpfgFOmX8DT59zDvB6XMyF5GKyCk/rBmMWLYRJUrXqOjHcWLIV3Pmqh9sEhLNRrOXpFX55pHMXSJRC79TWmm5czHThnibTRLVi1J9MHfMjgIRmGzXmaMScv5iJrxDZsS82m2/JAsbNJwuAhGY5bLC1hYxYLWrzIGsGTazOMWbxY9idaMDWY0DGCNT8fT5/5z9BKQay/dEmEC9etzIdVjvvZsVx73tucNfZgdnvpv7n4lhc47ng5Zy8+WqOzm+Cx7fvufC0A09bWRjQaJRqNEolEtnkvGo2STCa/zuJ2uFKuh05mQvteBeRsjI3C3f28iDx83kmHkQ+r7AxgELF9AdRAW1+fQwd9xGcdpZRHk3iBwdq2Snokmtl/l894t2rPgm7E9STAUam8EF7nWAnXxaptIVtWLSxMqB8JIjZGaAWNqSRt3jTxE7ZcQC1D7JQtAxVoAju8sxYxMN0Aoz1AGzbK0+LmVeRgNBkFxsky8bsU09KvSFxyQpFqzr4ZU4klc9rP57ZoQ6ECjVtsk+xdgtMcxd7SIvsXhMAhR3iYhdatbRgSyyqAF9NAKCEdsiVarKuVEYZQBuK7n2NvnJA1CrQ4p+UMAUIHOa01KuIQdCnBL4rgFlmkHRe+vUZT/7b6vxRi+e9mXv5Z8PL38+8EMt++0gaYzVaeYTFTFOyTTUCFzAAysM5dYgI7TK7vkWL3mgZSnk2v4kaOKv4AimFPp4luZgwDxcZdVnDLB9/nmQ0HQ88Ue+2yhfLqNpJph6a2OI2BwquPsnjzAFb3q6K+uYg3vF50pB2sehuv0kXHPXRMAIzyFJYP2dKAoHcHbmOUsu6ttLbFCFptonUWRRs06UpFukKLzseRLBlx5IKW3Qy8UhcCRbqbj0qbELIWusRFOQHuVkfm8UOBfRqUp+T+kalD/UhA1a5NdC9q5QO7hnjEJe0IGFCGxjYCsmU2ZlIAkfIlEFTcJXOCfQEmga3IJgKUFrZFBQrfKAAUI5DPI4h0Apehc1yOQcpU+WRLlLi1hUOCwBGjgSBjYqUUrpXLf9NgBVi2j1Ia7Rloa6cG5svq6p/Po/dTS5l51uGccswFrD/nHkrYO//+8cwmMXImM1YfD5BnBY7zShg7ZRXnXX8lH970A4ZceTZLgKPrYrw89eD8/IkTB/LmZJf2lb/gt8uWs/WN15m+j+hUKm+9kO++fx+/++OdJLstp6bnYn6fsKmqmMtJI2dh9bydPz87AniEN266hmkNx3L5xhX0O76Jntpl4wk2Z1/fk8FDMpzbu455CycTHFtF3c8bWDTtFIZNepphPM2iaafkt2fYpKfhz0ewy4oH+dEt4RfwqjuYt24yAPUDjhe9CLNYWJ3iyCdHMmnJID6bvYrF03rz0qpH6Gg+go0nKB4+YSMPLKpm3rrJjHhqDaNnzs2vZ/CQDN0WF/Or6zayYPQxsOoXeTezXPtXbrpW6vMMzOAhGXr3rWXWI7049aCBebBy7rA6go4zGcz8/DpyoHLpkgjGdY9y1IBjOGb0h1RVzM3vx4JVe3LMgA9p/M3j3M5I9kUA24+PLmXkeW/z7vQL+N7Rpdz9m/0ZN/pGFr5xGU3/DgCz++7SVqC1ZsWKFXz3u9/Nv7dq1Sq6d+/+dRa341VjM6jQaesLjlmFu/P50qKV0bncEyi0OeVanXK5JyGroG2D+Ocmhgq4vM/zmGgWtvZnU2MZdW1FtDYkqN6k6WzFnNOT6CAoBGb6yIA+ncFpTJOtiBLYprizhHkwIKBCeYGAiqyPCjTZsgjaVASOIW5jjiJVaWF3BDhtPpEt7ZitWfwSh1SlQxApCPGxTIKyIlLdEmgDfIkFwHcUVkqyZDAV2jZQaR+zLSOW1GE+jR1oUl2jtHwnRqmpcNY3CEuSy5eBAoB0vUILHuQtnEXg7xTAZQ44aS0i/5yexQ+Xk9Mj5drTHFvYHVPAjnJs/K7lJHskaOthEWkR5xud3Gl7+Z+uf6clco4h+U/ZH/9vwcvO+naXH9NifRymtucY5sAh76ylOl1mAhux9Y1KWGPE9tmjtJauTiuVdhvVZjurst1pS8f4XrwBW5kkgwg67lP1mmKrF2NzSQnH9PyIP68bQHJjMbrIQ5mgoz5Z36Q4kaamqI2KLh0sad5d+txcA7skg44aZLIGVociiAXs0/1zGsqLsE2f4miGTX45mSpFrNYQgXurWCz78QCj2cy7fflRjVnsEotlSbZHICGBycbmKEGzja7MoB1NUOaiOyycRhPDF3F/0GHJTTYFxHwc06clG6UoLiKUgT22kA1MsoGFY3i8HfTA/DiOlRKtULpCtCx2O5gZjd2m8aMqbNUThkmAjYAulLAuKiAfGCrAUoEHVjJ0gTPAaZCcm1yLndVmSvsa4MVD85logHaV5NpkTPxmG51VRNIKP70TwHxVLV0S4UczruBQvSDUvEhLUm9qWTa+P+tXF0a0/T+6mGvPe5ulS1qZPOBx4HRuv7+VP89+jF8e9RPeXtHMW8evZr+l4+BwuHPh3by36nwW/ew1ALpceiF/uvp3HLH1fBpqhaWhmwSWnNRtM70razl52CC8jbNYPeBldntW2qGWje/PvJp9KWUcZ18/G/PFk/GHz8mzGX+4fyS7LO5g2YNDOGT+M8ApLJp2CucOq8vv4+AhGWkHWxKBR3pxzkUTCMYezX6DyniS4Yzp/SLz1k1m5JCpPNzzduoHVPMjXN61hlABnL6kHzNveYH1a2u4pGIMm289l6VWT0YOmcrLjGHcsidJ3X9o4cC+8QfuXHgXf2EBa9frvItbxXjR1XQGLrkWsDwoAca9tZjjKAHqGT/kIg5aJPPn2KSc/uc4r4Tnr2/lrmvu5BhLQCQDQr1NqL3pM/8ZWn/1MmcuKGbqzE94cv2V/GV8HRVPXEvNpp4smpYBTuG2Tq1s/1NtN4BZHFJIuerWrds2z9etW8fEiRO3e8U7bOXavjoDkpwOJgcaoPB+50R62CbnJbesXAuXNgzSFQ5usea1V/vTOCjB6K5vMKHLX2nIFvHyG/0pWWNiukEYZhkyCzmb4RxYCteXYyes+lbSNeKyZaUCyTXJSpubEeadgDBBKgRhgW2IxWNckoaddk22yCDSHLZ1+b50zOXS6sPSEYdkz2ICRxFpCTDcAG0prJTCzAb4cQttKAxXWCJtm+D6BI6JHxcWxO7w8R1F+y4RSttLMGubJZAyp3nJuYzZVgG8dDq+Spl5t7JtmBvX2zY3J9deFvgFAKqMsHXNlM+yOEKmRxmZcptswsDMaKy0liTs9p0XnJ31z9W/GrzsbCf79pUf0RgRjd0S3ryywLdkgJ1jYQI71JTIWFqCL8tdEqUpdqvYyi6RZo4reo9dLZ8SI8o+Tj0BGgMLD59lzX3o2XMrnx9Yg9OkaF3ZhT+9dijpvVIU7dqC/3o5mcoAu9ah1i8HO2BI97W0uDHsoixuykbZAdVl7Rzd7SOWNfTh063l0Bije6yF3YoaiBtZlm7tg2EHxLq3kaorE72IrXFLfFTCQ7eKCYDZauFFNNo16FKZpL0+gdVs4VW6GEirmRPPohICbsx2E6tDAAeBIc5hpsb0FIFrk6q0qG8porJUXCIDFFvTCTbVl+NEXPz6KCqqsdolh8YtC9Adoot0CQNDsznWRdrLvLg4qGlTdC1BUcjedCiUB4buBGiMghW20oSt1oogrsW9zTUo69bKLqUtrPq4BxjScme1mELCtCm8InnNrUl/xTfl/+/qNecFrrhuI5+N/wG9+x7C4CEZnl/SCmTyA+TOJeBFQE6/VUfyo49ns/DlEm7/WRP9L5zPeV2m0P3sn7L7OfcwLzKZCcnDeGZFXxbxGre+9C4n1A2Eqwthk890Fq+3Xsn7h9TzydwzWLjPI/BnWLvPEeJOFtZ+p1ZzTvEEpg+fw3FeCcdWfc5ZmUH88CcLeOrBG+h/PlyzYB0lD1ZxPLMpHTYgL2IHsU9++LqNzJm2gsqxR3PEXw7jbKsnx3kllI5fxQOLqilZXMUutz5I7/WHcufCu+HoUmo29WTword5f/FiGFrDkU/vxsihQ5nQMRSWLGbT9Epm7jHmC1bEV/1+EIc+eBlwG8vG9+e43opZ1/dk+rjRjO8Hzy9pzbeQgYCSMYsXs2x8f4559yxaE2EL2eKJPDmUPCPTWTPTOrSeqlVzeaZxFA9ft5GLrh8BZDhl+gVcusdDPHzdRixup+IJoOpkxr21mIenbKTxtBuoeOJafvPRBLa+fSSLpp3CHHMTJ/vbJ+PfbgBz5JFH/sP3L7roou1d1I5bQSD9yDnQokLRfMjIiK4iN23oVGYolC0sS14DA5JnAmjLDK2ZhR2pPcjgypFz+c37R7NuawVBV4OVme78oMvfqN27mDXNu1K2JhANTGejgE4J9yrUwAAyEM+6xD9tJblrCVaHB1oTOCZm2kNlfIKoJbS6Jx79OtS/WG0BhqtJWhaRJo+orzHTPn7cRhuKdJWDF5VEYwyFjkTwuhShLTDTAXabh5HxcEsc/JiZZ3HsNj9sSQvbs4rkWASOIdbQjoEdupyluiUo2tqG8gy0F4KXHGOVbxWjAFiUUWDCrDCvxwifdzZMgDBbptNnmbOiVgrl2ARlxST7lODGDcysxkoHmFmFmdE4TVlc/o6F21k76xusHQ3EOLeKyFWnfdxr3vuGt2bHK7tdYfgGflTE6oGtZZCcuyejQZvivOWH7mJmhwFNNkZZEk8bbM6WksWgOXAxVIa4cjBQePhs8jK8u7k72YxFrE8b1JWSqZTBdtBh09ZhY5dqSvo10byhjKKqDqqL29mSLuHT1nK6V7SS9iya2uJELI9qu5WqWDsfN3bHSBmU20kiysNUAUV2Btv2cSyPVLGERQp7YRDrmqGj3KR3nzo2bKnAcnx0oIjbWcw2Ez8WoNqs/OA/2RCnZ+8GOhriKB/S1QGBY+BHNF6Fh0qaOM0KbSlaWhP4SYtkNEtlUQdrmirJeiZem43X6uC0KcyUHFO7DdLdRO+Sy9FxS3zsVpPA0jhNBqYnQNItE0MF01cEhgBIPyZsTGAKiCFkXnLLUr4iiGh8R6NcAx3zKereRmVRB64vNzTNmI8fKEgKS6Utmd/MKGj/v5OZ96+u1QNeZn3VXRxy3hQYKqAlr7OgwF5UrXqOh+KvUoM4fZ19fU/Ovr4nd1w3GDiT2Id30zz0Ug6YPYV5s6Ula82fhrFo9OXA/izY5xEC83JA3LleOvCH8NRfAbgxJcz8yr9VUw4c8+5ZAPz4qWc4+8YmxiV+g7H81zxQ/CuCsUfDXXDcmlNZPORIVj3zS/YuvwHug/fvg3GHXcTYKUfywKJqzqUuHyp5UsVcTqp4E6bBM42jmLzhcf7afAN/vQh6cirPr9cCdhZDw/ER4E0eP+qXAJzO5cBULrJGcO6wjcBF/PnZETyUmM/S8Dj+5qMJHAiYu/2QujkNbO4lA9YxT0fhlMuZsfoxWAu9z9rA0Z2O/9gpqziXOs6+vid3efMFoMyoYsH49xgzo/A5TOgYwUXWYjq7wh3PbHr3rWWfSR0MnpaB63vSXnwm5w6byqV7PMRJFXN5aMarAiQbRzFu9kWsPWsDg96tgKvuYNbs7rQuCt3mhmR4fP/vw5tsV+1M6utcOWtkQkF+zuzKlwwTZRmFtqVOoY0FS2Atbl8Q3vHX4t4Vi4Itlr9d3tXcutsxZFojRDc53NB2Ika9Q9FGRawhYNdPU1gN7WI77BXyUrTW+WXqQG/jlKXTPqrWIx5AqlcxZkhVq0CjIyZBxMRqyUi+jRcyMJbCsMQy2k5JVowKbYqNrEe2Swyrw0cbptg5+wHELVLdopgZadw2MgLgzEyAlzAJTHEe0waif1Fi7ezHLAJbYbhhS4Wp8GIipHSLDPzyYoyNHaEttVnQtDh2wfktdwxC8b0yzTyAzGtYAlfskI3QWCFnuBBoATk5K2wty071KiawFbF6FzPji97HMiTossOFbOrf+W3bWV9STxzZ9rXayP4Z97H/lOvY/7XKAZadtX3lFmlsQ+76G1nQhiKIgNNcsEb2EtKORCSguEsHmYxNtjmCY8lvXr9YLWVGloShiCoLA4WpDDzt80a6J4f0XM8HjTVELQ81vJ1SJ81HddWUR7K0rC3H6lB0vFuBimsyaZtmKwpAQ1MxfWsaqIh20JaKkHRtWrw4/Ys2s6FPOZ/Vl7ElU8Leic9xtclHDdUYbxXTUpkgiGn8Eh+zxcJqV2RWl2BENO2ZCCjItkRAw1qzC36x7IfVbFG0QdG+q8bearG5uBSVMsUyWimcJsiWKqi38o5sRhrcz6PYPhhdA5pTMRo2l4IV/pZbAWbKwivSeAmI1SlxLlOSx2JmwGq3SHfz0XaAn1KQFgZGxz3MrQ5Gzg3OBqeBvLGCCgi1M5CP+9Y5O2aFkVT4QEk0Q8q1SWZtVNaA1gimVsS3qLxFdLZE2CG7yWBnfbGWv+awyDqFeetW8hyjWbqkdZv3ly6J8JuPJnDpHg/xDKM4CXgGaU8aNulp3j0vgfNjl88WzWdC85F8fkoZLz99Nj8Z3ZNjt17OC7+/BnC48NKVXHbNEZxz7mz+dIvLOas8Hl/1FKeffTgAt5z3kQjWZy9mwXix8Fq/tgbGwbSSY9nnwGIufLqCX9cs4dFyaDjhl8AQnntiV24tL7jvHtLWgrXqSJ5fr9nrVtGkPL9e2roSDMwzMIMXZXj3vARPuAUw0FF6N2euf/BLj9PjB/2SZ8vO4MR1vfjeDBjZZyqE+TiTZz/OVYMyHLO/sEpjWMzU0adT2+NyajbdxsPXHYYF9PZrOWTG+xzdr5BZM3hIhuOuGcApE0dA6D62dImwKvMWTuZJhgOim3neCtmaTg1ZTw4dypgZi6k7QZ4PHpLhR1X38UHzJTww5B5YBROSh7HPbzvoVncgcBF9T3gFnhyJNfuvvPPbPVjP4dy1eArtK5/IM1XbUzsBTKfSfgCWDIiVUqH7VVDIdLEtaVcylLQl5R2wOi0j64r7lefJIDofZOmDsinakCbycBQ02G1iemCm28Q5zPNRuRT6oMAkaM8rDOx95HFu8J7T2vg+xtZmYqaio3exsCAgLWcBeRYGpbFSHkbWIFtq5fuys6UWdruP1R4IAPA0flz6mlUyA0rhl8YwUwFOSxazIyuBmKbCCDRG1sJpF/tkP2aiLQOrwyOIWBh+gOEK4NGmIW5nEYUbl5Wnu8ZJbLHleIMARCMoOK/lTBJMQ3RApimMkOvlHyvCzytkwATQ/N0H7PtgWSjbxqspJVtsSoscwg4pT6ykVaAxMi5eZGcOzI5a/9vQyp0gZvtqJ2j558tuMdAVYIUZJTkbXzOqQhcsMTbBkRtCQWAQibhU7tpOQ0sRgYaybkmKlSatoQsmKZ2l2fdoDCxuXHU8g3dZz7g+r5EwMhwS/ZT1Xilvd9mVIjON+x2T11v68Oonu2HaPkP7rqY+XcQ7G3vgp0w2NZdSVdyB55kYSrMlW0K100av4iaGdv2Ydi/CR8mufCdei2N5uBlE26HBLHIxSzN4n8XFAcyHhs9Lw6wWhZVUUFtERCthoNrFsUz3SGN/GCO7OYqVUfgxYUaURjxZQoe2wBagp7SwU55vUhpLY7SZBHEVtmiZ5FOdkfyV+GZFe6+ATHUgzmoKjPIMQVam9Yo0qjqDEWqTckJ8reTGmuT0kBfpa1W47+VH5JpipkXsTwBZ32RrYxG6yUFHAwJErJ8pN8lWBFDkobMG0c/tfFzAztq2xp+2iU837ZZ/PnhIhgUrJ7Ds5Bthrbz29Dn3MMabz0XWCJ5pHMVvPppAxRPXctX4FyhqexR2h10+ns3F573MJyWfYv9wDVv3PYo7e1zOR/u9wMg+bzNv3WQOOGoKDScsAd5l2vyeAExDtDGxMTBs0VMs4hQJbewYwbCfj2fRtFN4ZnM3/vb+frxz/NnMM9+jbOwn0A1uXbCSK47Znys2bsUfPodxy55kxhWj6O3X0vHsmxzX+7C8yL93X3nt4evkC7X4l48zG4ge/WheR7P4l4/T+sv6/LRHHiUZTj87/0wOun4W1D8GfQrH7txhdZxbPoa1f57Fgyte5kEuyB+vpUvg2WM3YPXcyPPrNcf1VqJtsXoxePVQlgLrRpzEsBFP8+i6iex/wMv0Xi3bCdLqVsNtLBu/gZIZVds4lHWunCHAMJ7OM2WlZeO4c2aUpW0Rqi96jkPaWljHSfl51v75CNYWN/LSb6/hV/Vz2PpuOYyGojkjgCO+dD1fVjsBTKdSplEYPINoLWAb+2JxIVOFVqYwgV4YmzDHxDBk+vBOv7Ytst1L2LpXlNZ+AYmNBl2XdojAPQiEaQGU5xc0IGGblM5ZOOfYCT/MNzFzehEz32qmUynUZy5FXkCydwnasAlsg8jWNIFjokxQpkJlAyzt40cMEf2nA8yUhxe3BHBkPAw3IHAs4puSYi0dj+IlbOx2aRvThoG2Dfy4jdLCrLhxRbrCQAUGsa1ii2x4GjPpCfMSs1DZADMt2p2cgUC6i0m8vATqmwrAzNVgEh7HArBR0YhoXQI5zuICJ61+yux0h+vvdUm5z8xQ4NhkKiIYnsbuCDB80Q1lKm3sNg+3xMKJmnjuzp7l/3T9I/blfwta/r7+lSCms4Xyv1O8v6O1ke2sry6lC5knkscVOpApwJR2JctQ5C7DHWaU8i7tOKZPv5p69i39jAHO5xQbFm2BR4Dmfddk7Ks/oaQ4RTrlkPJtjoqvxkTzaqo3c2oH8s6nu1Bd2UrXRBtbOopRdRFimwwW693pU70VP2uAZ5CIZomYHqVFKRzTp2+snqhyMVQ1tvKpdtp4t20X3mrtRVWig7VVXVCuklaqpgi+oSEWgKWx6y2idTbZMo0f0/g90qhPoxguRBoV2oSO7hrb8UhX+xAonCaFtVWsmlNRARfSqiUBn35U2sO0qUmlbbKuRRAPwNAkNin8GKSqxZbZbg/tmm2ERTE0RqBQnsJ2PDKBhGsqH2zHwzQDkiWOXHpLPHTKxCtSeX2S4cpyJFRUoS0twv6w7c8r9kFDfV0JqsPCTBp4sYBIg0mmPJB1uQqj1gENblGA29mxYWfl6+5npzCvTH4/c85YE06+UeyTh9YzssEFDGpHDaV33w30PeEVuoTzls5txx8urVlPq+9xyso/8NDHr2Ime9Hl0jnwm7sZufJXBLv/iYv6ng/8ivPuuIEjtp7/pdtS9utPGL//MwCMrN3MM7+ewQRmcFK3zfDpZsbtCt/99B1+PmQIk/u1c8Ux+3PrgpX8dtxV/AAJq2RIJmRZCuh6wcoJPLQSTrNHMWfaCgDOvn48Y8/awKxO6x/6y9NZuiRCxyrpofrZ+Wcy+rE7Gf3YndwZupTlakLyME4eNogD/rCIWUsijOUafvIdg/s/CcTRrAfSMrY6nCEEg7U9LufcYRfh9buMySM3EneWMvasI5h1wW1c8dEEUl3uY15lod1x1iO9qO09ETbJ87FTCjqdXPXuW5snTpZfNxaesOj3qw+4fJFo1645YB0nvPoym+96g7Vh+GfvvrV8b9BlfHBFNUuXROh2z4H89vGr+FP384Dzvurrsk19o5zmK6+8woknnkj37t1RSjFv3rxt3tdac+2119KtWzdisRjDhw9n9erV20zT2NjIj3/8Y0pKSigrK2P8+PG0t7f/cxsU/N09Eh0yAH+vw4C8MFxZVj7kU/udLJRNQ7Qvlklml1Lq94+S3EXj9OggWyruYDpiisg951SmNTomqfZ4nmS9WFbopGXI9tmh+1ZnBibX0pYDTQ1NxFc3YmbENjKIhOyL1hLU6Qdia6zBbvewW7No2yBwjNCdTBzDnBYPq75VnMcSUWk7y3iyDK1Rroj4fdvAzPg47QFmVgTwOWezzsfWTHoYaU8YDle0MlZKpnUr4oX9NEQ3VDBECPcvB0SMgm21OL1Z21gvg4BOHbqWiTNcCErDnJ7AFvAkx0RjN6YlgDNq4jR7+FGDTPmOge93uPPk31T/U+vYv8OhbN+Ru+T/dta3u3bI8yTUT+TCFA1XmAi3WONHQ0cyTxHYmmhRlnTWxjICDq1Yy+6xLSxL9SWtfd7NlvPfrT1Z3N4fpaD5sxLO3mcpr769O+d8eDoPNh7O9StO5N2N4gTa9LcqPl6wG6kXqolslbYq1sVZW1uJVetAAOXRFMVOmu5FrdTE5eZArVvKW5t78pfP+7MxXUE2MHm3rjsffdpVdDoJH21ozHZDXLiyhtgjh/sEEBR5OFEPtzzIt2KpAPzigEyHg477+UwUu03YmWyVT1AqbmUEAkbcEo2ZgSCq8TfHSbdEMNIGZpuJW1TIdMmxMGYGssWSt2O1mThNokNJbY0RT2QI4j7ahEzKJua4aDMEJUpD1MeLS0ufRAIUbK0NT0IxzRSFYE4NdquJ2eCgTY3fLYNKiY7HSokLWVDq4ZV5eJUufrFP195b//nv0b+4dqRz5cITr9nmec1cg/Vra2gdWk/N3MIQdemSCLMe6cXU0adz6R4Pcfb1PTlh9BmcVDGXkb3vZtbjzTzhzuXclb/inCt/AsDIBpeTjj2WxIkDWfSz19j69pE8PPBPvHHTNdxz+1vcc/tbnHnpEsrGfsI9t7/FhFvK8+t7ZnM3gv2r+PFTzzCp8gXic8s57M7XKb7zDU781fdYM9HizEuXsGaixXkzf0UyO5hxy54EhEXK6XMAfn/pVJ48Jc3Jkwbxxg038d6PbmTwkAwvHfjDL4juBw/JMPvpRmY/3cgt9z3K7DMuZv3aGhItdSRa6vLT1Q8QW+nefWs5zith1iO9aLpsOS8d+EPu/s3+AHlr5s41ss9UHlhUjdXzdgCS2cHMeqQXY8/akDc2ENBY2B6Ah6/byMPXbeTs63vmTRRylcvqmXmAaGVmrH6MKW/1obRsHFP/UMrqq/bizpkZHr5uI4PaKoCCg9nSJRFGNriMq76I33804wvb+4/qGwUwHR0d7Lffftx7771f+v4tt9zC3XffzW9/+1tef/11EokExx13HOl04c74j3/8Y1atWsWCBQv405/+xCuvvPLPu6F11l+EpcwwKyQHYjqHWJrGNjklyjREt6GUDJITMdzqYlp3dUhXaorXgvVGMdGtkKqJsPHYUpr2KUU7MlDWpiG5KKEhAL6PznRyyMhpOnKD9dwAPjfQz7mVBRpa2nDW1RHd3E7gGGQrHAJH2Bod6nSslIc2FG6xgxc18aNiq+wWC6sS+bQRPB9tW9KCpgkzXYyC4QEhGFMKq8Mn0qyJNgZEG30SW1ysNlcCxdIeKiUnRRAx8RLCaFmpAKddE0RMlG0XWBKltgWUOTCSY50MVQBwnlcQ6oMwNZYln0cOCOWeGwY66hBY0pecLbXwEhaZmrjshwnaUnhRg0zJjtGzvMOdJ//iOu3l4n+rffLO+v+jdrTzRNuSEaJNsVT2o2LBmy0N8GIaLxHgO8I6oBWua+L7BqYKCFD0c7bQ1W6hMYCnGg7mhYb++NrAMAJi1UkqrTbi1R00p6L8/r3vojZHiScy0Gbns0pyIY5ucdgaFfZDKU/xWUspXmBSn0rgGB5rU1UEKHqUNaOAlG+zpqkLrW0x9uq9mZK+zey+6xYodQlsTWAJWChaZxFtUNhtikijIrrRwf+kiPhGk0ijCNk7entYLQbRNRFUuyWgLbQ09uJgthuolCmGBuUuRo8k2XKfTEWAtgUIWXGPoMSjpF8TPY/5lMw+SVLdPLyigMCG9H5Jsl18rJQSwBZqYWKbbNIpBxXz5RhkDTKeKWySK+J6lbQwMwojI9cAI2z50wZ5YJMtl/9GVhGpt9CA3SHH02hwiH8m5gOBJQYBuZ4xlTZRmR3jWpKrHe1c+cv4i3j2WBnI144KqJlrULvXobxz9SEAzKu0+WNyDidViKbk4es2AmB8/H15f/2FgACFYPc/Eez+J55MGwxY9BQ3Dmrl9cgoZr14B4umncKvZhzL0ebl1HzwGu+fKkzMjYMK7VEzVj/GjNWP8VCikHfyemQUAHFnKT+951Keveov3D9mASe2vs34CU8x8MI3GB1dSur+Q6mZa9C7b20emDx83UZ+9JvJzFj9GA8squbgMa/R7z4Bg1Pe6rON09rSJRGWLolwfiLBfz16DN95/AUOun7WNmzH4wf9kgnJw1i48Che+d6r4lKGmBIs/1OScdViqHX3b/bn7t/sz7BJT1Mz12B8vzMY3+8MOV7rJvO9GXcBcFrrKxznldA4Y29qe1zOvEqbeZU2g4dkmD5uNOcOq+Mv4y/aBpCBhF7mGLPWofVMHX06495aTO0d7zPgAGlls3reTqKlLq/NuWHzSH5fb7Ng5QT2unUuP9jXYdyyJ/mv+LP0mf8MR8/77df52nz9FjLf93n44YdZuHAhdXV1BH+XaL5o0aLtXtb3vvc9vve9733pe1pr7rzzTn7xi1/wgx/8AIBHH32Umpoa5s2bx5gxY/jggw+YP38+b7zxBoMGDQJg2rRpHH/88dx2221fP5dGB3Ixsa0CEOgMDkwDsuHdo1wLV2jLq0LXsVzoJIBfHKFpjxiNQ7IM+s56VpR9B6M8w0G7fsrra3vTtaoFx/RJ31ZFbF1GgigDaSFTvlFgELQOtTaiC8lvU07gnmNhckYCYTqY9jzUZ2miW6P4XcvxoxZ+VAbsRlZYlMAWNiJbbKJ8TabcomhjCuuzRnRWrI2VZeLHLQm6jJgYgEr6uKVRvISJH5Ee6FwrWWArnLosRkocysy0j5H1hN2JWeBrklUWLf2g6m9i82xkhXXCzW77meTtqsPnfph81hnc5FzIcnqg3GdpmnLcPA/w0To0Y0imsdt9vITssxgPqPx++BEj1PJ0arD+BmuHO0/+j9ZXsTD/qM3s7+fZmf3yzdWOdp5oE1TWyN/Rz5b7ROssnBZFpky0HYYLXiK8GaQVh++6lppIKyuadsXXBocXfYSNZs+izTS4xbzS8B28xih0SfGnun3pWtpG76JG3o/U0Lw6RuqTUoo/V6SqcqNn0W6gNNrW4BooR4NWZDMWG1rKiDkutgpI+Q4lVhrHlB9bVxtUxpM0fVrOR9RQ3aWVdtdB+4Z4opg5a+KQmbAEMBmuWBKLRbRoRpwGk2iDInDEnU0YDIUXl4BIEh7aNTBKPfAMlCGmN35RgF2SwSjTlCTSOBU+Ayo2c1DxOl6O7U5zNs66xgr8LWUEWZOKns1U7JHik9XdUI0W2pLt8rMmVsTDLfcwY54AOQOCaIDdKK3UVkdob23IvoHsn7SxQYDGzCixx/ZCnY8CszQLyagwM4jI3yxPU5RI0/5BuexHLBCTgx2kdqRzpeMvK2H3IVTdM4YFNRNE04JLzQevUbvXoQyZmGHwkICRyRMxPgYqwf7hGri+J7WjAubFX+XP1W/yo9/I4PpHSKsWwKJpp7Bw4b3EnaUhUzOCRdPmUzP3VJZW2kSPHk//iffx/qnns/y14xjKhYzvdwYzVj+Wb4Wa9XgzN4TbmswOJnjrIs5ecDhUNjN+3aW8bq3hvbTD3hdkWfvgm/AITB93OTdZa6gZ8hp9N4+kZn/R2ZQsroKyQqvcjNWPbcNm5NiOD64YxbnD6mi6+UAA/lA+kidPSTPv4dm8XzmQq0fuxhPn9aRhXoRlmw4l0uMwEmVT6PIVksXv/+wZnpk3Nh8uWcNtTJ79OJN5ldpRASWEov2QsZk+bjTMnM2J63pRs6kntT0u5zjvQZ63Whk8JFMAVItlvtzz1ef3gwc/ZNWQDOP7ncEDi6ph/4c4d1gdV536AT9d9DK/By5cIOzRH9/Jcs8Bd3Fa6ytUTMxyzwGj+bDPOP52+vZ9d742gLnooot4+OGHOeGEE9h7773zAut/da1bt44tW7YwfPjw/GulpaUcfPDBLF26lDFjxrB06VLKysryJxDA8OHDMQyD119/nVGjRv1T69ZZV/YrB2QgtOP1O935DwqMSM6RTBXAjjYNkt2jNO4fsOeum4maLv32/IyY5dI7vpVlLbvT9GFXUj09+uhA3MoMo1O+iS5klXRmGIzchckoMEB+6JgW5Frd/MIA37HRmSzGms8woxF0cQKzNI4fMfGjYnOsfHHishvTmC0dkMnm3b5k3wO0KQN8N27huAFeSRQvbpKqMKVtzAC7LSBVIRcnN25BkYWZCjCyYuWsbRO3xAlbCjR2u4EXVWFrhQRUYodA0M3KvndyIRNAEjJkObas8+fm+yijM7jxt2k5Q2t0JouKRohsTeMWJ0S4mdUoLe0KfkThRgy5gH0LVJff5Hnyr6hvA/PSGaTkwMzOlrNvV30T54nKApYWK11fYaQNtKHJlii8ogC71SCwZKCuXIVSmgqngx+Xv8678e7EjQzFRhpTQVR5rGmvZH1DBUZaURTP0JyO8fmWctZma4iWp4nVa7ou9/DiBgQm2TLJatG2xuow0K6CdkeYdAVexqI5U0RHzOVDoC0doTgqA6i2dITXW3rjZiyK1pl48RhbdrEp6dqGarMIHI2RkdBLIys3r8wsqBaF4WncovAmniOtXVZSkS0JRfOWgBzDg0wFaCeAQKFSBjrroJXGKU3hJVx0s4OXtrE2OzRaRRg9O8h4PTmsZDVvbe6J5xlk2iNETUBpGjeXMmCfLXxidsXMQrpYo3broCyWoUsiyeaWErIZC8sI0IawX0FEQJZWsm3aCsHZ30lWDDdkWzxFYIrRj5kBP23hpBTZsgArKXqZIGviRk1h3xI+RAP2rKzjw6/3tf1G6j99rjzZ9H2epiUcrM8DhIUBWPvgm1wG1E4cCCzD8H8FXMv7H25i8uzH+bTpCFqvOoyRvMnBz09jt+8von7A8TyzJAL3jWL8uNGcFq7H+Pj7PMP3eSZ83l58Jqevm8HIafPgFVg94CU++VkTf3rhBRgVMGPJXfzplq6MnLZFtvOQKGOWpWXA/Z0fMq/S5ghmsxY4+oNMKGYPO2Zmyuv9vBLGDlvF2Q9Km9Tqq/vJ/tEpbHLJm/SdOFAef/AaAw64gI23P8X5zz/Ms1f9hZLFT9E6tJ7T5j3H7PRgrp06jxmLqqnd61Bu+tGNcDGwaTI/iD/E4Ldk/UuXRASEhLWsuJSTRs6i1rqRyZMuYero05k6+nSS2XspWVxFpPoRFi48igldf8YzwIkv9PrC55QLuuzMBj1vtVKyuCT/eO2D0HfiQJY++Cb0K2zHjEWPMaGjiO/89QV+DviX7M3H78uxmLduBbV9Ava6VY7xB78/Gbhsu747XxvAPPnkk8yePZvjjz/+6876tWrLFvnS1NRsG2RUU1OTf2/Lli1UV1dv875lWVRUVOSn+bLKZDJkOrVmtbZ2clcIdF7Mr7OuPHa9wiA4V7n2JdsRxsMK0+rDAEuvuoTPj4Rd99xCUzrGJ1uqKC5KYSj4tLmcsvcMSj51UW+CszWFdmxxIOuU/SItUKF7ieeB32k7ciCKTkJ3XWBntNbCCuXE/4YSRmVrFrO1HUNrHNvOt51pP0BFI+hUSsBRII5dWmuUH4Zh6tCa2VDS8hVonI4AKykARwWaaHOQByhoCbRUgSaIWGjbwIsZmNmASEtAtMknW2zixhUq0ymzJWdckNMWhQYJeRBnUnict0lW4kiWez/HSuVsr+XLgQr1RkZzB7F6m1SVgx8zsFvFaMDqgHQXCyyFmd7xEcw3dp78f1r/vwGX7BVv/59wIvtGzhMFJDyMFgerXQkr4cjA2Ewr0r2yqKQJJS5B1sC2fD5o7cqqoq58kO5ON7uZvyV70ydSx8q2nhTbGTINMcxuaXqVNrOlQ8C/yhik62MUhZvQtLspxgFa2p8IzQSUp/JhmUqDzhioSEC23aGBItyUTYcVxYl4pBtiOA0mpiMMS1ACKE1rbRGxBrnBY6akGcGLk8/PcoskT0Ub0i6nNPhFPmarME9ukZYslZjYjpkZhdFuEkQDrA4DeidxWyK01yVAK+zKNF7GQnlgBsAnCRoTcV6u3JOOliiGFWDHs2SqTHTSIr7B4q3Knhgxj2ypheEhOTml7fQtbiDp2mxuLSdtifkAvsKPB4Dk9GgT/HiAkTKwUmKxbLcJM+8lNGZW5XVN2S4+RlrhbLZRvhJApMWcIB21SDs2dptCmwZGWZa48XfdBTto/bvOla86Ty5YOYUj50kL2DH7P0TNXJfaEP/kBva/WFHCvEqbkQ1XcfoDG7jzkRsZt/RX7PPbV9j8nMWaDeM52PgLIGxG29pZ2OuSPHPKWE777S3MPGAoT5SkCbr022abakcFVK0SUf3llxzF0FvmcNrbjwKnc8PmkTBtnrAIvMa89c8xhlvy804fN5p1I05i0bRTRKtTJq5g8yZ1BVxSZV1YfX4/jvreqzywaBTzKiPUDHktr+up+OQPsqBxTwJXMPOQMezb4DKv8iGwHqLvxQNp6jaPWTxF1arnAJg9dTbexssY3w/+dNMy3rn6EK72doMLnmT6uCcZvPoxQJicwasfkza8WQNYNi4U9AOzOJSaIafkmZ/nrVZOYi5Bl348VPoq00fO4sQXelHb43ISLXUMHpJh3rrCMRs7ZdUXWsmAfBjm8w+2CmhZ/Ri1EwdyE1C716HcCNwBHLL7a1xy/FTgNXbvvxr6n83I9yX3ZlzjYorjv2P6l36DvlhfuzHTcRy+853vfN3Zdqj61a9+RWlpaf6vZ8/Ch1G4Wx9s89o2Fr+BLrAAYcuTdl1hQzwPbItktwh9+m/mgIqNtCaj8Gmcjr91oe3NStT8chJ1AVbaJ1KbxEi50j7m+QIyzIIVcF6w7/sFHU6oD8lbDOtAtk8Z+cG6MsPBOxR0OmG7mXZdmT8WEU1MmFKvk8nCvofTqlDrY6Z97HbJSvHjVv5H3G7zMTMCWlJVFlYywMyEwEMBOgQvpoFWisAW+2SlQ8eZQAuD05Zbty5sc9AJyOWOue+LQD/HzHTWAOVApQ620b7kWTPPk8we30f5AVZTikiTh5HVBBEDI+NjZnyijR52h8YoyJv+v6x/eJ7srG+kdjqQ7Xj1VeeJkVF5sbrhhaJwDXaHJMartIndalBcksKKeziOR8qzSRgZ9o1tpLvdxJpkJcvbdmO3eD1uYFK2iwwWPmsrpXZDBbRZlH5oUrTWonFfzeeHWSS7+wSOsBzRegPlKXRNBq/UR4XtXVaHwkiZ6LQJWQM3ZaN9RZA1SbdFsNpMggh4pT7ZMshW+tglWYyU9Fbl2AmtyP9OBpYwEpFGhdOiiH9uYLfJ9Sind9Em6DIXo0tWdCtVPqo6A5GAwIJYLItTnhbNiJbnRWVJtC0Awo9ptKVZ316BMjWBJ77LKquI1FmYWXBdE2Xo8EaaQqdM2tMRWtwYadeiqCxJWVESpySDkXAlIyYeFGz3Q1tot1jjx4Jw+8MWs4zsu5FVmElDNDsOeEUBuksWtzgIbZjlc890CYSRCRSG2vFviP0766vOk8bSn+enKVlcRaqsS/7x2gffpN99qxn31mL6ThzIgEVPsWv5K/hvf5/K5zJs7mVRd+gY5vU4kb+suJ1nGgvMzxNXPM7I3nez9wVZbhzUyt4XZNl37Cr2HbsKa96R7Dt2FSBi+PoBx3PlC1X4w+fw5CvH5kFG8OyZVK16jtq9DqXyuQxPnCfbXPHJHzBW1tNn/jMs/uXjea3OVVUnAzBy2paQkXiTmYeMYemSCMd5JSxdEqF2VECqrAufDZrIB1eM4rNBE/lskGiHcu5f51w0gffukW6UUw8ayJNbbuHJLbfgbbyMc2bO5pyZs3nn6kN4++eX5/d3zNNRxvc7g9q9DmVCxwgAaj54bZvPYMHKCax98M28cD7uLGXwkEzeECD+ykDOmTmb+CsDmZA8DP3293jhkTnEXxm4XZ9x69B6jvNKePrB+dKq9sFrrH3wTa7tNo8h6hEABh+/OP94zzlz2HPOHPa6VYwYvm/An9/bfqD/tQHMZZddxl133ZV33vp3VdeuXQGora3d5vXa2tr8e127dqWurm6b9z3Po7GxMT/Nl9VVV11FS0tL/m/jRhGEEegCUCFkNpCWsnzlBvcQumU5BYveHKjJZHGaPZqSMeqzRei3Sql+I6BmuU+317KUrPckONINMNpTqHRWmJIgEMAQaAg1NTrdScSfdbcVrYOsL8ca+SEACrdFd9bL5KyHc386QLUn0R3JcJ9yoCUosBY55sLzMVvSaEtBIMcpcAy8qIEfE+G/8qF4fRq7zcV3JCDTcAOCiIkfMcVIoNTCiyjs9gAr6eM7BiqAxGYX1ZHKfwa5HJ7O9sl5EBLaVsvxV9u2ywUaHbJJf+8+Jp+NkRfyEwQYbSmsNjlZfMcgW+6gFdjNaaKNWeyOvw+S2fHqGzlPvqH6V9so76ztq+wVb3/Tm/C/rm/iPDF80GmTIKLx4giLkJa7+ngKq0XARWttEV6buI9FTI+EyvJRuhufZqv46+rvsCFZzqfpCpat64Nt+Rz9nY8Y1ett9tlrA7vuuYWWAzOkKzVmWqyCtaXFGSsqA2inxUBtiUIkkHY2Qp1GUmGkJLdFJ01Uh4lqszCbrNA9TGMkDbKlAQRiP6wtnd8PMyN6EbcI3IS0XylfQjr9KHgJWZdTZxFpNAgc8oCuqqIVr8yj1561dK9sRlkBQTQg5rh0K28l0bONyp7NJD8qo21LyDR5wo7oovDGXMrEaLbRG+MECR9tabwYuGkLv93GLQsIbA1OQHt7lHc2d6elLU5ZLE2fkkYMQ2OYGhUJ5Hg5QCDtbipAjmMkKGTC2ICSFjPDI8+qWSnZdxQERT5eQuM0mPjNTh7oBG02yz7b9Z/78v6H6991rmzP9WTQnPvymorWofX0nTiQSPUjjGxwee8eh58PEgCdaKnjrmrNXdXyfbJ+/hYA3e45MD94f23IdzBOfJRru83j2m7zeO8eh373rabffasJhkznnVkDtll3zVxD2rwGvLzN6880jmLs8EtoOD7CyNp3uOAtEcnnRP7PDxbnslMPGsjBY16jdlSAt/Eypo8bzfRxoznOK2HwkMw2+pHWofX5/XzeauV5q5WRDW7enCAYezRjuv6MvzbfgHHiozxxXk9+MukhbrLWAMIw9Z/+Jk/dKKYGI2vfyQOyq73dmLf+QqpWPcfSJRGMratZ9dY9AHkx/cgGlwGLnmLy7MdZsHICC1ZOAOBHvc4FwOxxN2/ccBOX3FXQtC9dEslPl6vjvBLai8/MP8/tDxT0PIOHZAiePZOWqXsw55Ld8+AF4Jk9r2RS+hMav/NDRq/uyX5PPk7XTdt/5/hrA5i//vWv/O53v2O33XbjxBNP5OSTT97m719Vffr0oWvXrixcWEg4bW1t5fXXX2fw4MEADB48mObmZt588838NIsWLSIIAg4++OCvXHYkEqGkpGSbP2AbUJYbBGtXMmAKwZadhP2dgQRsA26cpjTuX7uw5P3dSXyusdt9IlszmNlA0ucjBmboykUngKT9AJ3OCLDIsQk5UNNZ35EL2wztlLXriQbENAXEwLY6FkOyagruZllpF8uBFkBFowVwpkMrZz9Ap9MYIcBIdzHJlFt01BRCMLWpSHURoX8QghI/ahJEDPyoQbbMon0Xh3SZBEcGjkJ5IQOjIVLbXjieIdOktS4AkRCUaDf8YttWIbMnKFhY63Dbt8mDMTodu3CZwpT5kHUxMh5+RGw7tQHZcicf5Gmld3wA802cJ99EfVvAy06GZMesb+I8yZZrVFqctXIDX7dEk64MJCk+LfoRp97CabBobk7Qno2w1S9iRXMvFjbsCS02axq60OFF8NMm9Z+WM7bL6/RwtrK5rQQ/MNCBIohqIg2KaINB4lOLkjUQaZL1prt6BJGAkooO/JgWsbnqlJmiNCoUteuIsBFiMKAwsoogIm1o1SXtYoFMKNz3wv0yhaHI2UIHTs75LBCnMk/E8coXRgSgqS2O3Wjx6SfV1LUUoT0DHQ1obI2ztSNOe0OCrQ3FWB3iFOYVh+ArKutvTUdBiS7Fr85SuUsLgQmp7h5qq4PVbEEgrI1qt1C1EdLtEaJRl+5FLbR7EXxf4bsGdFgYGQMzE2pzsqHWJauEYlJybZBWPNl3Lxa2yIVZM5GtBkadg8oYBBaYGbFyNjy5xhWvtki37zgi/n9U/65z5avOk4f2FceqGzaPZNG0UwARredanPb5bQe1owISP2ni2LNOZuro03nylDRqv7/w6xU+F513Me9dO40TVu/PCav357Uh0iFU99jxjJ48mtGTR4dtYFIvnNudxE+aKB69/AvbeOn9tSyadgq1owL2vWkZNw5q5aSKubx7XiLPUkCY9xLWyElXA/DMCy/kmZg/3fI7oNC2BTKQX7okEupGqli6JMLYKatoLz6Tkyrm8nif8fntnHnImDyb9MCiapYVl9Lj6JVc220eD1+3keK+Y/lTIMu/yVrDQbvI3YLe372Hm6w1RIo+56SRszipYi5xZ6ns9yNz8kGTAxY9BcDU0adT1PYoT56S5pj9H+J5qxU1fk/8TRfyq/o53HHRMIr7jqW479j8fjywqJrjvJJ8y1gOFPW87FSet1o556ICyMm5qj2UmM/Be/2Ke5+4hUce2JtHHtg7z3Ids/9D1I4KOH3dDFacfD7v/tepX/r9+bL62gCmrKyMUaNGceSRR1JZWbkNJVhaWvq1ltXe3s7KlStZuXIlIOKxlStXsmHDBpRSXHzxxdx4440888wzvPvuu5x55pl0796dkSNHArDXXnsxYsQIJkyYwPLly3n11Ve54IILGDNmzP/KWSnHwmjfzye7Y5qF3JFQQI+57eHLMTYAZmM7XV9PEV/j0DRAs/lQh7pBCZp3i7B1b9F9GGkvb5sMoINgW9YhZxmsO4Gm3H/bKmyTMlCmibKtbbfZMApsRvhfhaL2LwzyDSWtZSGjkx/0e54wTa6H0+ziRRWZUumBttsly8UtEiG/mzAJbAMr6WN4mnS5SabUJFtk4EXB8DVWRly/OrpH8KKK6NYsqrlNWrt0YX9VxJHjaZp5DYyyLdmukE3qbGFNEMgxyH0+YbhlXr9khI5kuYBQzxOA52siTZ7olkI2yUvY+FHzCyLOb6p21PNkZ/1nayc4+se1o50nKpCBrN0mQMXqkAF1EJPWpMDWeatfq11Bm83Gz6R9ZmT13xhR9R6JHm1EbI/e8a0oU0Mk4Neffo//3ngYDXUl1L3elchGByOtKNkQ0PX1DGWf+JR8miXSFKbc+wod97FMHzNV0HJqU+cDGs12Q6yMswrsgCDh41Z4og8JLYlTro0Z8XFLhFFyQ4bFyAo7khPoS5CkuHdZSVmfF9Okq3y8ChfDDggCcfOy2k3czxKgNMrxsayA9uYYzhYLY6uN3Q6RrSZGeYYgGqBabZzPHVo7olhFLn40oLxLGy1tMdHV2BqqMrLdoWW01W5IFk7axHXlDn7Gs4hEPBIlaVRW5bdfBWLvrENjBafBFGcySyyUlRbAZqUUVkptA+TMjMJuNURLmYJIk8LrnsHt4pHqqikuS33t79C/q3akc+WPP70WgLHDL/lCvsjY4Zew4mSxOj7k47dZtvt+LDj/Yp5+cD7Tot/hqJdEvzLn0NM51U1wx0XD8vOePGkQcWcps6fOBmCUsYoz338m//6xD3z+hW35zU8Kup/aUYG4ioVVteo55tXsS2ufn6LG75l3KwPy0+1707JtlpezLc4J3/tOHMjgIRnGTlkl2S3XDEC//T0ydWdxmj2Kofv/Ypv577hoGLv3X83hZdeyatipjJ48Oq8/+b4hy1/+WQf97ludbxfb96Zl/P6YaYx5Okr9gOMZPCTD+lMPZ79f3wawTbbO4CEZ+k4cmGd2jvNKOORjYdx/eNZf+fWKbQdBv790an5fxk4RxifHyqx66x7OuWgCh5ddS6T6Ecb3O4Pp40bnWaVcqfF7osbvmd+WksVVTBndwgWzmgDY57+f+sLn8lX1tUX8//3f//11Z/nKWrFiBUOHDs0/v/TSSwE466yzePjhh/nZz35GR0cHEydOpLm5mcMPP5z58+cTjUbz8/zud7/jggsu4Oijj8YwDH74wx9y9913/0u2TzlOgZHw/W1BRI6tUTlHMhG351gRFQQ4G5vo9pqi7oAobf083BIDM6XwSn0SSwNpm3K9AlMSaFmu7tQWFa5b+0GhdSoHMnJgx1BAODg3jLyDmgLoxMzkt//LXLxygMX8Ekwb5rJYtS2UJCyyxQJYzGyAkfEJTBsVgN1WMBkQ8b4pgCAG0UYR+geWZL+kywxijQH25y1ilhBx8mySbF+4Lbn9zgESCkxZ51YyhZl/T+UtlK0CGFOhOUBu3wEiDsr1MLI+ZsbEi4qldKbCxosq/OyOgWB29PPkf1NPHNn2PzqRfVvYl//L9W0Q8+9o54nTpAiMAuvgFoltr/IUVtLAaVNkizVBRDQisa7tJOsTfJKpIRk4GGhSKYcU0CuylUgiS6Y2zqcv70q6m4eK+mJdXOFhpAzaehqkKqT1OLBskl0V6RpprcJXNG4qI5KVdl9JvA/ZBUKtR8550RP9icoa+WmpzJBwsjRAOKAHPDqx8HIZy+WmBFFhXgDc4gC7zUA7GpU0CTImiV1aSXVPotYk8OMaM+KTiGdIpRzsWtkHI6tIV2oBFIFC+cIIeXFNzPbJamFgGj8vxegwifTsoCiWoak1jtlmyHYUeVgddmieoMi2O6Q9m3bXob05Bp6B6SmCSIBrgZEGbcvxMDIGhi/7EJhihBDYsl3KF0PQwAE/FP9b7cJWZSs9rHYbw4Oy8g6aPi/FK/PoUdTOB//UN+lfXzvSufL7qQczdsoqZr14B2s5fZs2pHfPSzBozn2cu6pOBu5LPuQY4DZmctiF43h+j5cAqL3qL6x69x5uPSfG2fyYRV1/zwOLqvl5cg5XzfwV8Fdah9az7K79OOTjt6mZaxC7GRhVGAN9/2c/ZoJ6B5ABfO1eh9J3L+D3v8D54By+f99Kbth8I+fUbOXEirk80ziKpQBLPuTh6zbyxyuP4ZCP32b9qYcDr3HOzNl5liK3PAjBzOJO4vdeJXlb5YW330LfjOhNru02jx/t9xc4bR/Ovr4nPSrrmN0wm9FZYcGe7NIP/YtRZCa9wx/KRzK+3xn05h7+eOU+AkL2h/WnHs6Wv7Vx4rW/4uRJg1g9+3EGhF1h756XYIE7gR8uXs3YKat44AOINW+lBnisFV7/89H8/ISFTB83mnNmzmbwkAztv5kMIXAB+OPLdxA9ejwPX7eRwYuqmX6XsDFzKlbwp1t+J25yq2Wfj+omep3xRUNouOY+KqecT91jx9M6tJ7xfzuD3t+9h+etVhq+fxA/3s7vjtL/pJilvr6ejz76CIA99tiDqqqq/2GOHbdaW1spLS3l6LIzsKyYgArYtv3INAu6is6p77nQxVCnoZS0ailLghqxTHTEwa0qwktYtPSVwX7NKw2oZFraxwwjL07P2zPn2IKck1aOOegMZEJzAWlv81HRiACWTi5mncXuOfZFu56As1D835k52kZXkttP0yiwIaVFpLsXoy0Dq11c01I1DlYqwG5x8RIWflT0Maku0vdc9HmA4UnCse8oDB+Uryl5byuqtV2YpxxQzDmL5R4HuW0xtn3e+XjkRP65z8u2tnFz28aGGZBsG9kfIg5BcYxMTYJMqYnT6pMttciUKHQyzcrfTaalpeUbbZ/aUSp3nvy76quAzLcRwPyr82B2BPblqwCMTvu417y38zwJK3ee7HnBTbi7RFC+6CoCRwbzaIXhidg9yInToxpjlyRuu8P39nuPlG+zW7yeGW8ehmEHTNzvrzz07mH4rQ52s4lb7hGptXD7ptljl1rW1FUSjbh0rC4TfUpa4RVrvOIAu9nID7rNbKjBIWSDwsG3NjTaCa8bnmgdlacIogGYmpKadiqLOtjYUIbxcQIdMg6dWerAEQATOFraqNLSPpUtC7DaDbzSQFgeH9xKj1hFilSzDIiNNotIz3ZSW2MYHSZBkS/ASYPdaOHFNGaYcK/jPn13rWNjQxnBpriAsJoMiaI0fcsbefv9XVGukv3RYLWZsn8moKCkTzPNW4uIrnfy7JKbCM0WXAkd1bYWvacWQwIvIXEDZppw31R++9zi0Kq6TViZZC9P5o2KQ5r5YZG4wO1az+rTf73zPAkrd55sGrKWHwy6mcUrb2T5dWPxh8/ZZrqRDW7eVnnpkggLzr8YALWXtG6doU5g9VV7sfLAx9kztjsntgqIqNuzJzOW3MV/bTrmC+v+7x4LAGmHyrEkIK1fI6dtwdt4GTdZa7ja241n5o1l7x+/xqVrn6Xyz2KEfVLF3HymSk7rMWV0C9fMlutj7V6Hsm/oErb2wTe3ATI5sJIDag9ft5EHFlWzcOFRADxxXk+snrcz65oBPG+1cta57/HIA3uTzA5m7wuy4jqGiPaP2f8hAS7fvYeJ736PfW9alj9WueUBXHjF3hxedi2jJ4u18uyps/nRbyZzzP4P8cIjcryfunEuf7rld3kjgT8m5/D6lUvzy1i88kbOHVbHrGsGcMrEEZwzU5ith6/byNnX92TwkAy1ex3KsNgB1D12PCdPGsQDi6rz8zxvtfLitDrW/+0CZqx+jAEHXMCqt+4R7dG0LXx/xTH8+I+f41T+lmzDedt1nnxtBqajo4NJkybx6KOP5kMsTdPkzDPPZNq0acTj8a+7yB2nTAtVlCBobM4P/vOi+iAUDmqNyov4hflQti0tUFkXnbMxzroy8LdtlB/gbMzg+AGxdVEZQCfT4Ir2RWcyoXWw2tYFLWR2MA10ppOTWM7eOADl2Hl3Lnx/G/CSZ3GUkiwXwwA/bFfLZgtsTW6+IMi3aWmtyTcbaI1OpwUEAU7Epr1vEYHtYKb8sI9a4ZbYuAmDTKmBH1VYSQ0pQn99hW+DF1XEmgKKP2iE5laxiPb9AqDIVRDIMQ1BYP6YdLa0DmSb8/k7ORCTcyfLAZ0cGMs9N83CZ+t6qKyH3ZolMCP4MQMVyN1D//9v05j/eHUGKjkw820ELyCA418FYnYE8ALfDhZmRyptykDXj2u8ItGUdG7h8iMCKIo+hfaeCjdjYcZ8tqSK2af0cz5s70pkQwR3txTPfLYPfrstuo7igIruLXTbo41DK9bSw9nKrc3H0tqYgGKxj1eBwosHaKXzifIgAnsVXkp0yMJoUzJdAgJ0NEDH5LpjxVwcU+O5Jpbpk3RlYJMDKma20DamAlmuduSxlVQ4raKz8R1pOTbKMwSZKJarsBst0m4CqzyD12GjbU02Y2O2m/iJABXx0Z6B2WiLm1siwE9odMwHX5H2LPSGBHa7Ir1rlp5VzRhK0yvRyMdVVaSaoyg7oLKyDT9QJNMR0u0Oqs2i7ZMy7BB85R3UQiCpA2n5y5brvGGBNsVq2UgbGBlpi1O+5MdoQ5bhxTVeMRhh3o+qTuOnLIKNCXRcY2TA9xU766urdq9DeeCJ3bDClqMfnvVX/vDI4aTKBpAbxrYOrWfkDbdiH/AgMy9fyI8HReH6P9NR+1fOmzmQC68/jcjrc3jqxj7MeOoxnh/dQteqL94YmzemK/8Vf5ZzOZCqK8fw+J6beeSTx7GmbuHs63syfZw4eK0NW7o+/sVMqq6u4pBwkP5q0WEsP/4xpj9hcXViV+qMZu68OsMCpM3q40ZpZRsTGcabnjAsQ/f/BW/e8QAli6sYeMm5DNz/XK7mCt685gFmAVc88AmLPr6V9+YdSv2Aah4YWs/6Uw9kfNNcyXQ5ryfPzBvL71akAThtXpT6cH/uvu5VNk2aB8DPn/8zz171F3Jc2Oypszm8TMDaQsmpZPTk0QS/6ceClRP48SDR2lSfUcrIaVu4epLMufvNF7J45QkM3f8XvH/dTZSUdaGVepiyinmTurI2cQUAixfdyLkhAzMsdgCHl13LHFaIdmf3/YAFxJq3oq7ck8fe+z33Ph1l6Nm/oDooY/2ph1M76q/UzO2K97N9WX1+gr0e+v52f2e+NoC59NJLefnll3n22Wc57LDDABH2X3jhhVx22WXcf//9X3eRO065LkFDozzuPOgn95IqiMehwALktCu5PJYcW5PTr3ge2nUFzLS259/PCerzrU0GBdBhhMt3dcF5yzTzIEcRsi85tkgX3LtyAngV7kO+AmkxywMXyG+Dsiw0CDtjmvI8Z9Ns2iHDZKLTacy6JuIxi2T3KG7cxvA1flTlBYvS/6xx2gIMPwQvoa1n2ZoMzmfNqLYO2RdTwjp1LIIuiuHHbcmY8TRGxkO5AWZTGzrnUmaHX9mwpU+FbWJ57Y9fcGTDNNHZ0KAgx+rk2CZDoYMAFQSoZBoz0EQCTbYiSrZSjAjs5I4v4v+/Wt9W4NK5/hUg5svAy/nZh7902vucs/9X69qe2glitr98R7JLvCL5HTFShjAx9v9j77zjrKju/v8+Z9ot2xd26SgC9grGaNRHMZqosUSNAY0azWMvERuCGKOiiA00xlhiDBqVh2CJ9RcLmtijGFCJSlHp7ML226ad8/vjzL0LeUyiSUw0D9/Xa1/s3jIzd+7lznzm0wyYKSeEaSFM/G+3g8xL3mYQtW6Jj7sbCBpiNu/Xhh/ZyLxljPUh+P0dOkppXuvYnLMGfkifqjzFgkcsNOmlNk6PJvYkUZ+QsBasnAXCrNfOiQq4QmhQCSuuJCoyRYza0cS2IipJhK3IFVJEgYUq2Dia5KIVlbhm5SSWE6F7m+ttI72yfCOtirpdJCaOWHkQ1mlULCASpFos/MAzIWUa3HRI6NsI7WCVzG0AqRUuXju0r+6HqlWU+sVsNmQdw2vWs6pQS0+UIu0FlFwXNxXSkC4ghWZRTwZpKzTgdJnv9zJ4MfJnYYz5tTFxJIyELhuhC7Yx62cjlCvRvgNBsttsbeKlOy28VouwyjBpKqXYa/MPefFPI837Hpr9NLypjQ//tR/BL8U8/87ZTHrXgXHGlH7qYJNu9uDMPbl9bhMnnjqAw6a9w28mbA+LYJvLJ/H80Clc+UQX9735HK8/Adm79gRhUq36jn6S+978NjVD+jJqp1PR8df42ozXK+ubcv6ebHP5JK6ZP8XcMPdgOk5sZfZVhxoT/V4+/GI2zetDWr49hb48yaqjVrPvTpMZOaaV2+e+wqQRx/HaY43ccuxXueKR92lSdbx29YWsXO9z5Akv8foTFzJr0lcZ6/V6cuZNv53FZ4xgxK2LmXzDS3xbLmTU+FMr989ddF3l91PHtHL73CYWHXQeN9Y0o0aOMyEC28LTPMT4m+ZyxNk/YuTaxbyolzI2fJgd1kzhikmw4OILeAx4JjIAo37CGwD0/Yng0NN6qxDGAjuMW8g521/PyvU+i9pfYVH7zawKTmCgO7PCnjw/dwo1G0Rbf2fEN5m14BuE43dh6vS3eG3kjhx9ST37tu/JEyPms+igl7hizfXw3kF8ddECvroIYC2HTXsHgB30Qv502V0AXHnRsdyVbM+jj4zj8N0n8ocT9maXT1kE85kBzIMPPsicOXPYZ599KrcddNBBpNNpjj766C81gNFxbE7WVW+iFVDxlAC9V/nlBqxAOcnLtYANwAtlgFD2ZJhyTGJlmJMN45nNinrZBthoOZXyxnInTcKWlAMHNpKBJYZ2rRNPTSIf24idwYCVcvmm1tqwLxusu8JCxcpIuEIT0ayjCOejFmq6aukZWUdQLbGLZjtinjyV3AABAABJREFU1xyM0eDXSJyCMT5mWiO81TlkV84wT0KAbaMaqonqUsSeRZRJDua+IsxKonSKMAuZdVWk1/o4bXnDXEUxulDs3f9SICy3V3pm272gMNkfFeBSfi1lNiYBcsIPsLrA06BlCuUI1CYAs2n+wfl7QcxnAS6fdP/nCWY2gZhPN1YIeMYsj6uIpTbHAGlAjWgI8C0Xp8fIqtwOiXJAtbu8bG1ONh3gNhfom87xcVcDIjIMTlCniPIuhVVVrOtT4s36YXSXPBw3IpONKPRz8OsFUd8QlMDKWVg+KEdg+aarJcok7IljTsZjL/GaeAoSv4nudJG+IK6LCIo2IpAmcCBvfCjK0bhdosLwKNuEEijXACWTSqYr220VjRQsToFyNF5DkaDgIiJBqSkmvdoY5v0GgdWk8PMOVmyYLLdT4uQEfoMmqBM43RDUglUXMLiqg/nrBlIMHJZ31NO/tptt+6zl9eWbsaytgUzKJ847CMcEEkRV2oQmiARgheZfGYpe66kEHUrwFKIgsb2IVE1IT7EGlMSSZh/gxWgsE9JQNHI5EQu6gzRWOsIuuGipifv5pKzwr31c/s/ODcc08fv3roX3MCb2dhjZcA5g/p5aMIb610ZSMbk/VrMjl85ewHUPH8tuP7+PkU/eyJVvbc5dwO7WOxw15Hq+c8o3efS+PZh11BROHngYN1/2GLedNJHdppn17jthA8N8O8zy53LqmEc48oSXKqlb++40GRbukTAJhwBw6PvT6NlpKE0K0vdfx9RkEd0H78LKmXvy+hP7sXK9z4hbFwOLDUiZb/wlOwCL+SqcFTBq/KnMm347AKPGn8rz86fQsvUebIfxyjwz/2QOOOFOttlpEsMOX8YfjrmXzmEmpW36D8dw1rQu9gqvYIdrX+NXD/yA5vdeYdtdzoKb5tKk6hh/7lUAFRC13bHwIUMZll/Gh9mhvHb1hbwG7HHqYRydepUdzoQ/XXY1b0/6KnsPXULf+/ZgHSZ5rSx767vwSezBo9n3x02V92Ji5hAm8xKTb3iJRSvP4+yHTkOLl1mU7JeWrfegfsIlqEGCJ2bfyw5Xv8avNv8B3/voLj7MDjWP+baCbQ+i76vgZj4ELv9Un53P7IHJZDLMmzePrbfeeqPbFy5cyFe+8hXy+fxnWdwXYspazDHVx2Jr25z8J1f0NzLOlz0WrmNut23DrKQ8c2JcjiguAwUpzVV+kfhkZK8RvezR0FGSQiatXvkTbHwCXg4QSJiG8vaVQUrZA8MGbFFlygzMnzFJesP1JCCpLDsry8k2ev1/7gdSGlGVRadcVE2aqNqrmPRFrLFKMTJSWB0FwxIVSxWvi0ilwJJE/evJD0oTO+YKoOUr7KLCKkQIpQmrHaKsRbk0U4YaJxdhd/tY7TmzzChC+0Fl+yvMkxQb+2nKErKk3FLI3j4YbNv869hoz0VVp/AbU+SzEfMenLxJs5zM5+2B+U+fvwVk/ppU7G+Bl780nyeQKYOYTR6Yjaf8/2SLi69G1HjEKZNqpVIKEQoj13I1uipCOAprjWcYDcd4RwyIAJGJ0QULuy4g6jTeFyQ43eY7uTA8YLPB69isup3XVmyGX3AQUiPXpLALhlHQlvFueB2CsNqACRkAwng9yolhQMJKmHQwBEa6hUngQhsmJXaNvFY5OpGRGV+IFhDUaqykvFO5BtBo24AP6Rvjf5TWhpGyoHFoB+tX12J32sRZ85rTayyijEYPzxPmXOw24xn1OoyhP84qtGO+0+0OE+UfZ2OchpJ5fLtDnFLUbdZJV3cG24kJ8i5OOiTMO2Q+dJEBBHVm+832GcZFOYl/p7ztrkYWJTKGeGCJLQe1sKKzjlLRNWoFJcxPzsZbZ7pz4rRhYURTCd2aItUiQUBhWMDoIe/x0P4zN/0/Sab8/2SnM07k0gc60AsO5MGZewJw1I2XoBccSM1Vl9N9yWUcOzrFY9+eWHnuxMwhjBl5Ib/yRwCwT8+7leccO9r4qsqxx2U/yomZxwAYf+5VTIq2oO8tJgq5Y9quACwfXeSyRw5lYuYQJo7fhQNOOILmhyVq5OMbRSi/NtIEATz33D5MOX9PphYeqyR3vTZyRw64ffVGkrF0ZxsAj83/Ll+5/AF+MOI4fn3H/2PU+FMZ2XAOD1y6LQ+rbdnurIDm917htZE7srmVZe+RS7j1nG2YfdVsHjm7XyWl65R3Dvxf+3LvkUvQi18GwEndBMDY4VdV7r9lXD1vT/oq3z/kAQY8PJnNdja9MF+ddAGzvlPCHnwDt89tqgQNjPXG8O59e1Se/4OVmtcnvMrzCWt15dFdAOw/f28ANreyNL/3Cn0XPll5zjmXf43dDn6OccPHcXLO+GlGNpzDFWsOrzxm+oxL2K/5EY5xjIzt3aOmMO2K8/h5n9M/Hw/M7rvvzmWXXcY999xTSaQoFotcfvnllYzwL+0ohbCt3lSrjU7apWEyHAfVUE1xQDXKSfpMJDi5COnHyFyACJN4ZKXMiTKYhLIoNkxOGZxEESKdNib9suysDBjAnJiXE8YApDJMA5hUMTDPTf7W5eVsOOVAgcqfCbjakL0pm/2TEUIYzLCBXE77vmGNyiMFOpeHQgHZncMrg7Ty6yh7ejbEx3GMcMwygsGNhNUOMjRenlSrb4IB8qbQU1sSOx+hpTAaZE8QuwJdaxPU2ji1KZwOI2errENphF0uvbQSw3/v38KR4DjGU5T20JZVibEWQVgBoLKrgKc1of4EQLhpNs3fOX+vl+XvBS8bPvfvBTJ/zrRsWGq5iYn566Ol8avIUCSAQIIyJ8kIjeyxKylfUV1kIoB9iQgFKIEONF6fIplUQGe7h5NIv/wGwyRsvflqlrb2YfnC/njrJK5rzPimt0Sbx8tepgFl2KA4bdiGijdGGzmVtkElRZMaTLSxEsiCQNvG4+KEvSf7UVYT1ShkUVb8MHFaG4CkkmSydEzkC5zIGOFVUg4psxEF30HmLRNhHJpenKBGowaW+MYWi1hdqGVFcy3dPRlydS6Zpjx12SKN6QLtxQyrnHrQAtFjE3Z5WN02MoSoMSaIbHYcshKlJaXYpsrxWZOvYf2aZjw/CU+oSXrDYqvSySMjQaSNrI7IgLNgqI/rRVQ5Pv1qevi42IgKJfSYY5nTWCL0zbFCpRU4CnwLOxCJT0aTWuGyvin7r/4IfilmeP1pkPAYj5zdj/tr9mZK+55MBE7Yeg08dBpHnP0u3Sdc1vuk6W8BsOW087nz27+h+b0m2OlOnuYh7nuzxHE1R/F09xwApk4fwzaXTyI78sLKyb89+AY6pvUu7pGz+/H2pK/SvGgBI8e0suM1h3PgRaM4/Cdp6ldq9p0wmUm/bKH66D+Q/1k9g4b/nJnJc8vg5fkf/wq4EG4fb8oqWUcNt7PN5ZMY2XAOQ9cso2XrPbjrvVdY/dQySk/fyaL2mxk1/lSmnA+THmhh/52geMyF8D+38vtFw3kX41c5qnEEN94/mQu+cQIj5GIA+s/Y2FMlRhhLR7lc4lf+7Mp921x+CmO9MaTAsB5/PAt78A3MOe+qCgg4dUwrL3XuAkBYOoGm425iyNcv5IJvnMDsq2Yz+YbrYD8TDnCdXMjiM0aww7R32ObySbx73x68e9QesHAys9Zey9GpV4FWTtqnnR3OvJDsXRfSKp+i+ta7wWAV/rAqz9e+M4ljnKn4rSfgNc1kuzmT0bM/fdz4ZwYwN910E9/4xjcYNGgQO+5oDl4LFiwglUrx29/+9rMu7gs1wrGTq/Ea5AZX7l0HaqsJm2soNrsEWZlcfTIn39oCv9ZCWQLbz+B2mY+Qk4uSxnrLAJwwRkQKYo12zIl1lHEQWhO7EhlqrGKE3VlA5Iom5CSKwLUTmdoGG7uhvKycRmbbBiCVje5KoxPmqAJWXKeSsiZsu8L4iLJ/J2EuRJnBiA3oEulUbxpYJY54A4BTTk9LGB8hBDoITMDBhjI32yZuqsXv4yIDTZSWWIFGuRbaFpA3CWXCD0EKvA6fOGXj5AFtCjJjT+DX24Q1WbJhjGxTJpTAdRIQKHvlYRJEOo1Oe4R9qglrDKujpQGVxoSpcXpivHYf2V0EpZCFgNQmE/+m+TfPPwJe/nw5nwbE/C1AUr6/DGSCCxfgXLndP7x9/4mjHY1dkAY8CG0igOtiRCywe0xUcVSj0JZCpGJ00cbKS8OCpDQEEstShLGFtjRhlUbEENfE1DX3MLKmlWXt9YR1IUHsoFKGKUGDVZBGukYS+6swTfIJmyFiKJc0WiZEybA/lpGTIU0xpZYKGZgkLmNWT7wtrvGNBA2KuDaCbotK6osw4EiGJkZa25qoKgFF2kjadN6ikHFIt0uTMFYQODkDjgKZ4qlgO9yqwJR0KgGWptCZplRwWaPrEOtd7MAw9wDKN+DFKgmsdIQQmvZSlnU9WQpdaZxWh9jTSAd6RkSIdAQlC1mwsHwDrtwgAXUWuF2iElZgexGhbxPENiNq1tHje3Tl0/idLtSG7DBoFe+5zXhORL/qHtqLGVqWNxjpmJd4gGzNR+/3/1d+/L40s6TjNlOGeAIcPmYtXALv3rcH/ocT+aC7lcdqduTGYTczdTqc96FhUWYNzDJ2EUx8fRc+uirPgpkPcVzNUcBR3Ns9h922nsr0XxiGJXWAiSXmY/j+IQ8w5M00y0cXGfJmurINh/9kLQsuvoADTjB/j/XG8Py1Rt7E3IOBg2EnYBHUyL70nzGJKeefAhiGp/m9V9j3x98DoHvf73Hl0V20vLMHFx69hEtn17LlYU18f/QbfPjBrtzywMnAxn0vqQNOhl9O4Zn5J7P/j+/kwIv24uUDR9P93jqemX8yN95vHj+230U8faphou7ueYbb5zZx4EXL2OPjOm6+7GW2O/YV3r1vD0bP3JbS03cyy59rmu/dmfzpsqvZ5dWPAANiJieJZNnTO8j/rB6Ao5PtUY3XAhB/EDLl6T0Z2WBuf+65fcie3sHiM0aw3ZzJMOdx3qWXtdnuWNNFI+seZsYPv80OZ37MxPG7MHX6ddx8w7ucMXg2ewPfPuNuAMas9Zk16FpmX7WQRe03M8ufS/qd3zLoxU/32fnMAGa77bZj8eLF3Hfffbz/vomUGzduHMceeyzpdPpvPPsLPklho4nh7S2K1A21dG3XQJgR2CWNU9SIWGMXVBIZLFCOIEpBqUHiVjkG4PgOQmmijMAq2VgJ26CT6MbYNXIrLYXRLKdBSw8nl6XxTz7esnZE0e9lVjZkN7ToTe/SSZRw2eQP5iTeIgEiAiGSBvoN45FlYtAvxzRvGE6gtCF+XKc3yrk8QvSCKrnBVQCle9kcu+yzCY1ky3FAa1R9FcX+WbQU2IUIy1dmX+YC4pRNnLLBs7C7S8hcgKpyDSsDRFUOyhbIQGOVFMqRFDavIesHiB4TXFABL1qb9aY84j415DarQtkiKSHTODllYjW1ATB+nU2xj41TzJBeW8Jen8Nan/tcP27/aXPA0f+7GOyvzdOz/74SzU9az9+7rC/y/LPAy6edz8KmuNftWAEx4aXvfl6b9KWesDbGKsud8sY/EtVhksHAMCW2AkejfQsRJ63u7YJiX5AlQXFlNXZTEeyE7SgJiAU9+RRvrhvCiD7r6axOs8qtg8BCOoq4aBE5xp8hcrYpV0y6aKzAHGfsUhIXbJkkMjQ4OSot8mHWyL/irCbOKLS0sEvCxBEnJZUyAG+9RVhtel/spHtFp43vMa6OIemC0YCTM0Ah7BMjihJZkFjF5EJSGaApQIHVYRPmDEOlPY2sCRCWJs4Z1kalFSK2IDaAK66NjezOUxBJci1VFKo8dCQRPTZ2j0CEEG1WYviA9URKsqqtlriQIaxSRj7miEq0tIxMjLQMIVqVQYaCZTX19IQetlQ4TkQpHYMSLG7rm9TBSaocH1sqWv0+xNUxsa1R7Q5WAF6r9Qmfkk0DBgS8/cC2MOYqjun+PfB45b4L9l1D+9XmJPnxs3slSPOm305NwXzvH3DCEdw7cw7H1RzF1OlvUU01pafvZLdpu3PXIMHomdty82UvM3rmtiwfba7wP/STN9nu2FdIHXAyy5+9jiMZw6ljWlnUfrPxpuxr5FLl2yrzPKw5V/P7M+aaAsl91zFym8Uct10TK9f7PL+2i3vmH8XYzCE8n8Qqf/CbVg68aBk/OeI25vTsyXnHXMLV3+8tzVz+7HXceP9knrp2KAdetMz8+9SbtDy2B/vzCt/bXXLpjEt5a9GVHGKyIRg9s8gzN57MecfAjfdPRi76FqlXt+VdfxxvH7MtR3Y8wtjxpzIw4Yq2uXwSJRKwBIztZ/bpEWePhquMbK88z7Uczpi1PtOm/9K85LVdPNTvImatvZbDpr3Dvd1zWPfeQVx5dBezlpjnTfzhGKZOf4sp5+/JD1Zqsne1MncRTJ3+FrP8uezQ/Rp8H07MPFaRo5UjnA0DNpeP4jzbfIbPzd/dA/OfNJUemIbvY5PIpCyJ8Dx0TZbCsDpKdRZCQ3p9hLIEYbWFk48Jqi2ilEBGmtgVBNXmaldmnUKGyRWw2FwZK9VbyFAbg7htrnzZviZ2odAszZUwbcyJdgH6LijhfbTe+GsSr4yOIjbqhtnQ21GWbCmdMEl/VohZfnwZ5GwgGzMbKioxzRtJwCrJaGJjr07ZEF9Zvt5oW8rSNa01wnXR1RkKQ2vRlsDtCRGBQtsmtljECuHHRHWmpED6MVYhRDuWuVCoIU7ZKEciQ7PdUdamVG9RtdrHXdpaAVk6DI00z7GJ+tbQPTxrTLI9cSLlSOK/fYW2BcqRxK7EChSlepsoLahbXIQ163hu6U2bNMvJ/DUPzGcFL//s+U8DMJ8XePlLLMzfKwXbUFK26f+JmfL/k80vuwrd4KFFItGSJCfeAqddEmc0cV1kovITAGP1SJy8oDg0QPgW2WUWfoOJ8w1rFXbeGP6jTMLGNIYQSNx1NlZRUOoXI0KB1y4pNcd46yzDtkhzoh9lNHbRAKXYM78jML6NOEkIs43R3SoZU7rs46MiCV2OkVZhHidU+XkGACEhTpueFqRGSA3dDnZeIgMqACWuiZF5C6db4nVClIKwRhOnNcpTJgEsMj0uspQwSRq0q7E7k3AcJ1mvStbbFFBbn6cuU6Slqxp/RRVuh8TvEyN9SWq9CRUo9YsQSuB0SoLGGOFL4zlyFe4qhzhl3itlg5M3r1U5GukLSv0i7LoAIRVRYCPaXZPY5imq++Zors6xS8MKlub6MO+dYSZOOTZsl9Mj8L0iH1+6qVesPOX/J6nlH/HoVV9jYuYQnp8/hcaXPU7OmRPba75xMM0PS96e9FW2mzOZ0TO3BeCXj40zrEdiJG+VnTSpOkY2nMPRlxzNlPP3pHqWiU/+YMIN6MUv87OfnMx++70AwNMzH8L5qMDYHY8H4N7uORxwwhGcOqaVxx6+g+rjb2bAslMq2/r8/Ck899w+zL5qNovab2b10Dv44DcmLa3m+b70O/MVFv1pBPvuNHmjbbl9bq/Z/d379sBvPYEH6w8HQLYtZsr5e1YenzrgZJ66dij77jSZ1UPvAGDAslNolZ2suOF/+NpTbwJw2SOHAtAz+ysVEFQGJW/tvjkA1pgr+ONXn6Sz2kjCtvyD8bx88JWzPvG9WH6HzwmbD2V17cbMUPPDEmeXO/j5NvtwzlDNQHdm5b7n50+h+WFJnyvPAGBu8a1KkMDc4lvcsf1TAJVunA++chbPpBu55p7BzPvmL/hR/0cAKt00x3T/nt9M2J58oPj23Ws/1f+TTyXyf/TRRwmTzpJHH330r/58qUfFFZO3ife1iBqy2IWYVEeM5Ru2RMYaJx9XOl9kaG53ChqvU29ApZveExFBan1AqjPG61Jk14TYpeRx2hw40q2aTKsBPak2jVXS9AzyUDWmV0eHYa9P5c8jgSHpgtkAkIRBwtaoXmlYmXnRulceJkXvjyrfrjYGPrBB90rcGzRQlplVlil6gRRUIpJFJo1qqKaweS2lRos4JYg9i7DWpdTHJcrahDUuQWPK7N/AyL+Ua+qdRUI4yTDG6QkI6hwK/T06RjjErqDQ5KJrsuC5SZqaYXui5lpym2XxumK8rhgZaaSvkLFGuRIZxti5EBGZcACrEGGXFFEK1u+Qprh5wz/2edo0/7L5dwOof+Z8nszLJy37H/GxbPLA/OXR0pzoy0CgGkNz8aQkSTXnCfpFWIMKNPfvxM2EeA1FtBcT1cSE1ebYUDe4k/yQmCijCOtVEq1vjPAqpVB9QogkMhNh5wVuD9g5idNjwIt2TLJYcVBEcfMARuSNjC2r8Zsi4qxChhhmImNYCC1J5F8GvOhsTE1Vkf5NnchGH52OkX1LRFWKsE4R18ZoS1fYbANkNIQG8IhQ4HYYf4uqD5GDCpBI22JPJ8b5ZH9ZGqsmJNW3iGwMjKwuASp2TuK1WthFgdstcHpMJLXlJyCmx6boO6ztrCEKLQPQUhqdjYmrY4Q2Hh0Ap9300mArsDVWXmK12zgJKNMWqIwiSiWxyJbx+4hQEhVswrzLgKZOtNRYDb6R7AlNVylFPvJIWRFWXZDI0QxIjFOaOL0p1fKT5pUr9uPyw82548W/fYI+19by8K0nkr1rT04d08o2l5vCynePmsIvHzPpYN8/5AEGLft5xVQOJkVsQ6bk0a0m8OhWE7jp2VewL3wgYXZgQNcUvn/4n9j3x99jl1c/qpj7y2zAId82wKUMIv502dU0Pyy5aeCBHHmCSdsqz3PP7cPDaluO266JbXc5i5EN5zD9h2NolZ0AHHjRMv502dWAMbWPu3Ihc867iteuvp5Xbv/NRvvhqUSyljrgZIZt+Qa3nrMNk37ZwsK3btnoMXcPeoavLlrAjfdPZmTDOZV9cNkjh2KNuYKWbytOP/lsPorzbPmHW6jreYsrj+5i350mM3uzq1h+h1/52fIPt7DszDHoBQfyy0d6uY/mh2UFeP18m3347z+9wC0TTAzy8/OncJvbyZVHd/GrzX8AwEM2dFbvwnPP7cPp1Y28/cC27Hbwc+x28HM0vuxxy3/1+pcuPt70/Jy4cn+OvuRotjsrYMr5e9LybcXmVpb7Bmy8X/7afCoJ2eGHH87atWtpamri8MMP/4uPE0IQbxA//KUcIYy5PuWhXYeg1sHpiXB6IoSyE+M+iEijXcO8KEvgFAz4cPIgI0mYEQiV9J9EEiuwsXMxYY2Nci2cvEZoRexK3Jwyy1UaJ28y6oWCMCPQnlNJCjNRyMLEL+tEiyat3m/muNf3saF53QCzJJxAGg+LjpWRh1mWYS6kBaG/cVx0BZRg7i+Xa6J7o4g3NObECViy7UrcsrBttG0RNGYoNtpYvjl49QxysHydpI+Z/QggI4UMYpQjK+9HnLJNuWQpNPICXxFUm3QX29eEWUlhs1qyfyr1Fn1mUhSbUybVrKSIMpYBR6E2arlYI0IjO3B6AuKMjfIMQ5bq1JTqBblBn1lhuWk2zT80/2rZ2D9jnCu32yQj+4Sxiqa/S1XH0OVg9wi0A8WuFHabTViStMUS1wtx7ZigmAEJUUOIsBUjG9exNuWzbFUj7iqXoDkirNXYOQu3T5G+NTlWrmmgX98uVg9xEIHE7ZSGFcjEiLyFcsFtKKE19K/vZvnaDKl1ErREeSb1DAFeu4WyDKAIaxTa0WhH4bQ6dBbqEJt1sEXzevINLl3FFLmsTbbeSHEKxSrsQmKCDyVR5Bg2KdjAf2OByNmEJQuvtTe8QAsqsmpZksQFG9uJiHO2MehrUJkYt8Mx4QAkYQO2iXC2i9A1UkFNSFBy0JGEUGBrww7Z6Yi45OHXGVkbAuKMkbxVNRbIra3Czku0SEIXGiJEURqpnGOkfso2nhhtA1022oJVyxsRWuC4EbI1TVepFu0pXlWCou8Sd7sGbHUlHT/VJpp60/zv2eNHz/HONQfQ/N4rjBy/GDGi977n13YBJ7Dg4l0qt5Wm38ni32wGGNAxEXPfDjW3cvhP1jL7qnMY2WDAUHkOZRTwGBf/Fo5nZwBOndbKjvuZ760DTjiCAy9axnlJkll9P+PRuNX9PuMazmFR+82cXWrh6uk9wJ486m7HlUd3sfTqI3jsigvpd/bJ7Fo/EjS8/sR+jB2+H3ucehhTzt8Tdr+aVtnJHqcexr1XH0HLqMPw582iZdRhtC7pZM+6HwHw/f3K4Osw9vi4jnuvPgLOhx1W70H64TZ49SOaH5ZAP05cuT1D3nwGMPK7GS/sQp2VZcerjuNAlvHLx8YxYfAPuHtQK1esgaVthjn56qQLKn6aHfd7l+qzd2Tq9EMq+2nqTiYcofaSExjav4nFu9zBfwOZA/+Ls6bBQPctap7vyxtf+S6zllzCVzFpZ7OBlet9Hunux6VcymtXX8/RPzXSstmlm5l91WzeqTLr8MUsRsd53ux/ON8565lKzPPTMx9i6vQxHBzf+ak/O5+KgVFK0dTUVPn9L/186cELVLwTWBaqKk3sScIqm7DGJkonSSOuIMpYOD0RmdUlqpeVyKzxSa3zcTtDvC6F5Wu8bkW6TSGUJtffodDPIcwIig0ykZGZzhPlGAq+VGchY3CKhiWQceKXoRx9rHpZEyF7WZJy14xWvWDEtiuMiEilENk0IpM2oMVxzN9VWUTZnxJF5j5I2Jw/i3NW8cYMTxQZ43z5cWW2p/wcbRLYdCaFqsvi15vIyygl8KtlxUvk9sQox7AuQgOxJk7ZJrUteXlBnWNkXmmHoG+aoMYwSal2IzeIXegZZCKQsSxwHOL6LNoSeO2BkaMVYyPp0xBUS0ScpO045uAVJ//KSGOXFF6nkVBsmr89/0nsx79z/h3gZROD8jlOkgamXQMGkMZknlrmmhjllML1QjwnItYC7SrS/XLsutVHbDHI9C44Vky2toSIBdnGgmEnQvBbM6xuq0W0O7QuaAZbIxp9I/kKBE6LgwwEcVrRUJMnDi1qvBKiwac4JDRFlol8zJylQ1iv8AcFWP0L9Nm8HavbXMCRvqB7YSMfrWugs5CmkPNI1fgMqe8g8G1ELAjrYmKPSkGmjM33cjnlTNkGzFiJnMztAq8dRGzSzcrX4NCglEBmI8OsKMDSlIYEKI9K670MBHberMPtlOi8TW1tAenGyExE3OyjGwOUEohQJKDHgKRyKaYQGrfNQvqCoG9MuH0ep9o3sdG2Rjf7pId1Y+eNd9LbrIc4a6Kw7Q4Tm1zsShH0ibH7lpDZCK0FpYKLu94iziiijKbUV2NvslP+xXnliv1YcPEFtGy9B8dt18SAZadwdufp3DKunn371Vau/APseM31TBy/C794oYFfvGAUEmLHpxA7PkXU5OCLWZWftdcu3ejnG692sOC57So/y0cXWXvtUhY8tx0HXrQMMLKuuf28yvqOmHIpi9pvZmhjE4veeJOphcdYFRin/x6nHsYbHYuwW4066ZjjB+GLWZzyzoGsXO9zTPfvmeXP5d7uOQz5+oVsd5ZB4KWn76Rl1GEADPn6hZV1eXps5fdyPPRDk69kwgBz+1u7b86Bt8xgm8sncfnhj7Ko/WaWjy7SWb0Le0+8lR/1f4QZL1xH87zfVJ7ji1l8/5AHABja2MR9529fkaCNWetz2+AfsHroHaweegeTb3ip8nPLhHdY1tZK5sD/InPgf5nX2/8pJt/wEg+rbTl3nwt5yDZFmHMXXccrm3VWtn3Lm8z5wGlBHcvOHMOU8/fkxJX7s6j9Zs7LXQHAbYN/wDvWmYxJ78Isfy4TxxsQOnH8Lqy+YNSn/ux85kvM99xzD9/97nfxPG+j24MgYNasWRx//PGfdZFfnNlQNmVJVMYxdHqsUdJ8icWWoFQnjUa2R2CVTGO88mykH6EdCycnELFJ1RKRJspIhDbmcRlpRGx8H1FKoDPm93IrsLLBrzaJLkJpRKh6yxZtC616r+JUyikVScyzkxj7E8O/JVF1Vfh9MgQ1NlHKHLAizyTKaMucsKc6YjIfrDeBAUFojiZlD40QoJM44g0TyIREuO4G+8vq3YfSQniuWX9thsLANH6NxPY1kWekdrFrjpxRShJUGUBnlTTSFji5iDhlPEdamr9FZICgloI4AXzlBuh0u8KvkWjPRgoBlqTUlDZX1WyBlQ8RsUZFFkGdjV8rcXskccZF+mbHy1hXIrGDast0IsT/5+1h/2fm6h+f8Rfvm/TjWz/39X8ZmZdN89dHOxrKJ80YX4edgzid9Ke02RTiLMVAGB+GFhRzHkvdRhoyRdpKWdoLaaJIohxtTsaFSexSjiSyXDLrJV67plhw8PsaBkY5mrDB+DtELGhtq4F1Hv4AG7kmhZDa+C2TBLIwa7pdZINP3OUS2TZunZFekZPEGYWVt9CrMkSD8wzp106sJJtVtbPcqycamGdY3zY+WNmMXJNCS8NwAMTaSL201cvGKNf8iJjKccjpESZUwLHQVRLlW4jQHDe1L3EaSijbSXrGwO0BK9T4DSYSGUtTlynSuaoGEUp0NoIo8c94ClmyklJNUH1CdCSIIqvSgYOriNpTeE0FVN4ce5z6IrXpEq2i1ijjpAbLXFgUkYlcFj0O4bASYd5BlCw6fAvZYxNVGeAKgIJSH82grday/F/9IfwSzGX9jmL3XyxgUdP+zF10HauH3sGkczVH2I2cl1vEs8HLjNx1NCfW78a8b8JJ+7RvvID63QBI1/+UV6t6JWVrztUcMeVSBl+xnBU/GsLMF9v51tjDGeFeyv33rATglTUHsu+b6UoD/b3zjuC0FQYglJ6+k3nTb+eIKZcCcEWfBTjP3MFz37kJgNPPvpMX9Qm8vfkPeK7lcETzI7TcP5kFxw+CmfCj9Tvyo/6/hZkw/oSX4DGYtnoWP+r/CEdu+xIPztyT5aOLHHXjJSx6403efuC3tIw6jPOOmYJecBvTF47iiCnw1FnncuAtM3jqrHMrr6153m/wGs7hkd37cfd+B7LNhEmc53Zy7j4XMuTNNL4wDM/LB47miGSXbNF4AkvbZvLMTr9nj4/h/nkrOfaGd9j1jYFc0WcBr9zesdFuHTNyP5a2zeSps87l/pq9uffqI9jurIC3H9iWC9pOYOU3YO/u17i3ew6vP1HH/iv35hHeYdEbb7J01kyGNjZx9kOnsXvjZCYmJaCnBXVMPH4Q0xeO4lsjvsEVN5rgr/L78dRZ51J94Vuf+rPzmQHMiSeeyDe/+c0KI1Oenp4eTjzxxC83gLFtw15ABcxo0XtCaxdN2Ra1Em0JoioLy1fI5LHKtRGxkUC5QUxU5aAFpNpCUu2YlvlSRDpSKM8Y0oM68xaUv5ijlMAumhP8qpYIqytvoomFqBRBlo37WscbmfKFECY22bbR1RlKg2rINzuEWbCC3pdZ6mMOpFZoOPVcP5tC337ULPPxFrdUiiErIxI5WjnvYcPAgPK+KoObsp9Ga7TroKVAWebAFWbNdqY6TBCCFSiTDCbBLihkoFCeRLmSoMbGciVOzgCMoN5NQA+GpcrHBFVW79W0GPPaHQftOgaopQWxIyFl9nFYbVcisJUjCKtMZIO2TV+CShtWy+uI8BtsZLAJwHxZ5u818f814LLhY/4VIGbT/GeNnRMIzIm5ysaEynzXhHXmOOKttwjrTMyw3WXKHEWbS2dHAx11IXTb6GxMtr5Ivm+EKzUN2QKrt3Fw3AhXKnQfQc+H1aBMCpiRH5vYYZ2JDSkeWIiGkCWr+5JZb5h/k7ZlgENYr7DykrjTRVabq8mrVjfg1PpEaQvR6Zp+k+TaWc73sK2Y9X4Wv+SQyfhIodl2yBrW9cmyrr0GoSFbVaJndTVCWVgFgZ0z0cR2sfx9nfhNXBIPTZIU1u3itFuE/QO8qoBweRa1IotI4pu1BKukCaoFxS18rDYHtCCILayiRKU0omRh9ySFoVbSvYO54CXdGJlSRJEkbIxIbZMjFdqE7Vmi0AKhiaoV0foMXZYi7BcguxzC0OpNVbPMuYGbE/g5B2yF9lSyXkHQGJvbHIuwLkZkIpoym2iYvzQPdvWqd36/aDh3/Owpdjv4OU6b3srU6xTz3niTibzJDn0W8DZfrRjEwcijTltxF7cN/gHkJrNFo2FI+FnygJvg1YTRePVxWHPuqSw+w/z99gPvcMLmQ5n5UQtnHmMAzVPTzmWXVz9iaGMTq2cItvDMif8ur37Et57+Kdz5NVZOfZc9rn6KvdbM5LFTbmK/5keYc95VzHjhCqbOG0n58n7Tldcy+9p7WDznAx7gen7U/xEWtd/M4uAJ4LcJWDmQkTvCSC5hh3EL2eGj19jl1Y94+cDRZiGTr+SpzjbenvRVFlx8AQ/OHMvyUUXGb/sS/i0r6dBjuc01++OXj42rmONLT/9vKVZl3yS/DznlEna4Mc0cbxJzMT6i8tzy8z0YDJxyxXnMvnQ205L0t/vO357jMF0099fszSsPGM/KvAslZz3QwchJo7nio3MBcHbJ8NRbp3DgLTMAw1IBjN92HmdNm80bA56iZdRhNM/7DS2jDmOXVz9Klvzp5jMDmHLz+5/PypUrv/wt3UKYGGBtTshlkHSkqLKxUWMVIqrWQrHBRlmCUl8Xr92ULVqlmDjloIVhOpRjDIaxZzpehNZEGRvLV8SeAUHlpDJlQVBjfB0yNN4Ob32RcrmiiUIWlf2v0RUZmbBts822jUiStzq2qTLa3ZzGbtNoS6Ass1y7mOTnJx6XcqxzbqBLUDOQqkUd0N4F5TLPsk/mz9/3sr+mnESW+GSElKbVPuPh90kZr0taY/dAan2IXTCgpLwvvA4DfJRr0sCKDTZ2SRlMZAliVxJmTVx1qjMmtdYn9ix0rWWAZArskkYoBbYFjk3sCdwek3JW6muSxcK0KcR08qZ/xumJCatNkhnCHFSrVvuIUOH0JPt40/zHzqcBLxs+9vMCMZvYl//MMV5JA2Ti2BjLwyptJE2OiQ22uyycHhPXW/AEbqdJJ4u6HJAaq90hHxlAkm/JIvpptui3DseK8WObVR21xCmVRDJr4uoQ1nnY7TZxWmH18VEtKXR9SE1Nkc5hDl6LjZMTBNWmdV7bJjoYCXuPWEKHn2HBh4MQUqMLNl6nNIZ7T2PbiirPZ3lLA1FsobUgVpLOUprvDp7HM+u3Zu3qekZuthY/tslVpdE5qwJWrFIveJEBJkFMGbZKBgKnR+B12MgILN8jyrq4Pb2gQURgR4a9D2ph2OB1fGw30rchh2vFiP4lUm5EaW3WrMM3Hs6oXwB529g3l6aJkk6d6uFdDG9Yzx8XD8WOBPLDNFZRoIbkCQouTdU5cm0ZrKIgDGxEJiIuGaBo5837JiLjbRowqI01S/sCkF5jUxzmE3saqzqkb0M3GRn85Q/L/+F55pTTKQ3ZnFHjTzUG+bNMw/sz/J7UAaPoOaYFLjQJXL+fegZzzivygH0T4576IWBYjTt2+j3Li4ojumdAy408sdtJG61jGG9UTpIHjL+TsRiz/FIRsKU7k6v/q5k9Gp/i2BvegfvNc6Zeei2752BpbiZ/Pq/c/hu2aISnzqrn7syBnMhTDOrjcWj1bAYsO4WJ419icQCzr72n8pxxw5/ggSUHM9Ybw8hdRzOSS5h66bV4C7vh/lGcd8wU3n5gW7bxJsEBJ3PElEsrrMuBt8ygs3oXhv50Lo9MPIpiXSNvdbZxIDMqsdKd1bsk0rFZTFs9ixG3Lq6wR7uOvRu4u7ItX7/TlF5OrR7JaZ0vMrTREBLfH2XkZv57NbwZjOSNCd9l2Zlj2PGawyvPXdbWyr1XH8Fxk0zowW4HP8frT+xn9stmnTx431b0f+U6fvv4g9xx4VMsvWVGBTi93mtL4p5oby4fZZiulgNOZsYL1wFw+9R9+PmntMF8agCz8847I5KT6P322w97gwSsOI756KOP+OY3v/lpF/fFHKUM+yAFRDEyVwIyFc+EqzQyiEm1xridFn69S88giyjlkmqPjawpVgg0sdeb+a5ciYxiopRFWGXil8OMREtBlE4o8bwi1W78MF53TGZVEWt9d68xPzHei1TKyLzAdL9syL5kUpSG1NE1zCWsEngd5iqVCRYAL6+w83FF2qZtQanenOx73TGRJ8n3syg09aHPHz2sVeuNz2XDVLFylwyYtJkNo5YtzPY6GPN91jXAQGu8LrNuy49NiWdsQIuIYqSQRI5MJA0KyzUAS8QG/Pl15sDjdRmhtHIkIklvi6qNNAGtTUkooG0jS7MCjV8jiD0DQoU2V+DAACnlCLRt3oOwSpBpUQZ8WtLso3ATgPkyzGdlXz4LcPnz521iYjbNp52wRmNbxnQuYkHUJ4RQ4qy3CBoUylN47RZ2EfwGjdchsUsmvjc/SCMCaUBMzoAfp0fgd9Ty0eYOKjFH6rUpbN8cQ5QNcSDxBuUpdXnInE2Uc3AHFKivLhDG0sQGWybZy+028isrJ7F802j/7vr+dHRnIJLEKzN4OWlKNQFVHSGlon+mm9Z0FUpDv8Yu9um3GF/ZDPNacOUI+g3ooNotsWxNf3TJSi4AmlJHoRM5WUQS7QzKS9QOdmLmLxqWxYADk7qWWm/6a4SGsFrTtXWJIc3tDKtuo6OQpiuXpj3OEne6RMI1WTzVsSnNtDVWi4sYUiBeYyQr0jcy6kLBoyObQVgaK4DUekGhn6Y249OlBK09VRCZC3RydQqUMfrLvDm+xynIDMhRlymyurUO4ZvXF2U0lCzcDknJc+jy0qzPVP2LP4Ffjom2cEh3tjFr0ld5u3Fb7rj6ehr234els2ZSWtTKDuMWMiQ54QbQvzqUfjVn03DoPgDM2R8esG/iK7+q4027kVerprD7vEYA+l20BQBrr13KaSvuYmJbK7e5nQCcmyyvHEHcAtx4v/GmlJ6+k6GFezfazvHbzuOoISv5+gTjf3n/wy5gAfs1P8Lsq68H4HveYr76ywu4mrcYM/IFbrn8guTZFwHwNtvC90EvOBCxo2FNyizMhreVpywde+qsc5k49QymVo/krAc64GdLWHrLDB6afCXTzuhNPVjWZqKdP4rzXPizJZXb2585YaPlnhZcV0lZY/Bk+l20BQue264SasB+MKRwKXdftAVrr13Khk7JWf5cJjDWBBRgpGblefnA0UxdMog3Zp3Iz3aZghXyiTP69YD/t+f0jfZ/R+eL1NftxTsvbP3JT/qE+dQAppw+Nn/+fL7xjW9QVdX7n9F1XTbbbDOOPPLIT73iL+QkJ6+ViOEoJtUWkR/gEFYJ/MCueCViTxJUS+K0IJ8V+DUGKAilcfMKGWjT+WKZL7Swylzljx2I6yysMJFwCcO+aAFeV4yTj7A7S8juAvhBr7fEsiBOyigBZMLGWBYkZnl/UC1dw1xkCE5O070FZNYKnJwmtT7EKkWmNExLonQvwLJLZlvxTH9NqVbSNbKK+p6SYWI2jE5O1k2c+GJsC6OrS072kwAEnfYoNqeIXYEVaJyeCKsUJWWVMvECaeKUZfTcWYldVIRZo3tGk7RCW5TqTZKLssEpGrmdcqXxJtkGXAptJHxWAUSkkJE2HhgLMutiopQkN0hi53VvjHKgKNUYGZpd0Ni+uR1lGJpYfqqMi//z8/TsAf82I/+/Crxs+Px/Joj5d7Ivmwz8n+9o23SIRBkFFlQ35ulZXW0ks3UBthNTstOg7ASAaGRoUi5VWoHUONUBWgv0qrTxiuQExXUpI+eqCfE6TSSw3z/EabdJr5Wojmpcy/SquLU+KS+kp+gRLK0hu15UvhfBeGDijEI3m5jnEfXreK19cwiNtDfVBj2ba6z+BSi4pJyIQFkcO+JNGuwcr3cPw1c2tXaRF7q3ZuHa/oSBTUdPhvjjKqSjkYG5cBTXRSjXMtHHQKpVVMz7YbVGhuC1C7NNqUQgoEyEcZwysje7YJ7jLkmzcuUAlvVvxElFxMuzyBBwQDX5Zv/4FnFjiJWK0KtTZj+6Gp2AjKAupk9NgRXr6tEqua3GAKoolkStaSIJVn1AXJCk1kn8Bk1V3zz5sJrYFUQZRbwuQ9VgH2uth9shKA6IqRvaSb7oUSKFiASlNVk+rN0Uy/9J88yZ53AQd/LuLS6LznuTuT+9DhYdzNBGGDPyQsYugtQ+5iS3fJX+/V/9lBFHXVpZxpnBlRy1Os244U9gHd7JU3XnUnvJBzAeCk/9ju4Pr2TZ+FM3Wu+MF65j5U/+d3rilPP3rDASD02+ssJivPJ0HQ+rbVmJeU77My/AOJJUr87eBVx9PWOSX19LgA3A3EXXIQafDytu4OyHTmPY/W8w8ZiL0AsOBEwYwdRLr4UVN/DLx8bx/UMewH+vhmKdAWNM+C4tow7j2GMu4MiORzhiyqUcMeVS9q6awu8XDWfZmWMYes9KlrW1csDtqzliyszKa3hYbcuU8/dkzEgTGiAGn8/3vCRAwIOl187kW2Mn8/VLDVA8vflK3n/ojzy0YhK3Df4Be4mZ/HC86WuZOHwlR0yhsqylbTPZovEEjroxzYM3LuKNWfdyzPGDeP2JXjP+VyddUPn95evG8T/D34W1sEc4iueL5ktg0pYvcOShYxj91Dd5/X+9K588nxrAXHaZyXHebLPN+O53v0sqlfq0T/1STUWOBYggxOkJsHzDAPi1Ertk4+QiZKzxumJK9ZL8II2sEXjtyQHBtUyTr9Y4BdMaH2YlUVoSVBt5WXq9Sgzt5mRbhhqnO0AWAgNeYgXldLAExIiyVMu1jS8GwLbQnkvYt4qW0R520ZywK0dQ6CcrJZAyVGhHIgKF0AqZlDfavkJZgkIfGzeviJ1EXgYUhtWT7c6BdAzrUzH1694OmigyoG/DnhlAZYxnJXYFVqgNSKlyEJE2PS+YyGRlSexSTJyWhFkrufKmk2JQaQIHQnOlTguBUyxrmc2BzMnpynaLBGQp1zZ+GQ1uXhvNd9LHAySFoxIrEHhdMan2iDglUbYwbA8GVKpNsZdf2PlPK67cNP95oxxN3BCDBBEKetqzyECaJC0tGNLQwRLfRrVZxOne7zUrAhyFlYpRSuK4EaXqmDhLUt5oIovFWg8ZQZjREBnAUeqrSK2TuAVBfrBGxZLulirSyx1cZb7X7KKRb8XpxE9SkHjNASk3pDNIYzsxoSexOyzCLKAhLLjY6xxSAyN2qV1Bg52jwc4xMNXJYx9vR226xICqLhqr87TnMjh2THdVjFWQ5uqc1hALrL4l4g7PbK+dsEiSSp+LFhBme9nysEYhfWmKLl2N12H0ziIGXa3RShC2ptH1ISpvyjxFu4vlC5xugV+vQdjmQuG6FJYvTPpaSpNuzuHZEbFvIQoWyoKwybxfTVU5eoI64rqIvg3drFvbl6hKEzeG5FdVY+UlUU1M/aAucvkU69qrwdUUNouo69dDKXAIelyEEtg9krAhZtP1sE+e8UEt93bP4d5bjgBgaCMszxzHxJZLeXbsPojiXKC78vgHu2K2/C9zrC+bv6etTm+0zB+t35EHt5jLz1ouZT92YvEZI5jQ2MTyzHFMLdzLFo0ncOvRt6G6zcWosx4wBvalbTP502XnMjTxbJTBC8Dvu3fG+rPulqcPcilufyjP7PT7ShLXKe8c+Imvc+mAsSxbcQMzXr8eXr+e8UetYYdxC/noqj8AsPm4LEMK9/L071IseOQCStN7dVTpzjaYegalp+9kh3ELWcwIWD2LHa5+jbcnzeKO7Z/iVw+NYHcmIwafzxFTmpjYswiA49S2XDXjYf50WSPiF20ATJ/TnwOeDNjm8kmsCk7guO1O4KbpB/L1qpuYWj0Sb+tunt9/Lac3vwDAQPcGHl/8CHt8XMeFPzOvcWzC9pTBXnmmrZ7FNsPncfathk3arN927DBuFgC/btqfb74xnvQ7H/DwSU9CCAsu7kefa2uZ+V5/Tnh8DdP27+Knn7gH//d8Zg/MCSec8Lcf9GUdFZuoYq1AGnGu7MiRrnLoHuLh9miCKknsOsjIXKVXjqGdESZlLE5StoCK6TzI2qawyzapX1YJ0JDqjLFKpnFeBjEiX0KEEYSRASjlb7w4NgZ+pU3CWHm0No9xbPKDUsgQqlbFpNYHoDWpNgu/3iZ2BIV+LlagsXyz3VHasEZ20TAwUQaEMgZ3KzSPK/a1SfVrRK5el+wfnXTM6P8dwJ34dMqhAnHWaLVkbMCZtgV+tZHP2QVTIKlcCywjCYs8sw+dggE3RmIHQbWh+p08uDll0sRcw9YoR+BhDspCgfDL7JR5L6KU8b24eU26PSbdBmFWJgAyRAbKGPiFOXgqWxB5Aq8nRqdkxZ+0af72/KtYmH8EuPyj7MuGy9kkJds0f2tEJEw5Y49FXKVIVfv4tiLULul0wLK2elTOQQ8voNan8NosglqNagBRsqjuk6NzdQ3UALbCyRo9RtjpQSRxegROD7idAm3ZFf9kUANhNZAwN065c0UmccXlPhQ3kRa3SXRnLXlXs9htNIb36tj0wVgS7WncbIBbX8CSio+Kfci5Hn3tHnbILOfX/s5EsaQtl2FwfSdr/VpKLVmENpHKQpvuFYSmrqZAhxbEeZv8sBi70zapZa6RtSkv+dc1ZZ0yG6K6XHRoLljFKSMpizMmGAEl0LZGpmJEh2OOA1Hyfe6awJfYMx4bERn2qTQkQHoxmze0s7i1L04qIvQtoprYlGxqQX2qQJxVWOnYdK/18+HjFFabg5MzF8eiBk1HWxWpqoCw6JhDYiyIlKS4PkNqrU1YrQgbIzJ9Cgz0Olj07/owfoHnF8Hv+JCv8tRZ5/L7qWfw7MkvM/FOs6ceX/wIC09q5O1JB7OXmMkh/JCB7kxWBSew4zUnsCOm1HICMP7Ji2D4GppvCnhwsAEvsze7iq+fNJMJjOXZX2QYeRb89vQi3/jZTL7xszQwA4BbTzedRpf8pMBDdY08RC94eWXNgezR/ykW3fIg+174HcAAnWmrZ7GWt5i05Qs88M6BnPIOnzhjvTHc5nYysWcRe192K+defoEBMcmk3/mA7+z8DmLE1xiojoM/O30ffeMiHkgM/BMBruk12m9z+STGemMQRcWwrd9g4gvXcXrGGPSfHbsPb8w6kS1uv4qFJ9Vz1gMd5M96BYAHzoIDr13KK0kk9L3vGjBySO6HkIM95v2GqdUjWSW3NCsaCrvPa2Ip8GrVFF455A1mXGnum37QtTxfVLxyyAPwnnn4IT+6jt8tbK1s58cDxrJZv+2Iz3iSJ9ifo0bDHgd0UnPV3lwXrGb33KVM2vI4fnLE8/x+zlf+9ocmmc8MYOI4Zvr06cyePZvly5cTBBsb09rb2//CM78EI6RpsBcSTWha4KMIb5mmNqqn2OxSqpLEnqikkskYvDZVYWiEgqBG4HUqZCSS6GRFlDIn5DI2z/PafKQfIUsGrIhSAFGc9LhIdBQjLG3YoHK3i4rRQWzii13HAAYhUCmbMCPItCpSbSHKLQcEKJycQmQM2gizEqEUQZWk0N/k6CtXI4qQbjOSqyhtUmrAHOCKg7JUrW1DR4k3qOx/KUvKyqyLs2GksiTMmvJJk66WgD0LU9zZHiD8EGEJwELZwsi3bEGpzsLJmx4crQXpNmUCEgIjyys22igbUp0G6MSOwO2OsXyFCMJKYpuMNF6PeU12XmGXYhNJjVuRT8QpC6sQIaQgrnfwayQyNgwQKePH2TSffj5PEPNFY1zKYGgTkNk0f2mUZ06GywlYceKlUNmY6J1a45OojpPkK1O8qIYU2W7gGt5dOYBcPoXbZhEqgagKcb2IQneq0t0SVRkkoqUBCFG1Qgtzom56UszxyO8TI2KJDAVWAZRnTu7BgBptJRIvz4ChoA5Ep422NGGNYSSk1DhWzMjaVtJWSFuYpS2uYqS7lr61OVraa1CxYJWspU99D4WsQ6noEmQcrDYHEUFmmUNHdQbHjfBSAZal6FHVyJJEV8UIJ0YL0wODEjipkLDHM9HFJUG6RZLbIgIvxm5xAQuVjk0HzlqjPijHIod1MXK9ZeR4dQqnrkTYkUI4AiLJ8M3XEilJaV0a6UvwTE+PzEQICZEyfTEqlPihjZcKKNa4uO0WQZ1CNPl8bfOPWNLZh1hJSt0eylM49SVyHRlSq23j4RlZQkSSMLAZWN/5L/4EfjnmJPe/aHnoNOo4DTiam6bPRvf9FU/sdhLN835D7eMHMtYbw0BmctSZTzDnpwfzoj6BXzftz0M15/LiBwexV+ZJLr70Axad+QwjzzofgP1+vRPwa1rOMcZ0zoFLqoZxSf1TMMnctN1ZAe/e4vKQXMio8afy0ODzKc54mvS5S7ivyjzv2P6GVXhr79/wujOPb//iIKYfBNv8fB59rq1h2JZvMEj2XuzcfHGvcR+AAA5JTpOfPsilZdYuHLzPLYzkSFPiuNsFbHHAyfzyseHcsb3kzbduYsdrRjALY/wHWHCxkWBNnf4WJMWP5cSw1UPvYKA6nw8/2JWp1ZMrq31j1omV6OSzHjiBQ+9tZnxxD4Zs4O25ZcI7FRZrwym/9q9v+QYAB7/+C8bXPcCbs//I+MTPU57xT15Ey6z7WRxcyU2Pz648/8UVBZ64e38ArFu34/4/Duax8SVKL/4cgOaxxzD9ICNHm7Z6Fj/bZTumLxzF1/c9+JM/KJ8wn5nUvPzyy7nxxhv57ne/S1dXF+eddx5HHHEEUkp+/OMff9bFfbEmaXEHKhHBOlZQLOGuaKN6SQ81K8KKv0Jo8DpUEl0JXreqsBxaGGO8FRgJmZuL8bpjsiuKpFfnsdfnkF0FRNHvBS+hucKmowi0Mqb9DZO/EtCgwxCC0CSIOTbFAVnTqIyRrclIYfkx0o+xixHKNt0pTkFhF2JkpCsJNG6P8aJEKYFdUqTbYuySxgo02RYjRSOVhAKqJCa5LGWzLMMWBaEBWeUEsjgp5wRSHTFRxiSIWYE2oC80ryNO2cggxmv3TcKbb9ZvBSbK2C6Y5dhFZTTijgEm5dhN45ERhNUWViky+zABdeX3RCjIDbQNoIq1iW52BGHWRluG9QmrTJCBFWicgqpI/cqvYdP8e+eLBl42nH8Wq/Ovmlvd7/+7N+H/zKhMDF4MdSEyGxLHpnAx26dA0BDjdgpEOqKuLk/t4C4YWqBPXY5SbJPJlojXpQjrFCIQWGs9CmuqSC3xcNdbWEWBBkr9Y0r9IqJ+AXaXxG2zsPMSt8tI1cIqk+5V9tZAIo91MKApKYeMPU2cVaafRRsptNttTux33uYjhNCUAocV+XpaS9X0hCk+LvXh47APfmTDijSZKh/HimldV0NjtsDAPp0MHbQeu2DAlNehibtc/LyLZSmqUz7bb72c7GZdEAmEpclWlchU+VhujJQa4cVYtebsL9VmwBm+KYlUtSF2dQi2QvUJiT1MRPWAEiIbEXsG5GWb8ozst476gV1oV2HXBKzsrOWDVc1IX5q+HkubwIQVKRw3YmimnVTfIpmaEt09aYo5zyTH1Zrwhbhg8/J7w2n5uIG6dBHhKLA0Kk6ujgkI6jVV2RI6ZxPHkiXdff8tn8Mvyzy6xngsfjj+aPZ6ehr+ezU8NPlKAG5zOyvme4A55xV5sCtmwcX92Es9CcCzH4zl1Au/w0Vz27hobhst59xFyzl3sXKRqPyc/tZk7r36iEqnyYhbF7PdWQFX//gMjqy1eGDJwZXlHZsbt9H2dVxxDyMP+COPHtcCGJbhnG8N5FsjDmcYSxnGUgDEiK8hRnyNPfo/hRjxNX79x+352U9OriznpH3aKyWcH/wuxQe/S/HsB2MrIOW8n/8PCy6+gAUXX4BecQMXH/V8JeWrPGXwMuP16/met5iVS9cDBgi8ed5IXtmsk2VtrbyyWadhPpx5PHzSk7woD+Lph4wcb2LPIqYvHMUraw7klTUHsjxzXOX38uv58INd+fCDXQEqrw8M63LubheQ2uu/Se313ywOruSoG9MMdI3vZsa3SkzMHIJ160FYtx4EUCkkLT8HjD+nDJZOf2sySx//bEl9n5mBue+++7jzzjs5+OCD+fGPf8y4cePYYost2GGHHXjttdc455xzPusivzgjRRIXnLTcJ9HBWglEyUe2BKQ7c3irMwRNSbu8JVASwiqBnTdFWTqJK7ZKGjsfYRVDZCF5Y2LT5SJiVWEL0L3rqnSraGPwL5+Qb7hdIuX2Psa2KDZaxKlyEo0BF063kZH51Q52QfVKCGKN26NIrbcR2ki0wDBGTk9s5Fkowow0ufsW6JQLOQuIEwZG9wYduI55Tclr05ZCSLMtVqBRjumBCWqMDyWokig7g5OPKDU6pFsCUAa8FPvYWEn4gbaSzpfIgCugAihkYPpyTKllEjvdVUr2YwyRASkykcKVY7D9Ph5ee4CyBcU+tkkds2RywNbYyuxzLQSpDgWbJGSfecpg4x9lYv7ZoOXLBjQ2zZd/RCjxsgF+3gUJOpTIkqT4cTW1W3RS6ucgQ4vuxfWGOejro7RgeXs9YWCjXYW3zoAVGUPqfUmhvzHyh1mNkxdox0T4a2WkttI3Mizl6F7Gv0ua4kqdJHtZEKVNyIAMjIFepXRyMccUNSIgqFPY6YgtqtYzKNNJMXZZ0t0HKTS2UCzJ9yVjBfTN5ugcnGFgbRddfgrLUZQimyi2SDshIja+Gy0EbrsFw0sMq2/HljFDM+3kQ5dCwSOVChnesJ586LGk0Jd4bQa0ID2km1yNQ26Qg/QFznoLEUMxGxN1mmOhKEmiviFOJiAqOUhHETVECF8ipeLj9gaKBRenzSZyY0rKJJW5g3OUVmfxWmy0wHiRIsn8jkFYlqKYd1FFGxFIZCTQdSGULOPn6TYpY0u8ZggSdq3Dxe1bpNRf4tT69K/pJogs6rNFVq2s+3d9FL/wM2zLN2CNMeg/vvgR2o9r4cj9x7By6Sv8cPzRPJs8bs5PD+aoMw0rcWStxZibWtnt4Oe5/56VPHH8hVw3ZDhfe8pELs+alwCQAb3pXEed+QS7cjdvzDqREbcupmbYVEb9P5j3zV8w6v+dxJsnjWVI4V5enDEcMCfW01bPYu38t1j6RAuH3tvMnbtdwNDGJqatnsWEWSey69i7Gag+AGDGoWMY+OgH6BU3sIxW9JqX+c7O7/DjlYfw4wmPMv2ep/hF0oUypHAv3lXH8cvHxvH1LWfBQnj59OEAnJ4ki028+AKmTn+L29y51F3Ty76AYWUWB1tzyo1pXjnkAfz3PuD7h3TDraPx36thaGMT46/cEtiSiy/9gF8+No7NxT3seJXLqx/sSt3q4ZSevpOBLqwKTqiAIDBdPOOGP4G3dTe/fGwcY72YAV2nMP2gaxkdtQGNHHXmE5z+qAFS+z4j2XvkCIZt+QAT5jWx/NHjgBsAsMJRzF10Hb9bCOeuM8llD2/VyrLdLmDqPYOYQYk9jzfaM3F0DbufuhIY+Kk+N58ZwKxdu5btt98egKqqKrq6ugD41re+xaWXXvrXnvrFnzJwKdtMPqE0UvgBMoxIdeXw0p4x0TsWPcNrcPIKpytA2xKrFCHzfmJeVIgoNr8n3SsVE36szG2WZdbnuYggREvTwaKjZBvKwMa2e5chJSrtEJkgG1MWWW2ZzhnlIAOF5SuirGXM8JGm0M9FxJq6DyO0BR0jbYIajYglXpcwwEcInB5JlLHQlkSlXKQUSdiY2sCsX46ykZWwASFMBHWqtUh+SAYRg5NXeF0m5rjQ7FBqsAwb4mtKfV1kaMz9AGFaIh1zMJWBNqVsibRNRgbQhGnjVQFzEM6uCRDtXb37UZp1+jWSMCNxcxqnx8RHa1tglQxTplwJpRirECFDRZSxkL7pjonSMpGcbZq/Z/4aAPlL4OaLzLT8tfmyeGI2sS//2rFzkoENHaxQdUTr0lhlJiSE7p40aEhnA4KBirAzBaGkK5dGfZw13WJNysh6q7T5fo9FhWmP05qgb4wsSmTJXOQqs9JogZYmsUsLsMKke8Umifg1Ec9aatwuSVinyPTPkW/JGs+Ia25XjTE6kmSsgH1q3uOD0gAcGbM8X8+HHQ1oLai2fbavW82xA17nN+t2YtF7g9BSs9avw/Ji3IZuE1qQKcvUNFkvpMYt8n57M6XYIesEpNMBYWhR5fi4VozyLUgpiAVKCTKNBYp+FSISRCmNHlxCtLvYeZn4XTQoCNtTRpImwYrBKgpyogYUWEVpume0QBvVN37JIdViEVVrrJKgZqs29u6/hKW5vnzY1owoSpy+JdSqtFm3L40vJ7SINUSBQHaZXh1/sPHW1FYVaQstbCemvZihVHBZnfeIe6J/46fxiz3fGnE4z46AQT+ewLdGHM7XX/gaz/zqUMSIrzHnp6dUEq/GjIT2Z8zv+6/ZG9Y8wuWbPQqjRnH/Pb/h6VMHwCOHAnDb4B8wbbUxj885r8iDj87lwUfP58hDx9Ay6jDgSuZ98xcATBgwlpZz7qqwLulzl/R2qJx3N+teeJKRB/yRhQfDmCcuZGnbTAaN1NzHAxw760T2bTQAduoBZwIPVmRsH8mDGMZSFj09i98tNCf7J+2TqTAw47edx4JtL8CfU1PZF0dMuZQRk6+slG2CiRjuwKSH7ZuW3MGF8AQ07H8lndW7AMaY/52d1/O1p97kmiv7M/0g+M7O7/DrP27P+G3nsfMlB7Hlf80ETsY6/CwWyO0qqWWFp36HqlvL8/uvZdmZY5hwz1hWyS0Zxhv8uml/htqNLGtrNUAwMe2/MetEhnAv45+8iOkHXcvAzAf88jHTc0PbDZVt33/+3szNHALAcb86m1HjT+XIyGL54PN58FGzn76+13/zTNqkrS3f7D74w6f73HxmADNo0CDWrFnDkCFD2GKLLXj66afZZZddeOONN/A8728v4Is8cQxeCu0HJvGrDCo2uF+X/xYSSj7CthBaU9tdSG4XvYZ26AUeYAz3UhrZFZiT/vLtCSDBD5J4ZGmkZGV2Q6ve5ZdBDKBcKwEJJmc/yErcvMKvN8yLXTRSrChlEXsi8aQIhFLGaxKCDAVuTmEVzWsLq40BP0pL/GpJdfk1lF/Thv6XJNpZeC4Eodk/josM4oT9MM+VgcIuhFTFmihj4XYFxGkbv97Gr5VYgTnI2kkim1XSWCUTKw3g1zvIhNFxc4nUK2VAjbuyA60S+ZoQCD+uyMAy6xROLikkjbTpn7HB7YlxukKsfIhK2yhhgI2dD1G2xOnWhGITgPk85ssKVP7afFlAzKb5105rTxWpVEjBzyADw0yD8VYQSoptHrIkkK5GCY1TG5NviIgzEqsoiaqNXFn28elpktgtblKiKFGeRvomYt4AEpPYqK3ysQHsPJWEexFR8c8o2wSxmEZ5zVZ9W3grNwSVl70lk46iuW8Xq0t1rHAa8WTIIK+DaruE0oKWXBUfdDbxZmkwfYb3sDpXCzGIbMzIIWtp8Aos66mn2KzQ6ZjUKoe4OiZf8Hi/vZn29xpZ7zXQZ1g7TdU51uWydAdp1hezEEpEJoIeh0JbhpqmHDoTo5UgNaTAiD7ryfdzWdNVg+eEVHsBazurCdZksUqCqEYhIkHQJwZHGbO/L/AHRRALKFlYNQFxp0tYo4kaIuKcxeZ1bWyfXclvPtgBb41NNLyI40bEedOH47TbhLaG0HT0CGUS1Pw+MdJRxF0u6wo2WBrtCeOfSYcUO9I4Nfl/wyfwiz/emBOAZ9jz+Pd46Z6tufnxVbxRPZLSThP4/ZPPcMf2F7JwcD/22morfmp/mzOjhwGYt78BDbu9kEib+m3H/+s3na8+MgSAlsMdxra1mujiR+k1pDOQDz/YlRf36OGHBwme/FYVxRkPbCQZ2zB97MFH5zKkcC8/36eWn+5RxQ48xW5XD2LP6fsxtLGJZW2tbNEIv/JHAFcz4rCP2Tdttu3YtnHsvNME3gdW58Yye3Y39IOWpC1z+sJR+O/VMH1Of87d7QJG37iI0sgBHPT4BMY+dz5jntgPeItndvo9zxcVTSMHwIq1LBzcj8tf/AGl49/jmQMmcNp9rzL+qBoG0YfmeffSMmsQ48dexHjg6KNr4CE45QwD5l4Hmm8K+MV+x3LS8fdx0j4ZRhz2Meeu2w5Yy9CfzmUiMJXJtADie4/y0PCVBnjUWhC1VfbNXk9Po2XW/Xx7UhM37QIjbl3MqPFjaN7PAJiRO0xh4sJDOHl8PU/f43Dy8otp/0U36wf9F3rhDck64X32ZDCw+1aTWTVxBsz+dJ+dzwxgvv3tb/Pcc8+x2267cfbZZ/O9732Pu+66i+XLlzN+/PjPurgv3kQRwraTk/SyZCo56jiuiRIG0HHCzCSMRK5gihnLkq8yyCizOJZEWyYxDKd3t4sghJKfpJ7FxrSv9MYt8FKYTRCmo0aX2Y7y3RGEWdMwLzR0bW6Dgqo1SQdNRhI75uqd3yioWxKT62+hLYuwKmlHVoYd0k45/ctC2WWTp0AKo7lGSAOmbNt4XyzLgL0y0Eo8RLK7gFBZRGTkYSIyci2rGCFCZUo8MxZaJh0vFqTaI+xCjHIksWdijYUSxJ40bEyswTGxzNoCtzsmvbQNkSuglUar2HiA8kVit444LYg9Qao9STbL2hX7jl2IsfIhMojQnoUMYuKURZyyzbY6ksj+zP89Ns0/aR6sP3yjv4/seOTfsh2f99zqfv9f0gXzSexLcOGCTV0wn+OE9RGqO4UOJRaGIZeRIKhXRi0sNcpTWIWENW6zyTtpiASpVougxiRxZZbZlJSH3Vwiag5MAlmbbS5EAUIJpG++q6OMRvogY4GyNGG1YW5kmJRHmjCwykRpjdtmsaitL7YbEbkOVsHEFrtVASPq1jGvZRDzWgbR1Z3BshTbDVzNkf3e4u5le7B1fQtzF4/kyTXb0VlIo9MKChbb1q5hx+xyfpE3khGrJ7nQ1m4TlSxqm9tY12AuTtWmSnhWRF26RKAssk4AtkIXTQmm8GJGNK7jIysmiGzyXWk+UE0MbWzn4M0X4oiYVaU6WrursHyB2yXQtoRBRdOt3OMkaWfm9VvpCFICy1IoJUzaWCZi82FrydoBS0rNyGVp7IIgAgbXd7IkY66QR9UxTjZAf5ytJLppC2R1SCodUMg5iKIFSqBWuXQ2xohsBKFAZDZdEPuk8efOZOpFZ/Lcd4wv4nveYuo7b0RstRXjFs1lX+DyF3/AdktSvDh8KnOeC3hp6HPMPOIonr7H4YDj/0h20kCOGn0Tl1RdxWuHLwdgt1Vw4/TbGZWclg474A3892p48FEYV/NHHj7pSbqsLXhjwnc5cvhdbLtiLdedPpyDHs/x5LeqGDX+VIY2NtE0cgAlJtByzk7MPOIoHn17MuMm3c1Lo58D4Mid5sOKtXzPW8zCm/vRZb3P7Wf+mouPX8Fo4M3509i3/w/4IzD+qDUGhLxtwMMrTy+FGjh3txtIHXAy/nuQmj+Npx/qZsv/gqM/vgRGXgXAvmnJ3OfOpwUYw4UsO3MMxVW/ZK+np5Ha679pGnkiACUmAPfRMut+pi8cxbhVsyr7+v1+B1Mbw/jxu3DSPj/hpeT2I2st0uNdZj9xFUd/fAmH9k8QxAdTuPkD6D9DsJo7GHnEbTSPPWaj9+/gh67jiasvZMg99/KzCd9l9mYXstsO9wGw6BfGb9P+i25GA0/f08ho4HcL53JkrcUM3mVoYxPfft+wOt9+v4kzfn4ycPmn+ux85jO0a665pvL7d7/7XYYMGcKrr77KiBEjOOSQQz7r4r5YY1nmBL38+4ZyKSl6WZDK42Xl8RXGpHzSG4bguQYU1GSJa1L4jR5hRuLkTOKJcoyPw8nFuO0lrLYeE6NMYtRXslfOZlm9y8YySWSYfhe0kVbJhNARsUkQK9UJuoc4RFnIrtS4OY3fKCpyssgWBrzEkG+ykKGLiM2yAKKMkY2JWJvXJsxVJ2IMOHPshHGi19gPBuQVS6TWFsgPqTI9NAJiS2AXDMiKU0ZGZhcUQmvsgkkJk5GJNo6yEhFLLF8RVhkwZRc1UVpglzR2Lia1rAN68ugkXEAIYYIPSj7VK3y0SBlPTbl3xjWSOqG0ia3WJmxBRAps02UTpSVut/pfb/Wm+fznz0HLX7rvPxXMfF6zSTr27xkRSnQsEUULGZroXcsHt10S4FRihrVlvCvmSRqRjQhqLOLq2LAI9UZS27+xi7Ud1YRFhyitK0b+oE6hLY22ddITI7FKIJOIYeWYNDRImBXA6ZHEnlmuVRL0rKkm3bdAmI0ReYmIIej2aPZ6WJGuZ3V7rUk+Cy3eXTUApSV532VdqQopNfnAJd+exq3xCdpTvNU+mHVBFSta6hGNPvaHKZOWNqiE83GK5evrEbY5djkyRiaoqk8qhyU065qyFEounhvhBzZ//HgwyrdI15VIV5co5j3W5bM81r4dQWCjQokOJZkOUZGqDWrsYsXKRpwOGzuX7N9OF8t30Ta4XZqgxuzfxi262aVhBQs6BpK2QkRkwKDjxLTmqoizJmI53Vik2OPhYAo2ZWRkatZHKfysh6VMEScC7IIgrBHQ4YKnqM58NoPy/6WZ+PRPOf3Ruez7jGTh4H486D/Nj555gelzmpk6SXDZ4LsAeOmcnzDiMNhz2X6MeeK/gZncOb2DGR9ewhNXu+w8qZWbdvkGYCRVI5dfzL0LjwKMTO3F+H22XbGWoxc/xLIzx/D6Qjh3nwvZ4+O1ALwx4bvs+i1T0l5mV254cjbne6/DUFj09M5sxRM8vFUrR2G2Y2huGjT21ov479Uw8qwjebNwL8vaWlk9dAr78oPK/a2LVrNKbsmiN09nj5N25Jo5+9K838F08T5DCvdS2mkCD60YyYz9FjF7xVqqPvgmuS3/HwDN+91Al/U+fGyWtfLH09js+O+z7MwxdC18n/HbzgNgcXAlex7/HtcAF18KpafvZMbr13Pw2p+w/U/35/57VvLcd3pDvafaI5k05FRO6Tuby+6+i3O2epk5Pz2YedNvB+Cgx3P8cUk1Zz90Ghx9GgOWncLqoXcA8CFbMHX6W8x4/XpKwBX9d+bNsX8E4P6DVrJ66BTezE2mZdRhNM/7DS+NvpYj37yI0WseYTQwY79FvHnFmQC8+Zuz4aXHPvXn5h++xLz77ruz++67/6OL+WKMSBK2yl0wZRYliTCuyMHkBqAmjiHS4DiGuSnLrDwX7diEgxvxG92KAb1cKqmcMsMAfp2NX1eF2ydNekU3IlcwaSuWQEeqd51xbNYBlW0RxZDMuph8f4soBU4BvE6dFD9Cer0mCIwJVMaazBpNfoDEyWmqV8aV7YpSZltkaDwzsWdM93ZBIzt6THWAJdEq7gV5sIHEraxTkIBCK4XV0klWCPKDs8SeMUl6XRIZ6YrnxfyuDCtjS4Iqh7DKMEZxVuDmzbLdbvP4bEeI015AduTQhUISciANeEmkd9g2zvoCdrOH5ZsSTasU4bUW0Z6Fcixiz8JO0tBEGEPWQQtMSWkhJKr1KnHSm+bznb8GXP7a4/9TgMznxcJsAi7/3rF7JGjH9LXkIKhNShsDkIHxqcjQXGzSdgIyIomwI1Q6uejS4BPXmO/b7RrWsK67ikhqqAtQyjWPk4m0qTECJYirTYeY0yMQoUA5uiJdQyZ9ZAEIbTwy2gYrL7H6KYZv1sLH6Ua8+RmizSJGZT9moNfB/0SjKPgu+bxJ6fqwo4FSyaE9lWFY83r26PMhzzsjaUjlmd8yjGWrG8n3cVElm/rmbrqqPJwcWE6M2yXIFx3cTIDfnub9Zf3ZYfOVBLGFJ2Oytk99pkhPLk1TYyeDsp28smxztBNT7Ephr3eQg4t0tFXjLnfNtbOURvUJCeo0Ts6UWMZaIN2YqNpCWRKvXeB2g1UyF9HsormAhRD0zeR58uNtyHelWVVbi7bN9UO9PEtIFtE3QNoKy1K4mZDsNjliJeluy2LnXLyORK1gmyjqKAvFgTGp5jzFdlOyWG4g2DQbz/xb7+bVkcOZeN5Irj51AAsHL+LI4fNJzZ/GS/fczU03ppkwYCylnSbw8232QY5/m1+8fSxHv/gDLtvrLsSi1Tw6soW5099C7HI+1y95iWsPOpqLL30ff85JeFt3860Rh/P44keoBZ4vKm7/9U5sv88orrnSGNwXDu7HtivWsuu0/2HqkkG8+P77vLqkmg+rtuDI4Tfw0pKrmfPmD3n92C341ojDef/99zmSCQzNTeO0FXdx+ajDAPDfUxX5WFyzHU8/9AqTDj2d/kf8loFzPqi85p8ccVvl94uPep5r5uyLKXwyU1+3FwBzF13HUWeVWPh+Pw7dYQoL355MbbwVDftvxdkPrTLJbXv9N81jf86HR9fAtma5I1wjgRt99M7MeGEUHYUXmTrpBr4+v0Ap3gowPS/jnzSRyMuPWsMbExbx7MnnsX7WO7CVCTwY2phI6eZPY3cms6ytlaGNTZxWuIuJy05haGMTe2V6DftTJwm6rFl8eHQNOw/vYdysJr7NzWYZ77/Kcb+6knu/1wRszQG/urUi1Ttq9C1mX4y9jJH11Z/6s/OpAMyjjz76qRd46KGHfurHftFGOI7xSEjTT2IkW/TKxsB4LMpsi5Ibxy1LUQExOpOiNLCGQrOD121SvbzuGDsXI2NNnDbsi/FdxGgpKNVbBDX1VC+1sVq70EGA8LwNpGUbeGXAJGgFIemWIkF1tuIJCdPmWJhKIp5laKRUPYOsyhU42/Q24SVlmn69gww1UdYizAjCDNgFTbpDmWQvyzLbIJM0MpkwVJLe9LQyCyNkEqccY63roroYUhxcQ6HJptRg4fb00hthVgIWseNWTKjKMnKHzDpTymnlfFPyGcWVkk+tEoAZx73lnhskuInuPFUfuxT7pwmrTFqcE27wPgLaMTI8bUvDxGhQriRuTJkAhU0Ksi/0PFh/+KcGMZN+fOsXOonsHwEx/whQ2SQj+/zGKgok5js5SpP4UzAyLpX0voQCu2S6XEQkUCkL0hFURYhuGyk0WwxsJR+6hMpCKYHtJl7FGgNYEElfi62QmYg4Z2MXLKK0AS5CJbHy2rDtIjb+mDhtjPwIY4LPtVTxUdHFdSOiDNDq8cj6nekoZczJ+roqZCpicH0nH3zcH1GwCGoKDKnu4JX1wxhRu46R2bWUtnf4YFUz61pqESVJZ0fWFBbbgBYUmzWyzUFW+ciCRMcCW8bYUpG1TRIbgLQUllAMTHWyRdN6/NimUOvQ9VEzfksKXRPh9zHMiIikCaHsG+L0uGgHWt5tQgBOIQl8kZBerwizgrBKkO9vvuODEUXaihlyHRkIBfmuNFSb5E5ZEqTWSZylKfxGKDSYHp7OOofqugJoyKzViS9JEGU0ccoARCsvKXak8dbaoAUFz/3Ez8n/9dnpjBM5NjeII6YAK+7iyW9VcdDjOR6afCWlnXK8eFDvY28602E80GW9z2lBHWLRan7WcinPnvwyomhM8tb879DiGXP4UWc+wYvvv8+L77/Pt7baCoDdn7yCS366P9dcuWVluROv1kyd1C85ob6bJ79VxRFTLuVYoOW58zlyv/kwHJrnTaP94xfYyjFJaL9ra2XGIYu46rHZlXUDHFgyfSzrjn+C9LlL6F8nQMLZnacDsOgXva/pTbsRMub30k4TuPzFXrZmauEx3BunMMc7nzufg6PO3Ir2Z15gznMHM3Dw+Zy7TzczXriO1F7/zdmdp9PnGgdr/ndI7fXf7PrKqRSPHs5pQR2Lnzmblq134sid5tPynNk3zfvdwEtjt2LP499j+pz+PHvPywDsOvbuyvrLAGfDOXe3C5iYOaSSBjf++IuId9qN6QddC0zgqsfeBu7i2uEwuCYLYBgsjLfoYUwi3L3f+wkP08pFT84GvsNer1SzpvY8zjrwXqb+7C99WjaeT3WKdvjhh2/0d/lq95/fBqbo8ks7lkk0ARK5VFLcqDY4OdeJnIqEkdBJipjcwLTv2BQ2qyPKSLxuZSJ8awV2UeCFxmAfpmVSXmZ8HlZJ4XWbqMnc5lVUKbDauyum/t5ttCreGlEK0GkPWQjIrnUoNTooW5DqNGWVuQFGQ2wXNFaigbZLGrtoZGGlBrMNIlJ4HSGFZvMFG3mGsQmrBX0W5A3LtOHlo3Kss1bGF6STOOjYXA1EWiY9TQpEFCNyBdJLQ9LLbaLaNCplVQCTXSz7WcrSLoWMNE5nCdmZM4ClDOASiZjZzyrx42izruRvrSIDYGwbu7ULN+uQ7++a9LLaFDLoZdKUI5HJv1HGqhRXmjZnRXbNJtPlF30+C4j5POefYeDfEIh8GjDzz2JYNoGYz2eUrcHVhFUGIKTWmWNIVGUSs7SjCftExD0WVkmAYzwx9TUFSoFDlAqpyvh4dsSHLX3w7IhBjZ0sb22gf2MXu235McsKDbyxaHPsuoAo56CkYXLCaoXqGyDaXITSWCVZYWEs34AZnQCK2DMGf7fdIvUnm/xAjRpeRPkWC1YPJCjZqLyD027hblXgm80L+Xh9AyojaFlbB0DKjvCVRS5O8fW+7/P+in44rQ5hY4TodEmtkwTbFIh7XGwNIhCUWrI0LBTkB0nWF6toSBewUFgCYiXJpAJ6Ao81pVoavAJ/WD6EhpoCzugOmrMF2vIZSiWHsDOF2ybRna6RuWU0MoD0WmmUCBKCWgMy1u8okkQ2nfTTQKlgI4CahjzdrVXokoXXVKCuqkjed8l71aRXWdh58Bsw/TNuTHdbNgFxZplBrSaqi3E6LNxOQbpFoNc5KMdsU7Qy+2/5HH7R57LiU/R5cjEAc95cTnHGy+z53PnmBHf+NKatnkVn9S6cu8+FlJ6+k+Yrr6d2kmCPkRdS9cE3wRvF1+/8Grv3vMQlh+zAubvdYIz7wIvv96ZhDZvyNDd/t0D79nXs8THEO/0agGuuNKCjddFq3px8JXApYPpnHpp8JVOXDGLdC2MqKWK7Jg33u469m5dyKViyE+9WjwLgtN1eZ8br17Pu+Ccq6526ZBA3P76qAl4AHuyKuc3tZLv+8zg2N46ftSRMR0uyT/YykrkO/1ne3M1l3uknMWr8qbQ/8wJzF5m46euXvMQlW+/AZXvdRZf1Plc99nYFQIHpk7kE+K9tzc/XB84C3gcMsHtjVhNsBS/dszVvzDoRZp1YiZsuzxsHXQvA3G8tYIuZ/Su3rx56B1+/0/T25Hf6NTWnHcvE+47n/Vl3M260qVIZuGhPbh7wEcszx8GK1yvPPWf15gCMG/0Dhm35BvtMHs3UJT9iKoPYOreEH+oS/DMBjFK9V8yfffZZJkyYwNVXX12Rjr366qtMnjyZq6+++tOt9Ys6tgWlMJGG/VnkYZDcLqS5z3V6T6bpBXAAYf86So0WqY44SYAxjfLpdSEiMODCr5XULI9wchEiMr0nVsl4QIopl8KQLFU9BUQQmmVrk+tfSQBLumNEZKOFwGkvIiJNz1APMKWVpT4WxSZNukUQaQNeRAypzhgZarprbJQtCGqNwVFoiB3TYSNDQ7FbLZ3mdZZNIUnIgAF3shfIlM39IvlIJZ06Oum3Eb653W7rBMBzXbO/y+BsA2alN0Rhg1EaHYW9viTbNutWGlT5vUq2MYrQSiPiGG9JKzLoQ1DjEGUsbAFWKSZKW6aQVAqiKsd0xQiwQoWVC5CFgDiJCN80G8/ivR9gxO/H/e0Hfor5rPKxv7SMTwNivugszIbzr5Z//b0gJrhwweewNf8ZE1Vr3AhURiGLxkhvkleMrMvutlCuxkr8LyIGLE3HmhpwFQds+yfebe/PknV9iDpdVsg6AOwPMqwY6DCidh1L2vvgrXQIam1IxeiijZWXJoClaGGFxqQeZY0/RgYkcfRg58yFqihF5QKcsg1T1NSni+5iCr/kICSk1prv73x7mkdW7WSYIFtR19xF2glZvrYBpQXzWwZy0ohXQQnCuhir00Z5iuLACBkLREnidhrQ5LVYaEvj9MCajhr8GouMXYfSAs+KiLWgq5CmK5vClTGeF+GHNj1daWwrZmTjOnar/4gn12zHx7LJMDG2Mr1tlsbvb5j5bGMBXXKIl6WTUk+gZBgwEQvsDpu2+ixCaISrSC31CKptuvJpSj0eeArlmGU53RJrnUeU0Yg6hfYUpb6mdsAwNhLLFzg9EKfAb9SGacvEiHX/so/el2ouTx/InXv9N6c3X8mSWzt4aaZJ9zpu+tmVKOHSiz+nFFzAbW4n5176Af57NWyblhzkjeJJfx6PDXmS63uMJT11wMlAt2EClph13DzgI2Acz34wliOHzwfg4Hfgie33psrdmUNOWsj00/oz9fEcy547n8vPHc5lSYnmG7NOhMRsPrFnEVNnnVi5/c0nL+Lc3S7gg9+l2Op7Z8KKGzh3twtg2X7MeP16Rh+9c+V1PrHbSRXJ2g2PvU3p9e+w11FrOGT9Qby//ocAfNjnJgB2e3YnHhvyJDOPMolqZanV6NcDnt/hfFbJLcmu6eSqx2BF96sMrslWwMvUSYKW5+p4KXdJpZQTAOOnR5TjizMkfS1UGCCRMf00G05ppwk8csdsrj3oaF4ZdAx7rLyfofOb2HXalYy+cRE0w74vr+DQF38Ow37JzsN7+OOSalbJLXlzsmbU+FYO1Sbw4LLJS9jx3OG4Z5UY8NNTKC27kyOmXMqcnxrgtAXA8Z/+s/OZRTLnnnsut912G3vuuWfltm984xtkMhlOOeUU3nvvvc+6yC/MxH1qsMMec7U/jjeOMN7wpBl6iyaTk3td9qbUZCkMSCEjKNVZWKG5OdUW4bQXQEqya2wyrQI7F2LlA0QQoapSKEeiHWk0ukoT9qvF/chHl8GT0ug4TAosbdMvE4QIpcCSWMUQu+hS7CPR0pgZU+uEiTOODEAJqwR2SeLEirqlIVFGEnkSp2CMoHYRCn0sYhf6/KHDvN4yWAGTvgYGOJSBi2UZACJFL9Cz7Q1YG40WaoOiUIEu+aANWNmIVdEapDS3lde9YcFn2X9TXs+GQQtx3NvlIxQ6BkGI83ErVn0NUV2KoN41YNGPidI2WiZJN0rj5EKs7hKip2BCGNSXmE3cNJ84nweI+U+JTy6DkU8DZDYBl789KqXQJRC+MKxIlSmfdLoBIQirTMJjWKNQnsYqmJAU2WOjBDQ6eVavqcdb7iEaYqLAhk6HqClm6GbreG3VUAD8phgRCrA1Awe2sbatFh1IrHYHt0OgchZBnTLyMQ/jjSnXkDmANAxMVKWJUqb8cvWaepqbuwhDC7koC9qUXDY0d9Pju0QlB+3GZGt7zGst2ASxRW55De8N6I+OBU5HwizlLILhRaSliTFshOUb9kO5BsxoJejMZfCsmHzgYlsxKSei2vMB+LCrEaUESphesI4PG+iw61k1rBbPipGZCNXt4K1wsUrgNxjGRTmaPBlk3jJAMUkN05bGCozkK2oMSTsRvm9kYaWUS9ztIOtjRN5CNgSUBgjcNiPLk6Ekypjjv/BNwaVyNXZeQMH4nZQDURbksBy21PhFB5nf5Kn8S/PAiCPYmz9y/R2HV+RGYGJ5izOG88ODBLe92EnpxZ9Tu5fggOXn8DUvz2V73cVeW23F9Te+xM0DPqI2PjqRJG0856zeHDKv8fqiSVy0qPf+hYP7weD5HII58U/NnwbA61+fT3GznQA4NkclJWvqVoaVOe/n/8PrA7dgOtfSvNMNTFj8DkefN5KpSwaRvuUARv3BAJE3Z/+Rm6lh99xklr9Xk8isDuOSQ3bgKn4N7MljQ55kSJ972XH9Azwq9gOonPBvKKc76PEcH47diiOBOT89BdxOrPnfYbMNXudL92xNy08PrvzdNHIAXdb71MZbVW57MgkpKM4Yzl7qSZpGDqi87rnfWsCLL/xpo0jp1Pxp3DzA/LtmyZ84crgpBq2bfygYUopXNutk4aR+7PbsTez27E20iFNYesIa6ubDjDOuryzr9ccF7lZbMS23C9secDJgSKfURu/W52jiX7p0KXV1df/r9traWj7++OPPurgv1MSeDSkP8olBpCwhK7ML5RNqy9m4WLI8NVUUh9Sik6tZfr3E61Ck10fY+QhtWWAJrJLxvMggRgTJ7eXlKbACBUoTVTk42bQBKGUGRkmwkrhmO/HERDGi6CNjRbrFJvZSdG8mzZUmDLMgdbnsUhNUCWwfRFETO4Kg2sjYAFTa6ILrF5WQHd1GjiUlOvB7QUk56CAp+dxoX5XT28A8rlK6KcxykoJOI0PcwHgvBDpURn6mlAEPScqbsCTaDzZmXcrARkh0ECJcp1f2t8HohKmS6ztwO22cFg+d8dBSIv0YESlkMUQU/V4WKIqS+OtNB5xN89fnPwW8bDh/i43ZBF4+3YjYnGwLDXE2xu22DQMSQ5g18fXKMd4JvyYmrorwMgGi1ieOJGv8WkTBxi5gouS7PWIX4vqQ5Wsa0AXbXERzFUQWDU3ddOTTiFUppKMRofHWKE+jPY3blCdYlSVOur+UoytdMGgI+4akanz8NRlSyzzWu9VksiVKnsbOCVRKmcOfVHjZgFKPx+r2WvYbtgh7uGLpyr6IWDB3yZYQCeMBCpMizqKNAuyCYSqcbkh1mBSwKKvxUiGOFbNDwyqW5xvom8rR5mdY2VOHFBrXMheTerrT0OVg+YLIVbSurzHMx+qUCchMafxGhU5KMHEV+NKkvUlt9l9V+YIZ6KoIN2MOlEF7Ct2RxQoMWNGdWaSjibscs5+kSW8LazRW/yJeKqS0uBa3M3mdKbOvC/3Me0QsECUHa42H1CBi/9/yOfwyzKFv5ZnvvsTv3N8ztHEcD02+kiOmXMpDk68kfe4SoIongXu/tye7PXsTsDcv+0aSF9yS4nzvdZp3MnKxw095hEfuOLyy7JsHfMQ5qzffSF5VnonzNVMnCaY8OoXLexZxWlAHwOUXN/IucNk1bez27E6AYUjuq3qAPcefSt99zuea499j9NEP0PdH3Wx1xh4c8dVLmTj8Sr721BmM+oOJTAbje3nTBr3iBrYYeSHnPPZ7stW/hWo48tAf8eCjc1meOY7lQ45DAEceOsZsXGI9L4OLlufOh61MLw3cwLn7XMhVPb+ueF5Ob74S/dODOerMJ3h88SPc/tuQraqe4P1+BtC8MugYtpjZn+KM4cx584cM4xwGAn9cUs3OO/Vw+Ys/oGXNjzg295tKOeWGU9ppAns+18rSfY6BJHRtSOFe9l6/iqdH3kxq/jSGJUxS6tjd+fEvzbHx6KN7wwkmPHsiPHsA6c3u5kMeY8LHJ260jl8NuRj6/dWPykbzmQHMrrvuynnnnce9995Lc3MzAC0tLVx44YV85Stf+ayL+0KNdiTadRB+UDmZhticIJeByoZFlsQVdkB4afxBdYTVlilO1MYgL5TGKsZYfozflCZOmfQxJ2dOnoXnoFK26YgBooyVnJibIkmVTWF153pLLS0JfoT2PLPeKDKm/ihGAHaPT2athQxtwoxEOckVJwmxZ5arHPBDizAtiVKC2BUUmi20gMw6ReM7eewV6yten4pMrMxIJP0vZRZGB8qAkPL+cexe0BdGlXhqTSJFUxLcpEdGK5NwtiEQLK838dRoFfeyNxtOrIwXSIje9ZQBVdnYnzA1WloQB1AqIXOmqBMpYQN5pI7K8jyVyNA2ZSl/nvPPkI9tuKx/taH/PxG8lGcTSPnHR2ciQhkjSxKhTOJXbBS+yLB8lV6bC0sFC+0I0vUhTVU5Fq9q4vWVQ9GWJqgzQIPQ+GZkKpEmK4GVl2hpZEvtq2tx2mxs31zcCbMa7UBYrUCBX3AQJKEuGcPKk5z0a1sjvZgwMKAorFaodpfIC4mqFSKSUBOyfo0x5uuUQqYj+td3s3l6HQ1OnlUdtcSpiNC3cdfZKE8n373g1ZUQf6omdk38s+WbXq//z955h0lVnv3/85w6bfsuLB0UERQMqCgq8Bo1YNDEghB8id0UUwC7KMaoKIoagRhNsSuRiEZNlAiWELBgR0VBRKSzy/bZaac+vz+emdlFTYJJ/Il5ua+Li52ZM6fNKc/33N+iOyobx/N0TD2g1Mixd6KBpB8lZnj4gUbU8IgaHjHTJZOw2JyrRmvV0Hu6yEAQpkwirULtpxAFXnT1N466L3nlgbKojgYkSrO4rkHg61SVp/ACjTDUQEKkSRBYyuSg0K0RcR/aTAI7T61OCeSHMXI2+GUBfrlET3gYRoCUgpjtkWqNoTeaGNtNtDxukZkv4yj8atSfDozz7TdHMnucGggfdP4Pdvr85JlXMj/xEK8/fCZzalZxmvRYOPZHlHUiSexYu42b170AnLjTd6ds68e87h8zf0AHnatzh2Hk6008dejZTEN1AnJLfscPv3Emv37m3qLg/aFJZ1H/3IU0bRgNQoGIhrMX8a2D96OBp3hkaX/S37lQBWK+8QS3joOb1ymtx+bkIHoBv558Ai/Rykt9D8BZPZI77h7CayWX0JudKVuvLThL6UY+sf1/nHEtXY9OMf7bA/MgJom+cgLnn7Kdm9eN5Q6uJPfKnfDKzTx5pXI821C3ih3JYdxx9xAAvvHgWFiqqGo/3LA3b1c/ALEPGDVwILnrV7O+WyldmcHEvIvYmGenMNQdyRXfOoA5F1fxdeuHGGdA69A/qQ4MUNU4jMjKGzl/0SU8f8gwLukLAy++iMHn9mLVnZv503ETeSZaBUCmXG1PQQ9UeP2NR+5i2k0v0vuNB/jR4sgupsD8CwDm7rvv5qSTTqJ379706tULgM2bN7PPPvvw+OOPf97Z7VYlQklYFkPPOsp5q/B+58F1ZwvhwluRCEFtBU65idXq5ylK+cGvUDQBpyqCH9Xwo+qCHt0RIA0Nv8xWGhiRB1CGQHM6Bs5uTZToDl1Rmgyjkw4nyIvWg6LsBE+iJTPYro+RieJU2uQqdIJ8mx5Ad9SyvLgSr3txMDJQsjUgtjWHWd9WBGlFs4ZAdYQwlJOGyoH5hP6n2BXJ7x/fV2DLtjvAh+z4XLp5ilY+6LOQMyMMHRkWzBPygCWUYJlq2oIGR+TXhXzHpwBc8rQ2NZ9OgCnId3CEpuhrhgG+o9axAHwK67nH7/ILr/8kePlX6t8BMf/NwGVP/efK2mwTdtGQlkQKZVaCR546lrf7bRf4sXxXwJC0tSgtBi0Wcl0EW6eonQlNiTQlMmViV2ZxdBMjJXCqQ/SswGwx8g+sJEZWBQR7cYmRUuHE0rHQc8pt0UipTnuoS6QuIRDIVgtZ6qFXOUgpMI2AbuVJcokMGcfC0EPSOYtsU1QN7kOBEJJ1mS78df0++E1R9HaNSFqBNa9UGdh4VT6iLkbUARAEUYlbpjJS3BKJW+VTYvmk0hGW1u2DqQdsay7D99RDqIqYYkS0ZiO0tsYhFLhVAft3r2fdjmqC7ZFi9ovmA16+c27KfAC0pLQ6Tcx2ac9GCAINpy1CvCpDEGo015WBJ9CzWl4PpG5VCGXoIttNIjt0BfQ01UHTvDxVrFUBvsA2lS5GQlaCle/4iALjXCd/v9pTn6xelTWc+uEfoQTa9AO4esFshq9y6DPzSsY9mSp2IKLT1vHapecybetIfj1Z6a/HPDuFaXPWMWtdTonSUaCh0HXZnEwzsMcLPH98llHPL8oDHFiy4m2+/6PDAXih9jjmLD0HnnqcaTe9yEdnbOeoJ1UHuk9VF8Yt2MwrxyhtzREXH8Gmafdz6odXsmjTGzx/yHusPgr2Pwr2B1b3eY/6re8CEG+/SXVJ/vwOs8dN5NCtT7GhbhUAm2Kncd7Z79I788CnwModdw/hvLM73ssNvRSAq6c9xBJ9DU9++Di3PtIN6MZlV37AHUtvIk0++2bc7J2cw3JDL+WOy6rIlTZy67jZHPUkrFqwGI7pxf+4l3NJ4npWbV/LtA8f57VxsxnWv11ZJqdmwMobWXLMPJatvJGub3zMrEmXYBz/NtuXvg9z+rPqoSizSmBz/9VAFZFkNePsE5mcGkDuhkvZsXYbvSc9sFM3DTqD0beYdbk6V88vX1Jc33NXOMDO3Z+/V0J+0k5sF0pKyTPPPMOaNcrRYNCgQRxzzDE7Cdm/SpVMJikrK2P04VeixWLYG5uhLbWTZkMNyPWidS9QpDeFXSrI9CnFbPfR3IDQ0vN5KkY+RV4FKIaWhh9VKfNWMkDzlPMWEqRWaPdr6LkQPesjNYFTZVHy+hY14C/oPYoUJ11ZP6N+E6FpRZAjbQsZMXGr4+SqDNwSDS2PIUITnErlnFKyKaBkXQqtPaNCNPPak52E+0JTYKOgRek0wJe+r+hboNbJMNQ65XU6siRGGLEISi0CU1G8jLSPCEK0lIvIOYh0dicnMeDTHZfCsVUM1BQdy+zUDQLU60JWj+d2dIN0/RN6moJzmvj0/AFf+DzXdA9tbW2Ulna0Qf+vVuE8+XD0Q5QYMWqfP+Fzz+OLBC7/ihvZ5wUxXyR4mfD9Y//uZwt/+/QXttz/VO05T1QVzpP+l1wPZerJkVsdEN1sIE11DXarApUTI1QHxOiWoXtlG3WtpbiOQZg0MZM6wgMzLXBLlQGLH5dotTkS8RyaFtK8tRyjVZkBhBUeSIEe8RFbolitglx1iOYL/ESA5mhojiC0ZUfOTFYjjAVoWR3hKyAV75LG99U1sLo0jR9qBKFGKmsjJTjtNkbUp7w0Q9Y10bSQ9m0lGO3KfSs0ofLwOmqiaba2l+H6OsltJZhJncBS4CqISKhVrYnQ06iuSRK3XAaU7eCD1q5sXN8FqyKHlzPQzJDq8hTNyRhe2oJQIOwAw/IJA52wxUK4Ammp67qe0QiiITIeILI6whHo3TMkYg4t20vRsjp6RuB19RTtbn0lZrsgtCgGXgYxifBAmkofZDfnWRERleNTML0RgbqfilDpiWQeSPkxibRCIvWKAuglJLLdYd3sy/ecJ/kqnCegAiQBXnTiLKvuAUD9QScwZ+lNzCoZwPQFakD7deuH/PUbKnRy2pEXUxYMZNHxCZYf3s6t42Z/JhjguBMBOK/rtUUA07ku6q/03OO/fRRPfvg4AF3feKK4TIA1Q5WOY331XF45ZiXTr5cEefet5K/n86cDd3aYe6XH3oxZPIk/917E6NK3ADj1wz8y7ciLcVb/49/+jruHcNUNTSw6PsFrg22uuqGJHWu30WVAd65efg7Pfu9FnvzwcX44/2UAcvfHGTp9MWu2juSxgUoMf7DfxN4bfsJerw9j0TG9eLv6VDbFTuNbm5Qn9f+4lzOv+8dMXzCbF4+ZXNzn0xfMZtakT1sng9LHAGzPa2Smt68t7tfO63zyzCvJDb20qLX5JHiZ3r6Wwd3eYNX2g7hq1F1cskgZBOxYu401D/4KGTik3/71Lp0n/1LShRCCMWPGMGbMmH/l67tvFQa2hQF5wUJZo0Monh+8F7syEZtszxI0TwUyAugZD2koqlhoCoSv0t5FPvclNAR+TCPUNXRXYjd7xa6N7oRojk8QNwksTYktLTM/mNc71rUTUJBSKvBYoERpOsLzEZ6PFYKZNPATFkFEVzkrhiCxTWK1uKrj4vkdWpWCZXFn8FKwSc6HVKLn//Z9tR80XelUDANhWXi9q2nvrfzydUfiRwWhrp78BRbojokfBUQcPQd2e4jV6mNvakakMvmfQgGgji5QXqAv8iCtIPjv3BErABTooLsV3is01AqGAVoeyBQ6MDtRA/n033vqU1V31BOfC8R82V2Xz6oCIPlnQOaLAC7/CLD8o2m/CmBmT0EQlwgj/8Q+pxFEleuV7gCBIDQgKPdBgpu2SCcsnLoYmisgHmImBX5UkukVYDXlheMa+FmD1nQJGCHCExgZgRMLwdHRS11CXyPeKCCE2PZ8qF7SINvPJfSF0ma4AhkNVbBm0kAL8oNyRyPdFANNokd9tjeUIdssKPEoKcuSbIkhcjq+L2iR8aI+RISCIBqS6+Fi2T71TWU0bOqKCFTejA7ombwLmqfE9Jrls3dNI++t60HT2ioyfdrJ+QbJTAQt4eFmTLQ2E+EKWvQQTcsDlJhPNOaQbotixVzCqhC/OUK8ezuplhgipan9HQ+QdoCMgi4Frm9gtBoICborCNoM2iJxpB0S5nTMpEDPKXtpEaj7FVkUXS9/W9H8fJ6N6Lj9yHynRoTgRSV+SdBha21KvLhQ97tgT2f/79WMYQpEfHPFW8X3XvzmwZz3i7Us18axKv/eX91f86IzmSNsFXHw6LqhzJ7Wn1urVedh1EslvHbpdxjc7Q1+s2E0z5xyTvHp/nLGsWrZZq66oQlQWTKHbv2IO+YMYdakS3htwVl0RQGXwef2Ys7jNRxzorKOe2zgDnJDL+XRdXPp1vN/mXX57xnz7Av8PHycZ5Yt5pVvvcici4/goWn3c+qc07nu3F6senYz41AA6qF9TuaZaBVzlt70qW0/r6sa3PfOPFDsthQG/wBXLz+HaUdeDEF3XnTiRZD168mHKaA1XQGJLT+/kem/O4Lc8jvZsNe9JO9fwbTFKtul6xtPYA9KUrZpNEfYaXKvTiA3TsCC2TzY+7LismehQMy0m9T3Oru2Hb5F5eVEXyoBrmX+nP5qvVMPqG7SyhuLbmmFrtnBv1jLHy8YwGuDbdKj72AeH3Ne12v51oZxjLOV1ui8s99l+bqhjB+wkuWnP8W3uy/jmYkdQZ//qHYJwMybN4/vf//7RCIR5s2b9w+nnTJlyi4teHcsESr3L2kZiMIAWYZq8Ft4yh8qIb8MQoShEyZiKmsl5aH5isokTV2BBU1gpANl12toCCnRXYnM5YGMWQikFOhZ1b2RmkDLeAgvhHJbXUQLWgzfV52FfOdA4hWBh9R1RBCo9Sp0JQDNU1QuvVF1ZQgCRJDfNj9PySoGZXa6wBYtovO6G9/vMCwo5r2IInjBMAi7VZLuFSPdVSNTKyhdLzFykvg2D7fcUPs3AD8iAEVriLQGuCUauXILrUctuispW9OG1pRUnSDP6/QDdfqxCh2xIOigphVASMFsoLNDWeF3hDwdzlYgpwCOOm9/oRPk7hFd/qdqdwQvnaszQCmAmS+q2/J5gMs/+/4eMLP7ltRAzw94hZd/wp9ROSyalx/0ZnRkJMBoNGmOxJFWSCg0ItsMBXQQyDalZQwjEhn3FXs26hMkLYQnyPX00KI+osEm0E30pE6oQxhF6W0ctVxrm4nb0wVHx27UccuF0nhIdQmVugRDKic0W2kqA19TTeusQUqPUFqRIWVE0HT1pXhtGtv00DUltG9oS+BuiSunM18UwzulVgjOBKfax2jX8XbEqI+WUNOtjeZogky7Te7jEoJYCGaIVWcWKXFuS0SZIlghQki6lKRwojla0lECX0dGA1KNcbSIj1+iI4ViNugxn9DT8Not/KYIRpB3YZNAOQRtJsJXGW26o8CLFB3dFcjrlSy1DaA6LgU6mZEHZaCm8St8tc/1EEJRdDwLynzCiPfJQ2RPAX8dZHHSwGc46smvsWnwWKbPOT0PMtST/VWfmP6gV+eSA6bUb2Zy/1OhWgUuvnHIVLIT+/P6w3cy/nLBowwFoNuR+wFwyeM9eeGG2QysUxkta2qPY03twE91HL5u/ZDR/a9jFAMZvsph+eHtwGyuXn4Ot0bHsH3pEn6zYQrZnyzh7KW38NC0yVz353e46oYmBtY9xbOP1/AsOTi+BoCGpScD0Njzf3io03IKdLLXLxgAQO/84B/ynYoFsznv7Hf57qYbmLD4drpefCEMu5AJN93CQa/OJRi6kJXWVmZVD2B041ZuTB3I8lF3wSi4evkLfOOdLJfu8zP6RhfTf+la1sx/mfXVy1hf/ye655eTHq0CVyacNYmF99xYBDFzLj6CwecqichpwzYW12vLQjj5nisZ3biVUeFlvH7BAE6eqbahd77TUui4HPyLtarj84u1cPcQjrz9bE6eeWW+C3Y56y4+lG7tYxn/7aOYA4xiIKPWPk/F5zh2dgnA3HrrrUyePJlIJMKtt976d6cTQnylAUzh6b0UAs0082GMuhrodrYNhvzg2CKMmeiOEusDRTF+YCt6gJfQMXIhejZUT20EWC0uWtZH2jpS1whsNcgOLV05k0mpQIsEPeN3aFDybl74sqOD0Lny9DLph/m4gfw0PgrYeH7HdgZBUaQutLxbWGcHL010AAI/7AAvQll9FuejCWQiRnbvKtp7mkRbQuw2SWALvLjASoHZ7qLnfJwqm1y5jlui2vElW3yMbIjUBUZO4pRoOBUa2ZoKKlfHiKzboYwKCgGWMsyDjU7rYxod2ymMfFdF76CChRKQavsL3Radjt+04JT2yW3uBAL31P+t+rJoYnvqv6sCSyLjIVpOXTODiETPKot6pKIM644gDHX80gBTC9HLHbz6KLnuPlpNGmdDiRoop5QzlucKyvq3UBbNsU0vw0/olJdkaa0vQVR6kNEJ4iGyVVNBmkIN2ENTdT4S5VlS2xNFh0r1gAykIQlKFOUKATIQ+BkDzBBphWjtOkZjhIwRQQP8rmrUnvFtspqFti2irIRTAisQhIZEkxBpVpQxP6aAXBCRCKkoZFpGo3FzOdW9WtGNgCCrNDphREBOV3oTF/y+DoYuEVrImL0/YEO6EoCN9VWETRYiENQObKA1pcIsXEA6+e0IBZG4i6OZSM/KL18xATRHEMYlVqOOntv5t5P5zooWKM0SeU0MoQI0XokktCVCavix/D42JIQK/bgZE7M8h2dYCDOkoiJNa/2ejv5n1X5n9OTPP5pPJFnNjBmKqlWgItGJxjVr0iVMXzCb5w8ZxrhnN9NyzfmcP+mK4ucHvTqX119VOpBTF3ThwfsvB+DnF7zAz89spP76NPvw4+JzzKsHnM7wVQ4H/2Itd9RfyawSBSTGnFxK4XA4eeaVbFhzL6A6Jcu1cay6czPxd0aSXb+E6i1/4/zyJUzufioD65TjVw0X0rBUOaJtqFtF306uWhvqVnH+oks4eOIwXtl2ObPHTQSuLXYuHl03lMmTLmHCWZN4qHYwN7/5Ahf1v4xbH+nGGzdN5aBX51J/CLxxiPq768JD4Z4FABy+5fcAnDTuYdYN+9lOWZDrpvyMnzZM546aJwiRbGETp176PLMnnQVrt+Ff+jy5Sar7kxt6KevOmsRVb/VR8+v2MI8tmljsqgAsq+7BHXcPYXj+dfnKbzPlt/2Yful3YMFspg+2GX7BAO4YbPPKDd0ZvspRdtDHJ5jyo7vZfsWh9J93DZTAyNNX88L9g4jeNobvcgNf29TKM7t47OwSgPn4448/8+//tlI6FEEYMdB1HVw3T50SIPMDXi0vCiffuTB1AltXoMdTgMArNXBKdSXY1yHWIPO2lap1LpKhAimBJLTzdsqhoqAJT51e0jLU61B2dILylsB4KkizSPsSGjgOslPIpexMlfJ9hGl25MnAzjqWMFBakc4UrAJlq/NAXubvdqCm03UoidM2rAteXCNRp0I53YSJ2S6L1pNuhY0IJG5Cwy0T6DlZpJcRSox0gDSUJifWKPGjGpmuJn6sG4lV9cj2VL7bQodNc75jUtTghLLjN4KddTF6vkskNLXvCvulAEYL26qJYqaNDAJk2EmDs6f21L9Ze8DL/60SEijxCTUDQjBbNPSc0rFIQ6I5qhOg+4LQhpJ4jubGEoyshp/wKIk65EQJYakPKTNvuyxoaSwhW2LhtlvYpQ7tqSjC08DTMNo1tAA10PbVtVyEYGTzFCdPR3M11WmwJdIOMNpNvCiYJS5BTMOyfNz6GFarhuyfwXcMlFmK0uMQgu7YxeyTIKIMCZxyig/p9KzAyKGoYgUzy5hKqkeXEJUEQiIyBo11pWjtBsJSRgd6u0aQCPEqA6XvyRqUd2ujayLF4PgW0oFFkxMnbLKI7FBAJ2Z6VNU0UmmnSXk2OzIlJCyHpkwcy/Dxojq5EoPUxjLcKuVIhiHRIwFgqG6LQHWuLPXj6VmB8MEI8l0kQZ6CnRflA35U5c24FR3gRcvoiJSOV6aMZoQu6V6axE/vnHaxp1S9f98WEt8+l87uYa8Ntrlq6KUMTjzE4xOeoP/YA5lw1iRoXwvOG5x39rvcMW4I5519NqNL3+LUOadz3tnv8voFAzh1768xsMdAmA4rZ43llaY3eOahgeQOvq04/1vHzebFxsm8xnzIO3QNf7ym01rdAyjb5EeYyklrujCwx5WM6rqIqUMXs/ruOKfOaQDuYvwNTZy64B7eqlXdiv5jG/jGg/P584/mc+u4VZz64R8ZfuMfitS2UaecRu/UqWzqP5LeeVBQ6FxMTp2qOi+x0xj/7QvZvPRSugzozgv3D+SY3x3BVZcLTht2IfU33cKWhZuov+kWRgNLjpnHSz3/l/7P38zA65Vd9Ia97mXugWO59ZFuRJLV3LH4zeLW3fIHEw4cy/iBA+m54FK2/PxGrj7xomLHJzVuJKcBD7zVh8T2Qz/zd1O0u9nMAo568mscefvZO33+2mCl/7tk0cPs+MVarr6sikt+dDf6ygn0nAArXxjL0OmLiSSr6Rt9k9QvXuE3c0ZyXy4F/HGXjp1/SQPz31qa46NrAVIXHcCl8ORf1xV9LJTqCX7+ab4IQjQ3JIhoBFGNTI1BaECkNVT6F1cSGgIvoWMm/aIjmZny0bwAPeUidQ3N8QmjpgIwUjmFBREdqyXXYaHcOWul8LqzuQB0rG9nOphhdFCxZKfOTdFy2OgY3BcATiGcEvKhnkHHAL9gHR2L0r5/DZkuOhUfqidyyT4mbokgsTVEyLwVtJHvbOkgfAVeIs0hgS3Q8h0rEYCeCzHbPexmBSZTvWyajuhGxcpWRF0+xljXOqhg0GGhnF9vKSXkHISuK22QYShAIqVy9ylM4wWIzpk1nSlmmkCgI/bkwPzD+ldE/P8X64sELp+c9x5K2e5TUoAZ8RBRj3BjHM1VD7Q0V6AZEJSE6CllrqKVeuxfXccrmQihtBBpnYamEqW/zIv+ETpBTIKr4Xk6wtFxmqMQgijx0LfbRTF6EFNgQIKicgWqa+A2RtEDlHGMLhFpdd8wMgJND/FyBm5LTDlyJSQRy8dLm5hZgZbPlSHfGdFz6vpY+N9szztDhooupvkCL5EXv8elAlaAsAKELtH1EE8KNCvAqDcJAgUIzHZBWOZCKNAadLSoj6mH1KcS/CY5CoBQCmSJj7ZVJ9MjYK+SJta3V7HVLycINdKORW08ydf7rKXNj/LYuq/hbI9hN2n4MUEQDyEn1DMxrUOU78cloSURvkAKiQjFTt2ZAiXMSAukrvaHunepfRBaOmE0xGzRCTM60pCErkZjJk5pJP2FH3P/DVXowsRX3sjjZz3BLX8wuXDxm5zaY39eG2zz57OVy9fwVQ7jBnRnyPXX8OIxk+kyoDt/OPN9vnPvfnx76+/pP+8aEtsP5YLuA+Gpx4nwOCvfUX2JGatmAHDUmY3FzJhpT15ftFcePkkBmNcffouf3j6ZZ767mDXcDCo5hGXJYUrncudmdqzdxltHqqDL8xqm8/NjJgONBEMXMn3BbNYtfpODu14LeTrc66sGcOHW97jlD2o5f5zRse25oZcyfMa1LF33An+7LcKWn9/Ijj+NhYGQW34np269h1vWjuXCiy9k4T0L2NRbdWemzUmw9Ed3Ay8QDIUPb4PI6TD1zcXAmXzjwbE8M/bA4nKmDr2ZUw6eyxyURTRrzmL5DcDabSw5Zh6R628EPoahl/LAW32IrLyRTbHTWK4pE4DJqVPzon5Fv5u+YDbpBb8kvm5HUbA/fJWi4C8dDTeve4FnH6+hb/RQFt4zG/uDP3HBAWsYvsphzrSz4aZbiP9iJD+Y9gIL7m3c5WNllwDMBRdcsMsz/MUvfrHL0+5u5ZXbis8qhKImZelIoS/km0CeZtTRDtaCEBxwKgz8CMVuAijHEs2XhLrAj+toniSIaJjtktDQ1P3JDyGQCC8giFuolGZD6WFSTr4LonXoUmSo7IkL4AV2pkGJTnSvMOigS4HKR/Hz3ZYCICoI3jt1IApan0InQ7ougjz9SkpEJEKuXzWtextEmhXgcsqN4o1A6hAYAi8GQVTDblHLD6ICchKpCwINvLgyMtA8ZWZQ6ERJ28BuDUh1M6gfWUHt3wJobO1wJit0VwrbUNheQoSpNDBFo4W8PqgwrSh0jzqVDMI8VS0PbD6LorendqrPK+L/IutfcSD7b6wJ3z92D4jZTUpGArqUp2nLRsiFaqArdTW497t4Cl2kNUTe4LE5H8wX9swhGmxEXQTdBTcBZoWDq9kkuqZIt0cQgDRCtKyO5ghI6titarAdeuQ7I5CrkUp74inrYbveACGRhTu/kARRCCp8uiay1KctZDwg1itJdSKNIUI+yln4UQM7q5LrjUweiAWKiiVC9b+RA0KlESl0f9SAXy3Kj0uMVp0gEGhp9SDK0CGoDVXXJifQs+CVqm6GdHTcmoBR/T+i1Y2xamVfKt4XNA8L0EtdrJhHrkYZ7ry4uR++pyuwlXDxUhbv5izeq+vG3jWNOBkTI61hpkBIgeibxctYiHYDI61AFgFYSaEeOJZIFTKa6XAZA+VIpnkd2p7QQLEqQhXYKWMBetzDD2z1+xqSWFWGIVXb2diwpwPz96ogZL91XjdmTrkXgJPWdGFDdizLtQij/rBIuVstuoQLv7MJgLWb+vP2yhvZdMgK3q4+lcjKG1lT/hCvDbZZc+nzsPJx+j/1OOsWv8m9w0YSX7cDrv+Y549/m+1LrwdgO8CA9wF4Ze3lbMo7kg3nHqK3jeHgicN4/LeXA4s55eC5NG14CxjG1DcX85vq0RzBfO64W5kA9K0dzFFPfo1l1fDnH83l1nGzmQ4svGcBxE7j2U6mAPctn0x1d1i+Zg0nz7yxOOiPrLyR1wbbDL/9bJb+6G700yfQd+EmFt5zFtMmDuP8cBEAJy48gZ6LOgwPlh/ezvn9VXBm78wDcD2chAJVbxwylf7P38ysSV9jdONWta1Nd8LrU3nnjTvZMWzbp36P+YmHGN9/JacN28iJC09gVGwRvTMP0O34/ZSNMhStpgumB4/XzSU6Yx0nz7ySdP8uLJ70UwCOvP1ssnP6M2/BWUyfsT8nz7yStu+8yKx9b2T5okuYdYy6Vpy2fSP+pc/zjZJ3eG4Xj5tdAjBvvfXWP58IvrI2yoUKNaHE9oEkjEUQLW07T+B1GtTnB7fCD5ERtRvduIbugpFUVzu7LUBzJVogFbWqzEDzQ4wWD4QgNDWkke9ARAz0nI8IJUFURxoCIxMoi+FCt6UAYgoaD63wv+jQ6nTuooAa3JtGx3uemx/wd1DEpC87fjudDlezUKqbnesqUAAghKKjlSVo3cciVq86LZkuJiKU2K0SK6l4xrlK5b5itYOZUaLHsF2BOi8qsNvVTUIEYKYC9KyngFwQIKTKqYm0huQqNFqGVlH5soNMZzsoZAHF/BYFQDo6S7IgzKfDMa5IqyN/rHai0xW2vwhedB2CPRSyPfXv1ZdBG9sDYnaPMpIGrZkomZQN8ZAwItBzgsCS2AmHkphDI6XQZBK0mWwvLQEgzOnoAVitAmlCoko5M0ajLpYREK1qJ2L4bE4qyksQkdhNGkYadFdClrxdvkB4qrviVEriXdI4raXojsAtDdESHqUlWbKOSdASoT1rIwRYcQdDD6hrK0FKQdBuYvhCdSZCZQlsZJWuxsjlgZnyZck7kqGAjKWya4QvMFKqgwNg5HRCU6pOlAfZmFnMXtFcgQgkotECoOv+Oyg3syxfsw+xOg2pSSq6t5FMRfF2RDFcQVDlEbVd2pw4wtHxpI0e95ChwA9U90O6yoHTK4HQkMSjLmkpCJvMoii/8ODNbBNYbQKnqvCAjKL+peA2Bup/PQd+ApzSkLDcp6K6naxj4Za6yFCgG5L9u9ZxRNmHvL35qx30/UXVfmf0pLr7xPyr5eiJswhTI4FzAFh152aWnzsOErAqORt4k3uXPw8jpgLwytCVTLj+h/nvj2DWpFMZc/pWVk2awK9O+Rn8Aaq738XwSerJ/jf3uoaT1igQ9PSklWTzblqHDrie5cCc43MqKLI3dJ1wIf6lz9N0zGTWTbiQbHYsD62Zx4612/jBtDjpn4xEXzmB6QuqueqGJkYdeSHL16zhuv4jadz2MCvf6ceE7YfywFvd+dvr1fxtRjVMWsnTk1Zy7IKhhKmR/HHGSsY9meL86yW3jlNgYPnDbzHq9hLGLkizuMdPKV/5bVZ9dzNThy5m7oFjGRUu4ruHTOWIZ+cX9+O6o8Zy+JbfM/0yZY3sr/+YP0xZxbErDqTLgO5MGDaJ/mMPLLqwKUOBs+hCh1D/lj+YXH1ZFY8MvZlF0xLwZIoH+q+EtdvI9P8z59+b4sQRUxHcxfiJU3j04XlcOWMQKwb2ZsSaTTy09T3uWz4ZOIdjFwwtrlt00kqWH34J5x9+CVvO2kT/sVWqG7ZIZfkAMOxCHjwevv63XT92dgnA/PWvf931OX6FS/dCRBAiAuUkJixTJblDB3ULOnQhvo+WdvBqYyDASocYGUUpE1IJ+XU3zNssSoysslAOdZ3QEpipgFyViR9VF/LYDldJa2wd4UusHWm1LMvsENrHrbyLlo4sCNjDvEA/5yALmpjOYKZzfovQlI6nmKWiK8c1KAIaYZkd9DEZqkF9wU5ZSmQY4nQrQfhgZpW2JTDBTkrMTFjMtIk2QLq7ht0SYqZUl8dMCaJ1GYKoumm5JaaiSJSqQ9FszSF1gyCmMnQAIi0hmRoNp2819od1EIZFAwLyoEXoav0LDmxFeljBqUwTiM42Zp3zZnR23keaAmliD8Hyn9audmHGtzz+/92JbG7vQZ/5/tRNq/+/rsee+r9ZoSGpTqRJWx7tERvPNRAbI8hKj9rydrrH28i6JpmMDhq0tsYJHR2j2cwHQUrC7jlKLA8pBW2pCFlpITSJY3voKQ0jrVreIoBctaJCqS6C0pyYafUQKShR198gpoBUGAlJxB32qWrgw6Ya/BIdzzWQgcBJ2pQnsrR7On5jVBkQRENEoClgFJH4KD1MaIDhKF+XwMpvuN5hDqB5SkdSuPRKoVzYRKC0M35Uien9hLKEFgHYTRrZPh56wmPvskYSukN5ZZpMwiJXI+mbD7ZMaSF6rcTSQ9raYwQ5Hc0VGG0G8S7t9ClvAaDViUIg0LMCLyEJIyGtjQmquyZpEVGkAX4ixEhp+IkQpKbMBAz1G5rtqpulBUrPI3XUensQRsBLhCqDx9Ex9BDT9HHSFlqjSZAICaWgNYgRSI099el6fd2FNFrfAOD8U7Zzx2VDuHLGIAauvAgj+iZwIKPCRXQZ0B1ugDOu2IR+ylnFLJZZo+9hwZQOncYrA58h/dI3mD50AD9+5BoWXv5rdqx9mEf/pKhMN4yex2N1KU6qTahBdl0KgJNqlXXxsbeN5rvcwFB3JH/6S5xhQPYnS3gi+hzr/vA8N697mIv6j2Sfn8D2Kw4FNvHAW02cNmwjG7Jw6oJ7WF+d4s+94TdzRvL6BQPyA3uKwKVQT09aqfQ+wHVTRnHFvOUw8SEOnjgMXoIzRx0FC34Ja2DGDLWPvrviBo54dj4vHjP5U/vypZ7/y0PT7ufQF4bQnV5cMQ9u33skpy64h/6XXcSaoTdz6oJ7aKreuSnxAPM4bdhGqrtPLGbePPDdX8KCe/jlpl/x3QMPh00HUtU4jJfy33n0YeVI3LjtYR5fpvbrA3nhf2HbCtt67IKhMA+eP2QYay6LcwGQvuAFQOl12ljGpr+M5Zur3mLgGzcCD+7SsfOlnlGzZs1i+PDhlJSU0KVLF0488UQ++OCDnabJ5XL8+Mc/pqqqikQiwfjx46mvr99pmk2bNnHccccRi8Xo0qULF198Mb7/+Z+e67lAdV8iOkHc7OhKFJ7Id9aH5PNJRNZBd0MCS2C1+litLlZTDrPNwWp1MZtzWG0umhtgpDwFjgyhWs5RHadUI1ehkasQeHEDr8TAi2uYKR/RlgJNQ8RjELEJulWT27sLqa91p/XgWhqO6ELLgdW0HtiFtoO7kT2gF7JHF0QsonQtltmhjdE+sf7QAVKgCGhkwfEsv73F7o8m8iGZOsKyaO9p4ccEbkLDbgtI1PlEGzysVg+rxcVq84nXeZR/FJDY5hLZkcVq80CorpWe9ZBCkK3SydTouAkNP6bjl9p4pTZ+1MDM+NitPkYmxE5KWvexkYlYB9DobHtsWsXfSrpuh2NcAWwaRsc0nZ3kCsYHsNM+k1KCtXsgmN3tPNnd6pP0sbm9B/1d8FL4fE/999Xudp6E0ZCI4ZFMRyiN59D1kCAiqahqZ0ztalK+jesYGNU5NXjfYUMgCCIhYVeHyIA2ZChoaYvTtKGCoC6GWBeDdXGSzXEVXmlJRWPSwI+Hir7lKvASmuCWS9zKAC3hkdmeQM8qypqe1ki3R+gTa8bxDHQ9VKjD0xA5nfasTeDraHlth4yEhJYkKAmhysEvC4oUqtAEL04RpHSmVZGfLVKtl8y7sUlNBT4G8ZAwIovTe+UhDEvStWcLR/f/gK52O9VmijG912AMTFLWv4Wo4TGgqgHTDPha9624rk6QMdCbTexGDd0VxGyX7rE2ukaT+KGGWeao/RMJERUuZoNJ1jUJSgNCAxXy6Qko9ZRMVAMj22EzbWTVe8pJTdHhcl1CvLKQIBHmkZkkYviM7PExvbs3IbrnMMtzvF9fy/yPD8EPdg8As7udJwf3v6X4d5cB3cmVNvL0pJXF99YtfpMuA7ozs7fJacM28u2h32bMs1M4/5TtnPj9x5k075Wd/t36o1ImzXuFWaPTLJhyaLE7U919IjeMnse1M1ez6s7NADxWl2L2Bnh8whOcMWo+WuIFqhqHAaCvnMC2ky9h4MqLAPjhjKv4wbQX2H7FoSzXxrE5meaWP5h0u+4VLln0MP3HHsgxJzYoTQkqkPKOu4fw2mCb/nn9ye/Cu3k634G5duZqlh/ezpUzBhGmRvJYXYpg6EJAdZ2UpgUEd/F43VwOXzGXM0cdxYO9L+O8s9/lwd6X8eIxk4v/fn5vNT+/t5qT7h5H97XKAjmSrOZHH73A3APHkittpO/6M5l//F08PeJNVvzsOZYcM48lxygg8sBbfZj85Dk7/Tbzj7+L6kte3+m9mTMv4jvzBgMgOYcLv+Mxa3Sax+pSvNTzfwGYMe9Mjl0wlGtnruaKecuL831pxFSOum8qV84YRPwXI9mw1707zbvrxRfu8nED/6KI//XXX+fhhx9m06ZNuK6702d//OOuuQcA/O1vf+PHP/4xw4cPx/d9Lr/8csaMGcP7779PPK74wOeffz5PPfUUCxcupKysjJ/85CecfPLJvPiiCtoJgoDjjjuO2tpaXnrpJbZv387pp5+OaZpcf/31n2u7/LiB7ml5oXmhc5F3HdMLT+zpcOACkBK7Po1TVoof19GdfNAjFIMtRdZTnv5COY4FMVOBlwodaSiNjJlRLX8/KkhsdjAa2tVyLJOgqgSnKoJbqvz9Cy1sLVB/a4HEtwV+F4NsdRlWsoTYlhRafTPSD1TIZGdXMiFQHs36zqGQoVRuXYUqBFeGEozCI7QQGbXxo2DkVMclsARWUuXY6BmVTeOXR3DKzLwVZpin2oGVVMBFagK3zMCLi2JOAELHi6l8GDMbEprq+1abn6ekmXhdSrCSqQ5QBSjeW6HdryEsq+P3CuhwGSs4qBX2g2apTpVhqA6XroOuIWMR/IoY7ZXAps91CH0htbudJ51rd9HAwOcDJp2n/aI6Ml+m69j/DxpZXdl7ALTLFPskP9up5v9n7W7niZbTWF9fDRtjaAdklN6kzMfxTFa09OPd9T3A1xB2AKEgNGWeR6VsjI/uvZaX6vrRsKkC3VEUrNh2QaaHRKR1NE/gl4ZKbC51zKSWH1hL3FoPvdXAr/DRrIDeXZvZtKMbZlLglUIQVTb9H7R3JZe2kI6OHvfRSzzi8RzZrEVpSZa2QKjOQouhQigdQeDYmK7AyFDUeoamAk0iVF2UzlSrMH+rNHKKIuaVQGhJ6OZQEs+R3Fai9IcCZNxnTL812JpPTHNxQoOXWvbivbpu5FojVPRqQhOSze3l2KZPbSTJ0J5beXtrD1xXI3B0rDZBWybKCrcPLTtKIBSYpQ5BWUBlbRuDqnbwUrAXQcZCOFremEAS2vn1tSRGThQ1S35UUcyMjLrfOFUBMuGDp4Ev0Nt1ZK2HHgvonmgjqrlUR1Ns10tx2y0CO8D3dCy5ezws2t3Ok8ld4ixPjmN8f5VwD8rBas3Qm3ko/0Q/SN3DjE1nEbz/PEx4gp83TOfPP+oGj8wvamYeGzkTgJNeUKr4s58+GoC7p0AVi7l+v1f4oGodcCDfeHAsI9Zs4vEJT/Dy8slcsvAERoWLqO4+kvnHw7ErDuRbt09m+/0mC0oncNgvjuLXM6/maK4i1e0VRoWLuGPlEG5dfyZbFh7KA2/14bQrDqXnhN4c+uxQXh6RYNyz8OIxk5k25+6dui6vDba56oYmrkyNBJQphZZ4gei0BK8NPo+TRg9ixYNjefy30H/sgTyWNwu49cGx3AF8d9MNf3dfxn8xkoPnDePBKcpC+vkzBnLUfQu544DzWPnOHQw94DxWDFTbnnzpveL+fuOQqfyg7zJeX/8W100ZxRmjFDXt2rEXAVXMmHEz19dv5vIRMHMlLJhyKIJVCO7ivuV3IejI2ymU5BxmzAC4txhQ+t0nITcRxk+cQvqCF0hXq2mPevUtrhsximGXnsOmvll4ddeOHSHl51MqL1iwgNNPP52xY8eyZMkSxowZw9q1a6mvr+ekk07innvu+Tyz26kaGhro0qULf/vb3xg9ejRtbW3U1NTw+9//nlNOOQWANWvWMGjQIF5++WVGjBjBX/7yF44//ni2bdtG167KIuLXv/41l156KQ0NDViW9Y8WCUAymaSsrIxRo3+GFZgEEQMtCLHWbldUpcIAWIY7fU8YRv7JvoHTt4pMF4t4nYPmBEVLZhFINNdHy/lIQ0NqGkGpRbbGIleuKRCQVvQyp0xH9ySJdW2IjAO2Rfu+5YSGoptJXc0viGiEOpipMM8dFgS2+qc76umW1ASJLTnMjQ1Iz9s5S6WwLbqu3v9HT00KwCdvVSwMnbBLBfWHl2MlpXLQ8SVmKsBM5sM8pSS0DVI9I+QqBGUfe2qa1lyRnhdaOk6lRaZGz7uT5e0+cxIrGeTpZTpWMsBM+zgVJrkyHSsdUvbKVtVl6fy7dLZN7rzuhZyXQidG66CWCS0PcmwLaVsEZVGy3aM072sgQnD0HB/Nupy2tjZKS0t3/UD+guvLPk8+HP0QJYbKXPi8AOY/TSMrdF/+3a7KFwFivmzb5C8KwBSAS6EKAGbPeaKqcJ70njUTvY8gGnPoV9nM6lf64de49OnRRLtj0bKhgt771hMxPD7c1kWlwe8w0TwVqtjl61tJ5mxaNlYgfIHdpGE3qw5AukeIldSUlsUXanAdglsZKtvlEBJrLFKDFC3ZKnEx3lYUmWz3ACQY1TkG99jGyg29qKhIsU9lI36orokfNHahOpFmw5ZqtFYTIy3QfIEflQrIBIoapuWv24ENbqnSkeh5oKK7FLsZkKdcmRQF8rI2R5g10Nt1whoXmTbACunarZUyO0eZrahiucDk3bW9iG408ROS6MBWupUmaXMi9CltIeebvLu5O2HWwKozVCOpX07ZImcNhBUgczrCDjFsn/LSDG0rqzHbBem+PkZS7wit3DuFm7EQzYriHFohdoNBaCujGmlIonslqYhlSbsmrW1xwpRJebck/SqaqI22syldgRfobG8vob2uhOqerTS3xDm823v8/ujf7zlP8lU4T54+ZCvzfla202dXX1ZFevQdzB43kdOGbeTe5c8zc+ZFrMtbASudBawY2Js7amZxgjwKgPeObeXKGR33givmLQdg08RyAB6oHVLsugCs/pnHoGtMVv+sI2T0x8ev4uCJwzixdiqP180tAqvnDxnGUa9+Wg++ZeGmnahTpYfvT/Kl97j6sioArrqhiUXHJxj3ZGqn9wpdlwJ17elJK1n6o7u5YfS8nehXj9WlWHXn5uJ2HbtCdXNW/GxnqfuFo+uK+pYwNZIr5i0nklQIQf99kuB/1TFXmM+Kgb2L2TFhaiSn1Sl3twF3Gqw910eb8E5RMzPm2SmM6lfNGnkL99fOAVRnCFCdqysE953Sm9OGbeSBt/oQpBQOOL1uGvfXzinqmo5doWhoufvjeQqZqoNencvMKfcyfVmcX15yFY/23bxL58nn7mlef/313Hrrrfz5z3/Gsizmzp3LmjVrmDhxIr179/68s9up2tqUaL6yUgVVvfHGG3iexzHHHFOcZuDAgfTu3ZuXX34ZgJdffpkhQ4YUTyKAsWPHkkwmee+9nW+0hXIch2QyudM/AKs+hdGWU3qVNgcZhh2OVWGgBsRBqITzhawVIcD1sDa3EG30cMpNgqiB1DWV5iuVq1YYNfFLbIJSK58bk7dfdCR6LlSp9E0eJaub0dqzBJUJGg+uxCnRlDtXILGbHCI7sphJn0iTj5nxsVo9Io05Ik0edmuA3eJj5CR+RJDtahN0q+wYqBeyTwqDfNdT4EVonWhVcud/QaCmcT3VfclrT8y0EubrnrJFFoEktDu6UqGlYeRCrJTES+h4iY6MmdBSJgXZSh0zLYntCIjv8LHbQ8xMiB/TVCdGAAK8uEFgirxPf77rUqB+hYH6PVyv4zcSmnrPMHbOtgll8bcD1GfRCF63CpoOrWHHISU0DzTIdQkRARi7qevll32e7C71nwIv/6l5/LdXXdl7nwIvu3N92edJj0H1dK1qw9BCVn3cQ3UdfA1b98m5JnpGwwl0nCBPhAhVLozmq4H/5ne60by1HGmHhCU+gS3J1UC2i7p+uaUhmpcXyLvqmiwNidBDIpst3HIJmsRsNPF2RHEqQ9xyiXAFZptGeWmGhOmgGyGlEYcSw6EpF+ej5moMLWT/8jp6dW9GVrr4CYlbGhLaCnzoOfVP+IoaRgh2s1qXwKYYBBlElJhfhB1uXn5CaURDV0c4GmFEIh2d2GYDe6tJw9pq1m6sZeXmnry9tQetuSha1Ce0JF4Xj1R7hEBqtKWjtORivL+tFm1LBKveIIhKjMFJRu+zjsrytKKuNVqgQc9uzZiWT1NzglBXoEsvdXdyGAsDDc0MCaN5IGhIZTftg1/hI7s4VCfSxEyXrokUvbs2M2CfbYzpvYbu0SSBFHywrSsf1VcrtzhP0J6xocmmwsr8x47t/2R92efJ1vu3cNqwjZw2bCPTr5fFrgBQHBBPXxZnzdCbSXV7hQfe6sNly6awYmBvti99nxMXnsAbE9cxv/ssVr5zB01PVdD0VAWHrUhx3ZRRXDdlFNqEd/jxkcdx4uHHMr7/Svr3/Zj+fT/mhOwiBlz8BCdkFxX/bVm4idkbQE+cxfj+Kzlp3MOseWEh3X9xOWteWMiaFxby/CHDeP6QYQRDFxYpZCeNe5jJ6xQQKz18f25ZVsvwVQ6Ljk8Ut+fKGYOK9sIFKttjdSm0xAuMe1JpcS5bNoXsnP5IzuHYFQey6s7N3LJMpWEetkJNM7/pYz6auhcjrjmaE7KLuHB0HQ9Nu7+47AJwWzP0Zq6cMYj3Zv+2qG1pvj1H+ZgWfn5vNWOencKYZ9W+1Ca8gzbhHdYtfhNtwjuECw9g8Lm9WHR8okjtOpl+RXexa2eu5tqZ6sFfeJ0sGgEUasa8M+n9cCuCuwhTI7ls2ZTiZ5HT1eCqQF/bsnATeuIs9JUTGHCj+ZnHz2fV56aQffTRRxx33HEAWJZFOp1GCMH555/PUUcdxdVXX/15ZwlAGIZMmzaNI444gsGDFb+urq4Oy7IoLy/fadquXbtSV1dXnKbzSVT4vPDZZ9WsWbM+cz2F64ERUW5g6ZwavENH5kqBfuXnuzKhBGwlok9nsTc2Q+9KnHITzZNK8xEqZzNpaHhl6n0vrgb60ZaAwNIIbUF0Wxa9NYPIOoQVCVoGJTByErvVJ7Q1zKSP5vgIP8RqcxWA0oQyHfBDQlNXeTS2aolbaXVVbusfp0xK9K2NHeCrSCPLl+9/2qYZijQ5IYTa3ryeRrg+ZjpE8wsaFGWAoGV9QksHVLhnplonXh+gu2p+oW2g53JoOQ+nOkqsUQVfikBiZAPccpNchY6Rk0SafUJDee1rvsoQ0F1JYHVa70KQZ6EKoMZzi0YGQjeRnXNzjE4Wy7pGav8uNO9r4FRJYtvBbpHoOQ27VeKy+9ko7w7nyT7LTqXuqCf+pfX/T4j5O2te/pPAY27vQXsE/n+nvkrABXaP86QqmiaIQMTwaa0vUbSqnMbWtjI818AvC2hNxQgCgRAwaJ+trKYHertOtE4jWqfhVAmsAUkq4xm2NdeiZ0HYeaASqk5NaEt0R2BkJPYOnZwhyXXzEZEAvcHCahUYaZ1sDx8toxGW+bgxjeb3q2FkPXt1bSTtWaxLVlPfVkK2NaI6NlpAKAXRhEPG1xApAwxJoElkm64uvUJRrERIMRNFSJVDo7vKzCW0lVjfTAvFVjYleosgyOnIaIC5w8RK6sS2S9r6q3loSQMvp6GVdDwZd7oEaGaAqIuwJVLO8J4beXdHd/zmCJar3NZECNWJNPvEdrBG74JwNUJLUlKT4oDKbWywK1kvqwidKF5CEjg6Rt5EINKqkW61MStyBMIEN6+dSelqnRMelqXYCgPL6ulht7DDLeXD9i5sz5XihzpuqGNHPDLbElT0aSEb9ehR0ca6tghfL3mfX/1LR/MXV7vDeRI+fhj39p0LwDcPeYuDXlV/K4G86g5sTioNRWL7oQSpe/j1zJt5fMZVnDR6E5ctm8INU0Zx7QGrefGYydz+1ku8seh84FBOBC5rfp/LrnuFEaM38TibgKfJTPldfumv7LQuQw84D4AHbmii9PD9OSG7CD4jyHHAxer+t3XhAcX3Gtd3g+O7cc/9Jmedro7bh7a+x6k99i9ux4qBvcnOSTEe1YV5dN1QTqpNsKLn/zJizSZgCiutFygs8Qd9l/HI0Jv54Yw4H94GFw98nO1Ll/GDvoWlbubE5cM4c/GbDOr2CoN4mEcfrmDDXvfSd/2ZGDcelaeBXcSiY3pxyrm9qKyN0LokwoqfPcegaxRYOP9eCPt2bAuoTsxJMxLMn6Nz4sITeF+cXNQOzZh3Jt948Bme+e7i4vT1N91CVeMwguPV6wK1D87hu08CpVDT9z7m50HLqQvUPmkjRc3C+5j+cCvXTRnFT5+9EPjxp/b5Z9XnBjAVFRW0t7cD0KNHD1atWsWQIUNobW0lk/nXnzD8+Mc/ZtWqVbzwwgv/fOJ/s6ZPn75Ttk0ymaRXr15ITVM2wV6AyDpF8PKptPeCsxUgs9kifUmks9hbWtG8UnLVFn7cIDSFSjTWhdJ+5F2zQkOgu4p6FanPoDenwA+QiSiZPqWYWUlsm6JcaV6g7IXDUAVdBpKgxAYB0lTdDC9uEEQ0jHSAnpNIXVd2lKEg0zNGSXMEku35AXyHxXCxU1GgW32STlbY1kIXSgoIQrJVyjI6tsPHTPtqneImwlcZL35Uwy0XWGmNnKU6TvE6kCKCV2IS2sr0wGh3lOObH6I5Ola7QHMlRtpTwMzS8WMGRjog1HW8qOjQtxTWv3NXKe8ipl7rHdqfQmCmpinaXSJGalAl9cOVJbaRT5I20wIrKfFiAq+zHfVuUrvDefLvVgGA/CtA5ovOe9kDYj5dXzXwArvHebJyfS8O+9p2+pc0sClRiR8IRCDIbipBahIrqRG0JpBAUOPhBAZ63EdmdJwK5SwmfMitL2GLnUCXysFLCwRWm46eA7O9EBApSXcTeKUhGCHxyixOziTUJbkqpZc0m3W8yoDSqjTtW0uxWwSh1Ei6Ng3NpURjDtl2JQTxt8d4vaw3O1pK8HIGwgiRdqjmUR6oPJisKNoniwBk/sFpaEg0T+CWynzuTYgs8RF1lrIeTmtIQ6KVu5SVpmlrqyTUBcm9wasIkXHVgkpUZOhemqR3ooW6lhL0MnUtD0xJ8GGCNbGutO4oIbFRx0gpRkBgwcbN1dzXcihu0kbzBGE0pGdZG8MSG/kwWYNhBLR3UwNMzQjRPBC+IFcTIqKBkr8GAuI+3ava2CIFEdtDCOhZ3sq3at9heHQ9tbrDm04tj6/5GoGn0aUmSXvWxvd1CCGViTB279Wsa6+hR68mVjs9gbVf+PH4eWp3OE/+0GV/js9rJF6fHqGrn3f1Qj3RP2PUfLotywON615BjL6LliUXMXvcRDQmcsNo9XQ/PRriv4ArH36Tx/74SJGaNQKVRXLs6KEAlI9p4bnWz37Q/uiMQVw7c7XqpKyDkAN4oHZIUbT+hymr+M68wZz10oPcc/h3WfxkT46bokT+x9x5Ec8+XsP4/itZVKkczu5jMg9tfY8TF57ASUDr0D+xarDN1SgqWXSVU6SKXbZsClsHfA82nFFc98cnPIHGAegPt5LYvokRa9Tgv/A5wDdXvEV9fv+t+NlzlI+BgTMv4soZd8Fy0PJ0tacnreTWld9mxJpNyvZ4CfTv+26RMja//ydiQ26A09aV8eQbg3ngOMF19cpQYfmE3vzqycEci3rdf+yBvHjMZJYcM+9T1LHC3/MntRGmRnLYin6EtSPzCziH0+reZR39iossH9PC3SNugDv/3lG0c31uADN69GieeeYZhgwZwoQJE5g6dSrPP/88zzzzDEcfffTnnR0AP/nJT3jyySdZtmwZPXv2LL5fW1uL67q0trbu9DSgvr6e2tra4jSvvrqz4qfgllGY5pNl2za2bX/6A00jjBhoKQeZy3UEI+r5vBTPVwnvbk4BGhmi7F9UJosMQ0QyhZV1MJtiZHuX4Uc1kCojJbCFopaFEjsZYiZ9zKY0oiUJmgamQa5HKUiIb1WdiiBqgisJIwZB1EDP+miuT2jrZGotrPYAKQROuYZvCxLZECMX4CV07KQPwiBToxOriKOlM3ndSMGNTCiRe2cZVGer6EKXSct3YDRDhVi2p4nvCHBKdKQm8GIGoZXvlngSIxMUA8y8qCBXrYLB/JhJ6SYljjTbAwVSPLU+QdQkiOj5zzy0jJv/LILuhXi2QWgI7GQIjtvRffmkNqlTtoviKfhKv+OGiIgNuo4sU/S85sEQ3SEwshS1Q26JIDAFTgU45u7VgdldzpMPRysH+X9XwP95uzGf5Ta2O9fC3z79petg/p36KgIX2H3OE5E0KTOz6IQILQRNIu0Qa7OlTF3ylxe3QrlwNaTihIGg28AdbNtQjQgEMuYjNAntCh24ZYqy65WGxDfr6C7YyYBspa5sl6s9ogmHdFsErdVEBOr6pnkKbHgh5BwTvcIhG9p8nKykPRshbLJItSstRzIZRbQabG8oI5Zw8B0Dwwow4i5uOkFkh4FXEioDGk/pXYKIelgmNYnZrqnwTB1kzyyxiIeU4NgBYaMNMq+f0QP2rmji432haWMF+EJ1ljKG2jcVsCOV4KDKTfSraWbthlqELqHcQ6QtGhtK0eMeoW7iVIJbJsj09hG6JNwQRyQUFUzLadSnEjxWP4y1H3RHxAJKu6TwXq/AqdaLXSLNFQg9pKIkQ/PHcXxpkHYtSuI5so5JGAoq7QypIMJLmX2o1FOsyXbHbzeJbTSpDzSO2X81m1IVDN93Iw+vVloFTUhMPaBU370oZLvLeQIKuAAcPCvHU9N/Bczm1B77k53Tn+i0dUxq7kPLkouYOfMirl0G33jwGW46IM5jiyZy7IoDufMq5ZQ19YC7SCx+k1euewVq53Fa3btkpvyOpyedzfiJisJUoC91rocmKY3G+IlTYOZ5DLhTDY1XlU5Au/zXLJiiBuaCVfxhyiqyE/vzmw1K57O+ei7jnt3Mi8dMJnobjGEKVw+2YebqomZnfP+VrOj5v0xqbuHKJRVcO3M133hwLPOXPsX8xAscumZn7Xj11w/nye3P8M2b3mLFz3rSUnsvZ3JUXqfSDy3xAtd+dA0At05P4ZtPFbsphZKcQ/NTf6TquJFMfvIcHpszl0duVlbMk59UDmPh63OAi1h1ywrGjJ+y0/eXHDOPAXcaPLTqbeZUnQ39oNt1rzDr8j5Mvn8LAOcdOR0eHMuvlt7H1ZfN55ZltbQsuYh1G/pxypQ4kdPThMxh5lEm780+h/nH31V0JFt8y2q++ZDqZq296QR+fPtkfn7N0eyTOohH/9MdmFWrVjF48GBuu+02crkcAFdccQWmafLSSy8xfvx4ZijLgV0uKSU//elPeeyxx1i6dCn9+vXb6fODDjoI0zR57rnnGD9+PAAffPABmzZt4rDDDgPgsMMO47rrrmPHjh106aKSR5955hlKS0vZb7+dXRH+WYWlEbQQaE3mKUeyI9ne9RTIAETnk7AgEBcCfIk0DITnQVMrUdfDLokRRg1CS0fPhehOgJbx0DIOIpPrAA+GjturCqfCwEoGhJZGaNo4lSaRJoGecnErLLxSGz1rkqsysNpDNCfEj+t5Vy+B166jBRKrXdk2e3H1E2e7xUnUtyJDqTopheDLwoC/kFRfoIoVuzL57TQ7aGcyDInW5Uh1iyvnsHief63lNT1OqDJvdB23VKVDG2lBvD7AavUUUAklwvUJIybS1Ami+fdClBFACNIyEFkPYWggwYsJyjbkKQWGoda1c9ZLQcivCeWaVujOOE7RcS2orWDrkSVkeoTEtmmUbArRPdVxMTMSu1W5ovkxDf65DvH/S+1u58l/sv5ZN+azOi67O3D5b6ivInjZ3c4TMyl4vb4XNXE1YNIyOmGpjx+TaL7ALQsxk+raZm+1kGss9C6Skp4ORqmLlIKw1YIQYj1SpOviWI6u7Io1yHYN0XyNZD+DXA+PSGWOwDHINsQwW3T0nLqWudUBWoVD2BBRmVsZU9klA3UNZcg2C83RCBIeyY/LCSMhdkbA+iipbgbV3duoiqXZ2lZGaEBsuyRlCNzqAOEJrGYdp5uPcDSVpRINEZUOMtCIWD5Ry8PQA9J6iOzlksta+K0WoinKulg1VfEMTSUJ9DqbUGqEEXXvTTXEiVTkCNBIeRZmg0lgSURtDrcqQABDe23hzaa96bZPA/XvdkVP6ejNOnpGIKSGH5VQ7dA1kaIxE0fEfWUWUK6skCk857JDjLQOWyOk4i6BJZGGxPF1KmMq7LNLeYpukTaqjXYWN+3PmsYulEQctJiP1WaScdT4IGp4RDSP/brXUWqosZKhhQRfbmpFsXa38wSg+bXZAKz42f6MuOZojni2ikfz4GXckynuuX8oJ9XexeBzexGdto7s0vc5ac0mysdczdOpCs7w53Pf8smkR99Bt+tUt+ayZVP48LZPLyt3f3yn17F53yNM3UX11w8nNu97/GLYYFqOE6SPDDi9y1GcxMM88rASrRcE9Wctq2XENUo4/40Hx1LGaP4yQtkvz9rv+9zU9AYtxwnOyC9jzLNTeOlMZcUcX6Zoaop+ZXA1VVx1QxNbB5TxQO0Qjt0A+8xawuPu5cwanaYin0t/66njgX0Y0Pwx4YyRwBjC383lg9cP5/a36vjRsMO5IHsb/cceyOBze/F43VwekVPhSbUOq+7czEBUt2jRMb04bAWc9uBPmdTch9Yl30NLvFDU8Ay406CNZVx1QxPjgKP8NryNc/nwNjht+0YeoI3G2Qfz8w3VPD3izeK+/Nb9W7i/Fj6cPob/+QlsPXga2oR3CMaWop3royXaWHzLJRw8K8fYC4fBwRAuPIAyzuBXS++DvsCqg3b5uNllAHPAAQcwfPhwzj33XCZNmgSApmlcdtllu7ywT9aPf/xjfv/73/PEE09QUlJS5E6WlZURjUYpKyvjnHPO4YILLqCyspLS0lJ++tOfcthhhzFixAgAxowZw3777cdpp53G7NmzqaurY8aMGfz4xz/+u2j/71Woa+g7kirFvZBu7/soJaAKQpRB2BH8CMpiGToGy0GgMkQ0HVra0NpSaJroZAaQD4OUUgEiTVNWydWlpLvbKkkZyFWZ5Mo1gohAdwyEL5XGJWIgAonVHmJkAkSoaGgiBDsJejZE80K8hIGfMNG8ELtNdX12ol7Bp8Ibi/kvrgemsTOlTBjFrocQAmNHEmQcPwLRxhAzFeKW6ditAZobIjUdM5W3oYyB3SrRs4oCp6Msq4O4BRJCS0MEEkyBH9PQcwbCC5D59dX8EN1RhgB2XQrp54GL73d0WoQGnq/ofobRaXtQNsmRCDIRpXFognSvgLI1OvEdAUZadazMlIbUBKYfEtoqK8HYTQDM7naewH/ePnlXqWF7wMsXX19F8AK733lipgSagIxn4TdFsds03JqAoFwQZkyCskBliGiSwNXQHR3NhY8bqrBsj14Vrazb3gs9J8h6JVDqw4Ach/bewPZMGdvbSmmPJLC7ZohpIdltCcykhuYINF+J5kNLEtmmk4urkEdqXEJXB0dDWiHS0YsdEyR0G7iDuqYyHCC+wcBcZ9LSVkVjopzoVoNI3rAliEq0jLo+e6UhlbVtZHI2OSOKiARE4y6uY+DmOxdR28NxTPbvtp2esVb+/Pow7G06rZTTVhZj7x4NrMt0AyGJVmXJNkcRnoaTtni7pQegrIylLrEtn6xmEi/LUhtpR1ohEUPdp3RX0dmCqCS+RdC6fwCBYM07vZVYv8IDOyS5rQTKAjAkOV11taQAu0WQ2ZJARkKMUhfXNaitSZLM2aQdi6QfxZM6m9vLyawro700ILLFpL1fyP6DNjMovp0Wdy9ebenLXolG+tkNbLCqMLWASm33cIXZ3c4TUDbJZ446ivD+LQzsV01IB03qkkUPs/qH73E9cCK/5Y25mzmp65Lidy9bNoXto5QVcXxZVVHwfnT5VcVpfhfe/allfk87m2MXDOWMCe/wdI/9eW3wahYd04+W40SxW1Oob654ixU/a+GP92+BcyH50nssOUZRtkYs2cSSY37PmXm3tA+q1inwkrcihoJY/X93mmfBMaxznVb3LvePOIfvPjmM+MrzYPTNPL3paxwK/LT3jxm48iJWvnMH2qKJhDMVDe32t14iPfoO9r3qdZ7iV/Cc6nBMPfou5s+4i/ETp/Dow/M47WB1jmgT3mFAYYFz9mdB5UYe2rqI+5aPZPK0gHce34rDXox7djNPvXkwlT+K8PaT59BU3cjQn8DscX0IUyOZevKHDLjzY6oab2b+pLM4deg9PJhvvh08K8fmZBpjwjuc2mP/Ik3uuo+uoX3Rwdx51etcUP99jPUn8+6G3tT0vY8ea3/HDaPnET9x1ylku2yjvHz5cu655x4eeeQRwjBk/PjxnHvuuYwaNWrXlvRZC+8swO5U99xzD2eeeSagApUuvPBCHnroIRzHYezYsdx+++07tSk3btzIeeedx9KlS4nH45xxxhnccMMNGMau4bOCnd8xtd9H9+mw4+2c1p5/r0Aj45P6iEKyfd6VrBh8WQiQ7By6mAc4wlItv7CilNSAMqQGdouPnvVp3i9GYAmMrMRuD9EdJWD3IwIjJzEyIWbGV7oaXeCWGhhZ1eERXki21sbIhIgQchU60Saf6LpGZDpTXBehaxR//oIAXs+DtgK4KXQ68qL4wt8iYuPtVUvT4CiRFklsu4Mf07FaHIKYSWgI/LiO5kmSvQ2kpuyU7aYcoW0gDVGkUIhA4pUYOOVK45Ko8zFTPqGhgJee9vBKLUJTI/7uNkXv+4RWRwZhMe9GCKEAmOeDbSsKYDRCav+ubD9C3cir3gsx0wFuQsdqD9CdUIE8lNNZrtqkqbfLuhu/fBvl3e08+bLq/xd4+U9rYL4MGtm/aqH8r4CX3cVGeXc7T/r9/Dr0/QJMM8BdW0qkQZAemsW0fbR3SnDLQ8KohISHtsPGbhZF0OH1ctivz3beW9cDo9lUVC1PUbW88kCl3LsaZlLgx/Ii/pRyalR5LPlIGU85m+VqAsx2DbcqQMtpisLlCSKNSmifOUCt1xG9P2b5hr3w2m3sbSZOb+WYZG2z8KMSu0UjVx2CLtGymgJf8ZBIVZayeJaG5hKkrxFJOERtl3TWxvcMwkCg19kEtQ7jB7/Fnz4cgtsSwSzPEYl4xG2XnGuiaSFHdl/HypaebG4sJ9geQ3OEMiqozeK1Ku0nukTYAd/e/x3ebu7BwVWb+OPSQzGyAq88xGzVCCISrXsWvyGCntUwsoLAlvgJRSsLEoGyUM4bEJB3gHO7+pglDl3KUxhayPgeb7HdLSOhOxxTsoqcNDljyfcxWnXMdkG0UdI6KseJg95mv9g2PKlTY7TTHkYwRcC1b48jDAWju67iniMf3nOe5Ktwnjx17q+Yd0zId5+EXqVxjrz9bJb+6G62X3Eop/bYnznTzmaoO5Jfz7wazj6a1knqif919WMw+0zlsaX/w0sjplKx4C0uueYOLn//UK6rH0P7BwMp2XcNV+TBzmXLpnDD6HlFcPLYoolcsuhhbhitdCXlY1qKNKzVG0Zz921PMb/7rGLifMFmGCjqRcLUyJ0+e6B2CNVfPxyA4/wOGtQT0XE8velrPPPdxVw5YxDX1Y9hjbylOJ/J68qY31/pRLTECwSpe5i+LM7scROpHH4JAJe8fAVvP/LHYgepYDhQKO17U7mi65Li8gH+p+bgnaYZesB5RRvl2ZGnuCR3HLMjT/He8NbiNKlur/A97WzKV36b5/42kPB3ylRh3eI3GfDIfcX9OX7iFBLbD8W/9Hm0g6cx4E6Duc+dw8GzVNexjWXs1ThV7a/j7+pYz0SH3urqy6pYe67PkL6biP7gAH46txeX936G0YfX7NJ5sssdmFGjRjFq1Ch++ctf8vDDD3PvvffyP//zP/Tv359zzjmHM8444+9yH/9e7Qp2ikQi/OpXv+JXv/r7/h19+vRh0aJFn2vZn7k+ngfC/DR46VRC19UgX+YDHk1j5zR36HgvVIJxsjk1n4K+pDDfMCSsKqdt/3J0T2KmQgJLw0vYBLag4kMXqQmSvQ00DyJtIZGWQGWqJF1CW8dLGGi+okC19zSx2g3sNuUQFpoqi0bzJXrGhyBQFy/b7OimFIBAgTZWCPAs7BPf71hvr8OJTPoB5sYGYl164pZo+HGjKLqXmnJe63ARAzupuiiaGyjjAQRCStxSEy+uke6qkRzqYNRbRFs0lTvgqA5TaBsEEZ34+lYFXoJQrYfrFfe3KADIIFT7X9NBz9PlLBOvtpwdBxtIoZ7i+REB6IQmBLaGH9XQAuXsZrX6ZGo0ct07HHC+zNrdzpMvo77KnZevuhbmq1K73XkiwXMMNE3iRyVuqSBsN9GiHn5cEmnUcEslnqkGwppPXlcikK7OjnQCPRrglwmEq+hZZpvAajEIouDnE+2NjNK3+AnVRVE5YB1hkqEliXRP460vwWrQcXt4CE2i1Vl4JRDfIsnusPE0m+eb98PeoWOayh5ZtwOCpIXb1UNkdKV1kaCn1DU62z1AuALXMRAJiQwFWpNJ1tGwa33CQCP0NGRGR+oS0/ZJ6A7Dem7hjaA3XcpTNCbjZNIRgqSJ1ajzRHuMeMzh63t9yAvmXjjrS4lv0dDXxWkbEKJVO5iWTyLq0MNu4cmGwQR5JoSREmieEtH7MYmXMTEymup0oaG5YLRr+IkQo03Pd2yEsrgGQgN131A/H6V2jo9yNWzLljGopI73nR4sbx2AllUxCbE6SaoPSF9jed3eVPTK0M1sJSdN3sv0YFTJB1iWTy5n8nF71b9/TP0Harc7T4CKMTczcGYd9sz1jBuXYuu6Mnpc9zvKV36bUX+rpv0DOCG7iPsmqfwXLfEC1F+Dv1c1/7PkcgaMOpQnxtzMbAbA+xUA3DB6nsooeetnhKmRzBqdZubM1TDzPIavcjh2wTxmjT6HwmindUkF455dzS391TJ+e/NxPD1i3k7gpFCnrStj3YZ+DLj4Cc5rmF6c5rPAC6h1p/c45j53Dqc99BtuOr2Fo8t/x5gLppCbYDC/fxsNf/gW0w56l/n94ZSJcWYnJha/3/DXQbxb1xvtYPieFvDaYJu15+78EPcvk1I83XUlsJL5cwpjzd/sNM3ac+HIXodw9A/ug5nKIIHX4IG3+nDtR9fw5k8HAnDsgqGMP+BE3jwAHu06iCN7HcLS5ZO5jjGcVvducV/s/1o5zaVxtgJrz/UJLnqRp48TSM7h8BXLmH/8Xeq3SikAc+3M1aw9V4G1k8Y9zNp1Ppkpv6P5J4tZeeoJ/HLqE1x28Pm7fNx8bhF/PB7nrLPO4qyzzmLdunXcc889/OpXv+LKK6/k2GOP5U9/+tPnneXuWZ1BTKF7IjSU6l39LaWP8HyklEqnAR1UMtHptZnfzYWuRgEgRGwy/UoxMyEikOQqdOUWkwoo+9jDaPdAQKwxT6Vy1ZM1PZsX1wcSPyoQUon4QxNFyTLU+qlwTA0rFSpdiRBqXQsdFttCxiLIqEWQsAktDS9uYGQC7Lp2RDqbD7oMOgVgFi5+IdLzKFnTTMvQKtK1BrEdvgoRK9FxE1qxWxRtDjFTStcTRE3l8qYJvFJD3YBzIV6pBoEgiCpwYQvwE6YCRbam6HJtqZ0vvp2BZBCAbqpuSyjVnVvXEKYJQpDpHkFqBY2NwI9IdFc517glKhg01hjksws0ok0hImmw5Qs4tPbUV7Me2fSbz3z/lN4/+P+8Jv+4vqgAyz31+cpqEziaul7pWYGVBKnrZKM2tqtAh5AQ2Wqq0Ecdpf0zQE/qNMhy0CRazCc0dEJX4MdBzwk0BwwE5EFKEJHoOaGsgWOhokRFAoSjI4Vkr/Ik6xMxhK1BTkOUenjlAZ4V4vSVGBGPMNARjbZ6qBOVGGlB2GJjtGvIXh5h2kDqEJb6CN9A+EJ1YQBRZ9MgSpGBIIwoSlZrcxyyaiBlpHT8kgDbCHh62yBaUzF8R6euqQyxJUJQ7SmL5qgCQRWxLO1ehH1rdvDWjjhewiCwlWFA16o2Gt7qSltfjTY/hmkGNLbHCSMhbrkgiIVoriBar+G4ptofger4647AK1XrpwUqC8ZIK+AjNSAiIacRmDoRw6dvvIkRiY9w4zrbvQpueGcs7o4YVrvqlrnlSssUSTjUJtr50+Yh1CbaKTVzrG7qwoh9P6JrSYr163tQX1vy5RyIu3ndeviv0ZdcxNpzp8GG3iyaFjA5PwB/5ruLWX5MNUcsO49u3AGjVeflygRcuffPYJNH6cyr+db9W+D0niRfeo/r6q9hjbyF6+ov5Ip84OVly6Ywa7Si8D33mzN4qO9U7ls+GT1xFnBW0T0LLuJbR94HQMOGM5CcwwO1Hd2D8gXKmOGBSfD0tJU8dDGMWLOJ+2vncH39Zu7/ay9qvr6aAY/cx9pTzih+r//YA3n6wbGMWPMSc94YzeQN/djHhRWTDSILfa7tdw1v3ncaA385nDA1kqaXD+EGfyyvfHsxf2uAw1fM5YERQ1gxsDffre/JXOD8BQnWyFt22pfHLhjK7MhTXJz7407vt9yugGjljyKc0Xcq9swOet0luePQEi+w9pQzaHp5LisHLQYqOPRPYwF4lHnFaa/ouoSnJwUcu0B1c5pH31H8rGHDGUwffy0Azy+9klH9Tsbu1cpfN9+jgGO+BtxpcO33ruHKRT9j9PAV8PIKuG0EQ38ykn3q7+aG3vDoPz1qVH1uANO5+vfvz+WXX06fPn2YPn06Tz311L8zuy+/Ah8Ms+hsJX1fDYgNo4OypOvqfSGU1kKGxSAsQtmhu+iceC/ygngNNdC2bUTEJtevmsASRJo83HID3ZPoOaV1AZC6UOL/bFjMQ5E6uGUmZlqowM2sxItraJ7quJhZie5KjLSPFkj8qOqEAKrjYppgGoSlMdL9SshU68WEZM2HwFL6FH2AhdUuKfsog7G1Gem6CMPoCL7Mb69oSVL+vkHDweVkagzidR6hIUh30zDSYLUrUT/kU5kNDc0PlTW0VLQ3o92jxodmx8LIgJENSPa2ibQF+LZycIutbUI6Tv436NQdKzS/rPzvFiotTdEWWtOQsQjZKg2/fxbb9tBeLlOBarbATIfYyUAFZXYCf1YyxMjuHh2Y/+v1ZXZf/h5o+axp/hGQ+Sp0Yb6q2pfdtfwIyBYLR1iYHuhZMGyBm1VuizL/kFQE+ZR6A9AUeAhiIVpKR/MEfheJEfXxARGYyqkxfymUhTu4VB0TaUiMlIZXERCryBKzPVxfp8R0MCtzBNtjGBUOZSVZGtvLqaxJks7a9KlqYXt7CRmATRHMNg23PEQaIX5NQHkiS2vGwNpu4pfolA5ooS0ZI8wYKozSCtm32w4+3NoFUe4ihERKgWwzsXumyBpRhB0gpaBuQxVGm47WM4dp+WitgtA0oMZB32Ggr46yucGmba8IZdEcmqPWJbRDtFKPusYyhAFsi/Ji9V6M6LUBL9R53+qK4xlIKchtTZDe1+HkA95iVWt31m2vwVwdRUjUg6xA4JWF6GktT89TgCa01W+AgE07KmlIxenVv5nuZiuHxT9kY78qlniD8HM2dpOGlwBZ6lGRyLBvST1uoFNq5hiYqCPpRXgr04cKO4Os9KiK7x4amN2tvrPjPYw/vUKPob/LC9wDHqgdwml8jwdGDwHeZNoch9c4j6dvdzjyxUMIN4/kyF6HALB0SQVz3tiLvU9fT+nh+/PDP+zFtIPgmYNbQcWWcMPoecVOy9LNr3Ikc/Pfv4BvvF7OMwe38tfNqqsw4E6DdYvfpGbhAVxfXw0outdAcSHhurnc0n8yKwb25o25Y3Yyxb68q4oYOH+B0u5s3DCXPn0VhWrd4jd57pH7eObgWlbdbPD0X1/iLwzjlMNGcGiDAgr7/GQx7Qxkdp+p0ACzD7uOJ9/ZwrINd3DxiEEI7uKmA05k6AHnoX1PzXfytIDv1v+ouA7lY1pwb32PmY8psf5zv1EgatwFzxWnWbThavZHAZj9XytnduQp3l1XRrgOegFLNw9hdkSN5d8b3sqRGw5R27FZgcFjFwzl6UkruW7uJcR/dx63LKvlhOw75DbMZRFXs6q/wdQZ87lixiAOW5hCjOhwq7tlWS0Xjq6j/YOBlJ62P6wey9u/foWWza/yy0c3M3+Ozh+f2fVjZ5c1MJ+sZcuWcffdd/Poo4+iaRoTJ07knHPOKYq8vkpV4GIeXX4ahhFVb3a2EO4kzheFLoaudQCUgvi9899B0EElK6bch0U3LFlTSa5nCUZKuXL5cR3NlWiBRPgSp9LAbFchkE6FiRcVGI7MP0VSQCayw8Ett5CGenrkRzTsVh8jEyhaVEInsBS4SXzUhtaWRlomXvcymvaLEBqC0s0+UhM4JVreCCAgsAShIZSlsK2miW1MozcnwXFVtkonXY+wTILaCnYML8XIgZcQeT2PxE4GeHEN3ZXojsRudtHcAK/EwitR/GOr1VNgLU85C6Ia2UodM6OocTWvNENjS4dov2CyUNivnatgsGAqBb6wLWQ8SsMRNTQeEhCtzmAvLSW2Q2mRQlPkAV+IH9NwE4oaoHkSkczwypM/+9I5y7tLfRkamC8DvBQ0MLsCXj6r/hGQ+aJBzL/TfflXAczuooHZXapwnvS/+Hr0SAQ/rix6zXZlaOKVSMx2pVcRIRgZim5YfkS5Y0lddVU0T6C5CtSIYhdBdWEKdLHQlmiOwC2XWP3acbYkkKbEqskwsOsO1jbUAKBpksz2hAqzjIYIVyC6OoStlnIpa7GJ1Om4ZSFGRhAa+XWJ5TU3GXW9rhzYRM+SVt76sA96s4nUVbdGH9ROtilKpDJHIurQ3BJH0yWGGeDsiGG2avhxiZ4R6K7AqQwo79tK++pK/JIA7BCjscMK1i8JELEArdEkrPbQrHz2Wn2kuP4lvZPEbJfGlhL8jKH0MYFAeBoyEtC3dwMbP6hVlLessm/O1QYYaWV2IEK1P400IMCpBD8q1bKlQCt3+cHXlhERPofHPqQuKOXilaeQ2xanYpVGrlqQ2y/Lvj3q6Zto5qNkNRO7v06VkeLPTUNpcaOkPZsPV/dAi7Xw8VnX7zlP8tX5fnLP4d9lcHJhnto1lGtnqlDK3ISOZ+yXHfFbjl0wlNPq3i2CjG7XvcINo+dR/fXDueTlK7h+9OH8cMZV9Hj0Yvapb+KNuZdw66QU5y9IFLUbBeDTp+9UNm5Q+o6lm19VA/kNvQFFF1sxsDfbql9h9aNn8MzBrfR67S7+fLqymx57/CjaDlFjjIIFdGe9yfNnzOX4g1YVX2em/I7nWq8uupBdOWMQ1V8/nOP8H1N/0y28Pj1C419f4rAVKV4ekeCMUfMZ8Mh9xeU2bDiDaXPuZs60s8lNMKg6bAR/a8hbRx99F7csq2XENUcT/4XS5DS9vIKlm3e2uQbVvQIF7sY1dHRh3hveStgplBOU2H//18pZVHM1ffIdq8I8CroYe+Z6mpcs5tczr8bwjuPgWTmOeFaZF1w5YxAVT0keeuBtXhtss6p0QnHe1sSHPrVuPdYqAKvXxziwoeU/q4EB2LZtG/feey/33nsv69at4/DDD2fevHlMnDiReDz+z2ewu1colfAb8rqPfPaLZRVBS1EkXqg8razYrSkAmc8KQRSaEu9HI6T7luLHNIysTxDRCU11MRVOSHtvC6dMENshsNsCslV5V6ycxMiFIBXNKdstQqgr4b80FOlZGgI/puOUGxi5ECupdCSEICM22X4VZLoYWO0SzZcIHwQSKx0qR66sonplalS2i5CQqdZxEyVEmmPE1jZCezrfbcrbMQN6fStdV0i2jyon20WS2EIRvBQAkQhC3FITaVhkanTspLJb9mN6Xo8TEkQ1MtVqnvHtDua2NmhuRZgmsmAoAHnKGB2AJQ9mCmJ+fF91YAIV2ik1iH9sEGwrzQd85i00A9B8iVOho/mguxKnTGBmhOrk7Kn/k/WvgpfCd/8eiPkiOzF7qGO7V+kuCCsPMiwV8KtyrgS6ozowmk9HNyZQ39FdRU9y8iGQmpu/tukKqIQm6DnVMXBjktCGwJJoPTPkUjZ2i4ZXGuKkLarsNN5Heyl9zYAUwlVam0CXaIFG0G5CLO/gldZwy0JCSxIEal0BoptM/KjEqwywd+g0t8WpjGbAV9fHMBIi2g1y2+PoVQ6aFpKwHcq7ZxleuZENmSpWmbVk28sRAXiVAZ4EPaORytiElkTPaoikjgC8ag8tEqA12uBoiEDQtWsrth6waW1XRI3DoB71rP64O65nkPmgXM0jQDmqFbRBO3Tq1/cgGkLk8Ea6lbTjhxobmyoJQ0HwcRypgwgF2a4KLIam0khiSkTEIx7P4YQmdV4Z290yetgtdClNsWVDAq9EkO0W0LOmlYTpsC1TxobGSt4q7cMOJ8GmZAVxy6UxFYeEzz5dGvn4SzgOd/c65u4hcCe8eMxkPmx4gn0mreRp4DXmo/WbmqctrQTU4PmgaSs5dsEQWD4ZRquuwzfv/w3Pb8jBaPh45fNsf3MZv+v2CqXdLuaSPu9AHyC3RDmWXXGoGoxvnsxpde+yefg5CgD99TiuExeyRt7C9fu9QvC/pZzdfzLQyNg/uLicytiHO9a77FUXgKNPcvPvPI//wlEAHHXfVHr8RL374W3w6MPzuGzZVcowYLR6KLfPrCWsZUn+b9gHsCccxWXzR8CyV7j1qhSD18Hm4efw19ohyslrBfzyoxRf7/86Vx3wB15/cxk/GraavVnPip89B63Pcfmyl3BmnMfRUNTJdNbvAHzj9XKi1yvRPADL4cjh5+z8w2yYy0b17INw4QHFz69gCdcC6dF3kF6yWO2D8qv4W8PrxX2y8p07KG+9mmumpvjLym9z5ZpNzI7cCIC3cS4HTQ2Y1NyHpzd9jWN7vw3A0NUrGP9ogvnzvwVj7t2lY2eXAcw3v/lNnn32Waqrqzn99NM5++yz2XfffXf161+Jkr6PNPI6CgBdR+T1KwXQUnS4KtgSS6mCufhEqGKhC2MYRdcxpBpch4kY6a66uoF5FiJU4nGkJFdt0rYPeIkQI6sG0tFGxWnWnVC5e0W0/GuJ3aYslCUqHFLqglBX1CgRSkJD5G2WQ9zupTQPUhQEK6m6DFIHq83HalPdFM3xEdIg2qQAVZCnWZmZULmEHdiV0g/a0JqS4PvFpHvpeWgNrdS+rLFjeAmhKZSJgFDAq+D04pTrZLqqbk+sQW23U6njR9SNVUhJpCUkvjmDsa05b6yg7KuRoaKGFfavJjpsrHXtE591MkzQNfVE01ZP2yItEjehYbWH2G0K4Pi2pgBdfr2MTIj3rzUn99R/qL7M7su/W/+IVvafBjF7gMvuWVKHIK4G05oPBQ6L5nUI7SEPcJRUj9BSgCY0FGCRkRCvwJjNqhl4XTzAxEyKvAmJEtZrUlBSniHZTSfeJU2m3Wb5x3tjtarvBRLCeABCxyx3kO0xjFYdmTdpiTQK0vu52OttgqgkNBXY8hJSrb8mcXp69O/aRLmdhbAg4gnx+2cpS2TZu7IRNzTI+iaDyuqoMNM83TSITMYmKA0wK3PsXdNM0rVpWNUFrzUC0RC91CXI622EFSqZaJcc1uoYRhrqNlZRWtuO2aLhhRarMz2w6g2cMp1oqyDT10fk9CIVzy8LsVp1/LjErQ44vudaYprL2209cDfHkZYkks47YQrVFUMo7UyQCIlVZrBNH12TbM4pUbgTmryf7EZTOoY0wC0FSnw2b6ukrr6W6MBWKkoyvN7Qi4amEsKcQWWtcpmSnkYXu/0LP+a+ypWbYND6bApUHmbeLasDvAAcNHV2sUNz5QwlLj969H3csqwnF906Ca6ByMIL2bhhLkuXv0rTH8czrgGiPziA8sNOIDFEdVDOGKVyYwbcafDn0xdzQnYR/WfexXmVOX7VbGD0bWTg0+V8NP1j7hr/IG/MvpQ/TFnFioGqQ1MYdH80dS+qjmvhO/MGc/7tSZ69Ss1fPvYtAMRJfyaxXdmAbx3wPaq/3nE/+PDrMO22E3feCU+D2PdZbp2UouGvg/grKn/m9Lq7+MupP2D+U6v5+thBDF7ns3T7TTS9PJe9565XJgH5WlRzNUtnDGLFwN68NvZFAB6YqwT0Ny1roXVJBSsG9uZXspXqr3+Hxr++xJG9DuHtX7+CnNu60+oMXT222Pl6+ojf8tpgG35zBs/95hDG5alvF+f+yG3dfg7bb8J/AfRVd3HQKhj6v+fR/kySEe8fysz3ZuPyHjP2v4Ty01qYdFofTsguonXNZE6oWUSq2ys8N+hqxgPLt+x6jtAuAxjTNHnkkUc4/vjj0Tu7af0XlbBtBPkuS2ETAzoGyygHD+H56rUUHR2BznQyUBd26MhUCQvTCYJSGy8hMNMSLy7QfJVgL0JJWz+N+GaJnQS7zSc01WdqcC3Rc4WOA1itPsJXr4OI0rroTgiGQDggjfzTuoyHNHXS3SyMtCx2GryYQAsUbcuP6piZ/JO4jLIwjjaEeKUGVquPNAS6I0nX6uTKy6l5U0evawHpIV1PaYYAfWsj3ZpTZPeqItnHwo8JIs0hVjbEi2l4cZG/MUrSXXR0D/yoeqJYstnB2tKCcDzwvCJ4Ua5j2s7WyXlaX5Hm56ogyyLQ1DWl18kncUabQgJLx0oqO+owz1SQGug5ieGECB/0XIDuqX3qW3sAzJ769+rvdWP+EyBmD3DZvUtq4FYE6mFTo3I8lCq3Es1VQKYwnezEiBWBkmGY7RpSQFgSgCfQPA2zXeD3CNH2TuH4unL4yukYLQZlpRkO7LKZVZFu7FdRz3OvDUambLLdA6LdUwyt3c6++9bT5kdZ3VrLh46BMELClAlWSKpUgKtoXmZKkO3jElohdtSjPJEhCDUa6suIGy5R3UNLeMgSEM0WRHw0LcTQQtpdg7jh8tfN+3Bwt80MrNpBrtygpn+KD1q7MrxqIwDzN1eipfI04mqfbvs2s35dLXgaGD5BxiDb24MQIttNss3lBAmJjAcYTSbSBLtJXd+1tNILORUSaSrgl+0J0doUlbEcT67fnyDQcNptdSsXFG38QyNPyROq6xQ6GrapAjgTpkuTE6dnrJUD4xv4IHkYcdslbUgCWyKzOon1Bm6pJJsz+XqvD3nqg8GEno4R9ziqx4dkA4unGocQyj0d/X9Wa8/1ee1Om+d+cwZH/+C+IqXs6UkrlTPWxCl8TzubawerrJmlm19l6YxBHLla0cIKlLOlm1/lyF6HsKq/war+1/HBmAOYdtB9yDvnc+/+N+eXdg4zZkCNt5pTe+zPpBPPZi/glsrD4d4r4d7juOtMJUqvvynGkRzCGTWKSnVCjQIM9x03me/MG4z/wlHcBLx1wBZ+e8YDMOxw7hr/IM6MveCHbyI5B5jGNx/6DQPuVOu4bvGbfPhDZbH8yWpZclHxb8k5bB6uXM4uuOE29rltK3N+8jiND8+jfEwLoEwCCtUf6LP4TeTy53l1+lMcMqscgBkzbua2QT/n0T+ORa4ZwgO1m5B/HQQM4q+bgeOGQEe8DmeOOkoFS/Jbqr9+OPPnvMvwaQ4P5XU90ZMPIPubd7ht6s/J/uYdml6+mqrDRmCsb8TbOBf998nivMp+eyoAp01vhfsVpS5V/grjJ04hhQoePbr8KpKXr6Fl8Z//+YGSr10GMP817mL/oKRfyA3Rdxocy7xd76f80/N0s2J4Ih0WheKTnZhCV0DT0NyASLPEzCqKV67SwC1R+gvNh3h9iN3qIXyJH9MV9cAPCSJ5upajOisI0NyAMGqgOyFeiaJiaV6ouh+GwEz56O053NoS0rUaJZsDdE+q/BgBTomG5iv9TWhohCWWEtk7QX47VNCkkfUxBZhpDbdEsP2IUrq9JNC3NRX3D0GghPaeR3RVlsjmEnK9yvBKDUJTZdiEpuJ8WyllQBCrczBaMoh0FplzwPVUN6pQhUydAngpaIx0DfywQwujhWr5QYDIGy0gNGQYgh9gZEO8hJ43KlC6F6nlu1qWRrqrTmJbQGirUYTuhZjte0T8/5fq39W+/L36RyAGPp8uZg9o+eqU5kJkh0FgSYyMKJq9FKhjBfqYCMHXUNks+c8LuSRCKkcyPasedEkDtEYLp1xDswNkxgArxE+E6FrIvrF6NqYq8aVydURA930aOLb7+7R4MeqcUta3V/NxfRXllSmyjkW/HvU0ZuI0bKqgulcrTbkK7BYdkdUxS1xM08cPdI7oth6/i06faCN3vncEhhVQWZqmvqUaWRehbXuE17ooKnlpaZZUQ5xXw94M6lLPkLJtdDGTvLq9D5uyFSQMF+FoSEMSmpJcyqasS1ZpbdoMQl1i1ZlIA4KeOdz+Pta6qNpXwsBqyT+okgoIdnkN0t0EueFpjui3ng3tlWzYXENFPMu2dTVE6nWCuCSWVPc9NNWNLxjYBBGU65qlHvC1p6K4EYNIqc/qHV3ZFKmgR58WMp5JeSRLvRkS36aTRic1wMNoNgiaovzJOYDomgiWgNx+AfVOCUk3CqFgW+bLy9Da3esPU1ZR3f9wlm4ewtOrVsIRv/3UNE9PWsnTk84GYPgqB/Kg5ulJKzlj63xuPn8crUsqimJzUHbGGzfM5YKLn2b18zGunDGIUyZ2yB1i877HkxcN5tgFQzl64sidlldw4QJ49Ncf5v/6Cb8+eAw3RcfxruYyY9Sz1K+4hVG/XMPFR/ej/caHKblU2R9P4098+5jJ1Cw8gNNRmpKNG+ayb9MpzNj/Es6AvK6kgiN7HVIU/O/z660AfFD1TQD2bfoLH9RNY+nmIWzs5fPUT9RYs+mpimJI5aULLuM3R88oru/GDXO5beqjvDpdvZacg0C5qY0/+VGOrrmP8oYE8POdtnmf+iYe2voe/cceyPBVDrfcPhiAB7vezvlzL+G1wXO5cvlkqr9+OPt8/yEs4Cdzf07FaGUf3fLwEJ4bczgfTd2LvU8bwCVb1nJd/Rgm7/sntp6rQNa+B47iVOCh95UTSX3Pa7h3ZDMAz/zmDDInrYU/fOrn/8z6t1zI/ttKCKFASZ4iJqWiFBWE+4AaJOs6BLIYRKkoYkrU3hnkKHqVumsJ0+qgpgklyNd8iVuiE5gCLyEIdfU0qNCNgTyA0ARBREdIBTwCu+NmGFo6bomJ5oXF5YZ5HYyRDTGasuD5eAmD+HYFmKQhcMo0DEeJ2J1SnUhzgB/V0bxQpThbSpcTRDU0Ry1X8ySxHT5WSiPZR6fhwARVpoa5saHDISxPmZOeB00tRJrbiNpWfp92rGMBmEhHcSYlKJBS6HS5XhEUFh3dCkClQN0rdLu0sGhrXfiN1DQhhBrC9bCaXaKNBq0DVHBmfJuiuIlAgiEpyZsZBHaHMYDI7OnA7Kn/TP0zXczuULVt++9xIvsPlghBywGhILTAyFKkk0kdtIzqhIeGyiIJIiq7RM+q6UNbEkYkVpOGkRFkugdojqY6Bs0moa00I0QlRrtG06oabvv4G8hIwObycoyMCrlMWA4akndae7B+ezVh0kTParQkTEROZ4vpE7dduvZppnuijUa7DLdcQ/gC39NxkzZhVYb1qWrG1agnwW5LBL3EQ0qBKHeRrZZiYzXZJPq2kclZoEmEgLp0KSWmQ5meZVB1Pd0iSTZnKhDlLvv33s6qd/tgbrV4S/bGbNWV1ibm4tsWRkZgrInilkmCgSl6VLWxeUclTmCr/ZAV+FU+TqUB/VPIQONvr+2HUZ1DtBtsf78LsiQg2y9AbzaQQmBkVdffj0OoqxBQM6n0ngiB1MFrs0jEczi+cjXzfJ3ndgykLRMlYvhgSqRQFDshjTwtUMPeGinqmyLvR3l56/4E3dS9sSGd+JKOxK9GTT06b1ecp4gNX+Vww4vfL1KYQNGgQHVqBtxpsLbuXVgwlAGP3MeOoy/j+Unn8fqVS5ix/yUs3fwqxy68haUj3uSv/JYtZ3bhvfKV/HLqxQBkf/MO9N3EkL5qsc4BewEqENLso8DEopqr6Xpxhh/Rg8HJhawqncA7H21j7B9G8e6i58hNmMX8vbcyv+ljeP01/h97bx5nSVGm+39jycyz1V5dXd1NswgIDKDsCF4XFBsUnVGY3xVcYNQR3Lh4URmRQS+DuADjwKjXKzMugCLOjMi4sa8qKFsj0LIICt1Ab9W1nDpbLhHx+yPynKqGhu6Ghqab83w+9alTefJERuapyIwnnvd9XoC//vfbO+d05Wvu4vDfHccdpxZ4cvXNLAI+d9l9cNmxcHVehwWvwrz59Rfyd78ZhE/Bhf98IbusuYLTdn8QMXoKjvP44hc/zXXfPqBTYyY7/23s9aqPcuAX/8zZc87ijHvezYOf9tdnl500993zbgCuOAbmcD9wMGfcM3O9x264heFDDmbshls62+5Y8iPcYft4l7OTzuaaQd259qdxNeRFMFff4H+37Zp1egR7/+Rmbj/6XB45yV/HR056BSdwOOKx5Xxz/C/Iib/m3DuuYiL8I3sdfT97zfru/+HS8wBYNLWY3W3IAxvyD0OXwKwNpdp8w4cjzaoFI/JQMVEs+Mm1mjXRDYMZlSW3SSbLfBhaO7TM+UJaBNqHCxiHrhmEg+JKA0qQlnzifFDLcEJ0vh2nQDd9rRgTSWwgUa08JE0JxnfVZCUYWmIQOQEK6sYnqycpSEmrXyGsQxjnHc8ycutliCYtMvVWzWlFYYoSEwiSisQUoLTaEjQyRG7vnFYUMs9bW7NniSExQvDnFZ60wEz+ibM+TwYgTTsJ9Z16ODoPrROz8oesL0gptM7JjJqVVyT9NWwfIxQzdXe09g9zN4sktZWbOEFXW/T/SZEVCzRGHWkZkh6JzEJUYmn1KYTz34tqeQUmU13Jv4tNh2cjMV1sfXC5Ha9M/W8nZ8LGdB3KK0wnLyYp+zpeaY8gK858RqSCZMiS9grozbCASyTBmgCR53jYNEDXfZ2ZrKio72hxTpCVLU475pWqDOoaY7UybiJEDcXM2WGaNZMVTLNI/dE+GhmYkmVlMEAwrlEtQbBzld5SC+dEp1BkywXcMbU9IvP5L9v3jft2nA95S0YyrBMk9ZBgVUAdaDxZ4cnKAL8Jd2TH0dUMRzWWrB4liDLuu3c7yo8qkJD2+bpg5ZE6c3pqPDpWRCUK0RKUlgsassSj4wWQEC2sIwRkqUJaQfhXdcpRwsTiOZRWCeqtEm4wRU5oRNMXAUV622mnwQW5+pXnIgV1r8TYwPkCnnVJnGqSzD/LWknAg3+az9yFE0zHEUJbajv45FPVFL7mz3BGmimcEKgUvyrnfJFLVVWYSvd5si5c+8F7OfzSvToV4q/Mk/jBO4+1twFcCZ0J9ZX33c3ho3tx3Ot+yF3zfs8R/+9rjIxvx4MXvZX3r/DKxbmf/zBcPcCi8W8zv34t/3bfzZx4n1fYhw86iy+8yi/1fze8kg8mOcH80ndYcOeFLDl8kjfjrX9XPflZRub/mnultyP+9NvezMIr5/KBW37AHW/2cVeLz1i7atwFx13MEHDJXbfgPj0PuJ8bjjiSLx+/jNPmXs33vCEY8vSL6F/kidPnvv/P/PzYbTj3f38YgAE8OVh9g1edDl92G++//VXsKj7FXvsdxj/ffBV73X8GoDnl1tO4d99tuXh0T58jk4fRHXqlV3za7msLb/8Ou4pPcdpcT2LahSmPe90PcV/ch4f+PmOXsUOBswF4y3jG4qNe3yFOtXm/57/+o0647+6I1ik4PsTeP7mZ+X/zYz71+n24+WM9LD7q9YzdcEsnV+l0duPML57Pj+6LuXO/U7Dcz9f23pWJIwRXHn039zz81z53Z9lt/PX/PoiftP2v14MugXkqZod8tRPE80mxcw4BnfovwEwOBvjfMn+vHeIEeb6GxQmLyAyykaKbvkBjUMt8dXolCciQEwZT1D4BX0pUI0M1Re6a5bBBSDjlP2NDH14WTTka2zha/RJpQMU+Ib38ZAzW4ipFsiLopiArK6a38bkgWaR8Ammu2FgNrUFJ3O9jgZM+hzSCoCYpCOFza5yjsrRBaaVXoVojEdPbFuif6keO+XjMTq2Yjt2yyYvAzCoIqvL8oU5xT2aCwDtOY/n3IXNLZO0tqDvXuv3ZzPjzbH9Xs8wUROBVMlFvEgSKnscD/5DfOWG7bcdYk8yn8gSkZUFptcFqgSlIhFE4sw6b5i62Smyq5P314cUkMY3H5wJQ2mblBn+mq8JsOtgARJTntxgfsmRC0C2/UGJC0TE3cYrcrdHvm5UcWclhywbRktiSYXBomvHlfYhUklX8QouuC1IFacWR9IHpzZCljEAb5u62gpVTPUgcqdPsMLCGuyfK9Faa7D38BPfruTT76qxcOoiaVsieFFsLyEqOnkdhqtLL9I4wt3caKRzbliaomQKPTA3hAouzggfHRjATES70/d17l0e5f+UowyNVpopFaAa4yEImcGsKPF7oZ7xZIjOSpBngAku8b2sm7OuRuQwXW6TGk5qs7BUqmUA0JpGpxIbA0h5PPMhzjaIC9X6L0pD2+pxK2/J5MbohEEZgtXeeNCHgPIkURoAEO6smj1P+JwoyUqOwVhAEGYPbrSHJNBNTZZgIkYl3LdNNTzrDNcoXYu6BeEELoRymGnpbZyOoVwub75/xJYxDv+sdstqT7StZxKLdv8bVS07u7NMmLU+FPfNYdj7yCf70kQO57uhpxl93ErscuQcPDr2V8z5xOTo9greM38w1g5o3Pno+i4Ab8eFXa355P+9Z1LYOPoVr8a+HjpiA38D44AAfzfbjsLcD/BbwqsuC134G+u6iuGqYwy/di5vGT2Y0uZ8Ljnt9p18Dd72DnfYZ55yzQ4696ARG5n+Fd1z0OBdxJB/9yc/oX3M8Z4lT6V9doVm4hy+f9Db+5dwacALwSyavHmDZ4f6+fdGlFWAZZ51+NWFhd04ZPQJ75ijZm3fgQxd9h11FP8EffgXzT+scv22h/JY7+jktJy83LrsNe+axvOmCD3HRsoW4M4/ly8ev4F+OOZizLq3Af13IA7lr2fbvPpA7uBqWwH5nLoKP3cfYpbdw3Ot+SGX5gRy74lXcyyd54/4f4oZlsPio17OYb/LQ4A4MDJ7AHO6nf9EEp7Mba345wNARE/zjP57Lv/3PMvvKD3a+T3vmsfzwvHv5TOsyHt/95yw4/jP8l2kBs+zengXdGdpszM5xaU+i20RFipnwsFm1YZilxLgknflcexKv8h8pOpNukaQ+vjnzE3pb1D7PJbWkvSFWCWQzI5j2Mocw3hxAppZwMkbFBqelT9IP/fELK/P6JVnuPFa3PrckzbAF748fNKx/aOYuN9Pb+7yUoGGRqVvrPRN5O0+Rxwjb0OfuyJbxxgEWUD4ESzio79gLkbebflp9lnbRz3ahT5mTF+NrsXSumZ7h087YGWWlXMRuN5fmnttQe/V8Jl+zgKn959N85QjNnUdIdhjBjA5BX2Um7KxtNCFyopNmyGqD8mM1Bh/MKD8csuy+UayG5rAkq3jHtdo2krFXKSZ3DmkOB3Sx+fBikYoXG5s6x6aNxuNz1/p5pu2z31sXRqd2f0H693KDzMDmOR7tXJeg7g1MwmnXycOzgSDpFaQ9/r5rit4Vyw2mPnk/EYhEMlhqIosZTjnsvBbJYL5I4w20sHMSCoMtbDWg9mgfjz00Svx4hd889gp+8sTeJNYn7QvhuH9yLlPNAv9z27von1fFhs7ftgPLvF1WUdvGh0dFQUor8/fU2GquXr4bKx+ag4j8sevN0D8LQoue3+APS7dBSsvUdJEsUT4Px4Ksal93RTjGVvey8/AYI3Oq7PbKJygWE/qCJq/sW4WspKxa08uK8d5OgUxTsbjAkwrRVjVy0tcaMbS2Tfz6WGgxZYuJHDITBOM+3M4U/Pcgc7ICnhBlJUgrkPTh7/+F3AUu86SnOl2k2QhJYs3cnhqHznsQJS2m5SMYvMFCRnNBRjJgKazx9c/MNi32f8VjvO4VjwCgphSmbJHa0sXTce0H78WeeSyQh1fBM5KXK4++u7Pv4ZfuhTz9Ij532X18b9FVjL/uJL58/Aruve4iLvy3cwB464++zWhyP/bMY7l7t6tYePt3WPNL7yp31Ed25uiDVnP0Qav56ZIa39r+VL61/al8ccnZvPtf9+Cj2UxdlzYWXjmXiX1+zv/d8Qkev910lKHz7nz9WvvJ0y/i0/sdtta2i0f3ZODSxQB8+fgVyA+fxInnLyS5cwnq3NcCvgjm/pf28JbxjL3jd7F3/C7+5ega59wwxoNDb2XJ/pOd9sP7vs2e2y8l2O4kRpP7OaV1BLuKT3WOd9bKRZ3aN+2/5ekXcf3xu3LIwnv5wNWHEWx3Eqfc6onPjcGvkP/fPVw8uifvve8irj38v/jTRxbwpvu+xeGX7sXwIQfz5H+/u9PeinA33nJHP+7MlC+86se8Yc5+vOLyJgOLzmWPhzPGX+fD8IaOmMCeeSyPH/4l/nPPSe48/xT6F03w72cHfDf6EW+4aB+uOvpEFrz2M3z5+BXr/id5BnQVmNmwBmQ+abXO51bMLlI5K7m/nSzeSTKHmTows92y2iFT4PNnkgQRaMKphLQnQKSW5twCqmUJqykytah6iqrF2GKAsNLnt+T5IwKJMD5fJe5TqNTXctGNPOzA+bouMnOIpo+9NQWd15GxxL0KHITTjqwkvCtZ6tBNQ9ITElUdUdUxvY0kK/u6BFZ7lcaGiqRPkxUk09tJhu5LO6ERzSFFaaQftWxVxx6UdrFPa3yuSzt3xZiZa2To7AN0wsaE1ohCgWybIVrDBZJeiW76nB2r89hx5Wu1eKMBheiPkK1eVCNBNGJEreG/AmsRUkKcoMYM5cziRC/CKFpD3kdTGmgN+HOOhw3RuKIxd+t02+tibcwmSi8UuXihsT5S8kz7b4w608XGISvhV/eDPB8moVN7CkGnPpYJcrITeIJjIghqgswGqFSgWpA5aKYB5Z4WNScQykGa3/sUmD7DwGCNaq2IakjUwgbpWJHK9lOE2vDkmj76epq4TDJdK1IIMpwTVFSLejOksFriJoqYeSnNJMCGkC6MGQwy+qIWbx1ZwnVju7LsyUFU6i2ZXUOjeg30plR6W9TGyuhxzZvffB+3rtiB6UbEvPlrWLZqEDGpMQtbLOyfZBnwxydHMZkk6VPUH+njV83d2W5kHGcEanmE2K6BHUggVjhlcTWJ0z53BeiE3qmmxGa+MGbW9KYApujIKo5gSnbCpIX1lsnt0GeZgmz6136xzhOS1vwMAouoBrjpACK/WJcaRZ9q0kgC79wWOHRNYBuKvu2miFNNI+3Blg1aOta0yvxlxTDBuEK1BK2+lG2GJ3nsRf0P3DLwpl2/hDz9IuAA//vomWrvQMeBbF1okxnwpODUC0aBUb505B7wjT343GU7AX7Cv9f9h7Fsf9jlGD/tvXr1nuhv7grAVQCX3cd3I19gcRRYedwhzL3wBj4YH9PZ/oG8T+9b+THAKy1XfRM++eHPdEjM4BFHAt+h90vf4QeXHcWHrv0Ev7hzD/rPn2D8zD3oZw9gBQ/97XEcx3Gw5AlOufU0zj7oLP7l6Bpv/ZF/HrV/X3HMCehvF7j4hj05at7vObvwS8Dn57Dan/vFo3v67dvBcfsfx/cWXcVpp1/UuX5v/O0BnHrBKPJ0eNMFD3DolX9LuG8/S/afZPfb+3nA/TOjCXz/19f7YBi+w43L4Ljt4bqHVvHmPU4AfP5bu+Bl+uqDufEPv2Jinzn87KB5XPMf/0r/Itj/0h7gFmDXXPF5AC54AJa8Ay54gGuAz1z8bn7w9Unu28l/F4ffkHLl0Sfzpv2O58mrL4RtN+Q/p0tg1oJf9bdrF6uUYsYeWdEpcClkfumse1rYEuDVhCzz4U/t7e3Je5ygGin1bfzdWDd9zRaTh3QFiQ+tspHuWD0K48BaTEWjGqkPPVAC2fBJ94Vx55PyFQRNS/RkDVoxKIVqZZioQH2uRjcduuUtlBvzHKXlPmQK4Ve06sMS3XDYEIorHYVJR2NY+mT/gSDvp6C+nUGYgN7HjA+PSBytkQKlqQoiTnCtGKF1p05MJ8zOOnA++LhT/LONtjqjNfT30ti+H2EcQS1DNwW6nmKKmrSifRKscZA6VG7/7LTERgpTLMFQCV0ro6ZbiMnpGQOBDGS1QeVPjmiixPS2EXE/pGUIMkc4ISiulAR1x+TIJv336qKLTY6NJS7P9PmnEpm2CtMNJ3vukAmQCpz0KjW5XTICssgvmlid58pYvwhlgzzkLPPqtg3zBZZU8MSTg77hRPqck5boWB6bHpiqlnzY1GhMGmvUtKTZDKkMTJPWA5pRRlROCIOMSpCweqKHJ5IBKqWYlqtgtUPEksmJMq7XoFaHTFRKKOH47eSOrG6WEbX8uddS6KoiKxjKvS1qyyuITNC/+xpeUVzN1Y1dsY9UeGJ7yY6jq1lR7uHQhQ8ihWNescoND+yCiyXRcAYOrJVMNouemElwTjA8NM34VBkT+/oupuDzU9rhYCr2Lmu0r1/N5xGpBNIen//TcX7TDl0VpL1eDcsqoGt58WjnHeDSPlDlDKkM4vGQtF/gQlCljKlmgZvX7EyjEcF0AH0pYjpC1yVTUyXk6pDCpCCaDEjLmodro4Srfb5r/0ErMVbyuv5HuIUu1oX3r7iXC888FtgVuHut2i+wNom5esnJcHT7nbtZtPvXgJkaMcOHHAzf2IOPPvplBngH8vSLSPY4gevf7Rlre5X/xuCb8PG1+/Fj4N3/XuSD8TFwAUzsU2HgLjok5vF99mebu27nf19awY0dCkd61WiXNVfwre3zRpbAtYcfQPVzi3jLHXDa6J64Iz7Ely5exmmnX0T/pfvw0N96peTCX7+X5N0n8OGBBZ0ckyfDmzv9GU3u560/+jYrwt24ZlB3nNF+NecMjjryJ5x4/m0c97ofMqwP5pqfHMZocj8XtdJ9WAUAAQAASURBVM5jaJ8LWbnHRwjv+zaHX7oX1x+/a04SPa49/L9422p/j//0aT/muA/7gpmHcC9vucMrN/9+dsCC8L8AOOe6v3Da3FsYTe5nz+2X8qs5ZxD84RauGdRccvU9/OygeZxd+CWfufoy3v3v/jjXnH4RXz9pGTu/dg27T87jH+vXdo7vrnyC9514Gp+9Yv+OicBhl36dQ6/chWt22IkHOGVD/m26BGY22uFHbdcxoQMf5mSM/9sYn+PScb8SMxPz3MK3XUxR2DR3MYvXLnyZ7ytqTcJqmbRHEVYNqpFhCoq0RyNcEdXMkM3MO48FClMMUI0EVc/DypwjmshQiaUg84ddIFACSo/VkdN1rzwAspEgjKM1JCg/mccBF6CwWtCzzHgFZdAbAbTJS3PEYgNJOO0oTFp00yIT6y2OBZQf0wQ1/4CQzpEVJK0BRaFcQCVp7uJmZtzC2kYHkLuJ5WFlxuQWyHRCxhjso77TADYQlJ5s5g5ovi0RKILpzIeuZRbRtq3OLKKZ4pTAFIOOKmNHKgRCICaq3lK5fU2AME4YnIiwxYD6giJp2ROX4ljGxCsDkqGu5L+5cdLS+1/QgpabK0xtU+TCPF/ysq621kVkuiTmuUFmQOpX+DvquJ0hLe1cC5vX2PKqgsD2+2RyYQXO5k6YBqLHA8Ip4R25Qt8W+eQ7XKOwVYXKYJ83/Jn7V8+lNhYinizyZN2zorgVYK1Aa0OkM3oqTaZySSOeY7FFg57UhAtieuZUGVsyh73mPUHmJNYJlq/s945qAZSWalQM032atKCQiaS8/RQ7D6zmruq2JCtLPg10KuKhifmopuRX6e7su2AZZR0zMjLF7oMr+PWjr0A1BakRTFZLjAxVqRYTkjjw4VqxgqbCFLySQo9D5MTFtYMlejOyVoBuCZC+ODN5mTanZ4wTbADpNjF77bCMlgm4/08LwAp6R6eZmihBS1GMUqwVJNvGuExCIrFKMTXRxx/WVBB1hWpIits0qU2G6LrANTTR9tOwAzSeqFBYpZA1hQlhp32Xsmf/k1z52G4UVUIXT8f1D3yOcHQvYO3QsafiqaQG6JCX9us3LnyA+4B/3P0UBnf/EF/abxmnAeF934bTZ8Kqrjz67o5F8OAP/LGv+2kvD/1/13PH7gnfXfIjDvzkzpy4486Qe2L9gL35yf/7E/vvfgj/cnSNi397KwBX7Q1w61r9uha4Zr9Jrj9+V65ecjd3nr+Mz81dyCELD+DGo2/j6N97YkBeULP1r77g5L6nfJXWD/Yi/J9e8XnPtp/nayv+s9Pul15/MHvdfxhHHfmTzrZf6m8Cnuz8/NhtuPLGce496ldcc/NhXD14Au7MtENekj1O4Mb7vs3wIQdz6JVL2PlOr06xYsYwgd8ezxevPJsVR8CKxfCnjyyAA+E4jmO/fV4PvIqjgNtOneT9KwD6uWZQc/vrD2ZOegQfPPMYBn99Plw9wE8uO4rDlu3Jsd//JN/7t6uQp1/E+1fcy4ND8OCx8L8vPYS5F7ZD9S/iQ6ccy8RPX4A6MC8HuCzDCeknuUrhmi2Q0qsEqfFiSHsSDpC5mZwL6WOphBDeHjjLZohQmnnlpm0d7FJEKyFa2cAGZVTTKy7NOf6LDOoCpyQuUohGgogtuu7rmaAVthTipC9a6eSMa5mTypsCTDcgTjypsg45Vae8qo+psnfaCmuWWEkGH0sprGqS9EckPSEy8S44TkJQg6zoHwblJ9OOow5A3ONdyHQDXz8m8HVVsqIg64+QtWZeSHIWAchtltvqlsvaVcTsjJolBfSUaezQj24YdD1FNn28gq3k59zK8vov4JTP+xFJ5mMayC2oY4OwFqcl6WCJrK+ILAaosSqu0fImA7mTnKg1kGFA3/IJbH+FdKBIWtGEU46eRjdFbGvGU8nLlhQ+tinJy1PbfSY1BrqKzMagnbPRsU1O/ITaBj6cyeVExmrIysKHNSUQVEGUfT4i5In9ed5HVvBJ6LbgoCVwgUOmgmR+ggotWUMz0Sox0lPDbC+pry4RPRlgInBVhZrfJFCGUGb0F1s8MDWXKMgoLJymlSfGD5SbrJqseEMA4Xhyuo8VS0YoTEqSPovpzzCFEN0CXVX0b9tkbI7mFQPj7Nf3GNeP7QJWkPUZ9JRCxV41adVChqMamVW8evgJFvUv4ZHqMI+NRggrGB6YZse+NVRLBe5/YpRIGQqVhBYhoqrQKbk85UlJVgSEo9jbomkEwWMB2FzFCnx+kUwg7fW1XQCCQsZA2OTP0yX0uEY4aA0EhKUUExniVkCpHDPSV+Px5YO4wFLsadEUkQ+tMZ641WsF6E/IVADCkaaKtBEi+xOK29fZZ2gVv/vtbjyyYg4PPjZK6aGI/3zVPsB1m+vf8SWNK4++m6/89gCu9qkgaxWvXBdxufP8U9j3pLORp1/ElUfPqDDXH78r4vSAq47+vxx2KZ2wqbNWLuLcO67i1LtGgWNZtPuxXD3o51tH83tWnlNi75/czN5Ha64ZFHz23P05BLjvKcc96iM7A/CTT9/PAax78ev2i2/g8Ev34otLzuZ67mPR7l/jc3MD0j00983RDO90sPcEYIZ8/N2nd+Y9P72MH7eOYGBHx6nbLwV80NZb5v89AG8BvsTB3L3bVdx9v3dM+/puy/j48E58c+wspo6/ggtfdx9vPf0ivrjkIN44/Dau4Tss+njGNWi+uOTsPCn/bt638mBumncy6asP5oqV7+LNh57Aot2bfOnIPfjHZadwKH/bOZ9X/teFPOD+GaBTV2bP7ZdyUW6hfNH5cNaSXSB/NJx2+oNMXP1pBhady6H/8rfcsPuDfOnvRlg4ehFvXHgAy3I3NIBlTMJ+ewNww7I9OWThvSy6/j72WeeVfTq6BGYWhJIIIdtRW568COHDoNqvnQ/lQsr8t8Cl2cwkHMDZTmiUaM/6nfVKjDGAwqUparxKVArIyhqrfCJnWHWIzCHjzIcd5P0A72xmiwFOCmwgSQckumExkUQ4RziVET4xCVM1fw7tRPbMUFid4ERIUDOYoqTyREY4lWAjjdOS4hpDVvAuZcJCcYWvRZBUQMz1A70w0bZB9g/luF+gY5/Xolv+gdGcE6Ini6jpem50kM04sqm8boHweTydnKL29S8USBb0IxOLamaoasuHhVVCTMEbHfhkHumNDfDPs7Y64/LzdZHC4V/rml/1spFG9FeQSertntvFLvPrg7PIJCWqNoiAchiQBpbudG3z44VWYdr4221PeFFJzEvVVnldJKaNp5KZbsL/M0Nk7dwX/wywgSctbSVGtRzxgMgn+HQcyVRMZ8ItjE8st4EnOmmPw5SsV2cChzCCZMDSM9BACUddhTz00HwKKzU2cKjIkfRbH/7swNQDJlPF4mqJ3p4m1T/3E1QlCEd5ShD3O55YNuTzayoZtzz8CuTKiKDmHbdsAINzq4zbPkwe4hwqw/DANI+MDwGwfLoHmfjcnqDqz6/2Ch++du/EfFqZZrueCZSwVMIYNamxJcvYRA9xqpnfW8WkkseWDiMCiwqtV6vIw8PKPnzMDHlpJcskspCRlXSuvPvrYiOfuK8bvkCl27FOoA2/eewVJFMRxbrvW/znMjZwmLIF5aglilYzJFgWEk0K0p4QVfLFSKM1ENQcrekirSGHmRejtMNaSe9gncxIpusFGIK9XvMn9ulbxi3jr+DBaC5vmf/n7vNkA/FU0vJUV7J2uFh7vzaRAeBocJedweEJiNMD3r/iXm4MM85ZUuSmD3+GZft/iH9YuYDDTu/h6iUn43b/GnLZRXz9jOWceP5CAC7+7VzulX+/Vh9OaR3B1XucwPV7fJTDL92LK8J38dW5T/APKxcAcMnSf+K8O1/PHadfjVh5LafmhgRD+1zIBILzHv4lZ8+5l1Vv2on3X/9wp93+RROIwS/w9x97CHXIeXAIHUHn06f9mHPP8onz1zx5GOOvOwmZh2YBfHz4NL45dhYnnr+Q9694K1868gpO2eME/t/N28Oav4e5V3PVNz+IPP0izvvE5Xzlrbdz+KV7MXaDD//64pV/y13D13LOsr9wzQWTnLfTw7zx4QO4dqFXiG5YtieCq0n2+AbBfRlXhuO8Nfkp21xdZyE+nG3pTb/gc9zH4K/PZ/LqAa7Kiefk1QP84+6ncMjCAwguGeKqbx7Lwg9/hgv/7Ry+fPwKPjd34dO+9xuW7ck1X90JPtgNIdt4CJk7ZbXJRh6eJESnUCUwQ2ZgZhtPsVdWaiY/po32ZL3txpUZ9Mop7MIBspKmZ1nWcVixRY1sZthyhGxlEChvoxxqsrIm6fW2xzhJUDME1RS9ugrT9fwYnij51xbVykh6CuiWRTV9zRdfF8YSjhtMKSAthQTTPtSs53Gfl5MVBM050j9gHYRVQ1Q1NEY0aQ8UxvEuY8676sT9Erl9hd7Vk+DSvLCl9b/b+TDtkDyYCa/TGjM6wNT2BXTsqCwzuNAXxczK3vrYRAJpFDJxBNUUFRtEM+2E+Xly5F1v0DKvuOy/N5kYTCUC04+cnPb1adoESgpILE4YaDT9912dRshuCNnWiC3d3eyFUl82Fl3ysh7kqrVKPJmBPKxJelJiIp+En5Xo1AxBe2es2bkZMgPsjB1zcbkC4a2TbeA/Nz1WRgQWqgEqFrRGM8KBFnZFCXozxESALRmwAqUtWVNTVxFO+gKbwbS3Ag7qArksIO21GKERxitBIvNELLKC8RV9qGmFXdAiiDIOn/dHLII7JrbjvsfnY5qK0oQgcYq0xxHPcaj+hLge8ufqCEI7xqfLzCtM8YrKGA8tnIONNSZRxKlm+XQPA4M1JiYquJZCF1vY1F8TU3C4koGmRoaGecNTZFayaqwXlecEIRy66p9ZMhFEE1DbzhFF3rjALCsRZCI/J29F7bTPM0oHM/TqABtolPXhejIVhJPCK2m5GlYYc8hEMF0JYCDBrSqQLUwphCmNsRK/v3k3ssGMAw/+C3v1P85Yo8yv7t8d+Mkz/LN00QlhAr7y2+O5cdltHXXly8evgAvWJjH2TK+k+NcAdwNwz+VPcOedSxC7n8IV4bu4BLj96GnSVx/Mk9u/mgP/8zvcueYKzj1rd+Dd/Pv+XwD248Tz4ZWv24/zf+8n1n67x/xHJVe+9m4Ov/Tb/PA8BSvu5f3HHMzYDbdxI3BF+C7es+3n2VXU8QFkMHL9w4zdcAufWnIO/5jndJxy62l8mh93kvbHbriF/kW+z6e0jqA/mMiPeBpfev3BDP4a0otXcM4NY+yf143Z5ub/4KtHwR+mT2CXcx/mth9NcuXRa+gf3449b96dc667lgtPO5u/v/0M/v5rLfrBJ/jfCn9/yhH0L5pgr/sP48Zlt/GPu/t+nbVyEZ997QXccfqMa9m+e9/KW1YuAxZxGn5h765li3jjfgfwD4f+iLuW+bnmv3yhRhZ46+c2iZxdIPPGZbdhv/lBAHYVn+Lcs97Np0/7MV8+fhmnXjDK1UtO5rBLvw6AOzNFfOriDf6fEa5TYv7li2q1Sl9fH2/ufR8qr/0homhmoq3kWkQFmHEha1sqt5F/BmsRgfZEph1C1vmw7VgGiyDADfaRDpaIc0lTJt4yWTcNpqAIJluIzJIOFMnKirhXoRJHcVWCqiWoyZpXEdJ0Jmk+TWZsiMMAV4wYe+0oTkJhypOTwuoEkfoJvClo6vPDjp1ylO/jlKA5qEh6vSITTnoFpjXsK0cP3G878cZhzVLd1ifYz7tpArFizYxq1S5imc5yaAN/XcIAEQQ0/2oejRHdsYEurUpIS5qkz187EwrCmidgYTX1KlXL5wl5gwSLSDNcMcKUQ2ScdWrFOC19eEFRo6daiPEpr8S0v7t2QU1jO25pmU24bvz7TE1N0dvbu4n+27ZctMfJ5sLzVWE2hri8mErMxqowz5fAtNWVDWlnY1zKuuPEoz1OdvlfX0L0FLyq0vL1X9r5L+2QMJwPhZKZ30e43Na35FUGmfj3hMnrlwgIpj3pyUpgIp/0biKfzB9MC5qj1i/e9CfoKMOkCjcR4rTzrl2BN6RxwlFYpdF1X/PLachK1tc3KTqccBSXa0zkfB6P8UUbs6J/FmYDGdFAizft8CcGgzp/rI6SWM3Dq4ZJlpf9OWpHONIgaYT0DdRJMq9usDrC9ma8YrtV/OXJYeTqsJP3Y0uGBduu4YnlA9BUiFRSGJOYgkNkgmTAUHlMITJoHlRjpL/GijV96EcKxHMMqi/BTkTIliAak6Q9jqzP4koZenWIbgh0g7w2Wp6PlIeb+QLPPuQP/DVWLf93WskDABoQVvPn4JDARJAMWJxyYL3iA14JYl4LKRz28RKprPP4yZ/vjpMcs58nX/nt8cDaJGa2wvJMoWSzlZnZr+88/5SOhXA776VdC6W9zY0d2mnno49+ufN66AhPIt648ACCP9zCVfnk++olJ3eMBPoXTTAbk1cP8P4V97LLmit4cOitgC+k+bGb/hcnHfkndhWf6oRhfefQb3Q+Nz9XZLIf+1y0kflf6bS3zc3/wf9aVCZ97HzmXngDP/j63rzlDu8YdsUxJ/DJb7yT8z5xORf/di7vf+1KVr1pp7XUmsf+5jX864J/5/BL9/ImCbm1tDz9Iv797IDmE3+m+e17AHjVOxewaPev8aYLHuD643flTRc8wNtWf4FP7vSzjuLUxhXhu3hr8tMOuXxqGF873+aslZ5xtb+HbW7+D5be9AsArjpzmrcmP+2QqeuP35XvRj/ig/Ex2E99j2s/eO8GjZOuAjMLzhhAdpQU11ZM2vbI7YKWaQZSehKDWttuWQofNqa1/5yZFTrWrh0T6M7E2WUGsWaSsN5E1XrI+iKyssKGklRLTCSwQQldz0j6NeFkRvGJurcJbqstznnikmUzSlF7Yu4srtVCCEHliYSJV0YwCWlRoioa3RLI2NsyWy0wocitPr37l9MCXTc0RgNq20iSPkE45SisdgQNR1gzOCHIShKROcKqV3DSwSLRVMHnEWVrk5YOKeyEuGW4njImlESTFht6U4K2YYCKHWnZb4t7JZWaQSa+Ho0raKwUyFY6Q5Yyg5pq4qL839s4BBaMQ0pIB4oEcQITyUyIW7soJvjvTM8ocF28NNAmIBtDZJ6r2vJih5O9mGiHiJW2WbleEvNs4WRdrAcyDwtTPgTMWDp5hFkEYRWvgjs/CW5b0juV/xa54hALH0UsAAdJL5hibqBiQDZz1Rk/Kbd9KcSK6LEIYQsQ+SKTIgPVEqiGQNi85lfkcxeTYcPggkkmJ8vIxwuolu+oanpL5+ntLSayBFWN7fPhVLKhiEWBq/+0KzvMXcPDD48yd+EEJlO4osFJT65eMWcNK2s+Zn+oEqN6ayxdNY/SwyF/zuaie1KY12LXeat4aPkINDXGCVRkMC2Fbgpf2yX1fQonvboS1ByNpWWSniZCOEwBVF9CsZjQdALT0GQtQTpgQDvCJ0Osys9p2pH0QrMCNrIUVyjvYBaDbjqfj2Rcx1rfRNCalxH0t7APlcnKPqTORN5hTiYCU3S40JJJ4Yt3Bhb1RNGbmBYcqK6i/0z47GsvoLRjhfet/BhjN9zClUff3ZkUX73k5HWSFz+p9rbL7f3av0+bezWlVwj+9SMauIGbpx7mykfu5ofnKb5z6DeYe/Z3+fS1P+60tSNw5m41vn7XuzjwP7/HxaN7cvduVzF+/ElM7PNzdjz/zxzNdsDE0/rRxns/abjjdP/6Jwe/inCnD1N592e5MHc/O+7D/r0jbv4mb1j+Nc793x/msv3X8D8K/8Q51/0lb2WmzsqpN/2CU15/EfaCY5nYp8IuO2nu26ld7BLO+8Tlax3/qTVUTnnHH3j8tr257IDFXAksygXz4UMO5rOHwFt/dBff2elnfOjaT+AuOwOY5qv5Z28Lboc5Z9DfuJ1Fu3+N0itmVJGjuJwSgiNv25vaB9pW1nd762qAJWcD8C+fuJxPfuOdlA66htNufQvXvPdc/teiL3D2QWfBb+d6gnjpLYwm3+FNF3wIToTftD7PtYU7uJZdn/E6z0ZXgWFmJeBNpaPRIvST2XaOSxtyxkFsNkQUzdgsd/YVMzbBWs+oLcorIi5NZ9qateKPEL69MMBpr0wAHeVCGAvNlnfTaisanY6IGZvm2bVr2vbOQQgDvYwdNEJUtcjMKy0qdqjE978+P/SqixCEdUvpyaZ3E9OStDck6fXOKkHdoWKvENkgJ2LCF9GM+zWNEUlxjaP/9uW46vRMH63rmBt03NvA93VogHhhP8I60rL2BGo6xZQ0cZ9CNx3RRIKTAlNUyMQSjDXyMA0Bxru1qam6v3bta6IVLg9xy/oKuLy/eipGPLHak6vZYX6dAqWKzCVcN3Fhd8Usx+ZWYJ4NbVKzKcPDXiwCszEKzKYKH3shVJjuOPFoj5OdP/UlZLHgQ8HMDJlxop0Dkyf457VivCPZjHOWivMaLwU6Ibwm9MfQTTpkyOauW+3kzazkSHNFQDYlwbQkqIOMvaIQ1P0xk15PkEzJ4fpTXFMhW/7+2M7bccoTB1N02IJFNiW2ZAjHtK9vsmMMdY0rGkRNIYcSbCoRymLrAdFKTbxtzNy5UxSDlEhlLK/2kiweQDehNewId6zy5u0eomlCnmj08cRUHw5otQLSyQJ9f9S0hr07pkzyvuXkTmQCs3ODqJBSHytBYAkKGSaTFO8rYoqw4xv/wmSryPL7R7CRRdcUMoZkjgHlUJPah9FVBbrpn2NtNcYUyHND/feW9DnCKdGxvLaB30fmBZ/Bf0/xoMEVLaqqEJkg6zG4Wsyyz5zeHSc5nvo8OTKfbD8b2vs8NScGnp4nc+Rte3deH3XLPewqPsVZB13D537+Vb70jn/gymP+xM3vuWyj+jz6y9NYedwhXLPfJAB373YV77joca445gQaj91K7QPv54nfnsPe8bt464++zXs/aTjg9bvSv+Z4Xw8FeN+Ji/nB1/dm4e3fYUW4G1d984NcveRkjrxtb/7Pk16h2NP+O19b8Z/cf5/v39KbfsFxH/4M4BUc/e4m5571btLHzufG4FcAfOpj9/HD8xR7br90LdUGPEH8ym+P522rv8A1Tx7GyaP/H/fKv+feR7dlV/GpvH6OV0YuWfpPnYKYZx10DQek+3fO/7OvvYA7z5/JT2l/bl2ofG+G9Fx2wGJ+eJ7ivZ80/PA81Wn/xuBXLD7q9ezxcMZ9O2n2/snNvO3bIbv94a6uArOxEFojhKbD6WaTmHbifqc+TO441g4za+d6tNUPJREyQFTKmJF+skqAyFwnnEk4h0gsutpCTNU8qbEO12pBq5UfY1bYmRQzilCb9LRJU5uodBQjtXaNlSD0r6s1Bu8pUNuxglECJwWNOZKwLokmM1TsaA5LhHEU11hspLDK91W1DFFmfWy2dR0bYycEqplhSj7J3kkwBUGrH1wY+OuVzYTQdcLx2iQLQGtsuUDSqwmmM8LpFKu9w5iuZ76QJ3izgGqMsBE28C5tspH48Dkpfd5LFPjcGeNX/5Ayzx0KvGtZahGZxRY0ulLCTVZnzASUwiVp53tFzSJZXbzgeG0aP+N7vw2iZ/3slpzXsjmS+V8qeTRbM2wAQueLOwkdktHOo0DQUV6E8a9tmO8jIC2BSj1ZyQqemLSVGaf9RN5J8tAw0Sk6HNQFMvX3Vpn6z9W3sxTm1hHCMd0IkU8UfP2wNQJTE8QmyNUfh57TIhsrIFKBi3yejevJIBXYgk/GSfssaT+4WBIMNXGPlsl6DTxZwJUNIgkoTEpwILWlL2oR6Yxlk/3U/tKHDhypFJi5fszvXFzFj5fty/KxPmxdEw20SKcjVE0SD+TXMp0Ju/NFLR0qgawa0tvToFEwuIZmaHSS8WoZJ6E16o8J/jpXHtXIGKq7ZPSMTmOMRDzSR1b0bmVZyatTKvGET7j82DmBRHr1yym/T1bKC2UaQVa2mLJFGIHTDqTDDicEj0dEqzWZTV/k/8AtB+6yM/hq+gSnnf+WTl4EPDupaROWr/z2eD772gs6nyntWKF+zmcoH3MOf6hF3HbqJOAn24PvH+98/vAf7cyX+Ie12jzt1rd0Qr3AKylt1D7wfirfy6h9YJSrTzqbH56nuP74c7gQOI7P8OGvFznzU98lXfIO3rb6ND60+i3cc/kB/OvVdXZ677mddn7w9b25/vhduerMz1P+zDm85r+LfGXqeP7pmEu4kl3W6s/nLzqXfzr2EgC+tOYKAM7+MXAkfGVgVz7LA6RzJgn+cAv//H/34MP//Ci/+2cItjuJIys/Y5vgdsCH6F3dtzdvywtfHrXN5Xzu5wfx4UuK/O6fTyL78c8AeDNF9OnncPWSk/n7jz3EAftN8g8rF3Dn4oPya74rp17As+I3rc8D8J7v38X433lF6YfnKW546H4W7f4LfnLwxRx1iw+D2/sn8JW33u7r7gBXsRM3fv378KZnP0YbXQUGv3LY39/P60t/SxCVcbEvANmxQW6HJpHXiDEGEYZPU146REbm4VE9ZdK5vbktb17DRUqysi8ICXmtEi2QmSOYaCJWTeShYMqHNznrX88iM0IrXJLMqC65etNRYMArHMonwaM1QkpcmiKikGzBEPX5RWwosEpQWOMdydLekKwoyYqCaMqQFSVWCYpjPmHeJ5E6r2aUA2ROYHQ9AQNOC1pziqQ9EhMK+h5uEDwxjmslMyQrS2YKVgIojQgCsoXD1BcUCWqerIQTLVygsIFEJganJGlFYwqSYDpDxRYZZ6haDMbiShE4T6psUZNVQkwoCaopTkuc8v0UqcWGyqs19QTxxKpcwcmveSeMzJCJlJumfszk5ORLVnl4MdEeJ5saB65Zvd59fj80Z5Mfd0Nw0ZLzXpTjHLv7JzdovxX3b57rMLrb+r+j7jjxaI+THT/2eWSp4AmM8cSjDeG8wkJOZFxb4A+9EqOS3C45cETjorPSL4zfXyaQlf3nVQzRlCOpCOI5DhP6/JlwUvj2JKCcP5YV3m1LgK76g5qSD4Oy2t/7TH9GMBZgIocbSHCJApN3PrDI0GCbmnClJu11BNOCaI2gsY2fwMtyipsKUU3pw8jyY8kUWnNNboPsQ9mySl6QcmEDs6qIjSxBVZHNTRBTAXpaIGNB2ucorBYd8wKnIJsfI7UnVAP9daamC6SNkLCcYB8r0/cwrDk4YdftVrC6XqG6ZBAnfDiXyMAULaolUTVJMjdFV3XHTMEFDlX3ZAbniR1q5jtUTb/dBl7Rkpl/HQ+6XLlxmIJFlDOKDxZQMaS2xcPf+qfuOMnRHieH/3x3rnzHc/Nne8f1nmB86soz+OfDZ5Luf/4mn9tx01dPYuSSX/Pjc/x+d+q7ANg324ef/5/fst93D+LJJ+8G4NO3H8I39vwOn7j3Q+y1oATAu77Yw0//cZq+932Z//nw3zP29ldQ/r+X8oMnj+BdX+zhCx9YyV4LSrzriz188fNHsmTpX/Gtxa9l+ZtGmXf9CvY/Ywfun9yL99/4aX52wB784MkjnvFcdq0/zAPlndba9i8jyzuv33jt33Rez73qzHW2sU/1Qa47606Omj6d1725j4//pMzIJb/mlH/J+OvbvCvaqsCTpCMvKrLbH+7iHde/aq1+vWOnObypes9a7R6yuI8b9p56xr5/9YT/fMb31oWDotM45u/+EYAfff+LAHzhAyt5wz+c39lnQ8ZJl8AAf/7zn9lxxx03dze6eIli2bJlbLPNNpu7G5sd3XHSxbOhO048uuOki2dDd5x4dMdJF8+GDRkn3RAyYHBwEIClS5duFSsj1WqVhQsXsmzZsq0m1nZznJNzjunpaebPn/+iHO+lju44eemjO042P7a2cQJb31jpjpPNj+44eenjpT5OugQGkHmCfl9f31bxT9dGb2/vVnU+8OKf09ZyY90U6I6TLQfdcbL5sLWOE9j6xkp3nGw+dMfJloOX6jiR69+liy666KKLLrrooosuuujipYEugemiiy666KKLLrrooosuthh0CQwQRRFf+MIXiKJnt2rdUrC1nQ9snee0pWFr+w62tvOBrfOctjRsjd/B1nZOW9v5bInYGr+Dre2cXurn03Uh66KLLrrooosuuuiiiy62GHQVmC666KKLLrrooosuuuhii0GXwHTRRRdddNFFF1100UUXWwy6BKaLLrrooosuuuiiiy662GLQJTBddNFFF1100UUXXXTRxRaDlz2B+eY3v8n2229PoVDgwAMP5LbbbtvcXXpG3HzzzbzjHe9g/vz5CCG4/PLL13rfOcfnP/955s2bR7FY5NBDD+VPf/rTWvuMj4/z3ve+l97eXvr7+/nQhz5ErVZ7Ec/C48tf/jL7778/PT09jIyM8M53vpMHH3xwrX1arRYf//jHGRoaolKpcNRRR7Fy5cq19lm6dClHHHEEpVKJkZERPvOZz5Bl2Yt5Ki8bbCljZWsaJ9AdK1sauuOkO066WD+646Q7Tp433MsYl156qQvD0H33u991S5YscR/+8Iddf3+/W7ly5ebu2jrxq1/9yp122mnusssuc4D76U9/utb7X/nKV1xfX5+7/PLL3R/+8Af313/9126HHXZwzWazs8/hhx/uXv3qV7vf/e537te//rXbaaed3DHHHPMin4lzhx12mPve977n7rvvPnf33Xe7t73tbW7bbbd1tVqts89HPvIRt3DhQnfddde5O+64w73mNa9xBx98cOf9LMvcHnvs4Q499FC3ePFi96tf/coNDw+7U0899UU/n60dW9JY2ZrGiXPdsbIloTtOuuOki/WjO06642RT4GVNYA444AD38Y9/vPO3McbNnz/fffnLX96MvdowPHUgWWvd6OioO+ecczrbJicnXRRF7kc/+pFzzrk//vGPDnC33357Z58rrrjCCSHcE0888aL1fV1YtWqVA9xNN93knPN9D4LA/ed//mdnn/vvv98B7tZbb3XO+RuLlNKtWLGis8+3vvUt19vb6+I4fnFPYCvHljpWtrZx4lx3rLyU0R0n3XHSxfrRHSfdcbIp8LINIUuShDvvvJNDDz20s01KyaGHHsqtt966GXv23PCXv/yFFStWrHU+fX19HHjggZ3zufXWW+nv72e//fbr7HPooYcipeT3v//9i97n2ZiamgJgcHAQgDvvvJM0Tdc6n1133ZVtt912rfPZc889mTt3bmefww47jGq1ypIlS17E3m/d2JrGypY+TqA7Vl6q6I6T7jjpYv3ojpPuONlUeNkSmLGxMYwxa30BAHPnzmXFihWbqVfPHe0+P9v5rFixgpGRkbXe11ozODi4Wc/ZWssnP/lJXvva17LHHnsAvq9hGNLf37/Wvk89n3Wdb/u9LjYNtqaxsiWPE+iOlZcyuuOkO066WD+646Q7TjYV9It2pC66eAZ8/OMf57777uM3v/nN5u5KF128pNEdK110sX50x0kXXawfW/o4edkqMMPDwyilnuassHLlSkZHRzdTr5472n1+tvMZHR1l1apVa72fZRnj4+Ob7Zw/8YlP8Itf/IIbbriBbbbZprN9dHSUJEmYnJxca/+nns+6zrf9XhebBlvTWNlSxwl0x8pLHd1x0h0nXawf3XHSHSebCi9bAhOGIfvuuy/XXXddZ5u1luuuu46DDjpoM/bsuWGHHXZgdHR0rfOpVqv8/ve/75zPQQcdxOTkJHfeeWdnn+uvvx5rLQceeOCL2l/nHJ/4xCf46U9/yvXXX88OO+yw1vv77rsvQRCsdT4PPvggS5cuXet87r333rVuDtdccw29vb381V/91YtzIi8DbE1jZUsbJ9AdK1sKuuOkO066WD+646Q7TjYZXjS7gJcgLr30UhdFkfv+97/v/vjHP7rjjz/e9ff3r+Ws8FLC9PS0W7x4sVu8eLED3Ne+9jW3ePFi99hjjznnvJ1ff3+/++///m93zz33uL/5m79Zp53f3nvv7X7/+9+73/zmN27nnXfeLHZ+H/3oR11fX5+78cYb3fLlyzs/jUajs89HPvIRt+2227rrr7/e3XHHHe6ggw5yBx10UOf9tpXfokWL3N133+2uvPJKN2fOnK7l5QuALWmsbE3jxLnuWNmS0B0n3XHSxfrRHSfdcbIp8LImMM459/Wvf91tu+22LgxDd8ABB7jf/e53m7tLz4gbbrjBAU/7Oe6445xz3tLv9NNPd3PnznVRFLk3v/nN7sEHH1yrjTVr1rhjjjnGVSoV19vb6z7wgQ+46enpF/1c1nUegPve977X2afZbLqPfexjbmBgwJVKJfeud73LLV++fK12Hn30UffWt77VFYtFNzw87D71qU+5NE1f5LN5eWBLGStb0zhxrjtWtjR0x0l3nHSxfnTHSXecPF+I/IS66KKLLrrooosuuuiiiy5e8njZ5sB00UUXXXTRRRdddNFFF1sethoC881vfpPtt9+eQqHAgQceyG233ba5u9RFFy85dMdJF12sH91x0kUXG4buWOlic2GrIDA//vGPOfnkk/nCF77AXXfdxatf/WoOO+ywp1nXddHFyxndcdJFF+tHd5x00cWGoTtWutic2CpyYA488ED2339/vvGNbwDekm/hwoWceOKJfPazn93Mveuii5cGuuOkiy7Wj+446aKLDUN3rHSxOaE3dweeL5Ik4c477+TUU0/tbJNScuihh3Lrrbeu8zNxHBPHcedvay3j4+MMDQ0hhHjB+9zFlgHnHNPT08yfPx8pt2yxsjtOunih0B0n3XHSxfqxNY0T2Pix0h0nXWwINmacbPEEZmxsDGMMc+fOXWv73LlzeeCBB9b5mS9/+cucccYZL0b3utgKsGzZsrUq1W6J6I6TLl5odMdJF12sH1vDOIGNHyvdcdLFxmBDxskWT2CeC0499VROPvnkzt9TU1Nsu+22vHH0A+ioRGv7YUwoUYnFRJL6qEZYkBkUxjN0y+CEAAG6nmIDhSkqdD0DwAlIKwFO+X3KD0/A+CSYDKwDKUBIkBKcQwQBFEJsuYQraqySOC3JSgqZOVTTt2tDhZMC4RxOCpwS6OkU4Rw2UAhjEdYhEouq1iFOcJmZOWaa+hN21h/fWf+30uAcSIVQEoSAYkQy2kdW1sjU0RoKkKmjuKoFgGwZhDEI47BFjQ01NpA4KciKCuEcumkwoUQ4MIGk/MgEot7AZQYhJc5a37d2P2DmegTa99lYXG8FWwqwgeqcNwDC9wMBLpCI1LfjpH9fWIeuxohGE9eMwRhQyl+H9opP/lsEAa5chDAA50iHS9TLhjuv+hI9PT2b+l9wi8AzjZPZuOGTRz7v4xxy3mUbtf9xb/3v533MNi684m+edxtf+ej7NkFP4LPf+sEmaQfg/uv/uN59dnvTpq2Y3B0nHu1xstMJn8cNFojnpey0wwqUtFTjAgCBMtSTiDhTNGoRUjqEcCAcaSP0DaUSWUrRUYbWjsbqEsIIolWKwhqHsBBNWFSaR4E7MKEg6ZEgwBQEWQHSiiMdtGAhXKNQMcTDFjucQC1A1SWmZHHlDD0WEkwJVAzC+B+VOHQLgrrFSf98E9b/AJhIIKzfjgTV8v0xocBpaA5LsgI0X5EwMneKxCgA9p+7lKX1AZ6o9lFbU0Joh7MCFRqcA2dk/liyqMBgjYKVETZ0BNMSGQtEBtGkQ8UgDUjjcAKsFsj8uqjEIQw46fucVnx/spIgLYGpOFRdoBLQTV8UAwFBzfnP5pUy2ucZVo2/Ns75nQWolkUaS2sgxBRFZ7uMHUHdEg8oGoWY+y8+sztOcsx+ntz01ZO4Ye8pAN79mXt418+feNa2fvqOBU/b1v5M+73d/nDXRvfxlkseIF32LU5/w3YAvKl6DwCHLO7r9O+Z8H8WfX+jj7cuBGfusUnaeSrS0+97Xp9/x/Wv4tO3HwLAG/7h/E3RpWfFhoyTLZ7ADA8Po5Ri5cqVa21fuXIlo6Oj6/xMFEVEUfS07VoXUOVeVFhAKoErC2QkUAVFYdwiLARCEcQxNlTYSGGHioRTCdYoXClETyeYYoApewIT1AyMDKKnYxCZn0SDn0gDCMAATYuK64hSEVcqYEsaggJCOXSakpU0yoINBE4LVGwRDmSkUc0UUTfIWj5JT1JPXJCQWX8QHQAOZyxCKD9xlzInU+3JvESEIWiFmdOHGyhQaGSeMKSaoJYhiiWcFMjAIlspWJBaYgKFiBROgOnR6IYlkBnK+YepK2nkgEO1LM6mOXER+flnoHMSJQCnEEaC0CActKwnRlGEKWmE9QROWIeI8qeoEBA6VGxmeNl0CzHVAgfOqZy0CcCTNcD3A8AImE4QKgOlCBrTBEWZN73ly9ubcpy0cfs/vHuT9O32f3g3+3/1xxu8f5t0fPivr31Ox/u3nx36nD63Lpz3yQ9u0rY+ed53N0lbPZUXf5LUHSdrQxUK2FKEHnRQKqJVRmIrvGO7+9g2XEPqFH+J53Db2HZMNoqkRpPEmv7BhMFyA+cEjTSglWoCZTAaspZG1iL0lJ8868CicDnZcGRKgpCoxOEykJMwvY3ERAZ6MjAhBnBzU3QkMAS4QCK1w+EQJYnVAtHyJEZPQxA7tHMo7fykHUCC0/77VgKc9gt8WLAlQVbw93ZbgGwUspKjd0ELFUVETrD3nMdJbJk0q1DuU4TljEKYkmQKayWZlQQqY7pWRAiHVBZrBakLEJlAGIUUAhs6dM33UUj/uBDW4YxAOofVgsBa3+8McKAySWokAkHW6xAFUJlABED+yJEZOAVy2p+vDbzjUWHSorDI/DoI6zCRRIb587gU4EIIGjmJKwlMEbSAyOaLZVvBOIGNHyvP9jypFCIK5ZD3nbgYlOLad3pic9j1jz9t36vetA2otbcddv3jqNyTqiefWz2+z/5sc9ftG3VOlVIP7HIKuvIzAArGLybc+j+aFAjX+ZnPvvYC7jz/FP7PRh1p3Tjytr0B+MVNdj17vrho96tSmPn+7jz/FAD2PensTXacO88/pdPehoyTLT4QMwxD9t13X6677rrONmst1113HQcddNDGNeYcLgo6K/wqtsjYUZiwmNArHzKxuEAhM+tfS0FzboG0ov0kuxIirEMmjnDSKy6mqL2q0D5MmhMZY3BJ6l9nmf9pthDVOurJNRQfWUO0so5MLU7lx08dMrbopiGYbBGsrqFWTSGWr8FN13H1Bi5NPTGxOVlyFuLYExSVf+VK+e3GgLFgLEIrXJriwoB4qOBXngAnBOFUimplYBzCOq+2KAlaklUCskqAjI1XjFr5ypQFXUuQiUW1LKagoX38XCXxpCXfZt2MWgT+ehgDrRgx3UCP1wkmW8jED24ZG1DCP7Ry9QlrkY0UvXISMVHFJYm/Hs7hWrFvc/axnM2vgwUpcMbi4hiXJLDm2VdctiRs0nHyAuC5kKF/+9mhnZ+N2f/lgG0OWPi83n+5YlOPE6thaLBGahTLq720kgDjJGUZ81eFJ9ghWs1Qoc5IpUZPscWC4UlGe6bZvmeckdI0gfL38HKYssOccXSUYQpeffEqgFechXE4JVCJI5oyqNihm16NCKcdIhOoFaFXC2KBmNawPCKYVKiWQNUk4bgiGpcUVwpKKxyllY5oyis8WUHgFFgl/PEyvxZkAuEJj137nK0GG0LS4+/lNnTUJotM1oooaXlFcQzjBMZKT9C0ITOKQFlSozxhs5Ko4KMGekoxhUKKCC3hhO+zDRxOe7Wl3QdpHDKbUV1U7BAmJ3gWdCu/Ni2LbjmKKwTFFQJhcgLmfL9N6BUWE3oiEzT8tWirOiLL27V+TkAeGaAS325QM+i6fx7KzD8PhXmO/5QvUWzqsfK+Exc/575c9aZNE5KXPnY+nz7tx+h3N1k09cz9ecsd/Xz2tRfw2ddeAGy6SfwvbrKcdutbNklbs3FreNjz+vxlByzmsgNmrkebvGxqbOx13OIVGICTTz6Z4447jv32248DDjiA8847j3q9zgc+8IGNa0j4m5BM/Uq+jDPojXBaoJv+5iUyS9IbkJUlMnUUVsekvSEi8yTDRBIntV+9Mf5mj3WgVWe1XyjliUtbBZkFFyd+kq0UYrqOaPiQrdJqvVY/acX+s9Z2JugYM6Nk5MTIOeeZbKDBegUGQBgzE0aWh5S5NEUUCpi+kr9pT/mHhylLr/xI34dwKkE1Mx/KpiUmlJiCQLUkMrWolsGGEhtIhFX+xh5bsrImiELfd9smLnZtGq115zzafUUKSBKEc6g4QZYKyGKAU9KrMLFBWIvILKLW8ApUkvjPts8TEEF+Da0D8nAy6/xvYyDBEyxj1yKcWws22Th5CeLlQky6eOGxqcZJe9KspCW1kmYckGWK8bSMKUoeTYa5p76QqaSI9IFLtDLNUKXOo9ODRCojkJYk0QQV48mMcD6Mywvbnjg40A0/O85K/n5rA0FSFqQVrwCIDJx2kPnwpnBKIEx7ESmf3DdApu1JP1jlyUFYc6jUoRsWmTmyosRp8g7k5+ry6ADh+2a1/zvtgaTfIgYTXDUgESFT0vFQfS79QZPBQoPRcpWWCVhR62GqXiRNFT0DLcarZQZ762ShQghHmmqoa7KiI8gEppB3X5GHePsFPk/ucuIAHaKRlRQmUlgtOuFgKnZIAyoRWOXbaofP4WaUFBX76ACRuTz6weGEQKQW6WRnAU0m0s8BhO9P+5o5KbDRS2tVfVNgU42VuRfesM7tG0NM2vuuPO6QZ2xvfbhmv0m4YJTK9y7mswcs5iu/PZ633NHfee8td/RzzX6Tm1R1aOPI2/bmFzdZDkqu2uRtb6o2X4jzfj7YKgjMu9/9blavXs3nP/95VqxYwV577cWVV175tOSy9SLP/5DGIlKDKQYI5wimM1QrI+kLsaFCWEdpedwhJDKxnQl9Vg6wgSSYSHFSYIoKGwhPKiCfNGeIMJiZoFuHc36bJxN6LfLhWrHvWy6NCiH8e86B1v4Zkt9QPSkxvh2ZxyY7h0izzmc7E3Zp1yIxQoegZK6mWHQtwQWKRIVkJUlY9Q/Jdo6JDRU2VOiGwRT9jduGEtXIcNq/RviVOhtITMETLqG1J17W+vC5/LoIrXFZ5vNe8L9REmzOcHKlSrRilNaecOV5RO1zclmWqzrCkziAUOKangiKQoRLY0RbCm0fX4qZa6/wIXhu63rgbLJx0gWwacPHZre5qcLIuirLc8OmGifC+tX8gs4Yq5XJMkUYZqxqVViiFzAQ1FnVqrB9ZZzMSarJCEmmGIrqFFTGZFJktFxFSUtPEDPeKiGlw7QLH1gfJdDJ+WvnHRpJWpKo1GFjsKEgqAlk4tVq3YB4QBBWQTdcrmDQUS5w+BAx6SfyLr+HqzhXuduhtTlpaEfltgmAEwKZeRIjrG9LSIcoZ0jtiJsBy5u9LChNMbdYJbOKlgloJgGVYkwWSkpBymojqcchkTZM1YqYTOFCiys6MhNgBlLUpMZpgQlBt/yzSbVy5SPxi2MiJxBtuHYQQOaQKX7hMXP+UaPyXJo0z/2JXee8ZOqQZlYYHZ64kVlQwj/ic+JiA7/oh2gTu7VVqq0Fm/qZ0g4Zez6KynMlLwDXH78rQEdt+OxrL2C2GfQLbQz99jfIl1z42EsZWwWBAfjEJz7BJz7xiefXSK4oOJmvrEgDsUMmPmk/mE5xSuK0QsYZphyQ9AY5gQGsQ7WMX32JPWGQqcFGCleIoNHyk+JAgxAIld8I08yHdrXVACn8xDpXaESUx15q7ZWczCCU9G3mCf+0HxTGeRUiTryaI33uToe0tNuXGtLMx5IKOUOQlCIrKKRx2IKeCU8QgqwkicYSVOwT+NPBAiaUBNMp4WSGDSVJryKQAt3MSHoCTKT8Q1DjwxBKEaLe7BA6EQReQcoyT8DyUC5mPSTIVay1kv5z8ues8aFvWTZz/dokph0m55xXX4QEYzx5sbPaN8Z/J22I2ZLQ1oVNMk66eEHIy+y2NxWJ6eK5YdM8T0DXBGvqJbS0zBmYphSk/GnNHJbXe9ljcDljzQolnVBLI6qNAkpZltUHqMYFjBNoYRkq1FnV6KGeBJhMIfNkc2HykOLUoFoZVkuEcejMUXSQlSRWKRAO1RQ+tKnhlQmnFFkRcD58CunJVjs0TeYBAk7SUVqyokIlNp+gi45yI8jVhpYnLT7syoeciQyiMUXaLOKGUgo9TXYaGmNOoUZZx9SziOXNXpZN9pMkmnKUMKdcoxLE/DmeQ0sGpEpTiFKmY03U5xeikoYCJ5Cp8H11oNL29fCKC3hC4wJBVlJkBYluWq+6ZD7krp1P6fJzNKHASX/+sh0i5vJ8S8NMFIV1yNggMr/IJhLjQ6udN7NBt9v1YWXgkHKLL7m3TmyKsXLfz94KwFVvumKt7evKgdlQPBcSdPWSk9e/0wuAs679KFT9619wy2bpw5aIrYbAbBIYi5qOsVrmrlZ+eV6kBgKFzN3AsnKJrBL6m7T0N2/RnnhbR1BNfDhTarClEBNIdKQR7Ym3szOKgckVCfBqipJ+WxRBoHHFqBOCZkONi5TPPXGOpC9Et9p5LmBDH8LlRiuolkGvqkK1Bs21iVOnD23VoW0oYC0un8g7KXxonPGSfHEsRSY+vwQlMD0FnweU2Xwfg2qkCOOvS1r27bRlfJuHytlS2EmA7Cgms53IOsn9s0hVO29F6pn9OsQkWFstaSsq7Vyatnoj5MzfIl8yNKbznfn2Z2UGSoGQW18Y2abCpkrg76KLrRW65bAGWs2Q7UbG6QlajLfKVMfLyCHHymYvgTLU0ojHp/txTpCmmtX1CvVWSJpoAmmRwrFisod4OoJYUmwJf59vpw4qgWwrDEqA8SHQNs8PtMqHgYXTXkFpDilag45k2BCO+XySZNDmKosgmhDouic0MqWTH+LDrgRZwSf6y8x1FAccntykPgy77folDbQGLKbiXdAA5pem2L38BKvSXpbWB1hZq+CcYKCnwWh5Giksq5sVyn0tlLS04oBKIUYrQzMOkdKR9iXgBE5pnATd9DmnTgofDdHOabSSrKg6z2rwxE+1rF+sFNBO9syKsuNeJqw/Jyc8EXNKIEVOemKLqiWg8zmCTTuh4EIaZJ7Yj/SqWPtaqfazuotnxPMhLC8Uzrr2owCcdui3eM9NM+Yol7xhuvP+aYd+63kf54zFt/D2N2y9i6cvBLoEZja0Auc6TleylfoVFvwNrHOTyny+hWpZgmqea2EtVmlkapCNZCaMydo8lEr4ECmTeCVFSE9YstyBizy8Kwoh0JieEvFIERtKROYwBemTCgNBWDXoluk8nHTdh2zJxPeLwN+07YJ+wjCAsYkZEgC589isr14pH4olPWmQqVdtnPSJ8jKxCGNRNZ93Y6KApD+YiQcWs9olDzHL47KdFsR9fvVLZm5GJRHCn6+UuDj2xEPNGrzO+R+7DscwIXPVxcyE4bXzWazJHcnyXBo168HeIU6zSKQU3iLGzZAoEQT+O1GzCE0Xa2H/r/54iyAxd90Tr38nYJ9XPbPbWhddPBcIA6boENLRTAMCaVj65BB6LCAbkEhhmWoV2L4yTiMLGa1M0x82GGtVsK6CMZLEKMYmK5ipENmSqJYnJU6R+/36Z5PIvI1v2lcAhQ/pDaUnUQpaA4LGiMIpiAcdZl4MRmBKknTQooeapI0QmwlvyZ/546imIAwEMgZTkMhEYvP8F5l60wAA8hA0J0THrli3HDYSmIGMUn+TKMiYU65TTQssjYeIrWZ5vZd6MyIMM6wTVIKYWurH4mC5QVGnNIsBO/aN8cDECFPVACEcxbJ/7jaDEGFEnnfjiYLTEhspRB5rJzo5QgobClTL+Wcy/hrO2O7TIXnC+HN0bWezjFyJ8i6gtqBxoURkKo/QII/OyEsjmJkwsjZxYqo7OX0mfKryb5usrV0eGuXBV6543u1cs+1x3PmjiHsyb29/5G170wIKzYcBT1yWBD9gCT/okBzgOZGZ0w79FuE5r+6Gj20kugRmNuIUyv7mk1W8vaSebPm8mJa3E3aBQsX+n8wGCpWluaUvuS+8w0mJMAaXkwIVe7XAOddJEkfLPMHcKwBCK1xPGdtbJOsJOzfVdnKmbhlvXxx68wCRWlRua5KVtbdsrqY+0TA26NSSVQIa2/dSDBRi+Zif4HfUDDwxsLkDWhB4AiMEuunbtaFEJp4omYJXb2yovH2my2/sxiFT63NbMosmv5ELL7NnlQAb+Bjr4phBTTU75gM45xUY8IpHO3G/Tepm56C0HdWEV41cm4+1a9rkbdAOl7OuE2bWcTVrKy8wo8i00SZJs2OldXd4vBSxoaTkubTZJTIbj59NHMRfD6y7Sv3LGfGAX73PWhr6oKQTXEthIodzgswptu8bJ5IZg1GDsk6wTrCgNEUoDU8IGJ8qY6ohMpbI1Csbug4qoTNpb1vq+1pcAhtIkh7p3w8ENoDmXEe2IMbFCpFKXCZRhQy90BOBcjGmPDBNLQ6ZkD30z6kxNVkiE9BqaPSkQsUCpxwy8TVTCmuc70fbCyC/d8qsnTgvSCtAKhntm2b7yjhFlfJ4o58/tBaQWsV0s0AxSukr+tCw/qCJdYJQZUzFRfqiJttWJijrmLmlGiseHaI8t05fqUmoDMuy3s6zqJ0sbyLpjWNaFt1IkXGek6lFx/q5TTCEcajEYpUgSCwiV5WcEl7Bkp6UCePzX1Qj889EY7FC5yqNf+YBuXLjCZINBVkkkLnFdad+WRcvKNrk5diLPgh7bJyN8myF5Xtc5q23c7SJSxtLgh+s83W7jd3T920UmXnj948D4Ma/u3Cj+vxyRneGNhtSIOIUGRtMSa+d+Kf8TQzpb04mlOimwYZ5Yn1qO0TGRQrRcog8Ub392U6SepiHJpl8tV8pXKlANlQh7fUmADIvymjyG6E/CEQTqS/YKPIwAi1wypMkmWT+RpqHfyW9GuEc9e0qVGpNmKohotCThHbo1Ozildb6xHdX6BTNtEWNqqeoZkoyXPIPhkbmHwBKQNEX0JRNO6OYKLyKlXkpvZ28GEyn/hht0iJEJ1dlLc/vMPD7SNUhNlhv8TzbyADAOZFbQeNJyWx75DYJaqthwts+d1Sa2Xk24Pe1Xvon0JjebgjZSw0vBHl5avubm8RsSfkv15nXUa9m69/xZQinvILBExFmRNATxOjeBCEc/aUm/WEDJRxl7f+nx5Iya1plrzpkAaHOCMKMNNI4IxBNn4gvjc8nlJnzk+SixmpBWskNY/DEJukVNOb5UDFCC6adm2EgkciSpbfcohSkZHmobV+xRTKo2X3OClZXKtTTkMlGkTplX1JMgqpJTCZQLZ9/oluu48oF+SRetHNpBHpKsXTVIPNKVabSAuOtEpHOMFYyr69KnPk6N0OFOhZBYhWZVUQ6o5GFjEQ1EqtZUe9BlDNKUcIr+1fzeL3fF7DMvGLiHUAF0jgwzif3Fz3J8GpK2wLadhbfEP5aAblT2EyhZKeZUWgCgcscIvMmPu36aT5HyJcUsKEEhzcByg0WZOr3MZHsfDddPB1L+pdz1qP/2vn7kv4vP+e2Frz2M7zh/D9xyX7/tEHhXUfetvfTyMlzwdjHzmD4/35hrW3vuamnE2q2Przh/D9xxuJbukRmI9DVNGfDOkgzdLXlyYEQmHKe66IUtqBJBwpeSje5e0uovDqRy9YuX9XpTJrJV2h0rjrkoVNCyk4YmespkQ1XcLmsrRKLrmfohukQmTZMTm7UdMsXakztjCIUabKekKQ/8sTBtSsQC8ywXxVw7fCpLJvJgQGvihi/sqQaaSexMSsoksECrblFWkOB9/4vad/HpvF206nt5AvZSGMihUwsJpKkZYkJBcVxg56OEa1k5njO+euAd0rrhIPB2mFjxvgE/rZVdJb5ei0mJ1y5+YBQElEqIgqRJz1SdMLVPLkyM0qOsTmpmRU+1nZkUwrbU8SUugTmpYQXmrxsDF4okrElkZcunh2+DgkE0/45EMqMSrmF0pZykNAyAVNJgUFdp6xjenRMZiXVuMCKag+hMkjpkNrilM/J0E3IimACHz5sQq+0JH2exFjlnbRMCGkFwt2n2G2Xx1kwf5zewTqlviaFvhhZSbFGMVKusU1lEi0tpSDhlX2rOHD+Y/QGLeaWqmRW0l9qUhhqMrrDGoa3maS80xTpYEZawds0R74ujD9p8km8/9ENRzAtyJq6k+sz1SywarrCzn2rmVOo0V9oUtQpRZXSrxsAjLdKJEbRzAIsgvHEGyFExZThUp2+oMljqwcIp7zjGcKHzTktvKlO7s6WFRXNOQGtoaBTs6Vd3wyZO5AV/HMqLUuyki8JYAo+ykAmDqshLYncFlrRmhMRD0akPQE2VGSVgLRXk/Yo0l5FWvJlFPz/QG6hrOls62L9eM/kqbxn8tTn9NnK9y7uvN4UuSmzcfK1P1nr7w+8/8jO66eSl7Yq0y4CuSF44/eP48a/u3CTk5fkM3/YpO29VNBVYGbBxTHIEDlVRyuFLQUdgiKTPFyroJCpQ9e8TYuqxR2S04lJ1hKcwoWatDf00nagOpNwl2W0i0q6KMD0FUkGwpyw5DaNQiDjDBv64mMycYQTCarhrY1dqLGBn5w71XZRUZjQKwiqZQknPElJ+gKSvpBSGOBaLU8OXB46Jnzxxo69srWIeotACFqjpY5Ti9WCYNqgEptbQrpOUUtT0ojArz7V50c46S0onQTdshRXG6IVNe+O1iYVbZcwKX2NFyFAS5+Q31ZfcvXEydwSuR3SlcQQ0EnUF4UIVymR9hZwYe4iZx2qniKnWx3XM5ekM8RtttNZW50B/zt3MUvLXQLzbNhS8mBeKHzyvO9uUjeyLnnZuiAzn1dhirB6ooc/h8MYJyiE3t69kYXMKdSYNgUKMiWQhkhltDKf5yGFw1qBzSSiYHBSkVZ8Yj14pUPFtpOrASCcIKkIGvMFzW1SXtlbRedGAH3FFmPTZZSyDPbX6S826Q+bTCZFBgt15herzAmnUcKyIu5DCYeWlt6oxXCxTj0LiTNNK9WocoaKgzx53+UqiM956VgxI1GxIJwCszzgj6VRKuUWtVqBkSFvuTQYNpDC0TIaiaOaFQmlIdIZ480SBZ3RNAHLpvtpxKHve9TgFw/sSfBgEdXy554WBZ6RQHta07Y+dlJgNAjj1RPVsjmpELkqQ66mzOTMmFBgAoEMHWlZYgNAQNDwbbbza2RqIfVKk8nDu50WOOefyTYSmFCQFQS2u168XrSVlzZ5WR+JWZdS8+ArV/AglwPrT7B/z009sBHqy9cOPWqtv7938WXr/czsApDPhtMO/RZnXftRxk/3i7z3HBlucL+eCa9J6/wuKD/vdjYEm8rMYGPQJTCz0c4DiRPUVB3hStj+go8lDpUnEnnOh3c7SRGpQVVjXxG+bdBvHDbS2KJGZt59xWmJkBLXnpiDv2lWisQDPmSlLcH7qr0WkVrCsQZQAkDV446qYwr5V5cTJ4GvtaLaNWnaoVQGojFD1hP60KxW7kjWnrRLkbuB4W2dhfC2mI0YFRdAgK6nmKLGCR8X7LTEOtGpSoyArNc/zLKCyKshO3TdEE7GyKlGp9+A70eaeZc1KXwIG/gCklpDms7KjVGzHMWM/1spH/oWKtxgH/XtezvXDTx5y0qKtKKR/REy6yWYaCIna76mTpKunRfj8gvYVmFyZSYrdR8468OLRWJeTPVlc4SRdcnL1geZ5EKyAPNokUeSEVRoWDA8iRCOgkrpC5o0TUDThtSykMlWkWKQIoCxWplmLUJIn2iRzUkRKwPCqg8jCxqOsJqBg7SicRqSsqS2jSDdpcn8oSn6oiZlnTCdREw1C2SpwjnBgj7/3qPVQeJMM6+nynhSomkCYqtJrGIiLtFfaBLKjMen+1kzUcEmChKJMMKfX16sUde8O6VN8uLC1iFTmRc/lggnmC4WaW3nVaWCzijrmOm0QFGl1NKIpgl4tDaIFpbpOKLWjIi1pjiYsmv/Ku5dM4/MSm65YxfKjyt0Lbc6NpD05bbNBlqDCt30kQ8qcZ48hD5UTFiI8nAyr46QP29dJ6eoOSyxoSdAWYFOoUwVizy3E8IpR1R1lBPr683Ydoiaf+5K4+vjSCPIIkl9niDtRpA9K07b/n9tcBjZUwnOuvZ9zx3v5LrRVz1jG0fetvezkpfd0/etldvygfcfyfcuvozLPzgTev7O7276L3VTEJc2bv7c8w+N2xCcde1H+fp7zuWsa5+f6nXkbXvzvYcOp+99GxZCuNEEZsWKFfz+979nxQqfKDU6OsqBBx7I6Ojoxjb10kPb1hcQcYKsQhinZP2lzso+gGzbIQqf1C+SDIfyoWKBQgJZJcSGEl3PvJ1i6sOgRBjgssyTmZ4y6UChI3uDX9Hp1JBJfG0UL3ErdD3Ma7L41Tdv9ewNAZzybcjY980UfP6LbPq8GJnkFsmd0CwDWEjyYpHO+nySNPWEwhjCsTou1D6euOwJStuOsu3SkvRpgpp3KpOpo2R8MTXVSFH1BJIUkeUFMAPtXccKAaYc4UKJCXzfhYNwIkY2EkSt4flEWyFpWy1Dbm+jEYWIdJsh7zaTOe94poRXr6w3IMjyFTEbCuK5ZXQpJFg+4fuQGUiTtZ3GclXMh6rNrLJ18ex4OSsxz1eF2RjiMvs4XcLz0ofMXJ5rkTt0xRJRSHlyvJf9Fi5jMGwwoBusTnrQwrCq2eMrzhvFDgPjjDXLhNowPlHGOQgKKTbSHdXAV7uXPpSs4BWFeEAQjxhGBqZRwpFZSWz8Y746XcJMBcielG0rE/xpag6TjSJRkNIfNpgbTTOelMmcZCIuUdQpcaZZWethzZoKruHzSXRVQW5dbAo+hEzFOXFp3zdz9y7VcjjpSPKaLc3VJRCwKqpwr5hPIw3oi1q0soBl1T6STFMpzCxW9BVbNE3gSU4zormmSDglEQZs4BUOV4bpPRKiZSG66bfrBp2QOxOJ3DXNF640gV+gstGMQ5hKHElFkvQJWkMOpz0BMmWLK1hELFE1n8/p1RhPItOyRqm83EInNE1gxUx4WtIryMoOUe0ymPXi4fu5ZL/LOyFkz0RiNjRH5s0r7uH6dWzfEOVlNnmBGbWlTVoe+uw2wPptnzcmD6Y9+V+0+9c6OTFf2Ptgzli8aWrDhOe8GoAv7H3w8yIas13Xvv6ec/n6e2Zej46c23lvxaqNU3/2rb6G983/5Qbvv8EEpl6vc8IJJ3DppZcihGBwcBCA8fFxnHMcc8wxfPvb36ZUKm1Uh19S6CSB50nejSYiTtDW4YohtqCxesbxyhQ0ItLIll+1zyohJpLolvRJjLkFc9ITUGxkCCF8GJMUPvel6BPt2176MrWoVjbj6qK9LaOJJIU1Pm7AlLS3Nm5muExiSkEnCVEY5xWfWdbPwljS/sjXAng8w7Xtg+MMioXcUnhmot4u8iiaXu0RmcWFGpl4O2iVWOKBgMIq/5ApPe7lzrbTS2gcIskLSaa5H38O21cinlPK/fZnbC+DhiWuKNKKQtcjgmoBvbo6E/ol/QOzY3NcLtLcaQ4A4UQLXc/9/KUgrQQdi0yZug7xsZEkHopw4RDh0nFEK8bZPD/GWLyjgpf+hdYIa30yaBcbhBeSxLyUcl/WhfWRmNlko73fhhKQF7JgZhcvPNq5D6opCMY1WcHgEsWD43PYZ+QJaiaiqBKaJmRBaYpWFpBZST0L0dLyiqEVPBoM0co0mZFMqZIvFhlBlkofriX8ZNtq7zYmBxIKOmO0XCUxiifrfbQyjRAOQkuhlFDPQsZqfnJRDDJqaUQjCzsmAm3U05DpRoRrKVRdEkzLPGTN5Y5oPiQLwESq49LlAoW01pelKQhU7Kg8BqDIioLmZC+PbhNiY8VYMUNISzodocoprWZIseTH/LKlwzzeHEE1JeGkoCjbasjM+aa9hlJfk7iQEdcDMAIRe5IjjLdNbpccCOoOqyXS0CleqVuOpEfSnCMwBUCCTLxaYypQHmqQJAo54sgyhakFZE1NIxBkBU1QUxQmLbphfBHLXOGxgSAt+vwXyElVF8+K9qT6ksnnnsTfxiX7Xc577njn07afde1HueljOz8tZ6WNyz/onlFZ2XfJdjN/fOWxZzz27un7+Fx1lPcOncvu6fuAjSMLVy85mTfgScLGkJc3fv+4ZyzG2SYvbRx5294d2+Yv7H0wPz39Rt515hvXS2xGR+rApwFPWABOvOTTnddPPcaGhtAB3Nn7O35+wD0bvP8GE5iTTjqJ2267jV/+8pcceuihqHzl2hjDddddx4knnshJJ53Ev/3bpvPz3izIk7x9gcnZCeAW2UiwfUVswbuQtZ3ATKRI+jXT2yiSHhh8QBJNZkjjMEWFbhpkrdWxAAafA+K0T3APahbV8jc/kRpcQZOVA5TyN8PiihYis754phZeESn4lTgb+pUv1TTI1OSFtSxq2uQ5PBqsw1R8fktHccgLaXacutpOYJn/PFIikhQybwftVSFf56ZcjTvEpk2WMA41Xc9dXma5fOW5LtlwD62RIq0BRTRtCOp5QqX1Vp8dVxigOVqgoATBaoWo1mYslpMUoRXJwiFsJAnHE0RscAWvhKW9Xnptt0uuVJlQ4oRANwxpSWN3GCZ6fBJRdTMqz1ORZjMhcl1sELpKzPrJxqYiLhtLhABedcFD69x+z/Gv3OA2uthwtOuhYEEZEJMCkUW4ACYLZVb3VqhnIQtLE1gEZR0zvzxFLYtYPt1LZiTVqMhwscaqRg/TjQK2YLGRn5y7PDxNZEDQDosCkwnGG0V6oxYl7ReY4lQzPDCNHHQcPPIX/lIfQkpLlikm6kW0tMRGoYSjJ4yxTnhDgVZEGns5IqhJgppXILKiAOny+ihtdy/nyYualYeYWlTsCGv+XmpCn+UfTQjStOBDuyJNOCnxT6YALKSyhIyhf4qOYY6JvDOYanqjgsZ8RzaQgXQMVRrUgpCatGSxpjCckGWSbFURpwW6LryqIr1K33Yus1oQ9wlaQ/7aqZYnPabovIqiHXErICqkXgULDLV6gClAVrKYgsCtFuhYoJKZAp4ur5WjEkdQExTWCGS1+zzZUCzpX87uk/OedztPnYy/jf8Abuj8/VSy8kzkpRM29t3HnnG/2SFnS4If8N4hv98ljzw3paNdG+apCswX9j6Ym07aeZ1E5WrWTV5mkxV4Oik6Y/EtcGTIPYtveUbSMaO6zJCXg3/xP7jl7b9ZJ3kBuOXtv2F0ZMOVmMsOWMzp//0hzvyb72zQ/htMYH7yk5/wy1/+koMPPnit7UopFi1axHe/+13e/va3b/kEpp3MDp0JuIgT0AoX+O1pxVsEQzukqq2AgG5BWpIENe+OIjLnc1KqdZ/E30kWFyAlQc0S1PKQsdT6BH3h3VOyokI4Hx4lHehGSpY7YznlHVFwUBhLsaHEGdGpx4IQ3tpZe8e0aCKFOPGkxblZSey2k7jucoc0lxlf5zL2BEdO1ZA1iQsDXCny1yTJ/HHSDBcGCOOJj7A8zZ7YVgq0RopkJUnQtIgMb0GtvLRvA4lu5m5qeWJq2hMAFQJjvHOZMT5Zv6dE0udryyT9Ie1oUde2nnYgE4NqZaS9ESaUnUJmupGiYklrOEQNV9DWIuIUl+TOaEnqLTGTFGEtpaXdolIvRzzX/Jc2mXgu5GI2NkZ1Oe+TH9yg4zwTeZn93j3Hv3Kt1xuCN6tf87OJgzZo35cbpAEr6NRKkQ7Cql/ltysK3CfnM3doinmFKeaE00xlRQCsEyhpCXXG9pU1lKS/P61Y0+cbtj6RP2g4VNOS9CrifolVEE0InIpoRRl/GR+kt9hiolZCCIdWloW9E6yMe5hOChSCjLAQY5wgUIaJRhEpHNOtiMFyg3KQYK3ETYYEdZlbFfuftiuaNH6RSMb5otUsgxSvvkuC6QwnNWlZdsK6ZOIorvKnYyJBVJ251zrpiY6TuWGB8KRJWBAJZGWob58R9LcInKBSbtEbtWhlmleMrEHm+UXLqgOMjfvCnm2TNBMKokkBNU8A04qgvsD6+C/rn9lZyYF2UM4oVmKEcNTHSugJjVvYJOyNcZWEbCoCIYkHfX6M1ZpoynhFSrddPKVXddyM+UIXz4zZieCbisTMxq/4n7yWj/KG8//Eknzb7JyWdf39TO89db/dvz1T++U9N/V03i/tWKHxSO059Tf5zB84jbUdxJ7697PBXXYG0SOXbVSBzH2rr6G2+/ufUcm5s/d33PL23wB0fq8PZ137Ue7s/d0GqTEbSl5gIwiMtZYwfObkojAMsXYrmfC1k8bBqxEon8thLPREPg9FC3TdeKet2KBiX1DMRL4miw0lTvtVnmh5wxMH8GpCXvHeF4cEpwVZqAimU9Ief41Vy3Riap0QpL2BL2apBWkxIKkoH3aWObKyRsX5ylfbmUxLTMmHtKW9msrDUzPnJ2YVjezYKM8ibU9NcDcGbG7LnM7UfHA6r8nSiv21aSsvWnVIjItC4tEKaVkSNHKCkfpqx9KBKXiSxuxiXyL3zQ9DZFJBjdc80SiEZAOljh1l0qsQdobQmYLPeQls7uKWGJz218Zqr24J40MeWiMRYThA+OQUAnyeTbtGjrM4K7z608VG4eWswrTxYhCXp37u2Y75bOTlmfZ71QUPbTCJ6RaxfAbMdoXPwCh8wngGuiFIxkOmyxF/qo0wJ6oRqQwpHL1BiwXDkwTC8o7+xazOenm0MYTSBlsSqET7ECjpnx0qdcgEXOTDlIJpgYoyWs0Q5wTlQsLcyjT11D9bxloVEqsYLtXZqWc1k2mRik5IjaKRBhR01ulLmiqCqkTGAhs4TI+fiKuGdxvrOHK1SwbkRYz9+TsQrrPApxKHcrNqr7RNV1JPTmTq3zOBJxLtEC/wC4HSCbIiNOdaKnNrBMqwx5zltEzA0uoAq1f24UYEe815gsxJVumMcKhFUo1wBYcx3t44MT7mzmlIesAW8mdVYLCJhJ4MhGPe3EmaSUCtESHrClOxBMoihKNSaTFpJEwXSHscTSsRyx3CSEIxY8ijY39tIuMwL+T/2laEp7pZ7fLQaKc45cbgPXe8k9OeIXTrrBMuXuf254N2m7PJC/CcycvzhbvsDADiHb3Vc/TI+h3TIFdj/u4W+MzauS5/uex/84v/WsCJl3ya2frNPqt+yV0jRzxrm22FZmPUmA3BBtssvf3tb+f4449n8eKnM6jFixfz0Y9+lHe84x2brGObBe0aIdaA9XVJnPUTc9FKcoXBdQozmqLERpKsqL1j2HhCcWVMOJn6m7ODaE0LUWv6UKUsW/t4EkxBkhX8jDwraZ+/kefEqEaGzKy3iexR1EcjWgOarOi9/4UD3fSqRVbUNOZFxMPFDokRmSdS0XiKnMgHUa4quTRd+3ydL27Zrq3i0nTG8jmvEUNmvHuYtf5aJKn/STNoxTPqDuQkSmF7izSH/MqUMI6sJGkNaUwgUa2MoJogDASNDD2doKdTbOBX37KCJJ5T8KpP3mZa0Z2Y6zbaVZit8i5opqC8qUFmUbEB6wlR1hPRGi6gYktQNWRlRTZUmbF2brentQ+nM1sJIe9ig7G5ili+FHNdXnXBQxtMfrp4Ovz92RFMO1TskJlXY8JpiCYhWq2YXlnhz2uGeHByhPGkRDUtsLLZw0RS4tH6IL+v78R1k3/F47V+pHS4hkY12xbKjmAqJZzM0C3nlR7pFYTeYotCMcE5mNdTpZn5hZ7MKbS0pEZRSyKW1gdZVhsgNpp9h5ay+9AK9hp6nILKyKzEGknaY4mHLMmg9YntkT+WrzcjiPs1SX9A2qPJyto7bjpyu3//PFOxIxrPKD3ZorgyobgqJZoy6JYlrFnCqiGomdzwwBFVDaWxrJOsL1Nf/yYZcBS3m+bgBX9h+/5xrJP06BgtLcXeFpHOiK2iqFK0tJhMQSrQxQxTtqT9hqTfkZV9rRwkiEzgioawP8ZFlrCUMDKnykChyUilhtYW25PhigZrJEkjZE65TqkcY/oz3GBC0mupL4C0LIh7FWm5bdPsz12mXq3qYv2YTV6W9C9/TuTlqe087b1vv/85tflU/NXIwqdtezYF58VCm7xEj1zW+dkQvCatd14Pfui+ta7hL/5rAcDTwsXWR15OvOTTa/09mxQ9X2wwgfnGN77B3Llz2XfffRkaGmK33XZjt912Y2hoiP3224+RkRG+8Y1vbLKObRa0VYhcCp+x9zWgJCLNUNW4UyhLZC7/8aFabaeytOILPUZjLdSqSUjTTtV7oDPJl80s96D3K2nkiX/eUcwgk8zbM+ZhallR5Mn+bWkGVCND5YpGllcRdlpiygG2oAjqGdFja3Ct2JMoqXzeS7uIY/u83UzCO2GuarTrw5in3Hkz4yf3WZsAOU/08qKUOIcLA+xAhfrCMipx6GaGbhpv7+wgKyuSvtBfO+ELdLpA+esoZm7+aUmSDJdxUeCVHeHtL1VsKaxJ0S3j83+SGW//uE/5ZH6du7QBQT0j6dM05mqSPo00FtWymJLG9le8E1v+vTtj89ygzX8j2hKx/1d//KJ8ZlNjc5CX8z75wU1CXl5IAtQlMc8RDn9vVz7hXKbOJ5Tn+RcqAT2hqY+VMHnOyWTLh5EtrQ6w5KFt+Lc7/wc3PLIztTikVQsp/0UTTXkyJJybqXrvckJRhHTAUAkSjJGUCwnVuMDKag9PjvfxRLWXyVaRkdI02/ZMMBTV0dLyeL2fpg2ZiEtMpkUsgpJOENLiIosrGVxgMcMJuiGQqc/zsHmuR/s55hef8h8tvItmKBH5YpJw/nkpU5s/R30YnEysLwHQsl7Zib0Nv0p9IUlTFGQVsDs02WfeMiKZYZ2381/e7GWqWSBNNPU4ZDwuM5kUaWUamwlEOWP7uWvY86+WMrBgChc4smLeX+3zeERg/e0+fywqaekPm+zUM0alGKOKBqEtUllkYNHSUp8uEPbGBIUMMTcmHjY05wiac3wtHhN5IwDVru3WxXqxLtKxpH8577njnetMyN/loVG26z+fV/+hxnvueCe7PDTK8k9dw5L+5c96nE2lwPxx1bJ1bj/t2++n8Uhts6gvbfLyXDC7Zsynjvkm4Tmv5reHHsJvDz2EfVZtuDvYbDyV8Hinsvoz7L1x2OAQsoGBAa644gruv/9+fve7361lo3zQQQex6667bpIObVYM9SGq+UTfOpzNCyqG2k/WtUK0YsLx3P0r9Cv9wVScqx0KW9SEUwmyliDHJvxkOCdDzlifa6K1r3hfT1BxkbjfExuZekcuFZtO4UynBVlZEdR9mJpMXGf1TddSZGaxQiETSzRtsIHweTLCh6EFS8dwzeaMwxrM/G6TFsXadVpmEZZ2/7F5PpDWXoHJi21i8vwfraFtk6wkpq/I9A5lsqKgtDpDxgZT1J3CYk56smWLGqS3PbaZIyupPPnVoVs+ebO6fchgowdZS3zoQTt0zYFVEolFJobCREZWksjYYQoK3cg69XpMOfCuNHmogsgcQjhsKEmGSgRSosariDjxD2NjnjnB/2WOE094H1//9g+edZ8NDSXbEOKyz6uiF9yJbHORl03d3gtlr7wxIWVdeNgAXEGgW46g4d2uhHWkJYlNHCr2oWRmTcDKZJiVPX241BciJhNEK3ReINHRTEv0TkE06WuM6JZFJg5T0F51iQRpRRAPOIpzGlSTiCxVDAw0GSg0qIQxmZVMxQWsE/xVr39+D+o6U2mBgsoYT0qsbpZpGU1v2KJHx2w3Z4KHmyOQSmRDoVdriiv9Qho2VxXcTPgX+BBh1UiwhQBTVqi8VooTdNQZGWeolncuQwlsnvgvjYMMbCgwLg+TTgT1BZD0WvZe+Di9OmZpfZC5xSqvqjxOzRT4Q7iNV6ny/BcpHKEyBIWMvkqTbcsTRCpjVb2CHGmRqAg7LTElh9MOV9PYfosILHE95MlaSJJpXjX8JJmRDPTVCbWPoJhuRSyb7CeIMob7aoTKsKZeYnoqIBmwmNiHqAnnlSqZOsJph2p1JZjninaRx6eGkz34yhW859obIM898dhjvW2Vdqx0/t7vQ2uXALnjO89N8XkpYL+DdttgtWV9aCf6H739tZzS+BcAXvVGn4pwz419z+g8tqHYFIUvN7oOTFt52RphCyHOKl8xXgmcNWANLs7te43uhEyJmichPpwqV1TaE/0sw1nrw6+sQ8zKrfDFJY2vt9KMUbElm6MQ1j+Ewmmb57xEvtaL8KQFC9GaxEvzWuSreBYbKJK+wDudxXksr4RorIlcU/UJ6kJ2nMbWqqkic1c0Q+70JXFx4rcLMVM4shMalr9W3tHMZT6srKNUCYHriTB9RSZ3Lnek/6DqDQKcEOimV0r86pQg6Ql8Pkzii0/a0MdWm8gXypSZIysK4sGI0lQTmbm8Dk2eOKq8K5tMDOG4wSq/gikz5wlTbmigGhmFZkY0oXwujPUPRpsqTKRIBwsAqIlpaLbWDrHr4jlhNol5KSgsz4TNFTbWxdYPmfofkRf3dXk9Ej+b99tFJig+oTBFiUyFd/YitwoOIBoXhFVPXHB5QUbjw4+d8gUc8/x/f0+znkksnDNBUacsKEwyqXyRypXTPQyWGyhhGdB1emSLHStj3F8dJZQZSji0tBRUSuok25YnmJ4bMVUvkk1W0HXRUVwEuf1/7h4pDH6RK7OdemUAMjZ5bRif2N5J8M/VdBwIMVN3SzUcWSUgK0riHklzRBDPNbiCoaQTJtMi4y1frqFWLNCyAXv0PMlIYZrMKrYrjvFYc5hqoYAa9GqJloam8TVn+ua2eGh6HqaUF6ZMBDqWmLjgOZjwOUvjk4PcMF6hVImZ01OjFkcMFhtUmwUcMNDT4JX9q1kTl5HC0RoIyWwBYX3hzMwJdANU4B3Zunh+aE92Zyf27/LQ6HOaBJ/27fdz1gkXP428PBv+n3nP07Z9RF2y7vZf5Ir0s/Gqy5JNWgxznvWLh/us+iUZ/4N7buzbJO168vMiEpgkSbj88su59dZb11JgDj74YP7mb/7mWZP8twhIsD0lVCvxE1iYNWF3uHbyS+JLLDuYmeTDTEJ8W9nIHVlcnPgQpXZOhfBqjIgToidrWN1DWpbI/MHllCCteFITTiSEqXcWk7llsc0T6p2SPuY4P7xuGfR0ghqvzTiOtfvlnHcYkwoweYKlmLFTNjOJh7QT9cNg5vyc8efinHfrarcrpN9mDEL5EK94KCKsW5KyJKoaspJCt7yqYoUPhcsiQTRhSSvKn7eQuWOY87bKeaFMkTnCmsUUJLYQolqGrKjypH0fcqbrGTZUuWpjvEOcnDkfl4dYyEYKKpsJ+ZMSV9D/P3v/HW9ZVtb54+8VdjjxpsrVdA40NEFgBmFUbEEadBzRURBx1FFAQXCU6CgoEkQFDIA5fJEZUNEvOj++Cj2I0IBgICqp6dxdXfmmk3dYa/3+ePY+594K3VXVVd3VeJ/Xq1517jn77LP3vvfstT7r+YQpbU/NJehJLl2YylVtq05cL/vJH+HNb7331f4t4HLiOleUr60uzPlTLlYYK1oL5RRBiX4yGnlZYEl0ld+iaB4FU9Fg63BF5SuAU9/GjVC0gGmXOpvTVVcZIh9I1mG50+KKJ9zB7rTHv63t4cb+ToaF5Mpsaw+5sLXKct7mttESD28fYNEOadqcQZFwQXuN3ek6R/I2Pmi+uLqD1X4Tbm4R1dQxJZQuY6jyVCRvTJeV3XHT4lND0bYSItk1xD2HGcm4EiKNxxKMrhYBJQMtWCV60tLjrWKyoJksKSbbPY1dA5baI/5D9w6OlrJ6PnGWuyaLrORNvm7uTo5mbeajMVll7LK7sU5qmmxLhljlaJsM3Qp4FPt3dBkcaqNHGpPJeBP1pDvk0kDZ8ahMYQ4kjFoRd3QT8Ir1pEHayGnGBbtafTJnuWttnnEW0WpmTKwnn1iG7YioZ/BGoe9WmMpNbatOXKezGr+RHvZF7pkqdjbrZGDl2HogRftnq/uysf7b5Ld58btfxg2//2r+9SNzPPKb1/nXj8zdp+5LXU995n7+73v2nPH7TxnA3HzzzVx33XXs37+fxz/+8ezcuRMQAf/v/u7vcsEFF/D+97+fyy+//IwP5oEuPcigk8jEfTKZgZd60l+WAkS0mVHCfJiFLNbAxVrZfmPVVCznZhP/skT3hyRHI1zSxOSyDx/NEuQxCpULePGR2FCWHblBm0w6I+mRHHt0IHbPFdULrSXLxXuIouoYHMoaQuGFFudq1zC7IbNlgyyq7tjUwMy5iopWgZoK2E2vk1KUc42pCD9dE22KHZaYSYmPDD7WxH2PHasqGDOQdWU5LxpKx8mMPcEoylSTrJao4ClahmIhJVqfgEooU0O2GKFcoGjH2LGfmifY3gSf2GmAZ4T4/2ur0ZMSrFAZUErybVoS1AkQkkhE/CGAP2WJ2Fad4zpbNLKtbst9qy0Qc+plioDrgs6rBZQKjNS2+aoMU32jckIvk46KdFWC2vCaE4GGcQKC6vwsk4UqQ0vsiPNOtepfWVhmzrIybNJMchq2YFs6IPOWQ5MOq5MGubfsSns8pLHK3cyzI+2jVeCuwQKHe20md3aIehqz8aunmBnZJPK53hrsJFTOYhLC5a2iTAUcqHLmVFaXzkpCPd5UAhQ5by2LXFUIpAqyaHdxd5lFO8ChWMkuwnk9pYwdzGRVuGFyvtDfw0XNFfql0OUOT9r085Qrukew2nF7f4lWkjMaa3SuMBNxWEMFAkLZA8mACb4S+fci6BSkjZzEOvrjBKM9ihb9YYrrxWRxgjKeufkRrjOh32iiypi8r0jWIURbCOZE9a28A/in+/1zT9Z9qZ8/VSrZw3Y85JQCIM9lveHvXkDy2bMPXgBWXv5E4Ik86fmvA14NMAUx9WNgCm7uqU7UvXnqM/fTftm3n1bgZV2nDGBe8IIX8IhHPILPfvazdLvdTa/1ej1+8Ad/kJ/4iZ/g+uuvP+2DOF9KlSWqcPhOAz0aT7UwFJnoO2q6VSgJZeXMVdOwjtVLODcVwYeq+0GoOh41CKjsme2BVVqFJ9vREOtk56vFGo1LBCx5Lyt2wj0W7YYdBhp3rqPGGWE8EdASR4Q4JjQTQmRwqcWMC9AaPcohy1GZ6FiCD1DkFeCiAj8VSNFq1mkhzCho1JS56vg3hmBacZ1xkYRzQkUxyGdgzg4KlLN4Kzk2QSuSdTEhqEPGfCy0ubojpQuPHVWrjqVHZw4/Z0nWSuywZLI9JihFPhfJ4N6RSapygbhfgIKyG+ONwmqFWZ+gnCMkBlUE4rVMaG2ppWzHRMNYXNW2OjAnrLf93v/mZT/5I6fchTlbVYOPMwEy/56Ay7FdmI35LmejtkDMqZfJZAJOqDrCOuASI5lVVdVCfB/raQaK8hD3ndjja4WPNF5JflYYiUBeF0qyVZS8x1vp0tih4oZPP4z23h5WeyZ5xPpakwODiD2XHWGURygVKJ3hVrfEobjDUjpkVMb0ipQv79tF+qUGOoe4LR0Jf+WIEBTsa2CHSgDNWAIti5Yi7gf8MBD3/JTaViZqmlXjq+66HRTTjjheOuGuYcW4pvBTepyPFGULirkwTbL3QdN3KV8e7qbwBh8UgyLh6s5Bbhst0StS9jbWuLp9kNWySeYsVnvWMuHXjV1EJ5rQiSf08oQQB1SmsGMojNDvkpXKMKDh5bq2HFGzoCwMSaNgsTmmn8Vs7wyJjGNURISKskeAuFHQSTO0CgzWG/L7TBRFA1SxBWDuqc6GJuJUq/6cb/olWXB/9e/+J1734/+waZt7o5dte0qH9/7Hz/KpW77Mp57yZUACI0GyVO5PQHNsMGVdi2/a/PzKy584fU6AyanXzz3ld3jqMwXAHAtejn18KrVx+8f2vp73cg4BzD/8wz/wz//8z8eBF4But8vrXvc6Hv/4x5/2AZxPFZRC5QXlUhudxJDllY7FT7u/IZQyWcfNxO01NSyOIMvkH5WwnapzXHVdppP/mt5Uih7GHAk0soLJng5l22AHbsp31j5MKVI+0kT9AnNwODMJsEZyXRoJoZVSdhIRRlo9pVopD6odoUrhDkcrI9RoQhgp6bIoVXnSGcIkQ8XxrGNE5UhmzCwnxgfw0pFS9cpa6aoEZhmgzMRV/GePa8boQuhdPgkEq8lbEvJlUyN20ErhjYCeaOCI18sq0FL2LwO8mATUQnydlaSHRcxaNg0o4U+HytnNjOXczMSJ882kgCoThopzTenBanykJE+hEaMHBraCx87LOh0gczLg8q9/ffcpf94jn7H3lLf991KnG3j577WUg7IpnZLa+j5Ua1mAAJsqEyVUOTGmEBcuMyql+6JAFR6jFGaQExKDTwzeaCKY2urXYY9xH9hnyNbm6e/JSVo5odDYvubwWhtjAtY60qjEaNGI3LG+yNF989ieIV1VxL0q6f6iCc1Wxt65dQ70uvR3aRxgI4crNVFSkq2mJIcsczcryqYEagZd5bu4gE+kkxT1cig9yki+WIjM1AjHxbr6JxkwRd19KcBU40s3mnDLZAfrRYNONAHg6FiocAdGc7RsTqoLjPLsTVYpIstNox3Y1LOWN8i8ZXW4gFYBrQLN3QNGrk16xJAsV2YLw8BkpHEthV2cMNcZ47xCqUBWRBxa77C9O+CxS3dyJG/zlZWd+L4wHOJ2zkJnhNGeYR7T7GSMOhHluhEt1HgLwJyoPsgP882cPWvdM6ljwcu91eh9Ee/92c9OQdfj3vvbANy5T16/E6bPbawLL/iDM+o03Fv94W89nuf+xKyLdSxwOdHzi2/6xD2CmBO9/qTnv25qqHDD77/6tI/zRCDnXz8yx5Oef2YA9pQBzPz8PLfffjvXXHNih4fbb7+d+fn50/rw8660ngoMQyJ6HhVHhLoToRUUTroxIJ2LjeL8sprYR1YoVr7KTam7LvU+6qpBjTGiuVleI80LfKcpNsiVLbOPBYjEqwVmUmKOrAu4qmlpcURIE8qlFi612EEuAv+5VFa7ELpZUPWAYsi3twi6TXx0iF7pi1NZVSqOhUo2dSkzKFsdf00Z00qOvTqvkOVCvSrEBnOWBwM+tvhI4xoGOxRnMLwMctEwVB7/ugIvTMWuwQgnuWxKV8fkAeU9ZlxQtoTmpSYldpihmzEqJGTzES5WxAOHyTz5XIx2MhkwfRn0QmwFEAag9OhhRkgi/PaUEotyCXpZz2yht+q4evNb/5iX/eQDm11yb7SyE4GX0wEux75nC8hs1emUjxSkAiyoKGSiywv4RG/qNkiavdjDU92ndS5hxj7Slf18wLXjKc3MJbpaMArYKmfGRxVA0grtFGaSUDZjrAI0lIcbFHFANUqGQZG0cg4d3ka0pmmvK1wEPobBRQFz8YCv232ATiTfMa0CrtOnE08YFAk7GiKav62zyKF0jnUSor7GjiBd9diRx44dLqm0Loj+RRXVgpHV4j4ZqSorxgNabPJz0faECMrFkh2dIWMXkTmLDwqrPVoFfFCMyhijPFd0DrNgh4xcwh3jbVzd2k/DFLRMTjeacHjSZuIiBnnC+qgxHaJ8BDaX61a0ZHy265q5i8ZT57GFdIxWga8e2k43mXAo69IrUrQKqIaDocU7zaFD84SyMlF4yDLshaLXxWTqDCyT/n3Ut/IO/vVn38Yjf+k/3q9dGICP/uzNfNMvXc5Hf/Zm3vB3L+D6f/7gCbf7wi1/zY+84qm8+ar9m57/q94juO6WZ7H8+VP7vDv3PY/r7Q9wXXl8I+C+1EbwArPuysmATF2n+vovVvurfzcbuzEnqxN1aer64iv+PwDctz0HEEH/i9/9stP+/Z/yV+q5z30uP/iDP8irX/1qnvzkJ081MIcOHeJDH/oQr3/963nxi198yh98XlZkwYEZVJMiK7QxZarOidKVUL1y9apT24sSFdnpZB+QrsbGgMSwIVuk7sxs4ARPaWbDMaYoMSsQxZHoWPJCOiSVML+mtqkquyQ0U4odbYJSRL0MlZfV6pambGrSIzmAULm0wowEkLlWxGRPh7gZYw+sEibVeU9tliuwptRmfU/dgdHiVBb0TEdjJiXKVaFpLYOuVtZ0KTaSwVbOMwoaq26aaTNOxA7UWwmw1F2LH3t8LIN8SIV3oEqPGk4wbQGY5XwqFDlklbLOXci6ct1tFoiWcxHtRwa0pmxHonkpHCavuk+lp3FgRD6fiD4msjDDdFu1oU7FRvn+qtOhhp0JeDn2/Q8WEHOuaWRbde/lIigXxe1QVVbDQvMSrUetI1FOsr1M7qe6RnEo82JVXGVs1d0KbyXra+rgVe07KKFsheoeqEpF1BNqbtmEsgUETciAoUaVCoYJ7QFTi3k85M2A25Fz8dIaPihWsyY1B2FPa53b+4tMSsuoiGnYAuc1re6E7ArH6FCD9JDGTBQmVyinKRsV9VnFxGuZgJfY4FKDi7Ucq5tdi5ruEPUg70LczdjZ7LM3leOBLrvTde6ezHPV/GE8iguaa1zROMQuu8a/ji9kV7LOwKVc2TzI7ZNtlN6wnjfY3VwnNQWDLKY3aBCvGswETC4GBEVLgjpdEjh6pANesXP3GquTBpfNHeUxe/cxKBNuWV8iLw2TPELHDhegHESoGnh1SubTMUZ79l0S4XpN1BaAOWF9kB/mDb/0Av7hKdfytzzzfv/8j/7szcDxtLK6vnDLX7PyR9fw5j/a/L43/N0L+OglNwCw9KgbTrr/5c8/afp46VE38Gs33sB1PIvrLzu7Bjftr7yL3/jQW6c/19bHZ6N+4eueyM+xGaW9/B//J79+57dTPvMbTvie06WUwem7t53yV+q1r30trVaLN73pTbz0pS+dTr5DCOzatYtXvvKVvOIVrzi9oz3PyscWCgVFSWgmqFUEiIAAkanLmJ91VADVSGeAZQpKNmhitEJFqXRZKscyVQdJxpFoXkIQzYXWkjnjxaUMa6cUr7BRk1GDoziiWGqhyoAZ5eismE7Wy6ZQrXThUJXlsLeymqd8EHoVULQj2DkvICbPq4sxC6mU3BVf5RNU51mBu43XAe/Ra0PMXELRMRDAxZrxNo0uIO5rSY8elDJYhtrBJuAioRzoMpDNKXQpXp0+UpIjUIbKTtqjxhnxoT7lQhPXkG6KyRw+NgKIEiUBaEYRr0sYqBKvToJR2EFB2Y5QlUucHuVy3asgS9cwM9C2VSetugtzf+pgHug6WyDmp37jj89p+ORWPfDlozrAUkIm66rzQHyVUo9TYnbSz9GjgpBaobgqJYtRVoMO4kKZWlSp8IloZ/KulQWe2rnMBWweMIWqgo3lOTdShGWZqMuGVEHBoVr0qe7DqdB40YG1cYOslCmCC4pOnJE5S2JKGraYAph9kzli6+gu9HFzQw6li2gnmWCmKQdmMumeB1ULYKQj5Z0YF1C5sblUT1/TJcTrivGBJsNtCStFiy+s7Oaq+cOsFC1WsyYLyYixi9ibrlEEw4prc9toGzuTHpelh/nKeDelNxzO2ty9OkfDFoxLWWBz/YjWCsT9gB0HijZkC4piR8W48ApKoY/VnZ7L2kf5/OpenNes95skSUGaFoy9QsUeFyymU9BpTVgeN1lqjOi0xxS+OQVpW3V8Pe5pv8I/8IEH+jCAGaCZ1YlZRx+9ZIWXXPUH/NqNz7vH/Z0M3Fx3y9kFMS999m/xivedOmj5X+kLAXEZu7c6EbB409e/kZW9T2aRD93r++uOy7Fl/vZdPPxX/zNwZrbKp7Um8MpXvpJXvvKV3HrrrRw6dAgQG+VLLrnktD70fC09ySHIJQlao9OEUHdajJ7q1qc0MFX15UOY6Vs0GyyUjehEtJEOSxTNwhGNEdF7EqNKJ4J5MxvlQpUvo1TVcXF+5nwGKCvdBLeti0sN8epEBr0QCMZQNoVKZcYenxg04FI5N41YCvvIiDjUKLJtKcrNYQ6uCmVOGzmHshQws9FBpijBVI5ltRlB8IBBFSXRygRvxZDAJZrGUT+1elYhULSt6FGKSpSqFSaHaOzxRlV0CwEztaVyPHLEqxlqNBEQ0x9hnae8cB6farFZjmR10uSSTWAmARdr0Q2tSxfG9Cb4ZoxLDCY41CRU4ZsCbkzmpJNTbrDH3qpNdb50X06n7mv35cFWJ7JS3urC3L+lS8RtMQoUHYU6ANoHodFaLV0UL5RlMyoxQ1k8UuPapj5AUaKqH1UcVfb5s4Uyk1X3SC/gJF0uKDpWDEwGMtYoJ8Yo3kgOl/LgUoWLJItL7r+eoqHI5oWypXUgtiXtOMNqz8FBB60Ct64voVQg0h5TCeTHw4RRocnmJly5/Qity3Nuby+R3ZXSOChdoaQnRi1mlOOTqls/LPBGEYyZJtXXJgbeihZGF2D7imERc/tgkcV0RKJLtsd9BmXMep7SL1L2pmsYPH3XoF8mXNkaM/IJmbdsj/scnHRoJDnDIqY3SckKS7RqsZNAuiZ0t6JlcUmAQkCUSh22ldOMChJTEmvHp5YvZC4ec3c+hzEeYzxZFnHhzhWO9NtE7TFaeyLjWR81iI1jvdeke3aCx79m62xTqs51veHvXsBHWblX8HJvdd0tz+IlV/3BfT7//OWf5207PsEFv/sn7PvxHzql95wKcLm3WnzIvYOXeyr3bc/hi3/7LvnhI885dxSyjXXppZdy6aWXnslbz/tSTrz4azAwXYWvb7BlOaOUQWWzXE3u66yXaeaL2zzJt3pmBa/UZo2F2rCP0qGiqLIwDtPPEtvmDRPryFK2JMRSgsIAr3DdmOGeiKKpUF46MWWVCG1HnrSfVYnIYs+pEacv14zR7SasrM/Oqe4AOS/al8iCtrPjrf5X1hJKh9IaszYgAYqFFGUC0djJgG3ADp3kA6SaqC9GBS7RRGOPHXq0C0RDuS7RsCRe9WITWjj06gDyQj4nBOnErE6Y7GpiJh47DkwWxYnMjKvMnEgTrYsTmTcav9jEjIupHkjlJbiACpUup2ExWQlFMeu4bdVWbagHqgtzqtvfUw7MFoi5/6pMISRBqFSV5g8FPpV8kKDrUEtAK3xa3VddQOflprFHxiVNaET4yEiXmJnwH8TtKluMGOwy0sEoJIMmHlSByGXAjpl9LgIWbHWvVEGhHcRHLOGyjO2NIQvJiGEZs9gYcXX3IHdFC9y+vjjVhBTOEEqNsh6lAv0i4eL2CsPFmOX9aUVvk+OzIyfOmM0IVRmnUDlPBi0LV7VFtC7FVtmOJdR4/407OLgt47JdRzictTmctSm95paVbYwnESujBl9s7ebIsMVglHLb2hIAg3FCu5HRHyV0WxOODFr0V1qooaFzSPYflGgwTQ7JapUvZgKMNMUCDPOYRrPgtt4iRgVGOkarQJIU9I+2oNQcto4kKummGYWXcV6pwKH1DupQggoBk2119E9U7zX7+PL1b3hAbYhPtz56ycpZ29ev3fg83nDbfdf+HDzc4v8evgpe+5snfP2pP/+Z6eP/+9rHHPfcierF737ZSY/LvufjACelkG2sh//qfz5hF8b87bv4o13ifPDpe/isk9VpAZgvfelLvP3tbz8uyPIJT3gCL3rRi3jYwx52Wh9+3pVSU1/6ekVoGgbp9WxCuzFV1zmZ0NfbaTWb7OuZ5kVVFDBVh0dOdSX1thUgqBKKJZPFiAsaSPdlMpFOj61cXJKIsmmIel6oBlrjW6IJiAcebw3jRUXQAlbSNScZBFqjsgJVKIxWwkdONMTArg5xXhBG41nuS20JbbR0X/Qx54AnOEQPU0rXxniPHk7EztlqXGqnDjx2LO5kuvSowqFCTDSsNCxAXEjmjc7Kqf2zGoyqrohGmSDHQ4E5tEacWIpuDEHSru3QYUel0MQq8asel2A1+VwsQWpx5boWAqoo8VEyDb/U/YmAxS0K2QnrfNLAPNirBhtni052rkIsT1RbDmT3XMqLda4dMs18KVPpLthxlVZfUbdCZXaCaPyr8cfIRHiSEyKLbyYU3YSyaXCpomjoabaMS0S/UaaKbAnsSOFiyOcDulTYgSIaKpKew0zks71VRH2HmThxqgyW8Q6DSwI+t4zLiIVKYqZVYK1osn8wh9Gei9srtEzG0CXsm5NuRBqVWOXZN5ynN0qBikZXxZCVTYOPUlyisUOHGZfo3OONEYovQFACrlSlyQlKrk2kKccpX813oiOP70eYkYzVruVZGcSsZgvokUY5WEmbhChge5pV28bHgaMLEWFoad1hSVYDcd+jy8oZzoAde5JV6eTn86KFqdfpMmdpxzk7G32OjNtcsrDCzcvbULEn5JqiEEC57AxaBWLrGA0S/DCidURjx2LSsFXH15G9r+JxT3sr9zWV/XRr8Ue/wMofXcPjnnA1f/xDnqf+/Gf4kxWZx91TR6TuvpzNOlvg7ZE/fiP/+rtXTX9+3+XfAsB33Pz30+dq8HJPVQOXn3vKybep9UpveP69O5KdCLzUwKWuM7kGpwxg3v/+9/OMZzyDxzzmMXznd37nJhH/Bz/4QR7zmMfwf/7P/+G666477YM4b+qYoC3RftQWwid+S51MLzkvXoCOVgjXbLbPWngfCGIEoKUDo5yfup8RKgezSusSxpPZ55QlRDEqicUxLI7xzRg7qpxqkmgGujzYgaOZB/KukYGsrcjbBjtylK0I1bQyqQ+SraJijc49RdtitnUx+wvJiSlLMS9QFU3OUBkYuJn+xVaBl3UwZgiEoYNJhh5NCGksDs1VVoxYMHuILMFq7NoEVUp4pSpklc7kCjXOxcCgdIQsP948IIi0NLrtEHrvNrIlGTSjQSH5MvsHhEYk5+s9ZRrjY40zkjOjyiCZa9YIqEmsmBD0h4QiB1fepz+nrTo/6lzQx862oP9UgcfG7WrQc7qgZasLc/+US0AbARC6lElyMOIahg9oD2YiYY41lSwYjc4ljywoWQwL1hDiCN+wkqfiZSUoHnoI4pxVpvK/LgLp0cB4p2Kyq4TYo3t26kw22GVpLjvMJEzzWHykcYmaZsnoUhFUYD1LWUqHWOXZ21ynDJpuMmE9S2mZjESXHM3bgARNNqOCyDh6WYrWAR8FxjvETCBvaUwByVopGshqscpbJblfpdyPjRfjFqGQyXgW94VS7CNFvp6Ia9hEOjtFE0JPY8diBFAbGNTUY12AyaXTZG5J0YVk1dgsTLVDJhPWRdES10s7BpMpBhcGQqE5dOcio119Lphbp1ekbG9I0npkHNdctJ9bl5e4ctthViYtjg5alF4xGKT4foSeaKJBpQEqtgDMierH7nwH19u33u8OZCt/dA3X2x78Czz9bX+G+dt38SPA+HeeCH90r28/ab3pg58D4OXf+ujjnjv2+brO5rk/8sdv3PCTPP45AFrV6xu3bp1wH/cEXI6txz3tV7jhuwc86fmvOw7InEz7AvCjBy+YgpgfPXjBqX/ghjplAPMzP/MzvPKVr+S1r33tca+95jWv4TWveQ0vf/nLH9wAJi8gaUonRinRpsAmytj0cSXqVzUprO5I1FV53deTfKUUJJFsU7mHyesVwEnFVStEhhBbdG8s4KaslojQhLIUu+JGA5Si7CT4WKNzh29YAQGRONUA+FgRrztGOy3pqiceiN4kKFBeYXwgWKadCp05jFaMdzZojrvo5TXRANXBlqqyTq41MbWNc6j+rztOdZepslxWw/FMJG/NrLPhZvk6OCfArnZ0c5UuSOspoFNaE7yrHOEqoJTlEEeYu4+S5vNkO1pkSwnxWkFoRNL5KYV+UXQtQSlMTWlT4DpJpcuJCFbTuHVFsnmMYQpCt+q8q++/oQPAu5/Uf4CP5IGr+7PbslWnX0JllWwpXQhty+Ilv8oF9MShJyUYJZSqEKb/U5Ryb9SaEEci7Pfi5OgSjcmrXBkP2ZxhuDdQ7snI9se074K869l10TJrgyaTXKNKTWHBrSnKVBOv5+LEGAIh0oDFJdItKfdkaA2jPKIMmivbh/nM6kPY2ejzHxbvYFAm/If2rXx0/aEsZy2yLGKuM8IHReYsWgXaacaw1SRoQ9FVmEyRrlYOaUqhjKJMDUXHzhzZDFMHMhVkLbDW9qggRgimcoasQ46bB6XrHrSavtcbMYQpU4VLkAW9ETSWxSzH1N0vK1bWwPQY7CRgJ4G8rZj7qoQjZ0uBQTbHV+aaXHnhQQYk3NWbQ6nAzrQPS7AQy4H1JgmDUUJYTohGinhNkax5orEnbHVgTlrXlV04jUnzmdb1tseP/OOfcffjnj/93Ottj2d3XgPAH//q/+VP/+RCznQWeyLwcirbnU1K2v1dn/rAK3kSnLALczLqGLAJvLxw7bMVyDq9OuWgi69+9as85znPOenrz372s7npppvO4BDOn1Leoya5/AtBXMNgs9NWPZnf+PN0su5nnZSwAfCAgKI03mQAEJopIY3xnQY+lY5Kvr3F7f+lw4Gn7MQvtGXfG8GRVtP969zhp4Mf+ETca3ThiXo5Uc8R9wo6d+a092dEPQlGs8NSsmJKj85KdOExY4ddHxP1c1AwvKwLSSznVJZyfnkx67RU4CXkxYz2Vp2XsnYTzS6UTsBXUUjCfZbLe/ICxhMYT8TCOctFe1KDl4piF7wcQyidgKUin9H0jJbX8hx1YJnGrcskRyYEWzmuORms8qUUVQahr5WVHbMThzZvxeYz3d+H9f7xpgVbtanub/rY99/QOe7fsa89EPVgNga4r/SvLfrYvVe8LhPp2trdWxHMo4VSpisdiCymbLjf1ItAkSVEVhbDkIl/nf3iEsVk3pB1pSNjR4pmd0KxraR/EfhuSekMk15CctgQr2nsQOyURzs0eddStC0+MRRNy2TRUDQUkwsKoqREG0dRWDo2Y9EO8UGxfzjHwazLpY0jALRshlWOJCkonaEdZzRswY5mn23NIcn8hNBwFJ0g7l5NcRkruoYyFRbCFLwE6RBBRb1zAZMH7NhjM4/JBciYfOZWaXIBL6ao/uUBO/FEY3leFwE7CkTjQNyfjUcqVC5nua/ClkXEH/UddiyOl3Yi2ydrgfSwIj2isftjvvpvD+HzNz+ElSNdlArc2l8iNQVaBXJvKb3GO0NIvJjPrIubmosULt0aUx7IesPfvYDryi67Xzxz6nrcE67mvyz+FX/8q/+Xb334Vxi+79P8l8W/utd9fdNtiyd8/uXf+ugpKNnYddlYb/rg5/jcLz/puOevu+VZ934S52Ft7Bx98RX/H5/qrPDFV/x//OWR6B7f9xe/+Q8z8HKG3adT7sBcfPHF/M3f/A1XXXXVCV//m7/5Gy666KIzOojzpYJSMmAoJRPoaR6Kn4VXgriRwWYwUwc/Hjt5r/NdarcxY6pBTAYun1hCZBjtSihaGhdDtsPhEkN2c5t0Uoidcu4FGFAZCUQRwWjJVQmg8pK802CyLZY8gYnBTBzKeaL1onKikY6CziprziBt9LJhMEah5hq4pkWVAdfUuO1zmCwXa2VrwdXhlnp2vmy4FkZNtUDKGgEu3s/yaopimoEj19HVF6nSAWkBTTV42WhlXHd6NoRnSh5PmBkNeEcYjrCjMaHTwi1JNk6oxKLRoJRQOBcwQQI9625VfHiAWlknuA0mCWbLuP/e6t+ThfLXWtUg5HTpZFvg5dTK5AEqV3oXM3ULq+10vRUbZVVWFvWu6ryUlZukNYRE7kU+NuRzMdm8ESpVV5EtACiinnQkHr3rbu5sLXCw26GTFozzCJwi2+5AgZ5oWNUSeGkVUREoG4b+BZZ8XjpFpllyyfZlDg/arB7tcPtgNlHb3hhwTWs/HT1mX77EnBlzYWuVYZFwsC8uZaXXxJEjjsd4r4jnMpjLmOw2QAMfGeJBpQfxAjR8lYujCzGVkcZ3LeoPU9qdRlX2yqEyfxHHyajv8JGAw2AljFOXkPQqGl69tlaNyyZzQp+urms9zuhI44KhTAVQ2rEAz2Q94AdQNhVhVeFtzOghJWvrLSLj6UQZNw53UHhNWRq0cdBPad8pFs0uUkJBz7cAzANR19seAE94Q8bP8Tvsu+VTvP5DL+CSv7uSl/7RT7MA8D74oUVY4HsAOMg9O3m9+A2v5aN/+KITvvacJ88B8DmexHN+menjY+tzv/wk+Nb1Tc9dd8uzmH/2zfz5P3/6NM7wga+fe8rv0Lv2tfDy76L74e30bpVFjr88EnH1Sd7zgWc9iz/atY+nPe7MqXOnlQPz/d///XzkIx/hKU95ynFBlh/4wAd497vffcYHcl5UZGXVyyj06qBqS886KNPJdBTLhDmOqi7ALNslBAmYrO2SpRshVswhjYUWphQhjnDNmPGulNF2EQ5mCzC+JOfiC4/Qf88ezKgUylWhZyGYzk1pV2aUozqScq9KsMMSl2jGS5ak59C5F61HJRYNRqMLR9BatB8wzYuRXIAYl4jANBhF77IWC0d7kOeQZahGQ7ogquo0aYOKq2ujlQC1KJoFdVZGBDUNTFlbASE3Ay/GyDml6cztjAr4Va8BlSW1g+BmLm8bc3eODQXtD7F5QYgsoZmAFnCn/MyBx2ROBrP1Eao3mP0dTM0atoz7T1Yv+0nRX5xrAHOq3ZXvv6HzgNDJHkzhlierjYDknsDMFnA5vfJWgRXAomtDw8rIBJhq+oKp0ukrmm3QGyhlLlR0Zo+dONxE48uAt5rhHjC5YrItUCx4WjYjMo7F7ohOkjEuIoa+xcWXH+LgWpdJP4HVmDKFbE6jS0PR0uKO5qFsgBsbJmUkAY2R48igReEM4yJiUkb4cClaBUZlxGrWZJjHlE4zHCUMmgmjIsJqz11r8xS9BNMu2DY/YDBJKJoprFTnryBYoWqbTM5TBapxlik9Lmg17VzVwMQb0bS4RKGcwlo1XYhSPhCNwvQe7ytaWh0a6qvPDKYa86IN3S9Vf650TUwepp/jIoUuZPjRBbTusIx3adz8kJuXt1GWGu80xXpCtGqYu42pjbW3snO7ZWp50updKxPe7oe3n/PPesdnfoUffszvcMFljwN++rTf/3NP+R0+9/zb6P4K9F45d9zr7/qQgJITdWDqzku9zYnqD1of4M8599fhbNfp/u6uWfgQT7vgvuXgnDKA+d7v/V727t3LW9/6Vt7ylrcc50L2kY98hCc84Qn36WAe8KryQJSrxOt57cfvN4w6VBPpigJVaWJUBWbqgMpNk++6artIpQiJIV+MOfJ1mnzRYwYaNPzg4z7Jl/u78AcdtjeZOZWB7G9Dx0Gvj/AXtGTA0wrlPHGvQJWBaFRiV8fisNVJwYkHP0pN9+dTEYbWN/ugxeZYO7FbzjuacnsXO8kI3gt4qehVKo5lwHUa0mQK0PxcswI3VYdnUqKKEjXJZgJ+hFYmA3hFUas7V6EOEQviulaXtQK6fGDqG1rn7tRho9pMHwdtYDgCQPUN8WpMlMYVlS9CTTtbhZxbbUpQ21YbvZUDc5J68Y/9wP3yOWeLGvbIZ+w9p3Sv0wUx3/eMkzuO/dlfP7AdrRN1ZbaAy5lVPg90AulRybmyY49LKuew0mPGBZQe5WUsUUU5MzhRShwfI6EQB6sltV4j918PwUIRe8KuDJziE3dfIrqMzgBNYH2c0tnVx2pPfleLKFM0DslilrcwXjS4pKJUVSYDlJqVUYOy1NjYsbMz4Ck7vkKiC24e7WQlb+KDomkLbl9LGQxTjPX4QrM6atBJM3Y31im9JrKOURbjg0JrT76zZDISWol2RrQtTnSYwappZ6q2eXaJpmwI9WyyJONvnQ2j84qalSjKhhatTOaFPr06wTUjik5UhSBLgGbQ4sjprQJlBDQGMHmlDa3G/mgkvyex5hfjhbgvrxcNVZkEQDCa5WhBxqWgsGNF+6jCjiAaeoJGKN6VjmdjtvVW3X9VO4rtfdPv03v5ET55ccL/7w/+M7AL+M/Hbf/C3z/IwcP3vt/n/vF7+LVXnjwH5oQ6mKrj8hfPfTvfe5IOzvf+4Yvgsnv//PO5uh/ePgWlAF9++XcBcPWbhJ539+Oez9kYkU+LI/PEJz6RJz7xiWfhY8/fUqVHDccz/UvwMw1KrbtIkuPpTf6Y5ZU64yWOZnSoOCLEkhxftmMm84b8wpwL9yxTeM0l3RVuHOzki397FQ852BeL4WwDlU2LpXE9SVfOy6CYGtQoiJ7FB9JhgR5mqEk+XdHDasiqcwSCMQSjKdp2tuqUz85B+UA09mTbU+zhWCb7GkLhJaMGxL2r3cQ3Eya7mxQtWUE0mZ+GkdlJEIvKkSc9MsEs9wXYwPT61ff1aeeqPt+NRgG1DmdDx2uT65sPs2U22Kxj8YEwGkGeV10ggxpnUBRTm2pgBoSsrfa91YG5pzpX3ZczAS73pftyrgFOXfcEXE60zQMJZrZAy32voMDmkq1SazzqSbaq9ZJV9wOo7u9iHS8LKNIpV8pX1u8aFwtlOGgo2w7bN6RN4amNhgnzc0Mev3Q7Nw+3k3tDwxYc6HUxmSJZFpeyZKWyUa50GWJtL2NU+2bLoOyi5nOCU4yKiPWywb7Jbm7vLdGwBRe01hi7iCQq6QVFeaCJcoqBCWgVWM2bbEsHYjk8aXPn2jwA7e1DspU5OZY16W6YvHYOk/HUR4qsK5P+yTbF6IIS5RTBBlSrJIxkIcsMDfGaonkQopFk6qhSOjIhEpq2nThxmgRCVOXu5HWuWHXRFfhYyyCkmBr4TH+uaGwmA1QVjFzRyxqHAumyBEED0/DkGrB4q0TKNJLP9FsuZCesfd94Kz/2LYf501c//Jzsv3ftEd739b/H3//5n/O+7mt4xT++hl993Y0n3f5Tn9x/r/v8i9//AB/60Tv5yDFdlnsT79d1MvBS13W3PIvrLzu17sSun/jESV/LJ11W/uiaU9rP2a5pR+Zx0OX508dns7ZI/hsqKIUaZyIoh9lEduomtsF1qwYlSkvXhYq6pPUMvNQgR2vRq0QG14g49PgWZUNWk654yCEevbiPtaKBD5qP3XEp7cNhClyCVqIhcV60L9ZO9SSqdES9nGyhAlRKBjc9yqEoRc8TiXtNADBqKpSkCrKcDp7VCpaPNGXTUDb0rNHRbqKzHIyR8wOILG5bl+GFrWq1TBENvKx4ZQ6fGHwk1DhXWVT6uIFZTEjvHqDXBwIYtIR+BScrVsBMV+Q1KrGzAE8Q8Fg7kdXbasNUmFSZCATnRYfj/Wxb5wg+oNYHxwFOZS1B+Sl9TFmLirc4yyer80n7cirg5WQg5WzRv+6pC3MqwOVk73ugOzJbdeZlJxCPIOqHKehQJVUnJSZ0Y3ykK82i6BVV4YQ+BqAUrhnhE8NkMSKbE+fEYIEA8dKEMm8yPNSisX2EzwzdNGNn1OMrfie9ScIdy9sImUY3AmVTsfTlknT/iGxHg7xrMBMBC9qJq5l1kK9qXJbg50uOrLX5y7VHU6ylmG7OQ/ccYlsyYK1ocFF3ldV+k8wGmex7RX+YwhJ0rYyhyyrQTTOO9lrsmu+z/6IIt96iTBWmCJSpqkTukHc1w72Qb3NgAu1tQ66aW0ergA+Kh84d4oZ9l1M4Q1lqJttj0Ally2DHgbiv0KXGjEqxpc5lTCjbMT6qxugKRAYrWkiXGHTViQlWYSYOGwJF01aUMoXJPXgZG00mRgK1DkdsmANlU/SrJmfGtAAay7IoVjYkyHmrjq8LPnYpfOzc7f/iSw/x9W+8ks9/agcfqJ57xatfc9x2v/r/Hsb96Z187/Pv5C9+/wPHvb6xetce4WIOHff8S676A37txpN3Zc5m3RNwqStOe9PtDv7W117z4awBmC9/+ct8+7d/O7feeuvZ2uX9XqooCaOssu9VCDG4rITj9aCiZ2AGNukwpmGVGwEM0mqegRroX+p44uNu5O7hHAvpiNJrbu1v44LWGo/eezf/tv2hM91IUUqAo1Ky3ypUEq2gKLCH1snnd0gXptKP+CRC1ytJRknavDG4ViQDqdWV4FEcbHwkQkeXaEzh0QNP0JGEr1mFb8fo1Q2ifWtwSx3Wr2jPVhfrVTQAo8SSeeKmuS1BixCz6ESMLu4Sr6VEB9cr2kQFHOqGh5nd6Td1SKydgRejkZZQqLolQUwElK5CKD2hZNa9iauukQ/inFYbAlQOciEEVBLjl7q4dkLRtkzigrPS5/waq6+lEMtz3Xk5U/By7Pu3gMyDsKqmcDACXOpck2AVntpJSxZ8VOGmjomqojxJ5pbsyk48LpGudlk5mj1q7918Or8QeyBl4lpE28b8p+230ncp/Txlba0FAytZWT1FvA7ReoEeTrDDqKKSKXwkICJZExCTLmvyUhG0xa1bgg2YQqHnAk2bEynHrqRH22RMdkZ8VW/HORnfmmlehV42GBQJ3WhC7gx23jOfjOm3Y4aNJi6ZuY6RQD6n6F/usEsTmnHJJUsrbE8HxLpkWCZc2FhhR9yjeWHOoaxLv0z4ytEd9PcYipYhXZF9mUwRYtEUqXqNK3cEK1k42m0w2KnMAep/oaaJV4t5LpVzCgqUFgMBOwniVlplyMj+PcGCNxoXgQpyXeUcjYj/FRRb68UPSD2uv8jDfvIDPOyd8HWtSwF4xX/dcdx2r/ivO7j7ja+C37/3fXY/vJ3FS7/AI3/8RnrXHuH2Z0ka/e63/wfg0Wfx6DdXDUYe81v7+MwZvPdrDcSctW9UnufccccdZ2t3D0ytrIGKZNJ7rH7FzVbnpxVEKxPq3BOY0ZxqqlOde1LdrEOkae43aOV52SXXYwh8qPcw9q3Mc7jfpne0xY59m62Yaz1J8H4WmOmQCf0kI16ZkC+m+MiABlPlwUB1ky69gIrcoXwgn09k8IqFD+xixXibJRp64r4jOTjA9HJcN2a8LcYnMyE+1uDn24x3twgaXDXIulhVacNOOj2RRk0cpp+JJXWVTxP5wHhXyvrlDeaMIr79qHRJ6nwZmAHIopxR8GBq4SwC/3gGLmvgFIKoLGs9i6v2U+uRanpaHEl3xwjYUXGE27XA6IIW/QssyXo1QI2Ks/rntVX3XufSErnukNxf9sf3Fbxs1YO7lAcfQ6Hl3ugjEYPXC1u6CKgQ0LFGhUgmxAHs2IkOU0OZGsqWkfchOpqiJav5h0cdfGGYe+gKjbjgos4qA5dw92SewwMJmDSLGW45IVlVtA56zLDSbRo1tSCuxeuiBwm093vydYU7pJhsV+RzMkEvJpbDow7bkiHzdkSiSxaSEbvne/Qm6TRj2CpP7mX8ibTc06+YO8KNazvwXpNtc0QDi86ozhFGFxdcfeXdOK/xKC5urdAwOXeMFrHK49BkPmJvssrueJ0D+Ryl19wMjOcShq0Ebw12COlqhBk74jXpApmscsZ0AZ8aWbQzoidyibAE6sU6qm6UHZaYSSkLh4WbupXV+wpKQIoKAibLRFOmamaZbQSUFReLXkZ50DNJwFbdj/XIXa+aPv7sUBbYn/3OW/m61qXTn+t682ns9/Zbd8K1R/i+D3+YX97ggHzZQ57OLXe9/74cMiDuabV+B6TrcyUSVfKZn7jn4Mc/+b1r+OAXHzr9+X+/9S+B8xfEdC994/Txl/Y+S7pyp1CnDGBe8pKX3OPrR458jXw7a9rXRkBS62Bq0ACz1zcm0sOmnJd6XzWFK2jNZDGm6AQ+8Q8PY+VxLZ6561943tLHOZq3ueFfHkb3FoMpfBVmWXUWapvhGixVn1d3J+yRHpOd4rJlx15yTaqQMl3lnYB0glQFwnwkN/CiqXCxOKbkbU2yVtG6nJObeZ1WX1VIYkYP6eBjRbIufO5gRcBoco9rWoJW0pbXwkemGgBcU7og0dDhYsVgb8LcoIs5tCaBlLXmpXYZi+wMvGy4vkqZqVvZps5NUW7OzanpZd7NAKjSFXXNyO+yk5BdME+2EEladCarbLoMhMGWbcxWnVmdbfCyRSd78FW6ElAtoRrpQrowIam0GK5yaay0FrWVcNAyKTYTNzN8UZC35XlSxdo1HtvXXBBnpHfGPOph+9mbrpF5y+54nfetPIK1wx3QgWA9qpSJeTSa3c+81ZQNLfkkkYAZhUy0ywbYLFC0NS4WDWOwgSgt6WcxgzKm8IbFeEjDFFzaWWbYiNmWDPjy+i4e072Tu7N5FqIRt422cWTYYpAn7D88j7EeGg4XWXQBBMjnAtsvWGNno0+sS+4ezdO1Y47kHSYuIjUFmbf0XQrAxEccyObwQROCotMe45oZvahD8w6LtwpdsQymNsxO0FVtpSw5YfXClxgZ1OuTyslClwoB1zAorcTps6KGKSf6lmBqvYxQ4cqGwieQV8ZU2XZHSB0UGj3RhMaWBub+rBoAPO2778Q95b2856e/a9Prf1/eAcns52f++l/xZk79HlsL1f+WZ/LLXMWBF/0L15VdHnLTDLw87IVnduwvueoPjnvuyoedes7iD/3YF6ACLcfWrp/4BF/90hX3i+Pbyap37RE++bGEJ3xjxgV3/CH7LnouF9zxh6e9n1MGML/5m7/Jox/9aLrd7glfHwwGJ3z+QVW+8uOvQYuqRPNVR0Z0FfW2lVOZVqhIuixTDQxIngkQrKmsmaU7cug/al75jL/i1770ZG5bXsTv0nwu28N3Ln2WQ9d0uGXtIuZv8aKB2WgUsCHhXtWZKiAT8bygeUeP0UVd7LAUMWRsMJMSlTl8aiW0sfQVh1puxrbv0UVgZC3JaknqqqTnZkTQisn2mDJVJCsIGEkSyqU2wYKZeKJ+ic5Kim6Ma5hpFyfqu4qSVtGz2nItfCz8ZGJNVLmcjXe3aC/3UaUmlH6WL1ML8+sg0BqwKD0baaytujXVzxsNE0B+dxt/l7UVtVKoOMLPdxhd0qVo6mkImsnF1jNezSk4pgu3VVv1ANb5BmLiNz0KgDBxFK/+wgN8NOdnBcU0OHHqcBVLfkltmmJHTtiwFdVWVxqYgELnniiEqbX9YLdh4cJVVpc7XNxa4WZ9MR/5t4fylEd+iWEZc0XjEJd3jzLYnbCy2sKPLNFAgZYuebazSbxmqkk904wUk4fq8yv75yCLV+lRhV9XZEuBIopZzQ2Hml2M9hyZtMm9IdaOnY0eC9GIhUScH69qikvpHWoJreDuuxdRY4MLkC4bkjURx7tEju3I4S5fVoFdLdGzfaG3h7VJA6M9fRIGRcLe5jorusXhSZv1vEHL5nivyINFa4/pFJRNQ9EUtzGTyYJZTSfTWUlwGm8r4X0QsGIyWeQLqZkuOKIlCNlHGj3NHKgW/hLIOwZfsZKVh7IJrgGjPR7XkHlEND+RSLn1BDtQWzkw93M94RszFi/9Aoeu/2t4+Vv5Fq5l25t+cvr6sYAGju96nGo98sdvBLo8+3VfZOX7XwvA8uefxPLnN2+39KgbTml/tY6m99wjU6D0vn1yv/2O3uc3gZm37PseXnrBicHKsfVb7/5VefDo4wHS/Vk/esV/4/o7nsQ+nstf3PkTcFHGlW+e49a/+Sb++R3xKe/nlAHM5Zdfzk//9E/zAz9wYgvVz33uczz2sY895Q8+L6u2RqYS5NdmV04yTJTVM9rShkDGmSVwELcvqFb8g7h3NVKIhBKw9G+BN132rWS9hHRfzGv734E+EtO+S9E46rnojjH26EBsh8tZXkoIYbrP4MMmp6wwcahDJU0P4ws7mEklRPeBkBh8YrDrmeTbVIOjrFJVtpHjyoe/sinWeUm+1MAOHUEbsXN2HpqW8e4Uk4noUWcC4EzmKVsGb2rPfllBRIm1s2tY4VkXImb1RqwvdYms8i100HcNK1tqM9O0xNHM+a2+BpX4XhkzBZBTDYsvqiDKylihNlzwQUBOzXEOsu/xhR18pGgcKTCZq1blqqDLYQH5+Fz+tW3VCerdT+qfFo3sTNzH7i/Xsa+1qgHLVp1aeQPKgB2LYUsNIlBy/1W+ohXX2SRaJsh1Z0AFqk6AJLlP5g0oWGyOWVtrcedogfiRa1w6t85iPKRfJvzT+qX0S1lWViYQrVrMRBH1A8laOevGV2YANcASsXqgaMl9ukwVZiJ2xRIyqXCJITQckXG0o4zSa/YPukwKy7CM8UEzKBIO5HMs2AiPomFyJoUFpwiRh9jjBlpCKDNF3gU7UtjbEw6NF0kvL2lGOXesLqBUoJNm+KAYZAlNm7OaNclKy3w6pqw6MEWh8S5mcX7AapKSzWvMYTe1MFZGoTIHLqBUkGyejU6XQbphyge5LlXXa8o8mDqUVVS7GvRl0t0ZbddMtgfKpsd13cxWuQp+0c0S1zDEp2DNu1Vnt4bv+zSdf/rvJFfImJLdNBsvvpN3btr22St33mfHrpsefgN8/kksPeqGTWBl+fNPOqP9nchS+dhOzKmCl7p+4vtfAdwEHz6jQzprte+i5wICNOu6/daddN2pd4ZOGcA87nGP49Of/vRJAUwd4vhgruA8WJkQK6Uq9ys/y3SJrNCVtBJa0tQBa8M+8qJKoS9lEj0NsnSgItp3TkjekUKAqC+rVWbSF+ew0qHqFHo/6ySEspxN7B3yuJ6811ob59DLazSMYnhxR7ogyM0Yz7QLgwrYcYnONfmcnQoR8zlLNHDYgRcAUAZc08gAMMrEEWeugRl74vUcM8wlENMotA/o3BIPZHXRNSS3wA5LfGLRzot3f1YSjBa3s0RRNOXDJ7uatA5Gcr1BAKL2M+e12iTBaNEBGSMdoaKcPlZUv6+qAyaA5phfsHNgLSqKKHfOkXfMVFjrYzlnnXuxlM4KymTLNuZ8rfsaWrkFYk6ttkDLmZcuAVc5fClxH6sBTJ0L4hItejvFTFBeAQpvBNCgYLDbsPooR7RiWL17O6xF/NvwQqK5jO72CYezDgeHXXY0+6xmTRJb4ktNNFbEfWisSB6KSwzBRORdM7XYDxpMIZ+tC4WPxE3LR0Ily+Ylo4xKJ3No0MF2POMyonQa5zT717rsW5lne3fAp5Yv5CHtVQ6POxwZthj2U1ShCSawd/cqB49KCHbZEqe2ogWuGTAjzdFBi8WW4qKF1el1PNDvkEYlWgUSU9KwBbEuuWVlG3lu0SqgtSe1JS71DC/QBG3QTuz79cAJrZrKUKfS/ygfpiYJdfdLroGfGt14q/BGnMqC1hWtD1BVdk4IuAZkOxx7Lj7KgYMLKOPx/YjIOpKopJHkrK7G5IsP7vnRg6Gutz0GnR+k3X8nH/zcD/JuoHjMX5FUYCW5osOg84NMflz8fDd2ZFbK03ekPJaG9anvfiGPe+9vbwIsxwKZU+3CAFx/2Z9vylPZWKfTealLwIvUA6GH+d7nPw2AP7rpf53w9U9+LGHfN9569jUwb3nLW8iy7KSvP+pRj8Ifm4XyICtl9GzyDKK1gE32xeJCpmZUpiqBXjo2VY6J1rJ9tdIfIku+p8vy1Sm9KzytuzS7PjkUgbv30mkBVOlmGpCKJhVqC+e6O+GqfBNT60XMlGoWxmPU3QXt0jO6uEvQET7SJMsTfGxQplqNyj02OFwiA5OZeMy4pGxaARxZiS48PrY0943EWrqZUrYiooHQxoLWhEjjmpGsXgXR00wWNcprGstii6zLILaWAXzDonIv4kiYGghMlgzNhS4cWZ0BsyKAobqOM2Cj0kS0Ll6us7jACdVP1XSzattp1U5xqto+jsgWE3QZiIYe7UQ3lG2LiPolRdcSp4ay2BCkuVX3S91T9+W+gpZj62yCmI0WyudSvH++0ci26uTlLWAlNFKMTqjuiZXmRctrZVMs683EV3bE4FKFi6vFGA3KweLeNdYHi7AWEZoOPbCoI03+aXAZKnHQi9g/2A0e4nXFfC/Qvb1AF57k6Bi9PsTPtXCtmGQVio4lLkLVMfdiMpBUk/hSclqCVqTLnsmSxg4VhY04WnbJSkMzLsgKS5FbimFEOpdxcXeZlayFD5pD/Q4uKNRyLN0L61kZNGkcrqyTNUSDgBkrio4iW4DJOGZVBa6aP8zdoznWs5Rev4mZG3L3YI7L5o7StRmfOvIQitKQJAWdhsxL2nFGiAOlFkZA0VB4o9F5BUCMnnW7KjZC/ZiAZMB5QCPjXyQBmRspzSoE+d0p5HrFSBhoruhPEuhbfOrBBsZjocI04oJ095DhxjDsrTondV3ZJYn+hL+4qc+3/sgf8JE/lowkrpht0+6/k+cdvpPxW3YzfuPp08XuqXrXHoG3bX7uW158Zvv6i+e+nS6SBfO+7qP4jt7neV93tqB0uuBlY71l3/fwHb3Pc3bP/tTqQ26zVcLzhk/j/Ue/B14mP//k6LtPeV/63jeR2rVrFxdddNEp7/hU6qMf/Sjf8R3fwZ49e1BK8dd//debXg8h8PM///Ps3r2bRqPBU57yFG66aXP7bGVlhec85zl0u13m5+f50R/90TPX4/hjVkhC1QE4VocBU2G4snbaeQpug4Wy0aJ9sYZs7xxHHp0y2huILxiSz4k7WEiMiNxrp7IQCA1JtacsJevF2spJS8vxRZX71sYOTE1pq0HT0VWaN60ItzeAT6ruSxCLTuX8VCwaDUqiXj4NShN3MuFIx+sl9khPnMdaqdDOslL2EQKqEBG/izQmc8QDL9zuavAbb9uAj70AGT0pp6tcUd9hx7JtsdicnacW3dDMEKE6vxqIVM+r2v3N2k3WyyCgM1SuZeIMV4HSKqdHBp/KZKEMRCuTyjrTEK+VuFSTLZwftpfn3ffkHNW9UcfOhUPZI5+xd/pvqx7cdb59T3QJdiL6lWjssZmvbHhn40y9iBPqDgdMc2B0IdTerCsC/9XlDq7tCU2HGhmUAzNRJPsj7P6EYAPFtoKyFWgcDiTrFWU30rhWTGiKCD5YhUuNhGE21KY0e/lM6RDZLEggY6QoWgLIVKGIDkUMb5/j0L4FxgfbcEcTNTZEUcnRSRutAmXQbGsP5RwbXgI5E09xa4e4F9C5UKqLrhKHs07AXjRAG0dsS5azJutZSjMqeNRD9pEVYgf9lZWdfPTuS1lZbzFebVDklvVhg8XGiJ2NPhi5tkUriFGCr1zIgnTBVClOmXZYojOHzh26WlSzwxJdZceEil49+0XJY1c5d9osYEeeMlG4JGC3T3BOY7dN2Ll3lfb2Ia1mxmN27eMRSwfYPd/j4ovOHw7Z+fZdORtVdyr+5j3/i+YdP8Q//8Kz+eYfifnmH4l5wjdmPOEbM7770Gv57kOvJfvVd6DdG+9lj2deP/Yth/nkxxKeN3za9LljaWU/fskXpv9OVHV3p/5/I3g503rLvu/hLfu+56zt70zqyeZl08c1eHn6tr/k6dv+ku+98Lf44PJ3nvK+HtAZ2nA45FGPehQ/8iM/wnd/9/Go61d/9Vd561vfyp/8yZ9wySWX8OpXv5rrrruOL33pS6Sp3Iyf85zncODAAT74wQ9SFAX//b//d57//Ofz7ne/+/QPaKP+op4kGz3rctROVkFNuyAbc0qU0TPdhtb4Zko5n9K7KGayLdC5FbL1DmYC450Jq1c26dzlWfhCTzJojJZclMoQQIwDNiTP15qOTZ0YM5vo125l2sB6n3g0wS51ybc1cV2LHbppexzAjkuCVhSduEplFvcy34iIRiXxHatQOkIaCwUtUGW6VC5lG6yagwc7dCRrki1jx5JxYPtiZawnJapwhEg0OWXDVsfgiSOFTwwqikTfo5Vc442Asb7OdXZLLbA/Vqhf/a+snl0rAG3k96O1nI8VfnQ+J+cVOpKLELQMXmWqyZqnjO/PaZ1335OzXOfSOnmr/v3U+fY9qRPZTS6TX1WtNZW1DqZKh69t6E0uk2ZTeFRPXs8WLJMlcbcKhaa7q0/pNOGOOYp2YLLLoSdaJuu5gjSQrEieV7LqiPqF6FuGOXhPiGKyhQhvhcIbNNNFJ+WqSb8TvYwdS2co7xqigaTcR0M5j8mSJliNLph2I4aDlJtGCbuX1mm2c7anA44OWqACfr7EHopp3ykUNZeIfTKA7waKeUcCtBo5uzt9HjV3N71Wyt5kjZ3ROvvmF5n4iA8fupJmVEBzjF9UDLKYwSjhlsPbiHc5bKugVJaypRjt0DQPe/SkAK2FPqckZkA+2EuIcmSEal1lo8ningCsoNjkKApCCdT5zEEuGNDGk8YFD995EK0CX13ezq6OuKpFymOV5+r5/Xz8tP+Kzk2db9+Vs1Hbv/i3AHzgvRcC8Du/sMgLHvHKTdu84Bfl/69rXcpz3vgqznZ1P7ydx733t/nUd7+QPwX4Z+i97QN0P7yd6255Fn/x3LeLrgX43dtOrre5/jLpvNSmAvel2wLw1S9JC+rKh8l+ahDzru/cw3P+z/77tO9Trettj+/9u98C4ALEcezp2+S19x/9nul22WD3Ke/zAQUwT3/603n6059+wtdCCPzGb/wGr3rVq/jO7xRE9s53vpOdO3fy13/913zf930fX/7yl/nABz7Av/zLv/C4xwmn8W1vexvf9m3fxpvf/Gb27NlzegcUqhZ+ZGcT443gwGjInageawpXZcurKtexOnQSwHUSVq9qsPKNOY+7/HY+NX85eiHjP150B/9068Xs2r5ObByTN2+ncVsmQZReKGTK6VkHIYRKa+MrcFS7bPlZ5kxNj/JBukNBwJW6e0K6nOJ2LeBSi0stZcuK1iMEEY1GirxjZLVvwdK+a4y9e4WQi7WxsgbXtBJ0mRg0oEaOYi6VjIJEHG1qKpmPFPHhHD0WhzIzcei8lO5Ow4ILjLZb1q+A7Z8VBxidS9eJIt/8O5naVVc/u4owvrFbVruQbQR7NXjRlV4IRwiVGcNoQjRwlC0zs8TUanoeLtGVluf8aPmfd9+Tr9E6WRfmnmhmx75nK/vlgavz7XviIygTSYcPSnQmdXZIQCi39c+60qAIjctMxfUA2TaPt6DTkv6+LsEGuDSDvJph54EyCbTuMhRtgx1JZyVbMNNuj+2DT2Mm29Lp/S4osUwOunbtki69ycM04LLuxkTDQDSQyXvRlFDMsg12CC6F5n5Nsd7AR4G71mP2z82RJAV55QQW749oHBKDgGxBUbYCBFlE8haUV7jb24wvHpA5y6G8S8tkfGL1Up6+7QvsjNbpuwaPXboTXV2YQ1mHXt7gTubp3bTArcmiiPRzjS4q++mWItvWmP5O7LBaSFMb7u0+oKo0ZlVrXDYI96fbBKa2zGVDgi1RYpGdj2KSuOQhjVWO5G2uXDrCYjzCKsdK3iJzFh2dPxqY8+27crbqetvjaOutPOeNr+JdrddDax7YrHX54At/is8Ob6Wxtsx4fumsH8Onvnuzd/InPyamGtdf9ud0+XMaS8t80/KJ/ZXf/pbPcMVvb+50bcx/OdM6mQXzd/Q+T+/a47U856KuK7t871OexnP/+D1874UCZDYCl7qS9gHyo6e2z/NjifkEddttt3Hw4EGe8pSnTJ+bm5vj8Y9/PJ/85CcB+OQnP8n8/Pz0CwTwlKc8Ba01//RP/3TGnx3yoqJrbaZATWlbWs2ARPAzRzI1AzvBaEZ7UlYe7XnoRQdITcEVD72ba/Ye4OLmMmE9ZvVju7j9lp1yY8zyqoPip25jaANJZVRedxg20qoqzU2dPD+d1DsnmplCuhYhy9G33E18y0GiQz2S5Qk6F5cWvFAGGkcKOjcPmP/0IexdR2cdD5CVOyMT/KLKeSm7KWXTMF6UkDUfKXQWyNuKstou254KLSEXK2ffjCm6MUU3QvlANFCUqQziupCASqJY/kFlgBBmmpeNIK3uPOnZQBScq4wOatqYm+qUpr+XLAcfSJYnEmQWz1xoxFWGaVAc5894c9J6IL8nZ6MeDN2XE9HMtmhnD656IL4nom9R5C017fjqUu4zAOmKo3mkJF1xleDckSznYmG/aHGxJm8rfBqI+oq0mWOGmquv2sfXXXYnC7t7kDj03hGdC3sMHppjJpXrWSEUNpN5dBko5lNcbWdfi9gDlV3yrFtkx7OME51LF93kXvKxsoDJIRoG0lVP6255Pu4F7ChIrosGlWvcMGJ0tIk7ktK6NaJ7K0Idq9z/lVfk857J7hLX8QQTCLoCJv02a3mDWwbbuPHoDvo+5d+GF7AvX2AhGjF0CZFyHB53GJcR1njcXMnli0cJQaGaDp3LOQULLq20L7bqpHiPKpzoTzXSeTGVQL+eESmmLmYgII8KvAQNZaqYzBnwkCwr9JGY2Dq6dsKjO/u4tHmUSxpHaJuMRJc8bOHgFHid7/VgHVNe/H038IyjBZ8d3srLfvJH+Ozw1um/D77wp6b/6jr0XZ7G2vI5P65jbZn/y1Ofetw2i+/+eYDjwMulz38sh64+d0L7Kx9202nly9zX+qOb/tcm17H7WucHyf8EdfCg+Mjv3Llz0/M7d+6cvnbw4EF27Nix6XVrLYuLi9NtTlRZlm0yJOj1erMXfZiK+UNeyOOi3DRRBmb6kyiWjoet0uqrdnO5o8v+J8FFDz3I6qTBzQe302mP0QruWFtg/gua7h0F6tMQL48JcSQOZBta1cpoiCKZR5cluA3HUYMoNgjdN0zWQwjSFarF/1pJR2U5x/QG6BCIo2hKOwvOo9KEMB4LUPDi2BVCQLkqDLNegdIV5csH4qHHjgTgKB9I10S8Lw4vEmipfMAnlhBJeJrJPcm6J1115B3x7VfZBipYbVxQa4sqg4QpiDNspoxVnTJlzOz1uitV217LHweq0hvptSGNIxHj7TGuoYl6YjRghzBZsmAVZnL+DzgP2Pfk32n9ewMt+cs//zXhRPZAfE90ASoPle5FHLEIkvgeKq2kHTlJcq+6vaI/lP0EK3StoANFJ7C7M+TI5fDUHV/irskiExdhdGBSWMbjGNMoKeYiTK5IVgV8qBDAC81XROphmvUiQErAjC6ZLlJJALKq2kQevMIUlYaksiWuwziTdU8dtimdH5hs09ixxg4DdgyomSNk3Vkq00BoVwtsEejYEdrw0J2HOTpu0TAFK1mTR+w4wNGiw5G8jVGBo7RZzlocVB3297ok1uG84qILj/K4+TtZmbToZzGrgwWah8RFs+6oRL1C8l4isymcWTnpwPhInCjr1pcOGo8HqyWYOYittNgpz3RLdhxoHlSs2EW+vLCLhimYi8a4QjN20oHaHvcJxYPDlv9cfVfO1XjSu/bItIPwX576VF7W/vnpa2++5v/wsi9s1lS8+Zr/w9e1LpX3zJ+VQzit+vN//jRc9uljMmf+HF594u13fvkTcBZBRk0fq2lp97cT2c9c/zc0f/pJjN5/6m5sJ6vzFsCcy3rjG9/IL/7iL574xelqvd/0XHB+5lJWdzqMEcqTMRIsWYVM0mww2p1wycMO8OiFfXzg9qvhjibDvAlB0TwYaB322InDrmXorBD6WOmE9pUmUFk0qlqwX1kAT4MaN1oMBz/NqqmPXRk97aKEskTF0SxPBUAbQiMRh7GqgxNGowpA1bbPSvZpNGbiiAayiuWatrrRQ9R3ssLXNoy3WxpHHT6qQJQCQgVetLi/+EiyVqKR0PWUl1U9XVlKT0FL7fxGBeSmlDE3NU1Qqu6Sudnvrg4erbtnyk73SVnOmAHOY1fHJFZTNgw+0UTrBSpAugJ511Kkp/Vn9TVX9/g92aoHpLYcyM6/uqfvifIQjYMYogwLymZEGYtmRRdyD7Rjh0sFtdhRgfIWXQTssGQy12B+T49xFlF6zWXblvnHtUuZlBGDPMF5xbCfEoYWnWminkKV0NmXEZQSo5VSHLhEr6GqzxEwU/jK2hnpRnsDNpstVFGZvdQWwz4SipUphPYm2hk/zQbzkaJ1yKBCQBeyj7yjKVpKQIOSfByfBqJmQac9JisilAq0kpyHdQ9wuxVaz+Wdo1jtiJSj9IYS2D+cY3nYpJ1mjEYJUWfEnm6PYRHzj6uXMJ+MuWr+EB+8Y6FydgMz9lOKnqpcQsHjk8pZdKq7lHOZUbQD2NkinM4cvnKG01HAIm5xtQ4m6ituX1/k8vmjJLqk9JphmbBepOxMDCPX4N9znavxpAYvd29/Kb/ZvnnTa8eCF4A3v/X8uIeeamDmP//Cs+EvXnvC12owAid3JftY+CG+Uf3Jcds/ENX98HZeyDv47l//Kvz68VqX//3QA6e1v9MGMM453vGOd/ChD32Iw4cPH2ed/Pd///enu8sT1q5duwA4dOgQu3fPTvTQoUM8+tGPnm5z+PBmZ4+yLFlZWZm+/0T1P//n/+QlL3nJ9Oder8dDHvIQaRHjp65jdWcj1F0MmK341/oKbWbdAB8gtpDlxGslq6MGR1ptwmfm2PEVh8kqj3mt8HE1uAzGctPMC2lt1zfUJIZJRphksxtqXhzfCaoE/croqehfxbE8rjsXLkzpZHJiAZRHDUayf6NnBgUbhPDTzkXpMOsT8vmODEI+4GNNmWrhAY89ykHn9gkqwGhXgqnCMX1ipnziom0oE0XjqMNOHNl8hPLQOlCghmMBVr4GJ2rzcejZ35nyVHbVarNWyYeKRqaFuqwqheyUdqanQn68R/fH2DSibDRwsSYsxMSrOdHaBF3GFHPnvy34A/I9eYDqbNsob9Wp1ddCF+aB+J5oh1CZqhwYHxmxrg/VpNqJAyIwXczRgxyVObKdTYqOrN5nheXyHUe5e32OlUGTbZ0h8+mYSWlZX29CPyI9bEhWZCJt8oDp5eiswLWFghxMZTqzcfwIgFJoJ3Q3XQR0EN2LtzIxV05AiKTVgyEQrBz/lBHlq3t9LFStjS5rtQW0zkU/4yIlFLdcYaznorlVjo7brI9TRnnEzcPttGxOwxQsxQNuOHQFV80fogyaWDvaccYwjymdjMfzjQk+KNZGDY4OWrTTjP2DLs27DOmqHLNoLJ2YJaQWXfiKYhYkugCmXSQBeqpy6pSxw6sqt0epadilHXnKpkaVQjuzA6GcHTowz8VzK6S64EjZmYaK3jzczny5eu9/qOdBnavvyrkeT1574Bm8+PLLTvjaH930v9j5V5pD3zUb0zd2bs7XuvX3P81zG8/b9NyxHZSNz58IxHyj+pOTApf7u/sC8NvxD/PC/B2nDVZOVKcNYP7H//gfvOMd7+Dbv/3bueaaa6Yhg2e7LrnkEnbt2sWHPvSh6Zem1+vxT//0T7zgBS8A4AlPeAJra2t8+tOf5rGPfSwgAMp7z+Mf//iT7jtJEpJaW7KhJHOleuw8SsmEuO4EyHMbdBdlKZP/6Q78VEger04oPr7Ex67qsG1/IBo4ol6BTw3jbREohRlXhOC8mO3CeXDZrAMUvHQRNkzSp570Sk1tnkMFUJQxhDwXOlVlCABMu0gAykmnh7LcJIZXaUoYjWfanrIkYKEo0MMI6DBZMphMUzSrLoqTwXG8ZDC5rVarwKWyCgciis/blZA1DwLeBnKtVYDk0GB2PZ2T7JyynCUn178b71GRhciKC1qV/zK9bhWY3pQHs/GaTfVCofo1O3RW4hJV0d4gX4hpZA5VBuzk/AcwD8T35IGoBwt4+bO//uMtIf95WA/I9yRQ0bMC+ZwVrV8ZiPtOsrHczCTGjB0qr+43WjoZRVO6JuN+whfX9tK4LcY1Ak/49i+wVjT4ty9eSOOAJeoJXS3uB6KRp3E0x6wNQCncjjY+FgqUNwqXznQdRVtTNGbanFq0H0xFOavm9mbiAMlSmVoLVxoRXVGLodKMlEHWmqq1IwCb+SllTivRwuRdRT6xrExatOOMhi3Y3+tyy+oSF82t0lcJWnkKr7lruMAgT9jWGBDrktJp0rhgcW5Ib5Kys91nsTXiwFqX3iglv7nL0t2exuECH4lbWrACvHysZ5ECmZdxREt8QIgtoeqwUGW2eKPYKF0JauO1El0QUMUVKOzRiLv681zeOoJVjrloQhk0y1mLYUUnO9/rXH1XzuV40lhbhp/9ev72jeLs9ZJnv4Zf+9PXTF/vLgldbGPP43wHL8fWsSBkI2A53VDL++pqdl/rvT99JT/wleOfP+cdmD/7sz/jPe95D9/2bd92um89rgaDATffPGv53XbbbXzuc59jcXGRCy+8kJ/6qZ/i9a9/PVdcccXUym/Pnj084xnPAODqq6/maU97Gs973vP43d/9XYqi4EUvehHf933fd59cMOqJfqhuboDQwza6XG2cJFc1pXABZmXArn+K2W8brD7c0784Jj0aY8eBwUMU3dtCZS1cTmlhwW/ogtT6DVNlxGzUvoBQpHyYTuQ3ptNPj1nrKdCZ/l/tQ7EBeNa6mWJDWCZApOQYrIWiJF4rGOy2lNUgGA1E4DlZijB5oGgZoqHwulGK8TZTucwoyhSikdzwvVUM9yQEA+27M9Ran1C6mXNYrd+pfw91Fk9NJfMVNS6Us3PyXq4BzDpHzgm7LLKVixsVMDSyTy3dqWS1ZLItomwIL7xsRdUAXlufPbB1vn5Ptur+rS362D3X+fY9CboOO5ROtS6lm6GL6r5mxLbXTEri1WIqLA8Y8raunMQUqhcRIs9kl8P2Nf/vlx/N4twQnWnSoyKiT1ccwSrSQ2PM2giKkpDGqCD0XjCYzGMmgdBAtC7Ioo2t3MdUkG5J7bQFsw5MrZ9RpZeuenX8qvCoUroSuqgADUzpwqZKHaDBNO8maAFcvh+x3G7SXsi4cv4grSjjwFCmmHPRhIOTLu0op5eltKKcLx/axWP33oU1nku6K+wbzJM7Q+EMB9a6KBUYrTdo9CRgsuhYon6JqbLK5LgQcKVUpaXUVZilriIChOpscj/tJHmrADMFZHXAqC5nuqCgAA8mg9445VDWpWFyLkhXuXO8iA+Klbx12n9D56rOt+/K2ah33vxZXvLs2c8vefZrAHho40q+o8qIebCBluvKLjeNrwB+iH8+5rX0o/+Rt3zTibsxcGK62EbAc3/ZJ5+sfvm6b+dnrv+b40DLsz61iz/cdmr7OG0AE8cxl19++em+7YT1qU99imuvvXb6c91e/KEf+iHe8Y538IpXvILhcMjzn/981tbW+IZv+AY+8IEPTH3IAd71rnfxohe9iCc/+clorfmv//W/8ta3vvWsHF9NxQJm2gqYrubLRrUjWXWjr7si3hPftcruTygOPyalf0VJ0dWYsaKcc7Q+6VHDceWwVfvSy0BCcJttgmuRfT1ZN2YmeK+Ph4rKprVsF0nwF0UpXaSNeTE1BW6jzqfuUpwAmNUBkvbQOt2WJe+YKt/ACy/YCBUs6s9MBqQTYyqBKqQrIvT3VmHHnsm8prHiifavi1lCEkvXZUr3UlNqm1Jqc7dlqoHZCMjM9DU1tVCuOlc+1Lyz2bkDJDGqkPAykxnKVCyls8WIMlW4/PwAMOf79+S+1Luf1L9XJ7IHS/fla7keDDSy8+17YvKA1iKa1xnE6wVmQx5WMIrgAnqUozIZB0IzAaWIxp6iKYJ+XQKFxkdQzDvUcsIoLVA7J6xFCUuf0diJE6rXIJuOJ6GVUrQsQUO8Jos+PtGYvBLsV3QvsXoWYGEnYqNcWoWuqMLKVeCmnNGoQHK/lAvStfDieFaX9n5Knys7ssClndhKe8DHoDPNYKXJ/M79XNE4xJwdc2DYpQyGls24tb/EMI9pxTmZs2zvDtg3mOeqxcNsSwYsTwQQrE4aGOO5YukIn9t/KdFAcmbytiYaCijRFRDzWmyqVRlQxSzyQAUBKkEptBPzg6B1xRIIM22mnm1PGTCFaHqm1L2JoiwNi/GQVBdsi/r8W28PqSm4bdg+o7+jc1Hn23flvtZ4fonJ79zM//rC8WGh/+2aj/I51gF4+TNv5k0vODvz1/ujrrc9bv396odvf+im1ybfNIM0J+vGnKzTIs/f//SxjfUz1/8NAD/wlc1amLx36mYXKtSzwVOst7zlLdx66628/e1vP2f0sfu7er0ec3NzPHn+v2FtY6YX2Ug/qjsTGyfA9Tb1BLsGMCFIN0YpsIaQxBTb25Qty/qlMtnf+dGjqNGk0rVU+pWynNkzb9TWlOUUbGwCMrW5gFICUtJEAMsGF7NQZ8XUBgNVl0bF8fHi//p8jj1PoysxvyHMtZns6RCsxg7ENW28M5a06fWCsmVxqehjxksaH0N7v5+uVrlYTcPSul9YRvUG0nmqgWKtwakf+/pY9OafN16PujNT/74iu8nNbbrvaYdGTc+HJMZ3GmQ7W2RzhrjnyOespF+PJnzuXT/H+vo63e6pCe6+lqv+npyrOhmQeTACmLNNIzsfui8nAzBh4ihe/YWt70lV9ffksf/19ZgkxWYSfBiv5ZiJhAeHyEwDFvUon+aS+GZEvpAwWbIMd0nQZLYUKLse09e4jojlt12ywjiPcE7jv9Rh2796Gkdy7PJ42tV3iy2yxaTK/IKyaSSoONL4WCzsa+AigY2VpbILU1dJW+kbayE7laBfOw8uYCYlPhK6cB0GKScSKhCgKDqRWBlr6cqUiWKyTZHPQdEKmAuHXLXrMEvJkJvWtvPwxQMYFbhxfQcrwyZJVLKy3uLSnUdpRxnNSiPzhZXdLPdaeK/YtdDnrv2LdP4tIV4XV7WkLw6ZPlJMHTSNwowdZuIElBXyf1CIqF8jXSUv+s2iaUWbVAZ06fFWVx0Z6cCUTUOZKrKuBg2TJcVor+Oihx7kO/d8npFL+NTahcTG8a+3L3Dj9//K1vekqrM9nuz6iU/w1S9dwZUPu2lDcKM8ft0z13n1e+YedB2Yunb9xCdO+tqpCPnr2hv/CXfnP/SAaF+OrRfm7zjh83+4Z0J+9MdP6Xty2h2Yj3/843z4wx/m/e9/Pw9/+MOJos28zve+972nu8vzp4xFtVv4lbXp5H8qqp/SlsKMWlR1PlQUCQUqL6YrNCL816goQjlPfFdG7DyN21KZQI8mUIj2JWTZzF1sowta1dnBaEJWgSq3wd7YI+5ideaJc5vAy7SLU3nfh4oyJceXz7o19ftqjYkPsv/6uoRAmEwEBAFxEjG4tI2PYsxYxJFBKYpuRNHSZHMalyrsKMC4GhyswkXin99Y9XS+vAJrPenK1zqjjcDQe7mmFQicXpONltZejnmav1ODmJrqVwOdGozVPxsz+90WJSoviXo53iS4hq4GLFVfqq26n2ojUKnBzIMRvMDZ1cKcD+AFHhxdmPOqjCzYRGM/BQASJmzwkSZxHj2S/K8QW3ReYgYZUWSYLMrQbEcV1Uxp7EhcIO1I0T+8nfKhI7TxRCNFVOtqqvv/5MJ58jmLnYhZgDeKYAScGOcIxojNs5d7tylFYO8tGF8J310FSkwglIAS8xmUwjOzudelR2VOmLuVQYrKqi5Tw8rkfyB20XnXoEuI18UhzHYUbr3NXWlOc1tOIyro2gl3j+dJTIkPilEesWuxRzvK2NNYZ61oMCwTnNdkwxg1sBy8rcXi7dIlMoWAlaKpGO60FB1F1JcMGjsJpE4sk0WnE2HHDjOU7tiUzr3R8ECpqVNbMBW9rPBgFMpplK+MEABVQnLEcHu6g4+nl3Nl+zCXtY9yReMQO9wiN96vf4D/vurgbz0Rrj3CV790Bdc++lX8Wfb3fPVLn+DHvuUwnGIw4vlc1+4SsPefP/Wtm4DKqepZBNydH+AFRMzfvfSNxz2ftCenHGR52gBmfn6e7/qu7zrdtz04qijwR1fk8cZJP/VTamalDLMuQK1dqfNY6m5NrV8pS0JRCJjpDaavhyqDZUpt0sxAh672X4RpZwdjpiBHUXVf6m5RtY+6AzQDXxtpYkIxmwIXmB6DspYA0p0xRn6ubZpNVHWYDGEywRxepdmwjPakFM1I3GWq1Tyx3AQzDsR9XzncCCdZFzB/S0Z89xqqP6x4yEYAWSMhtBu4ZiQZM2VAZyWq8JjVPmFYtRVre+SK0qcqmthUr+TC1JENYwiVMFbVXZ2626RFc6S8R40mGB9IfCBfTMm3aaHEjc5/Ef/Xaj1YgcvGOhsg5kTg5WQrV78d//B9+qxTqS0Qc+rlIiG2hiobzMcGVUo3GnzVsdD4liwCBiedd+X8NDumbAs9yccB76BxWIujVw75vzVJVwJmEiphuUZ7D4eXaWQ50a55ylZE2TQoJ9oNtyiUMJcoXKSmgnSTA4Fpd8FkAl58Il0ZXShCLQIJYZNGZNpt8WqqL1EhQOFQkbiu1SGSJpfuCFSamSKQLSj6N8/zVRWIrePjhy6ldIal5pAstyx1h1y9cBCjAv0y5aurO+iNUnbP92R9a6BJj0rHvegqJjEUXdHz+Ahc6jHzCjtU2ImAEZMJLU6XiA2yUpjMoXM30//4MO2+CI0uyO9IIRTnysBAu8oyWinsRD4Tpzg47OIrMwCtAj6cH5Tkr+V6+GNexBc/83Y+/eu/h/RgttP4q2XG80v86QN8bPelDv7WE+F1X+S9b/sUH/9v30jEb/Lr/+NbeNGvPOJe3/s7b3seL3jxH8z2c4J6Yf4Ofvqn3nBckOa5rn0XPZcL7vhDmk9/0vS5v81+gMf84am9/7QBzP/z//w/p/uWB00F52Sy7r08rqrWlACzVf6NonDnpFsSi1hyCl6oAUKtyZBwTJyXzskG97Hqg2bdBti0n2l4Y+0mVnVLps5iG2lglaA91Nzdij62qTsDM8F/TXuL7KbPnnahXOVmVuSgNKEsiW47RHd9jv6V8+QdjR3Lcbh4NhhmXU00koGiebgk2T9Arw+k86QUWItf7FDOp7jEUDZ1NZB4ipambKQULWgeadM4mBEtD6VzVTpxS6uvv1YoE8+oZ3VeznSA9TPgUp9L3Y2pOdBZjlmHJEDQqeTVbAGYrbqPdaYg5nSAy4leP5dgZgvEnFqZIqAslYW8xiUKO3REgwKVGILVlO2YsmUrjUksjmG5Jxo6dGEoG9Il8aknTyFes6CgbEHcg2gopij5nCVS4JMOeqFJMJpsKUKVAoB0Zf+rqgk3eUUX84HCqCp1vqJKFWHqTKac/JuOezDNVKkpZGJBrAiJEXpZVkLpILFQ0c1CEO2Jmcg9N2hduaEp4l6g6CgGX1pEOSj25nTmR9x8cDtR5Ii0ZzVvUnrNVw7vJARFWRjuOjpPtC+muX+WUeMjGF2dsWfXKodWhH7SSAuGR5v4iwvGvZhBqVCFIjmqsROIBmLtbCeBuOfQuceOCvCV1iVUFLrCiaPZlDauNhgfQLBQNsE1AirTjAvLjUd2oHVgNWvSW9tq6Z+reuxP/xif/vXf44ufeTvXPvpV8OHZa+P5pQfuwM5i/emrH86un/gEfz/+jDzxy5+BKt/lnqoGLxvpcy/M38G3HMz4+10zV7hf/42f44W/MXtfLbK/PxbGNtaOG/8OuPSUtj3jIMsjR45w443SEL3qqqvYvv3ByS3cVHX725jpiv7M5WqDE5i18ry10llJkypHRboZoQIdSmtZ5a+85WGDxW/1fCg3TLpr+hMwTaOHmYFA1WlQxhyXmbLJMU3rKVg5USdp2rGo972JuhWmdDLCjGI2S7yv7JV9QPWGdL5Q4LsNyk5S8YvFatNMHLr0mNWRdInGE0IFDFWagtGUuxcYXtCQlUAnItBoJFSIeC1QdCLKlri/THYk5Asx0aDE9jLMSiT7LEtClkOV3xOcR/kqL0fpmXvZMXompTXoaNaVKkoUoHuQhkC2lDLpbLguW7VVZ1g1GLk3IHNPVLF7Ay8n2/5cDT5bIObeK0AlHmeTpXKoc8Z8lU9iZHLvYwE5Ogd8IBpIkn3RUkTr4ugYr0v3JB7KfrOuJlgAjTeWxtGCohtXC0AKO65pXgGbebxVlVgdXAzxIFTdniBdFy0aF5NLh6hsaOma5H7amQgBythiJjKhF92hFi1M6cFDiGxlT1y5fCmFHZYShBzLPk0mVF1TCF2raAsAKVcjwjz4QhM1M+aTMaXX9IuU8XoKpSJatuhC0Twgx180Fdki5FV2l9WetJGz0BxTeE2yu8DowKSZ4b1Ga894Z8K4H5EeiIjXhNYWtBFAMyqk05QJN0wVs7yYOk/HR5qyoSlTRdGUzk7ZBIIi6sHqrYuEyKPaJdkkIt93//3t/XurT//67wFw7aNfNX28sU6U+dJ7EDqTHfytJ3IFcNMLr+CRv/SPzP3cyUmJHws/xPcl3wLMrs9jf/rHePyvPAFgE3g5UdUi+3PZnbn20a9iH6/ngvdvaLnsfdYpv/+0AcxwOOTFL34x73znO6chlsYYfvAHf5C3ve1tNJvN093l+VPeo6yZuVptmvRqmfhGEX6xw3hPR7zgS6F+RYMSnTkJIisqe2TvZaIMlRWlk05O3R0oS1SjMbNLdjNXFEAm5rXDGID20mmAmWVwuSH/pd7PxqoNBaY/VqBnY/emFvtXpZSSjLMNdLmQZdI1qksrwmAIoxG6NyCpVqSm51FrejZ6RDiHqjRT+UOWKDrRdLUvPZyJMcBQAj2D0TLgaeEju0QGiDBnZbVxLiVaFTrb9DN8QFk965B5B372s4o0RJFoihoJwZip4FXlxRSA6vURSQgU4QSObFu1VWdYZ6plOV3wcqL3nimQORak5C///KbHWyDm5OUShbIKX9YOVV4CgJtyj9a5R8eaMjWULY03iqKlGC8aVEAmxalQksxE4dJAPi+C9HxO4eNaVB/IO4poYBjtMJQtKtE62FGo8lyk42EysU0ukwosJFocuIxCmzDVfbhYDASAqX1w0Er0IqNSFqsyuc/7SLpJdZJ9SAwhmo17tSGAqz5LF4GonwFQdGOCpnILkw5+uU+zNpiHRU/eKLh5eRvDo01UpmkcMtgxmDFCVwPKFHqXe/xcCQr27FplPhkzn4zZ2eixK+kRKUekHBMfkXnLWtlkJW/yxcO7GIQ22XZFut9gJ4rGEYWZRLiGwY4ctp+jnMc1Ilwq5xpMTY1WjLdpijb4BLytQNlIoZ0iWwoY6ylWE+KjG8Kkt+qsVt2BgeOBSe/aIxy6+on02Px898Pbp9vW9WAItwQETPz2EmPkmK98mICL2sSgBjq9az+x6Xxq8HJP1fqjb2D4ox/f9NzG7sw/vfKTJwSJp1u9a4/A5+Txvouey5UPu4nR+2/g6rvuvatU12kDmJe85CXccMMNvO997+M//af/BIiw/yd/8id56Utfyu/8zu+c7i7Pm1KRlU5I3WkAmZDHEcx1KHZ2Ge+MyVtycze5TL6DgWzO4I3CZk3idblRRYOySqw3AnAKJytULsgNXivKZoQKQbICioAZl9i1EWowRoGAktjOMk3q2tg5qd3IrIQ8ToXuPkg3aGOIZRxNXdaUtdOOj6r1O3XnQm+wLo4sqpHO3MCmdsQbAE7tnlaHSSolgZpRtJnmZi1uxxzZthidh+kKn4+N8KSHIiBVmXRRktUMl1qiIUiSssElimzBUnRbtAqHXvZiShBHFQjUM3qYBtVoEBoJxbYORVe6OvVKY9CyOhn1HclKhu6NwYu4Nt3q+G/VA1z3Bbwcu59TATH3Bkjq12sgk7/880Svu+Y+H9/XZFUgAiW6QG+VOIEV0omZLEXknVpvIRQmXULZqPNjEDoula4wk22LTsAlooMxBRQtCCbg0uqzbEVrcrKfqDc7BpMHEepXY5fJg1gAl6KlAenwBCNajzrM0scyaS+bZpaPUq8bRRofV5ljLmzSkPhpMCTTAE3tfKWLkbHEjv1MMN82qOCZ/6qmbGrKRgddwvaB2DsHLZ0hb2XcRQlQDIlHJ46lhQEPnT/MLb1tpLbg0LjLetHAB8W2ZMjYRTyqcxcXJst8gQu4atthvlAYosgxSJvY5QidK+KBxRvQucI1I3ThcU1L0TJT/VDZENex8R4HnZJQaFRU6WIzjSo0dAq8V9iBzAG26szqWKBxLMj48OdeT5ff49O//nt0kcn1X/mHA7Czp4F/5NB3eT70oW/msS/9sel77ukzHizV/fD2KWWuC5vocxuvU+/aI/wMf3Ov+xv+6Mf5/Ifknv6oJ3/huNdrEHSqIOb/XXgGN/6P47OB3s4vTB9/7+EP8rEAj+VH6N/+i6e0XzgDG+Vt27bxl3/5l3zzN3/zpuc//OEP88xnPpMjRx58fwRTG+XFH8Y6PbPhrbUji3OsX7NI0VRTcaVyATvylWVwZQ+ZQtlQxP1QDThyEy+bCjOpONF16FVlKVwHhWULckMMGqIBLH0pI7ljBTXOBMTUVXc3Nlodhw1gSynR1mwAN3VWTSjL4y2TlZp2cTaZE9T7rkFKvU1NgdtoVAAzOltN47JGQAUI5S6KZLVuqcvowi4+ViQrRRUYGbCDHJfO7I9tbwIefDuepj+X7YiiZQXg+MpJRkHrK0dR/eGsixQqOp+1qDTBbesyuLgt1AkDdlwNmoYptSObt7gIonGgcXCCPTrATQb83R2/tWV7WdW92V4+9ZmnF4z1f99zZoFnJ/qcM93X+VxnC7zUdW8A5nS7KRu7McDW96Sq+nvyqB94AzZKBbA4IMj4MFmsJr87HaHhoVSoUmHGGuUg6lXdkXbAjhR2BC6qdBYaJldNiJISVxrJONaBcmzBKyhkPz4J0CnQhxNsJRdUpaJxJBANKjqbg2ggLpI+UdiBUJXlPildk9reWfkwBTQ6l06SdFzErYzA9D7tY111XGShqHb5UoXHtWPQoDM3pdLhA65phdbWMBXNrTpfo9jYCHeRqkBLlb9iFePtUFw2ptnKePiOgwDc1Z/HKDmeZpQTG0dqCrQKPLJzN6ku6LuUSDnumCxyZNKmX6TsX+tS3NQlPaJIVgJJT2h3tsq4GS8a1i+HYsHJ9WiUmMgTxSW753tE2uGCZlRELPda5JOIkBnSfRH24IQv/e7Pbn1PqjoVG+XetUd4+5N+4R63AXjRDb/Ihz70zQB8l/4if+Ufznve8B6+uvJWXvWWj5/0fde8KOfnd/81AI9wv8WLbpDJ84OhC3O6dV/Gk2+1b5o+/mD5coB7pZXVAPLLr33SSbc5tn72Nb89fXxObJRHoxE7d+487vkdO3YwGo1Od3fnX9V2u0ayQkK3xeiSOVwkq1XpSimt/o4BLas/LlEVv7laIWspmkc8upAbaDyUFafJgqy++dquMpMVNBfLc3WXIZ+Do49I2O4XSG47KjS0UqhOASp6VNUl0mpGk6opW5Wz1zQzhQ3i/Xo7qJLuN2htag1OLYKv9+c25OJUeTdT44KNFcI0jDIUfkoXC7U1ZbfFeK/Y46bLOSr3BCuDXbAaMywo5xNA4doJZlQIwKvEp6oM2JGbJlmXLcVkwRDvmSO+JUNRWV0XTqh5kaXc3qV3eQvlIO7LoKOrwcgOPcEKl9mOPEnumSxY1q5sMq8UHJiczb+sr+k6XfBypu/591JnG7zU+zwZiDkTKlj8pkcdB2K2alZqw+3RW8jbitEeyBdkxf6ivUdxXmO0Z5jH9Ecp2TDGX+jxpWJhccBglDIYxpBr7JqMOUoFrHW0mxNKZxiPY1BgWgVpWjA83EK3CkzkKJsR2bxHTTQ6V9ixrrQdClMETKxQtZGlEZtmb5Uce0A+z8nCm7cKRQVkqgWrYDVehyrkcva8N6Kz0WVAZwKMXCsSYBQCvrrvq9ITIrGVDlWXCCWLfVANP5GAmFAFRsoCogxFw52BfEdJpz2hk2ZY5dHKY1RgUlp2tfvMxyPuHs5z85FtLLRHlF4zKmMePneABTsi95bt6YClZEQnmvDZIy3M2FbXQ9gWRWHwEQz3QrGzYNeeVfLSsL01ZGXcJDKOy7tHGJaiKxhFEbFx3H7ndrAe1wgUO7da+qda9eSXJ5/a9m9/0i9w9THvfebPPfNe3/eFt8c84rW/tWk/L7rhFx80VLJ7q9MdR2rhfl0nAi517fzyJ4Djr1Hv2iNTMHk64KWufd94Kxd87ByJ+J/whCfwC7/wC7zzne+cprKOx2N+8Rd/kSc84d75ded1eQc2FoCgxRGsXGxhR440QNnQ01TfaOimbW9dSNs8qvjG+VwFEJQkDyfrgWQ1BxWjSnE0GW+38v4QUE7ROBywWWAyr0iXpUvTvyAhWm6iVweEouBY++Yp0IAZUKlb8UW++dxM5ZAG8h5twBUzd7V6H0rPgImZ6XFm2SuuaiExAzR1x0PNbDSnn6kUKrL4bpPxBW0mCwY7CbhcMgLKhiYauunnqwBmIlogH4ulqNIyuOnCYSYl410NyoZmuFMT9wKjHTHRkRZqOCZMsmm3p9w5x+DCJsm6q5xihPqmXaBsGHEDmgSKTkyUl6jSYxuayYLh6CMbtNJFuOVM/pC26v6upz5z/9dMF+ZcgJeN+z4WxNwXHcsWiDl5lQ0IMbh5jUvEoSrbWfCQi4+yrTHgqdu+xCRErJdNlosWf3/nlVx54UEuaq/QMAXbogETH2GU59OrF/Llu3bRaOV0GhO0CjxqaT+9IuXAqMvKsMkVS0dYzZq0lo5yRecwvTLl5m3buXbHV/nE8qUc7HcoDi1VXY1A0VIEZYiHnqhXYgoJaiTeYDJQioAfBT6y+EhRtC3eCABSrrJFtgo7cqjcY8clwWh0XlJ2E1xqhR5c3Xud1ZBUnR0n9OlgZ2wEFylUkLGx7tDnbY12s7HWxTC4CPyFE3Yu9GnFOYkpGZUCHLQKRMZxVecQRTAcnbSx1jHOI2jBeiZzl33ZAkcmbQpn2NNapx1lqGZJPieBlWYiQKxcBB9DefmIvYs99rTXSU3BJc1lbhzIgu5y1kKrwOFRh8wZHtJZY317yjiLmYwNdufwAfk7fDDXhz70zVzN5onw1T9/wxlNjE+1ahDztVCrv/IfNv288Mp/ucftN4IXOB60HLvtY1/5Y/dIJbv652/Y9PO9/d4aa8v8/i+/Ej52j5tN67QBzG/+5m9y3XXXccEFF/CoR8nA9/nPf540Tbn++utPd3fnX1WUKpUmhDgin4uI+iVRv0R5Wwn3pRsQ4spH3yiikXRcoiHoUlM0FcpX+SelxuQWO3AUXYuPDdEwoILHxZp4IGnBygeioYgtlRcRZ0iiY6yQK4pYqLho2syW+txM97FRvI53U1CmtKzABedFM2KMdHe0gSLbbBe9EZToiqpWd22mQZkbhDluQx5OZbesrCVYQ77UZLxkMZkArv4FkbjQOOF2SzYC6NKjcyf0sOr34dIqDXki1pYm8+QdoY/ZLFC0NKOL52h9aTIL+mymjHem2LHHTDxls7L4LILIY1wQZxkPUT/HNS0+kQ5ZuhaYLCgGF5yxSd9WbdUZ1bkEL+eqotddQ/Hq47nSW0XlVlVRnuJANJdhtGd7OmDkEy6Il9lu+8BO9s6tc1F7hatbB0hVUWWHKIpg2d3ocXSpRSvOGeYxc+mYyxuH0U0PcxApx3bbY+IjWjon1Tm3Zju5unWAKxKhVY3mY96z84m09mnSVQEeQVe2yAFcpEWXomV8U4FpxguV+D7vGtHmVEYA0napMrNGiOW+lufELlnhUsmCiYZiAOBSK5k1hXTAlQ/ocRURoGv3zOr6BVkUTNe8mLgYOeairbBX9Lh8uyTelV4zyBOOli12tfvsaPaJtWPOjlkvG1zcXmExGdErUlJTsre9Tq9MuXs0T2oKDvQ7XNxZJlKebUt9VmyL8mBKMZ7pbbIdJbsW+synY/Y01gFIVEmsS4wK7J/M0bAFiSlZGTUYpAnbW0NWjUftCBSDrQ7MqdbrX/oNm6hfx06Ej/35vlS9r42T6x9+8ls3aUkerPXQ5e8E4NCvvuqc7P/xv/IELlrawXtf9brpc1c+7CZ48R/wO2973mkDzVf/xqs5Hd7Lac/QrrnmGm666Sbe9a538ZWvfAWAZz/72TznOc+h0Wic7u7Ov6q0ExiDbzdwiRZVpBZnFl0GfCw+9slqQbIsnRjxi68sMkNENqeJxmHaFh/slsBHkDT6pFeJKDMBLwSYzEt3wk6Ed6udmjY7xCrZz4T2Xs/CL2tRffBQeohipkGYWqHidKbr8aJvUWkFEIrKxz+rRPD1vpwDvTFPpaajVVWWEnoZ2ZkeZuM1xKN0RGim+PkW2YIlaDn3oFV1nmF6/nZUBYg5SasmBOqxLJ8XEBlUhGta8q50ktIVoea5GPoXWJq3xDCeQBThFloEo0iPZgRxvqx425B3NMlqRTergJKr/telXP9kTVNsxcCcUm1Rwc5OPRDgZctF7NyVyUSfIi6KMglOYse4iLi1v43VvMklrS7DMmF73OdJ229izo5IVUGkSrpmwpprMnERlzcPc0njKNuiPn97+BEcHbe4cSQr/2MXsTvtcWe2xGXpYb462j3VeFySHOFTw0spguHCZBmfBnRGJeD32JGXjJNas7JRuB+JvXMYebFRVkKFmyxIR8lHFa3LAl6THrU0VmKioRdHsURXjmOl2EkrRdGJCVah6yDMKm+mFv7rwqNLGffq7ks0KsnmI9mnUWTz4u51+dIKPih2pn0yb9nbXMcHxWI8ZOxihi7mrskCB8ZzLI+btKOclXET3QmsTJr08pTlUYu9nXUet/MuLm0c5Y7JErvafR6xdIC/719NXoj7my5g20PWSIzj0fP7KIIh85Y7Josk2jF2EVd0j5Dogk8vX0gnzfBBYbRnW3PII5YOsG854dYH6G/xwVT/8spnse+NHz/lye8v/NIv3+Pr75ncOzPo9S/9Bja7JB0+pc8+n+u7X/9qDr3isrO2v52vENODE4Gh7379qwH4xIGnT5+r82d+cvv/PmvHcGyd0RJzs9nkec973tk+lge+Nk7QjcY3IwkBcwGvZfXHGcVkXuMtRH0lKchZiU8sOisJkfjIKyeuWqoMlE2xj7TjOtVX+L9lqghNXbXqq0OwkHXMlE+sig1hi9ZI2nFV03BKT2XzLC5cypqpAN/Pt8m2Ncm7ljJVU1qbrgPOykC66mjeeFQMA/KissSpNDRKQajsiDc6kCmNiuMN12uDmF8bVBLL5881Ge1tkHX11L4zGgVcrIBAmWrytpY06ElAW0U0KHGpWIkGLT+rUga8mmIgK4IyiDZWvOQhJBatFBjNZEdDBkGrREDqAr405POWbE4T9zWuGUvoGvI7ri2x845kLtSAc6u+9uuXXvPCk762UVh4rurB2HnZqnupasJfO4LpDEaDBKM9zmsO9dv08pTDgzZfv/sOAEY+5lDW5YJ0lUU7xKG4O1ugbTIuSo6SB0s7yljLGhyZtLHaY5XnwKTLoVGXYTehVyb4oLm4ucxHVq+iZXLGLmKtaGLXJVxYlxKAKTTm2SHbsascyxROK4qGokwNupCMmtWrFMVFE0KhQQeUCSgV8KUm22HplYrGQYsZy/3ZFAGTaci9UHebRoxUYJoZQ9XpQSvsxKEKcSXzsRFAk5WoTkTZ0EwWFfk8+IvG3L0+x9XbD5F5Szea8PWdmzlQLFAEw5wd84X+HmJdUnrNgYMLzC0MyUtDezHj/8/em4dbdtV13p+11p7OeMe6NVfmQCDEBAgIKg1oMwVoBlugBRREEIMM8UUGQwMaAe1+CUZekMbGZhAQW6QRgQZFASXKPCSEkMpU453vPfOe1lrvH2vvc05VqpJblUpSwft7nvvcc/fZZ+99zrl7r/1dv+/QyUK6aUiSK86sr/CQ6gH+tX0OFZWyq7rOjnAdfyIhjxU2NJBJBqlPriX7BlM0vYSb2ltY7NaZrfeYCAYsmjpnVFdR0iCEJc592nFIbiSD3Ke7GYx8l/W2t/wmv9HSPPsEZu7f+sbX3+nzxwNC412cstszvu63NnwEd6yHvcY5nT3+/Nfy0h88+Yjn/uv2T/Hj1WtOiRXx8eqtrz6XT68sso1TB2DuqovztcNP5tHbP8fXDj/5CNByzdLzjwlijrX8Tybfy6/P/9qGj2lDAObTn/40T37yk/F9n09/+tN3uu7Tn/70De/8tCvPc1QpGIIZK0Y3tN6guOBOSKwS5HWFSgyyFC4GHkI7ClSQavK6jxUQrWREq7iU+TinkhtM6Nro6aT7CownENp1KLyBu8GvL+SoVs91TYTAGjNy/jIWa/XIeYwC0BQCftuoEu9q0tvqk9VGdpwA8azA65ZCSUF3m0d/yzaatyeENy0UwZBjVQr3S73NuGFA+VmV4EaK4bo28N1ApJwoNKu544zWnBGCSk0xiOJmAlODCZ0lZ9r0UIEcWk+mU0EBenDuOT1NWlfDwVdo3Hv3fWzgO6BWEa6zErnPOGt4Qwvsksvt40COlQJTcV2tcC0nmfaQ6SaAub/Uyepf7gy4jK9zb4CYzfrJKquAQtsBAuuB52ssEHruunbb8jRp7HNduJ3JaMABJlnq11ipVdkSdQHIjWLBNlhKG2wLWzy0uY9HTd7MjOriC818PsFi1mQ66OMLzUzQJTMKX2gklpWkRqw9vnNoF81bIOiYkXVx4SRmPYHq565VXfq+FFSttClIpizZlpwLzj1INw1JtaIWpGRakRlJnPqs5w1krEibFjvtrJ1l6lBcdVmjEuceWbp4DrWSRbcFIZy4vxgzwNk2S9+FcsYzrpOlQ0sUZWgjecTEbRxOJ/CFpmMqHE4nmPL6RDJjOugz7fdYiuucsXMZawWTobNke/DkYQ70J6kHCTvDNWLrU1EpZ0Yr3NjfyqzXIQxzsopG1TO0Ddg+0aaThBzuT2AqHVpJhLYCYwUHOpNMV/p8d20XFc/R/25bm8JXmjT1WNR1RDa4V///7q/17IlRlt03vRkenq+c8n3cFQXtm97MSW33te/de4dlv/q0j/Ho2yZHC5YTzp9+JbwGfvjmt/Ggt74R2Lgt8Ubr6fYf4Hf+4ZTQx77+7kcPHz/iFV874rltZZfnNdwBvNxZHWu931p/OU9a/jy/t8Hj2hCAecYznsH8/Dxzc3M84xnPOO56Qgj0OJXo/lZCOBtg627IZVpkpBRZLzKzqH5OfR4G007IGG8JCFed7aSKNTrynfWkcDfJmFErXVhLXvVQiUGHDgSVTmVGQdp0ug6ZOW1HuDwYWSYLMey4uKDJQnBvXFClLW2DC+ettQfVMV6RtLziWvRGue16A1HYehbuYAWVubszIG3upP7jNVhtQRnmWepkxkI2gZG+prTDLHQyQjoralsNSWYjp3WpWLwORMsZXt8N3uVnEa454GMCiQ4kg2kPLzYOEymX3JzVnF11tK6J5hNHbZhQDkhGFPbWBjwFvufSqjvO5Sze4pFX3GyiDgV+z+XP+B1N1vCIp9TQIrR+KEFkBr9TfMab9RNbGwEv4+veUyBms/vyk1lZRaA8kIWgQ6YC4RkaUULNT5mu9OkOtiCVpZsErPUr9DoRUrnrTiut0M98pLBU/QyqLWpexK5glS1em3VdQ1tJZhUraZ1J3wEYgJWs5vYpLAc7E4ReTn5rHW9gnQ5ROOqXNQJdUah+jswNBomueuhQkkxI8qqge05OfWuX86fWAGiGMWtxhT31NTxhWIgbzJsGW3eusWCnMKkkmOuTrFSQqSKrC+JcEbYNKjXFZJMY/uig0N0U/jDSuDFODXJskaOWNiRGwWDOYJo5u5sdHj6zj3PDeXb4a8znExgrqcqUac+J5af9HsYKZsI+j5m5iVZe5eb+LNcvb2O6OiBUOQ+f3ofCspw1CGWORtDKKrR0lX4vBGWpVFIGVjAV9rl1fpZuxTmNedIwXR2wtdLhsG3SzwISrbi9NYWUlm2THQ4sT6ITxc7tawzMZg7MRus/Dlb4YuXkwMvJ6mPGuy/jmo6N1l9PPYN/BT58naOfveDCOYAjwUtRr/1P53LVp+c4+Ls3cpBf4dHbP8cZV72Jz73i1QwmTw48gaNy/dTyx1j4oyuHlK/y90bqeGDnaNBydP3b667llVu+fsznjgdoTgU43RCAMcYc8/FPXBnjug9SQK6R3RiokjYkQlsCY5GpJlrUBOuKZCqgs0uRRwHRqvPTl9ogcHzi4WYDicw1eaTI6gq/p8mqztEsr7jOS9AzRKtODxK2NdWDA9RyeyTML4T3IooczYvCFnm8+1KNiPdM0jo7IKsLwrUiobkHMoewZ/B6ekhts54gnnI3+2Fbk4eS3jZFf26W2e+EqIPLLstl3FUsz0dUOzlmtWysMznTBnyc+L7m7D2FtYQtt2+VaKc70Q60iFwjhSQvMl1UYlCBA1hCO/CXTHpgIWy5/z3jS0Qh7swb7sYA6yw5wVl7pnUXkJk03aydMM6K2ThnZ6LlDOM729C8IsjqguqCC0lDFa442SaAuT/UiXZfTgS4HP26zU7MZm20TDAycvT64MXQ6QVs33aYqcDNxq80qrT6FTKt6K5XQAuM72yAtZH0k4B+P2Tn7DrGSg4OJpn1O6zmdVraaU7nkyYLgybrfoWFQYPzmksMtM+kP6BlK5w3tcSNq1vwemNmKZm7fsrMYJUgm/BRhfbSBJLOLkUy6UIaL73wZqSwzIUdBjrgrMoyfRMw4fW5fTCLsYKq78TrrakY38+phSnznZBsCmTq4Q1c5ICzTy7ZDM7CPq+5ZSo2WF866q4AG0iymnOq1CEks5bojA6NSsLDZ/ax1W+zlDfpm5BbBluQwpIbRd8ETHkOzCXW49zqIgrLWeEiN3S3Efk5u2rreMKwPVinbwJ8oVnPqlRVSiBzVvOa60KlEiks1kI7dc5l1TAlN5KHb9lHJ4to+DHdPKSThmgjqVcTMq1Q0jgjBmXpxCHC3I8nd++leuNb3sM3Xvecu1xvXHh/qgT95XY+/LZnndDrHv7OH3Pg5mUuBxgDLyWQKf8G+NqZ6/zJzzwEgCuffiVPed+3aP3BA/iN1/0i/+kPf3C3wEtZ4+Dlzta5O7V731Gv/8Or+I9v+hwAT+u+akNdmKPBy59MvheAJx04a8PHccIamA996EM85znPIQzDI5anacrHP/5xXvjCF57oJk+fKm5ehwn0uSZayent8MnqgiT1hloJHUrShkRXBL2aIGk6oCCMJegZZGpd5oty2pms7mb5tQ96UqEKfjCiCOQSELY0fi/HW4+R7T4k6UhbotQwjBJwji3WIpQCKbHViGTXBK2zA2QGftfSPgeq8wK/a4mWM1Scu/R5K8krI4Dlxe5YCaG6ZIgnJK3z60x1YteJMfpIkX6ZA2Ok63gMicwMDRBsJWSwNUIHApU6IaeKnQONjmShBbLoSA0HMW9gyGqyMERwXS8dKuIpgUodn9wfMBxkpS7yBLRzzDGBh+o7brXMCwMFBdUlTR5JurskXs9ZeZpAIlND3HQ0NK/vbKzLROm8ItFyLEFts45bX/jEjvtMyH9vgZfx159KEHNfdl82Bfz3bMkUbJUiLNcBGjtQdNKIR0/dwgOiQ7Syn+HQvhlUPQMtEImiPtvDk4bVfoU8VwRhRj1I8KWmlwfs7c+xMGiSGkXdTwB4xNRtHEim2FlZZzmpo4RlLuhQVwnfXttN57oZJvbZ4ZgjcovSTm+iKx74gnjGH3bj0wlBOmHx5wZ0s5DMKM6orvJTtf3UZIIvNLekW5iPGzygsUBFZSyldZb7VSp+7myMayl56qFDRV4VeHEhrxzYocZQWKdtLK/hQrvcGF3xMEq6Caym099kMxkXblmk6mUsJ3Vu7c0QqQxfGA70JjmzsUJuFFkeMut3h0GVu4JVfJGzlDdZiWukucdKUmN7pUVXR/yot42B9glkzkpap+6l3NqbgZUQCVSCDNmwSGHZMbvOrvo6NyxvxUwJtkctftjeRicNacch/TjkvLkl6l5CbiW1HSlL/RraSITe7MBstH7+ry7m9S/cf9zn7ykb5WfK64HrN7z+X089A37/dwA468t/CcCt/8EBsJ8eW6987sPvW4SXwVPe5xQ2n33Zw2AfcPmtPOitr+SMq950Ut2f8XrNq/+AjwZ3vs44wDlRMHM0eNm/5yrm/2iUN3Eyov0SvAA8+dyNW12cMIB50YtexJOe9CTm5uaOWN7pdHjRi150/wYwMKJjASLN8DspKnEdgGRC4sUefte5qoQtTTwl6e2yyKYgXHXOMzpQyNx1Hvy+RcXuxjyvSNKGo5dVlk0haHc32zKz+O0U2U8deNEGfN91PAoQI0qqVuA5XQyAp7BhQLalzsLDXepydUljfEF/mxyGQMrMzW6J1CCsQfqOruUlBqME/VmPoGfQfkEvA/pnT1Frd0H6ruszFPUXTm1QHJ8cUc2KMlWnWdGBywswviSv+4gyVwBnmWyUxIs1uiLJampo6ylzlw+QhwKZORtSKwT+oKDc+U5X43ft8LhFAbJM4Dm9jIWg58SqeTQKbNOBIG1IVCoIW5poNUdHzvc/KTVJCow+ijK3WadN/aRkvmzWT26NG7MIC3kEMpbcdHCOS2dux0fjCYPfTKhXEzpU8CdjqkHGWr9ClnlIaVDKcLA1Qd13QY3/cuBs0sRDSMuWiS7NMOafV85hZ7VFLw+5rTvN/qUpvqLPxcSK8JDP1F4XxCxKYxIBxpOYSBVWzwLtQzwtyeqQVy35dM6Z0y08aciMu7YvZBOcES7T0yF9HTIVDPjWyh6UNNT8lJ3NNoc7TZJcYY3EJgqVUriSuU6UzC0q0c6qWRYGNiWxQ7rOiwsYdtdf47vXq5YiUjl7KqusZDX6eYCxglj77KmvsZZWmfBj+llAK6/QziPOrS5yIJ2mrmIWsyY1L0VWLIc7TbZXWqzmNRYGDdbiCjvrLaaDPotxg24WYiKD6rj3PVvv0U4iZis9VuIas/Ue61mFbUGbiSBmeVDHWsF0o8dk0OchjYN8r72bpUGdepAisWiT3Iv/ffffenvjfADe8aHdw2XHAjPH67zcGbi5s26NAy8nVyVAOfrxeD3lfd/isy972BC8lNX7Dac5fv+fXsNVn9443et49bodz+Wnlj92p+vcnQ7M/j1XHQFidu+7knlexGTn2wBc0/3gEMSUwOS31l9+zG2NA5eTqRMGMKUG4+g6cOAAExMTd+tg7vMyesyq2AU6yrUulbpPe09I0HGBWjrwkbmbpTc+RMsOlHgD6zQWfTdIlKLztOZhfDeQydyiYsBCtK5RsUb1M2SqEb0YkeXO2tgUxwCgtRPwG+scxsqy1q3je/R2RcgM6gc10XIK1hKtKJIpD+0L+tsCVOr4z3nFiSKTpsAbuA5MXgVhnMDdOcdYBls8om0zyENLxedT2DaXv8er0OmUpgK65rhaUjtwZj1B0nD0Oa+v8boZJlCgHCUsD8fyBKCg2EHacI5pfg+CrnFuYoHr1hhfEOLAhjAgkrI75b6LPHK6l6BnqaxqKiuQ1WQBIDNnDeoJRxsrkqbzUBB2NDaSQ33SZt113VtdmLsDXO5u92V8O5tUss26qwq6thCdUzgiQmVBkiQh2UMUsXXXyF8458espxXSKcUjp25lWvX4YX8HTS9mLa9yoD/Jgc4kN6/NMlPtobVEeYZKmDIZDciNdPlgwE3tLdyydxv1mz133Szs+mXmOtJZbZR4L4z7bWXhrOlD1nDHany49EG3sDSoA7C92mJPuILCsJBNcDidYCFpsCXostKrEng564OI7Y0OQliSxHfHZJzNfdZwuhe/Z0cuZzXlHDhTgzQGE0hn+GIhr0o3mZY7AxqdgzCCUOXsDNfom4CLJw+wkDSBAb50YLCVRfRzN/18Qe0wh1NHucusoipTHj51O4tpg9VKjR1hi8R4PG7LjRxMpujlIVNen54XMh30ucHbgfUla50qO+otFjt1OnHIRCXmzOYKW8MOLV3hnOoSEstaWmEm7JNbyXwyQW4l/3Hrj1jLqywkDZaSzVyxjdQnr/x9mme/nQ/u/Qhf/cB/BeAdb7vjeh/8r3dcdizwclcUs5MFLs+66k1cXtoGHwVKjlfHAjFPjh0Y+NxvXAVPOalDGdYnr/x9vvroDl96xJ0DmI3qYsaBzvhrUqLh4+AVMX946OP81dx/BOCVHAleysfHAzF3pzZ8Rl1yySWIQkj+8z//83je6KVaa2699Vae9KQnnfIDvFdLSJdgLySWDIxB5Dnh7ZaJfIrB1oC47trZJY9XaghXzLBDIwykTUG47vzsnXWyIY/cDbnU7nXhSoJMcmTswIqIU8h1ESopsblGKOu6QWXQpNHYVDv74sB3gEEITOSRVQXVRUO0kmGC0iDA4HcNourQRlaTCGNI65L+doHXc+FqYgCVFTfA5RWB8dxgqAMY7KpRn1/B5oU2qNS/lJSysuvij1sqO+6yMLZwVyvAnnJZOsFqikgyhBKAwnjC0bc8QTyp8HvOctNaQWXFcbRV6mh5gxkP47lgMwDtC4K2RiUGkWZDxzaZW8KOe09ezwztOSFw7kCAjpx4VUiBnvJJmqO0ZyKnx9msjdc9CWJOt45LCYY2gcxmHa9kbpFdlyFiAjG0fRfAF/c/gP0zUxgEi3Gdqpfyg8Xt7Kquc15zgUc39qIR3JrM0coq7GmuYaxgLalSjRKsFWxrdACIVE4vD/ju0k6WD09Qv9mjsmiH2Ss6KE1oXBdGB26yiMKm3niQ18Sw8xItCwZn5JxfX6SfBxzuNKlOpexLZtgTrqARJMYjlBpPGqaqA85srhBKzULcoBEmBEqjraBTiejpGjJXyMxNKAktkamzxPf6ZtgVErkdzovJzCJTR9UGB7TypmZntA4wdBrreiED7XNja46a72ayE+0hhaWVV+nljuo+63eYUE4X4wvNtqBNV4fs7W3h4mZCbhQ/XNsKU7AU1+nlAaLnYQKD0ZKql9GIEixQ9VN2RevUVcKhZJJpr8f2qEUnD6l5CT9uz7EU15kMBjyocpCbEpfX05KNe+Pf7iei2re8gat++2Vc+f/+Hr9y7vP54N6P8CvnPh9g+PhXzn3+ndLMyjpeR+buXLtf+969R2hcgKGF8Ebqsy972DGXP+GFGZ+8G/KUZ131JrYdeuhxnw9ecceYyPTd0THWdLX1d64avmYctPztns8OHz+bx/Pc8PE8fusVAEwtvBM4ftdlvMp1xgFOHKf8Hn92l6+FEwAwpfvYd7/7XZ74xCdSr9eHzwVBwJlnnsmzn/3sjW7u9CytIYyKRPnCRlkbxCAm2L+C16kTzFXpz3nDmaJwzQw1G2HbkFfczb8VThgvNG6GqRBPBqspMs2RndgBlzLxPteQZc4VLM/BGqx2tDE7fnxKYbPM+dpEIdb3GOyoYTw3UyVskWeSgygCytJmiC26G15fI+uStAEyE1RWHK0gq0mnwelDXnHZNEGnCNmMQkjToVc/QrjATKVctwiGuTNC+qDNsP0frWnyquuweLF1oC9z4EdHHjLVeP2MeEuE0BZv4AYrv6vJK4qsLvF7pXjfAZO8KkYgJBRkDUXQKgBgYWxQivadu5pHbV4QriSo1JA2FVnNQ6UGBGR1Z2SgUqeDKal+QXuTQnY61OkGXsbr/taNeU/wq/f1Ify7KRVbZEGRyotuh8gFKhasr9U4FE3wH7bexHzSZFvYZqHZZMIbsK6rNGTM3ngbi1mDmkpZSWokuRuurRVMVQd40lD3Eg73m9x26xyNG31m14qssWKiSWqL6hUOmkmpNRm5X1rprntBy4n6jXKAxm+k/P2hB2Cs4IKZeXKjuHbxLPbXpzivvkhdJdRVwpTfox4kGCvp5YrFXp1Wr8KOqRY1PyVUmn5eJ69bsoFzHUOC33dGMirOnduntehqMHTwBGfgkkeCrOqyX1QjY0+4QmJ8Jrw+VZniC8313R0stBtMVgec2VwlUhlVmVJVCTtCjUEwoQbUZEJNJsx4XfanM6xkNWbDHpHMMAgGqc/hQZPb16YY9EPCNUnWAG1Cbp6aoR6kKGGYDAdMeANuj2dYTysYBOdWFrmgMc++wTS7a2tcWDuEFIbFvMn32rvZGrZZT34Cgr7vg/rg3o8c8fvu1je9mbutM7l55YPAk4dA5Cnv+9YQvNwZkBkHLl+ffDMPfu7v8rno7tPGyvqp5Y/xuh3POy6F7GdfeAP//KELjlh2LFBzrApeEQ/BztP2Hb9VdM3S84ePN6qHOdnuzIYBzJvf/GYAzjzzTJ7znOcQRcdHbffbkqKwCy5S7gvrYGsEIk6QCymV9S7hoSrpXJEurwSm8Mv3ehZRBER6iUXFFq+XowYZsl9kq2iX5SK0GXYLsKN9DbNVrGtDzNdaAAEAAElEQVS1l12W8eMSUTBax1MMZhQ6cm5mxnMzVn7b0ciSho/XN0Xb3okkg44hWvYQ1lG0wHWM/I529CwMWVUivMJgIAqgqwBddGDsyOggcIClfG9WGYR0x6JSi/Gdp3/adDqUtC4xXhW/lxPP+FQWHDBSiWEw66EK84NhMnPuqGDAEBTJ1OXluFDLwna6FY+AYO4A1HDQLmywk9mQcDXFeILBrOdcx5QzDVCJxTMFvUEIojUDmxSyE64SbNzdTsypBi2nij62WZu10XI0LYuXFHoYAWCJ1qGdROxrb+Xja018X5NliiDIuTHayq39GVaTGoc7DTq9iDz18HwNt1fRkcV6ltZEFbse4LclXlcw2WaUsVIEIxvF0DLZCeaLTod21zjrldoUN2YIA1nTYhKYm+qQ5B6e0jS9hPm4QS/1WYlrnFfMXbZzd0M+GQxYjp1tcy8JCPwcYwX71yeJggw5k2K0IItDdAQqdvoWf+Box8ZX7tiK9ovQdtgZck6R7povhCWzzmWsrmL6JuBwOsHWsE2aKppTMXHRfembgMyqoaXyctagK6OhzfQN/e1oK9gWttEIunnArokWi706vU5EdFOE3waZSuIthvmDU/j1lEqUMb2lT0dHDLSzuF6M65wRrdDKKwy0T02lbPHaNNSAG+MdNH13g7jQ3uzAnEh96+r3ccOEu26Pu47BSBNzPHrY0U5idxewHF1XPv1KLvjSg7mhEPy/5XVH5iM+gWPnJX69WP6I9bfyiPW38vWPv3n43PuvXuPXmeJP972e91+9dlK5MG9+117evvfPj/v8l959Cbw72jBoKQHL8db/tPh5vnXu+4D3wWtccOfJiPjH632TG+u+wEloYH7lV37lRF9y/6kSuJQyk2OERookRWY5UatLWAmdiN5XdM5t4vcMfivFetLNLPWSIsfFIHI3y1RmrwxF+GW3R6miAxQg0gwrXQaLzYtjKIGN5422ISWm4pNXCqGogayhnEWm8ZGpQSWGvKacGD639LcFCG2ZvCXHKlg73yNtWoSWhC3hgI8Q+B1ZpCZLTBQgpSjMxsyYWL90SJNDswEhnAV1tDigt6eK0OD3DGHL2Rz3t/rE0wqhHbiItwTIzIn7AbKKRPrFoJtahBHDUEqZO0CTVZxWBRyvvHY4Ray2Rp+jdPtMmpKsKgm6Fr/j7KOtJ1CxceAqkBBrl4GQGRealrjsmLwiC8rZZp1M3RkAOR64OZ07LXdW95cuzGb35d6tUmciU4v0RpNbeUUStMDvKcSNdQZbAM/SmzB8sx+iY4Va8zCBJVxVeDnkNUt9n5ugyuqgbqlQmzf4fY0OpKOJSXeNV6lzv/T7FpU6+rIOJFjjAE1uMUERFinE0AFMB5J8NiUHHjx9GF8YpDA0vZhDgyZbaj3OqK+SGUU7r7C3M0sriWgGCRUvc+n26xV2bF9juVtj0A9JI8WO2XWUNOxb3o6JwKwKkoZExZJcuhwYv5sPJ63ctd+glMR4FpVAXhXotZDMKs4NF6jJhGt757Kc1pn2e+yYbhOpjAOdSRphghSWndE6B/UkmVXc0p0lUhmx9tkadZDCsjVsExufm7pzVFSGJzSz1R5r+7YQLbn9CitIpsFb9smM4HFn38RjJn5Mz4QoYVjLqoSFW8OZ0TJTXp8Jr49GspLX0QgCmTtXsmzT1fJEa3hdfQvc9Jvn8eEdM9y+ssiV/+8/3+nrXvDGT94tUf5G6obHX8/XJ998zOc+fP0v8oIH/+87LH/E+luHrxl/7fuvXiN6wq8D7jXv+rf/zs9xcsGWr/5MxLueeucA5Vi0sWOBlKOXjXdh4Njhmz/3hT8cPv7qE153l8d7dD2i+zv8LX+0oXVPGMBorbn66qv5xCc+wb59+0jTI1PbV1dXT3STp08VFDKbpM7xqwQVY8/b8m8hIU4Qnps9mmj3i+ViJGiHEfAAJ7iXckS7GloiyyEgIUkLe2TpqGRld8Oa0fZLEAOYQBUgwQlG05ok6BmSKdd58QY5Xt+QR6rw4RcILRDGOK1J5qhkQdegBu69ZQ0nLs0rkqQhaZTvoXxP4/qXwtpZhAGkmft8/ACZjpKXwQ1IXj+jri151VG+dMUjmfJIJqSjv2nwCkc2FVtU7GylAZIpH1l0dIKuxe8b8siBmuDAGtYUAZpCIBI9pIFVlwx+twgkza3Ln/Eg6Gj8VobqZZiKhxEO2Hi9DONJ/LYlE5sA5p6o+ytQubO6v4CYzbr3quz82mKUFdZpUqx0xikOYFjCdVFQjyVWRmQ118GmsIE3HtQOOD2lFRa/O6ZlwQnf84rrRJfOZ26HFBbO7ronMzeB5lwpHeCxqtDqZEWno+0xfd4qM36P8yvzHEqnAIi1T2YUxkr6JsAgOKO+ypJXp5NFBCrHy32kbwiURghLrRYTJz7dJEAI1x3SkzlWBuio6KgXOWEyM1jrDFVUnGP8YBhBIAsXM9FMaeVVHhLtJ7Y+2/11zo/m0VYQypzvru9iMho47aTKODNaoaEGfLt7BoHM6aQRWypdDvYn2F5tk1nF7f1p1uIqjcJJbDIaoGIH/oS22AF4fff5RlMxvjBkVpFZxZTXYyWts5rWmAvaAGRWsZw1hlqbtSJQdC2rYs0mgLk7dd57bgJcJ+WZV7tlz7rqTbzgjZ8E4Krf/tlTnmZ/vLrq01dx5dOv5BHrbz1ieQlKjgYv4+s9Yv2txetHYOb9L7qG6//of9ArzAqu//gfwJ6TO7afM5/lve9/0zGf+yzHNxtIxzoz6Z10acrlbzj3wB2e+9KP/xtTT1B3WH68Ov/Fd7Ty39UZ8LcbZNWdMIB561vfyp/92Z/x27/921x55ZX87u/+Lrfddhuf+tSn+K//9Ri2EPe3ynOE5xU36SVlqrhh9wNnJQxgddGZKToS3b4LZiwpXyXIKLs4SmKVcwzDH33sIs0gTgrXM+1E+8YemQIvhTsE4TJqbNntKJ/OIas5hxdhoXWWBwbqh4sMmsLRxXiQzAgm92q62xVWKTebFzPU4li/dP9SmIJiYJVACuGOSLiZPDwP0swdh5IjoFWYO8h2H2FqjuecGETu6FpqkCMy40I8q6rgYDu6Q7Sa4/U1xnf+/8YTCCPQoRN9Cm3Bd7bMVkHQ1lRuXkF0+1hjsUa7wbA3QAeT6IpAh4JotXA2q3mUTtReX6N6GTLNsaFCphodKXTkuWP1Jbl3wqfHZp2i+uupZxzx97PXPnWfHMc9Xe8JfvVeyYI5Vvclfe33NrNg7sHKahLrySG1y7fO7EUldui2aIWbPIrWLBhnd+/1c4SxZM3iJt5zE086cNfw0sUrmRRj1GFnUawT8HsCf2BcMGVQgILEDMGMDlyIcnlcMrUoafG7Fr8tman2+Pnm9fRMyGdaF9HPAyKVsRZX+O7STiYrAx46vZ9vruxhKuwzFfZpJRV8pdky3SHTigdtWWA9qXCo3WRtqQGpRMxmSM+QV92kmbNvdkYsGN/pdfr50Na5dEhzYEJg+h5reZVvD85kb3+OgfZ5SOMgu/1VujpkLa5wzsQKuZXMBl2mvS49E5IYj9vWp9k10WI9rdDPAjpZyFpS5Za1aXyluXVxhjPmVrnu+2fQ6LnxKIhBdG0BtCw7plqEMiO1Htf3drI1aBPKjMR4JMZnTddo5xUS47E9WKelK/hSo4xhMZnYtOW/B+qTV/7+mOj9nu24jNeVT3c7PboDU3ZYSsByrG6Le/1bueBLD+aq7vN4wgsz9/wxnNZOpvb0P8zf//q/AHfstBzdQTm6xp/baJfm6FrbesVQyH9X9eMPfO+Iv89/8U/xVx/bOP38hO/Q/uIv/oL3v//9XHbZZbzlLW/hec97Hueccw4XXXQR//qv/8orX/nKE93k6VNKuRv08vE4XUqKURdkuL4crj/smJQ3vVkGYeBAQbOGbkYkMyFZVeJ3DciC3ysFflcTrMaolY6zUQZslrmgyCFbS422jXJOZLgBrxyYytk3oZ2DWDwpaO/xyWtQO2AJupZkRgzpZLknHHjR0JtTyCxwpgMFnSuvOtqY0Na9NyFBWgemrHVATBTgSo3NLhkNg5hovk9vT93N+AnQSuD1C7pC5GhkXt8grMXrO5cwmTtr47wmEVqiEkNWd2DKG1jySmEG0NVEt69Bp4ctzAWEEM50IU5o7E+wInKamjJ3JnCUOmfdqYczoiI34Lksm7wiCdrmDl/1Zt3zdTRoOd5zP6lg5p6qTerYfVPGc9fhoOsmiFRcOG4VtCmh7dCMRGh3LTeewPoScmfGIo0lDxQyt87qOHDXZaOco1kybTFVg/UMXstD5FBZEogl153RgTM0QbhrqRVuPyJ1E1O5cIHAGmefrEPLLQuzdHY7fcuDm4e5qTvH7uoanSxisVNna6XDVr/NYqfOzto6sfa5aOogN7S3EShNaxBh6oLMKPJcIXyDzSQy0IRhRlqP8PpuckklZaZXMXHnOequKMYzoV34ZrhmyRY9vrm0h85kxI3rc8xVO/ztwYuIc4+paMBUNEAKw4X1eeoqRmHYl8xw4/pWksxj79Isg1aEGCgONKZQ886hrDOdIwLN7d/YxewNILXBGzjgokOBTAV5zbCzts7jJ37I9/pnkGiPpbRBRaWsJFVambvZa6cRc5UO+5IZOnlEw4s5HE9we2cKM9icELsv6llXuW7EM380x8ee+yKi7zqK093RxVzwpQdzw+OPDZiO7rYcr254/PVcCXydY9PQvvroDg//pUuovHrvCR3bJ6/8fc7c5rJoJvjdI567M/BydH1v9nkAXPrcP+cbH38Rlz7XaWuO1Xkp6/Hnv5ZHXvYPwF1PjB0NXk6mTviMmp+f5yEPeQgA9XqdVqsFwFOf+lTe9KZjt63uNyWEuxEvs2DKLkphYTykg8kxUKM15BZ833VuSppVGGB9j2z3DMlMMBSgl6GSxi87DJBMeiSTdYLZCpX9bUS3j8gFKIHNzWifWrt9wPBYxCCjuqTpbVfkEfh9CNftMHugsmxJUxdOKbWletjS2yHxu5bGAT08rjwSRV6A08zo0Inuvb5FrnWwFCDN6BHIgzGKW0kzk4DBGoNaWKcmBL3dNXToYQWELelccgqQ5B4b15XxJGndJ6u7jpGuCYKe23bQduvX1jL81T5yrYvt9wuTA+nAS0G9w/Pwl/t4W0NU4kI0VZwTLg6wocL4Ch0qvMINTWQaai6F2u/myH5GPhEO7aQ3656tOwMud7b+TwqQuae6MJvA5T4u54/iHCIzZyoitUH70nWKtXWXTVvmhkmQoH2JMoXxinKdl6wmaT0AsgmNamYAKE8jLVSjjG67gphwQYn9MyWd1ZBgVaJiQdCGoG3xPIFvnD28lS5rJas4CprxBVldOCDkGVKr2Omt8bj6DTyufgNVmfC4xg38Y+cCLqgc4obBDs6YWmPSH9ARlnOiRQY64OzZJb62djZrSZWKl7F1osO+eJrKlh7xIMBagdd3IcMys0TLKVnDc+OAdmNBEWmDSl3X3goH8IK24ODBabQVbKn26OcBC+sN8kzRrwacP7tIbhQ397cw7fe4jVm+t7qTQysTZH0fMVAE627sCm6PqB029LdK5+5mPKZvcJ0xHThQh4DKisGLJUuXSHKj6JmQqkrYU1nFF5pDySS3rs0QBRk76y3qfoISlsNxE18YGh54UlP1M9jswNwr9bDXvAyg0JTAM//iWj723BfBj/6c5338zwEXwv7M5/8JAH/zwMUTBjMleLkzgHJ36+qn/BGfPEHwUtbEdQ64HK9jspHOTOlklr474qf42J3SysDpYQ6963/wkU+Olp2ou9jbr/42O2obz5M8YQCza9cuDh8+zJ49ezjnnHP4whe+wEMf+lC+8Y1vEIbhiW7utCrh+04jIV0+iaNsMaKNgdNYlN0WI4+wW0aKIYix1Yh4Z5P+Vp+w7Vy9wrbG62o341Vx3Renu9AuTGxKkTanaNzsoRZb2DRFhOEYtWxMKwPOQSvNqCwMSBu1oSYkqzjwEq2ZApS4maTOLoUsJEvewP0OizDNZMpHZpa8psiqgqwKXt9SWTOFPbFyxyALNzJZdKgkI/e0sgsjpNOjaI1aatEYZAx2N+nPecTTiqAzam9kNQkotO/yWaxy7XuZQ3XJhXKqbuJCPnM9DPm0pgCYWo/CPccc3ES7R/22gMH2ClnducX52dj3CFjf0fCsJ10nxoIJJHomcgYKmxNmp3X99dQzNgxi3viW95zWTmR3B8TcHaCySSO758pK1yXRphCjAEbJoVjdCvfjxptRmVC6H1+Qh5LeNmfnm82mTG9tE6c+xkiiICPTCl9p6s0BO5ptJsMB26I2hwYT3Lg8R/tQg3xVDS2SvYHAGFGEB7vcK4QLXfb6lmhJ0o+qfKt3FrVGQly4eZ3pL9OQA57Q/AEzss+PB9voZQHfXdnFnsYa/7T2ANaTChWVsi1y+TTGCmRgsSshtXO75Lkiz5STfJrSYWxEbxNDc5qi66/E0FUtarkJLn/BZ7nSoBkk9LKAs7askGiPxXadH85voxqltFpVompK4GmSzMMYiVAWLPgdd52XqXPgDFqWaLmYWMwdpQ/rNJhEDCcZg3XBv91yJqHK0VZQ91IqMmU5rdGPA6phSmo8ql5KK42oehkrqaOTLcc1DqxODu2hN+uerVcvXege/MW1w2UOuBy7nvmjuSGYecFHfmtD+yg1MBupv/3Ag3nai68f2iYD1P7UMWi+Pvlm/p9nDPjvnxpZbJfrfOEpGxOyH6vuDGjcGXgZf/y9WWfH/OZ3jYGod931vv/om9cAsP/cG8jWv3BCx/3sySdwbX7X65V1wrdoz3zmM/mHf/gHHvnIR/Jbv/VbPP/5z+d//s//yb59+3jNa15zops7vUpJ57QFBV2qCG40YzfntqBTUXQkbOEiVg5CBbWqf+YkeVUSto2z8J1wg0eYOYF9VnHgSEdO56FiQ9h2F9DuWXXqBtRqeyjqHx2jGmprRJxiKyGyn1Kb94lnfIwniNZdWGV3h3KBm32LKgSeLovFDRDxtDsGkRvCtYz+VndS5aHr2GQNwez3eq7LZMaOobR1tsbpgmxhB62No5hJ5dzTpEDkGtHtU7k5o7LPI5+oYCI1BEzeoNSzlNQul5njr8fI9a4DLCWAKyhi7nM2hR7Hun0Vf1uTOwDjeXiLLYKaT2974NzLJqJh5gCA8SWy+J1X1TC4Uhj3mdQO9+6J/7LNOoV1IiDmnqxTIeAfByIbATOnqsOyCWLumSr1g1Y4sb6wrhvslgmktYjMkNfVUBuDtWR1RdqQ6NDRxeJZSzqjmd7aZnvDaUweNr2Pc6JF/rl1HktxnQua8wBMeAMkFl9oztizyleDc1i0MyR9hdcHqRVe7K6bMrdDPY2VTtgfrVp0qPjy4XOZ9Tts9VoEQvPjdCsdU+G8YJ5p5fJYulMh+3rTnFldYSFpAnB7f5puFmKswJOGg60JmMjoxQFBkNNdrBHIQtPiOVAFDkAYT2L8cnKOoXZHaBC+YxYYJWnVQ26V00hp6Uc+3X5IthYhY8laLQJlGaw2GAC2kUMikQNJ41bX/fd7FKY1LiTZqlHmjCwiENz3V7hdCgjaYPZW+PGWLWyvtWmnFfa1Jsm0whpBJw7Z3VjnQGeS1W6VPJdM1GOUNBgriDshwdImL/merKd8psvCP/w2LN3z+/rklb/PlU+/8rguZOO19YpfHNLEPvIGN4l6ydjrxsELOAF/CWJOtt5w7gGeddWbhrSv8Tq623IsWtn3Zp/n9EUnuN/Dr7bsf8sNw7/9ySccd90S3NzZOndVJwxg3vGOdwwfP+c5z2HPnj1ce+21nHfeeTztaU876QM5LcpTEGcFNewoGJgWy4V0zwX+6GYanHi/qGz7JPGMIlrTxcSbS5SvLGWI1IGLZELS3Jfjd3NE7mabVOw0IIMooL+nRr3TR6SZ27a1WMnIAazIjhG5hxUCf3WAyC2dM0JA4PcN8axiMGepLAhy68CL0BCta2RmaTc9jCdIJzzn8mJB++4CLjOnOVEL6+592jGqWBloaeQIyJTiflH8SxWZOrbItxGJW+6trAMQBoH7vEtwNtZZGZkojJWx2Dwb6ZI8z+3bWDDld1UcY55jjUVoTbh3EZnOkjZ98qrCE6BiF5Ipc5c3kNd95xgkQGUG1U2R/RRd0CM368i66TEf47yvPO+UbOtE6WPH28ZGQMzp3oUZr3ub/nWyICZ97d3nMf+kVlYTqEppbywJ/UI8r21BoXLUWZUZjJLIzIX8WumYDLHv6FNWAYG7tkUqY0vU5fzKPBLDUuxCWSa8AX0dEMqMg8kUxgqm/D67GutkeyRr9Tr+vhCZO7Di953Ww3GDLSp1FvZ5RRB0YHHvDH+rLuJn527mCc3r+Fz7Inp5yKTqEye+C3+0klh7GCvY255le7XNTWuzgAvb3NboFDkwDnT1+yHhgodMBCopMrqsm0AyTrIzCrIsPh8AHcmiU+/GpOZeRbpQJ29Y1hsGORB4WhQ6Is9ZL8eOjWDbPn5PEC1Zx4AYFMDNFh0eW9pbW8oWiTBuUk3FBpU4ExyZWby+YP5Hc7TPiKhHCdYKksQjzxSZ57ES12gNIrLUI+/5rBnJg3bO00lDlvuKcG0TwNyTVWpb7k495TNdAD771PpdrAkPvcidp9/+fnKnHZmvfGCMRvXz7tdfBH/HL6eX3WHdT3/fbePB2LudXXOkwcFICwTALMQXv46Ff/htzpiZG+3rXeUKJ7/vN77lPUeAJ/uRpx/xfLb+BT4tfp5nHwVcsvUv8L3Z5/G3b9n4voU9Ynr/32e1220mJiZ43ENfT3i442b7tT7SwljI0U2z1k7ALtXoBr6kz01P0H7wNMZzQkvl6MoErZzocBekJJ2pYJXA62aoXopIc0w9crNzviRt+Ahj8dsZwa2L2BI8Gev2Za07FmOdfbGnsNUIUw3onlFjMOucxLKGQKbuoi9yB1DyiqCy7CyUVWrIq45K4Pddp0ho6M8qEDD79TXkyrqja5UdGDPWjSk/FykcACmPURYubGMAD88bCwoVQ8AjPO/Iroq1iCBwXZW82GZJUSv3O76f0uUNCvvq0oTBGSyUdthmqkk+GZFOBajEoBJNXvGGWQ3u805R7RjR6UOWkZuUv194P61Wi2azec/8892PqjxPTjcAAyemhznVIOYnzT55I0DmWMBl8zxxVZ4n57zhbYhaSNASVJYt1cXcCeqtmzgBp0sEhtczoS1ZQzGYUsRbBFkN0imNtyVmeqLHL+y4kUhmXFTZx6FsiluTLcz6HSbUgK52QY3X9XYQyhxjJd9c2s1EGJNoj9tvnqNy0CNascMxABhSm0rKWh4JBlsEybQletA6Tz7jBm7uzvLoqVt4UHSQdV1lKW9yY38bsrCan4+bPGxiHz/qbWOgfW5rTdNLAupRwvz8JH6Uk3UDooM+wTrM/iBBxZqs7ijXKtZDZ7ThbyUKAOcob1lNYjwHDIUFrOtyqcR9jip113Gv58Y1mVuXwZM5KrUJCsOd3BTgZdR90qEkq5bfibPZVwNnKKNDyWBGOdOEyUK3OmVJt2VDgwIxUFjfQqidDLbtgRXYqsZf9mjeDKI14NufuHLzPCmqPE+eduXvcHj6JXzzivNPelvPuupN3L6yOKKPgdO9FHVnFLKy/uaBizzzR04f864t123YkvlZV71pqBd52ovv2gntfbc7/v4lP/WOYz7//qvXgGNnrNzf6q2vPnf4+M46Ld/0Zu4A2DZynmyoA/PpTx87VfRY9fSnP/2uVzpNS4ceRCH0CoFIeaNcdhfKG2rlHxksWVazzmDPxHBwSqYk4Zqhspzj9XKsUqBGF2uZakRaLC+3Z5x4EWPJ6z5+rYIwZtSBMRJUYdfsFZqYXCMGCVIbKgseOoxonymRBXiywjG7XNilJa0LvATEwKJ9QdpwNDYAU3Haj6kfx8i1tgMUUmLTZAiahkYHRcjnEZ9V6d4Gbr0hr1m47RQBnU50Pya8FwKbGUc/M8YBpTEQYpP0yK5LCWyExKYZIvBHYGqsbNGpkstrBOse/kKIrYZYKZGJRuQGOcgQg2TUBSpBqjpyW5u1WUfXTxp4gbvuxmx2XTZW6ZQmzJ0OxkqGQMFKp/PAOOG+St0NttPMOGF91nATYMI6GpS1AlP8bPfXuTHZTldHRDLDF5qWrqCwXLt+Nrd3pqj7KTU/Ya1TZbrSJyRnetc63eUZ8qooMmBG3SChLUK67ofUFm8gSC0YI1lO6pxVW+EB0SHWdZWqdGYBZ1eWkMLQ1RGJ8fhWaw81L2U9qZDmil47QggLqSTvRVQPKaqHLVKD304RSYYJquQVZ6evQ4kX68L4wDllmjK/rDCbscUxGsVQS2Q8R4/OKwACLxLDUE9PuS6PSJ2VfxnYiWSYjlDGfY1n6FhZdGcy68xn2m5fQceZ2wgtsJ5P3nDb9HoS41u0b5CRxgioHZD4HTHUm44nI2zWqS0HPOaOWPZzD3zg2F93HahYghc4MfBw+8oiT7jiF4HjO4qV9Z3vvZ5LfuodfOd7rx8+Plb9JICX8TpR8LLR2hCAecYznnHE36Xj09HLwAVd3l/L+hIb+IgkHd5Mg3Y3yCVQGQ+yRA+7AyKskOyaJGsoF5xonUBeGIsaaFSiSeYq6Mi5j/ldd/MsQh8TeS4jBsirqrgxd0GSphah2t1RqKWSkOTYMHT7zXMn6s81AvA6CdV5hcw8sqp0g6eimGUqLv4+JJlylIHIudz0tyqsgOqSYeYHPbz9y0Otz7DLVJoZFPkvZUfIpsaBkPLz8b0R6MvyoT21paCiGQlBkSNjjWMxjAPBcr+FpsYaPerejJc2TgskxGg/JaAqhf1F98pKBTqFOEZ2XVAnUoIZdYlsXtLzTEFD22z535N1qrov5bbubUH/TyJ4KWsTpNz9slWN7YGOKLoFLvfEihFVSWg3wSQEhW2vHJqZ5DWLjix+lLNjpsWFU4eZC9r4Imctq3EgnqSiMn7QcsGw/Tzg9pVpNxfWhFbiAMQg90m1cmJ246hWeaG99AZuwsyJ1Qt6FYKwZchrku5yla+LPbz0fJcrEcmMVV2nbwL6JuARtZtpyJhvqzP5WnoO31/aTqtdQ/c8/EZKvxeh2p5zwUwdIPMGxtF2QzXMpDG+KBzXnL201EXuFw7MZBU3lqUTTjsjUzAhpE2L13POZl48Wl8lJVXsyO/E+NKBQhh238EZCAjjQEz5eeRVVdC6XSdHWIv2lculMRC0HL1NhwITOD2PXAhQA+deJoxxGTelWcPmcHLMuuKv38Vrf/0lJ/36DxcC/KNr11vuCFr++KFPBOBV3/6/w2XjnZeyBu86l+v+bD+XXpfc5f6/dfX7eLo9l60FiLmzKgHL8YALwJ9+8X9x6V1uaWP1rKvedLepaHenRgYA7vc3Lgx58ztWeOvrZ3j7c3/nbh/bhqJhjTHDny984QtcfPHFfO5zn2N9fZ319XU+97nP8dCHPpTPf/7zd+tg7usSxmImqm6mf8wq+IibayGPeA5ARBF62xTJpE+wnrt8k4Fz95KZa1cnMxF5VZHVHM/Y62usJ8knwqFVpAkk1nO5JOXFO91SGQn3Pc899oOhsN7m2t2EGwcWZLtPeLhNff+A6lLuOL+pm6UCJxSVqSWrwWCLpL/NDaq1ec3cN3tMfX0e77BrYQ51PbqgkBWdFKCge5nRemVXpKRzlWAjDCHwHfgZo3jZNHPL8nxkjCCkcxTzvJFVNbhte54Db+X+y2NR6siuS3lMnhpl9xgLWToS+scJNtfY/gCbZVhjhqYD7jg3R5p7uk4leDmZujvg441vec9PNHjZrFNUuXS6jLTQsRS0J+O7SaPSZrnsJOQVSTwhSRuCtAF53aKbGmuFcxcLWw4s9M7kh+3ttNMKS3Gdup9grCQziijIaNZiZip9Mi3ZPtWmlwYESpPmirxmHJAwkEfO6Uxol1HjHDENXmxQiSVoWfxVj14n4ob+dv6lcz4HsynWdZUJ1WfK69HRFZbyJofTSRb7DfpxiBAWEWqyVoi3t0K0LKjfDtVFZ9qiskIkXzIIcJbKQSdz9N5CG4R1WhVRgJC0IejuNqSTlrwK/W2GdGdKOuX+HswK8ooYUr2SpiStS+Ip5SYGcWO8SjReT+MNNH47xetmBK18FC4qXXAoxoEhK8Dv5cUxavyOJmxropYLIK0dNtT3Gxr73E910aBSh5JU5gwcvNj93qw71hUv+Ne79fpxqthd1au+/X+PAC/AHcALwC93n7ch8FLWU/5+/4bXvbP6jT3vOKH9Hq8e/s4f8/B3/hhwIOYbF4Z848LjuwQfoY+5B+vS6xI++9Q6l16XnBJgdcIi/le/+tX86Z/+KT/7sz87XPbEJz6RarXKS1/6Um644YY7efVpXgayZoBc8yFOihta3I1zno/E42NdGKEkZqbJYHuVcC1DphoTqCJPxStS5A0q1kXysUuZz2tewc212CLQ0pYuxBbUIHf2xjPOGWxoW4wagQGlnPVzAQCEdAOC6Mcobaj0U1RcI57xSIXE77t2uAtAczNxk3s1jb1dZKfvQjR10X0YF+6X+pWy1Ahc2Dx39C0ojkkOjwnPwzaqmChANwO07wCI18sR2iC7KSJOEL3B0EnMlk0WOQaWSq1LuQ8xsq8eivqFHR2vFKNuynhZ677kEqgMM38KcKbHtl/k2WzWsWv+8f+HbV/6Tyf8uvsauIzXyXRi7kng8p9f+qTjPvdX/+P+PTn077G8jsL6blbf+BSJ7qOgYJm6LkHZeQHXFUgmBcm5MRMTfbq9iKmJHlIYlrM6vtAYKzinvsRc0GE5qzPrd9kfT2MQ3MgcDT/Bk5pGmLKl0qUR+CS5R5L4sCMmW6qiMopQYYtM3JhV5l6Joqnvdy2NWwT5QsQ/7L/EvYftMY897yYafkxVphxOJzkcN/nx2hyD1GfrRIdDq01ohzRuU1QWnXjeuV0WVLWCxlVqXWTOcCw0kXQu/cZgQoWuSJKGJJ0QtB+cUZkeMFitkG6zhI2ELPHQFUPsOVpe3hCkA6f9VCl4PUvYBhMIVCqGGTOuK+ImC23gKGwyGxtDcB0hRDG0FB00od135ujgpYumGFLaVOKo3sYTSG2dy5oo6IGbtvynvJ7yme6G9C0nWqW18kZtlS+9LoE9rqvyrKvedFxB/9cn33xEdszXJ9/Mw55y9SkBLWV948KQV1/QBuDJTzwLgFc/7F/4g7/9Pv/0mNF6ta+8fLjf+7JLc3fqhE+pm2++mcnJyTssn5iY4LbbbjsFh3QfVnlTXN6QlxbKktFNe0FRGnZlopDBrgYycyFcAKqfYT1HFTO+QORFV6XIfXHtaYlREpVawtWsuPi5pHiZ5Oia79rppjiePAfGuhKeNwIv1rouSEmJkgqR5YgsJzDgtz3yeoCOlMtZ8QT1Q5ZgLcVfaDn61fAmvrAsLi/kQ3cxMbqpV8XjPHefg1ROp+J5iCAg2zNLZ08EwnV88orAFKJJHYBKfMdXFjVUDGHHEKznhPtWEd1+8VU4ADSkK44DC88bmRmMd8OUGs7oDelu5bISz+gRyBlm1yh1FDWQOz7erDvUiYKY0wm8lFUCkrsCMvcEcLkzwHJn626CmftH5TWNSiCddA5WzhrYARqZFzfCwrlcWeUse/OaIJkx1BoxvqeZmuixrd7hcK/JWbUVtJXsjlaH+5j1u7TyCpN+n4PxJDNRDyksuZHsqLVo+DErSY2ltEYUZWyfaLO/WsW0XRfG62rX4RCAEI4xYBy9zEpZUL7Ab8NgTjCoBPzLvrMIg5xcS6wVaC2pVRLixGffehW54jNxq6RxICdcyzBeEUZpQCXuOps1fDdRlxrUIC80n4EDNp5Ahz4qtnR2eiRTEG/TbN21RmcQsmPPCkpY1gcRnmegliKEJcsUSTskTxSqK9GRo5fpRUn9oHbUsriYNBQCWWhiEIVZgBSYQCBy93noUKASsMK6Mc9ap0+l/LwcCBoBluIpM6IHepkp9Eab02HHq139j3M4eskJ052e8pkub/3qr/EjfvauV74Xq3wP4yBm3G65fPzp71/JZy86PpXsROtZV72J+OLX8fIfH+JlT/znI577g7/9/jFfU3ZlLr0uuc/pZidTJwxgLr30Uq644go+/OEPs3XrVgAWFhZ47WtfyyMe8YhTfoD3ZrkOicUGHqK8QbbG3fyW+grjhPxWG4SnMPVqMRBkyNzRlayvHFiQAq+n3UDlufRllVpsXACZoee9QA1yZFqI+/uZa6FPhu4CW2ox8tx1YorMFUs2BB5WKYTW7rjGnLlkloOSqGWBDR31TJRdh7zIRBkGZY61uIc0KjPqQA11QGXeixiCFzwPs32a3u4qva2Omta8xbXOa4cy0klveFHPIwE4p7RoXZM2JPFkgNy5DZVaJn7UQq60XScoy8a+oLEvq+yI6ZJELkcgpDQbKLszMPoeoaCkhQ7klOBo/P2X7mrpqZsV+fdepyN4Ga9xgFKCmXuq23IiwOWuXr8JZk7fCmYGhBM5g70TjkqW25FNMAy7AVKDlpBXIW0CArrLNc46fz+e0EhhibwcTxqUMGTGwyBYTBsMdEDTGzDl99kZrdPVIctJHSMEsfbIbZVWWmFlvY5UBl9qhAYVF3knUmACl79iBc4YppjIc90EF2qsUohWLKDI23V6AZjAgrIEq5I4rVNdg6BjC3czpwM1yjEQkO6xDpXrNhWWyVYo8kiNXMeUYP0cj95uQ7CuGOzMQVqmt7dQ0nDO7Aq7quusplUunjnAQAfkVqKtYDmus1St0+mH5FMK2/fIhWIgJXlFUZ2XhB2Dip2+xu8WeW65cUOccuJ8N065jkwJNN2KOC2TKtYxhTFOQQ0UBT1QGDfOy9RiArcdkVhEcv/VB9+TVWpg9lVfwOR3v8f6xRs3jfrRwdMLvJT1ySt/nye8MOPT37+Sp190lQMrT60fBRLuPnj5xoUhl16X8E+/+QE4BBz6BDe9+8h1znvFHV9307vh4ouO3M7b7/bR3Pt1wgDmAx/4AM985jPZs2cPu3fvBmD//v2cd955fOpTnzrVx3fvVjF7b4VA+n6hi1Aj6+DyxhaKm+MAU/VRiaOHAUMxvg5dSGRWV45TPDBDMV+wliIHOTZU2OKiDjjqWapdIrFxHv2qn99Rg5LbUQdhvJQqsleMGyNL++EcB2yyfPQ+tR6K1IUsBq1xmtg4bSs3I/AipAMv5XakwNarDM6ZobPLp7JmCFsWHQqymiDogt9JUXFOMhMSTyrShhvEGwdyvCJMzIstSUOSTEkGW6aYvqFKtHfRcaDLAEtrCrAxdjy+N3qfwiu6KoW9tZAFKLHu/ZfdFsXoO1WjAfsOVLUxqtxm/fup+4omtlk/WdWopsw0Y/ZO1LCePxTv22J2XxjhboiF08joyOk3MAKkRWKZCgb0dMBU6DrTh9MJ5vwOsfFJjIcvHcDp64BZv0tXh8yGXX6wtoNeGmCsIMsVWkukMmRGFTQ2ik6EM47RgZtgo+hIyMQicos3MICzJPYGELZKDWIBwIRwXYmii6MD97xK7BCoCeMCKEu9j9QWawUy15iCOmc8Z5MsDMQzFjObMqgrwqmYapRy8ZZD/HBtK2fXl0mNxyXN/fhCs9Vv8e3uGTyoeojMKv5p7QF06yGZVuxfmySvS4yR9NsBeU3h9RW1g5agaxBGOdaEGBkrGE/gpS5iwJb5a4KxsbGg/yWueyML7arEDmngKnEAKa8WE5ShwBsYvP4mgDlW/eDaq+EDJ/46l/tyR/3K8eoa8ck7LHulfdZw+Svts45Yr/z7ZOs39rwDeAefBUqwcio6HKVe5ZNX/j7f/f57+adXwB895Zf4nc868FIClkee/zYAPvLuNx5zO3v/77eHj7/xuet48ot7vPLQB/j0Q2vcNn/d/aIbc8IA5txzz+X73/8+X/ziF/nRj34EwAUXXMAv/MIvHBHmeH8sdwESmMhDKQVpWlCnBNjihlcWLloUnQtfoUPlQE8RvJU1PZKmIq+41nF1ySKzwgrSgmgbN1hoiwkLO2XjKGgicxc5G3jub1MScMuuSe4oX4E/on0JCUmCHQu5tONUqTxH+P4oTwaO6LZYo53IfZyCVVK2xm/kSw0JuPWUgkaN1iVzZDVJfd6FcqZ1H7/jqHdWQjoVIrQlrTsus4rtkF6GsXg97cwLNFSXLXlF0t/qk1e3U79uAdvpFt0WRjbNRcdkqMExdvQdwREuaaiiSySk++zKz6UEo+V7LU0BshyrNXYYkLlZm3X3axO8/PsqX+Wc3Vjl8GyTZGqCyrLTSEBBM9IUtCSnm5AJyAyCszpM1fvsqa2SGI8zwlUG2scXmqqXspZXGegAXxgqKmU5rTPQPgvKZSaEKqfhJ0MqWdeG+EGO5xkOrTeHYMO5f8kh0JCpHQb6lnksOhBHdIrs2LghtR05qlmn93DAyGldkGA9gdViaFSAscM8Fus7EwEr3DjZPkNiAkhncyYn+/QGAdYKHrb1AJdNf489lT0YBLHxqcqUmwZzdHTErb0ZdobrSGHYGa2TBD7tPGRrtU03C6l6GT9c3sqaaiL3+8NOifWK4yoDLXVBERMl9ZvivZWuZUW3qqBDi2K8F9oO9TEqodDSWLx4ZAogtB3qnDbryPrz9zwKVYTBn0j3Zf+N/8w1Y7ecdwU4xp8vQco4qDka4GxU/3Jv1xs+/kcAPNk41HfTu+GZfIKbnsLwb4CbeCM3fKB2J+DwujssuendcAE9/uCaj8G7zqXy6r3HeN3pUyclKxNC8IQnPIEnPOH43s73x5JJjpK6EO+JIVVrSEUyRQaJYqidENogU+PsFCuS/hYP40G0btxFMLXOBrKu8Nv50JHM7+bITKO6KVZJZJJjKr4DMMWsj44UwVo8slAez1op/x43F4DR8Y7TwTxvRMWyY52boeWwN7q5LwFOcSPvtlmYBpQ3+KV1dLVC58Fb6M8ppm5KAWif4ZM2BPWDpgjOlENxqFUgcgdeolWDDgWy6Fg5WoPB72SEq+6i390dsvIz25n67jpifqk4LjmigsHIQrk4bmstxAlCKacN8jwHSKx1mQTlOplGjGfWjFPMpECgEJs5MHdaJyPi//dY9yRwOXrbm5Sy06d8adgSdHnglgW+M9EgD90EVmn3K3Jn0YsQzmBRO0H/A7cs4UmNsZIb1rbxs3M3szNcJ5QZkcgwTGKsIJQ57byCtgKJZSmpu65N2GeQ+1S8jCT30EYgBPhKs364STVzE0tWMOy6+B09CndUJSgBL3YaDpFbdCRRmR06l7l1HPVLe6KwIXbGAAAUYEj7EqmdWYBVrsuiK6VpgSCrOv2PiqF3Rs4FDzzAIPeR0hCnPtNBDwAlDGcEq1zbPofFpEEvD5iPHWg7nE6wnlXJCze2fu7zyKnbuLCyn9gE3Lj6JMRAYj1L2nD7krnE6zt6mVUjEx0bFtd9z0LuwFU5OenelxiGjgpAJGXgpXJi/tzNc1rA6zlGhfGkY05s1h1q9txtrB3oAiNK1Ebqine8m3e+/hUn1Ck5Vhfm/lYXvmQ3H3ml66rc8IEaAF9pX8LV/3v7Eev9zYs/e5fbevq3e0dQzsruzb/xRh77nhefmgO+B2tDAOaaa67hpS99KVEUcc0119zpuq985StPyYHdF5VNhsgUd4PuezCgAA1ylG8CBc1oNJsitYEEkimPPGLYTQDHHZa5m53KawqZuYHA77iLmsQNZGiLyDS6FoAQZHXP6WG6ydDda6hLscbZE5fgBY6kQYkxupfRI7oUuHyUPB3ZDxs7EryPdSBKrU/ZybBpiqCgX1mLiCLis2ZZP8cjWnWAK5ksku1tQYnwHH9aVyThmtu/rgiIi0FPQlZzRgYyc2YGZSfKhh7huqa73WPhZ6fY9mUNy+sje+ayu1K+h/L9YhC+08AMjRYKfVC5rii7R2NltSmoagWwORZFb7OOqJN1IrsnaqMZMD/p9Z9f+qRNEHOa1HK3xnpWxZMGExl0qFAZQ/2E9STWGifw9osOvbBIYZDCsq8/RTOMqaqUjo7Y7q/RVDEdE6GtZD2rcltvmqYf084i1uMKZ08skxnFIPeHx6GkxfdzpDR4LYXfY6jZsMLdiFvltBplV8IEo8kbB0oYCthlWmg9iq6LVWIYJumCHwWl97HQ7r1icdkvxQRWaXCjA2d3nNddByraMmA67LMvneKiLYc51Jtge7DOjfF2FtMGsfFJjcdA+6TaI1BuPNg/mAJgaVBnJuphrOQHnZ0sZ3Uyq4gzDxRkdYtMHX1Phy4LLeiZYRdFZk4Hq0PHkbPKjdO2GA/GPyv3BnHLcyCwyGy8eyXd52wgq0vE2mYH5lj13Iv2894D7vt7+Yt/AFecv6HXvfP17m77JwGUbKSu+LO/5J0vec4dwAvAY5rf4W9e/J0T2t7Tv907YjsXvLh3h/19pX0J39zg93Ff1IYAzNVXX80v//IvE0URV1999XHXE0LcrwGMkcKJ7bXFVCPEWuvIFbKxm3o7mkWzkfsY05p01o1td6EPW9pZZWrHJ04nPGRu8Nayok0tnRc+ICIPFefu4llRWM9lxYjewNHBpBiBmFLjIcvfYqTVGe+igLu598dskLO0uOEfUcRsbkf0P8XI1cy4Uc6mqQMFAEI4OtpEnfXzAqoLrtPSn/MRxhKuW4K2G/DiaUFegaCDs3CWYDoO1GUVQdixGN91X/yuRg0yB+S0Ltr8kmjdEE9J1i6eYfraBNsbjChkmmH+jAMgo86SLYX5jBzj7Fi+ixjPtDGj9z8EL0qB3qSQbdbdq/uCNrYJYk6PMkYwHzdYiWuIWk4y5SFzJ4Yf1424m+NCEK4Ft7em2NlsszXqcGnzViKR0tI1+iakb5xrUFWmLJgmZ9ZWMQi6eciZzVWMlaynFSajAQfbTQJPU/EztjfaJLlHvzdbOFHi9hmIEfXLuokkE7iOiFUOlPg9d72VSUGJUgJZdCZUbIcATBbgxQQO1AjtzGvIDeDo2dmkcuzrwIEelboxIKtBeobmQVuW+fHaFpLMYyFoMMh9EuPz5eXz6GcBce7x4Ol5+nlAqhWByql6GZP+ACkMgcxppxWawYCb1rdwc2sGKSxp6iEmUqS0xH6IyARZU5AvC8S8wIvd5yEz103xBhYduMgDYSwG9xnpyOmBTOA6NjI1CKkwvnQgRUMQ58Vn52hjxnOZOzLe1FQeq65Yfgvn8ccn/Lqnzuznd86Ex3xr9yk/ppnL1uDDp3yzd7uu+LO/5IajKGEl8LjhA7UjHt9Vffqhbv2JK34XgENXwKEA/kP6xiGV7AL+mfd+YONdsXu7NjQlcOuttzIzMzN8fLyfW2655YR2/va3v51LL72URqPB3Nwcz3jGM7jxxhuPWCeOYy6//HJmZmao1+s8+9nPZmFh4Yh19u3bx2WXXUa1WmVubo7Xvva15Eentm+gVGac7iQ3WF+N7JRhRN0ad7vKc2QvIat75FVF0DPU5nMqixlB2wVfqdTRuYRxgkjjCfJIkUz7ICCe8enuCujtjMgbATry0KFC5JZgsef2FfiIIEB4HqJZR1SriGYDppowNwPTk4haxdkqB74Luiw1IFKMWQvbkdZjTPMhlBy7adejXBcAa9xN/dC8wGKNIdneQOTgDxxFTgduMAq6mqBr8AaGypJB5hCuGfyuJmhravOaqR92mLglJlpJCdqORpE2PbKJ0PGmAw9d9Yac4WjNkEwIkjNnEYHv3mcZ6lkcWynQL7srIggQSrr3UnRqhJLDn+F3qZQDeIHvfhfbFL6PCI8f/HRv1ul2nozX/OP/z4bWuy86JH+854Jj/mzWT2adbufJ9sk2u6rr7Ky18KMcL3YaF6sEOnJ2wVhQA40XG/yexe9Cq1MlUhlnVFZoygEdU3E5MHmDjolYTJvcHk8DsC1sUVMJD2gssKeySs1LqPsJgczJtWK1XSPVismgz2K37uhbISRTgsGspL1bsX6uYv0cxWBa0ZvziCely6KZlKQ1MeoO4RorMnfjmYoNXjfDb2WogUEmBpkZ18Uo81IkmNABgVJbY/wROEII0klItuaccf48dT9hutJntt5jOuyzq77OYtrg3MYSShq21TpMBz12VdcJlGYq6DPpO6OD+bhJPw+ItcdyXGem0mem0qfupzRrMUJapiZ6iMkU61mymZxk1jKYkSRNR20b6mOEGJkaUFLtbEGZY0g3M76joOnIdZOM777beMojnlJkNbc8q0N3x+kBYE638+Sds2854dc86eMXA/cMeAFY+bupOywbD4c8HeuCF/e44QO1O4CXC17cu0N3paznX/M2fufM0d//IXXdnfNecaR72fvNSbgs3At1n0YrffnLX+byyy/n0ksvJc9z3vjGN/KEJzyBH/7wh9Rq7kt4zWtew9/93d/xV3/1V0xMTPCKV7yCZz3rWfzLv/wLAFprLrvsMrZt28bXvvY1Dh8+zAtf+EJ83+dtb3vbCR2PijVCepjIcWKVEO76JQUwRrkqdCDWWsQgQaWGtKEI1nO8fo4c5KAEKlDusedsKkXuwi1Nke+SVxRJU5LV3eyV3/OGTi7V+QTR6oKUiEoE1qIn62RTEXnVGQSkdYkXuxa91JagrQkXesj1LjZORsAFimR7PTp+Y123pqRSFYDGpgZR3thbM3LvKqlpQiKCgM6ugLwqSDPpOk25E+PLzDiZjSfxuwJ/4BGuZXidFBN6JNOBs60cZOT1gMGMKjjGIHOFMGExiyfx+zkqlehAErYF6+eFzB2uIlqdUUYPOIDiB8Nu1LBjNG5CUJodZOmRTnKlMQCMdEQUOpng9EgeO93Ok9OtjgZHdwVS/njPBbxq3/04cHezjlmn23kSeTnbgxaLcQMpLeGqddbFgiFwsZ4Ti3v9lKCuSJsCvR7Q3haxK1ilbSrcFs9irKCiMg4lkwDc3p0mUjmdPGR3ZY26SvjG2hlIYRnkPg0/Zqo6YD71UNKwvztFa/8EFQM6gmRa061pvEqO52sGvYDuQOF1FMa3hZsWBGsCqyRezNCEJlzPnWB9kKP6zspfDGm8TvTvRPyCvDJ20y4FNhcQMNTL6ECQbHGWy4F0IZ07qy3OqS5xdrjI/myaro6oq5iZLT0eEB1mRdcBaHguTPO2gZtcvXlthkaY0gxjOmnI7voay3GdVhIhhKVSSdlW7zAVDdgrtlCvx3RsHb/lI7UgS9w4L0uamxJDevMRZVynxjEohMuXSQy+NQgD/VmPwZwoxjT3eaST0Js8PTr6p9t5su2/fxMe9B9P6r08dWb/Xa7zmZUTBznjHZhLX/A4AK54jtMRf3DHxXz+ud/lYwev552vfwXf+PA/nvD2704dq+NS/n2sOpoiduiKse/nTPij2+6RwzzpuuRt3+Y7b3zohtYV1t410f+KK67Y8M7f+c53bnjdo2tpaYm5uTm+/OUv85jHPIZWq8WWLVv46Ec/yi/+4i8C8KMf/YgLLriAa6+9lp/+6Z/mc5/7HE996lM5dOjQMJfmT//0T3nd617H0tISQRDc5X7b7TYTExP8zM+/hTAbdR+CvYexg0ExUz/qQDCmoRBRiJms0z6/OQylVAP3j26lQGSFs5jE0cZCD131HXgpZmiMB34Pgo4hrwjq+xP8hTZikIDvoWcaJDMRadOJBEXBhHJBW46ilocChHsuaBuqB7rIhVVsrl3IpDYjrUtpTgBHhkIebRUNzuVLiCO7UdOTzD9+Dqldd8QKqCxnyEQPB7R8MiKeCbASqocTVC8lrwcO2LVTrC8ZbK/Q2ekNZ7SiNTtMMvYHBqHd8qCVoyPF+rk+s98buO/FmJEepnxP41ku5fdVmhqMg5ay+1TS7jzPWUkrBUpiqxH5VJXONHz9b99Eq9Wi2Wze5f/RvVX39Xly02M+RsOrAicm5L+nsmBKAHOy3ZV7Cszc165j9zSNbH7iegA6tst57UdunidFlefJ07/wIs7d0mUhaXBLa5b2F7YRtC1BxxJ0NEErI53wnY18XzPY4tPbLunuMdTPavHy879CS1f5x6XzsVawq7ZOJw+JVMbioEE/C2iGMQ9oLFBRGf84fx6XzBzEINgatPnC4QdyRmONWHsc6Eyy/oNZp185r8/uLWt4wtFuW0nEwuIE1UbCRHVA3U9ZiytkuaJ1YALVkwRrLtQx6Fgqy85m2O+6yTqRGXTNjQ8uz8XlvIjckjX8oXlLqf9MG2oY/jjYIujtMZh6ztlnLnJuc4kzolUaKqajIxazBqupu9Ysx3V+dee/cHs6y/54mim/j8RyY3crqVHcsLiVXZMtEu1AW81PWezVGaTu2Pr9kPO2LzId9vn2oV3kuSTrB4T7A4I21A8agpYbI3VFklUFYcsU1LiRtlPkthDtS7TvbKGBoTvZ0sWCbFuGP+/j9QTxnCHc0WPGW+baZ/zJ5nlSVHmefP4RB7nyuaMb8Y1qLt766nPvcp3PrOy+A8g5GtB85WHu+bKbM3PZGgC/f9UNvPkdKyz95dM2dDwzl63x+ed+d0Prnmhd8Wd/OXx8vG4KHBvE3Nn6J1J//YlrTun7e8pnnHHDL++d4Jdf7c67jx28ntuvejuvf+9HNnSebGiK+Tvf2Zg46O7aKLdaTnMyPe3a49/61rfIsoxf+IVfGK7zwAc+kD179gxPpGuvvZaHPOQhw5MI4IlPfCIvf/nLuf7667nkkks2vH+ZGYQ26MhzwnxwYvnSZrdMpAdHtfI80AbZ7lNZrtCfCwhlIc4sLJmFkkgJMs7dbFvmLJTzmrtAegOL33P0smRC4cUWrzUAY7DNGp0HTGI8gd/VeAMnNtSRxCioLOlhIBh2BGjyiqD1gCb1WoB/+xI2yxyIgdENvGJIubJ58b6U4GhWoSj/RYqujfAUphKAAK9fWmc6vrCMna20EzVatC+IpwR+x0NHCn89drxoX2F95QJACw61yBnadYbr7n2lDUXQdi4uOhL4Hctga0BwmzdmcS3HXOLsCN1BoRcq7HbKTowMRtbKUgIKwgAbBuiJCoMdFVYf4CEMJCqGv93wv8+9Vvf1eXKy9ey1T51yEHN3wUv52s2OzMarBC6ne50u58kDawt8ff8ZTCy5a13Q1fi9vBhrJP0tEpUorAC/a6nMS9oTNQ5nk9RVjLaSTCsW4obTc2h3Ta54GU0/RiM5HE9wycxBLqrvpyYTfhxv46e33MZDagf4xOGHs7JWR0pI96TMTfRY7tbY3mzzmNm9rOVV9uxZpaEGTKo+vsi5Md7BwWSSr3rnsLJWp9/wEbkgXFboQCEzSfN2i2eAwGL9QrCeuq6SUQJCQV5xgcWuk+E69U734gxe8qq79tdn+tT8FF8Ytvot9qUzfOHQA5m/dYbGjg5nT61yy9IMnwoeSj8PCFROXSVkVjEd9FnPKjxuz17OrizR0RH7BtMsxA2UNExUYtYHEfVazP71SbKmy8XJUw/pa6fzFG7sVKlBB8450xSBlV4vH9L9ShvltKGKHBwwxT1Bf06SNkBXDRecdYh9k1P01irs3LlKaxDRjqOT/E++Z+u+Pk/+22/8BTPVCgArh554Uu/heF2WjXRojkVDW/m7KX7zkkfDBsFL+ZpLX/A4rnjHu3nezgdv+HUbqXe+5Dlc8Wd/yfX1RfjAkdk3xwMoJaUMoH74kQB0t//bKT2uu1OffWqdrz66w75fgsG7zuWT3Er+ui8xnV501y8uakMA5h//8Z5vkRljePWrX83P/MzPcOGFFwIwPz9PEARMTk4ese7WrVuZn58frjN+EpXPl88dq5IkIUlGoqR2uw1AsNDF8yuYoIbXSrCmcKYqRfPjlCWlHL3KF5BmBPvXsHKaZNInaDvbSWEcZ1bkBlPx0ZEHShS5MYV1cOK4xFZCtJIRHWwj4pR8S5O1C1yrvH4wxSpBsJ4iU006GRa0MeP2U4CuvKpQsSGvKQbTksHWEJlOow4sMQyqNHJkHZxmbrZsvDtxdENOa0eVA9edMO5i7fecMN+JUB1lwIQKmbttmEDixYagK8nqri3vtxx3wgTOpGAwrRx4i81Q8CgzFwBW2nwiIKt5aF8M2/rlcbl/nMLiedxm2vMcVcwPjgynNHbkrgYO0AQ+2dYJWudVSZuOqxxvMVQPOtrE6Vanw3lyutSpAC9lbYKYu677C3CB0+M8WerXCQc+C7JBvq8GAhegmNsihV7g9Q1Bx4X+6tB1440PasXnH+fP54KpebZXW9S9lER7NPyYxbhBahSRl7IS14i1hxSW7VGL5azBQTtFXwf8VG0f/7h+ATfs3Qmege0xs9Nd2v2IKMio+wkNFXNuNE8kMjqmQmx85vUEfRNwXmWB9myFW8IZsi2KxVadVNeKschpPVz2SZFXZkCmxbU2UM5RLZPDdPoy/FJmljxy12CZgd+R9FoVbrEzrMcV1rMK59UWCZVGDSSdww069R4P2jbPzso6X50/h7lal2uXz2Iq7HPTyha0luycavHwxq1s9VtMeH1gF+txhTj3EICnDI0oITeSLPGwWtCYGpDYigsQFU7TYgKB9hm6p7k8MwdghLao3KISF/yZhxIdCPpbBfEWS97Q4Fmmwz5n717hK/JsdjXW6adb6OenhwZmvE6H8wRA1V8EwOyOn93wsb/5XXt50scv5lH/2uWdN3+aK855+l2+5q7oZF952H4e83d3T1fzzte/gktf8LhTTi37Yf3tPLj7Bp73rhfysVd/aLj8rqhj4IIqXdWOCXi+9Ct/zOM/+KojdC/AERbLp6K++ugOUXuWC1+ym/fd9hj4Ouz5xDov+syFXPbKdwHwBfGhO9/IWJ0eJH/g8ssv57rrruOf//mf7/F9vf3tb+etb33rHZaLNAMvcm5gvdjdvMPo5rgUxOdFIryxQAjGIHoDwttXYY8DMTKzBK0MjHM2s54km3DLs5q7kFXWtJvtCQWVQwPUeh8xSDBTddYuqOPFlnA9x4QSv50jkxyRG4JW6sT0UiC0Mx0wvnJ5NKG7+Q96DqS0zq0xYS3q4LJ7H6Vr2Xi3LM/vaNMMI5qcKEBAoRERaY7fKzIMwPG5M4Mc5JhAAS7csz+rqC3oof2mCT1UHCPjjGS2QnU5LwCYxRto0kmfeMp1oaLVHFNYesrcIrWbxdNj9p5DOl9ZJVApdS5GI5TvAGj5HXpjFstK0n3wHKsP8EhmLNXDEK5ZVCwJ1y0pR4G506BOh/PkvK88b8Pi/aPrVHRhxjUvp1KUvwlijl/3J/ACp8d5cmDvHIuJZW6yS7QsHe2qo4dZK0IbgtUYv6Pobwvp7FbkFefSWFkU7N8/QzOMmQwGTPs9EuUx0AHTQZ+FQYOd1RadLOKH89u4aMchDsaTaCtQwhLInPfd9hgWv7eVMBYkO1O2b29R81Meve1WAFbTKofTCbb66wBoK1jIp/jX9bPIjeSs2gqJUTxgYpFpv8d10Q6+H+8kI8DrCeeslVlUrJEDF8YsewkiVshQgSxDH2WhnykmysTYtVwUWpvbQ3o7JA/dvh8lLO08Yq7aYenMGlmm6Gc+ocoJZc75U4soYdkSdvn+8g66SzUwgkPC8veVB1HzEpbiOmuJo575SjMVDTAIal5KahT15oAk8YkT3wV0eqXlc8Em0KD6TtNilDMhwIIJnWbJ+K5j4/eNy3iRAl01nH3+PHHucXNrhgun5zl3epmfnrwFTxiySspN9/h/44nV6XCe/JdH/wc+8d0/B0Dc4dk7r88/97u8/jc/gL74r/hvvOCI574c3FGLc7yOzJvftZdLX/C4U2oK8BfvcvdPJT3qVNTTv93jwpfc+TH+aNtlPHD+745YdvjLbxt7DC9rvOqI589rvAqOAi/ghPzveMw1vP4rr4THnPxxl/VzX2vwjQtDvvmJ7/Aw4FuPeBUP+/ofc/lTr+O2s/8XAC9qvJz/zeUb2t5JAZhvfvObfOITn2Dfvn2kaXrEc5/85Il7cr/iFa/gM5/5DF/5ylfYtWvXcPm2bdtI05T19fUjZgMWFhbYtm3bcJ2vf/3rR2yvdMso1zm63vCGNxyh62m32+zevRsrpbMJzjRikAzByx3S3gu3LsBpZEp6VW9AeGAdmTWJZwMn2PcFwbp0QVlCYAurX+M5gaDf1UQLfdRqF3KNrVfon9HEH1iqhxzlSmba2QubQk+jLboRuhkt33UzspqHjiReTxfWlqq4IAv6u6o0ViNod4ob+JHFMHnulpV0q6NdRMr3qgq9iHX6mcGMs4yuLub4vdwdU835/FvlqAPppCDoSeLAdZxq82BFRNbwMaFwpgedxNHJcoNMFEFHIFOL18scMAsUedXD62mMUmQVMdK3lMcvxrpKpfOaNYAaWSeXgZnS8bNtvUr3gmkWLnWUN68rSCbB7wmCtiWrCjJ5opfTe7ZOl/Pk7lYJQE4GyNzTbmabIOaOdX8DL6fLeRIuKLItgsNLE9Qy13mwZZdY4JwRi3DHoJUTTLjZf5FDuG7J9wfcMjlDLUrJi5v/CX9AK6vgS82WoMMPs60k7ZBvZ3uYaPZ48Ow8B3qT7L15G+G8RzAQZE1L2ExYXK9z1pZVlpM6t7WnqQcJvjB8i7OoyhRfaK7r7OD6hW1YK7g9nGK6OiBUOZMTfc6sr/B9sws7mZG3QtKGAOEmzoS2yDQrbPtxYv4yGLOYZNKhPMLZy0rQQaErsSArOZP+gKYXcziewBOGn9p2iFh7LPQbZEaxt7eFuMi4ibXHWquGGChsPcdawXpa4bb2NMvtGnmuqFYTksRHTXaIc4/bWjN4vhu7gyCnFqas+TVUKkgbziK5zHmRuXW0clvk9hRUZwdyIGk6GrTxCwq0b3no9H5W0xo9HbCSVPmpiYPc0NtOO4vQ2eZ4cqzz5Kmfeh6fOPM1J/0+HvueF/Ph5//JHZ+YvevXXvvT9XtMt7Lzx+8vHp3aQMj//c1XcQmLRyyLPzTqtlzAJ4aP64cfSZd/4/EffNVxuyx3VrWvvJzX894hiPn8KXgv77zkgaxe9r948r86acq3HvEq/mLl1uHzzUc/Gf5sY9s64WSlj3/84zz60Y/mhhtu4G/+5m/Isozrr7+eL33pS0xMTJzQtqy1vOIVr+Bv/uZv+NKXvsRZZ511xPMPe9jD8H2ff/iHfxguu/HGG9m3bx+PetSjAHjUox7FD37wAxYXR1/oF7/4RZrNJg960IOOud8wDGk2m0f8AG7GKPKQ3QQbx0NqlVBFXkrqMlTsoOAWlTfNxU2/NQbR7hLctkTjRicEyyuSdMInryp0WLTdjSVsa8LVjOptLdShFUgzUJJ4ZxMs1A7GqEHmUpGtxUQe6UyVfKKCDRUmVHT3VEgnfdKGTzytGEw57Y1KnbA+aOd4iaG/RaGnakNnMacdKYCAkEfSxkprYiioWfpIGpa1iE6P2qIuRPaCrOqRzAQkUz7ppBOlWuUu+FnFtdfb50DrbJ9swkcUyc9eL3NgMTfoio+OlMuE6WTIforsJcjMoApvfuMJwraBJB11X8bBCxyR7YKxo46TNs5+WSns9ATLP72FQz+jCNYF1XlBddFSXbBFcrQgmYJ49vTowJxu58lNj/kYcGIC/mPViYKRE3Ubu6/r/p7FMj9x/f0KvJxu54mpWIRnsGsBauDyVJzI3bksGl9hqs5O3+vl1OZzvL67sbcSomVIb6+zfHiCb96+h3/7wbl8f2UH37ztDNbjCrf0Z2n1K2AEOlEoabmlNcvem7dRvdUnWBfkdUteteS5IusG3LIwy9f2ns38apN+FrA1bHNrb4Z/XDifzx9+ENctbcMYiTGCWpBhrOBga4KVrOZS7ztuzjOvOdpzVhUk0z6DbRG64mPqISby0TWfvOoPQUsZEAluzJC5xR9Ygg6kM5q8YjlvxyK7CwG/JzVSWGLtUfUyWv0KDT+mplIOdZssD2ocajfRbR+VCIRvMEawd3GW+ZUJstRjqtkn9Ny4dWB+ivV2FQvESxWyfTWsFUxX+sU/T5FH1soI2hqvbwiXE8L5Ll4nRSVuvJMFYyBa1QgD8ayguxuSKYusZVRVymzY5Ukz1yGFpW8CVpIaK4Mqs2H37v+Tn4I63c6TX56roeov4ld/7vEnDSY+9twXccvsHx/xs5H6/HO/y5M+fjHvNx/gpR98AS/94KiLM/53+fjode6sXtv5MK/tnLowmV/+zK+xvz2if8Ufqg1/jmWfDEdqXsbBy03vHv28r/PHx6WKvfOSBwK4DgzwjQvvXrTEkz5+MWuXiSF4Ga/py54FuI7cRuuEOzBve9vbuPrqq7n88stpNBr88R//MWeddRYve9nL2L59+wlt6/LLL+ejH/0o/+f//B8ajcaQOzkxMUGlUmFiYoJf+7Vf44orrmB6eppms8lv/dZv8ahHPYqf/umfBuAJT3gCD3rQg3jBC17AH/3RHzE/P8+VV17J5ZdfTniCOR6mGSENsN4uKEdljornAIYsAM34dq0tRP4Ccov1PESWwco6lTQjbFQxFQ8TOH2KSjSynyH7CaIfj8CDp0h3z5BMeQRtXQxwIcm0T7QiUN2UdCoga4aogU884xF0nPd+XlNYKUgnBFlHOUvljsbrZmQ19xUPtteoL6xjjXWdlNKBq7zhHwcqnjfWlSnepz+inVljqMzHdLfXQCiymtPEOOtNx4n2BgajnC2oisHrCWoLmmA9c0DFWESaYyIf6yt0RQ0TqmVuwLg8GDHIEJ5r32dVwcRtWfF5ee5YSwH/sEtUfGeeGHVnksQ953nobVMcfGyD/k5D9ZCksc+gMtdx8fuWcN2Br7wq4a6NVO6VOt3Ok1NZd9WNORbIOd2By09C3Z+AS1mn23mS1SxyLaR2QKHS0c27CUTRJRfIJEemunCqFNQPStJGoS1JoXGLREeSwVYP6pqltQbWQrsfcbuYwlfuBl30FEv7p/DXFI0lQdCypJOCrGGctiOTkEr0IMRWNVoLDi1PsjDR5GB3grqfsqe+xjfj3UTVmLVWjemoj0GgKxJjJStxDetbSCUqFuQ1ZxEcdBwwM5EbLKwnwYCQYzkq2iLL4EzfWQz7PUN1AQZzkmxKs7u2TiRyFvImS3Gdc+rLHBxMsjBoIKUh1j4V1eYXdtyILzXfWd/N7UA7qDE12aPVqmIyBakbp3VTkBuJ1hKbKHIrUEFhfLM1YdfkOtq4dWUGUuMYGAZH0VZiFDRtLN4gx0pBPOMTT0oGWwTJtMVsSZG+IYpSvrZ8Nuc1l/hubw/dLKQqUyKV0wgS5oLOyf5rn9I63c6T5yxez9/McbeE7599ap3P4m6wP/sLd2QJnHvmrey97Sye8veOQnbpdckwS+bZv+Ruzv/HrxwJNsb/Pvq5O6uXfvAFR6z/pI9ffEq6PN4fPp5vfO46LvknBxrHOynn0ePTDz0SxBxL63IsoPL4D77qDs+d9woHbAAO/+4j2f4H/8Y7HnMNn3/PiQdaPunjFw8B0P7PuGP6yFNHzz//MzD9VGf68J7vfI3Xf+3LG972CQOYm2++mcsuuwyAIAjo9XoIIXjNa17D4x//+GNyHI9X733vewF47GMfe8TyP//zP+dXf/VXAbj66quRUvLsZz+bJEl44hOfyHve857hukopPvOZz/Dyl7+cRz3qUdRqNX7lV36F3/u93zvRt4ZRErXYdinupc1unuMiegWCIvF9fMa/uAAOb5YL0TtSwVoL2eoipRgGLGKcyN2tI91P4KNnm/R2hMOBrrxI6kigEs/ZUKZOrC+0JegYvL7jHftdNxsUtnGBYplx4Zp1H5kZwpbr+hxBvYIjrYfHM27SrAh1HKOUCW/Y9RBC4C22wdbII6gsG/yuIZ1QhOsamRqsVPhdCjDgKBFq4ChwCshrHroWDJ1dhLbgC/KqRMUeInPUCnCARiWGoGsJ57vYvAAupbGCKAI6s9zR/Txv7P3gbJKjCFuvsHxxnd5uzcSPFLVFjdczeLHG77rulZ8bTOgSlb3TBMCcbucJ3P3uy9G10W7MJni55+v+CF7g9DtPrG/w1yXhmsUbuOt3OuERT0mqSxqvVzgyWhyAMdZ1zfuOepVXJd7ABSH6HYEOPXTo9HpxI2DgV1AdhZ8JvJ4DBV7fuUNaD+ItFm9ugM4U9UZMUvFQyo1dg16I0YIfrc+x0q5Rn0np5QE/s+NW9vWnmK70uWRyPytZjRvzrXz98B4ARDXH9j3yqkV3BXnVwgGXg5JHCooMNW+gkbmzWnaWw24CT2hBWpNuomugsU2JSgSZhR+sbOdhjdsAqHqu+zMZDEiNYutch9WkSmI8NJKHVW7jgugQ32qcyRd4IL1BiOk5pzSrLISGbi9CeQaljANwmUREGf5kjM4US70aa7dOUekLvAHO5dPYYZYZODCmKz55xUPFLq8mnpT0twqsD6ZqqDZjKkHG6nqN25IZMq342bmbeeDEApHMCGXOzmqLJoMT/h+6J+p0O0/AAZBTUZdel8B1e4d/lyL/Ery86coLhmDi88/97nEDGjfaZTkWsDl62crfTfH8hd/kI1vfc4d1T6TOfeJD+carP8R3HutcyHZ/24GBTz/0SNBywwdqPKz7X+jz/iNef94rRiDlrz9xDc/+pVcOf5d18UUv57vffy+Hf/eR8Hqnlbmp6OKcDAj7i3cpPowDQf/rq1864rmrrvp/Ro+/C+qjbTT/DzOP2XhY6IZyYMZr165dfO5zn+MhD3kIF110EW94wxt43vOex7XXXsuTnvSkoSXf/alKP/Jf2PZSVM4d81DKm2FrsFnukumP1kcME+5FQQdTIxBUvh5GTl9SDRPvzVST7vkTWAnhWo4a5Kw+qIoOnM1y2DGoxIke80g4q+W+we/nTlejBGnTwxu4Do/IDINtIV4hQoynFJWVnMreZWyvPzwWoSTDr7+kiJWOayW4KTsdhSi+fCyikOzsbaxcWCFas1QPJ+RVRbCWoKs+xhPkNYXMLO09HlYKJm7NCFdiTOgNbSnBzc5lDY9k0mlc6vM5fjfHeA54qV5G1gwwvqT2g0OO3neUVqcM3LTaOcfhey6oMwwdBbAS0X3wVg7/jEKmgpnrDX5Pk9YVQUePnHRwTmfxrM/KnpS9f/jG0863/76q8jy5r+reAi+nWgNzX+TBnCx97WTAy+maA3NfVXmenPfbb6PaDwlbrrNcXUxJmx6DaUVl1VGIhbGuA5NkrhtdzPhbKdBVD6PcpI5VhUOZEs710To5oimmIHWldPVyFsX97ZZ0NkdWc/wwp1mLOXNilVj7pNrdvA+SAM/TZJnHpbtup51W2FFtcXN7lnOayzyicQu+0Pzd8kXctLaFQeoz6AVYK7B9j8pBDytg6sdFfkqR/aIrEpkW5iyxdstCVYQ0S7K6RKWWpKnQIfS3CQY7cipzfZ52znXM+h1uH8zSzkOuW9rOVHWAFJaZqMfuyho3drby1Lnv05QDrhvs4t9WzqQVRyzfMg0WbOA6P6Lm3nuWeND2QQts0xnrIC1CWvwDIX7HsQQa+zXVwzFZw3d2z7FGJjm64pPVPaR2n+3Cw3x01e0jbxZsgapG9BRiOmX33BpP3n49y1md5bTOTetb2FZrs8PO8//93Kc2z5Oi7uvx5FjgpQQfZRdlo0DmWNsYr1PhSFZ2jMpuBhzZNRkPrKxe8+t8q/7R41osv/b7n+K/XfSMOyz/m8/+Eqb7s0NQU9ovb/+Df+Ox7zkx/cvHDl6P+auL+PC2h/DLn/k1/u6a/w7Abz/GdfzKTlnZFVMfbaP/S5OutjzuhvTU5cCM12Me8xi++MUv8pCHPIT//J//M6961av40pe+xBe/+EV+/ud//kQ3d1qVzTIQ/h3By1iJUiNiTSFY9EY3/2WVy4wTjDOI3XZKbUm5XWMwM5O0HjyJyix+1xQX+BAdCqZuSrFS0N7jITOIWoZozXnp++0UEyp3Yc0dBaqzyyfoeC58K3cX25JvrPq5y64RAkJ/1E0pgUBJGyv1MeVnkuej485GTmQ21/i3L1Gd20XakOQ1byi6t9K13kcuYhC2XRdFpi4rxiIQ1pI2fbKapLdV0r44wVsIqKxJN6OYuA6TCV2OTO2WdQdetHHHkWbDz1uUAFIb9/lLBaqgywU+2bZJFh/uYYXFqtLGU2F8Jy7NKxKpncg2WM/pb5HEO7JT9J+1WXe37s+dl7/6H5+/z0MtN+ver/ohS2ick6Qu8kO8gcGLnSuXCSReL3OZX4HnrovC0ZWcKN644Uc46pXMhDNyMQ4oACSTCuMJdOTATFYTDLYZmE1QytnfZ6nH7JYe7TRiMhyw1J9ittpnXxwigOlGj8P9CW5fmqIzG1LzU/754FnInZaalzAXdajMZty4PoevNFIaVpPRjWcyIUjrHsaDaN2J360UJA2JsD5+3xQ2xAWNTrmJuMEWgQ6dCN7rKAZU+cT6w9mxa5XIy6l4GdUgY30Qsd6qoXYYLmwc4rEzP2ZGdVnXVdq5y1aZigYsNzPswEPkbvyKqil5prC6MBMIDAwUIpPY0CB7bpwJ1yx+1wVCpxOu7a5DF1SpYoWOCiZAasAIjG/JJjXh9ABPS/RCBboe/rY+58wt8+iZWzgrXKSVV9getliK6vxwYRuH5GnS0t+sDXVeTgS8nAjF7ESrpKCVep3xOppGVgKa/ivfzwWMwMvFF70cgO9+33XfjgVegCPACzgNzV9/4ho+/57vntSxX/7Yy/j//unv4OGv5mkfgvP/bAQ5SuDym5c8GoD34UCM/NzvwOs2pmHaMIC57rrruPDCC3n3u99NHDsR++/+7u/i+z5f+9rXePazn82VV1650c2d/jUOYsruiZCAHj62NkdkuctJ8Y6ikomxv/3iYy67GiVAiEL6ZzXx+87FJZ5SSA1+VzNxa4bXyUBAdbm8gLqZPDUoLJy1C60UVpBMSudlb4tZOSGLcExJ0DVOVyKEO9aywxIG2GqErQToeogJJFnNw+trwvkOojcogi716PMYNuwMNsto/GiVtYtn6G3zqC7mCAtZQ5HW5bBbVFk1+F2n69EV3wn3pSBrelgJXmzImhK0QFccuAgF5HXfgaJQOrpcq4s92nCgBJJag/Jdt6UMtFTSCfeFoL8jwspSYyPII8cx9/uWtOGCQavL2on4I0llxSDaHgfugX+tzbp/1v/e975jLv/FPS+7l4/kzuv+bh7wk1IqcbP8LiDZARLricKat+hAF8n1VkmMX+gtMoPINTItBO9+kaWCu345Z8rCFl5QOHsJkDDYbpg8Z5V+HBJ3QlToaE8HWhPEsU+9muApQ81PqFcS6mHCVNhneVAnTz2MFXTSEGsFmZUcHExirOC8+iKtLGLNq+IJw6qeRAcumLO3E2RS7H/OUdmsB2nTErQFMnVuXSopc2CKDDFwwCu0yBRUXyLXFYeYZvfuFWp+ygVTC9ywtpV14NzGMr7QPLRyGz+Id3NdbwfXrW4n8nJ8pak1Y9LIIwwz4kHA9sk2h9YmyIzARgZVyzCpcsHNmcTvSMJVB16qS87S3/hixA6wOPMY3zlj6kiRTCjXfVGWi3ceZL7X5PbYQ0jLg7cfZn97iu96uzg3XKCqnLPbgycOE8ic/QunZ5DlZrnaaMflWOsd63XjoKYUv1963cY1JOPAZbzGKWNHVwlaSsAyXh979YeOADUA1Wt+ncsfexn/7aJnsHLtv/LY3Y+4Q+jlyep3PvjVX+b1ux/BOWd/FICbb/kv/PglbsK8XAbwnje+EPXRUSaQ+LkrgVMMYC666CIuvfRSXvKSl/Dc5z4XACklr3/9/8/em8dbctblvt93qGENe949prszEoYEJIQEApcDam4gB1CUK4oDXEQmBUQ8KshBjiIH9Xi4SPSiqIDguUQUnA6CyCCCAoEkTBkgczo9d+9hzVX1DvePt2rtvTvd6e6k01Pq+XzySe+1atWqqr3feut5n9/z/N50tLs49WEN6GicbOWNCQ/EWq+ULCkVXhcieC28W2n+XiVfKVY98LvgH7EuqDHWhrKmNGF07jw2FqQHCvJpjSo8ahQmOqBMq1GooRv3Q/EK8qmIqF92CR56ipYclw5Ew9DpWPcN0npMIyghQFBcoggijZts0j93gsG8QhZhFUyaEGtpWhp1YUzc9UzdMUDvWMDnOULroMisInZiscP0zZp9T55msE7T2l3gtKC/SaL7EHeDqR/C5OW1RBoXoqF9KHvT3YJ1BhayONRwDy2dbQnpssUkEcJ5mt87gK+aYKlV6lglfsXl780FL804FlpKfDNlOCcxFwxJkgL55SmEA5MIor4j6djQKHMV+Ys7Dj2sFZhTASdTfTkcaTnUNg9EZE4HFeZ09b6csvDh3uxVHFTw8j6OYOXhONHYhkIWLtz3y8bHwgcigw/pXWogsKW/xEUS01LjxpA2FrgI8klIt3aJlOOijbtYnm2w/cA0RabHnecXhxHnbd3H903toFukKOFYGLVQ0hElhlaUs31pmjQyRMJxTvMAkbA0VYbzgnPaC2RO8z3pkUZQNBzFnIXIMzPfZWmhjR8pSCwycgyndAjDKSR6WWFbDt2VNPYKTCuQGlEuXEHwTOIF2+9ax3DLEs+a+x7X7drG+rkOFzT3cF68l3uLWe7NZtk3ajMqAukqrGKyMSJuW3KraMYFj57ay6On9vK1Pdvoj2LyLIKOJuqFxb5030pDZlmEBqM21XixQhZVVrZLEOH3NZyXuPkRal/M1+8+m83zS2zetMiF0/tYn3T57r717O5PMqGGdG1KKguaMudJ09uxg/XccPL+GmsQiMTPX/K0+5GQj330Pcw9d2W79730w/zxky/j1V//2v32caxlZXPPXeSyD2e8+w0/y0f++Zdxfx06zV/4Z3r8QL8aH974eH5m97e58LdvgVJxWe3beemOi/mLL/4UL33G/wrnNG5SGcrILrv6Ym7/57V/aau3qbYDoP3/8d51F8MuuOWW8NreW77Dze13AvC43puP6VxX41lbL+dft1/Hs5o/OD5fgOl9bX7yqj9e2fCSp8H/WJkbz33b+Uf9HUdNYL7whS/wgQ98gF/+5V/ml37pl3jhC1/Iz/3cz/GMZzzjqL/stEH5YCwqpcSGVX7vPaLs43I/DwysjfMdP0iz0iCySsoC3EQLF0saezJsqsCD7jukDTfObFaH2tzcYRuSoiHQWai7VZknn9SkezOEDc209AhMGvoJ6IHFJpJ8Kvx6ZeGRgzyUKjQSis1THHhcitOCye1mRe530Npjw4SoBfmEYM9lbSY3pjTv6aMWOmHuXdX13luH3L/M/Dckey+bpL8pomiL0Jys69EjRzYVUnhUthKlaZpRWO1SAjWURD3DuhssXoXUG6/C+RRNwbqvLkKntxI4YKtmnKuULusIraDLJLWolOvLkjhpwHZi/LxBjyDpePBBfQn9eBymKSmaMvQkKDyiarxW46ThVCcvh9r+cETmRJCYWn05deB1SDSEsgeMEtgkLEQJt/JQjPO4SCIzu6LOez/u/aWMC72ybKlaNPRKWVNZguUSyC8YctnGXUxFQ9bFPTomJVGG2/as4+zZRfYlbTKjiKTl7uEcy6OU86YP0BGeff1goj4wbLJpskMvT5iOBmxLDgBw82AzxisSZbhs8i6+MX8W9r4p7FzB1s0L7F1us3GiS240A5mwfr7DII+YXjdiX6dN1o9xQ4lvG2wRMdgYGnZKBFEvBL3IPJx7e77P4O5J9t83zb2bZjl/dj9XzN5JU+Z8N9tE4TSFV2xpLjETD/nGvs3kKGJt2bkwhSkUUWzYP9liY9rBWEm7kbGQa3zs0UNBsgPSRYceeaK+RY5sqWTpscIVfkehlCyQS8hmQrqanbS0mxmFk7TjnCtnbubfO49iuKuNXS/5l+WLubc/g/GKps65eGInu/sTJ/Cvr8ahUJUrwYpCMvfcxfFrH/voezjwiRkAXv31ryHu2YU/e2267rGWi33qJ77Bu9/ws3zyqZfAFz/Hm7/3p+y48BWHJC8AP7P72wBrAgcqNeZrFydcVqa1vf3iJ3H7P9/Aze138tJn/K8xSan+f9nVFx+euJS47OqLD3kMj+u9mZvb7+RdP/fjx3Suq/F/fn2a7/zE0/hvn38nBz4xQxVhsLSux/9743+s+V0AXPNjrwbgv/7bbx/1dxw1gXnGM57BM57xDK655ho++tGP8sEPfpBnPvOZXHDBBbz85S/npS996WEbGJ02cD4Yv6EkGjaY9uM4kJfVJvEKZVnZWK2pypoORXCEDOb9Rkr/nMkyZcZgUxVKBByIzNHdFpNNCZp7BcmyZThXpmKNAiHAhzKn4aYUp4Lx32sJIpQomKYim9bokSPuBB8JDnyaMDx3hsF6TdwNtcrCgMAT911I5BqGUq/BOh2aqnkYzCvy9gTpQpPm9/ZDt1+qTWUcM6D2LLHhK55dz5hmuN7Tvg+SjqVoyTEhEtaRT0Z4HTNYp0g6IW7ZNFXpxwlkbTAf9tnalRHtXIaFJUQU4atAASjJICuksSQylZkfY4ICY0PTTi+hdZfG7pwcd1yusv+l8WQzCmlCh+hsShANRCCgNR6ROFbycvBnTwaJqcnLKQYR7ie6LBGWZWNhF4eSpEBkPKoKVXGhD5VXMqgWGpzQQbUuwgN2SGcU45blsiHBC4YbHBds3sfWxiJNlbMpWuLGfBuFVVijmE97LGcpo0LTyxNsQ2CdIJYGLR2tOGf/vgmacwWZ1Txqeh+RsNw23MBC3uKmhY1cOLOXvaM2+5MJYm3oNT1Raphv9NjXaZOqgtnWgOnmkMfOhKaGUjj2LD2KuJkzs2GJqWTEXc058n6M62iSfaHkTGUChMdF0NvTRmgP0vOJ717MRWft4nHpDhSef+hdwrQe0DcJkbQ0VEFc9nqJpKMYafxQk7mIG+65ENuyqOmcy8++h4l19/Hv952H/N5UmP8KjxoFf04xGYz7FaomlvlUhGlI0oHFW4804fcqRpKZ5pBzJg9wYWsv1gv2jtqIXCAEfHtxM+saPfb32uSR4i51FF0VazzsGFxzK83XPWbNaxVhWb1NhYO3PRhHo8Z87cOf5xnnztN6UYvme17Bjgsf4Phe/6c03/MKIBCZt1+c8L2fM/xUSWSqErSqJO3FZ1009sW8+N0vuZ/yspqgHExmLrt6rZJzMJm5+YtHPLUHxFs2fJp3XHsVr/56uL4/f8nT1hCXa37s1ahffwkA9r9/aPy5xT8bHfV3HLOJv9Vq8bKXvYyXvexl3H777XzgAx/gj/7oj3jrW9/Kc57zHP7hH/7hWHd5ysAbg9eljwJAKUTpX6lIyzjhqoolLuuPBQc1Vax6k2g9Th3Dh4dr127S36DwCmQRh4mrNDmO5iOWHwVF26GH4UG6sT9k+avMhXSvVJY/e5LlEKHsCc0hvRI4JcZN05wWZcyyI988ycJjI4SFuFOtChK6QC+Hm7fMDMJrGgcCobJlmVU0cCEl7EkbmPzuMvJAB4wZd7r3RYHct8TGL0v2XjYRTKpR6BOgR+WKowym08GGoPY095Vmz1mFSYNKIrwnXXS0tg/QOxfKYIUQX413K2pWlfJWxVgredB7qwITVFB0bBJKFtJFT96WxF1HshwIjknkeGW0uS88dBTHFtBX4zjjZKgvxyuB7IHUmONNYmricmrCU/UWIfQeqdZaytecFngR7oWiLD8WMqz6exGCUEI3+/I960Kz5SQo9l6G+7NpgG05+kUcmj+6iHW6S0MV7O21kdIxqTMi6Vg/0ePRU3sZ2og0Mty5PE8/i9kw0UUnloV+k14/ZWnQ4I50nkhZpuIh2yYXyZ0mlpb9RXt8gibT3Lp3A1OtIVo6NrY6pKpgS7rInnySpbyBtZKZyQFXbb6Vixr38b35TVx7+6UM+m1UEe7L4073DuQo9JGZ2talP4y5Y2GO2+Y3EgnL5mQJiYcY9uUT3La8jkEWM9Mcct/+aXweyteEAJ9JhBNl6ECT6+/birurxYZ7LHoYfhl6aEPAQiyRxoZSPhPK+FwkKdoKGzH2J8kCkrRgRMyBXpOXbvsyu4pprt11OYVTzD36AHF5ze5YnGfTRAfnBXd254BDr7jXOHE4HCGZe+7imMgcibSsxpHUmFf+xc/wp+793EDwm6wmKKsxeH2IPD74vUqluf4PfpVLf/H3xq9f9p2M3/n3V8LT38eztl4OcD/ycjBWKzIVWanIyz+86SfZ9MxfZ/1jQ/PSH3zVX/CpY/DrHArv2HMVxbmXcs25l45fsz/2aq4BXvfXfzwmL5Q/VwrM7y/ew/cf5XccM4FZjQsuuIBf//Vf5+yzz+bNb34zn/jEJx7K7k46RJIgKFWW6vnXsvKwTOhiK4qyhMmLFUWgIi9jw3/5/6qniqu2E9jJhKItiPqeoiWQRow7FS+fK2lt9yQdSJZN2fRr1WrdqJoFIV4yCBN+tmnwuqjMgRaIrDIgghoU+EjR3xSj+36sNBRNgbShjMs0FNEgDBY1CBHGjX2OYlITL4Usf5V5+hsVo+lp1t2gULsXwRf4vAieIUDt2M+mhR7D8+bonB1jmoJ0wREPHUVTUrTCMUVdT3+9QhVgGpQxlhnxfYuIrICiGJOXkDom10Ynlz13xj1s8lCeNyaaSga/TtmJs3HAYWNF3PHjmnEom2+OPDpzCANqZFFFuKYmrglMjYeGw6kxx4PE1MTl1IYIuSlhoUhQlrMGsiIzhx6EMJVxQpcM/67KbEVh8SYo16K8J8lRTuQ9+XSCbShG0xKvQfUkT5jbyRXt21myTeZUj1uXN9BMcn7y/K9xWeMuLp+YZVcxw6ZokW8PtnKg0eKexRmMlcwmA4r1C3RGKdZIlnZOsqQ90+u7PGXubpoq557hHAC3d9fRHyaYszIuPnsndy/OoKVj37AdAgGKNkp47u3NkCjDf77wJh7d3M358V4iYZjXXS6Y2883l1OcVjgNpuHRo9DDxaUO1Zcs3z0NMzlT7REfv+8SFvpNLpzfOy4bm0wz+nlMEhnuuW8eCkE8ndFMc7q9BrYZ5lxzoMG9N53N5H1Bia88SMIHYlIFLOAJKlkZtOO0wKlAEvEelTv0QFN4gbACKcPvaWc2za7OJKM84uy5BXYsTzHfCGbpA8MmsbL085iJaHAi//xqHITnXPtEtj/n1jWvVWTlYBXmeKH/xi+x4Vd+md6mr45JyqFIzOqfH3/OveN/f/vu0H/pV37wXCBEE//FF39qTFoq9cX99ROQP/atIx5PRVzuufsPOPuc0MDyH970kyw+V7DIO3nX07/xIM7y0HjLhk/zqR/6PS77mUPTEfmKXxz/+4+BAojuup7+2/4EfuJlR/UdD5rA/Nu//Rvvf//7+djHPoaUkhe96EW8/OUvf7C7OyXgTdU3RK15OPZlXO+a0jEYl5uNmyfCOCVLHKzEVKqAlMjcki54omEo8RrNavIJSd6WSAOtPY5kqUAYj2kG46YwLnhlCMqL02EylLnFNTQqcxQToRRLFm6cphL1DKo7It84QX+jZGK7RRW+XOWDbEIijULmHqclbiIOJvvSvCjKRpN6aIgERH1JPiHY9fRJNv2HQO08ML4+WBuM9kVB4ztD0u0TjLZOUUxqXBSiM10Umq3FvRBA0NydoRcHiP4QP8ogL8KEXqHqqVORl6rZppJgqiQeCdKF77cWUQYtICTeOTBhxa1oqzKoQKDyMJmpzOFiSX+Dor3T4pKw0qYKR9StTfyPJFTqy0MpHzsUHojEwLH1ialJy2kEv1IWNn5oNr5UVUD1yhVOEcz8VXwyqoyyryKTXWgAPEbphRHGgwzBK3bW0FIZ5+gD3Ooicq+YjEd8/7rv8czWrWxWGbNqwMAlFF6XTSIH7NKTnDW1jEOwOGiglcPnEtWX2ClLYRV3DubZ2ljksa1dFF7xzf2byRdS5rcuMRmNmG4En4uUjiXdAGD/oMVyr0EcG85pL7BoWtzmN9K1KV86cD6ZDfPlaN4hTejDIvOgPlFOnXogYJiwpB37+xEYwbdHZ6EjSzaI6MYNkjTco5PtMTbxqLkhmyY7LO2eYPKWCGlCeqcehhI+L4ICJvyK4iNcUP5lUYYsEAJ0kAJVeBCgB6G0Wo1CLLVLHY24YGt0ANuWLM03uLc7w4FBi0EvYU/aRisbPEFZTFZo9i3UZWQnEwc+MQPP2bPmtdXlYkdC83WPGW+/WqU5eB9vmHzH+N8f++h7eOnqfRxGfVn9ekVaVuPln3kt8bVP5MK/+QvYAP+6/brgldn4eM4+5xd58dPfx0d+7PBE5uDXK/IC8JEPfxMehhTo+e9/Gs+5Fp619VFrXv/YH98GsCYgYeLXXkT3d4Oxf9vCzqP+jmMiMDt37uSDH/wgH/zgB7n99tt52tOexnve8x5e9KIX0WodPtrtdIEQIpCSskTM+zK2sowfBsJDslLBYBlXy/h+bGpfTXJ8ZSwHRBSvlKaJYMiXxpNPKGwkKNphtcdpxmoMlARChgQa4X1pKhTj5DMXK/KJKMRqlnClD0YPHfrAEApD0da0dgXC5LUgm5LoLCSXZZOKdMFiqjQcE/bromCol1n4Xll4mnsNcU/SOVux70lt5iJJdM++lYSwsmTOFwUcWCRdWKaRxOU1XRVyUBITn+XhWkEgKZXSlRdjUjhOdKuISlW6V6ld0o1jravfUdjGgZOIvCBeyGns1yxdGGJIWztDiZuwHrRnogwzsMmKcV8MagWmxvHBkXwxpwI2Ll9UJ5EdR3gNVpf9Wywhyh5Qg1Cq5CM1VmBcEvpoSWwoHZMC4Uo1eVhG4AuBTxS2Efwa0lrUUGMa4aG/bxOuG507/v6ZeMAFyR62F3PsNI6+S7h5sJlEGgqvWMqbaGVZHDXY1OiwrtVnX78FRuI3ZEgBjbjgtoV5BpMx3zJn0dAFC8thrn/C/E52DSfp5xFSOppJQW4UoyzCGoUdKopY880Dm9nfbjGf9LmgsZfpeMidy3PgQsiBtyFO2TQdwgl0T4EDF/lw7e5p0OyEBp5DDyYJ/Vis8gzumSRalkS9cL3F9ZPs3TvB5o5D2hAhbRpVMAIgy5+FDNH+SiCdL9PdAolUQ4uQgexUvhjbCD16VOFhdwINh5KO6wbn89h0J+c0DzCymm/fdxYuCwuNkXQo4RlkDYadFL9Ql5CdbKwmF+/uvOWYP7+auEz82ovYs+W3Drtt1eW+x1fHrw1e/6c85R+evXbDfwBWqS4Vvn33Np75oSfxhZfcwGPEL/P23/4Dbv25b/Mzu+HRBz4ZNtr4q9xz9x/wO//+Si549pO47DsW3nARXyu9M1Xyl3zFL/OW0u9yz91/wJue/r5jPvdjhYk+wbO2Ppu5K556xFK7PVt+C66Bx//fV1OQH/V3HDWBufrqq/nMZz7D/Pw8L3nJS/jZn/1ZHv3oRx/1F50WUGq8+oNSQUUpzeGiLBUTjTQ8XKtVD7pxtKKylDHJGBPK0KrSMu8ACZEuV4E8umcRHhp7LChB0QzG+ahnwkpU9fyuQA+DEdQmoV+AGpUrckqw8BiNacLcTRZREqCob4NZPS9ASkbTarzCZ1pBiQjRy5AsufHqU9FW2IbERoK8LbEpNPc5ooFBlPHORVshy7+xA49vMifWE925O5AWWPGfeBd8MgBFMTbUj/vh6LK0TqzyD7nQkFJoXZIZtcpXJMM1rL4jFit9d7QOvtbVSXCVcpPl6M6I6dsUppEy2OgpWpBPSKSJUbljNKVCdKn1qFFQYIyqTfw1jh8eiMTUOPPgpcAkApULlC19LB50Lw+KigjNLJFBLRd25XOIsglwZvBSgvL4WOMSDapS2SWqCPH3aknzrQObeWxzF+t0h416mR+cvplzov18O9tC3yX0bMrQxhiv2JIsct9gmpl0SKoK9mVtjJfE2qJ6EjnlOGt+iX4eM5nk3LpzA2Z/io988KikjtuW13Hfrllk5Ng8v8TSMEUJT6uR0e01ghEf2LlrhoV2CykdnU2hF8owjxBRiIt2TUe8LpRXme0tZC7KMAOgCEpMY78vy4wVoDAp2CSiudeRLBcM1mka+yDuWuJlg4sk2YxCZaX6YkJoix5aionQ/NM0QsCMKH2U0gY/q6v6wAjC4p0M25o0zIvJfkE2F5pnLpsGfRezKV7mXj0bPpYpdu+coTE1YrI5CqVmhUDMPDRPQY2HhsE1t/LuzlvGJKTJA3tdHkidGVxzK7zuo7zhLwIhenfnLbxh8h28u/MWPvbR9wDBA3IDcPWT38snv/4arn7ye1n4jb/jqz/0z2MSc7DaUhGWZ37oSTyTJ7HwG3/HM3/rBcDn+auffxQb81Al8N25qwF41taXE33zP/jln/8OV130LuCNQGn2fwOM+0yU/plPcdGRL9RxwtKnZ/jwc/4ROv8I16y8Xl3/Q13fOybuwuZHT/SPmsBEUcTf/M3f8LznPQ+1uqP8mYbVJV+VQbx8KPY+dDau+r8AKx4MCP+X5XtViROUfg2HF2WDskGBHoYGjVHPhO70ShJhkIsW2wgrQU5K1MCghmVdtPe4KCZeDp9xcSgvS5Y9gy2e0bREWlBZMKS3dmYhOrndwDRADwWmpehuCV4Qkyi8XFFsnIbRrCSbDpNpPuWRVhD1JKkQwVvjPe17BzT3BBVqtD6huy1lenkauT/EEY57xYzjlm2ZGbqqIagq/UPj5p6sikSuksbK30fZwVhoFUhPda2rzxobzrP6Xa0KUxBRUMlEf0gUKSbuizANRf9ROWdv28+BfDPtHaGDdXOfLbtaS4RVeFvHKD9ScLzM+0fCiSQxg/s2ANDcsucIW66gVmGOH4QLPbnUyK9KIfMrizjlNpXvZU23ei3KxooKZcIiFCL4YbxWoSlwEgzmAHbGsLm9jBSOW0ab+Yo5n6dN3MY+O4H1kp4NxKFvYmbjAQeKFlJ4njh9H22VsWia3NLZSDdLsNOGx23eg3GSwioKq0jSAjcnsMsxui/Imx4lHd4EFSXRBu8FT9q4na/v3krayDGRIo4MeaGZaI7oj8J9PHch8lhHliJ2oD3NNMd7wbIGUVXuilCRIEwoL1N5SQCHIczGRSKY8b2nsWDC4p4W2IZaSZksS8XyhgyhB2lYmHM6lDEDFM2yHNt4nArVEcIGVSZUQ4BNynnRhH0KI9i+NM3/MXcH26IFbnINnjJ1FzvWTbEnnqCV5nQHyVitUhMFTXH06Uo1Hj6895zQ2+Q1d7/zsNsc6uF6dYLZGybfAX+xQlzeMPkOPvbR9/Bf3vODmC/9AABv+eh7eGFJkj720fdwNRGzv/UCmnffwGxJVGCFtBwKs7/1ggc8l//z69Pc6m/hqovexadveuMDn/gJxqd+4htcddG7eNmnVxQn99dPgEv3AvDu1/2n8etvuPTfwj8u3ctg5HnFXx3ddxw1gTmd08WOGqs9LtauTRWTK2Vb4/Sr1SljsKLMVI0vhVxpuliVmQkRVJFytR/ANXQoSSscxWQMzhP1C5QHm6iQPuNDCUK8lI27Nnstxn6RdI8Mdbwm+GOSZRu8JYXBphoERAMXVpxsmBgGWwVRB1q7LcISeqCU76FB5aKU8ksfTK88buMgUqBCCZbwgv75k0x0+8HHIg568C+bflblYuiSvFQEx5ZxzKsahnrrAlHUGtFIsfOT5LMpNpaYRqghjzvBp6RGFtUvkN0BojcIpXsVya5+p4VBdga07hEI1wIRs72zkVTDcD4oTbYTGnCaFqT7FfF9tQfmZOIX773lpPaBebjwcJGYirAczesPRGpqEnN8IDzoLNyfqkyXyr/iYhUWrnQZ/y4EskpR9GE7Lxj3gMG58J9SpSJQNbUsO9s3C546fRcAt3Q3srM3xdBGPKF9H6koSGRB5iLmkx4AS0WTkY04J91P4RUbomWk8AzNNuItC7zqrH/lxsE53DWYp/CS/UmbW5c3ofoSL2BmY4dYWtKpjCgKPpctrSV+YOYW+jbmns4MS70mW6eX2NObYHO7w24xwVLe4N6laYxROC8gdcglTbfX4NGb97A808SqiGhZ4hz4KEghOgstBNTIoTKHaalyHgyGelzwM+KDqqKHKwmd2bQibwvyyTBvmGa4zAME+aTHxR6fOORI4qUjWpakB4IfNer54JlxIfxFlWXlsoDe3hZ3bZ7naa3beGJ6D4+KhpyX7OGbg7PZEC3zLwuP47v711NYhZSOaLWPqcYJR/N1jxmTl9U4FKE5nMdl9b87f/wufpY5COFZvPBFr8e8KJCVZ229nBe+6PWlt+VJ/NnvRXzy668Zf/aTr2fNvysPzBdecgOD1//pmvevfvJ7AfiXWc2f/d6TxtvJH/sWv7L4b7z79nt56Su28ek3HNv1OBJ+9LpLAPj1f/zdw27zXy/61XGvmkPh0ze9Ea56Fz/wvvK6Xbbik3/hZSvbbSf4ZF74ox/jx5/1OODoMpwfUgrZGQdnQZZLWs4Hb0VlGvduRZ1xfmwWH5vMYaUPzOq0rFWrbVgbOtpHmng5p5iIEIVjuCFFjRxxp0AWDtUvUL0M14gQTgZ/S+kfEUiEDX6VbEqhitDLRQ/CTRUPgjK1bBgka5vqso+MI5sMEZxx12OaIqSSFR49tOQTMUnHk3Q83S3hQV7lgdA4LYLfZkpjUkn3bMncdwoQIclrOKdorp9Gbd/LuP+jKn0rzgbyUnlXrF25RpbxNsC4bExojUhTzJY5RvMp+aRED4Nnx+mwGudU6NUSggYUYjpBjiZRgxwxyBC9UJbgnUNICVmO2m9pGYcXkwirGM2FCVJaGM2Ec87mLcmCYrDhDFYaa4yxWn053gb+E4XDkZcjbX8s6kyNY4NTAudFiOAtY/DRMqgpsoxJrpLJTIjKF7ZUo6milV0oa5aE/1e+Px/uySLYQUB4ptSAdbrD5sYymxvL9E1CS2ZEwnJXto492STT0YA92URQYbIW+4sJejbh5s4mpHBI4Um0YUKOeGy6k2XTYH/e5onT9/Hdb2wj6pRNhp0ks5pmmrFposts3GdLvEgqCi6duoedvSmaacYFE/vY1lqkU6RcfdZ2buuvZ6ecJLMReEHSzsj7Ch1ZjJPEaUHW13hJ2WYgeFtMUqZ15qHsTthwDUKpWVCBZOZDX7FGiD92GqK+Kz8bIq2LNoG0rM+Cz8ULpHZEkcVawfTEEOsECzumSfZo8glBY2+oRHAxCB8WAKO+gH2aL95zHlvSRZ7cupPdNqclcjbHi0zIERM6Y77d57LZe7i9v45up/ZUnko4mMwcitwAvHSVDb/5useMe79MvvrQiod7+0t4001vBN7Hs6+9hmcSepysNuo/kOpSEZZPfv01YwL0hZfcwM/shi+8JHz2mR96El/8MXjFzH/ipsuW+KkXHF9yXJGXI+G3b/o9fvut8OS3X3XYbX7gfbeOjftHwguBP/vcd3jSUW1dE5g18DZEkqxpVinFSjyyYtzgUsjy0jl/v7IlYEVNkPHK69XDe5ajBgX9LSGxRQ9DzxZblnRFuR0n01BVXdkwmdm2Rg2KMjdfIAfBdJ8u+GDKVxANHcnOHowyUAo1Mtgkpb9Bo4cePQoRyoNNnuauUDJFWXPcn5fogcfF0NjjSZc8g/mw0pXNROVxCvpnW4SNmLwnqDcq94zWpzSX24gsx4+yoLpUq4pVmZ3zwbUp5ErzzwpVOZ7WMD3J4JxphPVEPYMeCnS/wDY0RVuHCct6KDyqjH/2OvRIsI0mzDXRvRaqO0IsdVcCBAzIzoD2bZ5ksUl3W0I2DUULIuOJFwWNPZKo71laf1z/vGrUOO44VuJyuM8fTGQ2Loda6VqJefCQ1ocq11KpHsM4hF9R+4VxoVVMZhCFRVYmfusQWejh5WVQ2BmVc0WconKHyiReeopezH35LJEwbEsWWDAtEmlIRcHIR9zZn8ch2JwukTtN7jR9EzNwoXdMqgtyG1SRqXhIjCWVOWcli7RVxrc7m4mXZEhPG0DvninmHjfgiet28qTJexi4mK3xAc6L9jPyEedP7ec7+zexkDdxXjIb93ne5Df4drKFx7R386mdj6OfxTSTnJ0HGphCsaszuSKYz4QHMjmsYpbLKoBEEA09MvdEPVuGIIRkTjW0od+O0ggnMIkinwjzi2kI+ps9fuOIpFFw3vwBZpM+kXBMRwMWihZaOCb1kLbO+KR8HIuTLbLlGK/DfFNVJ7go9FFTI0Hm2nzYXM6/rb+AK+bvYltygIGLeVS8m+fOfpMDk22e2riLf00uZBgbPn2i/vhqHBKvufud/O1NQYX8kYtCP6ODicvBpWUH94V530s/vOYzN/7mfWve//RNb+R3/v2V/Ov26/jUT7wOnrQiNTzzQysKyuFQvbdalak+u/pzj/rjHQDc9uqzeM61T3xAJeRYcDTKy8H4+ls/fT81pipre9PT38f/erfiJ7f9xhH3c/unjxwFvRo1gVmFKvWqSh0TOgplTtaGn60NHpdx+pVYeTAvI3yrZorCFWWKWba28WW5regNiTstiglF3LGogcGmimJCI3wDNTTIoQnJY1FInlGDHNUPZVjCe5JFg8odqQwTpIsESkDznj6y2w/KAyAHOcJ6RnOC1s5QG2xTSPcJJrbboKDMhiCAirwM1weTaNz1pEsOPXTI3JUGU2jdo4O87kB6j0kloxlF2kpReVGmuNmVtLAq6ADKNLHSqG9tGYHM2IzP7BT9C2ZwkaC5c1gmoIV9iUgRdU0oXTMuTOqUDwHDAq8EthGNVRm3vk0kBGKxEyKVq2sCxFnO7GKCa0T0z2pQtAJxaew3LF4Ykc+tIqQ1Tgoe7jKyE+V9ORjHo4zsoZKXQ+3rUESmJjEPDjL3SBl8L8JTejIqBcWXqWMlbPDG+NLr4pUcJ1F6KcODuZAhSMX7UEal1LivSbQ/4vN7LmSwLubCdDdNmXFXto47s/V8q3sWdyzO004yWiont4qFvInE07MJ3SJlNh4QS8M3Ri3mkgF3F/N0XIPz4r38TefJ3PCN85m9zzNaFxTvibske7e0mYiDyt+UOVv1Agu2yYJpc3d3llacsyHp8qU95+EmBZ/sPoELkj1sipaYTEa044wDgxbtjT2euvke+ibm9qV5xDpPnmvsQGNaAqkkphWilpMlhx64cO3MCikMKkyZYCkFMi/9La3Q2Ll7nqN5/jKzzSH/x/o7mNV9duVTrI87RMKipSNzmrYO53PhzD5uMoqlgWa4pUC1DTZTRLsj0v1B+fKC4E/9bpP77mjwv9ZvIJ0dsWGqy7qzu0yrPo9KdvPPvYv41wMXso0dD/efXI0HwNc+/Hmec+0TefY14R53uIaVhyI0D0hyXnp/z8zBKV8V8TgUcalIzZrPfzKQnt+5+mvjz/zlNZew9Ws3rCI0b+HnfrWAL8Kztl7Ob7/19x5QCXkgPOfaJ9I879ChRf/9+b92VGTmt2/6PdxFoVHmp296I/KtH4KfCO/91BssP8XbAPAf/83D7uOC976eL3zlCfB7P3JUx10TmFXwxuCFDA+5SuGHI5AyqASFDWKIXSXVGb8S9StDLZUQItQpG7NChAoTlJsqOtgXiFFOsmeAi1ph5UgIhutC+VrUDxOYTxRikCMyh+6HfiZohWvGeBmaVnq5klrmpQqhAN0BZHkgVc4jl/u09k6x3ApJW3HPkSnJ7D0F6d4h+XRCPhEjcygmwopW1AvNxbyC1s5ipQEYkE2EFDI9CJO0i0JfFdMQmOkE2RuWjSRXEYAyZrlSt3w1+Ti3omZJARMtBudOowcW3S+QwwKsx7XLcx6Zsv8LYZL3IHIzri2XhV9ZtdSSYraJmWogGxFqfwc/GIWQgdKvJHoDZBwxtWsRN92mmGlQtDXxsmdiUJv4z2QcTF5Op/Kx40leDt7v4dQYqBWZY4GoSr88Y5+k0xKZqLAoI1ZHJns8qlyIkuN4ZSEJsf1lbxgfa1ysgmE9FtiEcP8dwd5Om2i9Zb+ZoPCKpszp2YRekZAZxXJ3GoBhEdGICvp5zO7RJBM6Yzbq07MJW9pLPH3qNvouQeH4YvfRfPGmC5m5OSSeCROUei+hmRTE0qBwnBPv54Bt0XUNduVT9POYi+Z286U95/GfNt5B16RYL9lezJK5iOl4SKIMy1lKQ3ieM/NtNuol7phbz8Al/O2uS7hr3yxuuYlrOExazjlDH7yYQoRraz1qZNYEIVSNmfPJsNi2fKHlcU+4l+l4SO4UPZuwVDRD75uiRVtlLBUNukXKfW4aKTwjG1FYhWpYotjQSHLyhqZvBFEvwmtwqoxudpDuFzR3R0Q9zZ6zJ/hTnoEQnok4484Dc8y3++wTEyfpL7HGavzF//yL8I9zjm77957z5gc0/MMKGfrahz8/fq1SRfa89PvB33BIolLhYGJz9UcqwrPy2ncu0GwtW6dU+5r//qex//P/AcCll3z56E7oUMd/CPLy35//a4f89+Hw6//4u/z3H724/OldUJbOAWsUIvGjbxu/ftuG0Bz3gve+nutvvIJLL/kykx/42aM+buHHDU4eueh0OkxNTfGD0z+DFvHKQ7b3a3rAjP/tXKhjdg4RaXxhwv+r0jN5aCa7JuFMa0SaUGyZw7R0WCXapok7nuaeIkRtekJXeinDQ7r3gbwoST6bUrQleuCwSSgviJcN8X1LsNQN31ceh9Ca/LwNDNfHRD077u0SL+cgBMVENG40OfZ9OHBx6FKfLIfzTxeDCjLYEJFPhqjL1p6wIihNSHNRBUzc1kXt2h/Kx4wpE9nMyvkLuTZ2ujrOVov8gg3YSKIHBr00DGVhzRibarwSIT7a+RBsUF3WXhZWL1XolePSVby8rElwsUL1c+TexRD3XH03jMv/RBRBmgDg44gicnzu27/H8vIyk5OTD/XP7LRHNU5OBh4OFeZQ6suJJjEPVoV5uAhMhaPxxuyeumkNuanHSUA1Ti5//tuJdBLUAF+WlNlQ8iqsQxRu7G0RVYmrEGW6pAyqsw3NKpHBPI8UuEhhmgqbSgbzYVEqmxH0zrU85qLtnNVc5u7eLI+a3If1goYq+Nq+bRRWYZ1AChhkEUlk6PVTLty0F+cFsbTcsRAets+ZWEDi+dy3HsvUtyP0KJyDaQqymeBNGZyXc8G5e3j11i+wTnf4dOfx7BhN01I5tyxv4NFTe7mjM8+zN9zM49IdHLBtvjXYyh29efYOJtjSXuK2xXV0+imXbb2Xq+e+TbdMS7t1uIlbljbyvXs2IqQnui8mPSCYutOQLBU4LcdleWpQlItZgcDk0zFFWzGaFhQTgu5jCs7aeoBHTe/jtqV1GCe5aHY3WlqMU2hp2Tdqs3cwQW4Vi8stTKZQByJkIXCRx6UerzwkjmhvRLRcepdcIDLpgkcPQI+C4jZYpzDtkOSZbygQmcJ3M+79tf9aj5MSJ2s+uexnvp/z/+BOLrv2yITy2i+vO2JqWeWJeYVc++B9/R/8Km/Z8GmetfVyALZ+7c/v99mDSU2lvAC87Qkhiqtx1nnACsn55IvvP2dcfLth69f+nA9vfPyDKiX76T0/z+CeB0+AVuNgtaYqLXugpLSKyLzuD7aS/7cX8blbf/2oxkmtwKyGkKHcyblQ9mVXiEvVqBIIhEKIoMi4Ff63Jl5ZqRV/TIXqgdmVZVXGovcs47bOYJqaie0mGBNlSCaTQ4NrJciRCalf3uNijWlp8slQG4wPDbmiToHe14Fuv/wOSzDtAM6hRoZ8Ig1JLsPQ80WURCBesNhmRNGMibqh1GzivlBrbVLBcJ0cdy+OO5akYxms1xQTkC4QUsZ8iAzNpiXynDaT+5bAF2VKmwv/r0hHVZIHK+V1WmM3zrB8TorOPO3tFh+HhDfTCtHHNhFIq0L9c6dAZRYxLMZlfiL8soLZVa9M+DiPzC22nYCdRi51Q3+a1QQqd3hhYTAMv+9OFyHrErIzESerbOx44eEmL0eL1eSlxiEgQrqYcH7cILGqGRPWIbMiKDOFCQtiOjS2DJuU5bfeI/IQ6UusoXBI55GRxFURyknwZ6R7FLdEZ5Gdr7loehcXt3bwjd42hjZiodtCa4sUnvl2n+nGkIloxHY5Q2EVm1vLWC+IlGXH/mnuvmMD0YJiapdAD0olfq/FxgKnFQho3hlzV2Oe7lkp+0YT3LC4Fesk6xo99vdaXDRtuXR2pUHfo+Ld7CymWYhbHBi1uHN5jkfP7uVuPcu3925iMhoh8czFPeajHjPpgPn1HZyH7q650Og5CgtSNpbEy3loAhpXDUHBNHTZ3yVcEzWCaJ9mh5hlOh2ye2ESAej5QF4cgu39GXp5QmY0o0JjlmKECaEBYS72+CT87qbnenSiBqaRoAeCeEmQLIaKBVVUsdmOmeUw1zslyKfK0vQlx/3bFdY40Zi54flcdu37D/netV9ed8jXH0iBed9LP7xGeanwL09egu3w6alL2Lzu23znghXicfVHDr1Q9jtXr3Sn56zzeNMnLxu/VpGdZ35oZZu/vCb4Vb5zgeanX/ckeMkNHEtb5EoZqVScw5WRHQsOVmuaZenOA8U8P2rPgfCPnzgAfOOov6smMKthLb4yWwqJED48aCs5JiqVuX+cQiYFQsUr+3DhM5SqDEqFCWp175yysaXPMoRzxHtjhGmSzZYzUjmFCaOwqULmBhyhHKqlyCYVKve0d+WoXo5a6oXysqLAV4SqTEtDa5ASudgD36a/XpMuB3LiVZn+VSogXoWoZWlEqDN2HpWFGuJ8UtA7SxK3wsqT14HQSAMIsJEg7jkGsaC7VdG+cxKx+0AoJfNihSgUq66jLUlWHCGiiHyugbSBNPU3JzT3huae+VS4djYO34GvasrLc9UqqDzWIYoCKQQ2ipGZGfeK8VoiBwV2MkF4j1hYXom6rsIDvAtEpvIqrU6Tq3FScTy8MEdDXCpF5EQpMSejuWWlrjwQEapTyo4DymaIQLmYsuotJcMCjSlV+/IeRRnOggMihShCt3jhfXhQX7VPNbKoQoEMnkY1AjlQWCeZi/rcm80xoUfc1l1HHBmGwxjnBXmh2TyzTO40Z08tMBWN2NJYpHCKhckWt9wxw8R9kmTBE/cdJhXkqaBohv5i6YJnOB/SuOxIcftoA02Z871d6xFA46yCwihu765jU6NDU+V8tX8+lzTvpilzLmztxnhJ38RI4TBOMtMcMrQRuwaTzM31KLzins4MQnim04ylxGMbgqIh0c2SEJhA5rwU+EjhEQjjsLFiOC8pJmA07/CppTE9YmgibC8insq4pzfLY6b2kDvNfNpjaCIGWcRgoYkoQoSyF2AmLHKyYH6mx6jQ5TNBOHdfJnDKKhpbgQh9RgOcx8dy3EvGrw5yqHHS8Omb3sizuZhn7nrXmte/sOmN/MQV+w5JYlZ7YFaTmbnnLh5W8ah8MD963fvY+wM/w/rP3X6/bQ5n5l+tsqxWZQ6Hqz/yJ7zkQ3/Iyz9z+HCAQ6F5nliTOLbUfCUA04P3He4jDwrHM2RgNWoCswreWkCOlRRfKSZVPHLV0LJcMfPWIlBr45alQFAmaZUP1UHNWVU6FelxrxRvLOLAEnF/iOpNYKYSTCs0Kiu0xCYCFzXRfUM+rYmXDI0d/RATXKkt3q+Ua1VKUdWLxTv8aIQQgvaOnMULE1iCoiFRbY0eCWQWYpmdFthYjHvURD2D1wLdtww2RvS2SPIpQbzsSfd5ooEn7lm8EJimRBhP3AkKTjHbIFlOg4/oICIwJoUVqTMGP9HCxpJkyeHiEEpQBQaozFO0wmvZpKTds8jcIozDpxonBXJUrJT4GYtaHuKT8s/begQOrEdKKGYaRFkOiznYssStaooJ4XemVxS4GqcGKgJyLETmwaot/9e2V51WnphjQeVzaW7Zc0Q151CemBpHiYq8KMCHxRhZOHRRBr0U4d7pS3U9+Dp8IC+VIV2FNMpqwcm0QiKWjeVKXL0L6Vg2CclYezttvhqdw3za43uL67FO0kxyer0UISAbRtydzaG0ZeNMlx1uii/edT7FckKyVzG5RxD1POmSDefgRSjZcqFEysY+NEVughgqvr6wjbPbC0jpKHoxdyyEcpCzmstc1N7BhByhhGOfmWTgYmZVn/m4xzOnd3BPNk8iLRc09/J9jXv5+uBcrJdM6QEz6RApfOgXU5baeQU2lWWoTKlSRQonwDYU+YRisFEyXO/xZw958rbtzCd9NidL3LC0lc3bDrDUb5DZkMQGMBsP2CGmKXIdviO1uFxC7CF1zM30OG/6APNxn0k95OOj7yObkqhmQeYkxfaU1vYQ1exGApNKdOaDIpQEw78qPN7UnsqTjR+97hI+fvmNvHHjj3H9rrXvVYTmWlYIyuH6xozN8h8+8nd+/PIb+dHrAK4Yv3ZwGdjBiszqn6ttf/XLbzn8l5zzFiD0anwoTS0fCnG5vAhE67roa/d/fSs8698vv1+4wUNFTWBWo+wI761lZXZYISzAqi7xFblZITbj1ypFI8sDGZIKpBo3ufRFsbK9dXgvoVsge32SvQlJHOF1UCbGx1UY4h0OhqOQplWWYY1RlblVykt1XJZS7clJ710iOitkA8c9F7LyI4lKVOg1Q+hG7IXANiTJooUsrAymC2FVysYQ9UMKjh7aYDjFI4uQChMNHEVbMlwXk9wt1pKXUp0aR1SvvoZSoocW4TwFOqSMFQ4ZSYpWSJ9JFkPJgG0oTCsi2l8gXLmC6cDFGjXMwrUDRGZAB8OsMA4zleKjkji2G4jlHjiz9hgrklnjlMWhSElFak738rAj4VQpH6txZAjrEdIjysASYT2yXJgRgGuU93chQjCJEmNTfyiFDU0UgbHvJZtS4R4ty47w1kMSSp2EhXhZYG6e4HuNCW5dlyOUG69lKW2R0pP1U7wTOKXZdU8LPRA0lmCqG0rFZB6i9qXx2Dh8OMTvO2wiyCcENgU9BDWQLAybnN1e4HGb9nDHwhz9bkqUGKRwLJsme90k6+MOd4/m6ZuEvomZjod0bYNZ3SeLNecme7l5dBbLpoEUnizXdLIULR3NKMdNGPxijFOMI/9tMwpl1onGaxlInSrVEQk6suwdTHDl3C20ZMZyu8HAxLSjnLm0jxaW9XGX7/XX04pyTKZBe0RfITMJ0uOtZr+awHuBmxa0dIYQIFQgVt4x7kmjRiVZFWBSsZI+R1BnXPLQy3NqPDR8/PIbgbVG8q+/dW249WrPS5XA9WDTvWAllvjqj/wJn3zxq7j6I38yLgd70ycvux95qbY5mOT83hXvAFbKzBZ+4+/G783+1gv4EMH0f6zk5YX/8S22r2oweTBWE5LLi8vuR1BWb3d5cdmYyJwI1CZ+Vpn4J386mPhXX5LKXAlj437173E5mfcr/peKPJRNG0W7hV0/jWlHYSIrSwWE94jcoTsjxHIvkBrnVxo6QiA+43+LVeTJrag7sNKHZhUhGPdYKaOJq34rdtM8vfND/rmXgrwliPueZMkwmtEM54M5cvJeQ9Q3uNIcubpxWvDOhBhQ29CoocE2g8k+m1L0tih037PhC/vgwOKKgb/yBFVlbpUCE0e4zevon9Mm6hpU4XBaBsM+If8fQGYW1c+x7QQXSXQ3Qw7yUD4nJb4RI7IilGasMr/iPT7WZUPPEMGJFOg9y/ilzsq1VQqfF+Pfq1GOzy58sDZdlni4TZdPL7LDvvfvUfKwfe/hcCIVmKMtIzsZBOZoFZh6nARU4+SpV/8WOkrH6ViyKp8t0xm9CpHEwnikDYmSTglMK5CU1fdbG0uyqeDrs2mIBxalX1K4smO8CSZ7F4UGxJWSbtOQVmZaofNj1CvLzYxHD0MplHCMPTUQSoNVFgiNL++HlSfSpqGZsGmG7XoXFDTmhjxj2x382z0XMNrfQFjBuY/ZxRNn7sMiuW8wza7+JPuX2yGdq5lx8fwuNiXLdEyDyyfu4FMHHs9ti+tItOEp6+7mX3dewMLOqUAqIkd8V0p7e4j194LQRiBzYUGrKclboV+ZacBwgyA/f8i2jQtcPn8PE2rEzd1N7BlOYJ1kOhmyodFhaCPu7gTFaPud61ADiczCNfRRUMNcw4GH5oY+l591L7sGk9yxex06suQjjdyZ0tgbmkIjyrJqt6rEugxwMGbEDX9Vm/grnCgT//V/8Ku844p/Yan5Sj538Wse9u87FO4re8Gsjkd+uPD6PzZjonYk/PSenx//++Lbj71k/lBk5nAEptr2aI+tNvEfJSrCUpgRJAqfhQaQQgi8WJVE5kFIUfpf4rUP46ZYITLCg1Aw2aLY0KZoQ7zcDz1cpMS2onHGfz6jcOumg3qxOETsLR/4pYIiC99RKjgVRKzwebaq7KksjJa+7HJP2aNGh6aReISX+KJA7N5Noubob27gYoEfCMSCgeUcZWPSvgxxyMYympY45WnsD4Z5Lxj3KyhaEVK68MA/yhF9QAsQDZLtEhsLRlOKqCfLQwxpapg8HLMU4ApQGoHAqILCjcA7Cg3x4ggTBYVI9i1eSUZtjZ2LibpFiJD2BmUzcA6fJmBGCO9w0mMmY2wsiTpFWNVUFt0bQhFqpH2kcC2FWCrKYmYTlsnUiofI2GLN38cjHQ/XdXjKgX0AmE7nYdn/g8X/te1VfOimd5/sw1iDTvfEB0vsvmUdGx+774jb1eMkYDyfuBG2VFvwoV+WcB5pSp+dCW+owmGEQBiPdwLfkxgJzgucFlBWmNENqVq5FthShQDQGeiSwHgPLhY4GRIkhQMxgsiCigNREYYQQw8U5YO2yjyUwS6s3ALLErJySis8GIkcgo9BDgVFG9JbYbBB8+ViI5PxAsP+PN4IduyKifNprBPcuWcO7wUqGlIUiuWh52uddXiC3+B7k2329tss7k4QRQN33kaykcH1MmhYROHxXbCZx+QOlXmMsTjvgxm/ELiRxFmBlWAygVk0LESC77kJjJtid6+N9QLnPdu7M9zebCGFR0pHt9tA7C/QS4GcubYfR/17FxLI3DDjtl1tcisgG1CMwO/QeDvC5AKRe/QoXKdAPMu/BwVWQE625u/jkY4TcR2+8Lu/yH97/Kfov+Qn+NytJ4e8ALzm9zN+75c0b7nqK7ztY0+iu6rK420fW0ki+80XrnhYXvUnP83G+ZvHP+/e/zgApgYf5L987fsBeOszz+ZPXvWXa77raAkCQN4NfQX3P+88fu6HQhXDv17592u2edZnfhiAS55wHf/P+l088Wcz/vxDN/GXO5/Lv28O5/HLn/pN/udzgqr11E9dPd7PL+3dxE9v/gQvf8lFjN7/ffy3qz541Md2NH8ftQID3HnnnZx//vkn+zBqnKLYvn07W7ZsOdmHcdJRj5MaD4R6nATU46TGA6EeJwH1OKnxQDiacVIrMMDs7CwA995770nrc3E80el02Lp1K9u3bz9jpOqTcU7ee7rdLps3bz4h33eqox4npz7qcXLycaaNEzjzxko9Tk4+6nFy6uNUHyc1gQFkadCfmpo6I/7oKkxOTp5R5wMn/pzOlBvr8UA9Tk4f1OPk5OFMHSdw5o2VepycPNTj5PTBqTpO6ly/GjVq1KhRo0aNGjVqnDaoCUyNGjVq1KhRo0aNGjVOG9QEBkiShLe97W0kyYmPan04cKadD5yZ53S64Uz7HZxp5wNn5jmdbjgTfwdn2jmdaedzOuJM/B2caed0qp9PnUJWo0aNGjVq1KhRo0aN0wa1AlOjRo0aNWrUqFGjRo3TBjWBqVGjRo0aNWrUqFGjxmmDmsDUqFGjRo0aNWrUqFHjtEFNYGrUqFGjRo0aNWrUqHHa4BFPYP7oj/6Ic845hzRNecpTnsJ11113sg/psPi3f/s3nv/857N582aEEPzd3/3dmve99/zGb/wGmzZtotFocOWVV3Lbbbet2WZhYYGf+qmfYnJykunpaV7+8pfT6/VO4FkEvPOd7+Syyy5jYmKC9evX84IXvIDvfve7a7YZjUb8wi/8AnNzc7TbbV74wheyZ8+eNdvce++9PPe5z6XZbLJ+/Xp+5Vd+BWPMiTyVRwxOl7FyJo0TqMfK6YZ6nNTjpMaRUY+Tepw8ZPhHMK699lofx7F///vf72+66Sb/ile8wk9PT/s9e/ac7EM7JP7pn/7Jv+Utb/Ef//jHPeD/9m//ds37v/M7v+Onpqb83/3d3/lvfvOb/od+6If8ueee64fD4Xib5zznOf77vu/7/Fe+8hX/xS9+0V9wwQX+xS9+8Qk+E++f/exn+w984AP+O9/5jv/GN77h//N//s9+27Ztvtfrjbd59atf7bdu3eo/+9nP+q9//ev+qU99qn/a0542ft8Y4y+++GJ/5ZVX+htvvNH/0z/9k5+fn/dvfvObT/j5nOk4ncbKmTROvK/HyumEepzU46TGkVGPk3qcHA88ognM5Zdf7n/hF35h/LO11m/evNm/853vPIlHdXQ4eCA55/zGjRv9//gf/2P82tLSkk+SxH/kIx/x3nt/8803e8B/7WtfG2/zyU9+0gsh/I4dO07YsR8Ke/fu9YD/whe+4L0Pxx5Fkf/rv/7r8Ta33HKLB/yXv/xl7324sUgp/e7du8fbvPe97/WTk5M+y7ITewJnOE7XsXKmjRPv67FyKqMeJ/U4qXFk1OOkHifHA4/YErI8z7n++uu58sorx69JKbnyyiv58pe/fBKP7MHhrrvuYvfu3WvOZ2pqiqc85Snj8/nyl7/M9PQ0T37yk8fbXHnllUgp+epXv3rCj3k1lpeXAZidnQXg+uuvpyiKNefzmMc8hm3btq05n8c//vFs2LBhvM2zn/1sOp0ON9100wk8+jMbZ9JYOd3HCdRj5VRFPU7qcVLjyKjHST1OjhcesQRm//79WGvX/AIANmzYwO7du0/SUT14VMf8QOeze/du1q9fv+Z9rTWzs7Mn9Zydc7zhDW/g6U9/OhdffDEQjjWOY6anp9dse/D5HOp8q/dqHB+cSWPldB4nUI+VUxn1OKnHSY0jox4n9Tg5XtAn7Jtq1DgMfuEXfoHvfOc7fOlLXzrZh1KjximNeqzUqHFk1OOkRo0j43QfJ49YBWZ+fh6l1P2SFfbs2cPGjRtP0lE9eFTH/EDns3HjRvbu3bvmfWMMCwsLJ+2cX/va1/K///f/5vOf/zxbtmwZv75x40byPGdpaWnN9gefz6HOt3qvxvHBmTRWTtdxAvVYOdVRj5N6nNQ4MupxUo+T44VHLIGJ45hLL72Uz372s+PXnHN89rOf5YorrjiJR/bgcO6557Jx48Y159PpdPjqV786Pp8rrriCpaUlrr/++vE2n/vc53DO8ZSnPOWEHq/3nte+9rX87d/+LZ/73Oc499xz17x/6aWXEkXRmvP57ne/y7333rvmfL797W+vuTn8y7/8C5OTkzzucY87MSfyCMCZNFZOt3EC9Vg5XVCPk3qc1Dgy6nFSj5PjhhMWF3AK4tprr/VJkvgPfvCD/uabb/avfOUr/fT09JpkhVMJ3W7X33jjjf7GG2/0gH/Xu97lb7zxRn/PPfd470Oc3/T0tP/7v/97/61vfcv/8A//8CHj/C655BL/1a9+1X/pS1/yj3rUo05KnN9rXvMaPzU15f/1X//V79q1a/zfYDAYb/PqV7/ab9u2zX/uc5/zX//61/0VV1zhr7jiivH7VZTfVVdd5b/xjW/4T33qU37dunV15OXDgNNprJxJ48T7eqycTqjHST1OahwZ9Tipx8nxwCOawHjv/TXXXOO3bdvm4zj2l19+uf/KV75ysg/psPj85z/vgfv999KXvtR7HyL93vrWt/oNGzb4JEn8D/7gD/rvfve7a/Zx4MAB/+IXv9i3220/OTnpX/ayl/lut3vCz+VQ5wH4D3zgA+NthsOh//mf/3k/MzPjm82m/5Ef+RG/a9euNfu5++67/dVXX+0bjYafn5/3v/zLv+yLojjBZ/PIwOkyVs6kceJ9PVZON9TjpB4nNY6MepzU4+ShQpQnVKNGjRo1atSoUaNGjRqnPM4YD8wf/dEfcc4555CmKU95ylO47rrrTvYh1ahxyqEeJzVqHBn1OKlR4+hQj5UaJwtnBIH5q7/6K974xjfytre9jRtuuIHv+77v49nPfvb9kh9q1Hgkox4nNWocGfU4qVHj6FCPlRonE2dECdlTnvIULrvsMv7wD/8QCIkWW7du5XWvex1vetObTvLR1ahxaqAeJzVqHBn1OKlR4+hQj5UaJxOnvQKT5znXX389V1555fg1KSVXXnklX/7yl0/ikdWoceqgHic1ahwZ9TipUePoUI+VGicb+mQfwEPF/v37sdayYcOGNa9v2LCBW2+99ZCfybKMLMvGPzvnWFhYYG5uDiHEw3q8NU4feO/pdrts3rwZKU9vrl+PkxoPF+pxUo+TGkfGmTRO4NjHSj1OahwNjmWcnPYE5sHgne98J7/5m795sg+jxmmC7du3r+lU+0hBPU5qHAvqcVKjxpFRj5MaNY6Moxknpz2BmZ+fRynFnj171ry+Z88eNm7ceMjPvPnNb+aNb3zj+Ofl5WW2bdvGsza+DJ00GZ0zj40lKnfYRNLfqBEOpIF0waBHFi8ECND9AhcpbEOh+wYAL6BoR3gVtmndvggLS2ANOA9SgJAgJXiPiCJIY1yriW9onJJ4LTFNhTQeNQz7dbHCS4HwHi8FXgl0t0B4j4sUwjqE84jcoTp9yHK8sSvfWRThhL0L3+9d+Flp8B6kQigJQkAjId84hWlpZOEZzUXIwtPYOwJAjizCWoT1uIbGxRoXSbwUmIZCeI8eWmwsER5sJGndsYjoD/DGIqTEOxeOrToOWLkekQ7HbB1+so1rRrhIjc8bABGOAwE+kogi7MfL8L5wHt3JEIMhfpiBtaBUuA7Vik/5fxFF+FYD4gi8p5hv0m9Zrv/n/87ExMSx/2GeYjie42Q1Pv+GH33Ix/b97/74MW3/0qv//iF/Z4W/+OQPP+R9/M5rfvo4HAm86b1/eVz2A3DL524+4jaP/YHj2zG5HicB1Th5wgvfip1t0HmMZf05B9jQ6jIZjViX9FA4MqfJXUTfRgBIPCMX4Qj3JOfD/42TGK/YsTxFr58Qfa9Je7sn6ViinkXmDmEcXglsqijamv4mxXC9x0x4/HTO5vVLNHTB/kELgOnGkGZUsDBssDxooJQj0ZYD+yaQXY3MBGogiPqQLHmividZNuG7rEdYF7pHlPderA+v+zD/COfwscK0IrKpiP5mRffJQy48ay/zSY8JnbE+7rBQtOialP1Zm4GJcF7QjAokHi1tef6KgQnXaFBETMQZ2xensXdM0L4XWrssemBRIzM+JjzjeVLmYZ7CONASMxlTtDSDdZrRvGCwyeFjF+bzrsJLj7CCdJ8g7vqwzxJR39PYX6AGJsy3Jrwp8zBHF9MpXktcLClaChsLvISiJRDdEd/6m7efEeMEjn2sHGk+edWtLzmux/cnj/nQMW3//M89gf9709VHte0f/cgUn7v113nr37+ct//wnz+Yw3vA49i8+YnHbX/Heh0Oh+d/7gncdsEefuzG5x33cz4UjmacnPYEJo5jLr30Uj772c/yghe8AAjS5Gc/+1le+9rXHvIzSZKQJMn9Xtc6RbUmUXGKVALfEshEoFJFuuAQDiKhiLIMFytconBzDeLlHGcVvhmjuzm2EWFbgcBEPQvrZ9HdDIQJD9EQHqQh3GwtMHSorI9oNvDNFNfUEKUI5dFFgWlqlAMXCbwWqMwhPMhEo4YFom+RvfIhPS8CcUGGmzYCdAR4vHUIocKDu5Qlmaoe5iUijkEr7Lop/ExKOjCBMBSaqGcQjWaYFCKHHBXgQGqJjRQiUXgBdkKjB45IGpSXYZJrauSMR40c3hUlcRHl+RvQJYkSgFcIK0FoEB5GLhCjJME2NcKFiUk4j0hK8iMExB6V2RVe1h0hlkfgwXtVkrZydpPl9Xfl7GQFdHOEMqAU0aBL1JDlrk9/eft4jpMKX/u1Hz8ux/a1X/txLvvdvzrq7SvS8Yof+syD+r4//Ycrj7zRUeLdb/jZ47qvN7z7/cdlXxPtE/+QVI+TtbCzDYqzUibOX+K89QNm44xYWh7V6DCtBgAsmDYDFyNFuGkVThNJQyQszkuWbQPrw31obtpxX2+anftnEIsQdS2RMIjYI6QPt9NYI71ALkkiIRl5wShN6QqYnVzk8fNLjKxGCo8UMDU1ZGAsC8MmC70JpGyilEIpiL0gyTzp0BENXbiXaxDKB8JS3cKtRxYGHCDBN8Pc6JXETSjyDYreRZ6nX3wnG5IObZ1xbrKPJdtEGMe0HzFvLYUP9+RJPSISlkhYBi6m8IrMaYY2Ineawil6CvYtJIgDEtGyKGdRziA8YR4pCQzOo4ocnIPCgROoXKOiCEYRzimy2OGaDoTHxxJRBPImGwI18mNSFA08ydCipURqjRAOaQ1eSkQa44VAJ3GYEweWxEqKpsZrASOwWSA5Z8I4gWMfK0eaT5KJ+OE61KPCP/7At/iF+15wVNv+6mdG6Ge/i7f/8BuPvPEx4txHX35c9/f6HT/He876s4e8n7d9/vf5Z/e30IKrLnoXn77p+J/7ahzNODntCQzAG9/4Rl760pfy5Cc/mcsvv5x3v/vd9Pt9Xvaylx3bjrzHJ9F4hV9l4Y6cLjpsLIiGDpk7fKSQxoEQ2Fgz3JAGpWTkMO0YWThkXj5MS7ANTRRFeFMqNIWh+tV464LqUakkwxHCWNRSl8ZSim8m+FjjlUBahyzA26BuyFGB7GWIwQg/ysJC0fjpXUH5fXgHWRYIiiJ8l1KB7FjCgz0g0ghfFNBMyebSMBkAXgji5QJZWJyWCMBFElFIhATTjrCJQvcKvJYrN30HepjjEo0aOWyqUUpCQamuUJKWss6xIhO6vDrV8VuLsA5tHTJPcGmETRUys0F5MT5MUADOITOL7JYKVKU6AX6UISK99ruq62WBWOGtC9+rFAxW6nXPBBy3cfIw4FhJDKwlIkdDZo4ncTnVseXyrdx33fYHfL/GoXG8xolNwLQ8myd6TEVDrBdEwpK5iJGIUMJhy5kgEpYJOSLShmXbIpEFmYvG+0plwaZ0mU6Rcs+cweyI8IpwryssWI9PFKJv8FogjEIakEaiMkk3bfO9UUSjkZPlmlYjY5jFCOERAvp7W0RLiom9gmTRo3KPyh16GOYaCIo21oeFI+PwWiIQpRIR5kOPCMRFSWwiKZqS0bxArx/Q0uF+2lZBxR/YBOslPZtgnKLwkrbKyJwmUoHQKBGUqqbMAXBegoRGVOB1eQ8XlJUJgPfIwoV5BcB6MBZRGCgMSIPUCu09sRY0I0HRlhSTAq8CIdMDgR5A1PVEg/JajDxqZMvvYKXawTgEK4toqheOU2QWORSIPA5zHWDy/Jj+fk4HnMpzyoN5cP/GPbt54tmHVlorvG/nP/Lxy298KId2WLx+x889LPs9Hnjy26+Ct8NFS5v4yT94AZ8+BabTM4LA/PiP/zj79u3jN37jN9i9ezdPfOIT+dSnPnU/c9kRIUJ5kiwC+ZCZgckErwV66JBFuGHlkxGmJZGFJ92XUUzGKxJ+IvFSh8nFilDO5DxoNX5oFkrh82JFBVkFn+XjB2jR7SMG4Wbf3KfXHCejLHzWufCQ7n0gJJWSkRdgLd77wGQjDS4oMADC2pUysrKkzBcFIk2xU028gmg5PPzblgzKjwzHEC/nqKEJEr2W2FhiU4EaSWThUCOLi2UgOU7hVVCMTEsTJXE4dlcRF7c2C0/r8XlUx4oUkOcI71FZjmymyEaEVzJMIplFuDCJit4gKFDVZFGdJxxEXspystVkLgeUBOtCGdsZhuM2Tk5BPJLISY2HF8drnKgCbOqYS/sk0tA1Kc4L2mrEtBrQdSkKT1PmNGVGKgsKr2jKDItECkdbjRjYhLYaYb1kOh6gWwVeRZiGxCUKWVhkbvDW4mON8wrf0iBA5Z5kAdzdmnxaUfRbSAfddntcGqUywcweT7ro0SOLzD3SloqODyRJWI/qZ6FkuBmX5dHl/KYkPlLj+dML8BK8FphUMNxkOX/9AgBaOgqnWTBtmirDUZE6jUWSygLrJUo4ujZF4WiqfKxCDW1EQxVMxBnRuiHm7jbCgsxDObLwHlFYRFFWOlTzorUlqVkpHZbGo4eO1i5B0RUU7UBgVAZx15Mse5KFYkxaZOGQhR2TtapywQsR5p/ClPOqCNfDe9Swmps9mDNrQQzOvDnlTU9/Hz963SVjgnLVRe+i/YEPAzxspOV0w03Tu3gL7z3ZhwGcIQQG4LWvfe1hJf6jRun/kNYhCottRAjviboGNTLkUzEuVgjnae7KxoRE5m78QG9aES6SRIsFXgpsQ+EisbIipBQ4g4ijlQd05/E+vBbIhF5DPvwoC8dWlp0JIcJ73oPW4ZbsfenLkeBt2I8UCBdSHUSxSr6uHtilW0NihI5BSUw7QmYO3cvxkSJXMaYpiTthUqg8Ji5WuFihBxbbCCtuLpaogRnXASPCpOAiiU0D4RJaB+LlXFA+yusitA4qlXV4wv9RElzJcKwFYxCjDKV1IFylj6g6J29MqeqIQOIAYokfBiIo0gRfZIi0lLKr75di5dorQgneam/OGYLjMk5qAMe3fGz1Po9XGVmtsjx4HI9xIqzHNxzzSR8pPBN6REMVqHLFflb1iISlJTMiYejaBiMfMa0GjHzEyEW0dMZIjii8pvAK52WoaLIgTVhQG88tgCgs0npUQ4eqgEyAg3Qp3EOdhmTZMpoJU78qwmfV0CGLUCZdcgWkL1WXat9ZeW81wROK8wi5QgicDvd7hBjvxzQFcjanoQucl6E0DoEUjkjYMUHLykeRSFgSEeaqzGmMUzRUTiLDa1Hpi3Fe0GpkuKyNHpZqiC8VkWG+ck2quc+UN3pbXi/jUIOCxDiinsLGkqItcVqgM48eOFRmUUMTzksJhHHIYZhTfKzHqr/wvixb82H/lHO0KBmgEAhnV6oEzjAcj7Hyjs+8hj0UR97wBGA1Ufn0TW+E41vRdVicyurLqYozhsAcF5SKgpcCUTiktJB5ZB5M+1G3wCuJ1wqZGWwrIp+MSgJDqLcdWbwgqDcQyq4ShU8TGIzCQ3Gkw01NlTfZwqyUkSm1Ul5VKjQiKWtDtQ5KjrEIJcM+S8N/VX8srA8qRJYHNUeGSWlMWqr9Sx0kdUUgMRVBUgqTKqT1uFSHa2EDOTJNSbI/R2XBwF/MpthYEnUL4iWDiyX5pCKSAj005BOhtExY8BpMKvDNBNEfjicYEZVla8aEG751JZlY5ZwsVaw1pv9yovDOIrQKxKW6fhWJUaokZz6oL0KGcrQ0WSkhg3BdotUK1+kfcVnj4cXDQV5W7/t4kZgaJxGrbjHGKebiHhLPHaP1zER9ZlWfkQ9KbyQUIx9hkfRdzLJtla8bpPDsL9rc3l/HbQvzsCsl7npU5pHGBQV6MIJI4+MIYS3R0gikDA/fUmAzFe7bRSjH9bIZHtbL8rCgoqvSzxLurdKseuCWAjfZQJRmdRyIgx7gpQkP+rYRFHuTSkZzMDvdYy7pj0nI+qhDS2aMyhK5rCRnbZWRyAKFJxKWZdsgkYbMaRIMiTRMRUOcF2jhyApNXPKSNcpLqYJU86wXAqHsiv/UuhBA48PcTo/gV+1GuFiFBczchX3ayl8kxhUH46qJ6vJ4H+bwwpTqix4vonkpgypj7HjOqnF/fHbjE7iY60/2YdQ4zVATmNWwDtXNcFqWqVZl7W9hIVLIMg3MtJqYdpDRvSxXwqoHb+eJOnlYCSosrhljI4lONKJ68PZuRTGwpSIBQU1RMryWJGFCaiTjEjQXa3xpjsR78qkYPaqkcnBxKOHyG9uokUXv7UCnB8O1xGl8DJXqUAUKOBduvgSVpZiMww3cQWN/gcwdclCESWoiRRoXJlDrEc6iBgXChutStMJ+ZJnS4sqbvmvGyHF9sl0hHpXaMTb3ryJVlRdG6pXtxsQkWquWVIpK5Smq1BshV34WpZHf2vHvLOxfrfwtSIGQZ14Z2fHC8TLw16hxpkIaoBB0ipQNSYdIWEYu4r7RdFBTolAmNiGHjFxjbGIf+ISBC4tWkVB0bcpNnU18Z9cmsuWUdFkG1cEGk7pwLijbxoZ7JiCGrlwkC+VMMg8P9y7V5NMNirbERgKvg5ozmlYUbZA5JB2HtMGqWCkwwoZ/y6wiN+HhXxg3VmaEtWXtWAhZsYnANjzzzT5npUsATOkB06rPpBxxgDYLRSBqbZUxH3VpyYzcazIXsSVeJJEFy7ZB5iJSClKpGNiYWBmSyGBj8AqE8UEdMTZcBynxspzjVKlaOTdWSkRhw+d88E8KGYjJ2NdSkQ0hAhGtKhxUSNUUWQiwGftrbJn2Wfpnx0RHgkchdAgQqHFofO7i13DxcVYgNtxSz98VjpeR/1RDTWBWQ4e61SrpSo6KINETVmiqlRdhgt9CjRxRp/RaOIdTOtQjD/KVMibnylIqEUqkbB6UFCEDYTFlAhdleVcSQ6SxE02y9Q1cHEzqNpUI77GRIO5YdGkodEqg+6Fkq4rTJJKYhsKdNU0cR7B/cYUEQJk8tupXr9T4Bo6Sa0oJZFbGdFqH6gXfjU0i8ukIYXxIQxOr9ktZYuZBDyxeC7IphUllIDOVSiJEOF8p8VkWiIdapXxUkrw7RGKYkKXqYlfK8Co/iytX3+LSS1NFLqtVqs5qEilFCA3wKyRKRFH4nahVhKbGGlz2u391WpCYG751dHXnT3rC4dNxatR4MHCaEATpZUj9wtOzCSMbMbQxVgcC05I5fRfUFiU8XZsiRfCKDFzM9YvbuHXnBmw3QhiJ1x6vCGbywoXV/apEypULUInCKxXijJUkn0mwqcQrgUkEozlJ0QY1lEgDpgXZrEcYGPYVpuXxmpDGVa0fFRAve/QIooFD99V4AU04P57zhAsBAMEzKljOUoY2YmOyzIQMpbxLtsmCadOzKdZL2nqA8xLrJc6LcTLblOgTa0PuNYumRSQsEk9L50ymGfsagVzhgjoivMeXUfihZGtlTqleF6Zsg6BKoiHK0uzcoDK/oqyooKBI4aCo5p4wp4+3gZV5RQq8VmHhMSoXGmUZatDQuNEqSa7GGvzodZcc1/3dt+N6NvDU47rPd3zmNfd77QvveysAz3zl2wF4y5WnhjfkkYKawKxGVkAryMamHeEjiV4aBV/MKMQJ+0iV6WTgIoUyRRnpuyKlV7KxL0mBysLKj/d+bBJHyxWp2/nwQD7Rwk02MBPx2GeiB2GC0CMb4ovjEB4gCocSZU5+K6SURZ0CREhA0YXDtCMG50zSiBRi1/7wgD9WMwjEwAVfCVEUCIxYKStwsQyrbB5sGtQbF6sQC+nL8t6q5KA00WsIZXYiTGqmHeEigdPQ2G9Ry8Nx+ADej5PZkBXBK1PA9Cq1BcJxQrki5vAVH6t62pT7oCqXcyv1yKyq0x7XdVSKTIWKJK16zet6eJyKOFpS8mD2WROZY8c/LF7BD818+WQfxikH0xAIIzBOMqMHTKgRB4oWsbRI4XAIptRwnERWeE3XRTgvQxmVyljOG3SyFDvS4AVeeZwOi0tVSuRKJH75wBwpzFRY/HJaUEwoOmcrRvO+NKMLTNvh5orw7O0EMra0JgK5yHPN5pkOwyLCOklmFMNBggd6Q028O6K5Q9E4EI5b5qGywAsxTueSuUOPPFFfsjxoMHQxqrz3Lpg2hdcsmKC+zOo+SRlgMHAr4y9zEQ5JKgokjikl6LqUWd1nkMQsJk0O2NUqUVm2lYaV92rxkUqZkpU6VCozFbdxpZpVrFrkEwKPRgiPN6tK5artV/teSl9pCDSowgzK34UUuCj8Hlyt6B8WH7/8Rl6/49Ljsq/7doRStD2PPXZPTUVSrp/8Ch+//EauetHO8XtfeN/hP1cRmate9Nbxa5/+6OZj+u77dlzPlrOOzzU4GGei+gI1gVkLKRBZgcwstqnHJAKCAiOsB+lxcUje0kOLi8vVm8KNiYxPFGIUpH3v3PizY5N6XN7IbLnarxS+mWLm2hSTIQSgqkO2scTF1QM4JItFWHUTIpSL6XCzVJkLSTTljbOYjMknNcJ7+me3afeGsNxDJHEgCVXp1Ormlc4F47tPx00zXUOj+gVqWJDPN0Oi2MCENBoloBEaaMqhW1FMFEHFMh6bSMoWB0TdInxHRVqEGHtV1mR+x1HYRqoxscGp4JVZFWQA4L1YGwft/EpJWkWCqklGyEAcK5XGH7Qi5l0oMZMEFWyynnBONTwc5OXg/Z9sEnM6+V8+a59Bv2OOvOEjEQLkSLCrP8nU3IBpNWA5aqClQ+GYUkNSkZOKAiU9SzYoLtWDfiQsU2rI5vYyu9IpTB7KyrwCk5R9sGx4OPdpjE9ifCP4OExL09us6W0TjDYamuuWSaRnOIzxQJIUzLUHNKNQQaClox1lTOgM5wXT0YBhWcY2tBGLWROA3CnunJijL9sIJxBeES+HkumxAi8COQhNmKHbSdk5mGJD3Bk36pR4UlnQlPnY51NFTFeldBJP7jUSV5K7NLyPZlb32TdshcjnoQ1pX1keFCD02H8SFurkCuEoy8CqxcU1c4BWY88MSqx4S1nx++BXBSeUxMlXvdQiPf5OUZTNPLUsAw4UNqm9lScCD5YEXPWinWtIylUvemjHUalKR5tedjxJ3CMFNYFZDRdWYXRnhI+aeCGwrTgY8oXCR2AmgxQvC4/TAggP+rJwuESFpJLcrtwsCZYOr2W4CValU0LgXUgR8+0GZqYZOhoDKneoQTAEhmSvlVImG0nigQk1uIBtJ6jye1yisQ2Ni2S5QucRFpwW2PkJ1HIvkBfvwPiVyGLKm3nZb0UNCmyq8QJMqrBJSFIrWop42WCbGpU7qmZhsgh+H2Q4BheFcjbTUBQtiY0FjQWL7maIUVlyV32flIHkrZoQwvurysbKRLZxJKb3+Or9VYRQCAFxI+y7KMJnUCsRmt6u7L9KOINyEluVyKZi3EQD26xrlk8lPNzk5Vjwhne//2Ex8p9O5KXGA0NYUCPBQrdF5iJaUca87iLxNFVGU2bEwpKKcC+fUEMscvwQHwlLVBrXm82Mbq7wTpSlUuUClCPcy6Lgj8xmE0xT0d8o6ZzvmX3sfi6aXGQmHrJcpAxMjBSets7Q0jIbD+gWKZnTtHTG2ekCE2qEReC8pGvT0FAyjYmEpWNSpuMhXxmeS76UEg2C4i5MERaHhAj0y3qE8UQ9j1iIWNjUHBOTKolsc7Q8jkyuoKRjTzFFz4ZFhEiGoJnCqzGxcwhu7p7FnpvWs3GhjDau/KrGhq2khEbwY7pEg2ccA135U8bGfBXmdiCUfglBlbZcLSR6t0rRqSKUJaW6o4J3tIyWxoQGl6HKQEEaYdqKXNSPW6cqVistxwu93/8E3HQtUMcvP1yoR9Qq+CwDGSOX+2ilcM2wmmVTHUgJ4YFeFh7dC31cVC/Dtspc/Cq5UUvwCh9riskYaXy4Ma4umxIyGPaTCDvVIJ+J0QMbysNK8iMzg4vjsJKXe+LFHDUI0cY+1riDsvcRIQ4SCWrkiBcNSEE+FZFPxTTjCD8aBXLgy9IxIUJoQBWv7ByiPyISgtHGoLgIF8ha1LWovCwVWNXUzDY1IpLgob85wcvQf8BL0CNHY58l2d0L6WiVzF6lhEkZerwIAVoGQ36lvpTqiZdlJHJV0pVnEDE26os0wbebFJMpPi5T5JxH9QtkdzROPfN5Ue5brE06q9QZCP8vU8yKVq3APBBOFx/Mw4XjTWJq8nJmQViIeoL+Ysp3BxvYHC2GhpVqVPpdXOj9Qniwd2V+cVAkwsNy4TQNVfCouX3cxjq6yw10T6JHLoTHODcOeHGxZjSrWXicQD22y8b2gMfO7GFd3EUKz3Q0ICv3N6WGRNIwKJtIzsZ95qMeTZkzpfoUXjPy0TjuWFnHyEUk0jCf9Jib61EMU1RWKhLGjVO65MiNFYykI0kWFDv2TnNne55HtfeSec2M7mO9JCojkwuvy/8rImmIvGZg4/E1WTQtCq+4qbOJXf1J9t24gfXf9KQHinE4gaiqCMo+LC7VYREyDZUI0kSQBV+rl6tu+d7jXZh/XKJwKqSorZg7A3mpggvGC3bOIYoqFMAE9d6Ui2U6/E59VKphGxW2qBfEjoQNxRMe0uf3RN866n284zOvGZd+PWy46CfgYe5Y/0A4U0vHKtQEZjUqH0iWo5b7CN/ETad4GXqeIECWng8vBWoYbp6qk4WceFuZxH1QIho6RFG6UoGRMigHfmUlx7cbZDNhtclXN0xPqCUuHPH+ARDke9XPxjdVm5a/upI4CUKvFVX1pKlKqSwk+y1mIg5KxahMJKse2qUo08AIsc5CIAA5yFBZCgJ0v8A2wmTgyonJ+dDwM5wHmMkIfIhKltaHJmF9S7yUIZcHayYD4ijUG0dlTHOlhFSJbEWxyhujViWK2fCzUqH0LVb42Sn650yOrxsE8maaiqKtkdMJ0kwSLQ6RS73QUycv1vpifHkBKz9NucJmmrXkfyScKBJzItWXk1FGVpOXMw/SeGQHogOaf7/vPDYny2yJF8aNKlNREAmD9ZKuazByEb1S8QDouYjMhy70c0mfwVTMd3spegiyKL2HNhAY244ZzccsXyBpPmGBq7fdTFPlNGUekrxMk6GNiIQllQWRNGQuYuBipqPBuIHkgmmxUJrlgZJgwcDFDGxMxwRDfqINxoLOggIChAUtb8dKhfaeJJa0t0tMM+Wu+VnWp12aMg8+n5KkxcKO+9yMfDTuBZNow5QakIqcSFi+11/P9Tedx+Qtmo33GOJlExYWHbhU4yaS0Ew6LRMvI4EwQQQJPXN86Bpg81DeRYh9rlLIrJaYVDFYH+Gi8LmxWV+GhDZpfPD29CxRz6AcoYyvqh5YHT6jVSAwDclwgxjnLNQ4NN5z1p9x1tcfwGhyVFhp2vLzSw+sfDzs5OVB4D1n/dlx6wdzOpKXd3zmNccUhHDMBGb37t189atfZffu3QBs3LiRpzzlKWzcuPFYd3XqoYr1BUSWIzsQZwVmujle2QeQVXRxudIjcoNHhVKxSAVluR3jYonum7Im1uKdCw0sjQlkZqJFMZPitQhGSIJkPe4hk5tyBUlStBS6H5c9WYJxMUQ9h0AAr8I+ZFbm+lerTsPgi5F5GZE8Ls2ygIO8LKXyLvhJiiIQCmuJ9/dDwy7r8a1AUKroaGEBAfmUJuqFpDJZeJrWo4chUln1c8iLEGsJ5fdLfBphWwk+ltgoHLvwEC9myEGO6A0Cn6gUkipqGUAEb4tIE4otc2XZng+JZ0qUsZghgMCUgQcuFmQbWuhmTLRrMRyDsVDka5PGSlWs6pw8JqQ1HhCPZCXmoaowx0JcVn9PTXhOfeghSO9p7BH09SR/zSU8fcudYyITCUuEZeRjImFY8qHMatk2aMo8pHCpIcs02Jh0cF6ye3KC7nSKjQUulvhE42NNPhWxfK7CP6HL5Zvu4axkEQjlWoVX4/9k6fyfkCN2Z1NYJE2d01bBwL9swjFUAQNVr5YqHSx3mr3DCXKrsEkoT/ZSILRcMcOX93uRhfkvXZY09ml2b5/ls6OE+Xafx8/spEgUTZnTlBmFVyyYdvAAiaD29E3CgaJFxzT49oFN7L1rjrkbJe1dBbKoepNp3FRM7yxN0RJ4BUUbvA5x/PEyRD1PNAhVBHFHoE3oAxNKx0IsstOSbD5hOKcYrhfYGGziQ1CNWSkpi7qCZMmPf8YnyMyECOeKvECZPhaae4YqBpB5rcAcCTue/MrjQGIC/t/pwyebPRwlY8cLD9XMv+GW6ISnof3odZcctdfngXCsx33UBKbf7/OqV72Ka6+9FiEEs7OzACwsLOC958UvfjF/8id/QrPZPLYjPpUwNoGXJu/BEJHlaOfxjTis8uiVxCubakSikaOwam/aMTaR6FHoSFytROUTEY2BCd15q9V/rfGNYLRHlKt1hUONTCgHI6g2XocO9+mB0vPS1CHaeGjwRmKbUenFKRPBSjkfquABRzGd4JQgvs/gq/jgzEAjXelMXF2CssmjGAa1RxiHjzUyD3HQKndkMxHp3rAi3rwveFpkFqKcY+tDs7Oqudeq5l1uqkm2rolpSJwOk580nmjgyNqKoq3Q/YSok6L3dVZKv6QK9cZVzHGrwfCCdQDEiyN0P6SeIQVFOwqx1YRVyor4uESSzSX4eI743gXEKMO7UIIX0srC79z7EBognEPWBOao8XCSmFPJ+3IoHInErCYb1XZHS0AezoaZNR5e6KFDSE/cAeEEw3ySz44ezYWb9lLMKC5Md6GEIxKGCNiol9kNY69IUwaD/5QajBte3pauY3HShpj8SIYV/nbMYL2id57l+7fexaObe6Dcz7JpcqBoMXQxmdUkyjCj+wxcQs8mRMLRMcEDI4VnaCO0DPfZgYtXmk06zdDF9E0w9meFDj1kXJkCVpncy540lEmcclSge4rWLgk+IpuZ5u6zmjR0QSQsbZ0xowUDm3DHYB339mfoZgm9UUJRKPJejN4f0dwlmO16mgcsouotFkuGc4reFom5tIvWDmsljSRHSU8rztnbaTO4p01yQNLYJ3CRIIVxEI6LA8HIpjW9TRLbABcxTtnM5i2iZfBOIATkiyFkBy8xqSCf0sTLhmRBIldVSFTJcJWvNeqBPLVvY6cMdjz5lbzjM695QAJytPjPfJR/Yq0b/1QmL1CZ/m/kHZ95zTElqR2N4jL78u9wzf6r+H/2TvFL65fXvPdTf//QrsvBMdMngkQdNYH5xV/8Ra677jo+8YlPcOWVV6LKlWtrLZ/97Gd53etexy/+4i/yp3/6pw/bwZ4QlHG9ocGkWikxcg45yHFTDVwaUsiqJDCbKPJpTXeLIp+A2VslyZJBWo9tKPTQInujcQRwCKAP9cI2FkQ9hxpZXNk806ca04pQKhChxu4RwrjQPFOLoIikofzKxaH5lhraFTOjc6iuLT08GpzHtoO/Zaw4lI00x0ldVRKYsSsTUB4ag3kpS1Uo9LlpdbIxsanIEtajuv2wGmdWpXyVXhczP8FofYPRjCLpWqJ+iNoUrpT6y0hmgOHGlFQJon0K0emtRCznBUIr8q1zuEQSL+SIzOLToIQVk2FyrfZLqVTZOBg29cBSNDXu3HmS+5YQHb+i8hyMwqyUyNU4KtRKzJHJxvEiLsdKhACe8L7vHfL1b73ywqPeR42jh7SE2GITVACvBEPZ4JZsE6kqmNXBazKtBqQyR4mcdbpDKgoGLmFCDkMJl9fgYOQiMqsQViBsSL/yUShtdhH4hmUiCgb8zAX/SuEVmYvomZjpaMhc1GdW9dhVzDAdDRnaEBhgnQw9VoRH4XDlKlrPJuROI/FoYdHCoaUj1pY8D95Myo71uLKkbdyp3iNHJqgwgMo0g6HEJRG3NdezOGqQKEukLLs7E/Q7KXJvgspA9wWNHswsOKJB8J84Hc7bRZKiLemcI+mfbWis63H5WfeSO02vSNDCMRkPaeucdjxDb7LH9j0zeNFAGInuK5QQSOtwkWSwTjNcF5p6VmXI+ZTHThnSmRHtRsao0AyHMXYa+olicJYg6krSvYJGFEJttHNIWxI4YxFCIEcW3ZdEXRmuVY2jwluufO9xITEHk5fTCW+58r2HLCd7sArL//rhzbD/KoD7kZfx+xw9kVlDWDpr37vmJ3+fjet/H4Dde1vHfKxHi6MmMB/72Mf4xCc+wdOe9rQ1ryuluOqqq3j/+9/P8573vNOfwFRmdhg/gIssH9ezAhRtPV4FCiVVlQICegRFUxL1QgMwYXzwpHT6wcQ/dg6GFZqo54h6ZclY4cYpKKahMA2F8KE8SnrQgwLTjMbfW0wo8JDuL8JKkhXjfiwIEaKdtURaT7JYxkxWiVxjE7sbG9d9mZDmjQ19LrNAcORyD9mT+DjCN5NwTXITvqcw+Dgq64BL4nAQKXDtlNH6BqYpiYYOYQgR1EqUk2/oLK0yBy40xywmIqBNZG1ILrM2mPUnmuRTobdMPh0Tl9/hq+hpDzK3qJGhmEywcSgR0AOLHhSoTDKaj1HzbbRziKzA52UyWl6AkIEoOUfzXkeNRx4erP+lIhMPhlysxrGoLu9+w88e1fccjrysfu9br7xwzb+PBj+ovsg/LF5xVNs+0iCcD+s3uUc4iLqhB8tolPDt5CzmkgGPbe1iQg2JsOOeJ7G2rKNDLCxNmbFg24xcxFLRCCVgVUf30mvhxiEu4LxgdzbF+rhLUhrwWzpjLu6RCMOEGrFsW4xc6YeJSmXfy3Hy11LRJJKWgYvpmwTjJQ1VIIGGKuiZBCE8ehiIi7C+vHeKsXk9lOGGB3nVD9KD8CCNQg8Vw31NlptNbBzKsdRI0BqF+VMNPTpz6KEnXSjCdSyTwWyiyKYUC4+VqIuXefqmHZzTPMCUHjCwyVhJmo+69GxKLE3w7CjD9/qbUblGjxRxVyCspJhQ9LYITCvMWbIQZHMW37bMzHfZPNnBecHdB2aJY8Om9QuMjGaYRyzunELmGpdIomGEl4IIQjkZjEua9ciSdDQmr+eTY8FbrnzvcSsnO11xPHws/+W7m7nkV49++8OVg60mLP9+5ffz71euff+G9c89pv0dDxw1gXHOEcfxYd+P4xjnzpABWpnGoZTGVfByWAcTSRnFKNB9G5K2MovKBCpz2CT0ZHFx6JgsLCS7BmVcMUFNKDveh+aQ4LXAxIqoW1BMhGusRnbcqMwLQTEZhWaWWlA0IvK2CmVnxmNaGpXZ0ECySibTEtsMJW3FpKZ9+yrGLVY1jawCBeSqiedgg7u14EKWvljV7MuXk5UYZeHaVMqLVmMS45OYbGOboiWJBiXBKMpmZx5sGkgaNigwXlUTlcTFMTJvoxZ6gWikcYibLg81n1QIt0LoqnjryJUpbrnF63BtnA7qlrAeNXKM1ifE8QzxzuVQzmwMVD1yvAslA53e8fqLesTgkazCVDgRxOXgzz3Qdz4QeTncdk943/eOmsTUTSwPjdAfJMToSwN6FAzgeEmv2eArjbOZPafP2fH+cRIZgMQxKUc0ZUZLGAYuoetS+iaUVqX7JUm3TKy0DuEZNxfumhSAjcnyuBRtSg2Z1Sv3sq5LGbgY5wWb4mWkcCg8SrQZ2JiWzjBOYZwiksGno4Ut/TTBM7Pv3hm27rZEAzNW7MM5l+0CVkfiO8p4foMaGqKuonEgRPObsjeKKucEUTamlFm1GBY+jw490QbrNPsv8ax/7B7OnlzkyVN3EwnL/mKCQdm3JilN/201ovCK3Gk2t5ZZ2NJksTdLsiRQuUBaGM4J8imPmbYQOygE6eyIRpKzZWqZts7YN2ozGsRMTQ2Yioe0IsUwiuhMNBnJQCid1kzcK2hEEt0rUCMz7hkjpCA9UJBzhjwfnUA8FE/Mjie/8jgfzemFSlHhGMgLwAvfsYdLj2CmPxxZed3/91+45id/f81r//G8L7Fxffj38VZjjprAPO95z+OVr3wlf/7nf84ll6yV9W688UZe85rX8PznP/+4HtwJh7OgdFlGpvCUMb0m9EfxjSTcZMt4d9sob9o63LTiBTt++M9mYvCQHBghesNQqlR1mK8gCYkpPty0TVMHxaQoIxszOza6FxOKbDp8Vlo/7sSsh2GyMA1NPqmIlxXJgWDIFMbhJjTJQoFcLCewilgUZW2lECueH6XCA7wJxv+q8aYY94shFD2XqWFi9YpSXu6vUq/KbsRussFwTpMuBrJXtBVOSxp7PVGvQOaWYjJGD804cGC0IUQx21iSrUtpjIrQ90YIirYep4xVCEZLT6HAKYEsFGpkgh8oCyk1NpGIiQRTlfQVHtNSyLk20c7SzF8FOFS/I1tPOI80nKwmlqei1+VY1Zgaa+EUKEu4VztC5LALfb4Qkk4yyXdnN3BhuptpwCIYuYjCa5ZEk1QWKDzbi1kWTYt7uzP0b59i5j5P1LVE3RzZy5DtGFeWPw1txHzcZ0oNcV5gZVB1Rj5C4cbNMTMXMXIRFsHApiRlU0kIasyQ4IXpmpTCKbSyaOlIpOXO5Xlad2vi5VHoV0YZ0AKlVzEsYo1TNWUgMDK3K5HHJgIliGWoFFBl+IzTMmw7KBDeY8po/KKl6W1WLDzR8qwn3cIVU3eMe+UoHL1SfWmrjFQWOC/HEcxaWBoKzp/Zzze2JQwPTCBzico9pilwqSOZHTI32WeQxcy3+8wkAzamHRqqIHeK9uSQiTSjHWWMbMSW5tI4RW1kIu5tzpJPJUzfqkmXJMmSRPXDomcVyqNkHUP2YPBgSMypQF4Wtv8gX//yLSflu8fk5UHinGv+fs3P7/jMa/ifH/kF4n889wE/dzB5ORgb1/fJn38XC39+8UM6vgpHTWD+8A//kJ/8yZ/k0ksvZWZmhvXrA6Xau3cvS0tLPPvZz+YP//APj8tBnTTIlYdvZFlOVSkQSYwoDKqTBfO+E2Oz/bg5lgoJWKapULkjWspQe5egKMZd74ExiZBDg5fxWIURvvSDOIEaGmRusDoel6mZhiDuBnJjo7DipgYGlMBKgUkEURVznIQGm1HfEN+7EOKDpRh3tx8Tkuq83aooyDgKiWzWjRPJ1mC1x0WHmGPv3MqDv/f4JMZNNuhvaaJyjx6acA5NCV5gWgqvBPFihhehQacw4Zi9EGW6TSjHU/MtkkE27pQsTCg3i7oOVZQx1UrgpcZLyKYUwkRBxSocXkmiviGbjhjNKNJFQbJUwCiEIqjpNnKpBzb83r11iCSGqrSsxjHhwagwl/3uXz1MR3P0OBnk5XgRl6MtJXswOBY1psYqiBBSUi02hZ4pHiSkC5DvlXxv3zq+2drKeY19APRsWprvGzgvWCoadPIG3SJhx80bmL05NAUeJyRKAQ7UyCOGilga5uIeqchxYoW8OCfJfERTZkTCsiVewHrJwCUMfELPBuVmsWiSSIOWjqbMyWTwvxiv6BvJntEE+67fwNzdZeJl2SYASfi/Y8XQH1WJlyBHZvy6KGzQmxwhxtj6cad7lRN+zotS2WmQTUd0t2qWLjY8+sIdPHP6u0TC0rUpCsfIR2RO0zUpUniaPmfkdWgI6hQNVQAFs1GffKPixrMbSKOJO8E7JCwUmWap30ApR2Y0PZmQNA0bog7DRoSbFcTKksjw37q4S9YMzT+HNiZSlrv1HJ28gb9bIpwm9qEFAcaVrRFqD8yJwKlAXoDTlrys3s9qP8xT//xmblj/wATmaBD/47nHHJd8OBw1gZmZmeGTn/wkt9xyC1/5ylfWxChfccUVPOYxj3nIB3PSMTeF6GTjrvDelQ0VYx0e2rVCjDLihTL9Kw4P4dFyMLW7WOEamng5R/Zy5P7FoGiUvU7G6obWQVLv56isQTYdbvSyCIlcKrPjxpleh4f9qB/K1GQemkeqLDTTlMbhhELmjqRrgyzfjMq6Ykt07378cLiSsAZrM+udJ4Tjr4p4XEVYquPHlX4grcsOw75M8Cr9P1pDFZOsJHaqQffcFqYhaO4zyMxiGzrEX8pAyLwSuIYGGRJlnPGYpipXLEO5hdOCzjkxs4MJZC8PiWtV6ZoHpySSsLqXLhpMUyIzj00VemDG/XpsKyrLE8J1FsYjhMfFknyuSSQlaqGDyHK8DNfgsAb/Rzhe96qf5po/+csH3OZoSczREJcnPSF52JPITmfysnp/NYk5dWAaAl0ED4waOaJOUBVsqinbrNDLJ/nH/ZfQXNcn1hbrBf1eissVFCKYzjuSqCOY2+lp7jcIW5YY56VibBxRH9RQMrIR66MOjnBfjIQdJ5hVzTEjYZhWAwqviYRh2TaYkDn7izZS+EACZD7uBRO8N469wwlu+8ZW1n8nNJCs+qBVsfOUaWSiVOP9VCuEwYwyRBHUdaREACIz44VBL0TZz8yH152DOMJryWhdTGebpvOkjCsfeyuXTtzNhByxz0wghWeuLI0rGopF08J6SVuNxseeyHAsmYuwXrK50WHx/D3c7TfQ3K7xCuIlSU7CYFIjEstwkOC9CMEGs5ZEGh43uZtIWFypkkXCcmFrD5GwLNsGfROTzWn2RZblpA0yLMb9/+z9ebxlaV3fi7+fYQ17PEPNVT1CN03LLK1c1ARRIoIaUHO9GHLxvqLidZ7lF5WbqCS5iZA4REXycwivH9EXMQQkiWKCRBwQAZnphp6Hmk+daU9rep7n98d3rbX36a7urqqu6qpqzvf1qlftc/baa6+19tnreT7P9zPowqG9hHyqpwrF/jJUA0oe3on5vs2Pn/dE+E/eefiSO5H9yTsvDog437pY4GVxfw2I+e98G5yC2158Kw/d/VHg7JSxc6lf/Ydv5lv+5q+fsDbmvHNgbr31Vm699dYn9KZXavk0JngjifFGEbwD7wh5vXLkLKooUWWFGgsIYYHvq5uJflURvJdMGR9QC9oKCZd0krcyyzG5p9pnUB6qRDosonlJWvGiLqSzk5wpWr6zqoT/7CNDsRQJLSqv6WEakrUZ+sy2CNSVbp3GdmSq6NoVzVE7fWlCXsjvG2qZNnPhP/VjI45moXLittIEUSpFGCS4pQ6bN/fwEegSom0xCAhKYWcSAuoS6TQVg0g4z4XQwnysMEXAJRKUqatA1VHkqwndrdl8RdMJxa5ZwdOFI153eNORU6uCAKba0MBMK9JZRbJhRAvjA7pQ+NLgEkO5KiuQZmMEs0wodn635f9EahHEXAkdlkery0Ub262nduXLimhL7mfKhTbw0U7KOtHdEk0M6bqhGC5RxXK/XBnJ/dml0mVP1z3JVtWGMaLEqET0iuJUacqAHWs+v7afv7Nyl+hoTEYRDC5oymDayXza/l9QBsOKnbQdGLOg05j6mEg5qqC5Z2Mfa/es0juhCdrjOpJ0rxvwAihXzrWQjSbGKHHzrGnY+Ic5P5YSL4DX80T7EPDdhGo5Zftay9bzC1526x08q3+UfXYkLwsWjcfVNLEb4jX22REjl7Jspkx8AnqegwPS3Up0yW17HmBWRqxN9hKNdG38oggTgy8VlQICPBCvcLi3xd543IKXri4ovWTqNBk2a2Ufj2I1nZLYioeA7aqPcppoEs0nWbvDyROuh3dXfuYyHcdjVf8nvgHe+eS/77f8zQvgn5+8JPt+OEj8wf/4E8DjU8Yeq/7qG/8CeGKamPMCMEVR8O53v5sPfehDOzowX/EVX8GrXvWqxxT5XxWlwQ+6mKyYa0TaCXsg1CtY4h9pxHGxmeTDXBDfdDZ0TUnKC9GNNJoKJd0YlRckx8Z4O6DsaXStjw9GUfYF1MQbBXEpzmK6tiz2taA+GE3Vs62o3WYOOyow6+O541hzXCEIJU4boKaLNY5rzoFjzlluhPpxND+/IPqeEMJc71In1zc0O2WE4pXvSYgnnqKnSbYdVddgM+mqeCVUuCpRJBuesm/kvJWuHcOC0OjqoExVBeKxx6Uan8aYTDIQRLRvRH80qfCxqbs2rqVpNOcTVO2AMy3BiHtasJqgNSG1+Ei6QWopQWeFdGFqV7XdOnv9xA/9Y978K4+/2r8LXM5el0rzstuFuXKq7ELhFaYUl8VFu2FTqHri7MUMxqjWlr9ZmHF1yKLYwoe26x2sag1bXM/iE4PJA8kmbD8w5P0rz+Sb9n9yThHzCQ4lmhAldswZorVx6FYPE2lH1xTstSPWqz5lMHx68zD3nNpDeKBH/6QiGod2nPKRERey0s3t9JscGGit9n0nQisl2WLezxfI6u2Vq0OWjSYkkdj+92KmBxJGT/M862lH+cqlO+nqnIGeMQ0JXZ0z9UkdzunZowW0DGrQBrBsprigiJXoYYyZ0TcZqap43t6U/9HZQ5hAMBIO3VgoK6/AQZFZtooUFxQzGzO0M0ol4GVcJpTeEOkOD2XLTKuYYZRxTXeTQ90tPm6vYVMvocuIrpKxWWW748nZ6o3v+U5+4VW/dbkP46LUn7zz8GUBLyDi+yej9n/o5/jLl8GPXvffnjCQObh/8oSE/ecMYO666y5e/vKXc+zYMV70ohdx4MABQAT8b33rW7nmmmv4oz/6I2666aYLPpjLXXqcwyCRiXuWzcFLM+mvKgEi2swpYT7MQxYb4GItj1huaahYzs0n/lWFHk1I1iJc0hVxZwj4aJ4gj1GoQsCLBGhBNRBKgMllFS49XWDXxmL33Ax0um7Xew9RVB+DQ1lDKL3Q4lzjGmYXMlv0/Jibjk0DzJyrqWg1qKmBXXudlKJa6ggg0JBuunqArjBZhY8MPtbEI4+dqToYM5APZWCNJtJxMjNPMIoq1SQbFSp4yp6hXEmJtjJQCVVqyFcjlAuU/Rg788SbJQSw2xk+sW2AZ4Q4AmmrhYttxXgBpURg2ZOgToCQRBJkGYKsCu7WFVEXi0a22215YrULYs69lId8VRFNIVaI5qMGMcEqdOVlIcsJ7RZE7K4q0e3ZSsaTNgxYq5q+Kws9ALryqFkg1orecTFJ+dTwGp7eP8216To+aByKVFUkumTqY9aqYZsRA7BVdYlql7GuLngg38MHTtzMqbUh+niKHSvsDFQl3X1vwSViqOISLQ5iVUBPDTpq7p1Bui4NsCnKVvupfADq3Bil5gtFqgY2GsphzOSARu2fccvgJKkqSVXZUuMWO0o9nbPtUzIf0dM5WUhqAwSPUZDVXZpFOlnf5NAvUScN0URJsHKkqHqKaqmCCOKkYlTWnSkVOJhskegSrVKqYJj6mKKyTKuYWFf0bE7P5hxONvEHNJ8IivHWEja30oG7hH9rV3tdLE3E5agff1efl1fDy3oMF5s69vB9L2phmmydr/xtsVV+Il0YeGIg5pwBzPd+7/fynOc8h49//OMMhzs/rO3tbV73utfx/d///bzvfe+7oAO5EkpVlbikDDro6azVwlDmou9o6FahIlS1uL2hYT1cL9GI4GsjAKVqP01j5iCgtme2xzfolZ58f0esk50Xa180LhGw5H3AJRpdD2o+1thJoPPAFmqWE2aZgJY4IsQxoZvICl1qMbMStEZPC8gLVC46luADlMXcGc0H6bQoLefVdFoIcwoaDWWuPv7FEExratc0CecEoXI1eh4AOy5RzuKt5NgErUi2ZIUxaPHN97HQ5pqVPl167LR286lkhdIvWZJNCUnL9gmPuliKJBl6IJNU5QLxqAQF1TDGG4XVCrOVoZwjJAZVBuLNXGhtqaXqx0STGLJ8twPzKPWrv/n/4yd+6B+fcxfmYlUDPi4EyHwxAZeHd2EW810uRu2CmHOrYKDsB4qBonNaFqMCYvYiE/sKBQQn3RSVO7kvRdJNVkUlmpBGb9hQlI10j1UIYpvvFbowJFuOpbsVukh4V3YbB65b52lLZziUbrEnmpAFuc+PXUrfZBgCWvk2Q+Xe6V4+fuoIm/ct0zlu6OVyDlUHxjeVdPbM2F7vYDctdqxJ1w1mFohmoleMtg3RdiHdlrISWvK0zoBpApKLUvLQaoaCiuN5Jlnl5NyMWCy7DsSJjEETn+DQDPRMcnFCREqJq2HBtH6+CIY9dkzm57qfCMfAzJjUHZsGuO3ZM2b7wYTOA3WX3kPZV2w9U6NWCpb7M1aSKakp6RkxdImUY2AyDkTbOBQbZY9N3aFjSvomxwdFGQyr8YTl7owTeweUxyX0UjXxBLu1oz778x/jhf/qyc2SajQqq9/5GW4brV7QPhrg8icLv3uf3eZnvuxFl03A/2TXry+/APPf3/HEd3Tbhb3snAHMX/7lX/I3f/M3jwAvAMPhkF/4hV/gRS960YUdxRVSQSlUUVLt6aOTGPKi1rE0gAJCqDm7uPmA0qyQxRHkufxjbseroO26tJP/ht5UiR7GnA508pLs8ICqb7BjJ4tUVqF9aClSPtJEoxJzYjI3CbBGLI87CaGXUg0SMApvdUu1Uh5UP0JVXQCi9SlqmhGmSros9coXGEKWzweWmoYmjmRmnhPjA3jpSKmGDlA5ASG+dt3JHDoX7rPrxuhS6F0+Ede2oqdxKdjUCMVCKbwR0BONHfFWVQdayv59XNO+jG6F+DqvSE+JMLbqGlCBqh8Ramc3M5NzM5kTekZWQp0J03C3qTxYjY8UuoDQidFjAw1+260rqs4HyDwacPnUu4+e8/s999VHznnbL5batVh+/Kr6AZUEpoege0qTbGh0WQp4CaEOiNF1GGQlVvGVQ7lInq/1IKo1X5HXhcjKvRjElZHaerhQpBsVpjDYzHJmax8bN3R51iFL2TUMbdbqX0Am41Mfc7xY4pPrR7jv7gOkxy39sWhxyj5Mry9ZObTNc1bXiLXj+PIQ5zW5M2xPU4o8wm0kJKcMw3s1nUQTbRnMpETn5bzLopQ4YTa0Zudl4WyRTgY1c0CAU1AQgkKrwMin9HTOyHdwQVMTuCXgkx5lMBg8PV2g8XS13BuacNDT1ZAyGHIfoZXHobl+aZ2/Ha5gCoXNanOcQjMZadjnuGFpnf3JiEg5OqaU6+USurpg1Y4ZOQkW7ZiSns3p27y2wZbPZn93xKnDA2bHe8QjjWpc2XbrEfWXL3sp77P/6knvZKz/1rNZev3Xs7V5fgtxf/LOwzuAS2MK8BbGrPJ+vu7aR77mo4P1i2YffCXUf3nj/4JffcHjbncudeSjb7sg97hzBjDLy8vcd999PPvZZ/8A7rvvPpaXl8/7AK6o0rWQ0HlCInoeFUeEphOhFZROujEgN+BFcX5VT+wjO7cmLqt516XZR1MNqDFGNDdnNkmLEj/o4npRPWEXqpVYDktAljm9JeCqoaXFESFNqPb0cKnFjgsR+C+lsrKE0M2Ckq6ETwzFvh5B94nXJuj1kTiV1aXiWKhkrUuZQdn6+BvKmFZy7PV5hbwQ6lXpMUWYd6QU+NjiI43rGOxEnMEQJgTRJKBLqDq6Bi8CYIJCsmgCVF3p6kiitcfMSqqeUBVUVmEnObobo0JCvhzhYkU8dpjcUyzFaBckRG0k+TghtgIIA1B59CQnJBF+X0qFRbkEfUa3QtTdemS9+Vd+m5/4ocubXfJ4tLKzgZfzAS4Pf80ukNmt86lq6DA24PqOfMnSOzqfrIfYErTeaSNcOVQ1dz9UeTm3qq8pwcFo6XSbOgDYiH4PpDttKqFzDXwgGhkmm30+ff9NfHzoOHzDGrFxrdPYtIw4vdnHHe8SbWsGW9QhwjC+wTG4dptvOHIP++IRS3aKD5pRL2XJTjlVDIm0Y1wljF3CPaO93HPTXuwDKaufMfQfUuiimtPCnKu79PXYGcnjZpxtnS2DxA00jpFVaZg52abRthjlWTITPFrE+l5+t8eOSVWJQzHxCT2dS9SA8qRa7KS7tiD3EV1dYLUnpJ58yQrVeObRDuJtxWQaczDd5lC81dLrEl2y5TokumS96rPlOm23JVJO7Ka9Zq3sk3vLNd1N9DWBj41vJF23qM3z9kz6oqjRx36ECPjoH78BXva4m1/0+k9v+2NAOjK3vfhWvvp3t/h7z7qDt3zLmB9/V5+3fMuY5/7Cbbz5lrM7l52ro9lto1Wot71cLmUXWmej+H30Q7fzvv/tNfzjv/79S/Yej1fn/I36ru/6Ll73utfxxje+ka/92q9tNTAnT57k/e9/P29605v4wR/8wfM74iutIgsOzLieFFmhjSlTd06UroXqtatXk9peVqjItpN9QLoaWs1/Dn6uNWk6MwsrTy3NbDLDlBVmHaI4khW6QkIcG2F+Q21TRnQcoZtS7u8TlCLazlFFRaj1JlVXk56W9rcuBHiYqQAy14vIDg+IuzH2+IaskMGCzXIN1prMl0bf03RgtDiVBT3X0ZiskhVEkKDIWMT5ugqYzImDmhMnnc6GBEoCzBLb8qurVKOHFj/z+FgE/SEVJb6qPGqSYfoyqFXLqVDkAFV6ydQxkA/luts8EJ0pRLQfyUSg6keieSkdphlkK0/n+JRiORF9TGRhjul2a6HOxUb5yarzoYZdCHh5+OuvFhBzqWlku/X4pTqVhCFTdxRq4X3TlVCuTrlEwIcqK3HlqvOu2gm984QGxFhDiMS8pO0gK7GlFxMAyYjRzmNnns4ZGQPyJcP6iYOUfU8woEtxSBueCKRbXpzFYpjt08yOOG5+5lFuXT5B3+RtRwHgULzJqXLImXLOWd8Xj9mzOuHm4Wk+vvcI62E/QSd0uoZoXKHzCj1SMna2gciKEFlCJ67dx1ybLxaUOFDG24HxOGKz7OCDJlYOrTxTLxqXqU8Y6BllsHR1zrKeopVn5FOW9RQQx7VN12vd1VJVEJuKqY2xyqOnBpOLi5s3ooVRDtTM8NB0mUg5VuyUjIhElxyONsl8RE5Ud4I8SzZv7ZVnPmZUJfig6JiS67vrHL92yPSTB/HRLoXsbPW95mX83nd+F7d9/TuBy6uD+eiHbuejt8CbGcI7kS7LO+FPziLM/+f/83v5s7e98YLe5+u+7dhVBWKeDH3Sry+ffzfnnAHMz//8z9Pr9fjFX/xFfvzHf7ydfIcQOHjwIG94wxv4qZ/6qfM+gCupfGyhVFBWhG6C2qBNZ8eYBZcxP++oAKqTzgFLC0oWNDFaoaJUuiy1Y5lqVqbiSDQvoRY1ai03ci8uZVjbUrzCoiajAUdxRLmnh6oCZlqg87KdrFddoVrp0qFqZxtvtfCrfRB6FVD2IziwLCCmCW9sLIR9vQKIF4pZc541uFu8DniP3pxglhLKgYEALtbM9mp0CfFIY/JANK5QXi5RUAJoXASmlO5LvqTQlYIgtC5T+FpLU+cMzHLikyOqlS6uI90Ukzt8bAQQJaodkOKtCjwoagcfo7DjkqofCSdZK9EGad3yzF1nYQKxW49aTRfmydTBXO66WCDmR37pty+ZE9luXRllrMdXoDLJtqK+x6u8GVM0oZnUVg6ynFBVKLfQ4a9BS9u5ae9Tej4eNPep2iBABQ91J0ZVBjt1JOvQPyr3U28V2vk6U0zAk080QRmy1UDv8Ihblk5i8OTekuiKVJUMbCa/MxFZHDFzER1TMnYJe6MxS3ZGZ3/Bnz4n4ky0wsrtEd2TivS00LCFXqxaUKaUg9LJOWldt1xE1RJtFXRPaWYPRHz2wEEOpVto5TEEDkSblMEy8QmpKimDIVaOIhh8iDhT9enpgiN2gzO+R6QqHKJNabQyLmhOz/rEm5p0wxFNHNmqJVvVZPsCZiWn8JaZi1mxU1JdtjS1Jlcn95YlOyPV0vXRSG5Z6Q0+KCZVwp54TGwcWRmw010f5Uer7/rtd152Ifz51oWCl6YuJoh57XuOXVIh/9nqfXb7SX2/s9V59TTf8IY38IY3vIF77713h43yjTfeeEkO7skunRVQCx2D1ug0ITSdFqNb3XpLA1MKIeyGub5Fs2ChbEQnoo10WKJo7oFvjKymJbEIHIty3q2BVuioVN1xcX7ufAaySqc1bu8QlxrijawNFQvGUHWFSmVmHp8YNOBSOTeNWAr7yOAjjTeKfG+KckuYExtCmdNGzqGqBMws8pTLCkztWNaYEQQPGFRZEa1neCuGBC7RdNZ8a/WsQqDsW9GjlGBn0sExBUQzjze1vagTMNNYKsdTR7yRo6aZTAJGU6zzVNct41MtNsv14GyKILSxLOBiLbqhLenCmO0M341xicEEh8pCTc0QcGNyJ52casEee7d21JXSfTmfeqLdl6utzmalvNuFeXKryi2m0jIv78iClarqhSmtCSauQQ2t6Qs0esMaqFgjtLFayK+C9HRCw+B1gdAsIjW6x4buG+YGKg2FONQ6jNCMYRrJ0XKB6V5LcU3BC/afwAdNHjQdU2CUp6zHxWPlSiuE71vp2I/KlMJbBjZjTzThKw/fy8eTgrXyAPFI190mcVZr3TgbR7XKocwcgMk/jS4dyWZJuqbZOD5k82CXRFdcl5whVSU9neOCYsuJ/sUFjdFeLKJDzH4teTEDnYkGxg3acMutqstD+Qp3Ht3PyvFAslGKVnPZUvXAdT2R8aSmJNElRvmWRna6GpLokg3fI9FVm7GzZKaUSq5RGQntrenKjPMEOxUzmt16ZP3Cl34NH//I1XVfulhBmBcTxNz3g6/ihl99z0XZ17nWxaKPXWhdECnzxhtvfMqAloeXcvVKUZMwvLC6BcgKWUMpg9pmuR4Mmht0m/nidk7yrW7NAJpVNBZ/bvZROVQU1RbGoX0vsW1emFhHlqonIZbKNeBJ4YYxk8MRZVehvHRiqlSEinbqSUc5wYqLTWPvqMtaaN/vwvrW/JyaDpDz0v6PLGg7P976f2UtoXIorTGbYxKgXElRJhDNnHSFDNiJE/vNVBONxKjAJZpo5rETj3aBaCLXJZpUxBseFUCVDr0xFhebysmxz3LijYzsYBeTeewskK2KE5mZ1Zk5kSbaEicybzR+tYuZla0eSBWVcNBDrcvpWExeQVnOO267tVsLdbm6MOe6/WPlwOyCmCexCrnfm1lNgzVKTEgi21LBGv2L8kG68bAjI4UK0ccoRYilsx4ig0+svKYZGyLRS2ogW41RQRZwmpBg7wXM6HHe2uw3LpW6cHigHCgOHNjiSLrZnsKheIuuztlnR0SqYlN3yaqo1Xx4FFtlyoqSTkSkK67vrDFZjjl2cJViEFEOY1TREUcyLdSxxnUyxBHUQEzaQXKNhFbm6Z725Pdb/mz56Tz3yDFOF3365iAHky0ATuRLgIj5BybjZDlkveyxlgy4Jj4DQE8XnHF9jhfLrJc9Pr+1nwdOrdL7VEr3lIAa17FiEpqDzhXFdsKd6T7ifaIZWrFTpj5myUyJVcVSnSmzVXXrLJpARIVHkXuZVs1cxLiKWTs15KBbmEvs1o5649/+Kd/CNZf7MC5bvZJ3ttbET6R+5mW/QbL/P/DbL/4nF+GopO77wVc9afbWl1TE//A6duwYv/mbv8ldd93FoUOH+K7v+i6e+cxnXujuroxSau7H39xsGs6u1/MJrV+4ETknE/pmO63mk30917yomgKmmvDIVlfSbFsPWs7PnzNGXNBAui9ZJstuVp4PSUTVNUTbXnQvWuN7ogmIxx5vDbNV1VpuppuOaFyJriYvUaXCaIWPDS7REAMHB8RFSZjO5rkvjSW00dJ90Q87BzzBIXqYSro2xnv0JBM7Z6txqUXVxjt2Ju5kuvKo0qFCTDSpNSxAXErmjc6r1v5ZjadtwrMyQY6HEnNykzixlENZzdRVwE4cdloJTazOxdGzCqymWIoJkZaMnZrWocoKHyVt+KUeZQIWdwecs9aVpIG52qsBGxeLTnapQizPVrsOZI9dKnWoscLk0hX2VuE7FlWL0glBxpnabYw4moOXsqoDhuvudxKDNbhORNWz+ESLeD0X8ONN3dWoECG+VVSJxpQBO63t6QPYWdkGFStr2oU6n1iKIdw83GBoM6Y+xgdF32TsMWPRmmDwQbM3ku6GqfNYtrqdOpW+YKAzshAxsBmDvRNG16+gXEw/yPAib6ygLIRO5r1YSzc2y8bUhgbSDe+sFfgoYYs+f3vyJkKvwnQcK0sTlAp0o5JhkvH5oKi85vi2uKQdGI64ob+O1Q6jAqU3fGb9IKfODLH3pQwegsFDFXYqi3/eKqKJp3tSaM+ZV2x3OqwNeqzGE7Zch73RqA3QBKTzYqeMXSrUupBwLF9mvejSMSWTKuboeInOvTHxdtUGUe/Wzjp95GdZ/XufeUo5dJ1PVd/2VRct/DI/9R289j2w/dLTALx3+LwL2s83bX+S4Qf2wXseHby8vBrCbWJF3fnev7qg93midc4Aptvtcv/997Nv3z4+97nP8RVf8RXs27ePF7zgBfy3//bf+I3f+A0+9KEP8dznPvdSHu+lrUWaFNTaj6alf/aXNMn0kvPiBehohXDN5vtshPeBIGJG3Vho+tb9jFA7mNXc5jDL5u9TVRDFqCQWx7A4xndjuQEH8Ek0B10e7NjRLQLF0OBiKPqKoi986KoXobpWJvWhFpDGGl14yr7F7B1ijpWSE1NVYl6gapqcoTYwcHP9i60DL5vBNgTCRDjdepoR0lgcmmtKhFgwe4gswWrsZlaHt0nnK0QGUyjUrBADg8oR8uKR5gFB7K2je0+ij+wl3yOhY9G4lHyZY2NCJ5Lz9Z4qjfGxxhnJmVFVTd+wRkBNYsWEYDQhlAW46gn9Oe3WlVGXgj52sQX95wo8FrdrQM/5gpbdLsyTU8HX3WmH6P3MXCOpmhX5opQxYLHTH+r7rtZyn4wjQhITYjFQafSDNnPozElnxhqqjiYo8AYmBw0+rp0em8yWImCHEemJiXRDSokE8J2IYiki3+N51uA4XdNYEItuZOJjjPIUwRCpCh8Uy0ZE8tu+Q9/kGOXrcEyLIbA/HvG0lXU+e0tCsdbFrdX319LN88Va1zHqhT8WFgI1qqgwIdA9obAzS3mfJl+KcJ2YSbdDMLCZBo7WwnuUdLsAHugNuWd4ECIPpUZnmu4xzepaoHvKEU0qMXIJAV16lJcxOR5Bui6f02QQCSAKmhv669JhUg5DYK3qEynHgdqlLNUl665H6Q2V12y5lGkVc+yhVfY+JLpPdgHMWeutB/7qqgIvF4s+9vB9XkxR//AD+85r+/fZ7YdpkM799b/3H67jZz73v/PPP/LhC6aUXUj3Bc4DwGRZ1uo3fvqnf5q/+3f/Lu9617uw1uK957WvfS0/8zM/w3vf+94LOpAroooSkm7rhKIquZkuUsbax7WoXzWksKYj0ZRRc20MtWg/qVfYGn5zE1AGhFTWp0JkCLFFb89kYKsqCVVBE6pK7Io7HVCKapDgYy0UgI4VEBCZ1lbTx4p4yzE9YEk3PPFY9CYS2qUwPhAsbadC5w6jFbMDHbqzIfrMpmiAmmBLVROvG01Mw2cODa/Zzs/JmNZyWU1mc5G8NfPBug3sRLYzRgbVqO5oFeV8EAeU1gTvake4GijlBcQR5ugaabFMvr9Hvich3iwJnUg6P5UnaE05tASlMA2lTYEbJLUuJyJYTeeedcnmMYYWhO7WFVf/8M8GAPzHl4wu85Fcvnoyuy27dQGViXmJcnN7eFW7hEnn3T8SvDTd++Y+msSEborvROJipoQd0IAYABdpXKIYHzJEE022VzF6ZomKHUoH/MySnLD0H1R0TwVcLybamsjCkBU62myvgYMZkXL4oOmaHB90212Y+oRlM2XZTImU46Dd5ES1TKwqBiYj0SU+aByqtRzu2oLl4ZTtgx16JzXRWOhqitqMwGh8N24tohXMTWNquh0uYEc5OnfEiSEeWVyq2nPXVWi1klWiMYV0pIq+Jl8RZ0uTBeJxoLNWYHKHmdbZbg2IDAHtPUaBqgy946BLg7eWbdtjqZOxUXSogibpVhjl2Si73JCeoacLjAoYxGCgYwp8pDiT9zg17tO9O6Z/vMRMS/wugLli6+D+Cf9h3V1WI4Htl54+b+BxseqJnPfLqyHb6WluvQx6mAuikP3t3/4t73jHO7C1HbDWmp/6qZ/iG77hGy7qwT3ZpbxHZYUMHJ1EXMOgBiFu/lgv3Iiayb0PiPp8ZxdHGS3ATylCGotVJsjPnUQm4ZGpnVigXE45+pKYzokhB/9iHb0+mlPNYJ5ajNgiVx1Tdy9khUvnFRowU4fysdywc492XjQejVDdeUm1DwFdWnThsVszdJVQ9TpMnj5kMJ5KIn1tQYmr5m5s9XmHopTAzkWhqbWtIBUQQFBfM9W4ujUZOk1Qpveyn4ZOV5TteQcvQC7Ihm1XqLWmrp9Tx8/QGWdUewf4jsX7usMVoNiTilNbJQOXR/7XpRMeeBWITo1ga/RI04Ld2lFPNn2sASuP9dzlADJXk63yw+uJdmF26WOPX8kpS6QVJqedcAcjIntVzEMpm+yxR1BWUJkWQQABAABJREFU40ishmutZDAaHxuCFbOS0BWb+qoj/0ZP87ieJ90748hgQuWlc35ms09eKezEYmcaO4uwkeRooRQ+0lRpTQDQFamq0MqzVXWJdIVDhOqnqyFZsFwbrXPG9cmCWAm7oMm92AwbAqkqmRKzGk850B+x8bQeG7MOQcV0Q8DMFDpb0FCGIN0JPwdyqvJiFKMUAd3SryIFdqbqnLDaoTKX+7VLaodPH4i3oXPG1It1obXxV6VDzUqhqTUg0QmVGU8bGtpZg6AMysc8WO3j1GqfXifnoe4yiano2oI90YRN1xWTAwyuXo6buJitImXj6BL7jofa5c3i/W4OzNnqcgn4t196mg/9ecLaNzwTuJk14H3/7eGdiCev/sG+qzs5++/+0VfywVf8Jb99ntkwt//kNzPkEndglFKtdbLWmqWlpR3PLy8vs7GxcUEHcaVUqL3pUfUEur2h+nl4JbRYpgUvMJ/AW7tDI9PmuzRuY8aIA4yWgcwnlhAZpgcTyp7GxZDvd7jEkN/VJ81Kca0p6gk+tZFAVK/IWSUi96KiGHTI9saYwmMyIzds54m2Spm0x3KD13klTjUhoBxUHYMxCrXUwXUtqgq4rsbtW8LkhVgrWwuuCbfU8/Nl4VoY1QISZQ2hcgJMmryaspwHmcGcLhBCDVy0cL0b8LJoZdx0ehbCMwXEhLnRgHeEyRQ7nREGPdweycYJVj6naFzhI0m+NkECPZtuVXxqjFrfIrgFkwSzO+A8Xn0xWSg/1aoBIecLZHbBy7lVvA02AjuRDoCufAsaAKHQao1yrgUpeC+0WSAkkdDGQO6fVrfgpezXnX0XKLuafFVx4wse5Kv23s2SnYplsEvompxPLx/hI/Z63MkBLlJCnV00hzEyhviJZeoSUlthZImH3EcYAmUwdHXBAbvV0sciVbEZukxrillXF0RKFqgkKNJxqLONvcZzuz3AdtnHFDHJmfqUGqMcqDNx6nt9nQejgpbAz0jXJjAaVXq0D4RI49DCGpiWcg61AQ8BdOWxo6K9djLGBJRz6Gk2pztDnecW0JVDhZSgFRYYPuDorhlG64bx9X02Bl3W7TLRUs7TDqzxULYi7mS6YuxSpi7m2GyJezdX2bpjD3s+D50zTvRKAMVuMPKVUG+/QSbL7773Z+Aa4JPf2D538pqfgPsuz3HB1ZcP09TwA/vgA7D9p6f5nn/6IN8++Gf83uifPe7rjt72+gsGL3AeACaEwDOe8QyUUozHYz71qU/t0LvcddddHDx48IIP5IqoyMqgYhR6Y1yHgzWT5YXJdBTLhDmO5EZo5tkuIYR51wVx52roAiGNZaVNifuK68bMDqZM94kFcL4CsxsLbrjuNKN3HpZWtzVQ6nkIpnMt7cpMC9RAUu5VBXZS4RLNbI8l2Xboovb6d6G2CRZ7yqB121Rp8mJQEHSMSxR2JnqU7af3WFnbhqKAPEd1OtJNUfXqlTaouL42uga4UTQP6qyNCBoamLK2BkJuDl7qcDOVpnO3M2rgtxh8po10RoKbu7wt5u48PBR0NMEWpaxgdhPQAu6Upw3PlO6UQ29NUdvj+d9Ba9aw69v/aPUTPyT6i0sNYB6r+/Lw7Xa7MBdWi4DkscDMLnA5vyp7gAWTgXa13q5Z3KpzwOa6xSbccsHEpe6SB6VQocIoJe5dSm7Bs72GYlmz+WxP6FX8w/13cFNykj1mTFfnrLs+n86uoWNKlnozTq32GNwn+8AYQiL3f+UCJgeVGR6YreI7kmkCooOZ+pitqoNWgZFJGfkOy0ZA0til+KAAXWehaAY6Y1SJHjHRFSvJlOv2bnD3tR2SdYPJI3GANLpdfBNa9nysbdzWXGpxXSsdJ10fuzCqRVeUiwW+jDFCg1alQ3lfL1xpuX7e126TD+tyNeOGbQKohYKmy5qhUHiGPqCCFT1pAtWm4fPZQbYOppzu9plUQv8eFzEnjq6QPhiz705PvO0xWW1jXXpCuTueXM46V2H7O553mNe+59F1Ln/yzsOXRAfT1OWkkj3RaoAMbwR4PUc++jb+6KNv4RW3/fiO7W7/yW++KOd4zgDmd37nd3b8fNNNN+34+a//+q/55m/+5id8QJe16jwQ5WoRZSs29GKf1ZR38ruirG2SA6oGM01A5Y7Jd1MhtInJITEUqzGnX6ApVj1mLBSy1932IW4fHcSfcNjtbCd9rFmlqjsOemuKv6YnN3Ytg1+8XaKqQDStsBszcdgapOAk6BKl2v35NMJ3bDuhD1psjrUTu+VioKn2DbFZTvBewEtNr1JxzV12GtKkBWh+qdvadBICKqtQZYXK8rmAn4ZW1mQBVPPOVaivuQ/iutaUtQsTgNBu04ZrgoCc+nHQBiayUqhGhngjJkrjmsoXodrOVinn1pgSNCuTRu/mwDxK/eD3/KMn5X3OFbw8Xj331UcuaQ7M+YKY17z60R3Hfv/dl7ejdbauzC5wubAqlwKoQLwJJg/ovBLqbulkAabR9pWVdB0Ww4xrDWZAqM2N5b5GOia68ARlqXqK655xkhftu48D0RbLZkKkKgyBU9WAT4+OsJ73GGcJ0VjRPV1hR7mEaKayiIaCdNORnrKczAYcSreg7qgciLY4aLc44/rclR2Yn1swZF4oZImuiJSjDOJSFtmKZTPlhnSNo/kKVjvy1HLyum22pstEU4MurVB4c4cOoosMRqIGfGwo+5Z82TLdryn7tIYEyoEuIZpAZ03owYQwBx2lQ48mcr06ibymsWmus9WCEVdOKjcHTdT7cQ6dV/jYorMK5T06t5gsxsWaqqspBprZesLayf2cive1YCra1qweCySbnmjqW61SA4bYzYE5a73LPMS3uEtvo3zD007ye//hOrjClQ5XO5VssY7e9nqO222aUe0f//XvP+Guy2KdM4D5ju/4jsd8/o1vfGKppFdKqcqjJrO5/iX4uUC/0WwkySPpTf5hN6eGEhBHczpULJQAHxuqfky2bCiuK7ju8BlKr7lxuM7nxwf47H+/hWtPjGQlKV+gsmmxNG4m6cp57MzjUoOaygCpfSCdlOhJ3up5glZgNeT1OQLBSEBa2RehY5MX0F4HH4hmnnxfij0V1+FrEEovGTUg7l39Lr6bkB3qUvZk4DW5x8VCdbBZkPyXqSc9nWHOiKZHQXv9mjWxtnO1uErZdFqqqjUFaAM/F13ffJBlyaYWdSw+EKZTKIq6C2RQsxzKsrWpBuZAyNp637srZo9Vl6r7ciHA5Yl0Xy41wGnqsYDL2ba5nGBmF7Q88VIBookiHnuhbbFAm9KqpagGmN8Pm/uZ1q2lP1rXgZZGdB5K4WPN6DpF1Qu85MCdvLh3Vyugd2juK/dyb76foc05OR2SZxHxWImF/agOA4YaUEngcbIJXzi+n5sGp0l0xdTFJLXz1menR3goW+a6zgYH1BYaj1aBVJdMK6GQeRlI8EGzasZEypH7iJFLIYWbVi0fP9AlX47pnEaE+lYLGSA2uI4l2xMxOSh6HrUv58CeLXxQGBXoRCXjIqZyhu1JyviBHsuft/SPI/rG3GMr3y7SqVm9aLZI/27DMhf0qo2utMlm88w7NXUYaLSVY7UimlqSTU33pCx2+lhRJbIfmzmiiZjMqFpPo3OHLirw4Hc7MGetSw1emo7G7/2H61j7yV8Bvu8xt/+mv/4eHs+F6w9OR5cUaJwPlezO77v5UZ/70H9/KT/ytT90WV3edmiKbru4+94l+S9UUAo1ywlZPdNvJrKtm9iC61Zzw1O61QaFEFC1owowBzn1YBQi8fE/+aIeVUecaW6+9iTPX32IzbKDD5o/v/9p9E+FFrgErURD4rxoX6xt9SSqckTbBflKskBJAD0toKxEz9OEhkHt7NK0zOtVqGbOX2cK+EhTdcWSs2109LvovBCP/ubcIovbO2RyXQ9dBlyiiMa+FVX6xOAjocY5rSh7Gh93MKsJ6dExemvcWoUqIDhPaBbDmmP0GpXYeYAnCHhsnMiabbVhbrIwNxFQ1ogBQLOtcwQfUFvjRwBOZS1B+ZY+pqxFxbtC/kerK0n7ci7g5dFAysWifz1WF+ZcgMujve5yd2R268LLTBSdU7Iir0svDlx5fV+2Mh4AqMJAWethGnF5I9xXShaO6oUv0RnK/Sw74GBYoQloPCeqFXqRhDZ+anYtZ4o+J7IBW3mKry2d7WYuC3TdFJwcE1phM0ey6dk+0eG+w3u4oX+GlTrj5PbJIT515jBLScahdFtE68Fi6sGjq0Vr4uobeBYidPAYpIvjgmbsEg52Rlx7eJ31pUO4jpGFro4hKEPZN4wPG7aeWzLct8XXHHqAZ/ROMNDShS+DZWBmnCyXyHzERtXls3sPcXd6mHw5Il0PJNueVIEeTUVvWtWOZ43WaAGUBGtkXLRGOmALrAGdl4TSzbfPC1Q9JpmJUNJalzSr8Vbj01pfWiy6yoGZ5ELhXlzw3K0nvf6PL38ha1/7K+e07Xfe/H8KDeoKrju/72ZelP8XPpw8Nuvpxa/8AB/mAxy4imlpj1UXDcDcfvvtfMM3fAP33HPPxdrlk16qrAjTvLbvVcCC41Wzut+KyBdcwRpv/yaschHAIO4xc1ADo6c5vuK2z3N0ssRKOqXymntGe7mmt8nzjxzl0/ueOdeNNPQCpWS/dagkWkFZYk9uUSzvly5MrR/xSYSuraAxSjjGxuB6kYRJWkltDlZLCFqkQIFLNKb06LEn6AhVBRGN9mP0xoJo3xrcngFbN/fRTcZB7QoDgFEirsxcm9vS8JfLQcT0hiHxZkp0YkvOz9fAoVmgMnPq1o4OibVz8GI0MrKHulsSZHBXug6h9ISKefemSbn2gVCUc0OA2u45hIBKYvyeIa6fUPYtWVzCpV+Yv+rqqRRieak7LxcKXh7++l0gc/VVNIZoGloqkSqFshQiI7SjhUWUYBsRP7Q2/nWXJHi5h+sQ8EGys7JVw/W3HudIb4vrkzVGvgNAV+c8UK6iCUxczLSKKSpDWI/pHw3oaS4LYdOsti9WKKshMkTTQPe44ZN3XUt8S0W3V1AGQ+Etwzhnf2dEVxdkPqKrc4wKRGqbke/UoZYWrTyZjyiCTC0SXTJyKV1dMHMRkXG4FKpUoUvp0udLmq2bNOZ5W3z14QcY2IybO6dYtWMMnolPGJiMVJV0kxxDIAsRe6MxyXMq7juyytrJHv27Ld4o7KiHHmVCW/ZC9W6z1xoLfqUIaqEb07jA1QwAVVY7WRaheezQtVmAMoYQWXRkRENad8yCVqLbMQo1jPCxGMcw0nDHk/O3t1vzeve9P8M38ELc7z1wTtv/p/v++HG3GX5gH9svPf2k070Wuy2PB14W6+StX8GdtwrouZoydx6vLhqAKYqC+++//2Lt7vLU+iaoqA7Veli7181X59uqA8dCk3sCc5pTQ3Vqck/qFZwQabrHDFp5fuLG92EIvH/7S3hofZlToz7baz32P7RwY4V2ZSh4Pw/MdMiEPsuJ1zOK1RRfD4ymzoOB2mGm8gIqCice+ctJ3f7WeKtwsWK21xJNPPHIkZwYY7YL3DBmtjfGJ3MhPtbgl/vMDvUIGpwBArhYYWfSMscoQqRRmcOMclRjFW0UkQ/MDqZs3dRhySji+9akS9Lky8AcQJbVnIIHbVimCPzjObhsgFMIIvJv9Cyu3k+jR2roaXEk3R0jYEfFEe7gCtNreoyusSRbHuUgTJ86XNSrpS6W7uVs1XRIngy6GDxx8LJbV3fFo5oiW4vvQRaXaMAKtbSyub/XOkaQybCqre9p1r4qj3El5UpKlSgOdEcMo4yDdosiGFbNmHXXZ60aMvUxPVPgvGaaxSRrhv5DuSzSQW0s48AlQpv2gXi7YukeUFXMx5LrGNyU07M5e+MxS9GMFTtl1U5a6pghkBHV2TGKgZmR+ajVw6S6ROOZ+hitApMqQatAvs+RDzXaQZUoxtdouret8Y3XfZYVO5FgSFVSBsOm7wJg6rF34hN6OscFxYqd8GUr93NDb52H9izz6f5hlO+QbKYkIWCyvDZCyIVG1tDymiy2xup/IaMsaI3C1Y5lC6BmwSWuce9sKOXKR4TE4GNFMIqqa8iXDdmqJtsLOgc7hfT+6BL+te3WxajX3fe2c952+IF9l1TMfykcyT6cfDMfuuH153WeT0Y9Mkjz3OqcAcyP/diPPebzp0+fPu83vyKrWXVZBCSNDqYBDTB/fjGRHub0p3qVpxEYBiBoTbYaUw4Cf/WXX8L6bT2+7eBH+O49f8Fa0efPPvIlDO824lgSW/R23VlobIYbsFS/X9OdsKe3yQ6Iy5adebzV85ThOvcE6kGxHgh8pAkayq7CxRCPJfwr2axpXU588XWTVl9XSGKm1w7wsSLZEmpEsAo7E09+17UErdCldIlCZKB0+NjgunIDjyYOFyvGRxKWxkPMyU0JpGw0L83gUmck7CitUMrMB5/Fzk1Z59Q0mqWGXubdHIAqXVPXjHyWg4T8mmXylYiipzF5wGaSGxDGu6LL3bqwutjgZZdOdvVVZ80RB4edidUv3os71oIhjAoCTAABNo1msU6mV86hitDa3rtuzObTEibXKvYnI07lA4pgeHp0hlQ5smD4ZLiOtbzPRtHh9KRHMYsYjMBkdTfbB4jMjkBl5TzKaeJtR7ylmZxOOH1tn8RU9FVO3+StPTMepiohVSUuKFJVgIJlM2WkOgz0jHXXZ9lM2XRdtquUSZWwngsYCd2KYGO8VVQdxfQ6x1ceeJAlM2vpaJGqmPoEU2ttQMDLluswduJw1vhxXpuu87TOaVJb8tFTz2B4vyEaWUwTpgxy/69d3nYwIloGQO36Vov7VSW2/mFRwwpyrSrXmvFga01SYqh6BpdoJgckTDTb7wgmEJ8xxFsL9O3desrUpdbCLNZjaV3Op178yg+wffuVQynbfulpvudrHqydy86vzhnA/PIv/zLPf/7zGQ7PjpLG4/FZf39Vlfd1az/MJ7tNsGJN3VLNFfO1U5lWqKh2UWk0MCB5JkCoRYTBSHfk5Jdr3vDq/8K/+dzXcu+ZVfxBzSfyw7xqz8c5+ewBd29ez/LdXjQwO1rY9U3UGKGqNSYD2kBR0r1/m+n1Q+xE+Lw+NpisQuUOn9aOL5WXTnitf7Ejjy4DU2tJNipSJ2FfrhsRtCLbF1OlimQdASNJQrWnT7BgMk80qtB5RTmMcR3TdnGikaspaTU9qy/XwsdarKFjTVS7nM0O9eifGaEqTaj8PF+mafc3QtYGsDQBliAApCjnwaIPH2yc2/lZNlbUSqHiCL88YHrjkLKrMUXAZh5TKEweiDcKSh7Whdut3bqMdaWBmPgXxY40ZI7yjZ+5zEdz5ZUuAkQiCFcBoSZVvtVjhIZ6XNTAIphWVxGUQruAyitUUbYif59G5HsUxbJnfzxiVKXcnh1hvxnRNTNWtePG5BR3TA6yNusznqQwijCZuHTJPdFJtyGJRR9Sd4RU3aGOpoHkjOaOYwc4MRyw2plypLvFdR2Y+piByXCoVp/i0Az1DEAS6ZVn1YwxNe1aq8DJbEDpDUZ51MhiaoPJYqgIJnDfaA8A16Yb9E1GqUy7vzIYpj7GB40PmjJoUl3S1QVbVZeuyomU44VL9/PZpx1kcvcy0STGbsZgtIARELCiFBgZj0RsX7uRLTiINrEHkpppduollSZYI/k0prZ7NprJoYRsRTHbp8gOVpB6dOQI4wg7VURTWRTbrSe/zLdfd07bfdcbvheWz68zcam7MJeqTt76FZdd5/O/v/7refXJT/Fensc3fhR+8wJ0OucMYG666SZ+9Ed/lH/0j85uofqJT3yCF77whef15ldcNdbI1IL8xuzKSYaJsnpOW1oIZJxbAoc5PaBuP6u8gE4KkVj+7vl04Bef/vfItxPSh2J+fvRN6NMx/QcVnTXP9ffPsGtj4e9W87yUsMDTDT7scMoKmUOdrOh6mF03wGS1EN0HaW0nBruVi/1mvdrnrUJbsYyOZpIVo2qbYl1UFHs62IkjaCN2zs5D1zI7lGJysa/UuQA4k3uqnsGbOiFaI/qXesXLdSw+UuhSBnJvFFVHoyso+xq3MkA/OKltqc1c0xJHc+e35ho01qPGtACy1bD4sg6irI0VGsMFHwTkhPkqGnHE7LoBPlJ0TpeY3NUhcXXQ5aSEYnYp/9p26yz1H18yOi8a2YW4jz1ZrmNPtWoAy26dW6mAyPS0qqliQjHCKEKT5qUUwelW+wLIxJog6fQN9TiO8IOUfG/K+JaC/uoUTeCZvRPckh6nwHB/NeREtcTHJjdwJu9xeruPO9mhc1KzdG+JOb4u1vS1DiQkdoEaFVBVQFmIR55kXVM81OX0SsRGt0e2N6JjSno2pwyGrapLaQypqkh0SRYiJlVCFuYUMoDMR6zlfazy5EBqKnQp4MzFkK8AAY6PBsyqiGRPhY5lor9qxzh0G8oZ6YoymDajpgyG3FvWygEGz0o04Za9p/jkdUt0zhjS2Na5On7eZUGc10Izti5mkrWZPHMKd1CqzV1rwkQXKyhF1bOMrtGMbynp752wL5Y5RGQc02HM9qBDMB26s52v3a1LW++z2wCscW7i/ZPf7Dl/EhP8+Lv6ADzt9S/k+9f+7AL2cPb6g9NRezwXq/typdQ7XnUYTn5qx+/eO3zeeWfgnDOAue222/jYxz72qACmCXG8mis4D1YmxEqp2v3KzzNdIit0Ja1kFat1wFrYR1HWKfSVTKLbIEsHKqL/QEbyuykEiEaSU2KykTiHVU5SmButRmMCUFXzib1DHjeT90Zr4xz6zCYdo5jcMJAuCLWLjaftwqACdlahC02xZFvnr2LJEo0dduwFAFQB1zUiPp3moBRuqYOZeeKtAjMpZLXQKLQP6MISj8U+2XUMwWrspMInFu08uhTAE4wWt7NEUXZr15qDXXonIrneIABR+7nzWrNSabTogGpBZiir9rGi/rwa955aOLujnANrUVFEdWCJYmDaVTEfyznrog4yy0uqZDcH5kqtJxpauQtizq12QcsTKZkAh5bOqgnG4CMxXFG+DhhOozqgMdQWvvXLNQRtULnCdxNGN/Yo+hrbmRHbir8483Se1j/DXjviwWIPI5dypuzx4dM3cOLMEn4tYXiPZs9ncpKjW4S8kMBgpQjdVFgBpnavrGnOygXs1DE4BioYykHMbL/lgXIVgMO9LfYmYxJdcboYsBxNuS45w8h1yIKlqwtGPiXzEVOfcF+2h+PTIduZ0L6mNiLa0ujKU3YVyoEZG8bbHXpJgVaBrsnZZ+X7PfFJSxnzQaMJLZDZKvuUwdBVQjvLfcThzha337zN9OgS/YdibFFBEVor6jlIrFkODZPBLoA5owlJJD8bRTAWVQdAB2OE1lc6qBR+kDA5GDG+peSbXvAJjiSbJLrkVDHEoXlwusL6oMtdJ65Fr+xSyK60eveZv+A/va0R7f/sBe2j0W68723b/Playd95fX5Rju3Af9GwfFF2dda68/tu5uZfv/PSvcGj1DtedXZdz5cf6TF8zyXqwLzlLW8hzx/9g3ne856Hf3gWylVWyuj55BlEawE77IvFhUzNqUx1Ar10bOocE61l+3qlP0SW4vCQM7embN/s6T2oOfihiQjcvZdOC0iru9GA1DSp0Fg4N90JV+ebmEYvYlqqWZjNUEdL+pVnesOQoCN8pEnOZPjYoAwoo1CFxwaHS7SI/jOPmVVUXSuAI6/QpcfHlu5DU7GW7qZUvYhoLLSxoDUh0rhu1FIkyq4iW9Uor+mcEVtkXQXMtJLOS8eiCt9ysRsDgWyPobsyhNMbc2BWBjDU13EObFSa1Lzl0LroNFQ/tRhK9nBdUvOZaQVxRL6aoKtANPFoJ7qhfG9ENKooh5Y4NVTlQpDmbj0p9VjdlycKWh5eFxPELFooX0rx/pVGI9utRy9vNUSKUKfIByv3TLQioCXgF9/qXlSonS/bHdS0rnphcHyNIdsT6HRzYusYFwmf2TjEiWyAVoFj4yXWtnvko4T4eMT+zwSW7thEr20RZjNxX9RKcryKUqjPhWttfrULkFrZZivQB4qRBq8ZLxmmZcT9oxUeGK1ww3CdRFd4eizZKSfyJY4km7XAXqNVaHNpNqYdtscdet2ctaNL7Dkui0tlT6FLMDm4UrOSzugb6fC4oMhCzNTHjFyKUZ7MReyNRhgCWy7FoTF4Iu1wQRMpx9BmvODQUT62ukTVs5iJlfEiBJRfABCLJjltrlitFbULC1cuzC2Tm1L1Z2o15cAyPqLYd3iT/fGIJTMlUo4ocZwqhySmYjmZkT5tRL4ZX/w/st16RHU2zwDwLe7nH3fbyZ7Hdxw713p5NeTOn74Z9sI9b/sYb/mWJyarmC3v2fHzgdv/SqhfV3E9GngB+JujE97xqsO89j3nTsk7557mwYMHuf766895x+dSH/zgB/mmb/omDh8+jFKKd7/73TueDyHw//w//w+HDh2i0+nwspe9jDvv3IkY19fXee1rX8twOGR5eZnv/M7vvHA9jn9YBynUHYCH6zCgFYYra9vOU3ALFspGi/bFGvIjS5x+fsr0SCC+ZkKxJO5gITEicm+cykIgdCTVnqqSrBdrayctXYsva/etxQ5MQ2lrQNPaBt071zG5F+CQ1N2XIBxs1dhABojGFdF2QYg0Pm7CucQxLN6qsKe3xXmslwrtLK9kHyGgShHxu0hjckc89phCuL6Ns9nitTXTqk43Fj52NHLYmWxbrnbn56nr8LHWEKE+vwaI6LlttTi92R3WyyCgM9SuZeIMV4PSOqfHRwKe5JoEovVMcglSQ7xZ4VJNvnJlxCRdcd+TS1SPRx27FA5lz331kfbfbl3ddaV9T3QVJBerqJPY63tXsE1Hpt7Qyz2ZSpLk1axE5SV6mkFeiOjcaqoOuBszrlvepBuVdGxJP86ZVjHHxksEYNjLSIc5diK5XIQg44s2QoNOE8KgS+ilAqjq+6YKQh3W9fhgZhXxVkX3VEX3VCA+YTl9/wrHv7CPE5/Zz19+/ul85MS13L55gDvGhzhdSDekCJYsROQ+oqsL+janE5dY68jyiO79EZ01TzR2KAc+gaoXWN475qbBaVbthK4uWHd9pj4mUo5r4nVcrXvZqrqcLIdsll1O5QPKYDhdDFrKWqpLDqVb5HsdVVfLwl1ZyfVtMtpqIf5ZnUbbD0/PFwqVanN7QlLrX6w4mrlY4VI42B+1oZ+RqjB49toxz+yd4GC6zTP2nsLdcOVQkq+078rFrHfvjfj7X/d1fOMrPvC4/y52Hbj9rzhw+18B8FPf9zr+/G0JS8vnv6B1NvexSwFetl965Zlv/ftXHjznbS8rKXMymfC85z2PX/u1Xzvr8//6X/9rfuVXfoW3vvWtfPjDH6bX6/Hyl7+cLJuvjL/2ta/ls5/9LP/jf/wP/ut//a988IMf5PWvf/2FHdCi/qIuZeqskAbELIZYGr0jp0QZLbqNOtHX9zqU+wdsXx+T7Q0M7gH7kQHpGZgdSHjw65bYeM4SIa4TmY1uQ7VC7TwWFrtejaajmaw3E/hmot+4lfkAWyPie0+RHh/jY02xGksQ2gKP184qglaUg5gqNbhUbJXLgXRVkvvXoXKEyAoFLVBnuui54QE1GFMKO3Ekm4F03ZOuO3onSuyolHDNrELNpF0vji3S0bIzTzwO+MTIymDTJVFqJ6BswEjTdWqdesSdrRXqg3RqrJXPowFCzc9aE1JxwFFeqHNVz5If6Mp5GAhWUaWafHhlcJavuO/JRa5/+GeDS2qfvFtfHHWlfU+ke0KtL5xnjASt8FF9L2q7w3NNjPI14KlF536py/bTe0yvrXj6wdPcMjiJVgGlArGumJYxlddM85jYOJxT+Eg0kLjGBlg6zyGO8L0En1pcT+x/g6mF62VVA6cCPS6wmznRZk7vWMGezwb2fdiw7yOapTsVyYMxoxMDHjy9wuc397NZdLk/28PxYpmxS3EoEeB7GavyUYL6fI/+g3JPz5cM+QpkByv0gYxrlzdb7UwZDIaAIdDTuYCSeJMlM2PskjZAc2Az+iZHE9gsO+1r14seIfZkS5J9tmhTHRqTmJauvHDtG3ey5uf6s5FxYa5Paqyvg5WFMB8HdH28kaowKuDQrNox18TrXJesc11vgxde9+AF/R1dirrSvisXs572+hfyX//opef072JP4Icf2MfwA/t4eTXkZV/9P5kt7+Ff2LvPax+/tvclO36+lCDjau/oXNYl5le84hW84hWvOOtzIQR+6Zd+iZ/92Z/lVa96FQBvf/vbOXDgAO9+97t5zWtew+23384f//Ef85GPfITbbrsNgF/91V/lla98JW9+85s5fPg8PbSDB0WtdZmHMNYHJDe4wglJuaFw1ba8qnYda0InAdwgYeOWDut/p+C2m+7jo8s3oVdyvvz6+/nwPTdwcN8WsXFkb95H59689v0XCplyet5BCKHW2tTuKM0xNQL3pgvTGAl4B0FJ9+hoRnomxR1cwaUWl8qEXRfSRfGR3ISLgUG5QL5i6T84wx5dJxRibayswXWtBF0mBg2oqaNcSmvrSOEyN1QyHyniUwV6Jg5lJnPoopLuTseCC0z3WbZuhn0fF5tnXUjXibLY+Zm0dtX1z07ObQe4aVzIGj1Q81kaWXmkqgBHCLUZwzQjGjuqnpyzrykezXm4pF5Z61wZnOUr7nvyFK1H68I8Fs3s4a/ZzX65fHWlfU9cpAmJRhcaiDB1B0bnrp0Y48UxEkDPqvnkuhHvdxPGN/QZXadZPrzJ04drfGn/fhJdcabsMbQZsXEcTLf58KnrqbzGlQajoOrUCzBao7odcRzrJnOr5tq0ZZG1Buygrnmj0VUg3nJERoGC3Gs6JzRmJpTjY3sTjkaeT0fXEHULjuzZ4kB3hFWeo5Mljt27l+EdluEDjmjiKIaGrZs0+TNmPOPwaSLjGEYyMW5smgG08qzne9kbjch9hEOxYqcY5XFoBiajbzKW7Iy7pvtJdMlW0WHiYlShMWU9vg06ollpcl3O1n2RP5JHPg4BauqZ8l4eq9qUQakaoMKJyYDRcsrhaAOtPEeiDVzQOBRdnbM/GlElF0cbcTHqSvuuXKzqbJ7hufVj7f7lY257/B+84UmxEhadiVyPO7/vZn72o0M2bnjvI7b7tb0v4eZfv5OHy/WvdpBxKevK4Micpe69915OnDjBy172svZ3S0tLvOhFL+JDH/oQr3nNa/jQhz7E8vJy+wUCeNnLXobWmg9/+MN88zd/81n3nef5Dj3P9vb2judDUQo9qQEyUDuTuIWVfz/viDSOZAte8cFopodT1p/veeb1x0lNyc3PPErHltzQPcNfbz2DjTsOMru24sbgxa1ML4RrNaDF2p0dBl3fWJWed4Bc7ZjmG6qbm0/w44iQF+i7j2LShDDoYZa6uMTgUrE5Vk6cuKL1DLM1gbzYaR3pPcHIBL/sWuLSUw1Tqq5htmqENqYhGnlmq3JTL7sW+hYz8+hCrJxDZCiHMUHL6mA01lSpdEJ0KQGVRDUQLAs59wUXMgEkdYes6ZYtfm7OofQiuHE7KGeEUAtZE5IzGeWghzcKXUhatsmRc0w0oQ7ovNLrcn5PLkZdDZ2XRZDSgJldytnVVZfje6LC3CBENxTe0stjqMFKaKnEqnSorA6bjCVQ2XVjir7GxfC8fSd4bu9BXtK5H4PnU9NribRjbzxhVKZ0o5KHzixjjqaka2CnvnWzDN20pSo34cbKy/Go8LAbnVFQyfHqhi7cbOMCdmLongSfaPKhITtt8LGhSqFYibg/txyNl6nWU+y2Zs9d0D9WtnS6sGQolj3XHVznlqWTVLXmpWOkQ99qXnxEqktSVbLmBqS6ZNVOOFkOMXgezFbYF49ZslOGVjJkTuYDKq/RuUJXYHI3Z0xYI+Cl0b8sjNdNJyY0TIuaRbH4Oe4ANUYTrMKUgXRNc+rUEqf3DbglPc5QZ3R1jsEz8QmlsTg0D4TOuf/BXsa6VN+VJ2M8Afj//qvfqB8tP+Z2lyMHpRHNb/ckP+bX9r6Ee972MV5eDR8BXODSu49dDhH/xawrFsCcOHECgAMHDuz4/YEDB9rnTpw4wf79+3c8b61ldXW13eZs9S//5b/k537u587+pA+tmD8UpTwuq/kkuKmGvhTFra9+235Wimr/kGMvgeufeYKNrMNdJ/Yx6M/QCu7fXGH5M5rh/SXqYxCfmRHiSBzIFrJfhAIVyTy6qsAtHEcDolgQuoeFlbsQpCvUiP+1ko7KmQKzPUaHQBxFLe0sOC/86NlMwJEXx67QhpzVdIiGApEYSW+eeOxUAI7ygXTTtwCFIIGWygd8YgmRpupoTOFJtjzphqMYGHGjyRcyWxrjgkZbVBsktCDOMH/c2iQrcSRrnm+6Uo3ttfxxoOpBXG9O6JyOmO2LcR1NtC1GA3YC2R4LVmGyKx/BXLbvyRdpfbEBl+InP/mUcCK7HN8T5cQgxc4cdlKit2eSvxLNjVeUc6iZJ1T1ItbCxBmlCLEmX1VUzx7zzP4Jro3PUAZ4ZnyCu/IDbJRd1osu4yphO0vxTmMKGD5Q0Tk+ka5+U62NcG3RDBJY3IrZdd198e0kX81KMX4pa1dLIzbzKgTYDsQbms5pi0sNVUeRL2nytZR4K9A544lGpXTYXRD7/K6hGGhcz7EUZ2gVWLUTALq64Jr4DGvVEIdCE7gxOUWsHEt22p5GVxdCJVOBMhjGLmUlkuc7pmQ976ErhZ06VOGlo9Nkvfiwc3GuudbN+VZuDmS8B6dAh1ZDivZirRwc2geibU3vuCLbE/M/u8/gpmedRNf2l0In8/R0zulqwKS6OkT8l+q78mSMJ/9x+HeZ8u07fvf6n9hsH7/tzcvz3z12g+aSVgOeBJ48unnzZ/5dzLN/oHjU56+2eu17jrH90tO8d3hxxpQrg+T/JNc/+Sf/hK2trfbfgw8ucFPb1Xq/43c7LH59mHcBaspTKEvphlQVRJbpoYQbv+Q4X7r6INvTFO7vMvn4HkYf24v64xV6pzw2cyQnp+hZWYs4nYAMM7cCbgX7zs11OLU+pLUYDl6OT+l2sq5MPXmHuU6nppuFspTXd2o6QZ1SH6bT+bm7hXAvozGZIxpLVorrWulOKIhGDpMLaJnts9ipx+Q18FAIDSGxBCPhbD4S+2QVAigBOqYI6FHz3mF+zH4ByDXX3DkR6DedmUUNUAMqg9+hfWm7ZlXV+v8r57EbM5KNCl0EfKLRucPkjnS9IpoE9Fze9EVZj/k92a3LUrsOZFdePdb3RLuAmZboSS4AJQQRgCvpggDiCDbJUFmBmmYwy1Djad0Jh/G1ni+99iG2qg4fn97A7229kD/Yuo1PbR/hExvX8JnTB/ncQ4dYOz3An0zpnFJ0Hxyjz2zLAlYzfoDoF0NAlQ6dl6i8vsnV91ehSQlVWVVeBPBFJd2h0qELh5mVmFGO2ZphN6YkJyZ0H9hmcNeY1c9OOfA3GXs+M6N/95j0xIRou2i72T7SuATwMKli+iZnyU5JdSldlxBTBoMPmr3RCI9GK89Bu8XhaINEl3gUkZ5TwBJVsVV1eCDfQ6IrDnW2ibYV8ajEzMqdHaZQj9uN+UsdNE0czS34m/HEh/kMqaGeVR5dXw9dOOy0Ih450jVFcbzHp0fXtG818h1GvsO2S8l9xNglF+1v7mqsJ2M8cQ/9EP+1+83tv4fX639ik72/+ENM9rz5or/3parP/LurA/iea13Mztd5d2Ccc/zu7/4u73//+zl16tQjrJP/9E//9KIc2MGD4kRw8uRJDh061P7+5MmTPP/5z2+3OXXq1I7XVVXF+vp6+/qzVZIkJMlZbiY+EPCt61jT2QhNFwPmK/6NvkKbeTfAB4gt5AXxZsXGtMPpXp/wt0vsv8NhcnHfClrhYyV0gvFMwEtRihtNI15PYshyQpbPJ+i1DeaOqq2VldF1J8Wh4lgeN50LF6SL1JQKoDxqPJX9m5q6ttjVWABDVA6zlVEsD1retI81VVpTI2Ye5WBwX4YKMD2YYOpwTJ+YFuyUfUOVKDprDps58uUI5aF3vERNZjLGNaClBmbtcej535nyNbhrAEujVfJBgiyDlvAxpYH5cxjdCvnxHj2aYdOIqtPBxZqwEhNvFESbGbqKKZeufFvwy/I9uUx1sW2Ud+vc6qnQhbkc35OgFgT8ShEiK0HBWTWfEDf0Ja3BOChL6YZ309o1S+53sa64c7Sf1JZc311n5iJOz/psTjs4p/GVwp6O6ZxQDO+v0FsTwngi9/Z67Apa3MyCSFnm4v7m/yaxvjmmhe6Nck3not6m0ZP4utsOkCp0KXpH5QKqELt95WuKbimdGDszqFITaceqnRAph9HSTTlVDsm8hGF2dcFDxSqHok0iVUEw+KBasb8mtI8j5ci95UQ25O6NPXSPB+xm1naO5CTkM5AxttaTNprVZlyAOvxStbk4QSkxOKh/D6AwkqEWxG0uHgXiTc3nN/fzoqUeQ51RBEPmI0a+w1rZp2oo3ld4XarvyqUeT7Zfepr3/sZv8o38lx2/f9ubl/mmv/4e/voZcg/7uurqAS9v+vGv4mff8heX+zCe1Hrh4e45b3ve36gf/uEf5od/+IdxzvHsZz+b5z3veTv+Xay68cYbOXjwIO9///vb321vb/PhD3+YF7/4xQC8+MUvZnNzk4997GPtNn/6p3+K954XvehF5/2ei0GczQp/KCUDZh5suSDsb7Qp7Yvmeo14I6P8iz38+eeeQe9YIBo7kjM5pvCSPp9oTO3KRVHueN+Q5YTJdN5NaEDNor6jCdus7ZRDWQl4MUa6OPCwVrlk1czdzQqhizXOXiAhZ20qcW3l7Dwhy9ATsYDM9hjyFcvkwDwEMxjFbI8I/X2sUR5cavCJxqWaYtkyPhKTLUtwpI8Vqqo7MAGSk+P59aw7TSGEeZelpriFBoRFdp7ZU1+P4LyAF9iZB6MXrl29T+mUOShKdF7hEoW3EDQUKzFNkKfNrnwAczm+J5ejrhbwstshuTLrcnxPGhcyQLouaSIr/mXVLljt0FXUDosqTQj9Ln7YxRuNmSk+c/oQnz16iM+eOsikSljL+5za7rO11WW61SHkhvS0YvXzJd17twnjaTsOKF2DGKvnblpWix1wkyPW5Gq1gKoGNk1OWVm1LmU7gBfsGGdUUQmjYCraG1XrfHTuMJMSu5nTOePQFTiva6CScyDaYsVOSHTJkp2yZKcCWoCpT9hyPbZcj6lPGLmUSDmWoyljl5B7S9/kODSnpgNGn91D71Qlx9AEQzd20tZIzktzro0JjnvYZ7HwT9Ud+/m29fnX+iBdemwWiEZwamPARtUT7UuweDRjl4rt87R/3n9Dl6Ou5jEl+d6zr+6/9Pk/y//2hU9yo+k9yUf0xOoDn3jTJaOQXan6l/2f/5/nvO15d2B+//d/n3e+85288pWvPN+XPqLG4zF33XVX+/O9997LJz7xCVZXV7nuuuv4kR/5Ed70pjdx8803c+ONN/LGN76Rw4cP8+pXvxqAW2+9la//+q/nu7/7u3nrW99KWZb8wA/8AK95zWuekAtGQxcLzi2k80oCb9uJMY/EfsrOL6dZH3PwwzHHbIeNZ3lGN8SkazF2FhhfqxjeKytxjW0yShH8Qhek0W8YM18hg/n/9WqeqrUei+n07TFr3QKd9v96H4qFTk6jmykXwjIBIqFdYSUMLN4sGR+yrfA+GntM4cn2RJgiUPYM0QTsVFa1ZnsNyktgZZVCNA3YXFy/JocTgoH+0Ry1ORJqV+Mc1uh3ms+hyeJpqWQ1NS5U83PyXq4BzDtHzsmCYWRrFzdqwGlkn1q6U8lGRbY3ouooTB6oepFoes7mVHMZ6kr9nuzWk1u74Oix60r7nugyEFKFSy0GUK6S+1TlZBJddwJa98mybLsxDdAwuWNwH2z0VwirBTNi7tyWSZrWYqWM9SQPpHRPBDoPjtBrG4Sy2DF2AXX6vJNgRltTyYKD0tfhybU2xss9sq0FXWZbtTYSX3crTEAVjQtmnTVW71N5T8CI2UwImNyTnLE8sL7C+t4eSVzWYEVW5w2BVTNm5DttN2bFThi7lL7JmPqYFTvhaL7SHs4dkwNi5fzQXlbvATuRsVuVNW1YS44L1MCy7bzUYMbM9as7RP6NuF+reRBmQ8OrrZmVD0RTT7ytGG8lHM2XuTE5RU+LYH296jO0M0JY4UqpK+27cjFq+IF9/AG/CZ/7dQB+99nfxv/1mXcC8K9+9Et4KT/LBz7xV8CTL96/0Bp+YB933npphfyXo75p+5MXRQdz3gAmjmNuuummJ/zGAB/96Ed56Utf2v78Yz/2YwB8x3d8B7/7u7/LT/3UTzGZTHj961/P5uYmX/VVX8Uf//Efk6Zp+5p3vOMd/MAP/ABf+7Vfi9aab/3Wb+VXfuVXLsrxNVQsQP5fBBHNDb1ptev6ZlZ3RZT3xA9ucOivFKe+NGV0c0U5lNW0asnR+5BHTWZ1qny9gtVkBYQFF7H6vYPz88m6MXPBe3M81FQ2rVsHNQWw0Jlhkdv7cBevpktxFmDW+OHbk1sMe5ZiIM5jpvDo3OGNUMGi0dxkQMT7RsBLB9J1Efp7K9kv2bKms+6Jjm2JWUISt90kOT7VUtuUUgJKGh53I0bdAchM+5xqLZTtXDujGspDmA/oSYwqK+F154YqFUvpfDWiShWuuDIAzJX+PXki9R9fMnpcJ7KrpfvyVK6rgUZ2pX1PTFahjZfui1boLJcORuPq1VCZqlqXWFXSBTe6Db7UWUnvZEywhtGNCe5IhtGeAx35TqzZLuvHl+geDwzvnaEePIkbTyB4VBzX2VpK3MhCQEVy7/SdCB9bjAuENJpToxqRe0Mrbib0zURe1V0JH+Zjl9a1dqZhB9Qd/RoohKjb6muCltDjdC2wcarLx/Zfx9/bO2Gq5tSiJTNl2UwpgyXVJV0tK9CrdowLmv3RNlMfo1Wgb3KM8lTeMCoSunfGDB4shaodWTmWBiyCAJlYtbQxtdB5CTWIUQtju1hd0y73KR/kGvgASrovPoCZeTrrivi04fNbB3jR4B56OseF+Xg6zq8cOu6V9l25WPUPrvseDv2S4vPvOcVP7NvPTzSn+InjfDC//7Ie25VUl7v7MvzAPt7xqrMD3ZveoeC6c9uPCuHhSyuPXW95y1u45557+Hf/7t/NJ5BXeW1vb7O0tMTXLv+fWNuZ60UW6UdNZ2JxAtxs00ywGwATgnRjauvGkMSU+/pUPcvW02Syf+CDayLYLMraPtnVlsi1k9iitmaBqrYDyNTmAkJvc6g0EcCy4GK2KHZXTRJ0WQk4q8X/i52jHbqShW6TqtPuw1Kf7PCAYDV2LCuGswMxduaJtkqqnsWloo+Z7dH4GPrHPLqSADAXK7QTbvHwM2dQ22PpPDVAsdHgNI99cyx658+L16PpzDSfV2R3rhou2jCDDFL1+ZDE+EGH/ECPfMkQbzuKJUs+VIRpxife8TNsbW0xHD66U8gXSzXfk0tVjwZkrkYAc7HzYK6E7sujAZiQOco3fmb3e1JX8z15yYt+BhN3UD6gZxVmc9x2LICWttSYqgByD48svpvi+3ErKC+WY0bXWKaHFMWKJ712RGwdRWXI7xtw6C8Cg0+fIpxca50kdSdF9boyvkRWrJnrMcnHFt+x6MLNzQRANCPeE4wRUNLcQxtwskitaqhlag4IUGpOMWuCgzsJwWpU6QjG4AYJs0MpmzcZJs/KeOZ1J7ihv86yndI3OTelJ0hVybrrc7oaMNCSEbNqx/ig2XRdpj7hZDnkeDZkWsWcmg44/omD7PvbwODeSX3NBSz6roigfWTEErry83OuvHTaKyfn05yj1gRrCGkk+p+82OlQ1nyGkSXElmopoRhGrN9iGX9Jwdd8yR182fBeTpZLjF3CetHjf33mGu77zjftfk/qutTjyaFfks/og1+QBfcDt//VZbFOvhh1Me2ULzd4aerR3Mi+81f/kuy6G8/pe3LeHZi/+Iu/4AMf+AB/9Ed/xLOe9SyiKNrx/Lve9a7z3eWVU8ai+j38+mY7+W9F9S1tKcypRXXnQ0WRtKmLsh1wRPivUVGEcp74wZzYeTr3pjKBnmZCGQBCnu/kHkOtp5HODkYTGrcYt2Bv7EHFUevO1Qj3YcG5C9qVvlBTpuT4inm3pnmd96iamhZCmJPMQiBkmYAgIE4ixk/r46MYM3MQIChFOYwoe5p8SeNShZ0GmImY1VuFi6BKFZ0Nz+D2ddjcFoq4c3NA0ZT3ck0b//7mmixaWjerhWrh5waALXapGjDW/GzM/LOtXXai7QJvElxHRKe6Us2l2q0nqRaBSgNmrkbwAgI4LhaIuRLAC1wdXZgrqtS8G62Lan6vWtSOLAYRe0fIcplkRxZ8JBN/L0G/vVMOXRrCQwr3hSV8ApGD1Yccw0+cIGxs1u+h5fUNPaoRrDfvW1aoer/BSqJ8M6EPSiyTVaPJWQxyrif2zX5C061wvna8rKcTjeslyPZlhc5qulk3RTlPtF2xfBfoMuWO7Wuxz/X0Bjle5PF4NF2dM9BCIVs2U7IQkfmILER0dc418Qb3T1e5Z2MPs7/dw747PN2TBbpwBKWollLKYUzZkzDOqqMxeSDeqlp9ki69OIpNS1Q1E/DV6GRqy2hAxoymS+W8LKQ1Qn8AF6NcINkIVPfFfDC9CZ4Ggzqg8+nd03xhb5/7Lvof2W49Wh3/EfnsbqaZsF+d4AUEdFwMEHPg9iuHQvdoXZi7Xhu45izbn63OG8AsLy8/aqDXVV9liV9bl8eLk36aX6m5eBzmXYBGu9LksTTdmka/UlWEshQwsz1un28E9S21STMHHbrefxnazg6N4LLWsAQnNpdyEGEu7K/F6q3bSlN1u78FLtAeg7KWANKdMUZ+bmyaTVR3mAwhyzCnNuh2LNPDKWU3QruASyU4TAURw5tZIB55tKvBSwy6hOW7c+Kjm6jRZM5BtlZW6fodXDeSjJkqoPMKVXrMxohQmwgQ1X+yNaVP1TSxVq/kQuvIhjGEoqEz1Neh6TZp0Rwp71HTDOMDiQ8UqynFXjEiiKZXvoj/qVpXK3BZrIsBYs4GXr6v+N2zbvvr8f/1hN7rXGoXxJx7hdqkpL0HGyOPm7wvkMWsNK0F5Qsr+yHgY0O+J0Y1DWkH6aZ0s0Eou7pw6LyCWda+ThZt/LyTHc8pYk2XJESm1W801OfGNQyroXHvWtSENP9Axp3KzUHYAiugYRQsakmC0S3YMZMC5QN25lA+JmjLZwZHsE9zHOyMmLqY/fE2pnZAWLVjUl1QOoNDk/uIU5WszH5+bT+zT6wyvDcQTTzlwOLSHsVAMzlkmO0PuDSgSy1IIyjS0wnxKGBnAZsF7MQTdSwmMuhJtpPSrcI8TLkR/rcfcH1uWsvnHCCaBTqnYdTv8InBYZ6+cgaAtbzPQyevHA3Mbl19dfOv38lP/sZdvP7Tr7jg118p4KWp177n2CNAzDV//rRzfv15A5jf+Z3fOd+XXDUVnJPJup87WgGtpgSYr/IvisIbF5PYAAvghQYg+HY1LBSl6DriaIf7WP1G824D7NhPG97YZNLU3ZLGcGAHDawWtIdmAKnpYzu6MzAX/De0t8jueO+2C+VqTnRZgNKEqiK69yTDrSVGz1imGGjsTI7DxQpTAAHyoSaaBlSA7qmK5NgYvTWei1Wtxa8OqJZTXGKoupKPYHJP2dNUnZSyB93TfToncqIzE+lcVY4wnc2vv1YoE88HbGvnoLC+Hi1wac6l6cY0q2p5gdmCJEDQKT5S+F0As1tPsC4UxJwPcDnb85cSzOyCmHMr5QIKoSuFVnPh5gYiNc04pPG8U7LoBFbnZgH4OihYO8TBUSNUqMY9rJPKuAKoJJnbJ7saZMRRq20JTYhm/XqF7Iv6eAliHdyE/i7aKQNzdzLv5+diJE8laCUmBa12cU4va7rtOIcGVFHRKR0mS1FVwic3ns79N61z/dIGm50usa7YH43oahHzr7s+G1UPTeCO0QE+ce+19D+Vsvd+12aP5UPN5IhmfEvBYM82h3tTOrZkI+uwks5wXjMuY9a2+pRrHaJNTXrakGxYOusRyRmL3cpQs1y6MIt0uVrnukP/GllCKu6bPlHkQ0XZU9gxrD+0zNaoi7WOfK1D93Nf5MFiu/WE6xe/9yZefwGdmEejjb3wR7+HY9e/7TFf+8Ev3HRJaWeLgv7XvufYeb32vAFMU6dPn+bzn/88ALfccgv79l1ZyO6Cqh5ElDHtiv7c5SrM2+m1rTLWSmclTeY2jE54vgBKa1nlX+DMtha/9e9DtTDpbuhPQJtGD3MDgbrToIx5RGbKDsc0reeW0GfpJLUdi2bfO6hboaWTEeYUs3nivdAFgg+o7QmDz5T4YYdqkBCMwsw8ygVM5tCVx2xMZbVulhFqYNgIVatDK0yu6eAi0cWY3BNNHWZaEW8GykFE1ZMcmWx/QrESE40r7HaOWY9kn1VFyAuo83uC8yhf5+UoPXcve5ieSWkNOppPGsoKBehtSEMg35OSDRauy27t1gVWA0YeD8g8FlXs8cDLo21/qYDMLog5h9JqDgycazUUqtuRyTGgCgkxDjUICKlQspv7tZ3UCnIFeLlHNrkrrmsprUK5QGyWMN1UAjB9IHTlHhuabo81rQsXWku4cKTRs6p1E1POiVuY1W0XImiNUn5+n1SqPY+2U7FAK2syb1RtVRwW7r2txkQpMW5RClM60rxib9mlcyZic7SHjx9aYu+hLfpJzr7OmIHdR+4t22XK3Wt7mG506Nwbs3I6kG56lIeir8lWNds3ezrXbfF3Dj1I3xb0TM7MxdihI1KuFf1nByNO3jDk+GzIF07sY3ZfD3+3gSBCe1vNFzAXO08o1X52xFFLU8tWDGVPka8ofFR3y05Y3KahigLJRBOPHrZguVu7dQHVgInHo5S9JvkaPvZvf/OszzX6oGM8NngB+LvPuItDv6Q4fP/rH3V/T6SeiC7pvAHMZDLhB3/wB3n729/ehlgaY3jd617Hr/7qr9LtnnsIzRVX3tc33trVasekVwYYFUX41QGzwwN8pNrVsGhcoXOHHheSXlw7tKiFdF9VOenkNN2BqkJ1OnO75MVWPMjEvHEYA9BeOg0wtwyu+cbKiDXwDjACsnq00J1puzCL3ZtG7F+Xari9C3S5kOfSNWpKKwlKm07R22OSdqXNzOkDD7ffdE5ccYDi2j2UgwhdipYnPZWLMcCkrEWkGjupCFqcYFyicLEiLFmKJUu0lBJtCJ1tUWiqrJ53yLwDP/9ZRRqiSAb2TiJC1drGWjV5Ac6ht6YkIVAuOMjs1m490bpQLcv5gpezvfZCgczDQUrxk5/c8XgXxDxG+brLUZTt5D10EtwgbXUnAh7A9aK64yIZYQ1ocUkzfiBUsjo8sexpir6YpMg4FBGPu8TjJXm+K69LtlxroKIrWVjCB1xqQSFamADBAB6xWFYKZRRUcl9UNVMgxDU1LBdXsNBM8rUmpPE8K6VZNKotoWVh0LWuYKpy7T6JxKI/KSriMxHdU13yJcP0wF5ODeHBPR68wk4VJoP+0cDq2GPykqAkEDofaEY3KqpnTLn54Gm+dv8d7LNCQR25DlMfk+iSVJUsmykOTaQqpmnC/elehlHG7Z0DbLOCtwblY3QhY5jOKsC1wCV0YrGgVopqEDM5FDM5qJkdCFQDV9PAIdoymJki2ZDrqSuhUO/Wbl2sevyuyNmfb8DL+dax69/GoV9SrbboQusdrzrMf/6y7+RfHft93nD4NbzrZ3/hgvd13gDmx37sx/izP/sz3vve9/KVX/mVgAj7f+iHfogf//Ef5zd+4zcu+GAud6nISiek6TSATMjjCJYGlAeGzA7EFD0tOo9CJt/BQL5k8EZh8y7xloCKaFzVifVGAE7p2hW5EMnEuupGqBBwsUaXATOrsJtT1HgmlN2qgtjOM02aWuycNG5k1rYDQtuxafJhGrASR63LmrK27fioRr/TdC7q/3ECulQnnbuBtXbECwCnEXw2FppKEYpCDA4WaW7W4vYvke+N0UUtrCyE7x2sgklNvcili5Js5LjUEk2AIAGZLlHkK5Zy2KNXOvQZL6YEcTQXxDb0MA2q0yF0Esq9A8qhdHWCFlAZtAzs0ciRrOfo7Rl4j54WpLsi/t26zPVEwMvD93MuIObxAEnzfANkip/8JNEvPPsJH99TsVo73sgSIktQipAYfMdSdi3ZqiFfEoG5cpKTpR0yca7v9d4qfMNW1uAig4+gGNQWvwFcDCpSTIaKiddUPUT3USh6xxS2NlKxWSDdUJi8vufXAIuq1gJ6T0C3NDLZSNLrW3pz0PPg44b21riNgTiXLTp11Qt2rVYTHuEOqSpVGwE44tOKaNvQPWWoUkPVNaACJpNOi8kdygeqjsUnQlmeHlJ0X7jGLaun+ZLBca6N1jlRLTF1CRtVl5mL6dmcQ/Emm65LV+cYNJmPOBBtkXctyYGKO5OCY919RBOLyRIR+LsgoZ8kuG5MNYgoe4bZqmZ0I4SnT1keTjncmeKCRhOogubUqM/4dI/0aEQ0BpPT0tx268qob3nTGwGe0AT6aqsLBS8P38f5dGPOJtT/1o/8Fn8DfOvR3+JbX3X4vKljTZ03gPnP//k/8wd/8Ad89Vd/dfu7V77ylXQ6Hb7t277tqgYw6DolObKg7Fw7srrE1rNXKbtKEndnAeUCdupry2DhKlcpZKuauB8JwMkjudl2FSazmLrbEJrVtVja/0FL67nqQNAJ0bjHns/lJPevCxe36awsdjeCmrt3hZqm1oj8QSbxhhqIKJSqE+gX7ZF1LdBvbJoXzQl8kMZPXAv4F51llJqDKr3whfBh3s2xjc6mFMpdFIkwdaXP7FCPoBV2WgklwgXsuMClVlYGE4PdztDjAt+PpSsDVP0IbxW6kAHNR5rpjUN6eYEaiXFBC15CkPdNE9zeIeMb+nirCAbsLBCNvaw6BgEw+bJlttcSzbp0TmTYtTFmbXxJ/9yeavV133Z+N6E/eeeFBZ6d7X0udF9Xcl0s8HKudT7dlPgXn9eCmPKNn7lUh3RVV9AK14mgG+E60jn2BmZ7NVs3B5Lrxgy7GXlpmUwTylGMnho6JwzRWLCCj2SBzFuoNe2US0HAQgjSRSnrbeKA7wRC6oi6JTpybKz0MDPpsqSnNSpYkk3AB3ReG6UUtRay1tDIAIWMhXXXYZ5KH3aAE1WJpkVl+ZxeFUetGUBQCj2aEkYTlDWEXqfN7KKm/ypr2qwW5Rxq5tGzEqM1thfhYyNgqwY+3mpcImPubI+meP6Yb73us+y1Y5bMhG3fYexSymAog6FjCgYmI1IOrWQfEy9UMYemb3IOJVus7pvwMe05dfIwpohINipUFYFWotHsGWZ7DOvPCaw+c42v3vcQh5MtPIrMR6zaCZFybLkOZ5b63DncxxfUIcKxiPQM6HIXwJxvvfWB/8+jPvcnb48eE3x8y5ve2D7f2TzDv93+Rf79v93gu3+0MVMoeeGv3cs/ecP/AcDHvv9G/u/r/t+LduxXWl0M8NLU4+lm4OzA5bG2/c9f9p3nDSbPG8BMp1MOHDjwiN/v37+f6XR6vru78qqx2zWSFRKGPaY3LuEi6bik6xXeKMqBAY1QmxKFrsR6F6DsKbqnfXvDiidedBwrBl0GEYjbelWmBBfL75ouQ7EEa89J2OdXSO5dk5WuSqhOAWp6VN0l0mpOk2ooW7WzV5uZwoJ4v9kO6pW0Ba1No8FpRPDN/txCLk6dd9MaFyxWCG0YZSh9SxcLjVvLsMfsiNjjpmcKVOFbm9BgNWZSUi0ngML1E8y0lAGzdvNRVcBOHbqU9616imzFEB9eIr47R1FbXZdOqHmRpdo3ZPumHspBPHKgQOfyejvxBCu0DTv1JIUnW7FsPqPLslJwPLuYf1lP6Tpf8HKhr/liqUsBXh6rC3MhVLBFELNbjywfG1xsCVaRrVomhzTTQwF745gXHX6II51NIiVdiO2qw1rRYyPrsnFzh81RhyhyVJVBqUAIimIaoUwg6ZTEUYU1rs2CmcwSrA4MuxmprVhOZsSm4mh/CaMCG9MO4/4AkxvAYqfS0QixbYHJPNBRSXij0QJEFrQuQmWzrf4yWMlWmQdaBkLlUE1D39XaF2sgTUTng0MFXWtJ3Vwr03Ryantm1RxXXaoK+FjjUk22YpgcVsxuybjtmqPsj7aJlKMMMqWJlMMFzaF4C608PmimPmbJzJj6hCxEGAJTH7PlOkTKsSea8FX77+YdN+0h2UrwRjpP3iryZc3koGZ8U8Xzbr2f5y0/RFcXXBOvc7oakPuIFTvBB0XfZByKNtkXjzDa8+DeZfKPL2P6u5Tkc63HAi5Nfd3rSr7udY+13cLz278IsABepD72/Tee9X2fakDmYoKXxX0+Gp3sfMBLU9/6kd/iXef5mvMGMC9+8Yv5p//0n/L2t7+9TWWdzWb83M/9HC9+8YvPd3dXVnkHNhaAoKVlXq32sFNHGqDq1InKLhBNXJv5ostAMEoctxwUS00XBKpEkWwFko0CVIyqxHt+ts+2jibKKTqnAjYPZMuK9Iwsgo2uSYjOdNEbY+lkPMy+uQUaMAcqTUekLHaem6kd0kBeow24cu6u1uxDzSkCmIU/+jZ7xc1X6BpA03Q8asrW3LKzXlWLLH7YZXZNn2zFYLOAKwyhY6k6mmji2vdXAeFpKyUrb050REGBLh0mq5gd7FB1NJMDmng7MN0fE53uoSYzyVGouz3VgSXG13VJthzK1QJTH9AuUHUM0bhEZYFyEBMVFary2I4MjmvP7dBLV+HuC/lD2q0nu77u2449Zbowl7LzcjYQ80R0LLsg5tGr7Ft8aij6ko01ORzY9+xTvPTgnRyKt1gyE2LlcGgMvqU3NZPwMohtMMAD+R6OzpYZRhkdXaBV4ObOSQByH3GyHJLqksxHpLpkpe4G+FXFspny+ewQH1u9jjtGN2IycYp0qUaFCAuoSb5TrK4RExfvoRAA4ju1s2YaC2ip9T1t5YV0Y5SCOJJujqkzVaJaG9sGFte60sgKeIns3ITGanw99gQjYCYYRQiKqmOY7rVsPhMOvuA4X7r3QQ7FWxg8Pig8cs0SXZLoklUzJgsxY5cy9TEbta6xDIa+ydrrNXUxpvarXtkzZnIwri+CMCUmRxTFrTNedMP93NI/SVcXdHWBC5Jb0zcZY5eilSelRKvAoXiTr9pzN3d29vO/1npU5cWfRO7Wbj1eXQrwAnD4/tdznEfSyL7lTW+Ej/zWJXnPh9d5A5hf/uVf5uUvfznXXHMNz3ueDHyf/OQnSdOU973vfRf9AJ/0UkrE9WlCiCOKpYhoVBGNKpS3tWBSVoNCLJ0XbxTRVDou0QR0pSm7CuXr/JNKYwqLHTvKocXHhmgSUMHjYk089rJfH4gmkkGiPJRdRUiih1khK7FfDjUXTRvaoIAmrEyzQ7yOdy0oU7VNZ3C1taYx0t3RBsp8p130IijRhjZckzC3Il4U5riFPJzabllZS7CGYk+X2R7b8oBH10SYPNTuY6rNNtCVRxcOH+n283CpFQvRrGydeIqBCF1tHih7mukNS/Q+l82DPrspswMpduYxmafqSu6BLoOw5VyoU6chGhW4rsUn0iFLNwPZimJ8zQWb9O3Wbl1QPdm0sYtR0S88e5dGdpbykcJ3NdmKJl8Bt6fkuXuOsT/eZmBmxMq1gCXVBfusdBEMHoemDIa6X8E+u80z0g6pLjldDTAEbohOk+oSHzTPScGhWvCTBel+r5oxBo9Wnr3RiE/vvZZwr0XngWgqxjOqqOTebQ3BmNZFE12DFCUuaSEy+JoarFyQxaVUuhR6WogDGswXsBoaMshCnZ93anCuDo1ExhJX05abcMwazBgXZChSEKym6mqmBxW9W9f5+kOfY9UKzbe5XpFyrVg/UpVkyXiIbUXik5ZW1lWupZmt2gmawJKdcqoYcsPyOg8+P7Bxxyo+0ngLs2tLXnTD/XzN6h1sVD3KYBi5FFcHb/Z0Tu4jUlUSKUcWInzQGOVZimbccMMpTnZ3x5Nzqdv+zReACzM8uVi1SD+7mutSgRd4dFH/tz4B8PKOVx1mWnq++7+fOKftz/sb9exnP5s777yTd7zjHdxxxx0AfPu3fzuvfe1r6XQ657u7K69q7QTG4PsdcYEJVuhisQgufSzhVclGSXJGOjESZFXzg0NEvqSJZkJ/ChrGhyTwESSNPtkOtShRwAsBsmXpTtjMi9bDqbbZIVbJfi6093oeftmI6oMIMonieRCmVqg4rXU9tcjeB1RaA4SyEnpXXovgm305B3oxT8W1tAE5iUpCL5vE54XcHFnF8ygdEbopfrlHvmIJWs49aFWfZ2jP306dUBdc7ZATArp+u2JZQGRQEa5rKYYyKqbrvhWxjq6xdO+OJdAtinArPYJRpGs5QUkzycdaKHoDTbJR081qoOTq/3Ul1z/Z1JS7MTDnVLtUsItTlwO87LqIXbrSZSA4ob/6JNAZZlyfrmMIbLquTLKDY+JjmWyr0E56DR6jBMho4IjdIIrW6KmKB80y217YDz5oshCh8ZQYeqpgEmKKYJjWOo/MRzg0PmhwimgSiEYldlygZuKaSVkREtFsqiYKwKhawG7x3Yhsb0rV1VSJUKCBNsDRlIHO2oBoMxddTSaujqqq7aOdl8W4JJFxqLaPnoMd32pg8Aoaw8uZQ3tPuZxS9g3ZimbytJJvv+5z3JIeZ9N1GZgZqSrFHtnHOz4Dh8LXnZRIOaY+pqsLtqquAETlyXxE1+R0dUHf5Dxn6RjPHJzk905/GW4toewHBgfGfPnSfaSqINExpTMMTEYZDKnOAejqXACo8vRUThEsZTDsjcbctucBPlcu8/lL+Qf3FKnv+geXF7yA0NPe9bOX+yieWF1K8LJYi2DvQqhjT6QuaEmg2+3y3d/93Rf7WC5/LU7QjcZ3I4IRHq/XIgB3RpEty6pMNFKYTISQPrHovCJEhmisUE5ctVQVqLoiorSzUDvOCFe4ShWhK491LTPxFvKBEXGmD6hyIWzRGoKf/1G24ZSe2royqoX9teDfaPxyn3xvl2JoqVLV0tp0JcJPXQXSDUf382tiGFCU0tFpNDRKQajtiBcdyJRGxQuDRbNq54WeppJY3n+py/RIh3yosXmgSoRq52IFBKq0tgON6mtpFdG4wqVG7D21/NyErgWtcDXg06WIXDvrnnyoCYlF19SEbH+nXrVTmIloaXxlKJYt+ZImHmlcN5YUaxqutgDCYmBQNX97t7446l/8s+971Od++p/9+iV//6ux87Jbj11By/08KHEFW+lmLNkpZTD4oBnV2oupT9hvRxytVkhViWN+j+/Vk+OeKhjogjJo9pkRy3pKgewnVSWTEJP5GKPn96xlM+VM1aenczZdl+PFEvFpQ7ItVFzp7GuoWWCq7oIErSSbJo1w/URoWwciNp6pKK8tiLvFDn1OnkVyPz6a0jsa0z/miLcqonGJHhfoaa0lVEo0N817RXaeqRKko9Pa/DeBwyFApSj7htERy9aXOI5cf4a90ZgT1RKpKtl0PQ7aTQ6abUYqJQsRDtUK9TWeqU+kS+MtZQ1kjPJoAkb5VnzvUXR1QWSEKq0q+Rx7SUGiS0a+w1bVbelmiS7p1p+RVoFUl20naOIT1qseubesFX02sqfAAu8XSf3J26PH3+gx6t/7s4OwP/oX93L/mVOXJE9lsZ4s8ALwof6bLur+Xnj43KNYzgnA/OEf/iGveMUriKKIP/zDP3zMbf/+3//75/zmV1xZK1QpmIsU1XxCa2fi2c+SJhhF1TeY3KPrbX1sUU4oUHHhqPoRQUF6piRdR1Lms4pO5fGJxUeaYlk+Am8VykmHws5kgt8/WWG2Ju3qVPCNz76pAyfdDucxpZSsnFlLGHTJrhkyORBR9sAsSGKyvZIUbMoAKMYHLdN9Bxnen5PcebIOhlyoRrjf8qMXDAOaa9UMNlq124Y4ImhVp0iLuQFAuiFGCKaQTlPQYKceXXh8ovGxphhaTKyJxgIwipW4Bj2gHUQTR9E3rTOPcsi5RxEhjgSodZR0VtKaUz6wrQW2jxRl3xIhICdohe9IVyvZqMhXLbrYBTBXS12o/uWxgMviNk8GiNmtp1YFo+p/4KNALy4wSDDlHrslQnMUq3aMQ7Hpdg7cBs9UJwJqtKYIhlg5BjprwUyGpcDgvKancyJVoYM8dkEzMDMyH7FR9fjjB29leA8kZ3Khz0JreaxcTU2OIxH3RxrXTyiWI7ZuiNj68oyX3HInX9I/RuktebCtUH67SnlwtsIdg/1sLQ8IxpJ2NZ0zmtQF6dQ3HZeZjC2tdqbRwjhPwM9/B62TmetEZMuGrWc6nv2c+7l1eIK+yfBB9D1lfV2yYCmCqWl5Bqd022HZZ0dsui5RNGLqYwYmwwVNqhvK13wqlPmIlXiCSZyYxwQIQcnn4ROmPibVJSOXcjjeIFaOM06AYqOpKYNhq5LPc7tKOZP3qPyuiP9qqQuljz0acGnqFT99I3Ajb4VLBmJu+zdf4Ci3XJJ9Pxn1sWPnbgZ2TgDm1a9+NSdOnGD//v28+tWvftTtlFK4RSrR1VZKifNKvTKli8Yvv+5WlAEzreifgNmqxRtFti8mWZeBymQOl0YEJZ0OH4mbi0sk40WFQNW1mNzjEgFBjVOZN1AMRdehS9F2JGszmnBFsUKWjosETdaCey9BlaGxDa6dtza+pI+3EI8D9oyIIL2R/dqZavMGUKq1dR4fiSmGR+h/YQPWt6AJ82x0MuphqL7R1xg9/znU4Z2RJXQT8r2paF06ATuCdK3ETgWUNNci2RDg42ONizWzVYvNvGAio3CxpuyJXXW66UhP5LjEEJaMAMlUMg6UFx43kcUlingkLmfZPkvVUZQdcYyLJpI/E40c5cCSrdQdLwf9Yzmq9ESj+hrv1lO2zgW8LG57qUDMbvflqVkubkxNQDlF6YTWtWSm9cS5IvMxy2aCC5rcR2y5DktmRt9kAnYQfYdHUyL6DR08hpxJiCiDJQuR0MV0TqpKSjSZj5n4mDJYtlyXzEdsPrjMtWsOM62DKa0GF6RjXzlwBZRKwjaXOmze3CXbqxg9q+Arb76HI+kmU5fQNTneq7r7UJDqks2yy3P3H+dz2rM1W6HqaHxkgZQU0FNTazel0zIX7JtHjiveS+BlWeHTlHIYMTugiA9Oee7SUW5KT7Zak57O0fi5GcIC/c5o0Q8NTcZAzzBKjBLGQcT2iS4Z6EyMErwI+zUBrZx0ySqFLhANjRFdy9F8mTIIfWzVjimClWseDA8Vq0TK0dVFTS0r2XIdjArsSSacVMMn609vty5DPR54Waz/+y0v4q31/9+t//FFPY6j+uoFL3AJOjC+sVF82OOnXHkv3QetoHLocQZ0KQYa5QKxD+jCkZ5yxJuGfCVmdI2hSmPSdSdtdOdRBFzy/2fvv6MlO+86X/jzhB0qndhR3WpJVrBlS0bGCCNyeh0wMGANYF4Gk+FyDcY2i+QRc2FgmZm5FwyeIdwx4+GaF/AQTfbYYK6BwRgTnJNyd0sdTj6Vdnqe5/3jt3dVtazQ4XSSz2+tXn1OxV1Vp/be3+ebzPRhY42uHFVqKLuGaOgo25JoVrWEeYmHnnRd/CDJtqP9yBizuj015tfGe5WmIvOijkWeZV/aKdmRBbaeEVN2FclGoOipOlgAkqHHDt1E2hasIluUk/1k21ElmuEBw2jfHvb8S4J5ZFUKImdTxZouGRCTZ8PENIZN50W/rBSuE8vBOwSSLXlukzvxnTgBLapyaKWpIgFvJveYWACWcgL+8gULAZIt+dvzka4jNqHqgS7qNLdKrg9WZGmmCORzCpcICFVBJGcgQMpHimDlMyi7ivYpL+DTaHmPdnP7r4o5V/blXIDLY++3y8TszllP4190YIeKle0u/QMph+M1imAoaimZCwJOplIkT6oKjAoYPEUwaDwRjr5vYQiUypzxVFp5PJo11yVSFcPaC7Ja9diqWrz92K20jxrsUJ4DJ14XVVZy3IssipQQWfxci+HhFmt3BLo3bPKyaz/BM1orGHwNmCyaQOktWzUb04syjtgRm0WLzeUOo8QClmAsukqIQ0CHIJ7LmdjlJjwAX8ct19eFJJb+lVZEvmjJFwM3LG9wQ7JCqspJ+MGs/ycKAjIyFRHhiOuI6gU9ogiGVJUUNdOy327h0ROpFzAx+HsUj+SLhLElWHBtOQ4YAnM2o2cyuiZjn91G1yDTEIiUm0jKmhCFVJdgYewiCeDZnSt+zjVC+WU//eM1s3KOz/OzL+BXfvC953y/K3We/5rvgQf++JI+5zlzmm95y1vI8/xTLi+Kgre85S07slGXbRo6W5tJSkq6VqF8oOxK+7vrRLjUUrUMRU/jWorhQc3W9ZbBoZj+4YR8sS5cLJtcfSi7Bh8rXCRmfZTClKFmDsTsn2w55h7O6DzYF/CSF1OZVu0xCdW0kyU0aS3WEua65NcKeNElRIPA9o3SU0OQE/ZkLUcX0qPiUo23skO1WZhsa3vFoyrYuqVLmOvWrErNAs0896TsUukzV9DqAITQShjvTym6BhdrzFh01y4xlB2La1uUC7i0blzu1PGWHT0xhgYDVceQLSrKjpJUNi25/FXLiDepLqdUQSR8AKry6KoOUDDQXnFEw0C+qOrkM+kT0GWgbIux344kxtrHGpdoqpb8vztPPZczvvhSgZeduv9j53KyL7sG/os7ugyYIqCLgC4VrtLk3jKnM+a0+EKKYHig2MdKJTHI+6Mt2rpg5BOGPmHTtcnC1GsYqaqWm3XYdJ1J6tghu0GqSg7YTWIlJ+9lsJwuevzRg7dTvXuZ5Y9UmPG0kFiFINKuskJVjtBOqZa7jA61WfkMzdLN63zJtffyjNYKAH0vUcQjlzBvaxZJVySqYtGOiJSjG+UsLg6IljLGhxzZsiKfNxRLKa6bCDBpphIApcY5apTBOCOMxnLcq2XTPtYUHUW5XHFNZ4tUlxJ77BP6PiWrV6Sa98GjKYOdeFQi5YhURapLimAweObNCI8W4BMMW67FlmvR1oUEJwT5nJRT+Aj83oLblk6wZAd8Rvsoh+M1fA1GjPKsu6583srT1gUHok0ORRuT5/dBYZUnNlexOuXTZC4VeJk838++gOe/5nskengH5lJ6X5q5ayBpB6/dIfDy7fEXnfVtz/kM7du+7dvY2tr6lMv7/T7f9m3fdq4Pd8WNsnbSeaKKkqhfYPJANAjk85qyK8Vk2gWSLYfOIVsOjA4qsiVF0VOMFw3jZcton8W1NLoQT0s+Z8gXNPmi+DCqRGHHnnTTEfcdyXqO3Rijt4ZC6UeR7MibPhWjUUqh4giltUi1rICFcm+XU5+V4FJFuulJNwO6UJMSSF16QiRMki7qE3ytsLlHucBoj0W7gItqeRkwesYiyhpUmkqyGUzBirUC9mZBjTGT9863xbPi4kZOp6m6crDRhYAfXUmZms1c7ZERSZhyEnbgYkm80SW4RPxBzUjstAC1dFPSyFQtX/SxnTx3NBKQU6ViyASRdhQ9TdkzJFuO+YcKeo9UKBfIFyz5UoSL1ATg7c6VN+/47WueNr0vu/P0HJMFTB6wGdghVOspH+/vZ+jF1zKnM7IQS7GijyaSqAUzpGcyAQu15+JYuSzsi/KTk3WHmjA5JytJJvt4fg3/PLqed248hzc9+Pn8wd/fiXn3PPMPOEzhRZLbigiJIUSG0E4JrURkY72EbH/CymdYOp+xzmfuO8bNrVN1JLF4b7YqMaIPXErfpZPX2jMZka64rr3OtXNbLM2NCG1H2ZVFoqql8S1JM5sY90GOb0UJZUmoXO3tnGFjQh0C2q7Yl/Tp6Jy2kgXUYtKXY2krYT0iVaHxGAJaeeKatRLwldDROT0zxgWNUUGSwrwlq7t0tqoWR8eLbJZtgpJFsFYn54bWCpmPKIIh8xEHoi2KYBj6ZAKEAOb0mAjHgh7R0yIFXLQjEl2RmCl43J0nnktdIvmOt0S84y3ReT3vhYCXZtS1PwiwYyDmUs/Da6d39PFe+dCfn/VtzzmFrPFgPHaOHz/O/Pz8uT7clTXezUQVC72tNwa0uhHbRxLifqDoalwcoatQ63whXZWTdDsO4rEYCZvRmM6LjpWVHCupXyZDWJFNh8lEk6wLhxpmk0jLCcUO4JwY+H2tV26mYWAiy/Bwii6h+4gjXRXmJl0zwhpFitGBGFPIAbVqaaqWIp9T2LEwMFUblBdgZUq53XivJT2wjH50pX5/6tjm5v/ZqX06DdhynRqsOGF3glXkPZHP2ZHDDkp8bMDU4CaR9zAaycqZSOyg6EliWjSEeCBgy8caO67ldoh/SHlQeQOm5LOoUvG9xMNAa93RWhOGBwWt1RJdeDHwK/EqeaukeLTvCKmesFK789Tzjt++5pLEKV8IaNkp9mRXSrY7ZzMmd6goYJJAvA3ViuFDxw/xT73r+bK5j7CgRzzCIl2TkapCTq71mGU9YjvIyfawBjcOTd+nE4bAKE9Uez+yEFEGw7Zv8dHRNXxg/RAP3bef9jHLgQc80bCSfZkPuLqLxA7qRS2lUF5CZcpuxPozLeWzRtw4t81n9x7kRLnAVtVmT9RnyQ5o67wGVQnrvsP+aAu09M70a9P6kc463SjHB8Wq6dEvU9SDBl0FIsAMrCzQqTApz2zSx84YJd1oykMUV5PQgEaat89u44ImUhWltN1AgLjugmnrkk2fToINekbARYmY/iNVUQbDdckq61WXo/kSubdsF5JGFm3KsTYbxzySL7KhO8zbMfujLdkOYNN1SFVBW+doJa9h3XUnkr5rog1Ka0l1yf22c3H/4J5G8463RLzwFeVT3/AC50LA0vNf8z07sg3f8+q/BRogdPX1zzRhBD/3jK/aMRbmbOesAczznvc8Wf1Xii/7si/D2uldnXM8+OCDvPjFL74oG3nJRmlpsFeaQClGwqoieTgwXy0y3h+TdTUuUZNUMu0gWRMGIJ+XEspiTpFsenSl6uhkT5XKCbl2cr9kTfLydSZgRWWF7NSrCrQmVA5l6h17UzTpHaFwEl8cRwIYlMKnlrKtaJ/2pGslPm4CAjzRwKPaM/Is7ym6mtFBhR2CjwNqDK01WW2qWlPmwcUwPtyhe3KNUNXeoMb/0oQ1NPHJ0WyksqbsSPmkpKvVYM9Il068XqDyEmUUYPBWiXzLKrIFQzT0aBcIQdFak1VDU3h0ERgvW7xFWBfARYp422HyuhW6lh7oKpD05TXZoReWp/RATL1YhksNZlShtMItRuRzGu1E+kEqfpzdOfu5mCDmSmNbGjC0C2R254nGZA5bFVJiPDaYQjPM2/zW6LM5ddscL5h/gFhVbFVtYltJp4keU6DpqAKvJY3HBUWE+Cm2XTqRSKWqpI9m07V5JF/k71aewcMP76X1cMTyyUCy7YkGwm7r0qMrL95DJceGRp4ctKbqxoz3Rgyvq+i2Cm7qrbBgRhMPTdvkkw4VrcTvsSfq0zMZHZ1TBMMBu8UD+T56JmPOZixEY+5N93Iv+9hWKd5a2lphtiN0WcliXTUjq6qPL0prQmQJVhIpq5ZieW5Yy9aKiV+oAXgezUo5h1GeBTPC1cWdZfhUgYmfWXnru1YdZV2RBctm2aZfJTy8uch2v0UyloRMkES4RFe4oCcMmnTrKDJi9IxfaeSTiXQNxFvT1vlEdrY7Tz2/f89P8fv3wK8c/dGL8vgXyvI8/zXfw//2sy/Yoa2ZzktedwMved2bd9zYfynmUoMXOAcA06SPvf/97+dFL3oR3W53cl0cx1x//fXcfffdO76Bl3ScgyStG+XrnbvzqHFGfGwN2+8S72sz2icJZCpAsuEnno1k21O16ghIJcZ45ZhItgDi9QJdVOh+JsClabyvHJSlpIJVFQQvJWhGT7Ow6gjlUJayCJUmhMgyvqaDtxKVrELdZ1KBKuXxi7mEULMbduTQXU3RA10qWmsB5aTNPtlyRCOoWtJNE/frks00gaKomZc6QrmqpW1lzXrUvTNKR+Dq+wHphpuUn9ksCOirIzxdatGFw45Ksr0pygXsWHL3o4GjahnKriYaNuZ9ASZVW01BSKIoe4Z4qwaAdbBBY9qXdDVL56QiWcsxhaeYEx+OKSTStOxKkIEpxAdTtTRFTxFv7x5wroS50sDL7FxtbMwvxd96uTfh02bsoMAaic43I0s0tKQbmng75l3Fs1l7TocX7/0w+6MtDthNhj5hQY+lPR5IVUlPjwHYdG1WqjnKYNioOmgCp4o5tsuU+7eWOfnQMr17LYeOOuy4lHj5AHbspEPLBXQppcvBaFnoASmrBFxLk88rzHyJ1Z55O+Zj2TW4oDmUbJB7SeBqmVKAhKrYa/vsNdsTFigLUgh5LFuiZWT1PLEVUVpR3DhmQIugDXaUEjs3Kbqkqqb1ACCeziTGpxEukWPV4XTMNdEmPZ1J8IFSAiKUZtO3GfmERJdopMwy0xGpKkmVbIdB5GhGeQiWYTBkISLRwt0YAj4oNvMWg2GKOpkQ9UW6HLwi9xGRGrIn6gPCOG269uRx582QVJesV13aOudItI6u/TGPujY+aB7ZusoVKk+TudQStXOdP3/9g5d7E8567hrcw++zs4zRL17/EuC/n9VtzxrA/B//x/8BwPXXX883fMM3kKbpU9zjKhyt6rjguuW+jg4OXqGyHH2qoLU5IHm0TbGvbpc3Cq+h7CrsMEjxVR1XbLKAHVaYcYke1d0qTrpcpDRsmjA2iSluqPQQhCpXDWCYbpdK4+ltrGG8bHCppJl5W7cOb4uMLO9F2JGcqAeNpKn1PemqRQWRaIEwRlHfiTwLT9nWKCvyrJDGMDCAqxmY2rzvnDBBzk9eWzAepWVbTBHwkfTAFHPiQym6Gm/bRMOKbDmidUqAkck94z1WTK+lxD6DSO4a70sDinQhfhgptaxjp7eyKRCsBEDpWgrXxGDnexKS9QJvFeM9VlLHjIQGmDxgvbznQSnSDQ+7ErJzngZsXCgTs9OgZafN97uzO081QUvaoq5KVFZhMotNLPF2Rboec+/xG/nA9UdY2N9nX3dAYisOtze5JtmkW7e8b1VtfFAMXMJHNg/SzxPGRURRWNyxNq2TmrgfOLgVsFmFrRkXVftH7LCcHlNcqNVXdZ+ZlsRGb6VIGCVSraWOMD+iQ1CUwdB3KWMf07U5PZ2hVZikf6WqxNXsQqQcczabRCsvJ0Nu2LtG6Q3H4wXWF9uYImZxuxDJrzUTGZk86Zl9Y+KHZMJeNCWRKY4CwygIG5LokgUzpO/Fo5P5CDTEyGJZUQMWHzSZj9j2LQyeWFV1iaUUUY7KmGoY0TuhSddEWj3airivv4drks1J98ya65L7aBKZHCuHr+maRp4WKQnAjpTjkWKOQf9peM50ked/O/IfeNlP//gFycne8ZZox2VZF4N9aeZqYWHuGtxzxvv6e3d+B3e/779d8OO+/5fODrzAeXhgvuVbvuVc73L1TANcGpvJ45RGqrxAlxXp1oCklYiJPjL0b5ojGnqirYJgNSar0MO8TvDyM6bEOnrYT0/6pRG5Tj5LYlRRErQY4kNVb0OzU7d2+hha41sRVUv8NcpD2TPSOeMjdOExuafqGDHDV4HRgRjlAgsPVAQDG7dYirmAcppkSwnwUYqor6nahmA0Po3RWnwiBD9dKWveqMbMb4z4oypHenrM8Egb5SAaepItiTke7Y/IlgzKCbjI9sboMhLWCChbGh0JkNBFQHk1KaXUlQCasiVeFRCDZ+dEgVrfmr6PWp4zn9OUbU08CER9iY8OVmEyL+Aq1pA5zKhCl56qbdC5dMdULV1LznbnfObJAMgTgZsrmWl5srlaWJhd9uUSj5FERJWJ/FaVFSqz6MgwN67oPmqo/slQzC+wNr9IvqC4tw35PoeaK2h3c8pS9rFVZeDRlHhLY4cwtxlorTmSzVxYlSZO3wd06fGRFplY5QWoGC3gpfaVYBQ+lv07IRCUPEYIsJwOORRv0KkLIYtg2aCDVY6uySZyqZFPGBUJbZ1PulZyv098JFXKetHGase+Vh+jAlllydoZ2YN7qDoRUekEwFQONRxP45VrX44qRRqcrgce2Zpnc3+bQ3aDGEdbl2QumjAsy2ZApCpGjakew4KSksvMR4yCXJ6qktRI1LF0xgRJJ4s8o1bMVpmycuwg3Uc86WpJ2bMMtjSDQsIUbos2WDAjtPITdizVEsjQgJVUy2KlRDJrYYzQaL27IHY+08jJZucr/mTAVz/3iRvgLwZo2Z0z57Hv7+/f81Pc/a8u7TH8nAGMc443vOEN/PZv/zZHjx6lKM5sbV9fX9+xjbvkU0vIQl5Ix0oDKmauD83vSkOWS0pXCMxv1+2hSk0N7TAFHiCGe62nsqtJgpeeABLyQoISjBYpWcNuhJmW4gbEAD42NUgIuASKjiYeevJFYV7suMKOPFVqcImqPSlygIiGHl2KlCweeMxYXlvZEwN+1dLkPU2veQ3Na5r1vzhPqCpUEkNRyvsTxejC1eyH3FcXHjsq6bpA1RbJl2tZyfif1yJ/c2ArYWBMFjCZIxrKe5QvRuia0YkHgWjkqVIBNfHxDYKvCzSVQuVuIgNrr4gOHBCQ5AJYiPuOaKvEDEtJx1ECbOywxFtNtB0o1S6AuRhztQKVJ5urBcTsziWcuiw4aAENAScS3xAIpcP0A1Yp0lNawERk8JGm7FmqVkLRSUmVLEzFfVmMUl4YltnjSqjjhhuGXU28LQqsliRKX+/7qJ9fKenNUgrlPNHQYQpNkUUcSLeJVcWyGUhXDZoyGBJV0dYSNuCComfG0sXiI7ZdOkkHK4Nh7GNapmTsIhJT0bMZBzvbxNrxgdYeqpbBbqkJWJmAF5gs9DWJmdEwsLbW4d7xfm6MTxOpinXXJgvRBEQAEx/O0CcYAqlyxHiGNElh09SyVBciNQsRLihOVfM8PF7m6PYi8Rak65UUTrcCyiki4zgYb9LROZmP5PF1SealTDRS4o9xKIY+IcJhlGfbpXJZlZxxKrA7FzZ/9pVd/uwyPv+v/OB7LyoLczXOy376x2EHGJhzmXMGMD/5kz/Jr/7qr/KDP/iD3HPPPfzbf/tveeihh3jb297Gv/t3/+5ibOOlnaqSKGXnmEqm6hP2KJbmeYDQRD7WjMRgJKtsjeSrARkNi2O0rHZFVv7Vo4oSsrxOPXNi2vfhzBZ4rWQTlJaAgYbtaK6uoOxIw7wKsHWDBQ/dE+IVKdu6jgWGfFmxcJ9jcNAQjKHsgsmYeHFC1KR/GbwV2VkwCq2UbJHSAqaslfhLYwTsNUCrDnfQ2yOU76AqkYepSuRaZlyhSi8lnm1D0ApTiFQtXa+wI4ePpIPFW4XyCpdIFLVyASLpzwkG4m1H6/411GBE8IHg5QRBD8e4eAHXUrhEka7XyWYdi2kKoEcOMyzRRUVIDLpwuNTgUivbGmkqe85fj93Zofm9xa854/e7N952WbbjYs8vxd96SbpgHo99KX7oA7tdMBdxVAgSvhJZ8VKW1TQmuLmNUlCAqde/CIGklIWrkMbTY0UIBGMIicG1Y8qupWprRvuiSTkvtecv2TYkG8Iqu8RIklfpJ4xQUEq2raz9m94LW1+vRSa64vpolVSVbPo2Q2+FjTGG3Ef0Sbk2XmOt6krLvB2wVnXZ9G2W7IDVssvhZIPTZQ8QaVYVDNe0tuhXKa4V8LGqy4jrxb7IyjHE+4mqIViNqjzpuiNaifjY5gE+p3s/23UkssaTGWFhTle9CROSGvG++KDIgsWj5fbKs1nN4dDMhTHbvsXASZfMP24e4RMr++Cf5ll+qCJez8AFbKwJ1jAfZzV4qv2bKGLl6FgBbS6IF8cHTapLYuUogmHOZBgVWI16tDpnLvbuztU7lwK8vOynzz2R7K7BPbyn+8TM1E7NiVdfPDR+x//+bWctIzvnM7Tf+I3f4E1vehMvfelL+Ymf+Am+8Ru/kRtvvJHnPve5/P3f/z2vetWrznmDr5gxRk7Qm59n5VJNeeMZt9eT208Yk+aktywhieXAM9fBzaXkywllWxMNhNb3kfg4ooEjXs8wa305yAGhLMHrqZzNmOljYySJDOo0GZFW6ZrQUU4SxLIFxfaRiKoDneOBeBDIl9VETlZZJeDFwXCfQZexhA7Ucq6qLbIx5YK8NqVBh8nKIpGtGaf6vWjGOxhnpCdHDI90pYdGgTMKOxKQ5VKRkdmRR4WAHUlKmK4k2rjqaJTTmNxLCaito5FbdRjAwJE+vAH9IaEOF1BKyYlCltM7lhNUWhfJyeem42YVM0hs9exKpNWgFVVLE2/7T/mod+fiz2NByxNd93QFMxdrdqVjl2dcy2JCLImLTVhL7XNUXhiHYI34IZtpfJB1yWQAQisW4NGKKHsx5ZxhuN8wPCRyM2KP0oHgFDiFHhhapxLapySJzIy9pDjmDjMuZSGoZoJcZCeLRC4GvGLopJk+CxFtnddFkAVDn5AHAQMuaPq+xaFoQ4z+0QZrrksRLFoF5u2ItbKDVoGWKViOhuTeChNhoEo1rh1hyxrAlFV9jFUT9iU46XKxg5LO0Yh7D+znvr37SXRJ6S37oy1OlvMTBsSoMNnmApGODUNM5mO0EsnbatUj0SVbrsVHB8IEbxUpHz+9H/PeOfZ8qCTaKtDjktD4SfuKRwdznK563BKPWPfdSVSzJJhFrLg5SUQLir2qj0NNyjL7LiX3dhKzvDuXfl77q//jjN/fe+hG/tdLPusybc3ZzflI4H7/np/iZT/94xcVxDwReNkpCdm1S3t5/1ne9pwBzMmTJ7n99tsB6Ha7k1LLr/zKr+THf/zqLOKZjFJyIt50wTQsSh1hPDUXzoAa56AKEEXC3DQyqyQmRJby2mXy5XhiQG9KJX3UMAxIeeJCl3hPi9axbdRghKoUGEWo/PQ5nZPngMm2qHFJe8UxPGioUohGkGyKnCwoaK0GikLKKbULtE8EhtdookGgd9xNtqtK1SRus+qI3KxKBXDojb4s7hlN8G4K8mBG4tbIzDTgCd5jTm3SUYrhtR1cYgkKki2NrsLE8yI/e2FlrKboRpRdYYxcRxEP5bHjbbl9Z6MkWh+hNwaE0agOOZCCz0Z6h7VEqyPs/gSTB3wknqTk9JiQGHxkcImRgyegSgedSJLaBhV6VFLNJ7tFlpdongy4PNntny5A5mKxMLvA5fJOMR+jqwhtNQZQ+cwK/EQm5adRwpGdelVmbheSiHIpYnQgZvt6TbbH4/fl7Fnus6c9ZCkZUXiDVoFYV/igOTXucXR1kXB/h+5RTboZiPsak9dpl1qLZC2WY5mPNS5WhFIzdhEORUcVpKpC60AWDGlS8ki5SKwcK9Ucy2YACBuh8axXXXpmTFsXnC7naJlSChx1xbwd8cnRAU5lPexAASKto3JyDK29olR1Ck7lUEZYf62g92iF+1DCH+55Li/Y/zDXJJtkIWJQl2kmWtEOOaerHp55YWdCPDH9GzxGedYr6WJZzbu89/h1eK/I11q0j1mWP1oSr2coJyxV0BqdO7rHPaeOLfKhg9eyYEZsunZd7ingZa3q0vetSZllk8gW4fBIh08ZDHlh2J1LO48FLs284JH7eUF93bs/8i5g2mdyNvPnr39wR0osn2ze5M/PyP/79/wUB3/+4py7PBXzshNG/mPrK2d923MGMIcPH+bEiRMcOXKEG2+8kXe84x185md+Ju973/tIkuRcH+6KGhVFohPW0k8iki2msjEQzW7Dtnh9RtwyWk1ATGinZIfmGO2PSLYl1SvZdtiBk8b7lrAv4ruQeMts0VDMLdK732JObxGKApUkM9KyGa8MtTGzKGmdGlP0OhNPSNkS8JJu+BqUiJSqf9hQ+wuxtXQ4qcs088UIXQaqjqFsK8o22FGgtVEfYI2RbdB1GpmuGSrNdNWwYWGUFj+Kc5iVLXrjkvG1c4z2WbIlQ9yfrjiWHQ0YXCT9LMGInExX0F6RUk4zyKXks3KTks/ga4Dp3LTccybBTW0P6T4UMz7YouxKWlxUznyOQIhEhhesrmUV9YF8OZUAhV0F2RU9v7f4NWcNYl73E790RSeRXQiIuRCgsisju3hTzBl0ZbGRFmnrIJOT9sgSImrWQU+KoYMRj2TQWvalkcW3Y8YHWmSLhtXnBQ7eepI9rSEghZFVfdKsCSS6ZDEasS/ahkV4ZM8i7917PZ88vJ/Oh1NapxUmizHjmeOHa/aZUmgcrVk+tr6fbE/Esh7hULigMARc0CzUWreiLs4c+oRUl3w0P8Qj+SLzdiwJYMDAJRxKNhi5ZJJUtjrqoLyUJU8W+5pppNcgFQN5hbKB4DXJWkkv1qx8aJm/qQxfcu29RLXkYORjVssuJ9QCkXI1AJOOlkg5ymBomZJ+lfK3j9xA/2SPaNOQrCs6q4E9W554K5fIaSeR08o5YeWRKoD0RMR7V67nYLw1kZE1r7MMFoMnD/L7pCdGVWy7lK2qzclsjmJ4dZ8fXS3zRKDlieaLnvOl8v+vfik/953fcFb3+f17foqXvO7N57xt5zIXkkJ24tXhgkHM+cjEdoKFuagpZF/7tV/LX/7lX/KCF7yA7//+7+ff/Jt/w3/7b/+No0eP8prXvOZcH+7KGqMlaQtquVRd3OhnTs5DLaeiZiRCbUDUM6b9yDK6foGqrUm2vUT4zivsWJGUYrAvWwKOXCo+D5N5km0xZA5u6NL1YNa3J6b+6TaaibdGZQWhlaBHBZ2TEdlyhLeKdFPKKgfXGCncHAVMKaBAulhEFpYtyTaoypNslIz2iyytSoSxKXuKPR8YygqZn9mGJtY5ePEFhToO2nmRmGkj6WlaoSqHGoxo3V/SOmqp5lv41EwAkx03fpZG2iWdOdFmht4cyEG+AXC1REzeZ1/7cYI8V/178JUAGGuxp7eIOxHDg7Gkl82n6GLKpPlIo+v/q7aZFFcqL+9J58TwYvyV7c4OzrmAmIs5O2HgnwUiZwNmdoph2QUxF2dG+zTOGdINhRmbKUCJjCyE1bcL1kzj9cuKkESENMF1E8b7E/qHDIPrPYeefYoXH/wo1yWr9PQYozzHimXpHjE5eX1CnfsIrTzPaR3n4IFN3tt+Bu8ONwMpuoqIB4ao7+puGNnnmcJjM02yrjl1coF/OXw9nc4niVRFR5VkwZIF8ZvM6QyATQer1RxlyNmoOqwXHcZOjiEL0Yiuydmq2rR1wf3ZPnzQbA5atLcDyUaJ3c6ElZqNUNbTxE1VVgTnUKXGWE3rtGLxowlb5QJ/3L+dbi8jiSqM9hSVoXQG7zXeK8rCEoJCqUA1jNADQ/sRTbIZOLThibcK7LBCF7VkO6oTN2MrPWVe2CmfGPGTHgsc//h+PjJ/DV+w8ElSVbLtW3R07YFBM29GrLsOW66FD4q2ztmqfz/eXyB+pDEr7c7FmvfdlvBbF3D/1/7q/zhrEHOlz9mAmD/6Vfm+fvV3FpP7XOjsVJzy2cw5A5j/8B+mJUDf8A3fwJEjR3jPe97DzTffzFd91Vft6MZd8rEGsrKWhlVnXlfUlyst18XR9GQaJqtoAOXBBbJlQ7rhqJ3vtNY8rZUSVQi4yOc1c0crokGFqqT3xGTiARmnMaMjHbr9Eaoo5bFDkFbgJgGs7o5RlSUoRbQ+RlWB/nUJoIhGnmyPYbwv0DqlqOoVNuUg3XToMrA9Z/FWUcxbSbAJ4CLpsNGleE7MqU15nWFGKtYUWno9BTKNuV/Vf1J1p06o+21ULpfbtU0AkjiedgDAGczKNERhZnwgVOXUl2StPLcP4JvPqt7GqiJ4WUVL7juNLvZQzEVUbYNV0pBdtQy6EhlD1Y2kK0aBKT1mUKBHBa6WR+7OmXPvF/4WN//1N+7IY52rfOyJHuNsQMyVzsLMzqWWf50viCl+6AMXYWueHjM65NHrimgkgSW2nZzZ81Wb1lUjIWv+NxoiQ9WxlC1FvggcyNnTGjBvRyyYIT2dse66ODRLVqRcOQJcsmDxXtiSJTvgBXMP0H9Gwj9v3YgdGSl0HHts5aVXzHnMCJItkQ1nKxF/dfoWDh9e54DdomNKCgwdnWMIbHuRba27LqfKOY4ka2xVLRJTcTrvciDdlhN4U6AJArTGizy0tYS/v0u6EbCDElU8JoWzqRloCi6h7vCq5deVp7VeoT9uyE62qNotRnVXmfKgnTD42kOrkn4wVS/apRueZDPDDmb6REKYHDJUJcEyKgRUKeWfelRitULnmg5QpRHv6j6L3h0Zd3SO0tE5Q58wcKn4coKEHLigKb1lnS4bVZv3rV7HiY/uY/GB/GL9qV3V81e3xnzJx3Ym4OC3Xv2WC36Mr/iTAX/2ld2nvN136W/nTf7isDA71QHzVIDkTuq/yVfvyNMBtXfnp3/8vEDMN/3hufXHXbBI5q677uKuu+660Ie5IsbtmcOWfVntd+7MCOPZk2aYFk3WJ/ehob7nOoyuSdEVZAuGupCYdK0iWh+B1nROWNqnFXZQYoYFqqjw3RQfaUKkMZmYPMsD88QP5oQGPPlAcHUxmZXUFlWUEkNpNGZcYscx4z2aoBU+gnRFSZxxJQCl7CpspomcZ+H+kqqtqRJNNPIEI+zMaI/BxbDnHzbk9TZgBSR9DQQ4NMDFmKkJs9lWa2dYm0BQfqYoVBGyHIKAlTNYlRBklbLRQ2t1ZsFn479pnmc2aMG5aZeP8gQHipLoodOYxTmqhZRiMRawmDuqliVoYamUD0SDErOdofoj0Yn7x4Co3bnq52KAmKdLfHIDRs4GyOwCl6ee5PoBeWiRbEr/VIiMlEk2scHWgKuZ68pNPJihnVAutRjujxgdVGSHS/bMD9mbDuhpiS4ug+FkOU+qSg5FG+JBcV1WqjmyYNHKM/QJIBKv58yd4JNH9pKfWiTelpJfVXh0fbLeBAl0AlTtiAd6B3h76za+YvmDtHVO36cs6+FEkpVScm20zoIZcaqcx+DZH2/T0gVJLe3aqlp0Tc4H+4c41l/g9APLLD4I3WMZ5tE1WbDqtmWBq6ygrAiZFBKrKJIQHK0lJS2rBGwYCZZJthxBKUzmRPpVujpprekH06i8vjxMi5GVk+AWjBLvY33bgEHn9XPUagJVOfRYoayUHS88AD6K+aPR83nfzUe4bekEy9GwBi6WRFdslm2qoOmXCQ9vLbH24CK9BwyHHqzQa7sA5vHmgT/4G3jWhad6veynd8aD/ayTf3rWEc0XE8RczfP79/wUvw/8xlnKyc4VuDRzVgDmj/7oj876Ab/6q7/6vDbkShiXWEgTGNYGkUZC1rALzQm1ic4slmxmrsv4yLzonIF8UZNseFqrFXZYEYwBIzvdoJUkYRX15c3jeaHz8YGqGxF1WpMDXtDUyWR1XLOtV64qhxrnaOdpnbK4JGX7eo2uwVNQouySsstA0VXYHNQ44CJF0RMZG4Bvifdj8ZMZemNbDiZaE4p8CkqaoIO65POM96pJbwO53aR0U8nj1AWdYrqfMd4rRSi9yM+8F/BQp7wpowl5cSbr0gAbpQlFiYqjqexvZkLNVOnVDeJNS3QqIbSTiUFTVR49LlHjfMoCVVUdf71r4t+dJ5+nC3iZnadiY3bBy9nNc/c/yj8MlihPW0mctBpFTfUqJStKtl78MRLXizFUvYTxnojRfsXg+oo912xx4+Iq16XSsRapipPVAn2fEjVxvfXOfrXqMnIx83ZMWRseDZ62LnjuvhP8/eI87rSSY8mM7FnlHoOczKfrhtYjln9aOMLz5x/mULTBghbvSxYsPV2gg2ev3WYhDNF4XNDkwXIg2WLkEnJvWS86DE3CQ1tLnHp0gflPGOYfKjDDovaQCtMSrEjqiCNZOJopkG48lsGoyf5YBXBWPKTKaULpUa4OvdFqcixqOnfw4gUF5DGT+pjdJMK5IAfIpidM1+9JfTxQRhIzVelY+nigtWrZeuQA77x2L91D2xOpWmId4yIiG8eElYT2cc2B457WSo4uPGF4/m3yT/c5W9bjieZlP/3jXH/gth3coss3O8W+XAnzVHKy37vzOy6ocPSsAMzXfM3XnPF7k/j02MtAii6v1gmRJsQRKi8mJ9Pg5AS5ASqzRZa46U4waZEfXqDsGSlODGKQVz5gxg6TO/J9LVwq6WPRoF75SiJ8KukzAFW73pkrKZL0nRSzPZiWWhoNeUVIkppqFyMolUMBtp/TPmnQpaVsa3wktHrQ4BJ5XB9BXhrKlqZKFS5WjPYbgoL2imf5Q0PssdWJ12ciE2sYibr/pWFhQuEFhDTvT2SnoK+sJvHUgVqK5jXEdY9M8JJwNgsEm+etPTXBuyl7MzuNbryJ4ZwFVI2xv2ZqgjbgCsgy9KDWItere5PPv5Fw1GA1zFy3Ozs/OyEfm32sS23ofzqCl2Z2QcqFzw3tVd7XqvCRSHV9VHdmRUGYj7IOJSlKOUnvtvHdmKobUfQ0wyOOzoEhty6f5PbeI1wXrwLSOQKQKtkfPlousqIcq1VvYizPfMRW1WbejiYpWAvRGLdc4m0sbH9ey6YaVqhS6NyRbDq6xxVbaYvfmf9MRocTvqT3UVJVoFGUQRPjKfF0dEEUO7IQs1r2KL0l95ZT+RxreYfNvMWpo0u0H7Z0TkkkMiHAwpx4G5sAg3pBSsVxvUgl8rrQSghphOskuJalnDNUqXSVeaPQLWG3dCGSYOUCZlTK4mD9/qom6awJwDF1UAJ8qozP+0m4QGgkziGgigrtPVFfY4cV7VOG8hOWfH6BqiWVCJWH1ijQywLJlkPnJdoFdO7Q4wo/3GVgnmi++XkPn3cx5cUAL+fihdlJFubpBF5gysQ84fzh+YMXOEsA42dO5P7iL/6CH/mRH+H1r3/9RDr2nve8h3vuuYfXv/71F7Qxl3uUD/j5NmacT/XIPObkejZCuLkoTXEHFskXIuLNqpYoNeJa0fDmyylVS1O1ZPWrddoRrKaaT8QDo2oAZRU6n77fxd4WrdNGVqasnfHhuNq07ia2E8qA3h6RFBV21CJfSsgWDS5W1NH+mFyeq+yIeb3sgB1B7xFH+5GM6NTWBKRNgKoTRgirZHXKcUYnjlJqhhWp359KVhVJkin4CNPrQ1FLtOrVtqZnRllD8E14Qg1YfJDVuSZu0zesDkDN+DTApZa1yePMACZXMzhKi3zNWqhy2cbJap+aMjy7c1FnJ8HL+cyFgJinM3DZnZ2bzEeyz6P+L4R6FyhsTDCqjsuv94mtiHIuZrTPsnkLpNcMWeqM6NqCSDkyHxErRz9IZG/PSOJXpBx9n6KV53C8AUi0sQ+anh6ThZi2LmiZgvZcRjAJKjApuFTei2RKKcy4JFa190RbNs0e3jp6Pv4WxV2d+4SJUZ5UOXqqYOSjSXywRzFyEl28UbT4wP3XkhyLWT4e6D5aEm+WkihZToNUVFX/3Bxvm328UpAmhFZM1Uso5yOKniFbVFRtRVDIMU0pTKaJhuLbjPuBZFPXBn2HzjUUFWrspyqHyqF8OeniaWTLKDUBUlgz3SbvofCoUkktm1KYzBBtFyQbEpxzxvsZEElefRxRzqOLCl8+ZgFud3ZkrgTm5Y7nfi/v/+Avn/f9n27A5VLNOXtgXv3qV/Mrv/IrfP7nf/7kshe96EW0222++7u/m4997GM7uoGXdDyUczF6I4Isr6lo5ABTVVMfzAwLo4zGL88xPtgm2ZCVHx+buk/F1i3yHpMJG6O8tMxXHYsuJXkr1IWWoUkhDmDGlcQbL0tKxCS2GHPGib+Kokkymqp3wmqUYZynNSowWYds2VIoTTSSA6iPIF9SKAcL9zl69w3Q/ZFQ5rX35AzjfgOcmmk8JyDPG9eMhhPZV7NNWEvotfFpjJuLcZFIvOywkp36oEBlOWo4niSJhWYf30gBmp/dzAFOTeOrJx4YFabbq9WUTZmdEORD1moqUXN+esB0M49f99nszuPPyS/9Qw6861+d8/0uN3CZnfMBMRcTvHzdd7/4Ca/7nf/69ov2vLtzceZENk+rl1G16k4ppSYlulS+li4pQqcFIeCtpmprtp+hWLx9hWu628zFYw4nG/i6OFLSxwI9nRGpCm+kLNE4P4n3BYnyLYPBqEBMhUMKKvf2hqyl87hEEW3XccFlBdaITCtIL5fJHJ3TEI0M40d6/P8e+QL+8lnP5K59D/J5vXslJhjF0Cdsug4bVYcyGByadxx9Fv1jcyy/X9M7XhBv5DOvud5Ga6CsTftlJQtaIMeSmiXxvRbZgQ6DQxHbN0BxoCJdkAQ0YzytqCQrIvLCMujHqFITbWqStZjWakRrrcKOHHYzR8+AFVW5KXBxfsrWN3IyJ6qAhp1Xvu6sCQGVlVNptDGYrEJF9XunqCOYfQ1mpgoNYFJ/sDs7N+camXyx5s4P56C/nZf99I+fcz/MToOXr/iTwZNe/5M/uizb+zSYcwYw999/PwsLC59y+fz8PA899NAObNJlnGZH05yQNxHKmulJe7Oq0rAyacL4cE9MkXXppBlJi6/IBmSVTVUeVfe+eKuo2hpvNKYIJOvlhLUxuUfnFa4T4WIt2t04quVTM0VY1k7BSwjCgjSSKG1QZYUqK2IP0bal6sa41EjPilV0Hw3EG4UwLmU1cxJfRxY3YGCSLqamJ/Wm/rmq5H3QIo0I1qLimPLIHvpHUlDC+FQthTeySuViMHlE1QJUB5NB0vfEmxXJ0XXUYFR/FAKApizQDLCwdmr4n2XEjJl2CzRyt+ay5tjupiBn0l1jzGOkgXzqz7vzKXOuIOZKAi/NNIDkqYDMxQAuTwZYnuy2u2Dm6phYVVyzsM2DC3OTxalpgaWr+7U0vhURIkO+nLB1ncU9c8hn7HmUhWjEvB3TMxmrVZdDJiPVJbFyaDweTapKimBYMCMyLy30WYiIlSGuJWYuaAYuxQXFQjJmJUYCaAJ14pYTSVW979RFvdjmIszYk24oWmuW9dUD/MGz53jw2mWua6+jVSBSjpGXRbaPbR7gk/deQ+9ey8GjjvaJMdHGeHpchYk5flae1YzqtAitBN9NKRYTRnsta5+h0NcN2TM/4FB3Cx8UvSjH1qaW3Bsqb9guU3JnOd3vkuUR/bWUeM3SPhXRO25pH6M29VcELaE2EtTjpoyLUnU3zpSVaRgi5ZkyRUoBMcoFvJbTAx+0gNPSSVBDKc8lb6j4VM94H3bngudKAS+z8/v3/BS/fw9nJSnbaeDyvtuSmgX67Se93fu/4pd5U/3zn7/+wQvyoFzuOWcAc+edd/La176WX//1X2f//v0AnDp1ih/6oR/isz/7s3d8Ay/lCEMSCLFFNSfIwcvJbyMz8mLkD86jrMF329K1MijRdSxliIyABa2wQydxvVbKzEwRCFkNZKKmUExhxkJ5B63Qo1ISVRaE6p/4NKpKmJg6JSVQToBHMAblnGxXY4IEdG0QNauKkMTiGWl20M1OdVKUeeaBRsZPGaiJD6jpe1ET8IK1+INLDK9tM9yvGR1QzD0QsFmg82hJsWDrgyJUqQJEx5xuOoqeJluI0YcOYIrA/Me30GvbwgSVM8bHWU99w4g5N5WmTVb37DQlrQGezecItRwuEZDTgKPZ19+kqxVPj1WKK2GuRPAyO7MApQEzF4ttORfg8lT33wUzV+7MR2NKO+SBSHq4zLicypU8db+WhyTCW81on6H/DM8dhx5lzo65uXUKU7PA80ZijOd0VpdLapGoaUhVCTjaJqdEYpJTVZKFiL5L6dexx12Ts6I8upQYZTMqoAET1giI0UwM6wZQzhAiTWslYDPD8HSLjxy4hX9Z8PhWzVAUGjtWdI4pDp9wpKdH6MrLgp6vfZBKiTfSSGnwpAA6rtPGOi1cL6VYTNm4JWH7rjFHDqzw1UvHmLMZbSP74kg5fNCcKudo64JUl0TKoZVnq2rzaG+ejaLNo/PzbOxvsX19zODalLl9c/SOV8Rb8hmYUYkajKddPHVxKFoT6mMmSsm2NkxMc9wMAZXLcUmHQCgdWqnJ+ycLnjPJnTVoU4+tZtidM+a3HvkI33joOZd7M3ZkGnDyvtsSfublPzy5fKfBwm898hEABgffy/vP4/4ved0NvOR1b+aO534vP37Prbz95efzKJdvzhnAvPnNb+Zrv/ZrOXLkCNdeey0Ax44d4+abb+Ztb3vbTm/fpZ3GvKcUOorqMsZasjUbGwz1yXGMb0eYXFasgIkZ3yVSEll2DTbzmLEXP4yCeKNAjytCIuVZLqk1xLGR1a/Q0N1gRtXUg1KneVGFKYMwO8bU3StedszNgaJCgE2zItQwLc2OWdeU+KxMbFa2VfkpeFFawEvzOFrMp+Mbl+kfjmhteJKtgEsUZUcRDyDqF5isIl9OyBYMRU/o9t7xCjv2BKOwWSDvafJFzXjvIksfa5Ped1oOFk2BZfA12JjZnshOX6eyE2qf2lMjoCTI62/YFsP0M23kAI99zTMgcHc+veZyycR25+k1VntapsTPVQRlZWW+SZNsGJnayxciTdlV6L1jbp9/lLYu8PXCjMEzb0aT0sRUlZRYypqJASiCoaMriThWJeu+y9AnbFVt1soOWgUSXdEvU0wuSZdNjDCRnaZ8KUVQoiZQRYWpUzKNUZiRIVnTLNwnXk0fKURrJaE12skikK6THSesPvXJv6u7PsL0+BFsLRfrJAyPdNg+Yug/L+Nrn/0BHJqWKemZjESXPDDeS9fmbJRtcm/pq5TDycYkrhkg0RU3dVa4qbNC7i0Pj5Z4eHGJ1bkFym5E56Qh3vbY1BKHIL1vk6TMusiy/miCUjMMTJgyRs7TaJ1VXVwt0c9WXg/IY7UiYX2axcCZ3rjdubC50MLKSzV3fjiHi8hwDA6+d0ce5/0f/GXuBuCNAFcNkDlnAHPTTTfxwQ9+kHe+8518/OMfB+DWW2/ly7/8y88oc7waR3woCp9ajDFQFLV0SkGoT3h1bQqnZi4ig0uMgJ661bics+RzRgz7BtorAV1Od/hq28uOzwV8oqaUfTU9qITYyu+THWfDmkhePnE03fEqDXlOmCm5DLNSqapCRdG0TwbOYFuCd1AWZ0qwGsnW7Il84yEBuZ0x0Ouw9bx9lB1N96SUchbdiKgv0rugoVhMUC5QdDXFvMJkYSIvwwfs0BGseHLaq4GqpRntj6jaB+l++BShP6jZFqYxzTVjMvHg+DD9jOCMlDRMzRIpLe9d8740YLR5rVpNOm2CcwS/u2K2Ozs3u+Dl02vmzJhuusnC8oB8YRHfjtBZOfW/wHR/26iX44obkhVc0JOixGU7IFIVhjCRjDkURnnKYNl0bQCyEGEIuBmq2qPQKuCDYhRitrIU5URtMN3Xe5FLZVWth5q+BuUkzSsYg2k8HTMTTH3ib6cR9o2UGiXdNyoEQu1BUc7LIp/WhFSkcyEy5IsJ6880VHcM+IpnfILbO8d5tFgk0hX7oy36TliktUKidrsmp2VK5u0Iozxdk1EGUxd9jibbdyDZ4kDa528qwyCfJxjNXAW6CvjEymuCOmBBTTpjQiTRycz2KzbAq0ncVIpQs0pUDooSVaqJ10XBVPHQ+G52Z0dmJworr9Z5320J9/3Pf94x8DI7d3/9q/i9334jL37rHVcFiDmvIkulFC984Qt54QtfuNPbc1lH5xVGu9qQpyZSrYkUydcJVYaJd0ISRjwu1biWZrTX4i2km178L0XAW0XZNUTb1SSRLBpU6NJhBgXBaHReyYpNndASFLjUEG9k0wjl2a6V5vfZcAGYbu+sHMzaqRQrzDA3k8hhOz25bwBOU04JU61wc4LfREe3W/Sfs5fRPsPivbKn374uougpuo9IGkvVEi8QQDCgKgEv6brHJQpdHwyUA5N5on5Jsi5gcnBtwtrnHWTx/Zuokyv1dumpFAymEcr1docQIMtRxog3yFoBJCGgVJjepnSo2c6aWYmZVigMarcH5knnfEz8n45zMYHLYx97V1J25UyqK4zJuG5hg/vnl3CpQZUOXVW1D6aOkHdhsvhlraOtc8pgJ6b8SFW1TEx+zoJ4NDWeYUgog8Uoz6brkKoCowJ91zpjW8pgqIJhbaPLQhmmIGUSE1xOwUltag9GQVn3odjaB+kF7DT+QVWDFFOqaUFkNZP41Xgz8dKxAgJe4ogQW1xqyZdj+ocso2sr7jz0CM9orfCx8TXMmzGltxwvlsh8RKIrrk3X2ag6ABPQ0tYFIx8zchJcIH4fjVHSf7M37rPYHlNdqxkuJhBS5o6CHVuRbSs1LRet/ARU4d3jL8o25wbNOI/KCjlup/GUqVHqDPDyuMEyu7M75zgXC7w0c/fXv6r+6Y1XPIg5KwDzxje+ke/+7u8mTVPe+MY3PultX/WqVz3p9VfylAsJumCq1x0zbaFv+k2glhlNDd7aecghX7RUKRM2AcAU9WqPUVQdgy4DLtVEfUmd0dQrVrXu2HViUIqya8UPM8gn6V4TCjp4iSduwAucKYNSM3Iv76ZyKajjIWu2pQFEjeF9hoFovD4NkxGKAkUtvwoBlaZkN+xh80ZLui6AK1+wBF0HghkpGyvb4FqaZEOe37UUZLLK5TSUHQky0KWEGTRMVEgsyaZjcNBy6vMXOfBuB6ub0y6Yhl1pXkPzevGoSDwwk6CF2h80KThr2KOZCXWMaHA1sHk8id7unDHnm0R2MeZsO2Ce7vN13/3iXRBzhUxL5yitSW1J1YaqZTBjjRpKbHGYGMcVPtK4BObTnI7OcaHEozkQbRLhKIOtk7/0xAMzqpPGUl1OGAqjw6QLRs8wE0OX8OhonviTLdorDpPV/TN14hcwkdQGKz0pk30mM3HHNYAJ1kx7yRoQpOrUzuYEv5FkG4UKckwNzk9lc1bjUsN4ybB5e8V1N57mS5c+ThYi2rpgyQ5Yr7o1OJFyTh80i3Yor7Vmm7Zci76TUs+xk1hpATIJfZXig+Lm+RWeuXCKY8NFPpYfompHlK2UzklDsp5LIlpTLkrtA2pCXoCgZyTKNficlF028mtjJ+BuwjTJByFeUaJL8We3OzswZ9sBc6nntx75yEUFL7Nz99e/im8++V1806uvXOB9VgDmDW94A9/0Td9Emqa84Q1veMLbKaWuagDj63x+5QK+naI2ts68QTlzUj/JsfeEVN7GoqMxBdhtARrJlkMXAe2CSKvmLbry2A1Z7fKRnmhmVWolktEHXMsQrMKOnEQMN2xLA2Iaj4du/ldTr84siwJyUIpmYpDLoj7hn0rEQhWmK02GaaqZD6Bq8NKAN6VEjjbfZfPmmPYpYVpG+yKUDySbgXg7oAJkS4qqBXEfiXDW4PsC6sqWIukHfCTsSzRwYnJ1ktCjgvTUpJuebFGzcccyS+/JCcPxVELmmPS3CACZMkuhMeYzTYwLMxpk1fiJ6ts3r38CXoyBXdPl7lzgXA7Z2C6IuTIm1SVexcS6omqJLzDomjFu5EQT74WUDo9Ly9AnYthX2SSuuO9bbPo2RTDEypGqkhHQ0wJQtAp0dE4ZzMS0X/poAmIyG7GZH6C1EmY6yhShFeO6dUlYzRq4RGRfTQGj9iKXVnk1c9yrX2QJVGb6WpQSadiMFwQvl6vSiWnfKEJsqdoRrmUYXKe45oZVDnS2ORBt8VCxZyKPS3XJNXaDlapHpBwbVYd90TaDGrA04KatC4zyEzBn8GxXKT5oWqZgKR4SKUfX5OhbAg/tWWJ1ucf4WMzeD0K8kdeAZKb7BZFyz5Zbymuv2ZSGudJaCjcjIzK50k0WG0Pj0TSakO1KyJ5qnk5G/p2e3/h5c8nASzOjV72J3+DKBTFnlRP74IMPsry8PPn5if498MAD5/TkP/MzP8Odd95Jr9dj3759fM3XfA2f+MQnzrhNlmW88pWvZHl5mW63y913382pU6fOuM3Ro0d56UtfSrvdZt++ffzQD/0Q1WNb289iTCnJKaqmkSdxyjCVbs2mXVUVephTdi1V2xAPPZ2TFa3TJfF2hS4DphA5l/IBO64jlFNDvhSBgmw5YnA4ZngoperFuNTKAaQKxKeH8lxxhIpjlLWouS6q3UbN9WBxDvYtw9ICqtOSWOU4gig+s5xRTU/UJ16PGc+HMjP+D+emvS4AwctJ/SS8IBC8Jz/YQ1UQjUUi52IwRSAeOOKBx449rRWPriDZ8EQDR7zt6Jx0LH60z/wDGelaQbzt0VWgmLOU84mszMUW15YOHYB0w5PPK/Lr96DiSF6ntbUhX7atMeg37IqKY5TR8lpqpkYZPfk3+SyNEYAXR3VKjpn066gkOee/oYsxV9r3ZHZOfukfntXtLgdD8gtHbn3cf7vz9Jwr7XvSUgU9PWZ/0qfqOVDUSZVTAKGKEj0qMKOKZD2wvtrj/cPrGHrZ9wxDzKZvM/QJ2y6lDJbMRzVLkROpikg5DthNFsyQns5YMgN6OkMrTxkMkXLsifqsDjoEpSjmDMPDbYbPXGblsxY4+TltTnxem1N3djj1WW1Wb0/YuDlh66Y240Md/FyL0EkJ7XSqQvBeGJyiRI1zSdlqfB5NjHDl64JmkWQ1KV3BanwkqZwA2YGKSHtu6oj3Z8GMKINhy0lhZ+Yj9to+hjBhX1zQrFcd+i5FqzB5nZpAz0hXzJzNmLNjtAoYPGMnMrSbeivcec1Rrnv2CQbPqBjuj6g60cyxfxopHSZS8sbAH6ZMVAgEawSk1MClAS++mxI6KX6+jZ9r4eZS/PyZsr7LNVfa9+R85qPdn7kkzzM7v/HzlzfUZ/SqNz31jS7S855NLPTlmPPywOzUvPvd7+aVr3wld955J1VV8brXvY4XvvCFfPSjH6XTEZ3ra17zGv70T/+U3/md32F+fp7v+77v42Uvexn/63/9LwCcc7z0pS/lwIED/N3f/R0nTpzgFa94BVEU8frXv/6ctsdkDqUtPpViKqOUeCu1AmYkV7UPJISAGueYwlP0DPFmhR1V6HEFRmFiIz83O+xKyi193e9StQz5XJ0+UwaioQUFLla0T+aorYGYK1sphIBb6FIuplRtCQgouhqbSUa9doF425GcGqI3B9I2P6vT1QZw0+33QVYCGylVDWhC4VHNiX3w0/SuRpqmNCqO6R+OqdqKotTCNFVixtdlfdCymmigiMaWZKPE9gt8YsmXYilKG5dU3ZjxsnTT6BJ0ZVA+ISiFjzXRqMIUGhdrkm3F5s0J+060UVv9aUcPCECJ4gkbNWGMZkMImrCDsjgzSa4JBoCpj4jaJxNf1q/HZK6078mVNo8FR08FUn7hyK38wNGruHB3dx53rrTviUfT0wXzdozulQQVT0+IGxmSUlCU2L6mtZ6yvR5xPFvgOe1HiFTF0LfZdB0yH03M6UZ5XNBEuiLzMUZ5jPIT0BMrx5zJiFxFGSwdnfN3/ZsYnejSacOgpcn2BMr9Jd3FAZ2kILUVldeMigilAtv9NtVmTPuYZb7TobVaYkYVZlyihlkNVkrxVhojhnUrx0iV1873yKJiKwb+IKEuE09MED+kSxSqXaJUoK2LSSDBkXiNZTvABU0ZDEUwJLpkwQwnr6nvWmTB8vB4D8vxQHpwTI6hBjQ4Si/s1LwdkXuRpgE8wgLjdsSJPXPkCz3aKwaT2jN8j8HUkrgmPc6rachBk3ZZF4DqQTaV1yUR1VyKa1uqdnOsgWqmEeByzpX2PTmfefvL38+zf/WiP81kXr5+Hbzl+ATE/PErDk+ue+vSw5duQ3bnjFEhPLXQ/7Wvfe1ZP+DP/dzPnffGrKyssG/fPt797nfzhV/4hWxtbbF3715+8zd/k3/9r/81AB//+Me59dZbec973sPnfM7n8Od//ud85Vd+JY8++uikl+ZXfuVX+JEf+RFWVlaI4/gpn3d7e5v5+Xk+78t+gqScsg/xfScI43G9Uj9lICYJXIBKE/xCl+1b5iallGYse6qgFaqsKeV65+0Ti2tHAl4WDWVH4S1EQ4j7nqql6B7LiU5to8Y5RBa33CNfTinmDN6AalIZE4XJRaJWJRJNrDzE25728QH61DqhclIy6fzU69KEE8CZpZCPjYoGSflS6kw2ammBk1+6D+2EHQkKWqslOneYkcRSVgsp2XJM0NA+kWOGBVU3FmC3XRAizfhgi/4hSzCSVpZuBEwuUrNo7FFOLo+3Klxq2LwpYs8HxvK5eD/1wzSvabbLpfm8mlCDWdDSsE+N7M5aiZI2Rqj+dkq12Ka/BP/wxz/O1tYWc3NzT/l3dKnmcn9P7v3C36Jn5UTjSiiybADM+bIrFwvMXO7UsYstIzs5Lx0E/TDg5u0X7H5P6mm+J7/+L7cTOm3Wqy6/9sALML+3TO9oQbw6RI2LM0+CrWZ4fY/V51rmP/cUX3ftv/BZ7QdYqeY4Wc1T1mWVLkz3zdKBUk3ilfuuRc+M5TpV8lCxl712m5PVAm+6//PZ+tAyBPDXj3nu4UfYmw4k5jkofNAsxwM0gbbJGbiUtaLLe05ex/qxBdrHLN3jgdZaRbqSocYluj8UFqbebzbgJCTRRE7meol4OUuPHslr9u0YHxl8augfTlh9UcadNzzMbb1H2WP7aBVIVcGcySiCwQfNpmtzolzgSLxGpCrWXXfSdfPAeC/LkTAzS3ZIVgcg5D7CBc2SHRApRxYienqMR/Ngvpe1oss/nD5C/717mb/fM/dQhhnk4gGqvUB6XKGLx7AKXjxMk/JLpVBZLiWZnRb5gR7rz07IF8HFgaobCFHAhSHHv+8ndr8n9TTfk//28ffS7nUnl5+thOxiFVk2/pff+HlzBlB5qrnYQOZysyA7Xbz5RPOm/6D5rh/1Z/U9Oasl5n/5l385qye+0BjlrS3xnCwtLQHwT//0T5RlyZd/+ZdPbvOsZz2LI0eOTL5I73nPe7j99tsnXyKAF73oRXzv934vH/nIR3je85531s+vS4l5dKkVYz6IWb6J2W0a6UGkVtaC8+jtEa3VFqN9MUlNkTeRzMpotAadVWLuLyVCuepoyrbCjgPRUORl+bzBZgG7NZbUkrkO/Wcu4K0iGjjsWOI3XarxBlorAoykGGwKaKqWYuuZc3Q7MdHDK4SyFBAD0xN4w0RyFar6dRnFY1WFiqkRXozxBt+KQYEdSTiBrgIu1uhMYqUJ4vlxkSJbVER9i0sN0WaGcmEiKVAebBbqdDIJSANINuV1FT1DvC29OC5VRP3AeH9M/JCdibjWMylxYYruYMZkqqZMjI6n0cpaAwaSmJDEuPkW42tarD/TojzkJoM/Pus/n0s2l/t7cr5z98bbdhzEXCh4ae67y8ic/TTA5Uqfy/090XiKoNDKs35inutWpKxYuTAJiglaC0MfS8BL91jg9Mf38o9z1/EZrYcnAEXjiZWjwLBazTHyMXtsfwJqmtSyCEeqSzZdm2U7YN11ecvDn8Pq8QVYqujtH/DcfSeYizKuSTa5NX20TvKS5DOYMjzDJGY5HnB07xKffMZeHj22TPcTEYv3KuKtiLgJtpkxrgM0/S4hMvhECp2pCRjKCpVplBVmvWqB1oFrWxvMmzFLdkBH52y6DmtVl9Xa+9IEF2y5NpmP8ChSKyWWz2itECnHghmxYATIDH1SMzQRDs3ICTs1cCltXUhMtc053NvkXw4skq7Ka1d1VHRohAm+ThFr/JKVk9dbJ7XhJfxF+UDotqkWWmzdENP7qhN85rx00XRsTr9M+cSjPY6f9V/PpZvL/T053/lo92d49uDHdvwxX/zWO1h44cY5H/pfvn4dAJvvWLzi07vOZ97k37zjIOY3ft5w7M7vOPPCvzl7au2sAMxf/dVfndNGnc9473n1q1/N533e53HbbbcBcPLkSeI4ZmFh4Yzb7t+/n5MnT05uM/slaq5vrnu8yfOcPJ+2rG9vbwMQnxpgoxY+7mC3ckK9cwqNaX5WsmSMyKsikQDExzYIeol8ISLeVqhKfC8qSKqWb0W41IJRdW9MHR2cB0zmhYFYK0kf2UZlBdXeOTZurTPvHykIRhFvFujCUSwktWzMy/PUoKtqG0zmqTqG8ZJmvD9BF0uY4yvTpBSvp9HBRSlJKbPsxGMJOedEKgfCTnjZkUdDMeajhCVRLuATIxrvEPCxxmaeeKApuwZdBaItBQR8LCEF4yUj4C0TH4xLNLoMVG1NqHEHCsqOxUXCMHkzBZDyh1NHPM/GTFsrUrEoPrOc0odpuhoIoIkjyv3zbN3cpphTlF3I9nraj2hs9rh/Ppd1roTvyZUyOwFemtkFMU89VwtwgSvje/K3/VvYaxwrRY/kpEXnUugrqVwGKofCgTdowI4d6YZi4eOG96Q3czDd4tntKcBo65ye8pP0Ma2CdML41qQnZt11ibykcGUh4pfu/yLWP76M3p9z+7WPcn13DYOna3MSXVIGw5IZMAoJfZ9OijEBOrrgULzBHjvg2d1H+eTiAf7CPgubJXS1wm7FYvCvk7mClhN5eV2I/LnwENfyZKtRQY6BQSuUZMTgSpGJnSjm0coz0rmEEyhD36WMXcS16TqH43WW7IBPZgdp64JT5Tw9k+EQBmmoEpbNgCxEpKokto5N16bvWmcAtESLQsLgOdze5P2u8bsggBLZLlWIj0fY+rrrpTHuw6QHJiSG0E4ZX9dj4+aI/HP7/PAN72JOZ5yueng0Hxoe5n7dPoe/4EszV8L3xL/tLvjmDwFnz75AXbb41p0DMR/t/gy6+7fMfe6FhQgsvHDjqulRuZzzvtsS/vLOb/mUy//HvucAHzqrx7gyRP7AK1/5Sj784Q/zt3/7txf9uX7mZ36Gn/zJn/yUy1VRgk0lDWyYyck7TE+OG0N8VTfC+wAksgozHJM8vA5HBMToMhBvleDr1SirKefl8rIjqzetDYeLNT5RtB4dYzZHqHGOX+yycWsXmwWSzQqfaKLtCp1XqMoTbxXTA4YT46GPjPTRJHLyHw/lQLR1U4f5EDCPrMrraFLLZtmyqvrUmGaYyuRUDQJqj4gqKqKhgA65vQQg6HGFjw0g5Z6jPYbOKSdBBiDFYVmGzkryPS3aq1UNwAJ27CgWIrJFYaHS9QpvJWJUVwHtJCTAxTPbPdP0DEyBSuNz8Q5lIgGgzWdoZyKWjWbwnH2sP9OSLwfaJyDZCJhMk2wGCh4D5q6AuRK+Jzf/9TeetXn/sbMTLMys52UnTfm7IOaJ52oCL3BlfE/+5wO3cvP1AwDiLYXJa5O4qUsSvRQVB+9RlcNajS48dmjQRcwftO/APtdzS3oSo4IwMMGwZAekumTBjMh8xJrrcsBu4VAUtV/kQ6NrefvDt1J+aJ4wF7j18EnuWnqARJcsmQFZiNlyrYnnpKgpB48m8xFaSVdMrCqWIynS3G+32Lo55Z9Xb8EONa2WFXlVUU7Zl8pJ/HIlcfym8vh2hG9ZfGLRNTsjHSlBmPeh5aHBMtd31+oIaT3pukl1SVsX9HRG36eMfCL9MMGwJ+rzSL7IdtUi0SXXp2vcmx8g0SWpKvCI9MwHjZ5h5gcuZd6OGLiU06MeOld1ZLKaJIoKUKlLo+vY58k0PS91BLXrJriWZf2ZEbd87Sf5/KX7eDDfx3XxKnMmwwXNoWSTm+Yj/nGH//YudK6E78lN/4/l5Def32PulBemkY29fH1nEtAWXrixI4/zdJ1/c+p/5xeA2+771NCHzz/8fP7iLAHMWaWQPXb+8R//kR/+4R/m5S9/OS972cvO+Hc+833f9338yZ/8CX/1V3/F4cNTzeGBAwcoioLNzc0zbn/q1CkOHDgwuc1j0zGa35vbPHZ+7Md+jK2trcm/Y8eOAfXqSx33qMb1SoHzUiQJAlhmu1eAMB4T6pIqNRyTHN8kXS3wkaLqWPI9Ca4t6WJBqYlMyluh1aOBo31siF0Rz0vothhdN0c0DnQeyYi2S9JTY8ygkJSU0qHGJT4S3bRPI6qFlLJnKecsygujo3ydZe9hdLgNrVSAiZ3uoIEzwYuZYWeaaV6rMWewHeNlzXhZDsRxX+KPXSciaImHrlqaYkFRdjXDAxGDg5GktS2kZPvauJbGDh3J6phoUKLzCp174r7HDj12WJKsZcSbEvssAQEBFzP1tzTbr2a2e5Ylo45OrvsNUAqlNcoaQrdN/3kHOfk5hmIhYAeKfAHKriIaBsq2ouxemCRyp+dK+Z5c6Ny98bbzTiW72GlmuyllnzpXG3i5Ur4nxVbC+rjNfaf2EG8FdOnk5L2Jzp9pp1eVQ2UiMbPDivkHczofTnnbJ5/LB4bXUgbDtk8x9Yl4VEcpa+WJlGOl6nGqXGC1muNtp5/H777vsyg/NA9BkV7b587Fh9HKS5qXCqyWPQYuJQuRsBS+hQuaIliRXPmYdddF43EoYuXo6IJbeyc5/Bkn6F+vqLoRvhURWvEkiWsSP9ywFiCvr/BNxQqq8lIaPapI+h47MIyriEUrcrhUl5NAgiPxKjelJyfenlPlPKtVlzIYeU+qFqtFB60C61WHkY85Ucj7MPTJRH7m6zCApjOm9FYSy2xeKwjqbXbhjBQ1VZRyzKsT1lRd7hySGLdnjuyaHsNDKevPSjBftM4rDvwd18er7LF91pwoKJr/O+YKcfHXc6V8T/S3fu8FvY4L6Wz5ue/8hhnwct0Fbcdj5+Xr1/G+266MJNMraV781ju47b7qccHLuc45A5i3vvWtfO7nfi4f+9jH+IM/+APKsuQjH/kI73rXu5ifnz+nxwoh8H3f9338wR/8Ae9617u44YYbzrj++c9/PlEU8Zd/+ZeTyz7xiU9w9OhR7rrrLgDuuusuPvShD3H69OnJbd75zncyNzfHs5/97Md93iRJmJubO+MfIHn8qUUPckKWTaRVytR9KYWcTIdxrS1qTpprgBO8R20PiB9aofcJQeBVS1PMR1Rtg0sULtXSl7LtSNZL2g9tYR5dq82QmuzQHAToPJJhxqUkoYSATy3FcptqvkVIRFs8ONKiWIgoehHZkmG8KN4bU4ixPt6usLlntNfgFjuTZLFJyVgjH5uVjTXRxFCDFXemDCsEVH9I57Sb7PTLtrQp54sRxUJEMKIhDkb6Xkb7Fds3wtYzIsr5CBUg6jvssJwcKFwrkqZqB1FfokX1MEeXHlN6glV4q0i2PeTFlH1RjwFdM90uE8CpJbRARZFI/5bmWf2cvTz6eYZ4U9E+qWifDrRPSSGnixT5ImR7rgwG5kr7ntz7hb8FnJuB//HmXMHIuaaNXe652rtYTs5/5KoCL1fa9wSv2B6lhIc7pJseXYe7+NhMOkOmEfce5VwtLfbYQcHC/Y74fV3++B+fx6888IW8t38jK9Ucx4tl+i6dSR2r6PuUf+4f4dfv/2w++L4baT8UoSpFcV3ODcvreBSlt6xXXR7M92Jq4AOwWgmYGfmELddi5GN80PR0hlGBkU9EqoairQtees2HKG7IyBcsxUKC6ySEtA55acJQ4khAjZX0TdPP0cMcVVSo0kl09DAnGnhUBZ0o55npCXpmTKrkfRr6hFg54no7ezoj0SWawOmix+lijtxbrPLk3rJWdlivOpTBMPLxBOSlquJEMc+Wa9UFoDGjOr2tZQqUU7LgV3r0MEPn9XGpPyL0B6jhWEz61bTfhcgyuqbF+q0J688xVF++yd03vH/CHD0neYQDdovMR3R0TqQcsb4yAMwV9z2p50L6X84HxMzeZ6fBSzM/+9ePD+bOZ37vt5+8RP5qmN/4ecMXX/vZO/Z45ywhe/3rX88b3vAGXvnKV9Lr9fiFX/gFbrjhBr7ne76HgwcPntNjvfKVr+Q3f/M3+cM//EN6vd5EOzk/P0+r1WJ+fp7v+I7v4LWvfS1LS0vMzc3x/d///dx11118zud8DgAvfOELefazn803f/M385/+03/i5MmT3HPPPbzyla8kOcceDz+Xoj2wuV1LjpoeFTttLYYz+0FCqE3+CqpAsBZVlrC2SasoSXptoc9j8aeY3KFHJXqUo0bZFDxYQ3HtMvmiJd52dbFZQr4Uka4pzKCgWIwp5xLMOCJbtsR9j87F8xK0ophXlH0jkcp9hx2UlB35iMcHO3RPbUqkpXfTBK7mhH8WqFgr/5wXsz9ANJWdBe9pncwYHOyAMpQd8cQEXXt6cumB8cZQzClMBnao6JxyxJulABUvFL1PI0JkcK36Mt90JUgfjBqXKCuxm2VbMf9QfRCwVra1MfA3Jv2m+8aqKTuT53Xaj8UdWOSRL+4xOuRpP6rpHfWYUhiXaBRINgV8VW0NTx2kcknmSvue7OQ0oOSJZGWPB3KudODydJirCbg0c8V9T2ygeKjL/P2yYIMLTMrYGwlSCJPVfayZpGApF2idyDDjmPYpy/bxffzhrT3uPbwPqxypqTiYbtEyJUfHi3zo9DVsHZsnPWXobYCPYPuGki945r0sRGO6dTfKetVhu0pZjEbMmzGJLhk5YSqW7ID1qjvxiOy124x8wjAkjHzCtm/VUcYjFhcHZIvLmNxgR1W9v46kgT6RF6m8l7UlpaZm+LpAOBgDWqNLT7Ku6JdSvrlsRHLXsCZaedaqLkZ5tmq52zPTExTBcKqaZ7Nq44MiUo6xjwHx9fRURqyq2tOTCKAJjkRLb06kHIkuOZ33SNYV8WAmgKA5zjdJlc00Xp9Oi+xQj60bLIPnj3nm4VPcMneararFo+Ui10brHK2WGNUMkMHT1jlWXxlFllfa9+S+f/X/ZeWhX7jg19UAkidLJ/vGn38Fd344P+OyiwVednre/vL3c/fXX77nvxADf2PW3xkNx3TOGcDcf//9vPSlLwUgjmOGwyFKKV7zmtfwpV/6pY+rcXyi+eVf/mUAvviLv/iMy//7f//vfOu3fisAb3jDG9Bac/fdd5PnOS960Yv4pV/6pcltjTH8yZ/8Cd/7vd/LXXfdRafT4Vu+5Vv49//+35/rS8MbjTm9LS3uzc6rqpAIFYWibnyfXfH3NYnVnCzXpne0gY0t9NYArdWkYHFSgNUcwLSGOMLtmWN4TYIp6nKv5YhsQeNShcktqgricUltLdvy2JFD+UA0cCgPyTaYsUeXXuRa3UgOEFvC+pwhvYIzo4dnO26Ksi511NOoYmUnrIdSCnt6G0KHKoXWqicaeIp5Q7Lp0IUnaEM0oAYDkGwGzFgkcAaoOhbXiSXWM5YDNpGiamtMZqW1ud5eXXlM7okHgeTkoG5B9tNgBVUXdJaVxD5bO/N6kJjkNCV0W6ze0WV4rWP+44bOaSdytcwRDYS9iiqPTzTKgb1CAMyV9j2BC2dfHjtny8bsgpeLP1cjeIEr73ti+ob2mqZzqiLaLlFFSUgMLjXovD4xbkoRax8MzosBPgRsUWK3I+LNlPbpiNHRlKPzz8DHUHbgH3qy7zNjRTRQzA/A1KmO/RsCz7nlOJ85d5RIuYmEaskOJzK0RJdycm2EIRj6hHkzxKNp65yOzieBAScrUVf4oOm7FjcsrHNvew8+UiK1ck7ioONIZHJBvI1SIaAJWqNU005vpEvFe0zm6Jz0HFtb4OF9e9hrt3FBs2wGDH3CpmuThYgFPSJSjnYdGT1XA7KTep7tMiX3EVY5luxwIpVr65yVOrGt8oZxiOianK7NSXWJIfCR0wewI8RnWczIxGrWXhbI4jOqB6qFFv1DEflS4MDeLT5z8dikSNMHzbFyidxHzJsRaNj0bQyerRqkXe650r4nv/V338lffPvZeR7OZp6MjXlsycfVAl6u5nncpLEdmnMGMIuLi/T7fQAOHTrEhz/8YW6//XY2NzcZjUbn9FhnUUFDmqb84i/+Ir/4i7/4hLe57rrr+LM/+7Nzeu7Hm+joCqFi2ofS+Clm07sa2r9hLhow03SLQF0QGaa/U3sxmh1iA3BqLbTvdRhe163LKCvMuKJ/bYSLFXYYqFqaoGNcrKhSRVAWO/LoykuEMuKpsWOPKTyq9FIQ5iSq2BvZQUuMsKKhVZS108+gkYhNii1rcHNGjLSDqhIQpxR7PjRm7bYWKEU0qFA+EG/kuLa0Gs8drdBlYPuInaaHwaQXQAz/UmhW9Qz5vKFsKUxuUCHGWwFeZljWkjiH2hoQGvDSfDazhZtneHYqAS9GQ2QZ3rjI9jMg3jC0V4UlKuYMKDC5AD8Acg89w+jgleGBudK+Jzf/9Tde8GOcz1yN4OV3/uvbL0sfzPnK165W8AJX3vdk7l7FwqmSdDWTE/k6kVI52U5J4lIz5Y7hDEZGVQ7KCguYUUG8YSf7zGA1VUvSHJvjQpUqXEvRv8Fzwx2P8LlLD+CDxqgSozx7raQ+NSCl8bsYpKl+y7UotXhLNJ5NOkTK0dE5RbD4oHBK44Om8FbKKJ2sHwUjx7OgVP2/vAdNbUATqwyAEZ9piKXU2RRQnGrz8A3LLNohB+wmBOj7FkeLPSS6nACwprCzCR1waHxQ7I37E1YlVRKv3ERLj3yMVp66bpPSG/oh5YHhHrJPzLP3pJdjy6RwU02P/U0ZcqM+aCUMrk3ZeDbowyNunF+dMEA+KPouZeRjeiabFI9mRJP45ythrrTvyU6Cl3OZqxG8/N5vv5G7v/5Vl/x5z5d9uZjgBc4DwHzhF34h73znO7n99tv5uq/7On7gB36Ad73rXbzzne/ky77syy7GNl6yCWUJKjqz+FCfeRKrGo9IA3AiOz35b6a5zGtxGY0zeZwZ87/sJD1+eYGt5yxgykA08LhYU3YTXKJYvLcgaMX2EYsuId3ypBvSeh9tF/jEUHYtuhIJVP9wRNy3JFuSEOYjiavUVcCMKumuUQqSaMqmNECgkY01/pjmPZkNLSinSWShckQPr9Ded5iip6k6VtLQYpGzBatnUsQg2RYWRRfSFROQ5JdiLqLsaIb7Ndt35NhTMa0NjR0qdC4HFZ9Ij0zngU3xJrk6jKCJs4wsqgGQztfdBEZApHcSlXxggdOfZQkqEEygSgXI+QhcIqED2kmyW7xZMdqrya65MjTLu3N1gpdmLheI2Z3LO71jJelWid4aTdh2VTpM1rDaaurls4ZgjaR56ZkTzBAk5avSmKKaKHrRmigy+NRSdiOqNKLsKfo3Om577sN8wfK9NVsiq/5LdsBKNce8GZKFmFQVDFyKVn5ibs98BBaWzJC+b028J22d0yZnvepi8Hg0a+M2yiEx972YMB/jY12HuMjxo0rFt2gzj3YSWqDLgM6FeXGptNgrF5i71/Dnye1sPqfFZ8wdp2syfF3amfuIk+U8LVMyb0YciDYxBIY+4VCywbwdczheZ+QTsmBZMgM2XZtD0Qb3ZftZKXoAjF1Ex+SsFD2qoHnPR29izyehe3SMXR/Kex1HwhbpQGglwizppvhYPsN8TsGhMV9y4yd5ZvsUq2WXPVGftpb3NFKOtsknfpieySiDnbye3bn8czWCF7g8MrIL8d78+oHb+eKd25RPmbMGMB/+8Ie57bbb+C//5b+QZULf/tt/+2+Jooi/+7u/4+677+aee+65aBt6yWcWxMyuxuAmP4dQSftuCOLTgKmUTM38HtVv8+wBCyBNGN0wRzSSVbls0aCdJJPNP1hi+yUoaK/WUqpCPCJmXEc4OymtVEGRL2h8hEiyrGyflGNq4oGwNSgl21rV0ZBJTGinhFaM6yb4WFN2LHbkSE72xbyo1FSydYbh3xPKkt7H19m4Y5nhAUv7dIUKUPYMRVdTpQqbBVrrnmggvh7XisQgqRXlnCVosJmnnNPgFK4l4CJRUHWFyfGJFrnc1uDM1aNZIOkcmEjYlqbQ0mgx7ivF6JqUoBuPjaJKA6aQLpuiJ8Wg7VUx0bpU01rzqG17RRaP7c7lmd89+n8/7uX/+sj3XOItefK52sMDni5jh5VoaEOQ48QsI19H4FPV0qvIThkY76f9W66W/0aPc6gOMdSxv2VHMToYOPLMU3zx8icnq/0jH+MRhqAxuEfKMaoNfrmPyHzEoC56TJWAq44WmVXmIwyBqL68kZQNsoQQQ7agKToxZRdGBxTFHgfdklBqVOwx1lP1I6INixkr7BBaq4F0w+GtqvvMAtEg0H4o4p/mr6V3Q8Y1yRYexb5oGx80j+YL7Iv7dHTOgh7R9y2GddhAWxcTWVyqKlJdslrNkaqS7SpFExi7iPlojFaBlazLw5uLdO+N6Jwq0Vkl8j6jxcg5eX/DROIdrAFr8J2E/vWwf2mb53WP4tC0TcFq2eOm9BQjH+PqAIQiWEY+5vp4leVkwN9yaEf/vnbn6p6Xr1/H5jsW+emP/CcA/uLFv8uPft5/fcr7XWoW5nz7bP7pF36Yj5/8WY7toGn/sXPWAOa5z30ud955J9/5nd/Jy1/+cgC01vzoj/7oRdu4Sz6uAhtNkq1CVckJsbVTyZIxcrlS4rUIflr+3iRfGWZO+L34R5wXNsY5SBJUmpDdsAcXK9K1kmLBYsqAycTrAhCMEvP/2E/6UIKBYj4iGkppmB0Hyo4UQPpIEY0DpgjYYYV2Ij/ztuHzlZzQRxY/12Z4Q4/RHoMuxfSpK3Cx+FPMLTFxPzB//wj7yDqhKERy1gC0+vWqjW0WPmpZ+awFRnstnZMl3iqGBzV2CHFfTP1QF4VZja48unQQLHbssf2SvRWs5zF2JIVu20cS0i1HlUQoH2h/co3QlGCZGXasIb/i+nPz4qWZxEJrLSVjy5rqpjFJUqLfM4/yUCWKaOhJtp0UZc6Av3jbY8e7DMyVMJeTfXki0PJ4t3kyIHM1sDBXs3zsShxdONBWFopCEHO4FZZC2uqNyKuipl+rlP1WzYI3Xhiqanr8gTqQpJaSGU05ZxkehuTmbb5o/730XUruLV2T069SjPVkwbJdibxpyQ7Fn6GgDJYyGObtGE2QjhlVkuqCCIfW/gwmpmcyjhdLjLOIzljO9zefBfN3rPJVB+9Dq8Aj4wUKb9iTDHFB8fBgifVxm81+i2wcUR5NqFoib5bjgxx70rXA6KNd/sbcyHMPPspSPOKW9CSbrs0t7ZMTX8umbzP0CWWwk1QxkYwZ2rpg03VYsgOKYHhm+yQPZXvo2JzKa+4f7OHksEf/vgUOPOCItkp0Pi2mnAQONN02DXDUmhBbql5MdU2BArQK9PQIHzSrZZdHi0UyHzFvR+y122y6NqUybLuU02GO7SvEA/PpPpeTfXnscy+8cIP/64Xf9SnXf9VbjvNNr36Msqeet7/8/bz95d/Oi996x2WRk53tvOHlA2677+LJx+AcYpTf/e5385znPIcf/MEf5ODBg3zLt3wLf/M3f3Mxt+3yTb1SphqmpO4SER+LO+M2Z8wZ5v4ZD0wTvdgkZSG+Fx9rWqfySSeMHdYeFg/FghVZVgi4liaf15RdTZXKR1bMWcnWd4Fo5OmccnROeOKtimRddsjFvOx8dRnQowK8J7QSiiNLnPrcBbavtbRXHUnfo0vRM3dOObrHHclWoOwoTt3Zpf/8a/DX7IUkFtA28/qD8+jVLfa8f5uqBcODEcMDBpPLwclmnnzeUMyJXlvVbFbVjvCRkuJNq4kGFXv/OWfh3kIO6gaqVFN2FPMf3YTtwTRwoChnDPx6+h5PIpNrqZvSk4OSrsBtx4SgsBkk2/K+FT0BeNFAfENlW1N0NUVP49Jdyv9yz5UOXh57+ye7z6VgRnbZlytnVBCWnMd4DnThhBGvu6k+pZC3SbsKcswJlSOU5eQfVVX7KQMuMWQLmvxgxRdeez/7om1J2dKOSFfc0Fqha/I6glhAkFaeVJf0TMY10QZH4lUOx+tcE2+wYIYcsht0lLAacd2jMvQJaZ1O1tYFrbSkasPgCDznC+7jy6/5BLe3j9HWBQC39k6yP97mGa1Vbpk7ze3LJ7hu7wbPuHaF4rqczed4YWy6IjMLCuwIWqcC1b09Prayn9W8w9AnLJsBn9l6iL1mmyxElMHS0TkHok2uS1Zp6wJX+1tOlXMczZdZqXqMfILBM2/H9EzGStEl1o7TDy6z8DFFslFh8ulJoqrqvpeiFCN/CIQmmCCyBKvJliPSbk43zhl5YbFGPub6dJW2yRm4hFRVZCEi1SUdnbPuupwu5xiVV4YH5tN5riTw8mTzx684zMvXr+M3ft484W3Olxk5l7mQ5LGX/Na5HT/PZ876DO0LvuALePOb38yJEyf4z//5P/PQQw/xRV/0Rdxyyy38x//4HydRfFf1+CAG/HLKMoSmuCoElNHy/+zBprndDEND8I8PcJQGbVCtlNH1c2IgNwqXGvGrWIWqAv0jMf1DhmzJUrUM42WNS2qQk0l7s48U44MpZVdjxg6TB2wufSlV25AtRxDE+B4NncRcpgnjG5fZvi4l7gfaK5LBr4tAPPS0VisBQFuOoMHHChVgtMew+Zwew+ccIHTbU5Ojn+78zalN9v/9FkVPMdofMLl03ZQdjYsFGHirKOYixgdabF8fS4KND9KRk9amzJZmtMcQNHRO5Oz9m1NwckXec1snozVxyVCHIkyBY5g0QldyuRPzbNDQedASPjhXF3yGuuxTAg7yRdFjmyJQthFwFV0ZJv7dufRzruDlbO97MQHGLni5wuaM40T9c+WlC6UQGa/IlsI0HKYx9EcRKopQSSz/rJV/dZcVRkzxVccw3qfYf2iDO7pH6eiceTviSLzGkhlyXSwn1j2T0TV5HelbTLpWmtF41qsuQ5/w8eIgm17Svxqz/NDHNeOhpItFBbI9geS5m3zJ8ifZEw0wKtAzGfuTbdq6YMkOiZRjX9znWd0TfPm+j/Ml+z7Jzdeeont4m3zZUfaUyIhzOQalm4H5e6F83yL/fPRaPji4lmENRFJdEtfdLoZAqsrJ6+3pDF33wYxdxOlijn8ZXcdHR9fggqZrMhLteO8D17P0fk33hBRpqtLhWxFuqUtoJdP3vy61Dql03KgaZJYtTTaMWRmKHG+hfo97OqOtC9q6kDCEYFnQI9o6Z6/tk+iSxFx4cd/uXJ1zvsDpj19xmBe/9Y4nvP5CAMZTzU489pe//V/vwJY88ZzzEnOn0+Hbvu3bePe7380nP/lJvu7rvo5f/MVf5MiRI3z1V3/1xdjGSzahqup44/pgYwwqTSRCWc2wMlG9um8ac58SqdlsqWLTTdJE+tYn38pofLfNcL8hW1BkS7HIpLUAlGxPxNbN0H+Gp+iJIbK16kk3PTbzAgJ6ZsLaJFtuImGL+tJWH7RIo3QZ8FahC4/ynuKaOdZvjcgX1OT+wUA0qGidKogGFWZUYnJHa82RrnmiQSCpwwPyBcPWZ+4nHFiWg2o0XVEKZYle2eTAe7bpPCoAwEf1yloWsJmAiHzBsHmjpewqTC7bmi1ZBgctw4MxRVeTbniWPzggvv+0MC9KTdkvN/P+ajX1G81GRNedLxN2xmiCAZeAySHdCBRduS7ZchLvXAMZUwqwa61U2OzKKLL8dJ3Lwb78wNGP7cjjPBkbs9NA43f+69t3wcsVOJO9RwNedP3Pz1xuzaRfbFIubM30f2um9585uQ7W4NOIbNEwOuS4ZfE0uY+kyV6V7LXbHIo2mNMZPZ3hgsIoz75YLtfKE9VMQRZi4roHJvMRx4sl7s33c7JckCQvHAtmVEcax2y5FklUoW8Y8kWH76PvUlbLrkimgpkUSW65Vn0yL9KuZ6YneG7rKF+67xPctvck0f4x+WKQ45ERpYDNPK11R+9owN7X4oPr19D3Ir0yePaabVJV0tY5LmiKYCapYyfz+TqJrMIHxem8x3bVYq3s8IePfgbv/svnsvj/pizclxOvF7X3pZJUuOYzcE6YmBAEXNoayBiFjwy6Cqi1mPXVHh/YvpaOKrgm2uBAtMk+u83BeIv5uoxz3XVZNgM6OscHjfPnfLq1Ozs477vt8vSdXSjrs/DCDf7pF374Ca/faRDzXfrbd+Qx/583/Z/8/Pe97cI36EnmnFPIZuemm27ida97Hddddx0/9mM/xp/+6Z/u1HZdllFJgkLXkbz1hY6Z+OGaiWly4sNMQ30DXiaG//r/plOlYSuUws0llF1FNBSZlq4UuhRWYOsGTedYINmGZKvCR3KdruR6kzWxzRBvVqhKfnepMBwm92AVKkfa6yMwo5IQGYYHY+wwoCtqpkGhneycq5YhGskKkRlVeKtprXjKOUu8WRGsAI7hAUO2sMDefzaYkxsQSkJRimcIMI+scnB9wPgZy2xfF1O1Fem6Jx57yrZIwnwEUT8w3GcwJVQtMBn0juXExzdQeQmNXKLJ37f6TB14E2/ZSPUKkedNgKbRNSsmH2RrzeNiQ7wdcLFsA9Tlm5mwV6oCkzlMHadcxbsAZncubH736P/9uN6YnfDE7IKWK3tUFaT7pKwEiPgZIOMC5MVEUjuJT27kZrPsTb2wpmDacxWJHyNbVpjlnL3xgHkzJNUlZZDD+rZPMQQORJuUwRKrVYpgBLj4CIeklLl6HTNSbsKwlN6yTgdTA52Rl5O/0+Uc94/20ktyblpY5fPnJDBg5BO0CiS6JPeWQSW/+6BYjEakqkTj6eicg9EG0bxjs2jxsWGMtxHxlqZaUZPFLlMEeg8pTqkD/OLaF/P/ufkA16Vrk5LNti6IZwIHVippdc+9Zc5mnMrneN+jRxgPY/zY0vtExMFPVLJ/H1forIJKqg1UXkrMdTUTpdy8/94TjBHfZuWJB55kwzKeUyzFQ7IQEVGRqpLMx/Xrjxj6GKMCK9UcK9UcHxkcZCNrX5w/tN05q/nZvz5wuTfhvOf//Ob/AT/wxNd/l74wT8y7V/6R0196E+/4yGvPcws/dd7xkdfy4r+6A87RxP8l/zLPT5zlbc8bwPz1X/81b37zm/m93/s9tNZ8/dd/Pd/xHRfXsHOxJ1SVGOwb9qQ+OQ51XO8Z0jGQAxMzBxWmGevqsUyMMRLtqzW6cKTrgWgs+fPZkqXoifdCV9A55Uk2S+lHaddRk5WfyKxMLswKSvTUvmUxuafsyWqdLv1EkhYNKkw/ozjQY3hA0zvmMGUgKGFH8p5GVwZdBLzV+F4sO+taG6zqokk7rogURENN0VOc+Lw5Dv6dwjy6Nnl/cE6M9mVJ68Nj0mM9smvnKecsPpKeAh+J1jkeSABB+2SO3RihhmNClkNRnpHWQ1HKe9eAl6Zs02g5ADUsjK6Te5xD1UELKE2oG6Dt2FN2TR1UIFKxoKX/xcea4X5D91GHT+RgbkpP1N818X86TcO+XIh87PHmyUAMcE5AZhe0XD2jQgDCxOui6mNDQIzizUr/tEi47hlrFsyak+l6JvLlhoUxiqoF2nis9nR0QU+P6fsWHi1ARlUTH0lPj9l0HSLcxM+y6aRkcVini2kVJslkKYr1qst61aUMhkSX9F1K6aWP5VBrU1LKVGDLtemajIFLMSqQ6GoCjDSB48USW65NW+e1j8WQmpLbbzzOQ0uL9E93KecsdqBJtmSBy2aBhXsV2Wqb/3nyDvSBjIPLW+xpDTjc3mRf3f1yOF4n0SUtU/LQaJlP9PfzkXsPM/+hiL1rnmgc0EVFNKzQuUMPClmEhPo9R86EjBbWZRbE6LoKwXmR/1UBMwYVeVqmFABTM1niGao4US3Q1jl9H5GqklPlHA9s7WFttXXp/vh252k3DZOz+Y7Fx/W/NOb+N/k3n/Vjrr3n788q+ex854vPI4Hsi37kF876tucEYB599FF+7dd+jV/7tV/jvvvu43M/93N54xvfyNd//dfT6XTOeUOvtFFKCSiJrJj2Q+2TqOOHATlJNgZcQMXNMv60/GoW5IgfQ4CMimKRmckTYXNhVYqewUWKsis0urdM2BioAYQWn4wKAjxcoiayMR8bil40LWFESi2rtpGEr7UxlBVl14rJf9sRrCKf19hcvDT5nCFdd1Qtgy49upLH9ZHCtTQ6l+fVZaB9uiIeaLavM6x8ZpflSBM9vDJNCLMSBxrKEtY2SNe3aCVx/Z7OhBzUwCTkYvoMMDXhA6Eop4EBTaJbA1QmuvGmaNRPYq2bz0hu48FrVFESrxe0Vi2bt4Bygc6jInFTLoAN9I5JzKlLpjS/Gu0yMLuzM/NEIAauHFByYOs5u0lkOzgh0gRd78M8km6FMDNUbnqCbKhPmP3EeyHXAYjJf3JUaRLI6v1fUNBtZ9yYnmbBDAE4ZDcoMLigyULEStWj71p0dM7QJ0SqQuMnrEoWInomIwoVWYjZKNssRiPauiDzEVtOTryHVcLHtvZjlUepwP5om9VqjqSOW94fbTFQKUvRcAKQEl1OGuqbaVK7lpMRC9GIuSjjeHuBY+1FqvUY19KkRpFuyL66vRJI1xVVq8Xq/jbH9zk+sFCQtgvGw4RQaJQNBKdoPRTTPRq4/mRJvNEHrfCJdJOJlDoQWhEhMaJeCKEGMBImI5HX4hlVtTdJoQmJJURaSo8LCKWmX6WsVV3SqGTTdTB4VqoeHsXIJ2y5Fl2TcXS8yOmNHmp4cf/edufTYxZeuMGL33oHCy/c4K1LD3/K9Y38azYA4Nid38GPnDrES4o/4Kc/8p/4rJ964SXb3os5Zw1gXvKSl/AXf/EX7Nmzh1e84hV8+7d/O8985jMv5rZd+jFmqk82RliU2kehaqmYaqVycj3juVBxNGVZ6phkqkpkaI20LHhAGuGDkh2zHThUgNYpB0ZRti0+FtZEGo3l8YMBO5bEMZdofKQxWS1JM4r1Z1mqNix/xKFqABQNnZjVixK0JlswYlx3gaojTIREL0OyKS30wSjKrsG1NC5SFF2NS6G94olGFaqOdy67hjpshrXb2yyrfUQPnBTQAsI0gbzmqhJwUpYTQ/0kecfW0jqlZiR44itSjXcIM+MrakTk9XPEatq7Y20dOzoDkhrmJi+w2xkL9xqqVsroQKDsQNHT6CrGFJ5s3qCCfC4mEwamMrsm/t3ZuXkyELM7T78JSGw8zqCQk2KUksWbJj5ZqcnCjqrZ4okHU6n69xlQE1lJxtJyHEBBK6om4GVBj2mrilh5UlWy4nqcKucpg6EIhr12mwUzmhRSLjDCBUUZTA1upsEsDjUBL6fzHidGcxxfW6CdFtywuFZLxyTC+GAsbEyiS8ra+N/WhXhiEHnaVtXGodgoOxwbL7Inlm2+uXOaQ61N9rQGHF1cZG2jy9ikoBTxtnR1tddK7MjBxwANZdeK9Gy7QheyQOcjTTTIiDazM0MRgFAzYKJksGAsuIBPjHhBrZosiClPLdcWqVkwCpTBt+SAHA0Camzo2YwD0SYg/pw11+VkPo9D44ImUo7TxRzbRQvntMgGd+fTYjbfscjCCzcu2uM3j/0f/td3PyGDcmYM83+lKTx5O5cOvPy/x/7hnFmYd//HHzhrFuasAUwURfzu7/4uX/mVX4mZbZR/us2s5Ksx3dUnxY0Ouel/Ac6MS9ZKcv+Dn0qcoPZreIIS2YAeldixFDRGg0ra6Y0mokJvOFzLStKY1phRhRmriTbXRzHxltzHxyIvS7YCo8OBbEGjHZhco6tA59FcNLzdFlUL7FhRdQz9w+IFqRJJ+2oYG28hW9LkCwrloJgPaKeIBppUKfHWhED36Ij2KWGhsn0J/SMpC1sL6FX5Uk26Ylwt8fKuLoGZKQQ1tX9oEiPKTCRy/cWb+I8krlLZ2pzfvNfNfSsnr7P5rGbCFJqgATUcE0WG3vGIqmUY3lxw3ZFV1opr6D4iRXDtFSlXc6lGOUNwu6bLT5fZKfP+U82lBDGj4/sBaB8+ddb32WVhdnYk8bCWKdXxyMo1vVhn/i7Jjh4wZwCbM5hrX/eKGUmINLkApU3XYdkMKINhJcSUwUza6iPl0CpM+lwMXsz5quKQHbHtUzHz+4hUFeyL+2jl///s/Xm0JWld5ot/3iGGPZ0pT86VRRUFxSwgVSBwtauxpER/zt4FtF5tsJ0AbRttG5cLbHWpaNs0jY12t79Gr62C11aUawuoICLIVFhMBRZQRVVW5XzyDHuM4R3uH2/E3vtkTZlVJ8eKZ61cmbl37NgRcc4bbzzv832eL2tlj5EJKk0sDeuTNsUopsw0etcpUlmyYUKvE+cFa6bH/miTL4/3si/ZYsu2WFQTxi5mb7xFT2bBo+M0h1obJNIQCYsSjkU14WkLx9iVjLjVHWJjM6aYKFQG8bBqBZCHeU8UBtWP8JFE5iFJTI00thPmCR8pMKFMz2uJaUeUCwobS4QNVQdOg6tK8Gwi8CoQFzzIEvTEE49iooElGhqEdZhU4WJBsuXoHFa868vP4KqnbvDVra/Qdyn79BZrusfpMlSjnCgWyK3GeEnaKhi2m/nksYTzTWIAPvWU957X/T9avOdln+KmD58bgXn9Pzv70IOzJjDvete7zukgLkvMe1ys3Z4qJmdlW+GhXM5Sxura5lqZqRtfzqdj1WVmQgRVpFrtB8LKjvWI0lEuxOA80ahEebCJChOcJ5gIN3O8CqtvXoupXyQ9IRE+lKU5LUi2bPCWlCasOAmIxg4bB3LiNIwPCaI+dI5bhIWyLafvoUEVAlxoculiiR5Wx20cRCECWliP8ILRdQv0BqPgYxFn3Kirpp91uRhazBLF6r4tUm1rGOqtC0RRa0Qrxa4uUKyk2FhiWmHyjvvBp6QyixqVyMEYMRyH0r2aZNc/09Ig+2M69wiE64CIube/j1TDZDUoTbYfGnCaDqRrivi+xgNzMfGvD3/hovaBOV84XySmJixn8/pDkZqGxOwM/Ny9v/a/4Py0kaWoy8jmiUpdGiuqv63dvtMq+dJHqlIJYGPYZq3s8bTkPjIf0XfplKAsyTG70uFUWcmq9BKLCOlicoIUbkp4LIK90RbXRGv8I9ewJQMJOZIvcer4ImKo8bFDCk8kLG1VsD/apC1zJF0iYVjQE8Y2ZlFPWNFD2i6iIws6ckDfpZwuO0jhSWXJ0XyJzaLFajLkia2TZC6iE5ds9EoKExbPWK9i7z0hNWySI73H+yjMRdYhSovMQxmwq5olYz1EhKjpZUWxFAhLvsthe5bWyoSV7hgPRNKRW4X3gkkRcbrfQp6KaR+N6N6nSE+XlF01LTtO1j3FHV3+du/1POPgvXxNeoRFqXhifJJ126bwii8V+zhWLLFRtNjdG1EuNn1gHit4z8s+dcF6ztzyjt/gvS/7sR3fb/u67llvO75z+KDvve6F/503fviHznpfL+p/hg+e5baPKoXsioOzIKubjPPBW1Gbxr2bqTPOT83iU5M5Iflqm+EctieaWBs62keaeKug7EWI0jHZm6IyR9wvkaVDjUrUMMe1IoSTwd9SlxkgETb4VfJFhSo9wgRjvCwJBIMqtWwSfCk21QgbesjkC0Eyjwce0xYhlaz06Iml6MUkfU/S9wyuCg/yqgiExmkR/DaLGpNKBo+T7PpcGUq0JUx2Kdp7llD3nmRa7lxHSzsbyEvtXbF2do0s022AadmY0BqRppirdpGtphQLEj2ZrZ6pwuOUgEhUQQMKsZQgswXUuECMc8RwHH4EziGkhLxArVk6xuHFAsIqsl0+XFUL2XI453zVkqwrxnuvYKWxwRTz6stOG/gvFB6MvDzc9ueizjQ4R0gxFZfnIZzHq9ADRjg/IzHOBZXf+6p5sttecgvh9dIgSo2aWKKhZ+t0i5Nlj9LraT8UCAb9WNgpQQGIhWXgWkgcJYoCifOS42YpmPhxyKqO+kC0MW0QearoojY18aYk2+3ZzFtYBIkIZv2xS1jU4X67qCecLHrT79ytB1gEPTnhuFmcbpPIkselpyndHvbFfSJhaMuCbpyztDyirz35IKW1VnkVqznQaxWuwfx18R45yEJpXhw8LnYxxcWSfEFS9gT9JxlWDm5y3UKf/a0tdkUjEmnoqbqHTCiBG9uE+/JlDl+9zD2PX+b05xbpHY7xEoSBaBJaA7SPSj5123W82UteeeDvuTE5SYQkqtLRdqkhLpK0lwruyVaw40Xu3PnfsgaXGGpfyuZfLQOcdxVm+cW/vuP7PBfyAg9dynau+OCPX3/W2zYEZg7eOhAurP5Ps/vFLB5ZUZEVi5iaM/39ypaAmZog49nr9cN7XqDGJaOrQn2xngRzoa1KuqIirMy5RE+bCdQ3cNvVqHGJcOCVQI6D6T5d98GUryCaOJKjQ8hyUAqVGWySMtqr0ZOQ7lK2BeP9nvaxUDKFCF6b0apEjz0uDl2R003PeFUGs/9yVB2nYPQ4i7ARC/cE9UYVnmxPSnuri8gLfJYH1cXOFKzZ9Qrqljdmm5doWo6nNSwtML5mCWE90dCgJwI9KrEtTdnVeAXSeig9qop/9lriEoVttWFXGz3soAYZYnMwW+U0IPtjul/yJBttBlcn5EtQdiAynnhD0DohiUaezT07+uvVoMGO41yJy4N9/kwis2/raQCNEvNo4Py0AeK2iH3nKr/eXISydXhjw2IPIGSVoHhmTL+tPqsUKtbEQ0d0WnN4tEx/IaUtczqiYORDOVUkDKXXDFyLtsiJZMnIJlgEzks6opj2UklF8K/s1n12qxFtmRMJy6Zt89mTB+jcFxT6sivJrWZJjXlWephUlBSoaWna2CVESTjukUvIXEQkLJkKfWYe3zpFXr22Es3UoRPlIrnTHGxvkaqSO0pNqVNsHOY6COVhAsLCYVFOyZ0YTaYeTBlF+F6bciklW9FM9kj6TzI852l38bSFY7Rlwd5oi7bMWZAZbZlX/Ws0FkHmYlajAU/rHOFLvb18LH0c69d3KLYS4hOa9LQkGoSeYZ0jks+Za/m5Jyzzf133cZ7ZuoeOKOipMUtywjOSo0g8n0/3sdvs5h/O9+9cgwfFO1buuWCqCJx/4nI+cK7EpcYvfN8fTj/7ht/7F/cjM/X/z0aJ+bq3fJH3n6VNpynKnEOdejVNHaubIVaJZNPJxM0nYM2pK6XBF2V4aK//zvO5soDZtmI4Ie5byl5VCjA2eAllT1PsamEWU+TEoCbhpmxbEQiBGhXTkoRkw6DHlnTT0jptULkjmjja94yQg9F0ApTjAmE92a7Q9RgPNoX0lKB3r8ULmKxoyo6YkpfJHsdkb0hGSzcdeuJINkqigSXpWzr3qGBmdKEBpFOCbFnhOmm1ouiDF8ZVcdR6jiuLOaN+TQDra6s1rCwyun4F01FEwxKZW6KtHFFahPFEA0NyukQPSqJhGUrnSose5OhBjiwsKg8eoXJPF78cegR458IxFSVyNCE+ssnKpzfZ+/Ehy1+0RKPQ5HLhHkO2Iih2zRHSBhcF59ubcqG8L2diJ5SeR0teztzXA+2vJjINzh3S2FDGVJMYXYebVGqCCb1HKE1Y7HLby8Wmi2jThryzfmS1nyZE0Qs+d3Q/dxV7GLiU0iucDzHKI5ew6dohJhk1TR4b2Babtk3fpWy6Nko4lHBVxLHmtGtx3CwycjHvPf00Rp9fpnXSoUcePRH0s4SRS+i7lEWZs1uO2afGFF7RUxkAq7rPLjVk3XQZu4TPZofIfETuItbKLpYQHrCih1wVn2ZFB0VkKRojhWehnVEuWya7BcWSDuSltFCUCGMRpUEUJWKSB/JSp4DGEUiJaStG+xXD50z45ud8mn++6w4W1YRVPZgmo6WiROFQ1UqhwodIZBzOS/bHW3zdvju55bovcONT76L7rNOMD3hsK5RXR31P706J+dAK/+XvvoGfveM7+G8nb+IfxtfxqfwQd5tlPp0f5LTtMrHx+f2Fa3DRMZ8KViswFwL/8Tef/qj38UjJy5n4he/7wwclKq974X/n/T/05If8/E1/821n/V2NAjMHbwxeyLBCphR+koGUQSUow8rYtppk42dRvzLUUgkhQjywMVMiJEoTJp86OtiXiKwgOTHGRR3UJCguk92hfC0ahfICnyjEuEDkDj2qJjytcO0YL0PTSi9nqWVeqhAKMBhDXgRS5Txya0Tn5CJbnZC0FQ8duZKs3FOSnpxQLCUUvRhZQNkLJCcagml5vILO0TIQn2ruzHshhUyPCf1jotBXxbQEZilBDidVI8k5AlDFLNfqljdzq5Fy7hr2OoyvXUKPLXpUIidlSIvpVudcNyCToca8rouuE15k6RG5nRo4y5U2ZrGFbEWotT5+nE1JjFASMRwj44jFYxu4pS7lcouyq4m3PL1xw++vZJxJXi6n8rGdJC9n7vfB1BhoFJlzQWhkaYNPQ4iQhDXf4wqmZCao/5WaUMcr1z1hqMhMNbegwx+vgym9teYYHmnzxev28Yz03umuQ++XDCxYIRm5ZPqAbqs+MaEBZSgbc4TkrLpxpUPy8cF13PrpJ7DrS6Dz4N8RVdr9E+PjxMJSIukJw7oLD+h1IlpPTjhaLvPV7buxCAa2xSmzgCOUkPVkhvUSi+SJ+jgLMuOw3IXCkUhDWxec3uowsS0mxxXxpkatW0RWzMrurK0aFlfXUkl8K6FcbjE4qOg/yfKtT/ksL+h9idJr1n2XgUsZuJQVNQzNPquSu9JriiqNbWjTSpVR7I83iYTlmvQ0j2uv8xdZwsh0SU+Hn6XKoXufY+FuMB/bzccP7uEDj38ysmVYWRrRikqW0gl33NMF/t/z9vvW4OGx/rX/mpW/P/s+I48GF1KB+cTLBrz4rW96xI0od4q81PiF7/tDPvmff5rn/Otfu997f3X7a/mrF4Z/PxDR+YV3nf2iYkNg5iCURAhZV20F8iJEmFzqf9erZ/UEIwW+NLOHcADvpqVRon7q9y70QrEWUPiyRK33SdoRpqNxSlAsCOK+R5iQuCL87DggJJu5VhSMipGkXJboscMmwcAfbxniI5uwNQznUBvZjSU9VeBFTDS02Jake8QQbxW4ROO1pHXaYtKQUiYctI4LXAxFF8TeQKzSjToGGaSBfEmg8+Br0VloDDnZHaM3W6jBqEoiM7NENlXJ/yL4eKaeovr6pynFwSVk4VATg+pnoSysG2NTXcVZWtByLskHZBmOy1fn6xOFJ/xbD0NwgEs0YqmLLMqwWlc3u6yuD94hi5KkPyYBOnFEGTmax7WLjwtl5v/uq3/4gpKYSzVW+YFITI0zyUyj0Dw4vBCz9LG69MvVpWQ+RMw7V6kvfpZ2KcN90s83uYSp6lJDGIfOLGxA596Iv7nzep7QOsnT03sZ+4Tdqk/mNXFFSiKCL6b0mi3bIhKWU2aBA9FGpTp4Tpke66ZLIku+NNnLX37haSx+XtFaN6gseCtHpWacR6zbLitqSOklYxS35we4r9jFgXgjeGy8pi3DwtU+1SfC0nctMquRwmGRVSmZ4fb8KlJRsGVbtGXBVfE6PZWRXRXxKX8VxUInNHKumoLOLkIgdUJW/sokxnZi8tWYyT7B/utO8azO4SryOWHsYgY2ZTUaAEwVqeAT0gxsylfy3RgnkcIjhQ9NPIVBCcf+eItnHjjCna1V1o4skh6JQuyyh2joaJ0qWbjHY27TZMsJ+WLK2i7BuoHWycl5/X1r8PD4q9tfy8s4P2VkZ/ZkudAlayt//59h5YJ93cPia9/ym/zBm9UZcc7b8Wh9Mw2BmUdVLoaryUaVCy/ErDMyzMgMzF7jjHhlpbZNSsD9S9CMRZ/Ywh1axrQ1vXtNyKSXIZlMTgyukyAzE1K/vMfFGtPRFAsh9hgviYaWqF+iT/VhUHXLcoEohX87VGYoeik6c6hJ6PkS+sI44nWLbUeU7ZhoEErNevcFX45JBZPdofa5Tv5K+pbxHk3Zg3Qd6i7TqvDkSxJ5TZeFU5vgyyqlzYW/az+MtdNI6rppKFpj9y2zdU2Kzj3dey0+DglvphOij20ikFYhC0/UL1G5RUzKsF9b2U3rhwYt8YLpz00WFttNwC4hNwfh4aEmUFJA4fDCwngSft79AUI2JWRXIi5W2dhO4XypL+eKhrycJYydRSXXaZTGBs+LMdOFlNk8U6n9UszIC5VH0/vpw3pI3rJIJWifdORf7PC/V5/O6lV9DkYbIUbZx1gvGbhWKJUSHiVK2j4s7KjKsL9Pb+G8ZNO2uTPbw9+deAInP7WXlTshXbeoiSM5neEiRWtZsXaqwwf7T+Jx6WluaN8FwJpZ4GTZo6cyElmyT26xW/cBGPmYjsy5OjrNYXYxdjFrZY/VaDA9hszHtGVBJCwdmXMg2iCRJf0i5b5WB9M6g7xUMfxCyrDIJyU+TTDdmPGqIttruG5xLZTPVWqK9ZK9UZ/duo8UoXSsLrkLTTvbjEzCxEZoaVnQWVClZPgZLaoxNy3fwVO6x/lA8kTuMfuIRmpaoaC3cuQ4J7KWVqRx7RiXRojS4rf65+kXrMG5YKeJxQM1kzxf33U+sNPqyzx+8DdatK976JSyR4OmRmYetRztfVAJasVljrwIISpVpkohkwIRx7M6Zefx1oU44Tq5zIX9Tf9UjS19niNGE+KTI5LTZUjYioO6YiOJjxS2rac/pXKlTbESM9kdIayne29O964h7S+eIrrvdEjdqgnVfNKXlMiNIXgY7dGYTsiz92ruIZ9g4o/GjvYJhx6HP8mWI94K6srwoGS4XzNeVXgdCI004Y+NBDrz2FgwOKRwu4LvZJrMBve7jnWiG3GESGKKXS2kDaRpdCDBLCZMDnSZ7I4ou5KyI0MEaZUyOl2N1CrUPTuPyApkYYIyk4dGZDIPP1M5LrELCX6xGybCOiq7XuX0lXdpqszMpck1uKjYCdLxrw9/4WH3891X//AFVUUuRtla+6oTD5s+9mCemAZnD2FDKetUOamSxqYLOTD1Ak7vk0LOGgHX+6kaWYo4CnNN5aURRdUXxYV7cOcI3P2ZA/zZyWezaTuctD0yH3HKLjCwKcfNIpmLWDfhgaX0irbMsQhOmQX+Kd/PxwfX8o7P3kD//fvY9zHH4l3F1GuJ9cjC0F6ztO/RvOfzT+VjG9dwZ7GXgWtResWinhAJQ+4ijptFTpmF0JvGLDCq1I6D0TpLakwqS8YuDuqPcKSiQBH+hqCOrKghz1g6yni/I1+QuCQK51/PWS6EH0znbR0aMY/3Cg49/hT/bOmLLKkxPZnRkxmRNKzoIaksqxK7CT01mQYJDGwKQO40I5OwXnSQeBbVhEUVzi0SlhU94oZdh7nqCScZXmspOyEMx3YifBo8OCIvkeMCvT5CrQ8Rk+z8/bI1OCc8FOm4GPvZKXznx599sQ/hAdG+rstfX/39O77fRoGZg7cWkFMlxdeKST251BJ/acJqj7UI1Pa4ZSlC2ZjW4XN2rnRMVL1jIj0lPN5YxOlN4tEENexhFpOKYEhKLbGJwEVt9MhQLGniTUPryCjEBNdqiw+kKaSeiRlhgnAeWYYQgu6Rgo3rE9iEsiVRXY3OBDIPscxOC2wspj1qoqHBa4EeWcb7IoZXSYpFQbzlSU95orEnHlq8EJi2RBhP3A8KTrnSItlKg4/oDCLgvd9ObIzB9zrYWJJsOlwcYjNDvwRQuafshNfyBUl3aMPEbRw+1TgpkFk5I5zGorYm+KT69bYeQegLICWUyy2ivICNYlbidmZUqZ4pcA0uDdTk41zKyR4p8bnQ5WQXEnWJWPuqEw9LUh6qnKzBw8ABhB4mQLVo4mb3Qzc3vyBn9+y5YBisw9cEJ45wndZ098JV/U8qQhQPPEv/JPiseQK//JRlnrX7KB2d01WhjGtoExZ0Rt+k4cFcBKP64cEy9x1fRh1LaJ0S7D3maK0VRJv5tIEyjmphKHgue4clLk65Pd3P1Z0NOt2QWLaqh/RUNiUrkTCkouSgDmVqVL1ndqsBaWo5bgLJ6lTpaX2XTs9v7BP2yS0WehkfuO6J5F9ZxSwmyMIgxlmlSNWqPqCD4jHao5k8IeebD3yOfdEmqSjpyYxTtsfAtrDI6WuZj1DeUQo9JVIdnVN6OVVitmyLtsrZrQcsqRFHyhWkcFyTrnH1Vev8iXg2J48fQE8EqhfhtSTyHjKq8mQfev74Zj65lPBI1JHiyyv86XNvO09H9OgRP2H9nLY/n+rLmfi26E92fJ8NgZlH5e/w1jJrZjIjLMBcl/h68lFzN9H5Xibg8yKQIalAqmmTyzrucTpBeQmDEjkckZxMSOIoZN3H0ey4SkN8xMEkm6aL+fkbYl1+UKsa9XFZKrWnID28SXQwZAPHQ1c15pKoRIVeM4REMS8EtiVJNizkHq8l6boMSksM0cijcoeeWFwUYs1k6ZDGE40dZVcy2R2T3C22k5cqzW2arjN/DaVETyzCeUp0aJBZOmQkKTuQbDqSjQIvBbalMJ2IaK0Mk3hVNuZijZrk4doBIjfB7CoEwjjMYoqPKuLYbSG2huDM9mOsSWaDSxYPREpqUnO5l4c9HBpV5DLF/L1ahwUtEUXb7uHTUqhphL8EXd3LI43rtDBL6fT9usGxre5psvQkW7D0BUF+fJUPLe+i2G2JFnMQniQxCOEpCk2RRXgjiY9EtE4J9px2pJsmWAwnJpSm5VU8vZTIwoRSOK2QmSXZcshSkq+1WDvUZbPVZlGNq4aYQUVxVX+YmpyctD0AMh+xWw3oCMNB3ee4DQ9Rh80KzkukcKSipG9T+jZFCc/B3hZfEavYVAUvpJKIOJqG5aAUJDFegNegYkdbFgxsi1SH+bYns2naWIiXDvHRA5dSeMWG6WC9ZGIjlPAsRROOZz3W8i7GSVTqsV6Quyg0Aq1UmwOdLY5HBxBz04Zrx4hIhUAZa/FK4ZsFsUsO8wpKrV7Mk4Diy8FUMiMt56641N9xqZeSXQh858efvaMEsCEwcxBaI4SeTSq1UR9mxv25yaUug/Lez/wvtfqhJEJGiG4Hu2cJ040QJqxmeR1M96Jw6H6G2BpOYyB9lkFWSc3zpQRSzBQhGwz903Kxug/NHCHY1mMlisO/+0NWPpMyvK6LVQIvBePdkngkSTYNKvdMVqtkm9MOlyicCseqMktiXDAsOh8IhnF4IVATg20Hk72XYFNBtgQ+DtHPGLO92WftAaoVGK1xnZRiQRMNDPGgxOmQMKZHZkqu8B7dzxEuwUUhpU2Oi7DKJWXwvSRR8M5YH0rvqnpxF0chtax0CONwqUZ32/jN/ixMQCl8Uc7K29SZLeganE+8sMwf9L0PR8lDfvZyJi4Xw8zfEKELBCnDgooLnsNZupicegenJWX1IpRSQX2uY5Odx0ca140pexGDqzWmLVATj87CopPKQ6S904QQljVP57hH3C6xcTv4KhUgIPYhUUwVEG+Voemxq/6YcG8OCricli8H0hAeF2RmiIaKaKgxm5Jj4wWOtJa5vnWcw8Uuxi5h3XRYjQbs1gNKr7nbLHBPsUrmIhb1mCNymV16iMRx3CzhvODObA9rRZetIuXJvRNI4fnM1kF2J0NGJg7H731YmBICIh365aQxvhVjeymmpUJD58p8n/mITdupfDChz0ssbEhkE46i6v8ycgl3jnfzxc3d9Ccpj1veYCmeYNxsDl4z3Sp8QDC0aSjHKzscGy9Q9hxlW6Cz0Hjat6Pg14xsiP+3fnsqZ4MLgk/+558G4N9+/bW8/+k/+pDbPvCD9aVVIna54z0v/9KO7q8hMDAlLKXJIFH4PDSAFELghZ+VJnkQsva/xNubk5lyRmSEB6FgoUO5t0vZhXhrFHq4yFAnW5cVFMsKt3spqBcbE8TJjaoUTEFZ+WgqBaeGiBW+yOfKnjwhGqzqVWOoDKA6NI3EI7zElyXi+HEStYvRgVbwwYwFYt3AVoGyMelIhjhkY8mWJE55WmvBMO8F074GZSdCShce+LMCMQK0ANEiuVdiY0G2qIiGsjrEMkzeppgZWV0JSiMQGFVSugy8o9QQb2SYKChEcmTxSpJ1NXZXTDQoQ4S0NyibhxjSNAGTIbzDSY9ZiLGxJOqXeC3xyqKHEygdNlb4SOE6CrFZhigzb8IMr2YeImPLbb8fj3Wcr+vwvNOnADD9S8vk+t1X/zC/d/ubL/ZhbEN/cOEfgo5/YTf7nnLqYbdrxklAfR2MDYRcBBk8kAHvEb5SNoRE4EMJ8rTni8D7qgJA+OBTjCQ+dlhtGC4oJqnFCdASijSQkWToUIWHQiBURThyj8wcyof0MKfDd8jSI21YfMJ7nJupOcI6hPch5r7y7ghT+XYqj4nXEvoFnS8a3ERzl1zhxOM0y+0DaOk4NeySF4qrVrZ42uIxVqIR62WHwkVslC0OD64NYQLSsTVp4bygk+Rsjlpkp9uIXPKp1V0kqaHINL1ewmDQorOVQX+CMVmI3/ch/stLhdOWUpU4b/BjizkM/2/3CUTSshhnDE1YAImlYWIiWrpkQWcUXjM2EafGXU6uLyCOpnjt+dzKCkKFsbaynLCvExErw6DYjxSe3GpODbuMBwm+lCQnCmTfIbYMDMuq9dscaXFgfDOfzONCXId/87x9fPBrHlm08E6j7N//3l3ctUz8+IeOW/7xP/pO/vbZW3z2+vcBcOxtEftfWVLcFfrMxI/fOKv9PBC+/rcfz+hVLwPgI/kv8fzkZ/lI/kvc/D+uY/Sql/GR/Jd49//5+7zkj7+Xd/+fvz/93E2/9h0AfOCn3wnAf/zGn+MHvi+Eurw8ehc3/4/r+Mn3/DzP/qqP85/2HOPfv/h3+fd/9S/59y/+3bM+trP5/RC+GU3cddddXHfddRf7MBpcorj33nu56qqrLvZhXHQ046TBQ6EZJwHNOGnwUGjGSUAzTho8FM5mnDQKDLCyEuocDx8+zOLi4kU+mkePfr/PoUOHuPfee1lYWLjYh7MjuBjn5L1nMBhw4MCBC/J9lzqacXLpoxknFx9X2jiBK2+sNOPk4qMZJ5c+LvVx0hAYQFYG/cXFxSvil67GwsLCFXU+cOHP6Uq5se4EmnFy+aAZJxcPV+o4gStvrDTj5OKhGSeXDy7VcdL0gWnQoEGDBg0aNGjQoMFlg4bANGjQoEGDBg0aNGjQ4LJBQ2CAJEn4uZ/7OZLkoaNaLxdcaecDV+Y5XW640n4GV9r5wJV5TpcbrsSfwZV2Tlfa+VyOuBJ/BlfaOV3q59OkkDVo0KBBgwYNGjRo0OCyQaPANGjQoEGDBg0aNGjQ4LJBQ2AaNGjQoEGDBg0aNGhw2aAhMA0aNGjQoEGDBg0aNLhs8JgnMG9961u55pprSNOU5z3veXz84x+/2If0oPjgBz/It3zLt3DgwAGEEPzZn/3Ztve997zhDW9g//79tFotbr75Zr70pS9t22Z9fZ3v+Z7vYWFhgaWlJX7gB36A4XB4Ac8i4Fd+5Ve48cYb6fV67Nmzh2//9m/njjvu2LZNlmW8+tWvZteuXXS7Xb7ru76LEydObNvm8OHDfPM3fzPtdps9e/bwb//tv8UYcyFP5TGDy2WsXEnjBJqxcrmhGSfNOGnw8GjGSTNOHjX8YxjveMc7fBzH/m1ve5u//fbb/Q/+4A/6paUlf+LEiYt9aA+Iv/zLv/Q/+7M/6//0T//UA/6d73zntvff+MY3+sXFRf9nf/Zn/tOf/rT/1m/9Vn/ttdf6yWQy3eYbv/Eb/TOf+Uz/0Y9+1P/93/+9f8ITnuBf/vKXX+Az8f6WW27xv/M7v+M/97nP+U996lP+m77pm/zVV1/th8PhdJsf+ZEf8YcOHfLve9/7/K233uq/5mu+xr/gBS+Yvm+M8U9/+tP9zTff7G+77Tb/l3/5l351ddX/zM/8zAU/nysdl9NYuZLGiffNWLmc0IyTZpw0eHg046QZJzuBxzSBee5zn+tf/epXT/9vrfUHDhzwv/Irv3IRj+rscOZAcs75ffv2+f/wH/7D9LXNzU2fJIl/+9vf7r33/vOf/7wH/Cc+8YnpNu9+97u9EMIfOXLkgh37A+HkyZMe8H/3d3/nvQ/HHkWR/+M//uPpNl/4whc84D/ykY9478ONRUrpjx8/Pt3mt37rt/zCwoLP8/zCnsAVjst1rFxp48T7ZqxcymjGSTNOGjw8mnHSjJOdwGO2hKwoCj75yU9y8803T1+TUnLzzTfzkY985CIe2SPDV77yFY4fP77tfBYXF3ne8543PZ+PfOQjLC0tccMNN0y3ufnmm5FS8rGPfeyCH/M8tra2AFhZWQHgk5/8JGVZbjufJz/5yVx99dXbzucZz3gGe/funW5zyy230O/3uf322y/g0V/ZuJLGyuU+TqAZK5cqmnHSjJMGD49mnDTjZKfwmCUwa2trWGu3/QAA9u7dy/Hjxy/SUT1y1Mf8UOdz/Phx9uzZs+19rTUrKysX9Zydc/zET/wEL3zhC3n6058OhGON45ilpaVt2555Pg90vvV7DXYGV9JYuZzHCTRj5VJGM06acdLg4dGMk2ac7BT0BfumBg0eBK9+9av53Oc+x4c+9KGLfSgNGlzSaMZKgwYPj2acNGjw8Ljcx8ljVoFZXV1FKXW/ZIUTJ06wb9++i3RUjxz1MT/U+ezbt4+TJ09ue98Yw/r6+kU759e85jX8xV/8BX/7t3/LVVddNX193759FEXB5ubmtu3PPJ8HOt/6vQY7gytprFyu4wSasXKpoxknzThp8PBoxkkzTnYKj1kCE8cxz3nOc3jf+943fc05x/ve9z6e//znX8Qje2S49tpr2bdv37bz6ff7fOxjH5uez/Of/3w2Nzf55Cc/Od3m/e9/P845nve8513Q4/Xe85rXvIZ3vvOdvP/97+faa6/d9v5znvMcoijadj533HEHhw8f3nY+n/3sZ7fdHP76r/+ahYUFnvrUp16YE3kM4EoaK5fbOIFmrFwuaMZJM04aPDyacdKMkx3DBYsLuATxjne8wydJ4n/3d3/Xf/7zn/c/9EM/5JeWlrYlK1xKGAwG/rbbbvO33XabB/yb3vQmf9ttt/l77rnHex/i/JaWlvyf//mf+8985jP+277t2x4wzu/Zz362/9jHPuY/9KEP+Sc+8YkXJc7vR3/0R/3i4qL/wAc+4I8dOzb9Mx6Pp9v8yI/8iL/66qv9+9//fn/rrbf65z//+f75z3/+9P06yu/FL36x/9SnPuXf8573+N27dzeRl+cBl9NYuZLGiffNWLmc0IyTZpw0eHg046QZJzuBxzSB8d773/iN3/BXX321j+PYP/e5z/Uf/ehHL/YhPSj+9m//1gP3+/P93//93vsQ6ff617/e79271ydJ4r/+67/e33HHHdv2cfr0af/yl7/cd7tdv7Cw4F/xilf4wWBwwc/lgc4D8L/zO78z3WYymfhXvepVfnl52bfbbf8d3/Ed/tixY9v2c/fdd/uXvOQlvtVq+dXVVf+TP/mTvizLC3w2jw1cLmPlShon3jdj5XJDM06acdLg4dGMk2acPFqI6oQaNGjQoEGDBg0aNGjQ4JLHY9YD06BBgwYNGjRo0KBBg8sPVwyBeetb38o111xDmqY873nP4+Mf//jFPqQGDS45NOOkQYOHRzNOGjQ4OzRjpcHFwhVBYP7oj/6I1772tfzcz/0c//iP/8gzn/lMbrnllvtF1zVo8FhGM04aNHh4NOOkQYOzQzNWGlxMXBEemOc973nceOON/Jf/8l+AEMl36NAhfuzHfozXve51F/noGjS4NNCMkwYNHh7NOGnQ4OzQjJUGFxP6Yh/Ao0VRFHzyk5/kZ37mZ6avSSm5+eab+chHPnJW+3DOcfToUXq9HkKI83WoDS4zeO8ZDAYcOHAAKS9vsbIZJw3OF5pxsh3NOGnwQLiSxgk8+rHSjJMGD4RzGSeXPYFZW1vDWsvevXu3vb53717+6Z/+6QE/k+c5eZ5P/3/kyJGmSVWDB8W99967rVPt5YhmnDQ432jGSUAzTho8FK6EcQLnPlaacdLgXHA24+SyJzCPBL/yK7/Cz//8z9/v9Zv2vQKdtMmuWcXGElU4bCIZ7dMIB9JAum7QmcULAQL0qMRFCttS6JEBwEsk8BUAAQAASURBVAsouxFehW06X96A9U2wBpwHKUBIkBK8R0QRpDGu08a3NE5JvJaYtkIaj5qE/bpY4aVAeI+XAq8EelAivMdFCmEdwnlE4VD9EeQF3tjZd5ZlOFHvwvd7F/6vNHgPUiGUBCGglVDsW8R0NLL0ZLsiZOlpncwAkJlFWIuwHtfSuFjjIomXAtNSCO/RE4uNJcKDjSSdOzcQozHeWISUeOfCsdXHAbPrEelwzNbhF7q4doSL1PS8ARDhOBDgI4kow368DO8L59H9HDGe4Cc5WAtKhetQr/hUf4sowndaEEfgPeVqm1HH8sn3/jK9Xm+nfvUuKzzYOJnH3/7Edz7q7/nnb/7Tc9r++1/y54/6O2v83+/+tke9jzf+6PfuwJHA637r93dkPwBfeP/nH3abp7xoZx8emnGyHf/Hs16LX+5x9Otilp+xxlULm7RVwfWdEyzpMaVXjGzC0KY4L7BItsoU5yWRtORWY5D0ixaZ0RztLzI+2Wb3xxSLXxqihjlikoF14f4tBMQRrpOy+dRFNq8XlD2PWMm5bv8pdqVjMquZmIhEGZyXDMuYSRlRWEWiDVvjFpNBghhq0hOK9LSnteaI+4ZoM0cWJnxXWf0NCGtnx6AkFCbc42MNSYxPE4aPX+DIN8CTnniE/a0++9MtOirndNllq0xZy7tsZG2Mkyy3JnR1TipLHAItHJtli1EZk1tNLC13HtvN8j8kLN0xITo5CMdQVPNbvWpbzx95eF0oCUriex3Mcpv+NS22roPiYEl7MUNJx3iUYAsFDigkwgq88iBBjSXtI5LlO0rSEyNEYRD1d1oLQuDjeHodypU2ZS/CtCSmLWEw5ra/+KVmnDwEXvbxd+zY973juS87q+2++2c/xr/666v4lm+55Zy/4+sOfh/ve+VPn/PnHg4/9sM7M6d8/Bv+FR/77pt2ZF+/Ef2v6b/7b3w9z/rCa/iFb3za9LXvffkaT3z282m/OebrXrD7UX/f2YyTy57ArK6uopTixIkT214/ceIE+/bte8DP/MzP/Ayvfe1rp//v9/scOnQIrVNUZwEVp0gl8B2BTAQqVaTrDuEgEoooz3GxwiUKt6tFvFXgrMK3Y/SgwLYibCcQmGhoYc8KepCDMOFGB+FBGkAAFpg4VD5CtFv4dopra4hShPLossS0NcqBiwReC1TuEB5kolGTEjGyyGH1kF6UgbggwbjwJToCPN46hFBhspOyIlP1w7xExDFohd29iF9OSccmEIZSEw0NotXGS4GMHDIrwYHUEhspRKLwAmxPo8eOSBqUl4FgtDVy2aMyh3dlRVxEdf4GdEWiBOAVwkoQGoSHzAVilCTYtka4QOCE84ikIj9CQOxRuZ3xskGG2MrAg/eqIm0CCGQNCMcBYAUMCoQyoBTReEDUktWuL395eyfHSY1P/LuX7sixfeLfvZQbf/WPznr7mnT84Lf+zSP6vt9+182P6HMPhDf/xCt3dF8/8ea37ci+et0L/5DUjJOAepzIVpt8bw/3+JKnXLXFVekWUnj2xiVt6YhFSd8JcueJhEEKT+kVzksSGR6MN0yHgU0pveIrI8cd3Yjy3i5+Q6HzAWLiQDG9j/tIo7xm6bggkgnjvZKJaXFsl2R15RgH4zET6ymdonCSZZlTOMPprMPGuEueLRAPNFFf0N7ydE5bkvUcmYNwGqFURVyi6VwmihxfOJAS4SVELUjDAp1vp0wOLbD2dZp/9jW3c117jVSW7I222LRthLUs+wkHfUHpt1A4FvWErsqIhCV3EQADmzK0CUObsFm2OGnB7G4hjkj0ViBQQlRkQszNadpD/boLx+iJULmkVcRMvMJojUhhqTtmdXXC1iSlMIo8U7jNGJEL9FDQOilYuqckHluUjBFKIYTAawURoBVeqUBqnENNBDECPwThLTavrtcVME7g3MfKw80n3/f5d52/g30I/K9feh7/C+DjEP+HZ57TZ88HefmpH9+5OeVrP/h7fGyH9vUPb3gKX/+L9wDQ+pn/yDHgB39vPNtAtElveC9f94KdOf6zGSeXPYGJ45jnPOc5vO997+Pbv/3bgVBb+b73vY/XvOY1D/iZJElIkuT+b3iPT6LpCr/KHSBJNxw2FkQThywcPlJI40AIbKyZ7E2DUpI5TDdGlg5ZVA/TEmxLE0UR3lQKTWmofzTeurAyVKskkwxhLGpzQGszxbcTfKzxSiCtQ5bgbVA3ZFYihzlinOGzHA9zqoqC6vvwDvI8EBRF+C6lwgRkCQ/2gEgjfFlCOyXflSKqZ3svBPFWiSwtTksE4CKJKCVCgulG2EShhyVeS1TmQ29XB3pS4BKNyhw21SgloaRaHaMiLdWKWU0mdHV16uO3FmEd2jpkkeDSCJsqZG6D8mJ8mJzCDx+ZW+SgUqBq1QnwWY6I9Pbvqq+XBWKFty58r1Iwnsndlzt2dJycB5wriYHtRORsyMxOEpdLHVc99xD3ffzeh3y/wf2xo+NECfIlQWdxwoLOsUgkli3bJvMRzksGNgWgrXLasiASlrFXlF6Ru4iBTZnY8BDf0zkrnTGHr16kd68iPq1RWx5flggpIY4QpYHSEAnBwqSkfTJmsjvmWK/HbUZRZhqpPb3uhHEWo3V4qB6vtYlPanbdA737DHpkkLlBFhaR1ypDda/0Pijl9T0UqvuomqoyAAiBizXD/Rpx7Yj9aR8lHFI4TpkeW6ZN6RXGSaTwOC+CCuJipHA4L7FeooRDifDdUniU8AjhsRFhHjkTplokrBfnqrnBOwfGInQ4znQ9oXMsJd+lsEuSSamJlMN6wWSUwCCidZ+itRZUqPRUHhYLrUeYunrAI+rvsw7hi6k6FaohTHjdWCjH9z/WyxjnOlYu5HwCgRD93lO/9Zw+81df+de8+Nr//JDbfFf2h7z99U97yG0eKXaSvMzv89ffsjMLYw+Gf1V8U/jHb57Xr7kfLnsCA/Da176W7//+7+eGG27guc99Lm9+85sZjUa84hWvOLcdiVCeJMtAPmRuYCHBa4GeOGQZblzFQoTpSGTpSU/llAsxwji8EthE4qXGK5BWhHIm50Gr6UOzUApflDMVZA4+L6YP0GIwQoxDyVb7lN52nGR5+Kxz4SHd+0BIaiWjKMFavPeByUYaXFBgoJL96zKyqqTMlyUiTbGLbbyCaCtMXLYjg/IjwzHEWwVqYkIpm5bYWGJTgcoksnSozOJiGUiOU3gVFCPT0URJHI7d1cTFbQ/z1np6HvWxIgUUBcJ7VF4g2ymyFeGVDJNEbhHOIYxDDMdBgSqK8Nn6POEM8lKVk82TuYJQAmFdKGO7wrBj4+QSxGOJnDQ4v9ipceKFIFsRHFgY0FLF9AG9qzI6Mier1AUpHJGwKBylV6SiJPMRpVdBhRCaSFhaqmQ5GXPPcolJImwrQrZTxJhw7zY2zDNSzhbhRiUtD8u3J2QnuvROemwqKBZaxLVg4WDfUUf7ZIEeFGHesx7hQlmYyIpZ2RiEMtt6ddT7oLxEUZiPhAj3UKXwSuLaEcOrBfuX+xgnsdV8VzpNT2WUXmGlpPRBEVfVtXBeBiITluVwiCnJaakSLR1Zz2OTqhS7DERhSmjqhatKMZqGrdakRgjU2NA+ZXB3aMabXfq9DgiINwSLfYgHntZaSdQvUaMSUdpZuVyNWu2pX7cW76r5w9qgkFkHZYm3xTn9/lwOuNLmlJt+85W8/Bdvf0iC8nbOD3k5Xziy+yeBR09g3v76p/F24OW/eDuHb5jw4Zfc8Kj3+WhxRRCYl770pZw6dYo3vOENHD9+nGc961m85z3vuZ+57GFR+T+kdYjSYlsRwnuigUFlhmIxxsUK4TztY/mUkMjCTR/oTSfCRZJoo8RLgW0pXCRmK1NKgTOIOJo9oDuP9+G1QCb0NvLhs3w6KUCQ1rz3CO9B66DmeF/5ciR4G/YjBcKFVAdRTT5CiNkDu3TbSIzQMSiJ6UbI3KGHBT5SFCrGtCVxP6w01R4TFytcrNBji21JbCJxsUSNDV6HfyNC1ZaLJDYNhEtoHYiXc0H5qK6L0DqoVNbhqSYkJcFVDMdaMAaR5SitZyuPfkZCvDGzevC6PjmW+EkggiJN8GWOSKuVoPr7pZhde0UowZv35lwB2LFx0gDY2fKx+X3uVBlZo7I8MuzkOCl7nt3pkEhYuiqnrXI6Mqctc5bUmMxFpLJE4hi4FiOXkIoCHDghSXRJKksyF5HIEik83gmkDdW1tbog5sumjA0P23m456utCXs2IrAen2pEaTG9JCz+mErZKMJnpvOU90HJqP8/p2TgZuoDQszuv0rOtgWII7LdMdmhgm6cT0kKBMVJVeRkYFPGLkbhUAJKr8hcxMRGaOlQOBJpiIQNf3vLcnvCxt4S05p7hKn9m6acHpef+mKqY6pVk9Ig+xNaeUlyKmKpE1F2NAiIhgY9DGVgorTgCGSuNAi73WdZq1E1eaFeMBTVwqWsN/Mz1f8KwpU4p5wvdeXh8MJ33wrv3nkJ4+Cp/7ij+7tY1+eBcEUQGIDXvOY1DyrxnzUqRcFLgSgdUlrIPbIIpv1oUOKVxGuFzA22E1EsRBWBAZxHZRYvCKtYEMquEoVPExhn4aE40iAEQlU3tNLMysiUmpVXVQqNSOKwndZhhc1YhJJhn5Xhn1DtFuTt4TiUT+UFyODdmZKWev9Sh1UrRSAxNUFSCpMqpPW4VIdrYQM5Mm1Jslag8rASVa6k2FgSDUriTYOLJcWCIpICPTEUvVBaJix4DSYV+HaCGE1mBtCoKlszJhCwehVtvhShUrG2mf7ricSFkgBvzOz61SRGqYqc+aC+CBlWxdJk+2RibfiZ1BDbVbErCTsyThqcF/Iyv++dIjENHhl2YpzIwgafovDkTrMcjQA4ZXq0ZcKSCkZ+6R0KifWiUmE0Y5dgEVivkCKUVR3LFrlrYxfRiQg9CfNMTRx8WS1owdS8DkwfsGW/DAs6lUKirQclQonTGURF2DmiUqsqAGkStnVzJbu1p7P+rmr/XgpsJ6Z/SLO85zT7W31aKpjyezL4W4ApqUllSSQsEo9DkIgwfwYfjJ4qMwBDm7AYT0h6OUUnwqUaaWw4NmNnx60VwoRFLSFEWDD0oYwMTVjUsxY1KVBbkijRwcPiXLgucD/S4dUsfCdc66rywdqw6CVFWKCrlR4pwZkwJ5krT4GBZk7ZKTz/PJCXKx1XDIHZEViHGuQ4LatUq8p0V1qIFLJKAzOdNqYb45XAS5DGh5t+9aAd9YtQzlRaXDvGRhKdaET94O3dTDGwlSIBQU1RMryWJBBpfCuZlqC5WOOTIM3jPcVijM6qCcSDi0MJl9/XRWUWfbIP/SFMthOn6THUqkMdKOAcvnqQ91KE0jjrEQ5aayWycMhxCUpgeynSOKRx1TYWNS4RNlyXshP2I01VAlCVDrh2jKxv/rViMp9ENjX3z5Gq2gsj9Wy7KTGJtqsl9Xxae4pq9UbI2f9FZeS3dvozC/ufrRAiBUJeeWVkO4WdMvA3aHClQhqHHgrGJkK3XFUWpdmyLVajwbRsDGDgUgqvpyZ+W7kka5/MPeMVPnt8P+ONFklRJSd6ZgtBtUJiRVjkUrJSYkylSoQHe99tB1+llrhYIyOFyAxoiW1HeClQman8K1XqoxYIE9QaNamUidxMzepT0gDVIlm4x7qWpliCa3oDDqSbtGVBIkvaMqcjCwYuZcsGH0xbFnRVNj13hWdFB+Vq4EIyW7iokDtNqgydVk7Z7eESjRxX3pOaULnKkyPETKV3dnaM1kIUTb2oSIEoDT6JZolqVXlcvb86PCbsy81UqaIMi2vhB1btb0b8fBIhXAqTmR+zwflH+SfXXexDOGucL/WlxoXwwVwMNARmHpW5r066klk5ldi9mvlVhAl+C5U5on61quIcTmlkacPNtF6Ncq4qpQorM94WQUkRMhAWUyVwUU1CSQyRxvba5HtauDiY1G0qEd5jI0Hct+gsrO45JdCjULIli3BcRBLTUriDS8RxBGsbMxIA1erQvPSuwk1eBtIgy6DaeEkwxBcOYR1qGHw3NokoliKE8SENTcztl0pe96DHFq8F+aLCpDKQmVolESKcr5T4PA/EQ80pH/UE4h4gMUzISnWxszK82s/ibJVIVnlp6shlNafqzJNIKUJogJ+RKBFF4Wei5ghNg2248Vf/6LIgMf/4mbMLYvjqr7pw5tIGjxF4jzQwKme/W0ObYJykdJpSKhxialYHUDjyyuBvvWRoE+4ar/LpowfJ1lNwAhd7nA4LL6IIyoovyxCDX/lBRF3alRcQR/iFDi7VmF4S/IlKUCwEpV2WYX/ZssQmIRkyXwSXeGQhkCUIC3oMrdOOZMsSbRWoUR6ITJYH4rTt/upD6ZWBrTxlaBJW0yGJLImFnZaJZS6aqiu5i6bm/bKiFqksacswx45dDF6RSEMvylhtjzkWERYWa//PvDenKKukTTnzh1Y+0NrIPy07g6pEzG5LMfN1zH49zwg5U1bqOYq6NLv6nK4WGedK6XwSQwycPh+/aA0uNF7+i7cD0P3EMT7/o0tcfWsLgH/584e4xSyc8/4+/JIbeP55MPBf6WgIzDzyEjoeYT2mG+Ejid7Mgi8mC3HCPlJVOhm4SKFMWUX6EiR87/FSIqzFVzdPlbuZkbAyiaPlNDse58MDea+DW2hhevG0xlaPw6qRzmyIL45DeIAoHaqS1E0npJRF/RIEiNyiS4fpRoyvWaAVKcSxtfCAP1UzCMTABV8JcyZMPQn7dbGclkHYVM9W5XQgKMKHkjVZurBCZRyaILN7AcKF6+gigdPQWrOorck0fADvp8lstfQ+TQHTc2oLzFbPRFCNfM3H6p421T6oy+Wcn5VR1PXKtfICM0WmRk2S5l7zuhkelyLOlpQ8kn02RObc8a6N5/Oty2fXpf4xBSHQIxiWMYtqwqoehJIxEcqkchfRlvnUsJ/5iGGVSlZjaBP6RUo+iRC5DP48GRbUxNwDdHionnvwjiN8K6jhppcwvComW5aUdbq2D/4cl4CLCeXHCxlxaogiw8HekNIqcqvoj1PGwzAuNjNF++6IlTskreOghJj6K6fqPkz9NXoMW+MWuYumqlLhFaXXbNk2SjhSYafEBUKogaz+BoiFQVZhL2ObEAnLUjShpUuikd/u3ZmPXp1TT4BA7oSfEZBKpQKq0mwTDPhSzhbZ6oXIarv6/17JQGrqOaYOz6mVl7k+Y17LkCRKc2+5kIi+6054/SP77AvffSsffskNvPwXb6f7iWP332Dutaf+1iawCcD/+qZj/CAhEfNcg2WO7P7JHfer1LgS1RdoCMx2SIHIS2RusW09M+pRTRjWg/S4OCRv6YnFxZWxvnRTIuMThchCiot3bvrZqUk9rkqTbLXarxS+nWJ2dSkXQgiArJoy2lji4vpmCMlGGRo2ChHKxXS4marcIQtT1eiG8q9iQSO8Z/S4Lt3hBLaGiCQOJKEunZpvXlnJ4fh0Wj7gWho1KlGTkmK1HRLFxiY0sFQCWqGBppzUq24eFEHFMiElppqHiAZ1ycHchFd5VbZlfsdR2EaqWU2xU2GVcS7IAMD7OgGGQEqcn5Wk1SSonoSEDMSxVmnmfTYQtnUykLtIYxeaErJLDeeDvJy5/4tNYi4n/8v77Ncy6puH3/AxinTDcezEEuV+RU9NsMjpw3xbFqSioFPFJ5dGT1O3ICRytVRJN8oR0lcx+UEN8SJUAkz9K1UIClrh4wi73GZ4dZvxHkm2C/IVh+8WyMTinQAniFoly52MRBs6UUEvzjjQ2qKrcroqZ2jDOOibFptli0haRibmn/bu4bRcZneZEEtBNMoQtWezKm/2UiCNIxp5BsPQu6X0irGLyQn31agiLgAKjxIWi6D0CoXH4afKVEEovRvaZNoA9PYj+9l30iGKKoEtr6ohar/nnFLia6O9FLOysW0+yOCbqQNxakO+L2blzqENwVxvsDPnD133dgvvCesC0TEO25HYTvyof5+uZJR/cl0gHRcR0zj+39rkqd/6N9uIyiPZ1+S3/5Tf33t2pWGHb5hw8N2P+Ovuh627/8Xc/y6fOeVc0BCYebgQFan7GT5q40UwIsrcgFD4CMxCgk3lVHaH8KAvS4dLFMI4ZGFnD82EycZrGZJM6tIpIfAupIj5bguz3MZHVRlB4VDjUIcckr1mpUw2ksRjM83mt90EVX2PSzS2pXGRxMuwWiQsOC2wqz3U1nDOyOhnkcXMZHZhHWpcYlONF2BShU1CklrZUcRbBtvWqMJVKkxQYERpQYZjcFEoZzMtRdmR2FjQWrfoQR4iOWH2fVIGkndmSst82ViVyLZtYqnfnyOEQgiIW1WsZllFZ6rpZ/BzhtM64QyqiWgukU3FuF4L254jVQ0uOs43eTkX/MSb33ZejPyXE3lp8DAwnvbJEnUs4ehTFnlK6wgLckKfUCoWjOuGVBZYJ1hUI6Rw0x4wSWVs7+mcxYUxm07gC4lcl6jCg53dL0PZq8Lu6pHtbbP+5IjRIQerE1RkiaWn08pZamXTz7R0yd50wMRGJMrQ0xmPb51iRQ0ByHxM6RVXJ6cZu6B8bNkWe5Ih/3vj6eR3R0RDGbyVtdemPh4XlJF00yFOx2xeHVSYSM1Iy6oaUfrwCFIrUwrHuu2QuYgxMRYxjZXOXcTYxUxsxD8cuZbOR9u0jwwqM35V6l2Xr0EgdFVJl3B+NicoNSMbXmwvXUaFfU1JiK2aX1ab18mgzm0nNfUiYF1mXrdMcB4XKcb7Uwoh2LGugg12FD/4rX/D8Mb9/PSxb+fX7vutHdtv6we/k7NtjrLTZWSL1/zhju3rUkVDYObg8xxkjNwaoZXCtSNcrLCpDqSE8EAvSx9iFoVADXNsJ0j19V3Oawle4WNNuRAjjcdHKtz06rKp6sbnkwi72KJYjtFjG8rDKvIjc4OLYxAgC0+8UaDGIdrYxxoXKereNV4AQmHjoCCozBFvGJCCYjGiWIxpxxE+ywI58FXpWJXOMo1Xdg4xyoiEINsXFBfhAlmLBhZVOLwIr4VeAZVnKJLgYXQgwUtQhcdL0JmjdcqSHB+GdDQpptn8wYMiQ48XIUDLYMiv1ZdKPfFSBGWoLukq8tD5uDLqizTBd9uUCyk+rlLknEeNSuQgm6ae+aKs9i22J53V6gyEv6sUs7LTKDAPhcvFB3O+sNMkpiEvVxgU6EFB756YW08c4tndw/RURlwlbCkcsbBkbvvKvPNypkwIRy/KeMLKGncKz/rJBZINQbxlkIWZJUtGGh9HDK/pcuK5koWnrnFNK2M5GRNLixQe4yUtVbIYTVjUEwCsl0xsxK5oxKIek4qSjiwovaL0btp/JZFlIBl49iVbHDqwTiH2hmqAOplMuLmQGI+YFLROFXTvafGF1X3sTodc1z5FIkt6MsMhpw0qMx9hPZRU6otwjG0aUslkCDLYMG3+ce0QR08vsvS3LVY/NUCdHoSQmvmUMVeRisoT4yu/i/AeYUxIJYP79WDD+el1JK4aWtcemNLOQhFcUH18RVJ83cxSCPBmSpoAvFaUSynrT1UUUsAfn49ftCsDb3/90/i+73rXju3v4Uz8ZzY/7n7iGL/GzpGXSwFXaulYjYbAzKP2geQFamuE8G3cUoqXoecJgsr0GMrF1CQ0t1L9PERS1iti1gcloqWRxoGrFBgpg3JQezuEwHdb5MtBqq8Ng6FMwCFKR7w2BtoAqFE+vaHatPrRVcRJEHqtqLonTV1KZSFZs5heHJSKrEokqx/apajSwAixziJI7HKco/IUBOhRiW1pvBA4FWp6nQ8NP8N5gFmIwIeoZGk90nj0yBJv5sit8fba5DgKK3ZRFdNcr4DViWxlOeeNUXOJYjb8X6lQ+hYr/Moio2sWptcNAnkzbUXZ1cilBGkWiDYmyM1h6KlTlNt9Mb66gLWfplLITPvKjVPeKVwoEnMh1ZeLUUbWkJcrD14IZGFZvKvk6Gd28TdLT+Gf77qDnpyghCeVJakoGfmE0usqPnlGZmrCsKzH0IJ+kbKhu6hJ5Ts0Va8wa/Fph2Jfj7VnSla/6iTfeOAL9FRGW4Zxs2Z6fGW8CsCinnAw3mDDdBjYlD3xgK4KysyWbTNwwYeTu2jbsUDo2eK8YCHJOKlFlULptpvhvYcizEF6Q7P8JU2+3OLOPausxkMWNVNjfiQskTBYL6dpY1I42sJOFSjnQ6PLL2zu49RH9rPvs5benVvIrVEIMPAeoRQiDSV0rtfCV808t/VxqZQVUZazFLE5rwqRwrVTyt1tbKLwipC+5kGWDpmHRUxZOuQwC02mjZ2lmtWlazWEgFhgU0W+y+Hm1K8GD4zfe+q38p773rAzO3vFrbz9EXpgLhZ+/S1v46d2QIU5svsnL6l+LWeLX/73r+JT31vw/zzh/39W2zcEZh51rC8g8gLZhzgvMUvt6co+gKyji0Uw9YvC4FGhVCxSSMB0Y1ws0SMTDJJl1aE3jsIKkJT4XodyOcVrgSwCqQk3yqqHTBF6o9hUUnYUehRXPVmCNB2inkMggFdhH/VN1qbB/yInwRcjiyoieVqaZQEHRTX5eBf8JGUZCIW1xGsjfKxDA7ROICh1dHSoeYZiURMNQ1KZLD1t69GTEKmsRgXU9clQfb/EpxG2k+BjiY2qicZDvJEjxwViOA58olZI6qhlCKt8WiPShPKqXVXZng+JZ7Wx1YUAAlMFHrhYkO/toNsx0bGNcAzGQllsTxqrywF8pS7NlWg0eHA8lpWYR6vCnAtxmf+ehvBc+hAmxO2mx0esfnqRT0dP5OQze3zd3i9zbXKKVJRTpSUShk0fFqrGNpk2euypjMxF7IkGFD3NkYVFyoUUF9XRwB5ijWvHbD4+IXrGFv/H3ru4NjkJgBJ+GlOspcU4RSIMHZmzQWcaX1z3WMmJpmRFCsfQplgflJK6N8ta0WUza+FUSJz0UoDSlandzrrRG4OYFCSnMha+orl33yqFVVy9sMH13ZOs6BHtqqnn2CUcK5YYmYREllgkI5MwsRGbRYs7T60iPt3jwD/kJEe2QvpaaUJq50KHcqlNuRCRrWgGV0uKZY8eCXr3eDpHC6J+gYKQNObcNESmLvvykcYttslXEiarGhsLvAJZQjR2RKPa7xlS25SWKKUQeTFNgmOuFHra463yqoLCu2ZB7Gzwf//OSx/YOH+OGN64H/iFB3zvTPXlUsKjNfMH1eXynR/u+dT3AueJwBhjuP322zl+/DgA+/bt46lPfSpRdAWU20xN4JUcPJ4g8gLtPL4V41KN07PEK5tqRKKRWVh9Mt0Ym0h0JkMaWBXBXPQiWuOqmVa9+q81vhWM9ojQL0WWDpWZUA5GUG28Dh3u09OV56WtQ7TxxOBNyO4PXpwqEcw4mIt+FtZRLiU4JYjvM/g6Pjg30EpnkZf1JaiaPIpJUHuEcfhYI4sQB60KR74ckZ4MK3vt+8JKmsxDlHNsfWgC5v22zsVAmCB2tzEtidPBmyONJxo78q6i7Cr0KCHqp+hT/Vnpl1TBWF/HHHdaTJ6wG4B4I0OPQuoZUlB2oxBbDUEhqoiPSyT5rgQf7yI+vI7IcrxTc8k54WfufQgNEM4hGwJz1jifJOZS8r48EB6OxMyTjXq7syUg57NhZoPzC+FceFguLAuf3yTu9zjR38+Hvs6j9jqiJPhfOpVKorTntO1OO9R3VUYqCjIfk7uIns5oxSX9TligmUa/a0W5mLL5ZPj6g1/hia0TKOGxXrBuuqybDqVXRMIRKceiHk9fj4SlLEOcsyQ03IzkrKHklmmhcCTSIGV4v3QK4yQurrwuzjOVv+uGw5WJXhiLHJcs3JPjooT1jd1sXNtGX+VwbUFXRWQq4lixxEdOXsux04s4J3ClhFwRn1J0jsLqcUd6akx0ahhim4XAtxLscofxVW1OP1WR7bXIXRmHdm+wtz3AOMk/fuVqJp9OWbhH0z6mUIMsEI46d0KG/RR7u4z3xjgNNhazBboFQdlTyDLMKdHIoyeeKJbBC5qlqK0MOZpAls+qBZjtXxaOeF2SpVfAM9IFQK0cnC+ScSmTF5id/7koMedSKva9J17FHW/5hm2vPenH//qswwYeDi//xdsfsfrzWfVqPvbdZ//ZsyYwzjne8IY38Na3vpWtra1t7y0uLvKa17yGn//5n0eeWVd6uaGK651mxdclRs4hxwVusYVLQwpZvbpiE0WxpBlcpSh6sPJPkmTTIK3HthR6YpHDjDoCOGRh+kBOYkE0dKjM4qrmmT7VmE6EUoEItY5nCONC80wtgiKShvIrF8vg95hYZGkrydyhBrby8ITse9sN/pap4lDL3XVSV50ENtfJONzoQxx0UIVCn5tOP58Sm5osYT1qMAolYdN6YD/1upjVHtmeFtmyIhlYopEP/WUcuEhMI5kBJvtSUiWITilEfziLWC5KhFYUh3bhEkm8XiByi0+DElYuhPKLer9USpWNJV4I9NhStjXu2lWS+zYRfT9Tec5EaWYlcg3OCo0S8/ATzk4Rl3MlQgBf9d+/+ICvf+aHrj/rfTQ4ewgTPBmi8k6kxwS7bl/gvsX9fOKGgvZqWPxZUsF70pMTImEYyBYjl7AgJ6SyJHaWTS+Y2AjrBIiKNEiJSBJ8HJGtRvh9GYfSDWJhsNUq2NjF5E5jkSxFY3oqoyNzTpSLKFzVOHP2wG2RME2f9xinKNDBB1M99Xd0Tqwsbgwit9P5MSz+zRasvA1eESkE0WlYKRzRKOW063CrP8ThpWW0dDgvOHJqCXkkpXtYoCeeeOCIxo7k9Cio8sZN5xMfheCbwXU9Tj9NYZ8y4qkHjpPqkpV4TEflU4+Pu0ZwR2cPJ1cX2P8PMal1iEkRPDAmlH0Ve7sMDiV4UTelhrIjyFbBdDxeeVQmEFag8kBuhFNEA097zdHSgqgiq6KaT7ypevGUBpUZ0tOEeOYGZ43hjfsflRKzEyrOxcSDlZM9Ul/LjT/7TgDueMv937vjLd/AjT/7DXzil77jnPd7w5tm88qtr72eL3UibnjTF7n1tec+r5wr8TlrAvO6172O3/3d3+WNb3wjt9xyC3v37gXgxIkT/NVf/RWvf/3rKYqCX/3VXz23I77UUJvZYXrDFHkR4imj8HrZDRHBUJdU1QoI6AzKtiQaCqQJZQRqYhD9UViZmprFg3QdDR3RsCoZK10w6AuBaSlMSyF8KI+SHvS4xLSj6feWPQUe0rUSF0u8FdN+LKHW14UGl9aTbJQhZrJO5Jqa2N3UuO6rhDRvbOhzmQeCI7eGyKEMvQXaSbgmhQnfUxp8HIW0FlcRhzNIgeumZHtamLYkmjiEIURQKwEieHf0xIV+OS40xyx7EdAlsjYkl1kbzPq9NsVi6C1TLMXUFeO+jp72IAuLygzlQoKNJcKHfjp6XKJySbYao1a7aOcQeYkvqmS0ogQhA1FyjvZhR4PHHh6p/6UmE4+EXMzjXFSXN//EK8/qex6MvMy/95kfun7bv88GX6/+nndtPP+stn3Moaz6WdV9SCYFnXtH7PpMjy8sHORge4vF3phdekgqg8KufDD271Z9AGJhGYm4SuGqGh4bEeafym/hk5h8UZC0wj5OmR49OfNbtFVBIkucl3RVxqZtk7mISFoi7DS6OXca5wUTl5BIQ241fZMED4pTlF5RVMcwyBIW1mcLZtOmkfUcMu3FFUrKRFaihKB3D8T9mNFdHQa9Li4KZVorW5546In7BpXZUGWQGeRwElT8miQJgVvqsv6MRU7d6PiqZ97JC3d9mRU1YuwSBjYl95p2FURwXXcNLR2fKhX9e7voUYQcx2EOEwKfxmQrETYBGwlUAWVXkO3yFLst0WKOM5JyI8anDrQHIxClJDmhEE7iZUKnCD3Qpo1E61J05xF5ycI9htI1cePngre//mmXvFpyvrETJvwvveqJ/IvlXzurbW/82XeeNYmZJy7JU/pc+9VvA77I29rfAsAr3/RFkqf0+fBLbjjnYz5bnDWB+b3f+z3+5//8n9xyyy3bXr/mmmv4oR/6IR73uMfxfd/3fZc/gYHtMrCrFJOiDDfSXhJ8KFqgRzYkbeUWlQtU7rBJ6MniYonXYTUnOTaemfukqBplyao5JHgtMLEiGpSUvfBIrrLQQBKCGbRciEIzSy0oWxFFV4WyM+MxHY3KbWggWSeTaYlth5K2ckHT/fKcaibmmkbWgQJyjrSdaXC3NiS7eD9rWkZIWAEQWR6uTa281F2OqSbXfV3KjiQaVwSjdAjnkR5sGkgaNigwviI1IT46RhZd1PowEI00DnHT1aEWCwrhZoSujreOXJXiVli8DtfG6aBuCetRmSPbkxDHy8RHt6rVuFBPXV8T70RQfxqcEx7LKkyNC0FczvzcQ33nQ5GXB9vuq/77F8+axDRNLB8EkQ49voinvUpkf8LC4Yj89hYfWnk8e5/YZ1+0RVbdxxwSiwjlXsKicCgfUXhN4TSTPKZ93BNtZIisCIstpQEH1oa0rtrzEsrGghk+FcFXAiHlzFXdUBZVUCqkcIxtEnq/TKukPYm0GB8SzAqnmdiI0ikGX15i77FhUOkrNQg5S/4SxlTNkmdR9WJSoAuD2spIT0ZhvlJVEEBuK6N9lcJZmmkvFUozbdJZHlzhvhe1MU8bcv2e03zj7s+xWw84bbtVcprC+voaWroqZ08y5MBKn6OHOnROaqItFTyosaRcaZMvSvJlQb5S+ScTh9tVsrJrQC8p2Bi36OeKdDGn28qZFBHGSDKdYluayVhSttt0j0YzH+c4m/psRFbSPtynlA2BOVf89rtufsQk5lwbSV5pqBWXf/Ew252Jh1JP5kkLwJO/58389DvfB/cQ/rTfN33vbe1vgXvga67rMr7z/DxLnTWBGQwGHDhw4EHf379/P6PRaEcO6qLBWVC6KiNTeKqYXhP6o/hWUtX8gldgW+Hm7LVED0vidTt9+M+XY/CQnM4Qw0koVao7zNeQYNMQPyycx7R1UExKF8hJbqdG97KnyJfCZ6X1VZ8X0JOgWpiWplhQxFuK5HRYfRPG4XqaZL1EblS/QDWxKMNqXWhgaafKk7eh0aRXctp4U0z7xRBM9HUzr2JOoSiq/dXqVdWt2C20mOzSpBuB7JVdhdOS1klPNCyRhaVciNETMw0cyPaGKGYbS/LdKa2sDH1vhKDs6mnKWA3hg9JVKnBKIEuFykzwA+UhhcYmEtFLMHVJX+kxHYXc1SU6Wpn561Wz+mdkGwXmsYaL1cTyUvS6nKsa02A7Qpw+oCReK0RpEIUjOj5gJZIcW+nx+b37uD49hlThXuOQFF4x8C2kcCg8A5eSu4hBmVDe2WPPEYMc5/i8wGcZMm8RTTzFMGZkEhaTCR2ZI3G4io0UXiOpF9EgcdGUxJReEREim6XwJMJQ+mD2N1IhK/ICEEvDp04cZPlzAtmfBAIDgbhIGeYNIWaNkud7bdVxw5FH5rMYe1HamV+yLjuum1LWc08cYfYscs83tnjezZ/jBYt3EglLKktGLmat7E0T3CJhKZ1m6DWZi9DS0o1zyr0lg4Mx6emEKLchva3qvVYseuxVGUpb0tiyuzfk+sWTLOiMtaLLV9q76MY5u9MhpVO0VMnnF/ZSHNRsDVPWl9pku2KW75CkayIEBlSLnqLqkSMpz9vv2pWMR0Jivueqw/z2eTqec8HFIlE1eXkkEKdvf9htfv3LH+Iv9Ifgl+D3eOFDbvuqb579+wPXvO4RlZY9GM6awNx000381E/9FH/wB3/A6urqtvfW1tb4d//u33HTTTft2IFdFMjZwzeyksJrBSKJEaVB9fNg3ndiarYPiowEFVZwTFuhCke0maNObkJZr1LNqRwQHthlPFVhhK/8IE6gJiHn3+p4WqZmWoJ4EMiNjUJ8shobUAIrBSYRRHXMcRIabEYjQ3x4PcQHSzHtbr8t7lGqQGLqpK84Ckky1k0TybZh3uOi1dS4OX3w9x6fxLiFFqOr2qjCoycmnENbgheYjsIrQbyR40Vo0ClMOGYvBE6HtLOyLVGrHZJxPre6F8rNooFDlVVMtRJ4qfES8kWFMFFQscrQDTkaGfKliGxZkW4Iks0SshCKoJa6yM0h2PBz99Yhkhjq0rIG54RHosLc+Kt/dJ6O5uxxMcjLThGXsy0leyQ4FzWmwQwuVngTSnmBsCDiQs+tZG3C4pcjPnP9Qa7ubHB1sk4kLJnX5C5iy7TInSZ3GuMUW2XKP/7jEzj4MUd6tFL06wh670k2LWo9YmIj2iqfxieHPjNR+OMjFB6LYFGPARjalMxFWCGnTSJbqkRVRhgtLc4JSqewXvC5U/sR715m12cHobTaVYTDAVT9xGofTJ3o6ColpVJRsBYxmfllRL0P78PcUiHchyW+12b8+CWOfq3mcTfex4uW/4klNSZzEYVXbNkOudcMbRIUKx28PaUL/p5IWJbiCYcOnubeYjfpRsKC8ahxuL/rzKMmkmIQQReM9EzKCCU8XZVDDL2VDCl8Fess6OocueJwXnJve4mjaclgsQPErBYxIrdI78EW2+OlG5x3/Pa7br7o5OW2m67e0Qf1c8GjIS/z+3igUrJbX3s9H3jVI59nbrr7jdz046/csf40Z01g/ut//a980zd9E/v37+cZz3jGNg/MZz/7WZ761KfyF3/xFztyUBcNuxYR/Xwahehd1VAx1uHGqhUiy4nXq/SvODyER1vB1O5ihWtp4q0COSyQaxtB0agmmqm6oUPkpBoVqLxFvlTFVpYhkUvldto40+vwsB+NQpmaLIKBU+WhmaY0DicUsnAkA4uLRPDJiFCGFh1ew08ms4Q1mP1dx3AqtvdpsdsnkelqmveBpMxHUNrK/6N1KJmoVuHsYovBtR1MS9A+ZZC5xbY0svTT6E2vBK6lQYZUHWc8pq2CuuQ8OgsNNPvXxKyMe8hhERLX6tI1D05JJA5ZWNINg2lLZO6xqUKPzbRfj+1ElfkyXGdhPEJ4XCwpdrWJpESt9xF5gZfhGjyowf8xjh/74e/lN/7b7z/kNmdLYs6GuHz1VyXnPYnsciYv8/trSMylg8m+FnodVD+rSmyrdEYiRF7Sva/A/G2LP9/8ajr7RrTiktwohlstfKHACkQhiDclybrgqrsN7SMTZGFCSa0xVRiLI94saJ2MODZZ4MaFEoVHCUckDBmhPC30XAllaZEwZD4mEpaBD31fhjbBuHBvTaTBEvp9DU3MZtHiK6dX0B9aZP8nB6j1qqeW81UnehUCXZSbLgD6SAfFpchnC1xahde8CYTujA7205JlrRHC4pZ79K9f4OiLHC961mf52qUvslv32bQhWS0VJbt1n0gYJJ6hTbBhAiGSlrYosF6ymgwZm4gTyz02ntxBT2LaJyv/ZeZJNkFYTb6iyBcNpwrN3a0V4gVDWxbsSYMnyXlJ5iKUcDy+tQbAUjRmKZlwb7rEUb8LYWJ2AfG6QBpbne92ctbg3FArGfNKzG03XQ1wzkTh0ZSlnS0uZ/JS4wOvehs3/eb956ibfvOVvPDdt/L8d3+ID1zzOm66+43nvO+f2iESc9YE5tChQ3z605/mve99Lx/96EenMcrPfe5z+eVf/mVe/OIXX/YJZC6N8U6FjvFK4J0FZ/F5tVJkdahlLg1iWOXe1+krgKwf9I3BOxcmGOcRc96KqbGxLBGTHJU7zG6FcGCSoLAEz0soVwvN0MIKV3K6QPhKrTFhVctFimIxCmVReVUeJiFZmyBP94NBXchp0ti2niqySkWzVElfEp8Xs5WyunFkbfxHzRp2ORd6qRg7a0QpBL6XYBdbbD6xMzVoRv0QEOCFQE9CE1CbBKWp6EXBD1OEsjAXC1ThsUlolCmNx7QE+UpCe2uCNFX5nA0ldqiQyiYLS7xucaoVTs34QJiqQAM1NqQTQ7KhghfGeWQhcKXCJopyJUziaiN0dvZlOU2ka/DIME9iLgWF5cFwscrGGlzZGB7QpIVADkMIjFBqFi/vHPEJWB2VtNbaTFYWcBpaE1jasngpKNshCKa1VqAHBTKvglPqB+K5RSdZWNI1zxeP7eHEyiIrekhHlIxcQlGZBuuysk7lj3EYElnSlgW51ygcTszKykqvyJ3m5KTHl47sIf18i8W7DJjQU2xbaTEE5b2qNhBxFDyFkZ55J50L8cV1A0nvZzH+1bODNwaMQSiF77ToP7HH0Rc5vuWG27ih+xX26a3p8Q1sCyslkTAsqTFSeIY23MfHLpCzus+OEo5RknDVrk3WkpKTcom9t8aoapEMH+ZNacBNgv50ZGuR/a0+SWKmylXtLapVq54KyowWjsUkwx7c4GS8gE1TVj8jaJUWJo2Sv1PYVpL1rot3HA+FK8V782+Xlx/0vQ+/5AbyN52dt/LBsBMk5pz6wEgpeclLXsJLXvKSR/WllywkuF4blRUzj8j0gd3jq5shRQGySuuvH/JhZoivlQ1ZrUTlRVhpqj0VIqgxIi9Ijg5xukfZkdQeP68EZTeQmnijIC5DspisIotdZaj3SmI6empq15lFDwrU+nCWOFYfV526IhVQlYvViWvWgg1hAUAwTUIoJavPz4eSBe/9zO9Sda6vy+yECiVe+a6EeOQoOpKkbzFthc6CquJEKIUziSDZcJRdFc5byCoxzIcyuiqHXxhPPHTYVOLSGJVZTEtVpn0V/Ecjg4tVpdrYkNAjZ+fjQ/IoclyCCg8BXsvQrTnVuCioQWIxQWZFUGGqVLUGD4yzvfk0xOWBcb48L40Kc+kg2wXZMCLeqlIa1ZwKnhdBSc8KupOSTqSmDY/FJBAe20vDQssor0hPUK+nBEApRBSF+7T3tE9Zhne0eVfv6aw8foSKNsh8ROlDDLKsysJKryi8YuQScheR+9DbRUtHSwRCc+d4N1/a2s19J5ZRxxMWDgt69xqSzTKcS006KjXeG1PNIy4smuUKoRU+TYL/p17sq+dTJQkTrps2dg77q+dOidmzwKnnSG58+hd5Qe/L07K4zAdFySIovUIJRyozRi5hRQevZ+KS6bmmoiQSlqvSDaRwPGnxJJ9ODzA4vo/Fu8N1VUVoeOxiH0rBgbzQDEwy9Qr1VEZOxMCmTGw0VbRypzFe0o1y9rf6PH7xNJ9MD3Had9k3TomqtE5xZil2AwD+VN3Hd9qrLvZh7AguJnnZSfVlfp8PVEr2vSdexT/9AY9IfZnHoyUx59zI8uMf/zgf+chHtjWyfMELXsCNN974iA/iUoEc5tBLwoSQZbObbf3Qb0y48Uo1KwlzftZksSYuWoft51GXYlk7e/A3BjkYkaxF2KSNKsI+XDTrII8SiCKQl9B9GUwv3MBVlcGfnirQa8PtNcnVhCCcg7rJqLVhUildKIuzdWqYnuvZMqei1YpNTcysrUrRKlIzH5VZkRez2AqEQEK6aZGFQ49CFr6LFC6WxAOHnoiqMaYnXwj9bqJRUJzUxOGVwKSSZMMgvKPsKMrllGgrA5FgUkW+EiGsp+zG6Ikj3izBg+5nuERPG3hGhI7RUktkZkBXBlshQn+bTmjUCeCTKDSy9B6azsmXDHaqjKxRWx4dGhJz9pAljPZL0vWEZFJWvVsq8lGVdYX+YllIdKxUCWFDR3c1yMC60FQYgkruZn3JgPDvokT2J7QcrLR7rOldvG/hyTx/5S7askAKR0fmpLKk9JqRS7DIqcqSuSh4R3D0TcpHNq/lK7cfoHtYsud46Meix7UqpMGmqFgjo6qcuC6TKsrZ/Abh2PNiRmoqiDMXh+p+ZNU5QrgPjw6muKsnPKUXnjVKrym9JvMRI5dUCksgZiOXhAQyJLmLkMKRuwiLIK88QA5BS4XFt4PdLT69ey+LX4FkwyCNwqSa3EuyjkGkloVOhvPB/zOxET2VsWVajGwS+uzIUHbnvGAlHqOFJZGGrsoxByWfLK9m43TKSuHQm+NmQewSwm+/62ZueNMXefYHDu/Ivi42zgd5eSj8/t7f5IY3/cSO7OvRkJizJjAnT57ku77ru/jwhz/M1Vdfvc0D82/+zb/hhS98IX/yJ3/Cnj17HtGBXAoQxiBKi+u1kOPJ1AtDmQd/R11u5Q3eyKmRckpe5lGb4KsgACFEkAKUmpGAKp5ZH9ugUzryPa0QnWzrNR+JTQJZcs5jE4k04ZhcLNEjT+vwFmKS4ydZIC1xhI9jfDvBRwqbatQkZPTLcRFW/vIw8XjnoSxmk4fzQWkRMpxXrbTgZyVo1CVz1fHPN8HUqkpNC805IZRy1X4eAD0sEVbjdOhj46Ug2XLT1UXhA3GThZ8qUrJ06HGQ+IVxyNziFjXJpkGPDNnuGC8ExWKEcCB64SFVWE88KEGAWYhxSqClQG1lIYEmUYjSE2/moawt1ZhuTDSKq67KzYTzQPiN//b7/NSPv3LH6ljPFjX5eCRE5rFEXM5UYeb7u+wEGhJzdpAGygXIljXxKTUjL1LOSqdsZXKvPRLeQ6RDU998EsqRK++EqLx/s073chvpkeOchS96olGHO8rr+NyTDvDVjzvMtZ3T7I36WCVRwpH5KEQpe0lbFkSRZcu2+OjatXzp9oOsfFZy9VGDzEN/sWxZsfGkmMlehywEUT8iGkOyEbrSJ1uWeDNHbU0Qw8n2uTDLZ+XTlVLv3dz7UT33zC0AynCNyrZkeWFMV4VUTYtA4aeR03XQABBKugil0okspyQGL1HCgmQaLz20CVo4in0lZVvTOjZBFppFC4NSke8W6MiymGYsxxMSaYiExXpJJCwtWbArGhFJg/Mh/GBJjWmrgsxFpLJkX9rn4O5Njl2/j+7xOAQGuDOeERpM8UgbHz4a3Pra67kVHpEf5kW/tZ+XH3zgpotvP3L7g753OeLBVJgX/T9j3HMvwgHN4awJzKte9SqstXzhC1/gSU960rb37rjjDl75ylfy6le/mj/+4z/e8YO8UPBCIIoSs6uLTGLIi8rHUhMK8L7qsIudmdvr0rA4gjwPf5jF8QqYqi7Th/+6vMkEP4w65WnlJdmBHqar0EMLHpwWSOenJVIukkSDEnV8NAsJ0CpEHrcSfCfF9BJQAqfltNRKOBDdCGHaAETrY8Q4w49FUFmEqPL/FT7LEXG8La0sJJKpWZ8Y58EFRUrUpWcmrNIJF0q26oZkwjpsO0aWobzLJSG1rehIbAo6VSEOWgicCqQnGlriLVM1tAz7d3FV9qXk1Igvc0N60gfy0VYgPKYb4atkNzUJ56YyG+KpsxKqnjDYakIxDrTERQJZgG/FyKGiSb28NHEuRObBiMtn/uzIWX/fV337wbPe9rGCJmL54VGseGTq6V8jaa2lqK1RKM+tiUrVDwxjw4N+RUyEjSqSY6eG+DrpcYp6kalWY+qY4lFG+8sFByaLbJxM+UT/Oo5eu8izdh3hQLJJKsu5njOhBOsr4138w13XkXyuxaHPGZL1CTZVDA7FrD/dE18z5Jpd6yzEGZkJn52YiFOjDoM8JttISY90Wfl8i+69E9TaIDQfhm1BKL5aENu2qFcRsPrchJIh4CWO8HMVdxYZetn44HlRwiFxjF1CRozzAoWjLXMcklgZCh8ac0rh2bItbEVyjFf0y5TWYka2vEBPS2RpifvQSgXjNUXRVbR0SUsVdFU+9QPlTrOgMxb1mNIrxk5P+80s6jFb1fyaSMOB7hann9Bm49gi0VaC6Efn9fftcsWfveIkb//yS3niRfr+337XzXzgVW/jD+67+qy3/+0z/DfzCsibfvOLD6qIPJJO95cy5Md/HPfctzzq/TzSxdCzJjDvfe97+eAHP3g/8gLwpCc9ibe85S1XQIyynEn4SciUF3E0vfEiBZR2tmqkdbWSVqkSpnqwj/Qsmrg0M9Wl3keNmtQoFTw3pzdJixLXa2M7UfXAHkqtQuRwicoM6tRWIFd1WVoc4dMEs6uDTTV6WASD/2Ia/B+EcjMvgirhEkWxu4OXXeK1EXJ9EJLKKog43haBiVIIXR1/XTImRbUCWJkv8yKUXpUOVfjZKpwAF2tcJLEthR6FZDDC4hjRyCNLMC1ZkZdAYLwg9BTwYNqy6pLsEc6hJiWmU5lDM4Me5ch2jPAJ+VKEjQXx0KJyR7EYI61HjU0oyQB8rAMh9IBxyFGOTyLc7hSDRtgEeVrOknEa3A+//pa38VM/fnF7lzxcWdkDkZdzIS5nfqYhMg3OBeWeAmVjTA8m90QkR6NQ0lslWqJU8IfMLQBhHV5YkG6qgIskhiQ6I/qeWWKXmBEZYR0IR3xyxGpmSPot+l/ex7uv2sOu60+znE5Q0pFbzdqwQ3+jTXI4Ydednu6RHGE9430Jp5+uUM/c4v/3uDvYH2/RlrMSsEU1Yst2iISZ9qj5TP8g//ikQ2x8ocuBv9ckh9dhks2UIl+llVXzhfAuJI21WlBWiWreQxRKeL0SeAWlVWyUHXbrAdYHBSkWlkgEM/2W14R2baFMLhYWi6+8LwUletrAMxz7hBU9wnrBWrvDYGmhqlIwiNLROlXSvU+ylSTkV2kSaVjUk2lT0MyFUrLcRWzZEBizJ+7TlgWpKNkC1srQVPNx7XU6Bwve/1VPZunOmGQtPq+/b5czXv6E/83bj5QXTbmo07ZuufOlfP434Ru/9IPb3v+D27/9QZsxnkv5Vr3tlUBkfu2jz+KGN32Rm+7emf09EhXurAlMkiT0+/0HfX8wGJAkl3mZRqTBghpWD0U6lI2J2nwpZGVUr1K96q7tpUFEevqwDwRVQ4rZ/6sbduidUikzcyky0xWp0QRVGtQ6RHFYiRNFaOJYG/Pr0jZRRVD6dkq5p4sXgqifIwqDr/wmpi1JT4XJRxaBeKhxmBhtJyI70CNux+hjGyEWE+ZiliuyNp0gq2OvFRgZksq8nPloVGbCCiKERpFxMOdL41GZDQlq1oOA1kZoKAkwSUIPF6fBpBK5oHETh4uDod+nwYkvjEOMMlQ3TAZmKQ0lchD6LQjwCvKFcN117olOF8G0H4Vma6YbBc9LaVFFpT4ZR+vYmGIpCf6YSMOM0zWYw9nEKF8onEtp2CMhL2d+/nIhMee7jKzBw2Nxecxg1AIjMUl1/zE66MnVYhlVGIswdSJk3QxZbd/ZfNRwrVzUD/1ybrGlVjLyAr1hWRrmLHw5It+VsvmV3dy92+MV6IkgOQ2HjhjSU6MwN3hPtrfNyRsl13/NV3jByl30VFalb4W5IRKGddtly7SDguMUy9GIZy3cx+OevM5HVq7lmNnHXr2L9NgwdKT3vipxnpsLvQgVCkoCEQLwZRnmQUKpcLrpWO+32DRtCq9RwmF9aPQphaPwqoqDjmiLkp7MQtqYS2jXZMZLTtsuUJWQqZyezHhcus6JzgID9iCtQxYGF4d5WeWgcsHauE2/l04JTFsWLMehWXfuIiSeVJasqNF0/w5B7jTOS1ajIWmrZN/+Dcr2bmLdLIg9ED77eLjjrV8NL/3YxT4U3ntdCJ35bc4ufOaRek8erCzrcsPbv/zN/Df9tTuyr5vufiO3nuNnznpEvfSlL+X7v//7eec737mNyPT7fd75znfyile8gpe//OXn+PWXFlwccuopDb5VrZZU3dlRai5lzM0UFUC0QnRjICxye0+V6nWRptVkU/UwqSehJA4rUVrPJqnKECkGI8RoElayJhnemJkkX5OjNKHc1UEYj97Kg88F8JEKPVFKjywtclzOUmwIiWBqYlC5pexGmL1LQXmZXoxqta8ibtNShvp6TI93bqJ1Drk5QuUO25LB59JRjPYrRvs02a6IogogEI5grRFBjbERqDIQjrIbIqVtKrGJxKvaS1OtMk5y4hMDZGFxiaJcTHFp6MsjSw8eVOlDituWAUdFmkLamB6G2m6XaGyvIix6do62NTPUNnhwXAoqzIXGoyVBNc5XUliDSwe7OiNQHlEITAu8mruvVEZ2Yd00ocvX6Ye2CozROpQlz9+LpglkVe+Vep9UDSHruSMrqj8lanNM+8519n9gnWv+94hr/veEQ+8dsO/DG3TuHqA3J2HekJLNJ0QkT9rixuV7aKuczOtp0ldPTUir2OVFPWZRTVjUE/LK93FNusZN+75E8vzTHPlnMZOrevhWUilLlbm/Vu6h6otWzTO1D7Mo8XmOGE3o3DehfXvKbWsHOVkucLxc5LTtEgtbmfljSh/IgqoSQjMXUsIAenKCEo4lNaIns6oHjq/CABSbeYtoGBpKy3EBAopFzWRVUKxaOnGJcQpbeYXqSGaARJZV6Vg2fU0Kz6KasByN6eiczIWkMiU80vqQLtfgfvhPm/dc7EN4RHi0xvmdNN5fDDL0Uz/+Sm792T+74N87j7NWYN70pjfhnONlL3sZxhji6mG3KAq01vzAD/wAv/7rv37eDvRCQGYF+HBJvJTINMHXSouSU9/6tAxMCEJer5/5WyRzRkQVfCJShZWlKJoREKWC6T2JZwkuakYGfNVfRohKcbFulnxGZeiUEru6gE0V8UYWfB3e45XCtEMplZo4XKKQgE3DuUlCpLCLFC6SOCXIV1OEXUQd3wglc1LNCIuz20lZaULUpJoLI/AOUIjSEK1nOB0CCWwiaa25adSz8J6yq4MfpQQ9CQqOKiCaOJwKmfzSBtJSRyrHY0u8kYcVPecQgzHaOszVS7hUhpjlSOB0KDWT1qMyj41l8A1tBRVG9TNcO8YmCuUtIvNV881AblRug5Jj7HZy1mCKS0V9ORfsFPG4XPBABKlRYS4sTg67iJFGFoKyJ/DRXBkuVPfPcK+ZlSnLmb9FihAvDJUyM1eGXJMY58M8ElWLb1rdf+FFCMQ4QwxGwdtZ+Qjr7xNlUHLyqxfZekbJTfvvBWDDdKbG9awiAJu2HZSG6vWxizlZ9MLDu57QlgU37jvMp7VlbWsPBzYS9GgS5tCqb4yIIrwT2yoQZn1tqrnUOlQ/Y+HuNseOLXNyd49IWPZGW0TC0hZ5SE0DpHekoiSVBaVtTf0yCk9b5KyosiotC+c8tClH80XuuWsPhw6bkERpLDI3eJViU/CRo6VLtLS4qv9LW+ZYJB2ZM3IJPZWFxpZE9OSECFDSsawFYzuLX86NpjN2TSjMQ+B/fPBjl5XxfafIx+WsxHzgmtfBrz66GOVHi3MqIfut3/otfvVXf5Vbb72VEydOACFG+TnPeQ4LCwvn7SAvJIQNjRZrMjCdDKq/vTGzkjKoYparG3Hd62Xa88Vuf8jXchoGsK0koP5/vQ8TbvLTEoHqu0Js89yDdaQxndDEUtiaPAnsQszoQETZFggXlBiTCnTm0WNHOsjxOvRcEdYHQlNWRvtuG9a3ZuekdTgOW5U3RBqknh1vvfqnNd5YhJSozSEJUC6nCOWJJjaUcCnQI0vZ1dhUEg1CUIFNJNHEoUcOaT3RKFyXaGSINxzCh/4IcmMYVuiMDcc+yYk3MrJ9bVTm0BNPthKSyNSk6pkTSaKtkETmlMSttFGTcuoHEoUB6xG+8uW0NCo3UJYzxa1BgznsVCnZT7z5befUD+Zst38odachMRcO42GCygWyFNNExdD42M1KyIytgmJseKBXKqguUBn3K4WiJjPVwpVPK7W88kH6JMK2q895kEXV9NKHslu0ClHGg+Hsnh2FZpNkOUQRk1XFNdcc4xndI1jCQ/hq1J9rFLn9flirMxMb09F5IBYq5ymdYzgv+ZsnrJDd0aKdlcjqvh3IWVWKDcG/KUUw/StVlZXVi2eW7n0ZS//Y5q+6T+arDhxlTzIkkSUHk02kcGyYDrLyvJwyCxzOVziWLXJ3uso16RqRsKSiIPMxJ8sFjmZLfH5jL0fvW2HvhyTt+4KvwbcTRGnRY4csFGKiuG9zkZYuiYQjEeEHuKKHKBypKFDSsWXbSASxsNU1CT+XtsrJXcTYxZxe77KQu+B/anA/fM/4f/Ln//VHLvZhXDTsFIn5xC99x47HKftdT3tQX8qtr72et7/qiTtWQvZIcM59YBYWFnjRi150Po7l4kOI6cqUqIlLbZx0cvZAOx+HaG14oLeziWb6sC9nnhchBN652SQ1Z7yc1T0TPlu/p1SY3KjSWbIsTAC6Sm5JIkxbEfVd8L1IiesET0A8dDitmKwIvAxkJd20REMTJpC8RJQCJQUuVthEQgzs6xEXJX48mRkw60hoJYP6Is84BxzeEvwwJqg2yjnkKAtxzlpiU43wIUlaT0I6mTQuNG7zMdGo8rAAcRl63sjcTOOfxXBcqSISoXw4HkrUiU3iRFMuxOA90nj0yKLHBtONQlmF98iJAS0pFmN8JEOPncoIK0qDixLq5pdykFXRn00J2QPhUvLAXO6oycZONba8kKVpTQLZQ0NIj7ACYUJPGOGpFJbqvmlCE0eKchZTr2cd7r23cwtoYvpZn0T4OBjdRR4igl0cIvNFFcnsZCAGMjcheTHS0OvAYBRKkpkr4fIOum0muyXXdzeC4mLTSnkI/WPmyUtP1rHGkkU1IRGGtCqpasucgUtZ0BOW9vc5/dQVVN4lzQ1iNNneIBqqioczSuRg2kNGnxqw+zZYz7vcdt31mNWSuFewd2lApCwtXbIUTyicol+kHF5fJs8iut2M61bW6EY5ibRI4fji1h7uObqL7mdSDn3Z0Lmnj8jLQBSjEAqTnM7oHg3z4XghZbQUU3rJ0AbFJRUlFoHzIdGsWxn6pXBkLuJkuUDmIhb1GIDTRZfonoSoP9yeItegwXlATYRueNMXEadv35F9PRSe+Jtf4tbXv5V3bL3jUX0XcH5TyADW1tZ429ve9oCNLP/lv/yX7N69+5wP4JLCmd6VOnffOsSDVBPVnelDnxcXiM68CbOOS66UFI8Pq09V1r2wc6txVQ+AWmr2k1l9rTcGohiRxCExLI5x7Rg9tggPLolmpMuBHlrahadYUNgYiq6g6Cr02GI6EaKtw0O9D4ZJEUtk4Si7GrW6gDpahrx+Y0J4gaikfcXMbFr7gHTV8HIuEcePQjSoHGf4NA7ifdUrJkQwO4g0Xkv0ZoYwoXmlKC0+UqhCICZFCDAwFp8X9w8P8EGkj75yAnlwlXxXqH2OhmXoL3N0iG9F4Xydw6QxLpZYFfrMCOPBUZVgBE+MygxiMMKXBVhDg8sf56N8bKcN/WdLPOa3q0nPuZKWRoW5MBCAiwOJCQElEqnkTKF3bnujYAj3tdxN77tAiKrXeqbYGwuRQhgQRYlPo6qsLHypjRXlLhVKiIsYPXZE/SL00EoT5OnNQCSqEBqRJNjlLuO9nr3JIPRbEY4EE5pDOklazWMKNy2jsl5Qek1b5Sg8Urjgl8HT1TkHF7f4p69qkd8Vk843SK6DaAgLhcLNFgt91RRZCAEGhLFExrI6Lln6UkK2GpH3OvR7XWwMNgWbeFQRSo/1BCIHZafFp1cWca2qH9lE0rtbcvBeS+e+AXKYTeOsRfW3TyNEXtI5WuB0QrkYc3RhAYnHdSWJNFNCt2nbpKJkRQ8ppSYVJVnVnDQ0vwyPVv9w7BpWP+OQwwxrGwLzYPiR5Wt4zr/5YT75n/7bxT6Uh8UNb/oiPEpycCZ2upTsQvbUueEXX8zbj9zOJ3/1P16w76xx1gTmE5/4BLfccgvtdpubb76Z668PF+jEiRO85S1v4Y1vfCPvfe97ueGGG87bwZ53FCUk7bDKJUS4scG2krHpvytTv6iLwubMlOH/YuaNoTLtJ9GsdrlehasJTlUS4COFjzWyPwnkxph66S6Y+PMiRE8KgekluFgGM3tLBxIQKbwK+3SxIN6yjPdq0g1HPAx+Ey9AOIFyHq+ZKhUytygpmOxt0Z4shImuDiyo667rJpxCTMsXpubMWnGqVaYqclmMJrOVx/kabTvrr4O1gdjViW628gVJOUvWkTKUVDg/I0p5AXGEOrJGWiyR7+mQ70qIN0t8KwqrksbhpaRc0HghUHVJmwDbSypfToTXktZd66HUQSnulwTU4JLBv/i7HgB/+M8GF/lILh6aIIBLG2YYkUwEeizQY1/dz+1Uofe1ub1elIHp/733YdGsLquKotm8Ud9LFRBpXBpRLsRMVjUmERQLgvFBj4vC/V0PNAt3arrHDMkaiKwFG8VMBRGCciHG7s9Z1JNAQFTG2MVkPiKlZOyTqcoCkIqSgU+xyMpEb6dKRCpKFtWEpXjC8uKI/uNadO9J0OMMUVcUiJBc6auUS1HKqQd0GnBT3/vzArXpkeOcaF3TjXUIo6kDaUzVQyySYUHOutBnbDHGJf8fe38ebllW1/fjrzXs4Yx3qLo1d/XcDU0zyWSD4gCKOAWiAYFE9JufJEYxKGi+Doj8IppEE1ATQ2LMg/jr6EOi4VETFUUQ0bZppgYaGnoearx1xzPtaa31+2Otvc+51VNVdY3N/TxPPXXvPfvsvc8+5+y13uvzHgSydKis9CBuUiKyfPpegAcxQjSLh/HxIXOFwURtVttdNtsZa0UL6wRtldN2BRtVm168GoCc7yrFJ4n67xkvkd26g6UHBr7Ts93Rf8z6vbu/g2t/864LfRqnVE+2s7Fdj6wzDcQ+ZQDz5je/mX/0j/4R733ve7eK7/DdhX/+z/85b37zm7nlllvO6EQuhhLWei6uENBKpu1uIfEK/vCzfJRAMesIhvRb96mkX20SApfGXjAJ/vdW4ifhkcJJ6dOC51MOfUNM62ifPR9fRa4OplQzmIaX4W2Rq5YK3QvfQZB5hQTU2CBsjMp9Hoo01ms8aqG6sX5FzjlkqZGFRW9MkFVC1WkxurpPbzj2/Og68dhUUze28LpdUU7tMMPrFFo3ZgOAH6jDNROzLmY11Q5vWlBTJ5Ai0Cr863ZhpdL5Daerk7U1dXhMHFmhNcyodvawLY21ocPloNiRIiqHqqzPwsH/L0uDSbUPzzw+gI3BI00LtmtLnW/6WA1WHu+xCwFkLiVb5ZPryXZhtuljT1ythyKSSqByRzRyniLrvPmJqzV20UnZICGxXlgHceR1L0r5+6uUuMhP+m3is6xkZbFaUnYUJ54lMPtyklbJ3v6Qfd0N9qfrfGrlIA/2d1PMRczfI+gUBjmaeAdIAK2w2ncw5tSEnppgnGSMPzeDpHSKzETkNqKrMparHgYZOjKCxqUFGirZ7mST9W6LL165wMbRDvMOn2FWVlsF7XUI58mifmtnYgmMH5+L0tO86xBQ6xoTAhnpKZNBCPS6ntnXTE5OXjxSUB+O77QCa9FrjoWvSJxKWc6XWN7bo9fJeHg0z450RC/KPKVMlkRBHzOyide9mJhjeZ+/+uwNHPycp/C5NMaRPunP1FOx/jj7LNf+t3vP6zFv/ulffMzH3vDLP3cez2Ral7Kg/3X7n8FLf+kaXnj0pTzvX731vHVjThnA3H777bzvfe97BHgBv2Ly4z/+4zz3uc89qyd3vssJ0awIUZQzeSh2Gl4JDZZpwAtMJ/Bab9HINPkutduYUmH1SOK0Bx0uUoz3JJQdiYkh32UwiSK/u0ualYi8gCJM8AlGAlGEU9LnqjgQRUXRa5HtjFGFRWUKlXmgEm2UftIe+8FA5pW3DnYOYaBqKZQSiLkWpq0RlcO0JWZpDpUXXvypNZg63FJOXy8z10KJBpAIrXCV8cCkzqspy6ldJszwoN3UZSeJp+Bl1j607vTMhGfWAWmN0YA1uNEYPZ7geh3MDp+N47R/n6JhhY0kwjiU84GedbcqPj5ErG54CkNtkqBOWyL2VVdnunKyXRe+ahByukBmG7ycWsWboIUjXXdEA4PMSz8G1As3Sk1dxmYMXbyo34XOS7gHhbHJ/1PkO1Js7KmwNhGsX6t45ovv4qbFe9kXrQOe7rWkN7ksXeUP3XM5VOwmXVG0jihkmjR5NC6Jw/1ZNBbEUlisk4QlPHIbkciSOTVmUQ+9y5ewDEyr6cqUAcTUlsaJrFhKh7T2DDnxnB6q6NAvKuTmeErfqhe6ZmhlwPS6RNqDivrvxnrAIiVOxf46Bl1mTQVrxoyymlL1auME4RfdGjOchpZsA1j024i8JDq2yVJW0T7RZv2aNsPFFhvdOe7bkXHj/sP0dbb1WjnFkWKOOzd2c89tB7nsFkPr8MifayxxbjvI8mKoxwMvcGaBimerPvn2D/H8f/2tF+TYT7Y+9jN38zHu5vf+1VtP63lPZg5xyjO0PXv28IlPfIKnPe1pj/r4Jz7xCXbv3n3GJ3JRVOQHDKcEcm3ogUYzWZ6ZTEexnzDHUTMQ+U1EaP3LKcdXB02Lsb4DE0T6Lo4w7ZjJnpTxkrcAzhdgcmXBFQeXGXxgH2pchVwaOQ3BNKahXalxgej5lHtRgR5VmEQy2aFJNg2ysF7rYVywCZbI0vhuTx1pE/JiEOBkjEkEeuL1KJtXd1g4sQlFAXmOaLWCk0xYSZQKEYdrI4MtZhRNgzqDEUFNBRBaN1aaDXhRyr+mNJ26nRGAX3gMCJbUBpyZcshrWlv9/oRyziEGI3RR+gG/nYD04E5YmvBM350yyI0xYnMmZbcxa5hJvt6uLVXnv5xrAPN43ZeTt9vuwpxZzQKSxwMz28Dl9CqfA4cgHjhUbv2Euq5a5zFrFqP86r8fR0wzbtRVLx4Ka4mGFaN9CcUuwfr1jqVnHOO7d93OVfFx5mWG8v1qSie5LFqln2Q8lFpsrALNWCKSuAFTKjPotYTPDfazKxnQ1z4UMhKGEs3YxgxMSipLDJIlvUlK2VgTq6B/KZ2mTe7DJVXBznjIM3Yf5XBnwvJkN/FGh1ZlvR0+TG2kKzN1WpPSj8ORxnVSqrnEGxIUwfSlnDp6CetA+cUvJ4Wnk5XVlK6sFTjZACZgqlENY5aTNO+FqAwu9nEHIi+Qa5bupCRe75AvaoqOJF/s8NlrruLhK+bZ1RkyLBKEcBRGcXR5jvRLLfZ/piRdniBy3zki7G+7Hllfcx67L08EXgB+fPkDvOFxHj8Xbl91/bAdXVAAdTZq1g778XLizsbc4ZQBzNve9jbe9KY38alPfYqXvexlDVg5duwYH/7wh/mt3/qtSz4Hps4DESaI12tv/pAc3JQNzi1FOW1jBzBT83e3TL7rciFIUghcoigWY5afKykWLWroKWTf//xb+NJgD/aoQW9mW+ljxmzpOMiNMfZAx9+4pUAYS7xZIipHNK7QaxPvsNVLwTjUONDjwv5sGmFbupnQO+ltjqXxdstFT1It9dFZjrPWDzKBXiVinyeAkZAmDUCzc22adGjnEFmFKCtElk8F/NAMWI2Qte5cBT4x1nnXtbq09qCrpuqFbZBMwzWlan52UsHIO8GIgSJei4nSsNKYRoims1X611abEtR0AyW3c2Aeo978z/7xeTnOqYKXJ6pnvWr/Oc2BOV0Q832veuyb+u9/8MJ2tB6tK7MNXM6sqq4jHvtQXT0MhiS1ljIsdgHTcaIGK01gstvanXaeouykX4gCmOwU3PCC+3jF0h0sqiEdUaBwpMKQOcVR0+feYon1rOWPa8JQFgACxnqh/OqY3n0JX75+F63dJV2Vk0rDTj1gSQ8Y2JT78iUkjo7MAbCBQlZ3XHy4pKbtNJEwLOgRmY3Yk24SS8Pxa3psHGoTbaboQCOrtSFCewc2l3hr53Jnm+G+hM0rJPlOi40cMpfE6wI9gXjT0TlqSE9kqA1vudwsDhal319Nu1MhviA4S9agJbwRUyBZj7U1da2sfBhoWZHkBclRjYs1ph3Rvz9ltGcn980veSM1C8ka7D9ckaxMUMMZsBJAojh5PrBdAPz2nbfyT5/2onN+nFMBLxdDnanG5vn/YXrPvlgA0CxIqc/vbJ7bKQOYH/mRH2Hnzp28+93v5jd/8zcx4cuolOJ5z3se73vf+3jNa15z1k7sQpWo7Fa7x9reshatGwNJ8kh608mc2roFHkdTOlTs7S9trKi6Mdm8ojhYcHDfCqWVXNlf5cvD3dzxf6/nsqMDv9qUz1DZpJymNOPb6XpiMalCjJ3Xv1hHOiqRo7zR8zgpfNJ8Hl4j4JRfhSu72q9AWYcsZlb7rCOaWPKlFH089pN9Ca60Pj8AvHtXt41tJ2R725Qd335XucXEPlRSZ87nv4wt6XKGWvGaHgHN9auJA03nqn69s0YBgVYx2/Ha4vpmne8M1TWrY7EONx5DUYQukEJMcijLxqYamAIhrcO+twecx6tz1X05E+DyZLov5xrg1PV4wOXRtrmQYGYbtDz5kgUkq45krUIW4V5SVVO75KaTPNUP+icGs5cmG0x5wJF650mkpGpHDC6XjK8teMXSHTwvvT9knhgiYSmcZOQ0kag4UfYYZAnCCOKh866Pk9xTs+puw6Sgf3/Fg/fPszK/zq5kwNjEDGQKFXxmeJCHRgtc1z/O5cmJJvckEoaRTZpOjP9bRUcWjGzMUKVEwtBSJft3zvHwFW36D8XoldA9CYHPLkqwvTab1/VYv0Yyuapgac8KL9xxlI7yYEAKy8PjecZVzEae8uDDiyx8usPinRo9KBBF5dPuncVVfpxDO28KU3dkqqlTppjNYjPT8UJUBheJ6RifF0ELCjKKkEqilyN6X4mwqTdRcALUpEROyiltbaars2Uhcru21LkGL83EfvkDZ22fbsczzqmY/1S7MC/4J980/eUz/+zR/w7c9rsfOWvndqZ1LkDVaZH8X/va1/La176Wsiw5ceIEADt37iSqJ7SXeDkh/I093KyaiWzjJjbjulUPOEI2rX3n3LQFDtMbYFgFcpHCtCKOvahD1QJZwbWXHeM5iw+zXrawTvI3D1xF97ib+tNL0Qx0rqr8BDzoSURliDYL8oWkGfCEAzkuoKz8ClvkswEcgApgBnyopnMNlQwLKvf5K1VbUbXktNHRbSPzYitnO9KYnX1GBzvI0mESQTS0qMIic4NNFDby1DgjBWVHYuMWajEhPTREbgz9YC796pgzdroqVp+jlYhETwM8wYPH2oms3lYqpiYLUxMBoZU3AJi16bQOsTF8xGAitMYJ26x+Cq0R8baQ/7HqYtK+nAp4eSyQcrboX4/XhTkV4PJYz7vQHZntOvNqnRB0D1dE65kPRq5DeJM4aCADZaye4NYajdClFzMuWS7S2DT29C8hKOY0oxtyXvmMO7g6Pk5PFmROEQmLcYJ8RlQ/MRGjcUJyQtE6niHXB1sn9EGLkqxktA/3WL2+TdWV7EwGKByfG13GJ49dRj/NSWTlhftOYhBkNgpOZILM6aAF0WTOYZFEwmCEf3x3e8Dq09YZ3DtP61CC2Bj5MUpKzGKHE8/qsPmNE5554FCj5fEuX35g6MiczX6KdZKRTfjirn386cINHNrVZ+7umPaxkmRZINalHzNnQIOrHdyUbNgKwJSOXLuDgo9FKCtvDuPcNCLAOq+fCWOOUBIVRcgkwqXJ1ASoPu7M+O/nBNsd/QtRP36awOWHPvDE6fKf/InrzhmNDJ64C3MyQHmiesE/+aaLAsSc7TojlXIURezdu/dsn8sFL1FWuHEe7HsFMON4Va/uNyLyGVeweuWmDqucBTAwdU0BEDC4yvDi53+ZQ6M5FtIxlZXcO9jJgc46z9l/iM8vPW2qGymrZtVIhA6Mq7sSZYk+tkExv8t3YcJN2SYRMlhBo4RPm1cK04l8mKT2fGGnJcI6bCRAgEkkqrTIocXJCFE5nBbYboxcmxHta4XZ0WPj2i7SAM7TEmpBPEp4S+ZsahHqpEBYR9mLGF/RJ15PiY5u+NdnA3CoGx5qeqPf0iHRegpelMS3hFzoljhvIiBkCKH0q3BN92Y23boOjhOysXt2ziGSGLujj+kmlF1NFpdw7hfmL7l6KoVYnuvOy5mCl5Ofvw1kLr1K1izRwHldRtB5iJrWNCs6hynVyda5KLPOk/VY4EMrXawp24LnXPUgX9u7mz1qkyiMT6lwGByxsIycZtVpVosOZhgxd8QRrU2mHXxrPYhRCqcVMiuZu9dwZM8u7mqN6evMAxAnWOqMuLy7ys5ogEESYTxVTZZ+8Uu6xq3M4AHG2HrR+tjGTExMZSVzrYy1vsC0I8TQa12qxQ7HXtjGvnSd7z54J7viAZdFq40bWuYifx4IOjInFSVLwLwa07824zNLl3HH9XsZfKHNzs8pOvUYnheNHb/Qs8HLoZybWlpbO82jCZqVLQtnwYm0CZYWFU4pT8Ery4a+VgMXl8S4dkI158cSYYDBEO47d5+37To7Nb5n+MQbce67MI9WpwtcHu25TyUgc1oA5vbbb+eP//iPWVxc5DWveQ07d+5sHtvc3OQtb3kL//2/X8ID7eo6iBAKdjJf1UxX55sKqzOuzj2BKc2ppjrVuSehq+AiSfuwQgrL2678cxSOD2/ewMOr8xwfdNk80WHXw26rm0qgGLgg8Gwm+1pDlhOvZhSLKTZSIEGFPBjwoEJU1oOKwiCso5hPcEpgY4nVAhMLJjs10cgSDwzJ0SFqs8D0YyY7Y2wyFeKjFXa+y2RvByfBKMCBiQV64rNkUAIXSURmUIMcUVtFK0FkHZM9KRvXtJhTgvj+E75LUufLwBRAltWUggfNSpgX+MdTcFkDJ+e8yL/Ws5iwn1qPVNPT4sh3d5QHOyKOMHsWGB/oMDigSTas54qPaw+e7TpfdbZ0L49WdYfkfNDF4MmDl+26tKt9vETmQQtYBht45ceDhu0aOucurP7XXWgxQxt2cdSEKovKQiqa51skbVl50b6wmJmmeuYUK6bL8qRLdELTXg4gCN/xxthp5kqkEaWhd/+Yst3l862D7H7ugAPpGvuSDZbiIbujTRb1kEhURKIiDvSx0mlK57NhFJZYVBROo3CUCDarlNJJCqtp6ZIjuxxVW6MTT4lbv6bF5EVDvveKL7A/WWtoaR4EJUhh6cickY3JXExH5k2g5u5og5fuyLi2d5wPd69jfbSD9HgHtTaC2ijAlV5/UjtgzoIYY7b+riRYn7nm2RZiqk2SAsoQegne3EYpiGOvea2Dr+OIcnefbClmcEDhBCQbjqTc7sA8lepcd2HOla3yU6kbI594E18f+tCHeOELX8jv//7v82//7b/laU97Gh/5yPQiTCYTfud3fuecnOR5rVnesVLTvJGGeqWnjwc6V+NUBtPt6oFhJmnYSUm2GFP2HH/3tzfwnx/+Jo5XPX5ox8f52svuZ/BQn/4XYlTpcLH2qzp2RshZVf7GGrpArqpwZYle3sRGgmxnTNXSlHMJVS+h6nrKwZZOUPjZRhInoWwLTAyqcBRdbzGMlP6Gb0FWMyMi4JKY8WU9bCxINiyt5YpobEk2PH3MtDVVaxo0VlMebKx88GaiiEYGPXEM9yeYnf2ppkaIaXfFOu8Kd3L4lxQhL2ZG8Fr/XFbTkFElg6tcsK6cyZzZonWZ75Fft4fR5V3yvkLlDp15/U803OYsb9eZ1dkGL9tg6NKreGWCGhU+9b3u+obV/UYsHmyARVlNKWPQ0MgoK8RoghhnPgNFS7KlmPEeyYH2OpEw9IRjUUoWJfTC+LNiE+4tdnHL5jUc2phDjwQqC26Y4X7pqckmhGv6Lr8cZnSPlLQe1ty9uZPNKqWtcnZHm8ypEUBDEzMIak/M0ilSWZLKknYAGHNqRCoqcqtZK9qMSn8vrvoGm0hsrMl2pqw823HD3mMNPa3e38CmGAQ2oLrSaTZMi+Wqx7ppN+CpqzKe03mQf3D559m8saRYTHFJjNDK/6spXPVYUodW1oBjyzhb2y57OrhotfyCV3DQFJH29OIQLirSxI81WuHiCDvfZXz1IhtXpQz3+v1HY0e6boiGM2yC7XpK1LnMbfmJf7FVM/Jkui8n19nc14WsU+7A/MIv/AJve9vbeNe73oVzjl/5lV/hu7/7u/mf//N/8m3f9m3n8hzPX1nrIZ11U4pRHawYqFuivmI2cGOlQER+Va3RwIDPMwHPc460bzdLOPZCyb961f/mP3zxZdy3sojdI/lsvo9/sOMzHLuxxz3rlzN/T3BnmW15zyTcizpTBbz+oyhpP7DJ+PI+euRDvWysUFmFyA021T60sbKe6hX0L3pgkaVjrDXJWkVqHCozmHaEk4JsKaZKBckqHowkCdWOLk6DyizRoELmlU9xbqmmixMNTKCkBXpW118LG0tvDR1LouByNtnbobsyQFQSV9lpvoycATMwBSk1oAQ/qBTlNFh01jABpinX9XtZW1ELgYgj7HyP8ZV9yrZEFQ6dWVThg+fitYKSk7pw27VdF7AuNk1M/CvPBsBlhvLtX7jAZ3PxlSgN6JkOcui+1G5YwMzilPATZOemuSez9CZjvItZJyWbU4x3O57deYiOzMkcpAJSoZBISlGw7CRHqzkOT/qMVlvMDUAVnpJcdxdcbX0vxFQnKQTRek77WMT99++iNIqnLxzjytYJElmCo9GllMbTxSJReSrZTKWyJBX+bzuiERtli0RVSOGQY4ksK2yqGVymcYsFFsFK2UEJy5yaYBAoHDLYMxfOD7wKR24jlHS0Rd4AKOMET28d4pqrjrJ6+QGiQYrcqBcbwxhSO182dD07pSDXWhcCbdk53w5T0usjqyrknynQfhFNCP+eoXxm2mR3i+F+xXi3wKQOWTnURKBHYJXA6W1N5cVeFyrE8tHK/s9nXehTOKf1ybd/iP/dPgDADa1nAvCGt5zenOuUAcwdd9zB7/7u7wJe6/FTP/VTHDhwgO/93u/l93//93nBC15wWge+KKu2RiYI8muzK2PDqouc0pZmAhmnlsDOu33B1LIxL6CVQuQtf3d83vErV38L+WZC+nDM/3fwXcjlmO5DgtYJy+UPTNAnht52uF4ZC+dT79NZt8Upy2UGcayibWFysOdX2vA0BJcobKLQG7nPt6mCTkYLpPaW0dHEZ8WIYFMsi4piRws9MjipvJ2zsdDWTPamPtPA+UBMpHcdqzoKq7zzmJN4/YvwYknT0thIIEuHcP5mXrUksoKyKzELPeRDo2BLraaaljja0jlxM6JMoVQDIBsNiy1DEGUwVqgNF0JQWWOF7fy+Jwd72EjQWi5RufF6Hx2CLkclFJNz+Wnbrkep//ENg9OikZ2J+9j5ch17qlUNWLbrFMv5/C2URBRuOj5IMe1qz7qNheeIGuCEHC1R56K0Ekw3JtspsPsn7InWWVID0vD0zBnGruJw1eKOfD8fOn4Dd37xMjoPKubuq0geXIPx9J4mtJ52JqwNgZASNczpP5CQL8QcKneyuS9hsivihi4saq8P8N0PhcKSypLSSsY2IXOaOeVzYyJhfLhjPkdWRZRW0Ysy3w2aGKpexHiPP/nNPOWE7tLXGYkssU7Slt59TOEY29hT0oI5gUEwtglDk4aQzZglMeA5Cw/zh9fvp/dwhD4WNTbN9bX1bpWe0udNFaoti16NtfWj5IsBzbjvwvsjANdKWLmxy4mvrejtXqetDJXxSTxZFjEpNNEDCQu3bQdZnu/69j8Zwt++55we41zmwjwVqwYus1fsi5PPA/Czvwzv+ukbTnlfpwxgkiRhfX19y99e//rXI6Xkta99Lf/+3//7Uz7oxVrOWNB+QiyECK1lO810ibTXnkgRknxrB6yZfQTBoKuq6QpNTRUQEd0HM5L3peAgGvicEpUNvHNYFVbZmhttuKnW1pu19mV28l5rbYxBrqzTUoLRFT3fBQGvz7E0XRiEQ08qZCEp5nTDuS7mNNHQoIfe1lNUDtNWCAtinIMQmLkWamKJNwrUqPCBmEogrUMWmnjo7ZNNS+G0RI8qbKKRxiJLD3ickt7tLBGUbX/wbE+bztGooTYgpAcctfNabZKgpF+NVD6EzJVV87MgvF+hA+ZmeeZ1BR60iCKq3XMUPeUpcvjukKi8lbSwDpmXVMk2Z/lirScbWrkNYk6ttkHLk6iygjrot7FIDnSmmRySLRNsaChMdVaLKCucVthuStXx92w7iPjbwXU8r3M/S/Iwq1awblMGtsUnx1fyibUruPMLl7HwBcn83TnxsZF3yGql0G1PXbhmJ+i10N1YkqNDdn6uR7KiWR/Nc7sTRNJwRUshhQcSQ+MtkqVw2LA41JYF1nnaV+4kx8o+y1mXE+MOSloqK2kfEci8YrI7xilgpBnkMbLrmNNj5pQHWdaJGWMAwdj66UokK398G1E6hQx2mSObsDfeYMf1Kwy/uJPWw+nUBKdmRswuBJblI3SUQghcDRrr+IRII6zFYafzgqry43GaUO7qsvJcy3d8zee4sfMwqSxZrbpsmBYPThaZmIhbq6vIv3LKjP3tOkv1f7+zyxueIP/lbHRdbnvXq7n5PYr3LP+vJ72vuma7EeeC8nWhtDB11+XRqu7EnGqdMoB5znOew0c+8hGe97znbfn7933f9+Gc441vfONpHfhiLKHkdPIMiNCCmbUv9voTsUUbU4eSNTkm0red65V+F2mKfX1Wnp6yea2l85Bkzy0jL3APScTg/ecxNY0q2D/WFs51d6L2q1dBXFjfZJ3DTSaIQyXdyjK+oo+TETaSJCsZNlYIBUIJRGHRzmASP5CqzKImFVVbe8CRV8jSYmNN++Gxt5Zup1SdiGjoaWNOSlwkvZuM852Vsi3IFiXCSlor3hZZVg41rnznpaURhUVlvlVfGwhkOxTthT4sr02BWelAhVVCNwU2Ik2mWhcZVjMD1U+omQHiZF1S/Z5JAXFEvpggK0c0skhjsVqS74yIBhVlXxOniqqcCdLcrvNSj9d9ebKg5eQ6myBm1kL5XOpVLjYa2XadYolghz+7sl/rYGqqbGPNLwDnF7TqCbdWlP2Y4V7N8Iacp19xhF3xJuumzcBp7i8XeajcwfGyz58+fAPLh+bp363Y8bkR0dH1ptsgiP2CUG3zW+tupEBMLE4rRFhISw+DnrQoey3G+2OWsy650SzHPZbiAUp4O+W2zBnbhEU9JBUlhfMgB7wDWW404yKin+bcf/durri3RDjI5iXCgSgEUsBiPKInM2JRIbEMXIvSKQ9gnGRoEiJpyI2mtHUnRhIpg3U+VLOrMr5h7938n71LmE6MHKjpa6yvfU3bmxXni5mFr5M6Yn4bb2LTdGiCI6ZLYjauSJm7fI2leMC8GtOWuf9XdQHYqFpcfuAEhy5bONufqu16nDrV4Mqbf/oXzwqIecNbDC/42Se9m6d0/ewvf/FxH/edmFPvwJzyksAP//APc+jQow/2r3vd63jf+97HS1/60lM+MMDHPvYxvuu7vot9+/YhhOCDH/zglsedc/z8z/88e/fupdVq8fKXv5y77rpryzarq6u84Q1voN/vMz8/zz/9p/+U4fDUbPAeUbXzS3MCoQNwsg4DfAcmUMvqm5ozMxbKQUTutCLfP8fyc1LG+x3xgRHFnHcHc4nyIvvaqcw5XMun2hME+r7NL2aE7cF9a7YDU1PaatB0Yo32Xauo3HrgkITui/OWnsJYz392EA0ros0CF0lsLIM7mXcMizcq9PKmdx7rpJ52lld+H84hSossLSaSqNwQDy2q8Nzf2tls9tqqcYXMKt/hKL1WRk/8tuVie/o6pdcNTQ0RwuurgYicrpY1ZgrqpE5YbXhQ62Bq4WpYAbWRB0/+mjii1cwHcKaKeL3CpJJ84Yxcxs96XXTfk3NUT0QdOxcOZc961f7m33Zd2nWxfU+EtTM6i6m5iFPeRtnrLgyuKHCTzOeP5T7DC/BBu8MRbjLx4ZUtxWi/4LlXP8iLFu/nOemDzKsxAxtThgyWRFREyiAminTVgfCuWMBUqA7TTlA9tlm3daJvLWJSEC2PWPhySfK5Nnd+6nL+/pPX838+90z+4sjT+MpoF4fzeR7Md3Cs7DOyCZmLsHgwkYqCSBiUsCTasLzRZeF2RXJsDJVf4Co7Dtur2NEesSueLlAMrM9FS0XJgh5h8R2gsYkZVt6ieWgSv61Jyax/jQrLwWSVyYES09L+Wuc+tJigRwW882UNXIKzZwNeZgMu658j37kXaYJIYv8vjiHSlD3B/rkNeipDhra/dZJ5Nea69Cj7kzWunVumvDw/o8/RuaiL7btyIets6l7esvS9vGXpe1m66VtodX6SVucnz2g/59IcYLZufs/FxzL5rX9z6p3KU97y1a9+Ne9+97sf8/HXv/71W1zJTqVGoxHPfvaz+U//6T896uP/7t/9O37913+d9773vdx66610Oh1e8YpXkGXTlfE3vOEN3HHHHfzFX/wFf/Inf8LHPvYx3vSmN53WeTQ1q78IJZSculrBVPAXgq9mc0qEkl63EW56ttOi3NVj8/KYbKejdy/o23qkKzDZnfDQt86x9sw5XBxuqkr6lncwBMAYf/Otq9Z01JP1egIvT1pZsg42BsT3HSc9MsTGkmIxxsa+W+OCTkdPKpwUlL2YKlWY1Nsqlz3fVUkeWPUDbKQ9Bc0RxJ9yanhAAGNCoEeGZN2RrlrSVUPnaIke+NU2mVWIidcX2URRdXxHS08s8dBhE+XdyOouSe1IVlcNRuquU3A5q93ZGqE++E5NnXRdA6H6dyl9orX2VqTFnKbqaPLdbf86FDgtqFJJ3r84Wv4X3ffkLNfr/7p3Tu2Tt+uroy6274mTJ3VcZh0uQ5hlo9eDGav3MMYEuqtIEqqdXdav1ojnbnDT4r3sjjZoy5xIVIxsghKWgUmxCKwTyAqSgUFOqub4dQfIaYWLNC6JvGHATOda1C5ceYGY5IhxRvvBTfZ+fMyBvzTs+5ij98WYQ4cXuXN1N59d2c9n1w9wz3AnXx7v4Vg5x8C0yFxE5mIGJqW0ihNH+6S3dNlxh7/W2b42470C9mXs3rfO5d1VAMY2Yd20GduYsY0bCtmcmjT0tK7OiYShr7Pm7wCR8K+1dIpkIaNqK1wrRiTJlKlQU/bqsaVmXdSB1PV7UWfwOBcy08J1qgMvtQrsCoUJ0pZIGG8lLWwwNzB0ZM5uvcF1naM847IjZ/Q5Ohd1sX1XznZ98u0fuiDHfcNbDG94i+H/fmeXj/3M3fyHyW+e9j5OBi/nEmS851On13Q4H/Xlyd+f8rYXdIn5la98Ja985Ssf9THnHO95z3v4uZ/7Of7BP/gHALz//e9n9+7dfPCDH+T7vu/7+NKXvsSf/dmfcdttt/H85z8fgN/4jd/g27/92/nVX/1V9u3bd3on5CwIgtZlGsIYTsjfuAoDwk0pXMIL+0VwHatDJwFML2Ht+harX1/w/Gvu55Pz1yAXcl54+QPceu8V7FnaIFaG7FeXaN2XTwcPJRFGTjsIzgWtTbAMrs+pFrjXXZjaSMAacMJ3jw5lpCspZs8CJtWY1E/YZeG7KDby3YiipxDGkS9oug9N0IdWcUXhBz6tMG3tgy4ThQTE2FDOpVQdhUkEwtBQyWwkiI8XyIl3KFOZQRaV7+60NBjHeEmzcS0sfcZ6h7Qi8IrLYut7UoO1mg5q/GvbAm5qF7JaD1S/l0r561ZVgMG5YMYwzoiGhqrjX7M3HhDN6zCJDFqei8M15qL7njxF67G6MI9HMzv5Odt2xxeuLrrvSRx5x8dCTFPva/oWHkQI50Al/t5flls1KUGz59KYYj5i81kF33Hwbl7Quo+Ri0mF4epoBYOgdCPulbs4UXYZ5zEqE8FopfQLYa0EXOwt/W3QCtb30JOF67X+UghcsLJXWYUwjngDpEnQo4jhziVs7Di8YHHa8anU0J2fcP3O4yzEEyYm4u71nax+bol9n3b07hsghxnVfJvlZ0eYpw95/mUPszMekcgSifOuYk6Sh47KibJHT2UezDhJV+dIHFI42rKgpzIMotn+WDnHStkhX/UmNEiJa6f+5dXmCE1A6Mzi3/SD8khThdmx5iRbf6cEsoTDm31OLHS5KjnmgzbVJrZe4QtD0g39I/zZ6X2CzllddN+Vs1g3//Qv8uXqE6e07bl2HXv+v/5WAJ734/+Mt73tx/jVX/11/kv3e/hhO9qy3See9zk+9Zmbmu1n62IEGRdLXRxLzI9S9913H0ePHuXlL39587e5uTle9KIXccsttwBwyy23MD8/33yBAF7+8pcjpeTWW28942O7opzmkNQ1Y5vsV/7ttCNSO5LNcGydkoz3paw+x/K0y4+QqpJrn3aIG/cf4Yr2Cm4jZu1v9nD/Pbs9DzgvpgLD+kYrFSRJ2KedghQIwkOvuamT55sBKaQP11QElxfIew4R33OU6NgmyUqGLAxWBcMCA63lkt7dQ+Y/dQz90IlpVgp47q/yE/yy7TNeqn5K1VZMFhUmEt5lLHcUXUEVtsuXUoTFHyvV2HZM2Y8p+xHCOqKhoEq9c5ksfUAlUTzNbtHav6Za8zIL0ma7MPX7ZkwwOqhpY4YtGT7O4fICrCNZyXwQZ+wHeuEcKnc4BWVHenHpSYzCi7Eu5PfkbNSl0Hl5NJrZNu3s0qoL8j2pV/tntRfOeY3JaOLv+XnRaFxqm2U3SzsL+6lakuuuOMrze/exTw9YUoNGOL9sOjxULXLvZIlbV65g8MAc6Qm/GANh4j6bhVLTo2Yzy5Rs6G1o1WwrjHfmlJMSNcrRa2O6d22w++/WOPDhEXtuqdj9d4KlWxWLfx9TfWaeT33xSv7yi0/jEx97OpM/38WBvyyYu2OtMapBQDHvuHxpjavaJ1iKB76rIiusk4ytv//POo5tVK3m77XD2VrVZmDS8FIsmYt5OF9gvWwTrSof3FxU02sZwIu/vieNmcHJsqmaXjf7XGO3vpeAyA1z91esPzjPw5MFTKC9zasxi2pIW+akwufjqEe4ylycdamPKRdjferd/4XX7X8Gn3r3f+H5//pbecvS9wIeuNz2rlcj/uE7HhW8nOu8lvMt4j8dh7FTqYuD5P8odfToUQB279695e+7d+9uHjt69Ci7du3a8rjWmsXFxWabR6s8z8lnqFmbm5vTB61rxPyuKP3PZfXIlZqavhTFvuNR3/TDylW1q8/hb4DLn3aUtazF3UeX6HUnSAEPrC8w/wVJ/4ES8SkfeObiyDuQzbjSeApU5OfRVQVm5jxqEMWM0H1msu6c812hWvwvhe+orBSozSHSOeIoamhnzlhEmni+tZDhNXl9jzA2aGiCNbMUnvJlHfHIosce4AjrSNc9t1lYB04gS+/qZRONiyRVS6IKH3yZrhmKnqJsC0Q+k9lSGxfU2qJgkNCAOMX058YmWXhHsvrxuitVu8z4Dwci6I3k+ojWcsRkKca0JNGmNxrQI8h2aNAClV38COaCfU++SuurDbQUP3n7U8KJ7IJ8T8oKIYKzZFk1DpV1Rth08mxp7CCFCPesYAzjHK6dsHGF4qr2Jm2ZkzlFR1QMbMy6jXio3MHd2W4eHC9wdKOHHgn69xtaR8fNOdXU5C0UqceyDJ41EzDGA6GajaAUWE9NE+McvapI24nXcypJ78GI/G5FsgbpiSFyfdQEdLo0hjjyZjGRm3ZSVE5ptadgyYwN027AS1v56zqnvTNZHZgpcZRCYUP3RQrL2MZ0VM7EROiRQA8L77xWd13qWIKqmr4egrOn8+OVA29dDWBqSpmd6ofqazYTk9A6Mmbui33+ZudVvKB/Hx25VesSCQ/M1sv2Y36GLqY6V9+V8zGe3PweBcdObdsLmfniHcZezcXB8Ti/dUPrmY1t8pOtixbAnMv65V/+Zd75znc++oPNar3d8jdn7NSlrOHPKk95UspbMoaQSdotxnsTrrzhCM9ZeJg/u//p8ECbUdEGJ2gfdXSOW3Rm0Os5Mi/9SldlPO0rTaAKE/dasB/oBM3gMmsx7GyTVVOfu1BySzCXiKNpngqAVLhW4h3GQgfHjceNoLF2OxMhqEtlhmjow7hMWyMqLxCNBgZZOcquYrKkaZ0w2CiAKAG4AF6k18nYyGetRGNP1xPWoQqQwVK6AS218xsByDVtfNOslAlRd8mmTjpN8GjdPRN6OuhUFQ7PEhTGotcmJNqLY20iiTa8XiddhaKvKdPT+lg95epxvyfbdUFq24Hs4qvH/Z5UxoOXqvKLQky7G8DUZj8vfJ4Y+PtUUQcVS8r5lMluRyQsd2d7KJ3GOMGJqs+hfJ57hkvcu7bIZJxgTiT0jwrah8bI9dH0HMB3WMJ9sXG8rPWGtXumOanTAKH7bRE1yasyXiMTxiKV5U04pD6haGuFmOQwnngzleAeKfIy0OZA5YJhGYfAy4oN60FLLks2qhZSOJSwjE1CT2W0pTcEyJxmHMT74HUnbVmwWnXIrfb6HxzJGt7+v3btrDvyMHXxnDV+mdW9zgK5xjkugCChGyDkrA8GlZOS7lHD8P4On7v6Mi6LV+iIgsxFFE5RoiicYqP66h5QLqrxZPc7LvQZfNXWG95i+NlfPjv7umgpZHv27AHg2LGtcPrYsWPNY3v27OH48eNbHq+qitXV1WabR6uf/umfZmNjo/n30EMP+Qesm2aRQDOBbgYTmE7uIbhlxVOL3pralBfE6xVr4xbLRRf36Tl23WbZ/QnD3r8r6N/v+cSitMjhxK8SFaV3fqlvtmGVzmUzqzlFuVW0DmFFLHQojAm6FTl9LTUgq2lY9T9nEcMxbjQOr6nW09hp16LuXFQGtZH5JGHrr5ONJVUqMS0v/BcGevdnRIMSE/uATFlabKIwifJGAnOaKhFEQ4seG0wsERY6R0rEaNK8B3UOz6x9ckMXq9OjYQpYZmkAoZt0svtYbVVaC/mxFjmYoAdec2NiSbEQ4wRE6xnpakE0uvhb/hfke3KB6mzbKG/XqVXxk7df6FN40nVBvidCIMKiVH0/cnVgZGWmK/paTV0WT6YKK+8IKRws510eyBa965aL2TB+fFnPW6RRhTWC9Liie8igBhliOPb31XJ2/AoT8VpvWd8jG6qufWR3pp7EW+uDIQPYqsMcKcomABpAjLOwjV9AE3rqtCnyApUZVCYw1gvdAVJZYhGcKLtsVi2GJiGzEZuVdxjLbEQWnNbq5wAYJ8mcbv62Wnb4m/uvYu7+EjEYTSl6tQVysyinpmOpme4PwJlAM2vGQ+Md4QLQJIRfNo6jQLxR0X1IcPvKPlaqLgU+uyZzEStVl4FtUdhLY734XH1Xzst4cuzUANLN12yc/WOfg7oQOS2XUp02gDHG8Nu//du8/vWv5+Uvfznf/M3fvOXf2aorr7ySPXv28OEPf7j52+bmJrfeeis33XQTADfddBPr6+t86lOfarb5q7/6K6y1vOhFL3rMfSdJQr/f3/IP2MKBrSfBrvSdgGmw5YywfxZIwBZwE69llB/fwd988To6hx3R0JCs5KjC+vT5RKKCK9fszd8Zi8tyDyxqDUcNamr9B0zDNoMux5UVzhiEUh7EwFSsCH6bLe5mhaeLzfjhizSd3sxdsHI2FpdlyAAwsh2KfEEz2j0NwXRKMNnhhf42gBKT+q6GSSXFvGa4Pyab98GRNhZNB0c4SI4Np9fTmK3anmBS4IzF1faikX5EN8wZ6zUwsDUPRs5cu7BPV4UJRFEi8wqTCKz2LI5iIW6CPHV28QOYC/E9uRB1qYCX7Q7JxVkX7HtS37vdSeOGPenecpK2kcjTrai8zX16XPDlo7s4MpkjlX68WC56HBv7Y+3qDJGHU+bvsnQeGiPGme9+lOVWp0xjG0qXpz3P6AhnnR8bZ7QZsFN6NkCjIQlVT/aFsZ4uV5R+0a+2jq47TkUJmdfRxGswyr0wXwrLrmiTrsroqpw9yQb7kzXm1AQdDFq8u5psfk5l2Yj7xyYhkhWRNBwezRF/pkt6ZOztqQPYwNrGQh8h/M+zeTDupH+zBgf1olh47fUiZ6NVqgx6VNI7VHH4yALHqjnGNsE4iUUytgkbVZv1rPWYn6GLqc7Vd+W8jCen0lnZ/Q7+73d2z/6xL7F6KoCj014S+Jf/8l/yvve9j+/4ju/gxhtv3Br6dJo1HA65++67m9/vu+8+PvvZz7K4uMjBgwd5y1vewi/+4i9y7bXXcuWVV/L2t7+dffv28apXvQqApz/96Xzbt30bP/RDP8R73/teyrLkR3/0R/m+7/u+J+WC0dygzEyCr1KIWZcr9Ujs11C4ALU6ZM+tMYd1i7VnWAZXxKQnYvTEMbxM0L/PeWvhGW5yMzDU3Y+qaoSdW7Qv4ClS1vlzEnJLOv1UpCmn3QzrtnQuxCz7stbNlDNhmQBR4GNrDWVFvF4y3KupUm9BHA0tqrBkOyJU4Sg7imgEeuzb9pOdCmF9YGWVQjR26Ny7fo32JTgF3UM5Yn3g6RO1c1it36nfhzqLp6aS2UCNc9X0NVnrrwFMO0fGeHZZpIOLG2HgVX6fUoJxJGsV2c6IqiVQuaPqRH7V86SVuQtVF+v3ZLvOb22Do8evi+17IsrSaxvb6bQjYYxfaIoiD1DqFf56xR/C/VziKj9Zlusjeg91OL63zdFuj+UdPUqrGVYxSnoNx3rWonVM0LtviD6+4Tv3tRFMnTkDU+A001XZEqRZLxrNWgrDlFYmJQJwoVPuJFNgUAOjOmOltt8K1s2iybepaB+3HF1pc/ygdxmLZY4KrimRMMypCWuu4zd3ip7KvD2yLCmNoqsyNqo2kTBYBF8Z7WFUxXzl7r1cdmeFHGX+tdeLirOW1gTwMVt1gHStq2zeRBEMECy40P2PPe1PQNPNF7nxuWbHYj4/2M+1yTHm5RglJqzLNqksqdwj5wwXqi6278rZqje8xXDze97xuJ2Y2YT77bow9a6fvuExQy2vb33tKe/ntAHM7//+7/OBD3yAb//2bz/dpz6iPvnJT/JN3zR1WfiJn/gJAN74xjfyvve9j5/6qZ9iNBrxpje9ifX1db7u676OP/uzPyNNp1zSm2++mR/90R/lZS97GVJKvud7vodf//Vff9LnBvigqnpQqbUVsHVAELUjmRe3110RYS3xQ2vs/TvB8a9JGVxbUfYlaiKo5gydW2xo78+sxjVCwRlaVDi2M3Y6WQ+0seZGWw8Wzk5zBSLtb7AznZnm/Guq2+yNuhFpPspNNvCk9bEN+h1N0VOowqEKi8wNVkUe0AymJgNevK88eGlBuuqF/lb77JdsXtJatUSHN7y4NYmbbpI/v3Au9esWcqrhaTQws4BMNY+JxkJZTylzIqyW1a8dIIk9h7kwqFxRpd5SOl+MqFKBKS6OG93F/j15MvU/vmHwhE5kl0r35alcl4KY/6L7nhQlgjI4WqlAZ/LjiFPK6x6DlqIRlofQyYaehUVMcvpfGVD0+yz35vmb7rXsTgck0nBNb5mWKvmTe5/B4v0G/dAydtN/X4RS0PL3QFeWW+izSBlAhb/XOq2CxbLbCl6kmNo/zwAAUWegWel5HHarQ5cQAkfocLTSaQ5LWKBqHytJH0r4/BX72LlriBSWJHSW5tSYSFS0ZYSMLG1ZoLBEwlA6RaQNuY2wCO/sFbo4DwwWWPiMpvPAhgdLSuIMzTWdnrzwAaNC4KQ3Jdgy3s5mkc2CODEDgmQYjyrjNZWlIdrI6T0Qc8eJPXzDfJf5eIwJoCWzESujzpl9js5BXXTflbNYb3iL4aW/9D7+2eAHLvSpnJV6y/M+dtatlJ8K3RcA4bZ4Bz5x7du3j49+9KNcd9115+qcznttbm4yNzfHy+b/CVq3pknIs/SjujMxOwGut6kn2DWAcc53Y4QArXBJTLnUpepoNq7yk/3dHzvhucJF2dwM/QpdWL2qV4/qToyru0J2y8S9/t0Z48X/ZTWd4Cs5pWHVBgOhSyPi+JHi//r1nPw6lWx4w26uS7avh9MSPfSuaZPdMXpiiTZKqo7GpF4fM9khsTF0D1tk5XDC2xZLA8I4+l9YQWwOp3xj2LoCVruh1SuEs7/PXo+6M1O/X5He4ubW7HsmALThQScxttci390hn1PEm4ZiTpP3BW6c8dmbf5aNjY0LSp+6WKr+npyreiwgcykCmLOdB3MxdF8eC8C4zFC+/Qvb35NQ9ffk5Zf/CFrMaBknIQQwjqZd4lp/CH78iKKtk+bQOXC9Ntn+PhtXxYz3CvJdhnT3iN1zA4Z5An+wg52fWkMcOj7VTUrZ5JM197s6A0Yr3x2qGQD1vbF26wqLR4QxYwulaua+2qTXQ7OPWc2oUNLrOYXATTLfrUkTzGKXjet6HP1Gw/XXHuby7irz0YRFPeJAvIpxgg3TwSBIhd9fT2VkNmJgU3IbMbYxh7N5NsqUBzcXGP3VLvb+3YjowRNTepjWuN6M+1dNc6ujCpwLlOJqa56a1v5ca+OcQKduNJhCNKYLIo5wnRZEmtFVcxz+esULXnIn37rjDgbG2z8PTMrvf/rp3PeDv7T9PQl1rscTqF3Jpt2YC+k89mTqbNopX0zg5dG6MFeIG/mh/9ee0vfktDswb33rW/m1X/s1/uN//I9Pij52UZbSiG4Hu7reTP4bUX1DW3JTalHofIgo8jezosTVdKyi9BP/KEIYS/xQTmwsrftSP4EeZ4240uX51F1s1gUtdHZQEpcHUFXflJ1DWH/zbBxWjNkCXrbwma31ydAmaEaKYtqtqZ9nLSJQ05xzU5KZc7gsa+wl4yRieFUXG8WoiQEHTgjKfkTZkeRzEpMK9NjBxLuRWS0wEVSpoLVm6X1pFdY3PWnAmOkAW5e1/poGENhck1lL6zqUbTaArQZgs12qGozVvys1fW/LClF4nrlVCaYlEdYhK1Ffqu06TzULVGowcymCF/CA42yBmIsBvMCl0YW5mMophVPaC99PnuxLMe261B1jmE6S68nzjAlLcnzEQuWYv0dgYslob4/lXX3m7rXMffoorG/6++Ms9TkApfp+7gJAETp0gAJFygUKmXBiyipo9jOThzLbldAhiLN+bbPi//o11ff0WvwerPvlpKR/zwgbdflKcYD+czN2RCOksB6w1C/baSJRkcqSsU38P5OQypKuyrBOcM/aDqoP72TvbWOioxtTSvbiHMWuLpOlCOHASUG8UZEeHfl8mKDtEaXCZfhxb8b9Mly46WsV3njBzYI4oAmbBpITOTtub3HL4tUsPnvMvmQdJSx743X279jgvrPz0dquUyxPF/s5bn6PuqSpY7f97kdwf/hOXvi/P3qhT+Wc15cnfw+88JS2PW0A8/GPf5yPfOQj/Omf/inPeMYziKKt7dk//MM/PN1dXjxVltgTq/7n2Uk/9Z/EVDwO0y5ArV2p81jqbk2tXwliShFFiM1h83gtqG+oTZIp6JBh/6WbrvrUbfigYXHGTnnFbureVQvgRZP6HKpefauBCzTnILTGge/OKOV/r22aVVgxlAqXZajja7RbmvG+lLIdIY3DpAJZEQYKUBNHPLBIE8BLDLKE+Xty4kPr3iGmfk1a41oJrtvCtCOfMVM5ZF4hSotaG+Bql7LaHjlQMUSgiTV6JTN1ZEMpXBEMCuquTj04Sa85EtYixhnKOhLrKBZTip3eiCAaX/wi/qdqXarAZbbOBoh5NPDyL4r3Peq2vxn/wJM61qnUNog59RLGIGzVLFSJOPIAoyhB1Z12ATLeSueFLV0SwIOLSUG87HBa4rSkfX8wazEW1ja2uDA2i08hz0vMiteF86BFerdIFyjRW8aS2Un6bKhxoKBt0ZDUC0cNPU1A5Wa0J3raSTIWRhNEZdBZwcKXALrc1r2C4irN1d1lxiZhTo995ouoWNJTfQx4Tcxa0WZiYj7+wFW0/rbL0ucy9PoE201xi10me9oce4GmuCJjYXGN0iiqSpGNY1p3LtA+4ugcrYiGFWpYIMe5DxadZDM5MeGAtWXy7ELZrAuoEAhjfTC0gPZyRe9LMR+eu46XXn43fe3NBk5cRBSyr7a6lMFLXeIfvuNJdWIer/PyjXvf9oi/ffTIr57xsU61Hk0Lk3/3d8NjS5i21GkDmPn5eV796lef7tMuiXLG+Mm6nTpaAY2mBJi5Wc90BWonk1gBM+CFGiDUmgwfjomxfjCbtWf2B5p2G2DLfprwRlm7ofluSW04sGXVKAjam5WiQB/b0p2BqeC/pr1Fesuxmy5ULXAsvUWzqyqi+47R35hjcN08RU+iJ/48TCxQBeAg70uisUM4aB+vSA4PkRtDP6AL36a3iz2q+RSTKKq2xAmByi1lR1K1UsoOtJe7tI7mRCsj37mqDG48mV5/KRBqZhJQt/1ng+Lq61O/lnoQCoOSyAvUBiQOnEx9Xs02gNmuJ1lnCmJOB7g82uPnEsxsg5hTLGPBlt4cBZrFJ1eUHmAoD06EDuPGLJUraFSa3Jba/tg5RGn8Qs04mxqdzFKHI+3Hl7Do1Cx+hf2eXKLWXtb3y9m8lABWmsn7yd3uOkS4HrushKKY6hjrkrJZFMMFTY5zqBObLH62RGfzfOlZV3Hi+R2unV+mpztEwrA/WSdzEeumzYmqx4myS2UVX97cxd337mHp45qFLw1QwxynJfmeLsvPjpk8d8wLL7+LG3uHSWXJsbJPWxaMbcxDVy/wpRO7eeBIn9ahFnP3JLSPpsSrE6SUMMm8E2gdjlx3mYK5wjRsOVCRpcQlEbYdk+9IsFrQOWzZ/EyPDxdP48o9J5A4xvdv08a268nVbb/7EW5+jzptTcxjgZdHAy4nP/ZD/+rd5xQAngxifuN5jx0afHKdtgbmqVg1F/Obe29AO+0n/2H1aAu/t75hx1G4YWt/I06TKad2lsYl5fTmX7uZzA4ONf921i2msTE+aUAJx26skuv/a8HkLG1gtuqVspM6SW72OGFwq2lnNZ1sy+s/WQ9kHaLbwaUxtt+i6iWNSF8Yh8oMsrKotbFf2ZtkU7vNNAUlqfYuMDrQwkReF6Nyi55Y1LhCWEfZi6g6ijp9UpaOaFihN3PU6tDvs6pwedGcf9N5kmKrnqamkM3ym+sVwzpMLtK4JMb2UvIdKaNOxaf+4Oe2Ocuhzgdn+alcTwRkHo8q9kTg5bHqXAKZGsRsa2C2VqOBueJH0UVwd6yH2XCfb+4/J+vzomlYsdNTC+Ja8A9Mx5J6gUpKvxgWOv1Y58ekWaOZupNT03LjyAv3q5lxoNZjQpN1AkwXyeqFL7N1YUfUjmb1IlFZTp8TR8251uf2iOcphV3ske3tcuz5MZNrchZ3DujEJbvaA6RwjKuYtazF4cOLRMci5r4CnWMVyYnMW+F3E9avbXHi+ZaD1x3j5Xvu5EC8SlvmZNa/9pqOVv98rJzjztFubn3wCvTtXXZ8saL98Bi5MYbNYfMeuarumsnpWCkERBGu38H0EvIdCUVPkS14h8540zu0jfZKRpdZWChIPg1feffPbH9PQm2PJ0+unqgbc7odl1Opc9mVufk9/rtVg6VzooGpa3l5mS9/+csAXH/99SwtLZ3pri6estavhtWuVlsm7f7mJaIIu9hjsq+HjUKeiYRoWCFzgxwWiDLYI9fe83j+rajMdICynlomWq2pXXJtXxnK5cVWO0ppfacBppbBdViY8tbAW3Qk4Ae/me7M7Crd7MC0JcBTCI8ZZuhyLs/9YFSXFLjhCMZj5OaQpAZp9euo+dIncYVFoBwWl+2g7EXI0mt50uN+BU2PfKCnUxI9qnBS4JTAJAITC9ycppjTRHMp0Zqns00tQh1Cy2mHzJrgkuN/F5H0HGwlPWVNqUbEKurcAmOQG2MS5ygvItvL7br060y1LGcKXmafe6ZA5uROy2yo5XYn5gnKOVB6apEcEuldtxW0f9Z3LYTAtuMGkIhap6j8PVWUBirbmMu4NMKmEaK0COewaejSGIcoKpyWmFaErGwzHqG8zbGQoQNSd9tnQU59v67BiA2ZWcE4xREo0nXQcRO2OZ3Y15pEEYIrmzImdIICdbnO4xLelllujGiNcw5s9ik+HZMtLjLqCO5c2IsqPP1YFo7LH66I18aoUd5cp2q+xbHnt8lePORbrryLl859hZ6cYJEhRDJF4YhEhQoam77KWNKb7IvXONha4+MLV3Oov5elz3Tp3+1QZeWvQzkj8A+aVrTCtRLKHR02rmkxvEww2V8hO7k3yywkrXsT2kcc3cOWZE1Q9lP0scm5+qRt11dhnakY/0zBS/3cJwNiPvCdt2z5/TV/clPz85l0eU4bwIxGI9785jfz/ve/HxtW95VSfP/3fz+/8Ru/QbvdfoI9XLwlIh1u3A7kzMp9HMFcj3J3n8numKIjvc6j8JNvpyCfU1gl0HmbeMMPNNGwCon1ygOc0iAqC8bhIj8AVO0I4RwmlsjSoSYVen2MGE686LKqvO98nWlS1yy9rHYj09oDpFrobh2uzoeZXREr64Rk3azqiVq/EzoXou5gGA+6RCvdmhcw6wzGVHxad3yEELii8AYHszQ3rTG75sh3xsjCUbUkqnDYWOG0gFEYiPMSpCBZyzGpJhoBzgdkmkSQL2jKfodOaZAr1psSxNHUSaamh0kQrZYfcHb2KPu+q+OkB5VOgqwc0cCQrObIzQlYixwXpF/1vcntutD1ZMDLyfs5FRDzRICkfrwGMsVP3k70r2980uf3lKwakMiZDkWkcZGiWmgx3hUz2Rm0KNYRDUHn/l4UjSuweP28DItWYbHMCYFJFbKwyNLitMBGPhwZPHW36Hkqb7LZQo9ss8gWLY8Qk7yhozXZLfV9HbYAmYYiFZgEzomtjIFZ22UpvGPLjNtj7WZWO3Y1z2nc1yzOeSAmihIN6GVo1xqgSOG0bMZNUdO1A/AznZjl57SR37zKK/bfw4t693JZtMLApqxXnnZ2vOiRyIquyolkxZyaYILApS1zDiYrfOuegk+/ZMhnkmuIN9u0J4HqXYVFtzTFtRJMr022r83ysyLG1xQ84+r7eX5njZ7OSGVJJAwbVYtPHjjI/ffsZv7zmtaKJR461IkZLdF2nXadvEK/XadfTwa8zO7jVEHMyYDlsR6fBTKnU6cNYH7iJ36Cv/7rv+aP//iPeclLXgJ4Yf+P/diP8da3vpX//J//8xmdyEVRUvnJfaS98LDWjizOsXHjImVboDNHNPGrZHpsg2WwwEY+rDFblMTdyAOcPEJYR9UWqEyjQrfBCUB4vUgtoswXfF6KkwnRsMOOL+YkD6wiJvm0szLb3XBi6t7lgpVwLfIHP4lXBCAiEKJeTXNbgA8qmto0z5oTWOcbPzWXelbIWYd5zWbjgO+A1N0cXetsSk/ZCu4zdqHLZG8HJwV6XKFy66/lsMCkGpNqSBR6M0MOC2w39l0ZoOpGWC2QhUNlFhtJxlf26eQFYuCNCxrw4pw/bppgdvYZXtHFaoFToCeOaGhxCnAewOTzmslOTTRp0zqaoU8MUSeG5/Tj9lSrb33N4dPa/kMfOLPAs0c7zpnu62KuswVeTrVOp5sS/8qzGxBTvv0L5+qULv2SMoAWje22MN2Y9WtSVp/taB0csHduk0ga1rIWq5sdirWU1sMRreM6hADXnRhPoRW1w38FwoI0YUyRUHQFVUtQdWB8ZYnqlJh1b2GsB4rugxE7b4fomB9DRGX8wo91wc1yKzWsCftNE88eCA6cDqgDgUUNfKqpnrK2sXdBzykGI8hzz2xIU58P0xzEggGnPFNA1I6atT6002qsoJvAT+1BjVOK0cE2w5eMeeOVn2WnHhCJisPlApu2RR6oY13tbaUjWdGWBbGoGNkEhaUUitIp2irnBfMPMHx2wtF7Lydeb6E3QsdEa1w7xc61GVzR5vDLHC9/7u08vXOERe3HiMxGtGVOLAybUYude4Z8qjXkNq7G3qnpHrZEg+Jsf7qe8nVf9eVH/u1Hpz//3X+84TEBzeM5j938HsWLf/TRgxSv1Nef/oleAnU2wMvsvp4IxDwReDl52zMBMacNYP7gD/6A//W//hff+I3f2Pzt27/922m1WrzmNa+5tAEMTLUSyq8+uX6H8ZVzmMh3XNLVCqsEZU+BxFObEoGsvPUuQNkRtJctsvQ36nhkwUG2oJCl8wJxDSoHVYKJ/d/qLkMxByeembBkF0juO+EHkVr8CIEeFbpEUkxpUvXKWXD2mgZ0zYj36+0grIC5KXCpNTi1CL7en5nJxampA/VK2GzVmh4pcKVt6GKu5nT3O0z2e3vcdKVAFNavrlnvrKNGJdV8AghMN0GNSw/whDfOEZVDjw2y9MetOoJsQRHvmyO+J0cQKBal8dS8SFMt9dm8poMwEA+Mnwjk/vl6NF291GNLUliyBc36dW3mhYAj2dn8ZD2l63TBy5k+56ulzgV4ebwuzJlQwWZBzHY9spzWOB2DVthuyuhAm5UbFfK5G3zHwa9wVWuZVPhV+8xFnCh7HCv6HH76HBtFihQOYyWVleSVZmOYghMI6VDKUpUKU0nfKJ8oEBC1S3bMD3ne/DLz0YRBldLTGcfzHrftvRyVpSw4hxqV3nmrNpk5WQorgjC/1gm60HHXyo9HM5bJtVmMgOn2QviQzLriKDAEIoSowEmcsI1GUUg57QLNUNiEDWNe7dgZzqlaaLF+dcqJryt5+dV3cWWyjHGCsU0onGZsY6yTtGVBWxYMTIp1EoUlsxGZ82OTdZLMRqEzM+ablr7Ce79mD90jKW0p0IH2Xe5ss3ZdyupLCv7hMz/DDe3DDR1t3bQpnSZzjrEVtGXO3qjg6xcKes/J+eSeyxh+dAF14qRAze16zHo04PJo9eIf/eIWQPOI/TzOY4937KcaiDmb4KWuxwOIpwNeZp9zuiDmtAHMeDxm9+7dj/j7rl27GI/Hp7u7i6usAR1P2+NaUS120GND6qBq+Xa/NI5oZJrMF1k6nBLecctAMVd3QaBKBMmGI1krQMSICmRpmSzpqX2lEbSOO3TuyOYF6YpvsAwOJEQrbeTa0HcyTrJvboAGTIFKkxtw0mqPCk43MKUAmHLqrlbvQ8gpMNniIlO7z5jQQmKrUL7JsWEKkGqLyUhj+20mB7pkCwqdOUyhcC1N1ZJEI9McXzhQmR+obOyzCoSUOAGyNKisYrKnRdWSjHZL4k3HeFdMtNxBjCa4LG+6PdXuOYYH2yQbBmFokqalcVQtRTQsEZmj7MVERYWoLLolyRYUJ57VopMuwj1n8kHarvNd3/qaw0+ZLsy57Lw8Goh5MjqWbRDz2OXaCU7E2G5M2Y9Zu06RvmCF77r8C1yXHmVejYgwWCQSy/5ojahTwYJ/vsIhscTCcNz0WK76RMKgsBgk82pEZiMsknXTJhL+PpqKklSWKCypLOnJCeumw/XdY/z/lr+edD2hfdjTmGWkEXmByIopQJjVLloLdfO9fqzWQpbBNKAowVmc8CBEkExNBoIuUtTsgNAZx3qrZ+dmMm+sC2OwwqXxdDHOOZ/XVRnfyWrHnLixRfXydb738i9xMPHBl5mLsU5gkF7zEl575mIMgrFJ2DBtpLDkNqItCzIboYTFOolBIoVl3941Nq7ag55EyHEKWrJ5MGXlxQWvfMYdXNs6Run8WFqgmudtmBY26CZTWdKWOV/Tf4DdySa/9+wXIDa2Acx2nf+6+T2K3/q3Z3+/v/Vvfxx4ZBfm5vco+Muzf7xHq9MGMDfddBPveMc7eP/730+apgBMJhPe+c53ctNNZ8Zju6hKCC+uTxNcHFHMRUSDimhQIawOwn3fDXCx77xYJYjGvuMSjUBWkrItEDbkn1QSVWj00FD2NTZWRCOHcBYTS+Kh9fu1jmjkM0iEhbItcEnU3MgbDnIYMPysXvmNYSY5mS3idazZ6n4TcmKIIz9AVFWgz+Vb7aJnQYlUM7xlN7UinhXmmJk8nGC3LLTGaUWxo81kh0blfmAcHIhQuQvuY/46Al54WhhsJJv3w6SeWiCzEqx3Kyt6EoTnjJcdyfiKOTpfzKZBn+2Uye7Uu5pllqqtPPgsnWfLmWBHaiEaFJi2xia+Q5auO7IFwfDAGXtcbNd2nVGdb9rY2ajoX9+4TSN7tLJABCbVjJc04wOGb9x7P1cmy/TkVNBtvIydtshJZUk8c0/1gMXRljn79RqRMAxsSuk0i2qIwjWT6XpfI5twtJqjJGJejBv3raenh1F7JxTdNm0hfM5WXngDk9qNcVYHU5u/BKczF0eeDjezsCWM85qaopy6jG0JF7aP6oSJMX57qcJ4ZafHrYzvDNXdIRHGPCFwcwkb13YovnmD77/mNi6PTyCFZWwTchthEETC0FOTBuyVztKWBQoXrjUo6RjbGOMkqSybAM2hS3nujkP8zYsTNkYL6HGCVYKNawQvuf4eXtK/i8xGbJh2c939cyvGJqGtPF2tdj6zTrIQjbjpunv5280DT+LDtF3ns54qXZhv3Pu2cwJeZvd/MpUs+suPn/H+TrcLc9oztF/7tV/jFa94BQcOHODZz/Yrd7fffjtpmvLnf/7np7u7i6/qFSKlPGc5keC0p4vF0gOWWOCkJFkrSVZ8J0Y4/1yfaByRz0miiac/OQnDvT7wEXwafbLpucsq9+AFB9m8707ozHqthxFNs0PUIWC10N7KadhWLap31rvVRDFNEKYUiDhteMl+QHGINAwmwW3F5UEEX+/LGJCzeSo1HS1UVfnQy0hPtTmz1xCLkJHnDs93yBc0TvrX7qQIr9M1r1+PjR8YjfM6GOeQ4XDFvAeRTkSYtqbo+4EjXfXUPBPD4ICmfU/sg8iiCLPQwSlBeiL3ulIBNpaeoteTJGuBbhaAkgn/y8pf/2RdUm7HwJxSbVPBzk5dCPCy7SJ27kqUFUJEiMpSdgXRrjFXtZaJhGFsEyJhMKIicxEdmQOezmSFxCBQODIXefcsHKmoaIsKJE0qvRSW0ilKp5tuzdglDGyLsY0pnB/i+wEwSWVRhV8MkoOJt6KvgzZD59rVzpVBKI+xuDSm2tmlmI/J55VfoDNei5MMDPFGRXxsiBiMQ9emmjqZ1cYuSvl9Ouedb+p8HHiEAydONQGS9bm5bovJgS7HbnL8f679JDe2Hmped6rKLZbJSrimU1UL9qWwlDYiEoYSgcQhZ7pWkaiQwnJZusrX74cPLz0PkyjyeUV1zYTnz93vTzW8T0pYjJN+f06RypJUVETCEImK0mkMkp7IuLF3mHsPtHn4nHzSnlp1qvSx7Xr8Ohe0sSeqM6GOnVzve8Vf8gN//vJT2va0AcyNN97IXXfdxc0338ydd94JwOte9zre8IY30Gq1Tnd3F1fNTtCVxLYjnPJCSSu9ANwoQTYvsRqigUBlPjHeJhqZV7hIEQ0FwnhXLVE5qrZEOC8el5VDGK/7qFKBa/ufZWjTWw15z/OZhXWIciZsUSucnVn9qsMpLcHKMgrC/iD4VxI73yXf2aboa6pUNLQ2WfkxQlaOdM3Q/vIJbxhQlL6jU2tohAAX7IhnHciERMTxzPWqbTQ9PU0ksT/+XJvx/hZ5X6JzR5V4qp2JBeCoUknRldgoXEstiIYVJlUI553CoqGndwnrDQ9MAHyyBBtBa9WS9yUu0cjgfJPtannwqAVq5LU0tlIU85p8ThIPJKYdI3N/4aVxjctP0VONQHa7vjrql37hXzzmYz/zC795zo9/KXZetusJSvqFLoCyK9g5N6SrsmaSDZ5q5CvneNUjDhPqetKtsL6jICeksiRz2lPLhGXVdBsxeuYijJN0ZE4ROgNzahLS7EtGNvFA53CH1okKOQnHVQFIGAu6zgBzjfuka6eUi23G+1JWbhRU10xYnFtnLsnJKs04j1kZtnDLCQt37KC9PE/r8AQ19F0ZURmfcD/b2ZF+8c1bEtcBw6YBTwAzUAYA10oYXzXPQy9T3PDMB9gXr7FSdVHCMbIJqSjoqwwbaNYGyab18xEP8Pw1yWyEVJbSapSwSOGvr0EyCML/0ik6QfjvhGdC9HtjImFYrbpeX0NYmcQDI+s8jUwKD5pS4bBYrJWU+ONvjyZfPfVo4OH5H/0ffPIbX39eEu7PJ3h5PC3Mua4z4si0221+6Id+6Gyfy4UvrX1LGxow48R0Qqsn1oOFOYlTgqqrULlFhm1trBHGU6DiwlB1I5yAdKUkXfX2lyqraFUWm2hsJCnm/VvgAyB9h0JP/AS/e6xCbYyalnwdBFkbDThntjiPCSG8bbLWuF6b7ECf0e6IsgNqRhKT7RToIajSAYLhHs14aQ/9B3KSu441wZBN1cL9JoztZJ70jL2yFM22Lo5wUmCVD/cqO/480zVvhKAK32lyEvTYIguLTSQ2lhR9jYol0dADjGIhDqAHpIFoZCi6qvYnQBj8a48iT3UQULWE76yEnISypxsLbBsJyq4mwoMcJwW25QfWZK0iX9TIYnvIuVTqTPUvjwdcZrc5HyBmu55iJSVoiYskTkEvzomDjVhb5n6F3gn6KsM4SeZiBlah8F0Hr+WwDcgpUU2eSb3Kr4h8l8FJVKASx8Iwr7weNRIV1klWTJePrFzP4u2C9NAAMZpMxfth8cnlhV94ioOLWCvBdBM2rm6x8i0Zr3r67Tyz8zAynJ9FMrIJQ5Pymc3L+MTiFWwcTth9W5vOQ6AGDnJ/7s45KEtvg1xTyWpNzUyJ2d+lbMIki31zHLlJ89wX3MU3LN7VgLJY5NPrNaM/MU5iwr6sS0hlydh6ipd1kkhWDRAEyG1EEp63VrbpqpwqrRkOkJe6AUJjGzddl5oyVjoVOmuxt2l2nspnEKxVHVaKLqXZpiRfKnWm9LHHAw6f/MbXN9ucDxBzvuqxtDDno07pG/VHf/RHvPKVrySKIv7oj/7ocbf97u/+7rNyYhekhPA2wMFxRRYhIyVkvcjSocYV3aMwWdRYJciWYpJVH7aoMoNJI5zwnQ4bCbBgEp/xIpyjamtUbjGJB0G1U5lVUPRlsMv02o7kxGSL+0rdcfFBk0Fwb32739W2wcF5a+2GLlZDPHToFW8yYJXfr54IpKHRuNS2zsP9MUV/P92vrMHqBtRhnrVO5qTBptHXKDn93YXwzkjj2gn5ztRrXVoOPYD0RIke+0G8vhbJmgc+NpaYWDJZ1OjMekykBCaWlB1vV52uG9KjOSZRuDnlgWQKOnOIYLFJpDGJIB54l7NsSVO1BGXLO8ZFI58/Ew0MZU+TLYSOl4Hu4RxRWqKB2Gr3uV1PuToV8DK77bkCMdvdl6dmOSX8WOBA5pBVEZmNmFfjptNSD8EWiXWC0ikv6g+aDCCAmwjlLIYpr1Xh6KkJpdPNJN5TyjwwKp2mFMqDGyyfffAyDh4qIS+mbIM6XFhrXO4n40Qas9Bj7cY+2aJg8Nyc737657mqtdx0jwwygChDIkv2p+u88Or7+VJ/N5vLC+gsJZECJaXvxJSVP+6sm1itc6m7MoGG7IKjmStKRBLjui02D6a4q8e8YP4BLotXGrCSuSjkr1QNgAMP3PrKUjiFEo5UlChhfScKqNU4qSiDRmi6gmydZGgSP0Za74AJHqQMTeqpZzjaKmv2YYVkbD0jYSwMpfCgcGwSjJNYBJXZDkZ+KtfpdD3OJYg539Sxj/ynHuIfntdDNnVKAOZVr3oVR48eZdeuXbzqVa96zO2EEBhzYVpJZ6Ws9d0H6YWEcpgBbYqeRBhHbB2yMKTHDfG6Il+IGRxQVGlMumr8QGUsAodJpsJKG0tkZahSRdlVRCND2faOZlXLd17ikSVd9XqQZNPQPjRBndicihiD8F6kqad5EWyRZ7sv7ZTs4DwbV8WUXUGy5ih6IhgLQDKy6JFpqG1OC7IFP9lPNg1VIhntUYx37WTnZxLUoRM+J2DWVazOkgGQM1bLdW6MsRDRhIwhQDhHsuGPrXLjdSfGgxZRGaSQVJEHbyq3qNgDLGE8+MvnNThINsLKXyR98JmBqgeyCG5ulX/caU9LU4Uj7wtM4kGocJ5yBh5I2UjgtH8Pyq6gfcz6CYeS/hqV2wDmUqjT7b6cDnA5+XnbnZjtOuWS0tvxG4fKHavjFpnzeSFK+Ml16ZSnNQnbdE0yFzVdjjhYLEeiQmKxSMBQukcO3YVT2EAly1xEKkoGpkXpFH+5/DTSz7fQg5G/j8sKisrb3huLaKcI2fK0t06L0ZVdjr+04unXHOLFO+7lymQZhT/nzMUYRyOat07S1xnd7jE2i5R7FuYZ7dLert46ZBD9iyoI92cWwxp3MmO8xtOG+UMU+XE40pi5FuPdgit3rbA72mi6TQavafTXKnTZnUY5uwWQdGSOcbLRyFj8zwZJLCqMlY17WCQMWhqOZn1U5hcmi56gk3oTgDk1IZEl1kl6amrEMLYJEocS3jAgFQUWyVCk9FTmAZGcAqztunjrdLsv7g/fyTf9yOC0j/MXB9/Itzz4O6f9vIutxD98x1nd36v/yYf5gVOU05/SkoC1ll27djU/P9a/Sxq8AE1ysAyi9MqQrlQI6yi7Pv3ddCJMqqlaiqInMS3BaK9k4wrNcH/M4EBCvhACF8ME2CkouwobC0zkxfoIgSpd6Bx4sX+yYeg/kNG5b+DByyx3uG7z14GSMuhfggWl63fJL/PgRZYQDR2bV/ucGpyfsCcrObLwOSomlVjtBxGdueZc28sWUcHGdV1cvxu6KmHVbObYTdilkFs7M8EAwbUSJrtTiq7CxBI18RbIJlGUHY1pa4RxmFRRpYqqE7jiHRkMEfx1qzqKbEFQdoR3ZZMCqwVVS3ltUginFM5T+ABEZZFVMFBQ0F42RCNHviCC85nzoLJ0lG0/COqxt7G2sU+0rlrTZOvtevy6kPbF5wu8nK3nn1wXsvuyLeA/xxUWVURlicYwGqSUThELQyrKpguzXPUbQf68GrOkN+nIAiVc0FOU9GVGR+a0RY7EYhCN0D8SFYtqSEcWLOlNemoSTAFgterwwUPP5uE/uYI9t2aoWvsS7I0BDxryAiKN7XUYXjvHsRdKXnTDPbxh3608q/UgCsumbTGwLTbMVq2rQTRArBvllJflbF4F490RtqVxkcIlsc+CiaIt3RdXlLgs9wuHuddguqL0YAZwWlF1IkYHDVf3TyCD3mfTpIG2VdFXGZGoGiE+gBK2yWmpuzOZjULnqGo0RoXTDE3adE+8pbIgq6KwgCbIlhxXzK3SVRnXJEfZozdoy5y2zImEYWST5rmRMKSiaGhsbVkQCcOCHrPQmrBdF3edLnj5i4NvPCPwAvCucgn3h+88o+c+Vl0I4f7Zrv/9uy875W1Pe4b2/ve/n7xuNc9UURS8//3vP93dXXQltG4yT0RREg0KVO6Iho58TlJ2NU77LJhkw3hqwA7HeK8gW/SrNZMFxWSHZrxLY1oSWXhNS95X5POSfMHrMKpEoCeWdN0QDwzJao5emyA3Rj51OArpyHWeipIIIRBxhKj5wdqDhXKpy7HnJ5hUkK5b0nWHLEQTAilLi4t8J0kWYYIvBTq3COMY79RI4zBRoJcB46sWEFoh0tQ7m8EUrGjtwd4sqFGquXa27TUrJq7pdJKq69sfsggrc5X12qLMBI2Mp4QJ480OTCy94UAJJvH6oLq87bQHaum6dyMTAUDbWDfHjsYe5FSpaFKsTSwoepKyp0g2DHP3F/QOVQjjyOc1+WKEiUQD8Lbr4qsPfWDfUyb3ZbuemiWKCpGXyKIi2TSoh1NuWb2KTZt6a2QxHUczGzVdlY4oGgBSOhUE6WnTebBh2DbOu5UZ5wXomYs4VC5yX76LTwyu4ncevInf+fjXM/qDPez+5AQ9DHqUSOOSGNdKEL0uot322sFIU+1osfo0za7nHOMl8/ewQw23TMxL53U4uY0Y25hamt5TGYt6xOXtVZ528Cji+iHjPZKyHRaVnB9vZjNk/L8Cl2W4PPfdfmP8v7JojATyBU37wJBrWsfpq6yhfdXCfONk8zegMTGIROU7WDb23alAe0tliQ32nnnofgFsVG0GJuXwZI5BmXh9pYCq47iys0IqitD5EVu6L3W3xwQhvw05NEpYkpAHk8oSuU1JPqW6EPbFd1/1S2d03HeVS0/quN/0IwP+4uAbn9Q+Lpa6EK/jtAHMD/7gD7KxsfGIvw8GA37wB3/wrJzUBSsb2th1J8lY5NqQ1okSqwXxwFF0JdliRNH3dr42gvSEIN70LmN2BgCY2HcNJjs0RU9Spd71Kxo43xVZ8/aTyXJGcnyMWhkiN8f+xl5VU2/84JnvajpZXXUHJtKMDqTIErqHDOmJgvbhjH1/m9M9YnACxnti8vmIci5msithslMzOKDI5pSf4LehbHmdiaw85WGypDF7dky7PnU2TP3/bHpzPfBAoI8FsGJ8d8dpQT4fAJ1xxBuFd/0igJtEYDXozCKN74xUqQeEwkE0gtaaB1s2lj7fJbckA+tBmgWR12DKvxcAZcsDqNaqYf6einTNEY0drRMl6YkClRuE8U5uVguqxJsLeNC3PeCcap0vMPFkgMvZ6p6c7S7Mdj1FqzKenmUc8UZF7374zD0H+Uq213cOZEZb5izpTebVmI7MSUXJvJwwL8fs0euhG5M3lsrG+dDLVJTN9vWkemQTHsx38Dcr1/Cntz2Lzf+zl8v/yLDj82PUqITKel1O4h0qiXxGVxNSrBWTpZjRFRXP2XGIa5OjHK963F8sMbApSjjasiAJuSkAiSzpyazpNFgnWEzGPG33cQZPKznxrIjNa3qUCy1sr43tpn5BLByzGW+t3ZoTA76TryVFR7K7P2BOjZtuSipL9kVrTRerBjTWyabDlYoSgyCVBanwQKIvJ6SipKd8RyuRJbv1BnNqTO40Q5OwUbRYn6Qk6y4s9OG7Mi5uumVjm1A63XRfpLBE0hsmrFZdjlZzZNbbY/dUxk49oHLbHf1Trbuv+qXzcpwr9fVcqa8/IyrX2eqevKtc4hv3vu2SBzJrz/rn5/2Yp22LUYvIT66HH36Yubm5s3JSF6yE9Cs/QuLw4V6iqkgecMxVC0x2x2RdiUlE40omDSQrvgOQz/kQyqIvSNYtshLBOtlSpb7rIo1/XrKSI/MKmXmgIrLCD3hV5UPDKoNQwVayDpq0BlcYb18cR42Li001ZVvQPm5JV0psXBsEWKKhRbRn6FnWUnQl470CPQIbO8QEWiueclW1pp0HE8PkQIfu0RVcFbRBM+JPYEpDiGYtlSVlx4dPenc1L5q3ymfpxKsFIi8RSgAeQOncb5vNK6KRBzHOCVorftBVhUUWjskOjdX4rgtgIkG8aVC5nQayCQ/CkoF/TXpkfZentEBMnftmUoUaVwgpMAsReV8iTQAuqdfjbNep14c+sO+cZcJcbN2WGsRsa2K267FKlCXCSLCWuDQsWocsU367+noGz095Xuc+YmHYtFFDOZLCUgQRfxS0LiU0AvXMeQ2HdDbQomKWqx6fG13GbccOcuLBefpf0Rx4wJCsZegAXITzAZOidlYsK9AKYUI4cRxhWxHZgkT1J1zfPtrQsWp62MBNqWORMKSqDODKNpSsgUnp68xT5Z5e8cUde1jp98nnWnSPxETDijgrvXVznkMZnDSboGbnmQZp6rPYlKLoCxaSMaksUThG4QYeC4MJ4ZTrpoPCNp0Rg0A62XSIDDQ6F+/a5gGJ7+LElE6zUbUYlCkbWcrqsT6Lxi9q2cTTyjyIiZrXWl+b2f8NounqdIJDmXG+Y5Oo6ix/wp669S0P/g7o3zlnmTBno8tzptSxx6oayACXjEvZLeaZF/T4pwxgnvvc53r6khC87GUvQ+vpU40x3HfffXzbt33bOTnJ81bGQJJO7SXxK0RikhE/tIIedIl3tRnv8g5kwkGyZhvNRrJpqVphZUl4YbwwNJQtgHi1QBYVcpD5AaXuZlTG39SF8B0PZ3HGC/Xd7PkphStL75OfJrhIM9nXwWpvlSxcyDOpQJR+/0U/wQmIxhY9NsiupOiBLAWtFYcwPs0+2TBEY6haPpsmHoSQzTSBIjjX1BbKVaC2leGmHHJnhIzAhOfhu0xV23dYdOY86CtDyz3VyMKgxyXZUoowDj3x9vrR0FC1FGVXEo1q8b4HJlVbTEFIIih7ingjAMBgbFCL9r27mqZzVJCs5KjCUvS9DkcVFgSUXW9koAqvg6lakqIniDe3KWQXQ11s4GW2LjVh/2/GP3ChT+Grpwq/GCWMhcoQOceOUYmedPmf2Ys4/oIe3zD/ZRbVkHk1pnSKeZk1T1c4lLRErmooYpmNGNgW1kmOFHPcO97J547sw97RZ+FOy9VHCtR40owr9QIZ1k07+s55QX2gdQkhfFBl15u/zPW8DmfddLBIejLDIBmbuEmdr+2dU1GSyqIxDljUIzKnsU4yF2UcXFjjywdj1tsJVUvTPi5Rkw66KHHGTPNewtgiRN0dikK2mcC0YFc6ZF6N6MlJExIpsWREZCG/JZFTGplxJaksifEmCHXV4KXuoNSdpNIpKqvIrUZJi1rXtJf9+IAO3Xyng3W1d3rbYqcsCyJRsVp1acui0cmUTjNyMZmNWM8u8Zy8p0hdCIraqdbPRst86vcSPvqSC30mp1Y3qc/z0Qt4/FMGMLX72Gc/+1le8YpX0O12m8fiOOaKK67ge77ne876CZ7XkiI4pISU++CW4qxAZDnyWEFrfUhyuE2xK6TLK4GVPqhMjxwiBETq3KEyhx5VqEmJHIdsldAyF8Y23QLc9FgNLcs5f/OsvfJnzkuk8XQbrZjsUJjUu5lZHdxUNr0BQN6L0GN/I3YST2cYWNITGuGg6HkP5WTdEg2Mp2dhKdsSob29s0tjGCrAhA5MEO8b4ztBxjavzSmLkP5cVOEpdVYJir7XoRRdidVtolFFtiOidcwDI5VbJju1T4kuve0zeMpdrX2pQZEsvB7Gh1oG2+mNbAoEKw+gZOmpcLUNdr4zIVktsFow2am965jypgEqd2jrr7kTgnTNwjaF7LSrBhtPthNztkHLNu1ru857xdoHAFeeEiwAWRnm76horXT55IPP5KNPu57FXZssdUb044xdyZC+nrAzGnrXLBcF+pjmvskSh8dzHBt32Ri1KO/u0b8Xdh2qSI9tIkrTODHW44jIZjK9ZseWKoCHmk3hvM1/2YGr59aCZsN6hy/h7YBLp+jKOrG+ntQrOjgMHnC1ZU5CSW4jOjrnss4a3Stz1va1eWDvApvrKU62WdyYIPLCL845Bxg/poAfT6wNLpUWPYTVok1mY0rh3cAi6fNcMudpWiOZ+P8DpSsSlXcjwwTntKgBgLPgQyK2OJat5m1WNjrMf0nQeXhE2YsRhcYgSUIeTywqxlWyRYMzax4QCYMUllj4DpoSjoFJWRu0z95n66ukrtTX8xcH38g19/7Mk97PpVDvKpfgey+drJhzcY7zd/z2KW97ygDmHe/wVmlXXHEFr33ta0nT9PTP7GKvGrjUDsiPEhop8gJZVqQbQ5JW4kX0kWJwTZ9oZIk2CpyWqKxCjvLg4GURldnqe2+nk/4mTMwYSGJEUeKk5ya7KpxDPfhovcU737YiqhZY7XUgZU/5zBkbIQuvE6k6yovhK8d4T4wwjvl7K5yCtes0Rd8hjCTZEB74CEE0kFRthVMSm8ZI6TNtcHZKG6svVC3mDzQAKkN6fMLoYBthIBpZkg3vyDPeHZEtqsZaNFuKkWXU6GHKlkRGHkjIwiGsaEIpZeUBTdnyWhUAp6FzpECsbkyvo/THzPuSsi2Jh45o4O2jnRaozHpwFUvIDGpcIUtL1VbI3GfHVC0ZKGfbdSb1eADkscDNxdxpeby6VLow292X81wBHLiy9BldlQkdckP6kGH/coz7G0XV6TGaW2BlTnJPDOM9gmxfSWuHp0NF2iCFY325S3wson1IsLBsaB/PiE6M/aJNvRim1bQTHcYWV3el64WmetvZIMnwWNl3XN09waIaNpSrddP2lCxck/1Sd0EyItZN21OmZI6yKZmN2DAtCusn7zuTEXvSTSJpKJcUJz5/GS6JEEp5aptSTTQAzk5dLwGRl3SOGe5d38FoR8yOMOTEGEYoOqHLMa9GKFyTe2NnhP2Zi5qOjbewzpgLIn4lXNAjTUIGj+CuWy9n7v4CuTFGC5BZRFsW7FBDOjJvTALaAQy1ZU5PTYiFoS1zYmHoSO8Wp4RFuZDNs50Dc0ZV08lOrn/zt2/itS9662M+71IBLZdqnQxeXvMnN/GB77zlvJ7DaWtg3vjGS1to9LgVKGQuL3zGSg0qZh53jVBdQpZ7ly7nmNsch7+LaVAXbBW6h1ThhnbVOHjJaZhXXjQ84Nqj3+/HTvdfgxjAxiqABIdJoOhI4pElX/CdFz2p0GNLlSpMIoImRSCs9VqT0lPJ4qFFTYIgsudb7lVLkvckvfo1NIPdjP7FWFxV+QTnQAsgipGFCd0P/1xZWPS4pGscVdtTvkzLO8zkc9LT3wzoyndgVOZQmSEa+WuUL0TI0NGJh45obIPhAMQPr+FsCNAUApGbhgbWXrZEwzAYVs7nz2iIB4Zoo0SNSmxLY4UHNnpUYrUk2nSUYhvAnIu6VIHK49WlAmK26zxWVuBsWBSzYVJed0bGBjX0QcVaK5JI04u01zTG3q6/6ra8RbwBlRl2VhWyKnynxbgQkum8q1ikoM5bySrvyCiEBy/ggyTNTHfGOd+SD7+LKjg4akci/T03FSVGimBJ7FgP4MVrUTyFDLy2pBas17+XTtGSRUPtSmTFNb1lpHD8VXoZphUho5npx6y+kqC1tRaRl6SrJYeO97nvwC526QGRqBi52LuPBV1MJrzBwaIaNhk43kJ5lkJW08tEk69TWkkpFOumzaF8ns+c2M/8lyE5OkQUJcI6VC4Y27gBJZbId20klMYDpB6TkOvjj+G7RZZNk2KRDMxTcMH3Atf/+5L/yv/Lf73Qp3HO6lLpwlzIOm0AY4zh3e9+Nx/4wAd48MEHKYpiy+Orq6tn7eQuSFWVt1I2hillqg7XiqdBW86EzkzoSAzHgcMrtoKMuoujpB9MIu3/hRJFCVneJBG74PK1JQVeCn8KQnqDgbrbUT9cQdnxCfPCwcaVGix0j3itSNmWwRYY8h2C+bsNw70KpxRlF1RGw5l2kTcbKHoKq/0Y55RACuHPSEgPprSGovTnUa/2gf87IDfHCNtBVJ4eJipP11KTClFaH+LZVjgpUIWnqqWrFXpssJHPYLFaIKzAJN6KWhgHkc/PcQriTUPrnhXEcIyzDmf9CqccTTDxPKYlMIkgXQ2rix1NGM/RY4MaeYtTlyhkYTCpwqTan2skqfRpfz226yzVHyy8asvv37P2wQtyHue6fjP+gfOSBfNo3ZfiJ2/fzoI5h+WDGQldBYurAGkRJztulZUHGFKCc6iqQlYVsdb+fmqMN3VJYlw7xfZSqjmvKcnnFUVXBAqxQ5bQWrG0D41Rw2DTbKeaTmYXoyozXXAzEicELvFdlk6wTDZBCF9TpKzzmS8dlTcBnD01YWBaZIGWZRAs6BEAiZ3SzboqZ7NqecZAqnCRbpgJQmsfJF367pCQ0wXEaHlM655F7rh2L1cmx+nI6ZzD4l3ZipCv05E5faY6ojorxlPHFIXTPrwSR+E0Nuhh7h7v5m8OXQUfWWDvFwaI1Q1cZZCtBJX1qayiJyfhckpGJB4k6bIR9Tc5M9C4pXltk6atctrtrXOl7dqus10fPfKr5yUL5lwCq2MyOeVtT3uG9s53vpP/9t/+G29961v5uZ/7OX72Z3+W+++/nw9+8IP8/M///Onu7uIqpaY8XKW20qXq8MYt28tm+6ZjUk96yxKS2IOCfgfTT8l3JJRtSTS0IL2mw0lBNDTEqxlqZeAHMgLtwMopnU2p6b5R3okMn++C89SqsHDmA7hiyOYFmwcjqg50HnbEQ0e+QzR0skoLD14MjHYpZBl704FA56ranjYmjPOvTUiQzoMp5zwQEwFcqZkB2RqYZKRHx4wOdr0lsQCjBHrsQZZJPY1Mj71Djh57lzBZWZwWVB2JMBKVWx8Cqr01ctUKZgBDQ/rAGgxGuEYAKrzpQpbTeyjHidRragr/vsnYU+qEdcjCgx0nPM8aLUEKqpYk3rSPeKu369zXyaDlsR57qoKZc1Xb1LELU6KdIErh7+XOgQnjgwj309oUpe7MyBlLY4KBjMbTimXl87729tm4ImXjWij2lSwurdJLClLtuyHDIuHIah/5QJf+PV16D1ckK5nXYObe/dHvPACZsJjm4ihQhh259ZbEmzb13Rds082wTlDM5K3MB4vnRTVk3XqNh3VeLxIJg5Su6doMTIpFYCN8Jsys5nO2Zv9mHSLLWfiy4dM3XMbTe0dpy4K2LJhTIwZ22tmwIbQyFd7RbeRiRjbBOknhFCObMDRpI9x/KFv0tsdFmzuW98BHFthzywC1vOHfM4DK0D7q+PLmLpbn+1yhV1hxXRQWKSwK580EAp3MB5XKcN0cCMvARgxNirHbFLILUXft3vGYj117bOU8nsnp1c9GyxdUIP9Yda67QsnT/zE8+L5T2va0AczNN9/Mb/3Wb/Ed3/Ed/MIv/AKve93ruPrqq3nWs57F3//93/NjP/Zjp7vLi6eEmOEO22kXJVgYNzdWOQNqjIHKQRT5VaSaZpXEuEhTXraDfEfcCNDrUEkb1R0GfHjifJd4Z4vWQ5uI4RhRCVACV4sypV+NEjWIqakIk5L2smG0V1GlEI0hWfd0MiegdcJRFD6bRhpH+4hjtE8SDR29h01zXlXqz0WWXjNjEi+612OHXBv4TC8lcXZGbAlbaQkQHrM4a1HH1ukIweiyDibROAHJhkRWrtG8+J+t78poSdGNKLu+Y2Q6gnjk9x1v+u07ayXR6hi5NsSNx4HHLbdYcKI10YkxeneCyh028pqk5PgElyhspDCJQgc3NFEa6ETeqW1YIccl1VyyHWR5nurxgMvjbf9UATLnqguzDVwubLlWClgEoRtT+o6Iq4dda8DS6D+EdsF5a2orXGd9uU6L8TWLHHmxJrphkxfsOcTVnWXmHiVQcbw/5tB183zueft54M7d7Phsl7n7cvS6Rplho8tESZwOnfw4ompLwDG2MQUqBD7KRt+yS2+ybtqkomRkk6YTYhAYFAPTCgJ/2yTbt1Xe6GZWqw7rRYtkzVPiZrUudfepoVVDoFULhHV0DmX0/6bNn87dwIv33Me1rWMo4TwzL1DhpPS20iP8Cq51couovycnTVjlZpVyx/pejm32yO7pM3cX7Pj8CLU+DtfGj/GirOg9WHL3PXu4d/cultQmQGPXnIXXqYTDYumI3Gf6CJ89M3L+8dIpqmp7PDlf9RcH38gV+Z884XY1uPmvv3Arv/LD15zW/t9VnvHpnVKdaUjmuerC/Gy0fEZ5Oadb50TEX9fRo0d55jO993O3221CLb/zO7+Tt7/97ae7u4uqRBR5jYT0+SSessWUNga+vV13W6zcYreMFA2Ice2UbH+f8e6IZNO7eiWbBj00PvG+5bsvXndhcFKQLSiK/gK9ezTq+AauKBBJMkMtm9HKgHfQKkpaxyYUvU6jCSlbHrykazaAEk+lGhxQ1N13Hca9ZN2gMuM1JqWj6ijKtqBsgx47Wms2iEKVPwcZ3Mhk6FBJpitpdRdGSE8BMAa1vEFvUjK5rM94lyZbVMSDaXuj7EhAYSKfz+KUp5PJCtrLPpRTDXPEKPN0g9LbgjprG3qF0AFQztAkxOaI7v0xk70tyq53i4vKmfcRcJEfvJ329AnhwMYSs8MHrbltBtlFXX+w8KpTBjE/8wu/eVE7kT0ZEPNkgMo2jezclemn6Ej4zkdWYLPMG0vWGV715F3rGRvhGWG9UqAVtptSLbQ4/PWaZ33dXbxo4T56MmNftEbmItZNB4BUFI218Y2th/i6/le4bedV/N/9N1D+9RwLX1GkxvjAX/vIFrPKHNGq4u7BEuO5hHk5JsPrW8B3XNqyzjaRjbNXR+Ycr/psmJbXo4TtxyZmTk3InCYShtxq7t3YQbrqUIPMm9VUxr/uWgcaxVOmgw0UPGPRKyN2fF5wtLfER16saV9eoBK/nQ+WjDlWzhHJijwcv86vya1GYTmW97n92D5Gh3vEJxTpCswfMrSOTYjWJlMzhFqPE7pE6bExc1+Y5/9cdSPd/Rl9OWnsk4HQibHeMU7YBlAZBKXTDEzKctGjGJw6NWa7zrzu2r0DTgG8zNabfuFFvGn3jlPuyHzLg79zzqlaT6bTcTZAzP+TbPL99081Rh89heecDSH/qx7+vVPe9rSnaAcOHODIkSMcPHiQq6++mg996EN8zdd8DbfddhtJcol/QZX0N0wIdCkxFWDWk3PnmmR6oaTXwDg3bf0HatX4inmqtiTZtN7Cd06gJ4Kk9AL7suXBkUm9zkNllmTTW/gOr+zStaBWNxtR//QcVbNyJbIC10qQ44LO0YhsR4TVgnTdh1UO9ykfuDl2qNKDAp/F4mlh2aI/B1FZkrWS8W6/WlQlvmNT9gQ7bx+FpOSZc6htnZ2dDjhC+JUr6UFOMzBVBjEc07qnpPWgppprYVPVACY9qfUsNbXLZ+ZE6xlyfegBSw3gAkXMX2cb9DjOHyv87mzVcKr18Q3iTsRob+zdy+ZSZDHtpNlIIsP/VVs1wZXC+mvSOTI6F5+y7TqLdTog5lzW2RDwzwKRUwEzZ6vDsg1izk2N97SQGxK94R3AhApjipTeLawW2NcLQHUqfT2Z1wrXaZHt7bL8nJjuM1Z48cK9XJMcZV6NsU4yqFqUTpGKkrFNGNhWoDc5dulNvrZ7D+1rCn6vfB6y6KBHLfQgR0zCSpYUfjGorIiGFZ3Dmq8c2cWdS3v5mtb9AJRMxemxMMiQg1JP2jMbMbZxAxwy60Xuiawau+JhELEfe2CRqw4VyM0xbjTBZdmUuRAWB0FuGWcBxFgQHbPsuUVwPF/g9575Qno7R7TjEiV9l8s4QWUUlZEUlcJaSZFp3HpMckLRedgxt2HZvVKih2PEpEQY09DqXBKB1N5iOiyK+UXCip2fz3h4535u+dY1Xrn4ucayuQYsShh26GHQwQg2bUoqysZA4OikR/vembDn7Ton9RcH33ja4GW27joNEHOx1+mCmJMB00fP8Ljn043stAHMq1/9aj784Q/zohe9iDe/+c3843/8j/nt3/5tHnzwQX78x3/8XJzj+SutICsDNeyk1Nwi/F1I/1gcTSfThEEoVLl3nmyHIl0zBOU7rRVLa7lEFB5c5HOS/oN+0BCVzz1RmdeATNKY8cEO3cHYO6HUbjOS6apdaLeLSuOEIFqdICrH4PIEEERjS7ZTMdnlaB0TVM6DF2EgXTfI0rHZ11gtKOa0z4hxYCKfYSNLrzlRx9b966xXxYLJgAd3cgpkanG/CB+pkKnjQr6NyP3f9co6AEkc++tdg7OZzsrURGGmrMNV5VSXpLU/tnVg6/cqnGNV4axDGENy93FksZOi7zneWnj6QtVSyMoHuVXdyGfFCFClRQ0L5LjAhO7idm2tu176e1z7sdedlX2dLn3ssfZxKiDmYu/CzNb5pn+dKYgpfvL2c3A2T43auFKR3K1QYy9YbzSM1np3lDrEOGhg6vts08VvJZhewnBfxPig4br5VXZHG6TCu4Ct2zYjmzROWzVtq7TTYX1ejXhW6yE2rm3xR8vPo3MsplVZdF56wFTZZgIfnRjTPRQxfKDNxw9cw9KuAfNq5LstNiINGTArVbexJx7bmCU9YGz84uVG1SKRFXYmX2VsY44XPT67coAdn1QkR9ZxI08BEMl0Uu+sneahhfgCIIw1PoogWh2z+xOW+XsSiv4cJhKUideTCuO3VxV0Sk9P1pnzjpObE+Sw8KY5dQxB81646bgG/r0I4Z8iXKf4GOy5VfHXizeweNOIF/XuaWyavVGAwTjpBf0Oxi5h3bU5UfX5+OrVfOHj17D305t85ex/zLZrpk6FNvZEdaog5lwK5s+WzuRCuZgtfO69rD3rn5/2817zJzed1vanDWD+zb/5N83Pr33tazl48CC33HIL1157Ld/1Xd91uru7qMrs7KPLgV/tN2arhfHspBlogibDoOPqwanfYbwvRVaQzStU4EmmKxXR6hikpHNE0z4u0MMSNSoQRYXtpthI4iKJyrz9cLlnjvi+3HOkQzfImXAD1trnyxSld7VREjUp0ZOYyU6Jk14smS4Lb2dceYBSdgU6k0TGMn9PSdWWVIkkGluc8t2Z8U6FiWHnJ9b8663BCnj3NQiDbwAuSnkAIsUU6NW0CP8knLAzQaECl+XNYL2lq1Jzvo2dHntW7Fnrb+rjzBotGDPN8hEWZ0BQEt1/HLXQp5pPKRZiDxZzQ9XSOOm7VMI6omGJ2swQg7E3YbAngajtuuTrXICYp4p9cg1GTgXIbAOXJ67iOSOG40XiDY0cimlXv+lWh2wtGSjJs1b5aYJZ6DC8rMVov0DOF9zQP+pzT/CC9OWqj3WCJT3A4N20RjZhGHQrYxuj8E5YN7QP8+nrLmP4xT0ka0HfUWeTlSXOOeRwTOd+xY5Oj0/NX8WOZMRL+nexQw+JhKEnJ16YrocYJxnbhI6MGJhWQ6dKZEUkTNOZiIThvvFO7tpYYvnv9nLZnWPE6gZmcxMRx8j5Ob9wVfj7rcs8RU3Ese9QOed1QmFBSjiHLiv0+piOEFMHt7pCJ8eF5wrju0uNtsja6bg+S6PTylPadNAfSYljZtGurGjfv8n+D8/zJ2sv4m+fdxVfu/t+rk6XkcKS24i2zDF4C+mNqs2Xhnu49StXMvfphMs/N0E8tH4OP22Xbv3d/7iTF7/+aU96P0+2+3Im9f8km/z3vH9W93mxivdPp77lwd+BB3/nlDsxC5977xnpa540y/+mm27ipptODzVdrGUSDWkCYXWooZDV3YV6Qq2i6YR61mq332VycM47rAD5giRZs7ROVOhRhVPeq19lXvMiC4Mowt/r/VlQhV/9qboRUaflAUrdgbESVOBKa9nYYYpJjjSW1jGNSVI2r5DI2nBGeGaXD7t0FF2BzkFMHCYSFD1PYwOwLa/9WPhKhlzb9IOAlLgin4KS2ujgEatkbureBtMBqBZjStkEdHrR/YzwXghvoSlVWP0yjcubUBKXF1u7LvVEQEhcUQZeudzi4gM+T4CqQp5Y+/+39+dhklz1mS/+OefEllvt1V3d6m7tICEJEEiAEGAbNALMYmwW2+M7ZjzMyPYIj7fxtbEx84zn98As92fu4GHs4XcHsGfG5mdsFhswY4FsFiMEAoGQ0L51q5fqpZasXGI759w/TkRkVqOlu1XdXd2K93n66arMqMyIyDxx4j3f7/u+BCse/mKIbYZYKZGJS66WwwwxTEZVoDwv7K9r0WWNJ8fZQl7G8VTVmJq8HBteecH9fGnfi+nsDVC9BFlqX9RYNowUkOnq2ikK8mImW/TObbJ0qSLelXLlzsfYFR5BW4lEckS3WS0CJDOrkMKQWo/VvEliPUKRo6StdCoTcsjLtjzIX+5YYOJRRSALAX+WjwhVrpG9Ie29IfH3I26eeDbbL1tlSg2YUq6d1jmPOWvgSGSsmUYllM+soinTop3M40jWIpQ596/Os/eurez4do6/f8VV5MfdOsvWsVLL+AOERI5y2WAstLOYNzzlYgAKQmKlGJGXcv7RBXEp5qJ1i2Jag3bz1zqLa+0IlVCyIkKd+yA61GD5kXk+e/E86oIeYZDjKc1ElJBqxeqgwWB/m859ip2P5DR3ryJ7Q3R/ZLhQY2NxrKL9jcbPPvKhDa/CnAqh/KnCsbSTHW/VZRzHRGD+6q/+6phf8I1vfOMJ78zphvUlNvARSVrdTIN2N8jlBXc8yBJdXQhF2CDZMUXWUS440TqBvDAWNdSoRJNsaaAj5z7m99zNswh9TORVgWN5UxUXbRckaVoRqtsbhVoqCUmODUP3vnmRH5BrBOCtJTQPKGTmkTWls6xUrmNBh+51jQ9JpsgakjwS6EAw2KqwApqHDLPf6+PtOTzqQS5XB8uKRJH/UlZhbFr0d5fnx/dGpC/LK3tqS9GKZiQERY6MNc7hbJwIlu9baGqs0aPqzTiKnnFRrMStI1TlZFhUaqxUoFOIY2SvCDaTct0qnM3L9jxTtKHVXsonExvRPjb+Wqda0H82kpcSNUl5+tjZOEI2adChcItUvueqLYU2kFxDkmEHQ7eQ02yA52F9j3SmwfIlivTiIS88bw8vm3mABW8FQymeD5DCYKwjMwMTsJo3UUeF70bCrWLF1mfO75FuT9GRhwk8pLVuH6BaRMJavG7C1IOKvNnkrzqXwy54cetBmjIpcl5kIVwXrirju/0YmIBQZihhOJy1WU6bPLI6w9Lds8x9V9A4MHTXW89DTnQK45fiOl1qYKTEygyyFFJdnRMCH+spbOBXC0vWkwhfITLtWo+TrNCGJm7Bz1o3NxR5Ms6WWrl4Aynd3U9JcsrWNXDbS1nNYVaDUEXFLMvxD6yy5Uifue+GxPMNso7CKIiFa9OeTS3bVhJU7PSYMs0RwwQb1wTmiXDHp/by3Dedc8J/v9Hk5Xi0MBvVSvaOV53LP/mfv/S0X2ez4ekQlKfCMRGYN73pTet+Ly1rj34MXNDlmQphLGayiRom1YUdjrq5HrcQLh+KIvTCNMmUT7CSFy1KZTsAWCVIZiPyhiRvCKyExkGN9ST5ZOg0MKIgUJ5AJqNJKJ1v0Dio3EqV543pcHQhWteV7ITMIrsDwjTHGzRIZkLiaYUOBEWLMipx75W1nHg9a4E3gM5eTXNvjL+4WpG06nPWriKEJ5zrmGZUZSm2G1VFivOTF2X7MByRDzt6vmwZKIM+y5wZ4SmsKc0TCsJiLAT+KC/BlFUdgKLiU/Uvm7HXGSNMuqjgCOnaFDwP8mSstcCO9tOs/27X2HhsJHk5ETwdEnM2E5caG4fEeNjQYDzprlWl1oJCyC+KioDvFnOElM7OeL7DwReEpJcM2bVliUs6i0ypAYOi0tEvXLdKGCsrAX1TplXOSWl/XAYthjJjYWGFeHILLYmb48r5urQNTjJkd0hDW+Zsi0Nijj8dXEXv4pAXth5h3uu6FjEMCMisR2pVtS8DHWIQ7I8n+eYdFzJ1l8e59ySEB3qQpOtdJEsNkDsI939VvVduvmlEmFYD0w7IWz46kOiGJA8FxhfIzKJSizc0eAON18+Q/QQRp666NLYIVS2y5UVINVTEBjmqyIjy/YvWaRfU7BzKRFnNSTLU2oDWUg8bBcUcOVbxqSIXikWyM/i+aLPjyXJeThWeDokp3b7+/n9u8E49A3BMBMaMXQS+8IUv8Ju/+Zu8973vrVrHbrnlFt797nfz3ve+9+Ts5amCgWwiQC77ECejHmVViNVLHcxYFUYoiZmdYLitSbicIVONCVSRp+IVKfIGFbtqjDAuZT5vecjMOW/ZItDSli7EFtQwd/bGs8VEVdoWo9bd+AvfrxxbSitKMYhR2tAYpKi4RTzrkQqJP3DkxfiQzAiEhqkHNJ0Hesi1gbvgF9qTdcL9kjiVUKMJy+a5a9+CYp9ktU94HrbTxEQBeiJA+67Fy+vnCG2cqDJOEP1h5SRmyyKLFKP3LPN2yvcQI/vqSgMj7Gh/pRhVU8ZhrfuQpRi1qK1rMxh7/SLPpsbj48ArP83CzT923H93uonLOE6ExJxM8vLWG17zhM99/EOfP2nvW+PkoJs3mNjaI56ZonnAR5XX51J7Au4aHkXV6r9pRhx8YRP5smWuml/kguZhdoVHSK1XaEpcwntTphgrkNISibSqxrg6vCM1CtdCVloe93TE1maPhye2YkIPueraqqwxCFW4ouXazQODhMZjhu3diOH9DT5z+TX8/VUXc+22h3hp535ahZ1yZr3KNlkKw1Le4lP3PRf7YItdt2iau5edm2RxPbZ5jhDCaVyyrOosKB9HKQh8hO9jo4B0YZLhQsjaOYreuQa2JLTaMZHvJop+5jEYhJjlEK/rER2OCJfatBZzov0DZG+IGMSjaoy1rh25tG4+mkABFoOQRbbY+HploYUB1psA5HpERMuKlh4jLUK4Y6IJKxv17aoBm4O8lPj7/f9XkQ9zfPkt41bFG4G/nH4T/+qmH33c5973lts2/P1OJ45bA/Mrv/Ir/NEf/REve9nLqsde/epX02w2ueGGG7j77rs3dAdPKcqLWXlDXvUpM9Z/W6zSlFWZKGS4o4PMXCAjgBpkWM+1ihlfIHKX9i6K3BfjCfKmxCiJSi3hUlZVbVRikEmOLlabhCn2J8+BEXHA80bkpbw4l6s90vU2iywnMOB3PfJ2gI6Uy1nxBO19lmA5dRWXLB+7iS8siytBaekuJkY39ar4Oc/deZDK6VQ8DxEEZLvmWNsVgXAVn7whMMrlrOgAVOKTNwDRQsUQrhmClZxw9xKiNyg+CkeARlWgMWLheSPB/3hFTKmxiUWvf6zkM3pEcqrsmqLFoDreEo9TbasxwvGSmM1EXkqUhOSpiMzJIC5PRliebNuazJwZmPIGPHvuIHdunWbqgbGbZRhVP4rWMiEEdqLF8vOmGLy0x2t2PMA54QrTntOeLOctpr0+kbAonOMVQhIId0PdkglrukGzCPoqrZVLd6yejoiNT9tPMIHrNig1IpWDZmHdjLWIJHWuX3GGf6RPc2+Tpb2zfPqqSe65eCtXTO1jW+BcGpfyFonxuO3ILh67fTtz37F0HhngLQ8QvWFRfbeVXtRqgxD5qIvD84qqh0S0mthWg3S+xdqOkMMvALl9yM75ZV4ycQiAtnJVJWPdfg91wGoWEWufg/02K70GS4+1mLxvgvaBFo0DMWp54NqJjVs0XKd/KRbKqgyeMXL5A8GaZSuaGs0NQht33sb/tiQ2pS7HGNcKXWPD8O//4Qb+8mS+wbXHf6Nf6leeqhpzMtzBzrnN7e+/epJt3vUXV3EOV1W/f/Qn/uGM1twcN4F58MEHmZqa+oHHJycneeSRRzZgl04fXIXEYgMPUd4gW+Nufss2I+OE/GU/rWk3XdZKL0PmrixufeXIghR4fe3sej2JsK7cbeOCyPhlIKVADXNkWoj7BxkiMzAVIiyjMnieu0pMUca2jCwhrVKI8uJaToyALBxY1GGBDQPXI1z1/Y7SkO24jSSMbvQxowpUpQMyRd6LqMgLnofZNkN/Z5P+VslgQTDxkLOxbO3LSKe8YtKEPBKAxEpn6Zx2JPFUgDxnAZVaJu9ZRR7pukpQNhZ3O66pLytiWo9a044Ohht3KCs/Ryja4UJHcsZsTI9uQyNNnv6XqgawOcnLOMYJSklmTla15XiIy1P9fU1mNi98qZlUMcYHkVtX1RfCaTC0xsaxq8AQQeAz3DXJwRfB6y+6m8tbe6sqR9+EhDKjJRM6cuise4WqKh+RcKSlDJlUwhCIvApULLNIfKGJtYfXBzlI3f6UxMJTzoGLseqBdvUcay3eyoDZ7xpaBxoc3LGLz2w9l2TeaT1lIvD6gsn74fwHB3iH1kZzTJa5a7gQiDBAqKKXWRuEtW7eEgKilgvtnGwx2Nlm38sV5zx/P2+bf4hpv8+5wWEy66GtC4dc1c0ia8ZZSoMjbYenOxxMO9w3t4VHd86wvBYS7G3ReaTF1EMJ/nLsrKPTwrilbBuTcrTYNWazXC1UjsUkCOE0N9W8AZAW2wa+y44Bd3dVRg3kuWtZrvGEOB4dzJ+cdwPvCq966g2fFk68UjFOUG7a9fbq55NBFkriciL4p5+4lnO4FoC9V92wUbt0ynDcBObqq6/m137t1/gf/+N/sHXrVgAWFxf5jd/4DV70ohdt+A6eUhQXKSsE0veLMMaiZWvcNhiKm+MA0/RRiWsPAyoxvg5dSGTWVnixQQ1dz7AVECynyGGODRVWSXToJg4TKOdMZgtHFQtqkI80KKWDSm7X9exWKFaMbO6CvaqLcV6seo2Xv7WuROpVKX28TWy8bSs3I/IipCMv5etIgW03GV44y9oOn8ayIVy16FCQtQRBD/y1FBXnJLMh8ZQi7Tgzgc5jOd7QYJXAiy1JR5JMS4bz08zc3SR64GC1Qli1tOkitLLcH98bm3S8kTC00NQ4UmJHq2ZKuUJW+ZmqsZXRo1vVxlrlajxzcLraxGqcXejrkEQqso7BemOr+9qMqg9ji0bxtKK5c40XtB+lI2Ni61cOX2WmSma9qk3M/bkgxoVI+sJZGEsMsQ3IrGKQhxzO29VrHOhPEPRslZlSVV3GbtBtEbgpcu1sio1rtVXa0Fod0nrALZiZdlAdgzAWEedu7ipbrcpWZHCdAnGyrtpTXtOtkND2yecn6O9ssPgiePnL7uSK9l7aKiYSKZHIWCryZ1YL22aJZaaoUHXUEI2zbT4vOsJC0CWZ9TiQTHDfzi08OrNA3oyYelC5+TdWqGIBT4zPo55ab6+clxX7Yt4v9TulU6W11T2CNW6uEvlY63Opiym1NjU2BM/6wKv4y30n9z1eskGvczIrHE+HvDzRa51JROa4CcyHP/xhfvzHf5xdu3axc+dOAPbs2cPFF1/Mpz71qY3ev1MKp0MRmMhDKQVpWrmjYIsbXlmIwikuSr5Ch8qRnqxYCZrwSCaUE+wraB6yyMy1k2FBdN3qE9piwsJO2bgWNJEVvcKB534vy91lRSjP3eQQ+KOVIiEhSbBjIZd2vFUqz11PcZmdAut7fo12ri/jLVhly9b4jXypIQGqsLFOi9Urt5C1JO0DLpQzbfv4a671zkpIp0OEtqRtSTopULGt2sswFq+vsZ7T5DQPW/KGZLDVJ29uo33nInatV1RbGNk0FxWTSoNj7OgzgnUuaaiiSiTkqId53HCgPFYpqkwbqzXWjLUP1KjxNFGTl2cWApEzH/RQ24Yk0xFhGLiqR9mWVJiKICVWSdKOYOvEGvNeFwBlDdoKJlRcVVOUMMRjpCYxPgMdOH2MzIlETljcbCsMWdF2nBnFwAYs9ZpMJWPXyJJwCDGqmkBFtChv1j1vRE6sIyxylaIKX9gZl61YZWVfSkQggbIl24wWzWCknQRMK2Lt/AYHXmF4y4u+yUvaD7JmIiSGCRUzMCEaSWzdLUsociKZVdkrJcGb89aIZIYu2su2+SsshF2+oBUHsi2Az/T94EuBTILRot7R4vvxaIPxLoUSRdhoWaGxRjvCBuvn2Cwt8tt0nStWY0OxkeTl6Nc9U1rLjpvAXHTRRdxxxx3cdNNN3HPPPQBceumlXHfddevS6M9EyCRHSY1VYkRcypV/pVz7mLFuBb9YzRfaIFODjpw7ymDew3gQrRinf0ktxhNkbYXfzStHMr+XIzON6qVYJZFJjmn4jsBYJ7bXkSJYjkcWyuNZK+Xv4+YCMNpfs/5iW7Vi2fE+3VEPcnVzX158y3BKqNoJqhv80jq62WDtsnkGWxTT97s2hu65PmlH0N5rELawgvaKypYqWikEREvOXlQWFSuhQcUGfy0jXHJksrcz5Mi125j+zgriwKFiv+SoFQxGFsrFflvrWjWEUk4b5HmOkFiLEHa0TaadcLXU+oy3mEmBQCHqHJgnxYmI+J+JOJnE5ejXrlvKNg98qZnwYrZMr5G2m1jfK4xSnPW7PUpjZzxBy0/x0QxsSGx81kyDoLAuLlulytaxUgNStlK5n901O7MKhRP2SyxSWDKjGC41mO+bkQZHjuyTGauOVFUIIZzIv9SxjGs8AJtrR0SkrHQslTGKGWvhHa/4l4tfUoKS2DBguL3N0qWCH37+3VzbuZ8jeZvY+igMAxMWBEYwqYYMhMZYSSizIgPHsqKbJMYns6oiM9W5ETkXTh7Gf47hsflpsk6DqQcUnSRHptnIvAbcefFdrIEYq5isIy/ji3/jWhpj1wc4F/Pw0Y6tNWo8HZws4jKOf/qJa7npJzZ/Js0JBVkKIbj++uu5/vrrN3p/TiuyqRCZMnIUGTJKoS/zTaBoMxpNPlIbSCCZ9sgjqmoCgEpB5hajBHlLITOLjiT+msV4EglO/K8tItPoVgBCkLU9p4fpJZW7V3WRtcbZE5fkBda3QYmxdi+jR+1S4ErkeTpmE2lHK0NjFYhS61NWMmyaIijar6xFRBHx+XOsXOgRLTnClUx5WFkYginQniBrgm5IwmX3/rohILZYJdASspYzMpCZMzMoK1E29AhXNL1tHosvm2bhSxoOr4xWL8vqSnkM5fFiEL6bRKr+5UIfVG5bTaBjcMJSgdUFsXm8Fr0a63CiTmQnA8eaAXO24603vKYmMZsEkcjJhEZbgQ7ANkNEmo1s6pV0N7fVwhAEMicQGkOGFpIp5UxNMqtcuj0CVYRWlu1kvtBVmGW1LSMrZYCh9jkQT9C+z6exuIaIE2yWIcJwrLVNj1XgzVgel3YVhLjQcHiey1Mp932M7FTGKOXvpfNXaZtcVSeMqzz5HmaiwfKzfba/ZC8/PvstlDBEMsO3OQMTElufgQmYVC5HpWyvKzEwAT0dVSSudGSLjY+WgkhmXNJa5Fmtgxyc6fDVzgUsTs+AbdF5RKAOd0cZa2VOT1l9KioxPxBwWS4qlguJnufmmcKl1JEWBarQpEYhwkoYbNjXq8ZJxEve+JOnexdOO0p9zGZuKTsmAvOBD3yAG264gSiK+MAHPvCk2/6rf/VkHgibG0YKJ7bXFtOMEMur6zfIxm7qS/FfbrCRO41pS6JS8Lrugh6uamRqkdq61qpJD5kbvGUnajS+xHpFBSLyUHGOMBbdUFhP4A20sxguL5IliSk1HrL8X4y0OuNVFHCThj9mg1yUtF0IpywuxmNONIqRq5mxIAryUpI3IVw72mSblYsDmouu0jLY4iOMJVyxBF2LsBDPCPIGBGs4C2cJZs2RuqwhCNesE7hq8HsaNcwckdMaYV1OTbRiiKcly8+fZeaWBNsfjlrINNWk6AjIqLJkxwSWYsz9poQo9UTF9uXxV+RFKdB1C1mNp4fT0TZWk5jNgYZMQEa0g5SDHeGsi6Vc395bahuVRGaWw8M2XROhigwXjBPhlzbKZcUhEilKutfRSKQ1leg/Nn7RRiWRwoLnWs++vbST9j6DSPNCVB9iJ1royYbTvViLzAxWuG4EMUicm2XMKA8MnG7FjK6dFlfRcXkpwrU3lxEEhaZE5AJrNcILRyRJSfAU/Z1N1p6f8BNb7mdW9TiinWbHETRH4nyhiYSruEQyZ81ENGXqdD46RFvpqk3CMNAhUVGdybSryEQyQwpDuxEze26fWzvncZ/chfFaTA0zZG8wIigwaqFThY5y/Dkz9vlpDTJwVSivqCplwlWshHDBm8ZDBL5bAKxR42ngVFRfjsY3f/Mnufo//P9P+fseC46JwLz//e/nZ37mZ4iiiPe///1PuJ0Q4owmMCozCG0Q2jmJicB31oswat2CkS4kz5H9hGyh6VbP+gZv4FrKhHVCfpW6CUEYF7ZlPIFRChMI/J4mnvXJGwKZQfNg6qQ1oULkluBg371X4I+E9q2gKFUrbClgN4VAP06wpSZmnMyUK2PGFj3XZqT5QDnHNagIjQj8UfuYLTICSjvlYjUt2dZB5OAPnbZF+xB2Lf7AVJk2jUPQ3y4Jlw1+z606+j1B48AA3fBBQtrxQUA64b6K/kqMVR666TJ0AKJlw2Bekpw3R3j/gXW91BSkRSi3/6UDW9UeVjqVSYEYtzEr2zekcFWl8XMkHUkTJ1SffGbhWKswb17+1Cl3IvvPuy593Md/efcZbPVe44xBW8Y0lMcFncM8umUHJvRGOkYlEdLH5il2GCOspfNYzqN7Z7l72zlcFC7ii5wjul21RmVWoa0kkplb3MeghEFhnNBdZq7dTDqi07UNACKRMSDk0b1znBNbdDtEt0PyhmL1woDBVkHedlV0AKkhPCJoLlqaixmNx9YgSRFx6lqRy3apsnJfuEBaa90VttJtllUINbJKhlGFxrp5dvV8xXPO283ljceIre+OwQpi62OsJLUeHTnE4HJwMuthCmvo0tBACeMMDITBV26/OipGIzCFfshZS+ecGx5mbusa3lWGu/X5hKsdGrtB9oeuhawZYYVwVZcSYxqZSsQvZNXJYNNsFCtQVm7GNDKO0NULYk+FY3Uie8kbf5Kv/9Wpu6l+6w2v4Y/fc/sPPP7237vylC0W/cl5N/CuU/JO6/Gmt76Kc976qk1ZiTmmoIuHH36Y2dnZ6ucn+vfQQw8d15u/733v4+qrr6bT6bBlyxbe9KY3ce+9967bJo5jbrzxRmZnZ2m327z5zW9mcXFx3Ta7d+/mda97Hc1mky1btvAbv/Eb5PnxXyxUrF31JVLolj+qSpQr8uP6kCKfRAwTVGrQgSBYyQlWUoIjMf5qQrCS4i/FBKspMtV4vcyRI08gDOQNRTIhiacl8bQga3lkHY+sJfF7OWK153qLW02IQvS2OeILt9B73nZWrlrg0LVbWH7BHCsv2MLqVdsYPncn9pwtiGbkStqBP9LGyKP2H0YkBSpCY0vHs/LCXFZ/yjK5VIggYG1HQN4UpG1JuKppH8hpHMoIVjKC5ZRgNad1IGPqQU17X0p0cEiwmoFwVSs1zLBCMJxVDOYVaVuSNxX5REg2EZI3PPxBTriS4w0MYdeycnGIbTdHRGO819gPqs/KpunIMa4km5432mbcSW48IXnsnFlrIdgcDGazjZPNhqPbx/7zrkufkLyUz9c4+7DZxkkkMqbUgJ3RMtlMjg5lZVVc3QgXVXQ7iIkODgn3BOxNplDCMCGdA1epa2mrmI6KCWWGsYLMKvqmqD4gGZiQtGg1iwrb5SnVZ8br8Z3uDqIHQqyE3s6IfS9v8vBPSlo/cYDL/tF9vPpHvs3rX/lNXvVD3+FHXvkdzn3dw5i3HWH3az0Wr50hvmAWMzsBE+0i+2tMqD6eG6bUSPhfEoDxFrOylayo5phmwGC7YVuji0awolv0jaugzHtdZrweLZlgkGgrKz2QRhAbn8w4V7KwqLAo7DoNjLHyBzRCpSHCszuLqPN6DLZ4mHbgPpvxljhZVF9KJ7HiGFxgtCwqSJ773egqZwbPw7YamJkOesskessk+bZp9PTEcX+HTgY22zjZbDi6fWzw2NbHJS8Af/ye2xk8tvVU7Bbv+ouTbRt95uG03qF96Utf4sYbb+Tqq68mz3N++7d/m+uvv57vf//7tFotAH71V3+Vz372s3z84x9ncnKSd77znfzET/wE//AP/wCA1prXve51LCws8LWvfY39+/fzsz/7s/i+z3vf+97j2p+85aEyWQjNy8pF4TpWrhpJRg5cANYSLvZJJifIWwqVGBf0CFWwpRhmqMT9nUw1uuk78jKtsJ7TyPgDML4gbwjaexK8Q2uUCb56tkMyG5FOKIwCUV5ftftZakseCvItHsO5SYJuh+ZjPeTikhNZqqPaFoTAeTSr9aGQxq4L6KqCK42FQoiPNdhGSN4AL3YVFx0Igq7LsVEDl02TT0Ukkz5W4ipSucFGEHQdcbFSkE56ZC3n1GYlIBRZ0+XD+EOD8d3fB6t50ZLmk23pEHR7I1IFuL63Ug8jXcpzeRyakcsYYytqUoAM3MRTTkJFGrVtRuTTTdZmgN3H9RU6Kdhs42Qcm0UDA8dHTMa3PVkVmdPpOnYq2sgOTN4FwJrtcXH3xSf1vY4Fm22cNGVCTMSkGiKbOSbwXDtvEUwspHSLJKWzV25o7odvHd7Jc5r7aAbuxn3NRK49yhoyqzDGXdvKikMksso6ObIZGluRnik54KF0C996ZBcTK9Dbrli9POPKSx7kBVN72BUcxiBpyoQJGZNaRSA0csYQW59v7Tyfbz7vXO75/k7mvjHF5CMx/n6BSFJsTKE1HHPsgpExAFSxAkIbV70pqzTFNiZU6JZhe7RS/fl41aQ0LNBIBibAFznGisI22hGVSGYoLApLUyZOyC91tc2kclbLkciqNjttJOdFhzlnZpWDWzq09wWoZUdYhDZY38M2PER/OJo2xoiNiML1H7YsJuYwwLSb9C6epLtLkXUgnTYYD9RBBd89rq/QScFmGyebFU9UdXk8lCSmuWPxKbassZEQ9hgsMn7t137tmF/w93//9094Zw4dOsSWLVv40pe+xCte8QpWV1eZn5/nT//0T3nLW94CwD333MOll17KLbfcwkte8hL+5m/+hte//vXs27evyqX5oz/6I37zN3+TQ4cOEQTBU75vt9tlcnKSl7/iPQTaR0ceUhuC+/aPAqvKFqoxCM8rVvY9kvNmGWwJaB1IkImuLJmFtsg0R8Y51pNYKdETAcP5gHhKOhLQd+1lyaRCZZb2A6uIQQJhwNqzpzCeazezyr2ejiRGgd8zzqpYCHTo/qnEaU2sFLQfi/EfPeTEmuNZKuWxFCFi9slWTUriU1gVC09htkyz+NIpgq5F5gUB62n8bhHmaS0m9OjtiIinBZMPZ26blbhqzzOBIpkJGMyrwp3MXf+92BJ0ddFepgi6Gr+fk0z7xJOKoG+YvHWvq7KMfy7jtsnj+17mvJSVGDlqLRNlX3MYYMMAPdlguL3B0rM9hIFExTz4vt9mdXWViYnNsXoGp3+c3P+KP6PjNYHjJzAb3UZWVl+eblXlZJCY022bfLIITElcSpQEph4nDuU4+eR3L2KtMcvDyTz/469/hPM/0UUt9bADJ0YXUehu5Isp2Ew0Sba02PfykKv+0ff56S1fJzZBZScMsGYaLOctYuMz6Q1oyrS6KZe4yovTingoYTiQTfLf7n85yTdn0A2LevYaL97xKBc3DzLnr7HLP1JVbcpKjrayaMnK6ZuQFd3iO71d/O39l9C6tcnCrT3U8gDRdR0CeGrkPAbuscJe2Tac5kUMYmeHn+fgBwhPYVsN+pfMs+8fp/zGlX/LrOqhitW5ro7IrMdiNokShqZMkcIwpQYcyjuVzqVsIfOFZkb1aMm0MDlQZNYjNn5leqAwlZtb6XB2a/cCvvrly1m4xdC5ZwnRG2JDv3AiU04bkziHTaxzFKsWu4rHqmMugjiH21o8+gbB1c99kOlgwIQX09chX31gG3f91H+qx0mBcpx87U/vod3sVI8fa5glsOFtZGX15elUVf7mimtOiqnM6dC/HI2T0Ub22AuuXvf7Zw9fxs/v/ugxjZNjqsDcfvuxsdCna6O8uupE8zMzMwB861vfIssyrrvuumqbSy65hF27dlUD6ZZbbuGKK66oBhHAq1/9an7xF3+Ru+66iyuvvPIH3idJEpJklIrb7Trf/WCxh+c3MEELbzVx9pFFyr0riY+1LCnlhOO+gDQj2LOMlTMkUz5BVyDyItyrWFkzDUeMUKLIjSmsgxOLio1LpT+SEe3tIuKUfH6C5UudmLG9N8UqQbDiWtHSqbCovBj3PtqgI4+8qVCxIW8phjOS4dYQmc6gHjs05hgzRsTSzK2QjbdUHc1nC0eV0iKzFG/6fSfMR7jqidAWE6oRgQkkXmwIepKsrRyBWXWVHxM4k4LhjHLkLTbI3KJDJ2TNiyqMFYCArOWhfQECTGltXLZ+mcIOdNxm2vOcWYEfrA+nNHbkrgZuEgp8sq2TrF7cJJ0QZG2I5w3NvRIvPoYv7WnA6R4nmwUbRV7K16i1MU+Oo4nLZsfpHiffGFzIpAf39bfQWCwcJePE3QCX7Uk6H5mNxBnBcszCrZJvhJcy9aohz23vAag0LgADGVRtUMZK+iYsRO6pc+0qcleWdJv/3z3XYm+fJN6qufg5e7l69lG2+l2aBelx7VopfROyphsVkfFFzoRyF8Bz/CV2TR/hWc87wH8VP8TaYpOOsXhJWtgxj80bZsy9y7gWaxsFbp4Zz1Yp2rB1KAjCDIWhbwKUsEVI5WghKjY+k2pAR8VMqT6H8g4dFbOmI3yZY6wkAwyy2v9AaBQWpNO+BKLUdFLoaJwZwlzQA1t0AJhRxo01FqGzkWlO2f6W5y7guowlKBfCwoBs2xRLlzZY/uGYX3r+l7ggPEhqFcZKDuUTpAspm3EEne5xMo7jIS8A/9/PfIRff/3PHdffPNlrwdMjLwCv/d4t/OUVb6qdMZ8CRxOXEq+YvuOYO1+OicD83d/93THv1InCGMOv/MqvcO2113L55ZcDcODAAYIgYGpqat22W7du5cCBA9U244OofL587vHwvve9j3/7b//tDzwu0gy8yLmB9WN38w6jm+Oy/So3IyEjoRPR94eEjy7BLkdiZGad5sM4ZzPrSbJJ93jWcqs3jWWNDiQmFDT2DVErA8QwwUy3Wb60jRdbwpUcE0r8bu6cYXJDsJq61aDC7lHkBuMrl0cTupv/oO8mgNWLWkxai9p7eGSNWbWRFShEpetsmqFaZRKiIAGFnkakOX7fkQ63vTNAkMMcEyjAhXsO5hStRY1Ki37n0EPFMTLOSOYaNA/nBQGzeENNOuUTTyu82BIt5RhPYJVA5hapQaUWHYzt93h2AYyISpZWRgZC+Y6AjttdlhbLStK7bAtLz/ZIZi3N/RAuW1QsCVcsKZvPRnkzjJOLv/zTHHjlp09o/zdCzD8+MWyknqUmMU+MM428bIZx8oX9l3ARfR7rTRGs2lFoYqlLLFuSipR24XvIrqU5zNiRT/DZqecxe02PS6N9NGVCJDJi4aOEZUU2iURWtVZFIsMgkRgy6/H17oV84fuXMPXNkHgOzr90Py+ff4Bt/grzXpcl3eZQ3iGzyond7cieGUAhSa27/jvjgITnhHv5oQse4CvPeS7hSoRa7rvQyiLjparyS4Eow5SlE8PbMHDulaWdfXHdltqSJD4DEzLvJfhC0zchgcjxRU6nIFEledNWEgn381Z/lcPFMZSmykfydiXoh1ELGrg2NACsV7m0dfNoRGAKp09bWOiLUtMylo8jhMBiq0U/ISU0IvRsh5WLGjTfeoB/fM53CYvXn1W9yk1t2m887vfndGIzjJPp//CPyf7tX5/Q/n/8Q5/fEAKzEZWXcbz2e7fAjg15qbMST0RejhfHJOI/Fbjxxhu58847+djHPnbS3+td73oXq6ur1b89e9wqly36ckWmEcNipUCbUYuVseuzVwA7HGKNcVqT/pDwsRWiw6nTs7Q8krkQ3QzQkee0H6X20RNuNainae7p4x3qutWqdoPBuRP4Q0trb4zfzYgWh6heishNsW8ZxldYT2Iin3wqcuL/CQ9hXEVHGFcVEQYGO5rQiBwxKSfPciVsnLyoH2yTq45VqXXVjuGsZDirENoSrDn7Y93ysdLZQ+cNSTolyNqS/oJPb5tP1vbIpyLiLU10Q+L1NeHhIX4vQyY5MjEEawavb/D6GeGRmGDF2T57fe0ydAJG+pZy/8fb+8arZDBmSiArAabwFLbdZO3KbRx4iSKdsng9QTIFWVvg9y1ZU5C1n15F8WRgM4yTp4s3L3/qhFenTvaqVi3w/0GcaeQFNsc4WRk0WBx22L1/hmhVu5vhwMdGwUgsPu50leWINEOsDWg8cJiFL0v+150v4uu9C1nSbQY2rFq7OnJIRw1dZUZkrJmIfek0dw138OFHX8pX/vdzmfuKa+PJLhnwsvkHmfPWmPe6GGQV/DgwIUt5m4EZaTqMFaRF+5Wxzhwgsx4Zisvae7noFY9w+Aof025Ump6qFbnMHBMC4RXViVw7MlBqR7V21vzDhPBIhlkOWcpblfWxYlRF2VoQro6MURjWTIPY+m5/Cme2uNC69IvAyxXdrIhLRXyQlfFBZlWRo1Ms0BWty+Ta7as2bn/jBBvHTruT52P5Li7DR3Ra6IVZhhfMsvjiDsmPr/Dz532ZC8KDzHvdikg5owVRBY9uJmyGcfLuTx96Wq/7dDJbXvLGn9xw8lJi8NhW/uS8zefcdbqxUeQFTlDEf9ttt/Hnf/7n7N69mzRN1z33iU984rhf753vfCef+cxn+PKXv8yOHSPaurCwQJqmrKysrFsNWFxcZGFhodrmG9/4xrrXK90yym2ORhiGhGH4g09IiYk8ZM9duKpgRFXkpWS5S3hPY2c1bA0gq0wWawyi2yMYJvhHmgx3TZI3JFiXkaJD4RJ+jSXsGvxujn+kj1juupYC3yM+ZwIstPa6SoVu+JBaTOShGx5qmCPTHBMqBgsBwZrGCkEyJclDQXto8GJN1laE3RyEx2Be0ZxuIfuD9WFlSjiR+3jb2LhVdFllqvzuneBUrPVpHdQkHYWVgqx5+8KqAABKBUlEQVTpYYKiWpJZvIF2wnzl8l7iOUHWseRNn4ndLuTTX9N4/QyRuf3RDR8dqeK5DDlIi+ciVGbIQg/jCcKucT3JZfXlaG3SuDuOKFrGAh9S43rOlcJOtjl81QxLl0PjoMAbUmmH0o5A+4JkGhJ/c1VgNss4uf8Vf+b+7mkK+I+3GvN4bmObGR//0OdPuw7m6eBMJC6wecaJEHBwrU3jnojwcKGlCAN3068NNo9dhaLUjJTXZWNgGDN1xwoqmeSzV1/NF571bF597t28oP1oVaEwVqKERQrLIA+5Y+0cbr3vfCZvD5k9YEg6gpUrM1587m6mvb7bzoQc0e0qyV4KU4Vgljf1xkpCkRWEwj3msmgUkch449bv8r5LzyG/LUTGKSLJigDkoq2qdO2E0eJYqSMpXcvyHAt4q0OiAw2Wc1dRSoUikhmx8Ss3Ml/kVYgn1onxV3UTbaMq4DOzijgfkRY9ZrkM0NNRVZUxSLAu8DI3imC1yFzTBhvHrl1aCOxg6IhWELjIgqJ6j3HB0nq2Q/eCFisXSy76Rw/xo/PfqwwVtqhBEcA5+l5IUc8nj3vfBbz3FS/lYzOPnvCxvOSNP8lbb3jNcVVjxonPyXISe8tXP83PblAlZtsvvZ/9f/CrG/NiJ4CN0L9sJHmBE6jAfOxjH+OlL30pd999N5/85CfJsoy77rqLm2++mcnJyeN6LWst73znO/nkJz/JzTffzPnnn7/u+Re+8IX4vs8Xv/jF6rF7772X3bt3c8011wBwzTXX8L3vfY+DBw9W29x0001MTEzwnOc857j2x0xEznFkpUjmNXpd21EZZuXSiwvtSCkQt0V/rLXuQn5khcYDh+ncv0a4lOANNOFyTnQ4pbm7T/OBZYJHDiG6ziEFT5HunCWZ9pCZwQSSvBMSbwnR7QCZ5uhIEm8NSeYa9LcHro0rMYWLlyCdFGQdhfElwVph21wUj4bbWgjfH+1z+X95w18GP5YEx/NGPvfCkavSmc0aQ+NA7PQiM4rueR7JpLOETtsSq4TLvFGQTghUDI0DgtaiIVjJkJlx+qA0x0Q+JvTQDYUw1rWL5QYM2MBDDDNEasBC1hRES0e1YZQCfhjta6FtqYhNklSfo942w54fneXIlZbGIUFnt6G9T+MNLc1Dhs4eQ7RiCte44/r6nDRstnGykXiqakz5/NFtY5udvJzpOBPJy2YbJ9bC4L4ppu/T+MvDatHFjgn3MXaUrZLnTpeY59gsQx5ZYeKOQ5z/10Oan57gE7e9kD957Bq+cORS/vbIZXy1+yy+vPosPnXg+Xzkzmv47t9ewpabA2buSbESjlyluf55d/Ly6fvZ7i/TkkmlyZDCMKP6dKSzZS6zZBSGjhoyIYdMFFUPXehs1nQDX2i2eF22b19isCVwgndwbdS+X/0DRtrEsRMilCws/YvqR5zRecTynSM76JuQCRnTkkllAw04XY/xq6rKjNdjR7BUtZdJLFIYDKKqerhjsZVwv6y8gHM50wgUht39aVr7LH43dYuLfhFIWVaLCsF+dUzGzY920pGX/a/UXPuG7/KP5u7GF9qZAwjDEe0CSfsmLDQ4ujIoON3YbOMEQP/W07+ef/xDn3/Kasxjz19ZV3WBk0deNhq33XLmtjc/9oKrN5y8wAlUYN773vfy/ve/nxtvvJFOp8N//s//mfPPP5+f//mfZ9u2bcf1WjfeeCN/+qd/yqc//Wk6nU7VOzk5OUmj0WBycpJ3vOMd/Nqv/RozMzNMTEzwS7/0S1xzzTW85CUvAeD666/nOc95Dv/kn/wT/uN//I8cOHCAd7/73dx4441PyPafCEZJ1MHuqE+3TLrHVkGIVptR8CM4UTyMWpnKMrNUsLyKXO0hpeudrTzyCzcTSjFn4KPnJuhvD1Gpm9jiWZ94SqIjgUo8RG6dxiXyirYt41aNjHMAEwbCLqihQWbGtWu1fWRmCFdd1Wdd6xX8QHhjlf+SZo6wqKK6BCC8agIWQuAd7IJtkUfQOGzwe4Z0UhGuaGRqsFLh91wVJm9CuGJRQ9cCp3CW1boVgAUTSIS24AvypkTFHiLTlQWnzA0qMQQ9S3ig50SU1oyMFURByLIcW4aJVceDs0mOImy7weHnt+nv1Ezeo2gd1K5dLdb4Pdf77OcGE0qEBu+pjVROCTbbOIGNt08+1tawmricfJyJ5AU23zhJH20z9wC09g4hSd3cIQQ28rCxHHOEdNf8yiylgI0TSFP8LGd2rUlrscPK/E6OhJA3BToCmbj2p9meJVrK8IaavKU4/FzBy59/D9dMPEhTJkUeSk5LamIbVJULAB+NsYJBYQYArjpRQhctZyUB8HXOtlaXR5tbsX6xeFRoCtehFL6PtY6hFCKUbo6xFtKMiUdiHnhwC/cubOMFzUcAaMkEbWX1T0oDRaVIYVEicxWkQqdY5r1MqgG+0JUbWWwd8Sgtp8ufjZXE1ufBx+bZseYW74Qu9vUHsm2KvJc8x2qNaDTIJxv0t0kue/ajPL+zm6ioWHXksGpl84XGFI5nEsNK1jyu78/JwmYbJ1f/hx/itz70Pzfs+I6npexMIS9nMt56w2vgtiMn5bWPm8A8+OCDvO51rwMgCAL6/T5CCH71V3+VV77ylY8r0noi/OEf/iEAP/zDP7zu8Y985CP803/6TwF4//vfj5SSN7/5zSRJwqtf/Wr+63/9r9W2Sik+85nP8Iu/+Itcc801tFot3v72t/N7v/d7x3to+LsPYXNGdrylnmLcvau8IJeVi/EU+/KxLAc1Vt2g0GKUNsYlwfEKJ5lOi/65baS2BN0cNcxZ2+mjA4HXt+QNiZUBOhDkkcAKD29gkLnBFm0HxnNVD5UaRGbQoUBohTBglLM6HoVxFqtfZWAjjATwZTWjJDdhOGZX7FYJy4l47ntDjlzeACFc8KaxBMsJuukjcsPE7hyZWbq7vJF7GK5a5KpMxX7klryjSCYVWUOgEoWwAcZzxEv1M6yAoKsRqz1sSV7Kz8Yat0+l0015HCZ3E49yFaT+hdN0L4BgWdE8bPCGhnRCgQCVOOIHQGKgoxhs2xwlmM02Ti7+8k+f8LE8HZyJ5OV0tZGdqIXymUpeYPONk623Wqb2rCKX1wB33UNrlw9Wtr/COiMSW1X0yznILczIpTWa3QGNh/x1oYquWq5ci3E7YDgXcPAqyXNfdj/XTX+fKTXAIEmhqmhMqT6Z9egX7U2J8ZHCVG1WvtCVC5gUhlaRrZJaj8T4xDZgOWkiy/Zj6xbHbKO4cZXOtMYtjjEyLyj1PiVRK7QyXjdm4r4G37liBzNerzIVMEiW8jZ+EV4JEFg9nuZVVVwm1QBw7WPOyEBVVZayRQ5c9UXinMm+vnI+re9FNPeuIdfiat+qToQShfmN1UVIZadF79wma89PeMnMw7RkUp2vskXPF5qOdK+ZWsWqbpGYkXb2dGKzjZPf+sONIy/HgzORvOy96obTYqf8dNrH3n+SyAucAIGZnp5mbc1dkM855xzuvPNOrrjiClZWVhgMBsf1WscQQUMURXzwgx/kgx/84BNuc+655/K5z33uuN77cfcny0D4o5UxWEdCAIRShR1kQXB8b/3FDkaPGema9Ibx+r7g8nWNwcxOsXrZFCqz+D2DDiRZO0SHgun7U6wUdHd5yAyiVUO0rJ0lcTfFhIqs7SFzJzpf2+ETrHmEq84hzPgui0bmFjVwIkQhBIT+qJqSj7VkeaM2seqcjJsWZCMnMptr/EcP0dyyg7QjyVuec0MLnC7GenLMRQzCrquiyFRjfYXFOdWkEz5ZS9LfKuk+P8FbDGgsS7y+QCauwmRCDx0pWg+tOG1SMZGQZtX5FiWB1Madf6kciTTaWSUvTHHwKg8rLFZZ8sgROeODDp3pgNTO2S1YyRnMS+Lt2dP+Tm0ENts4OR04E8lLiTNdC3OmYLONk/ZDXWQ3ww6HCM9zAbs4F0dgncW7c0V0FXprLGBGNvAlshxR6P8qolO0NwlvgrTjs3i15MqX3cePzn2PCRUzMCGpVbRkyqF8ogq8DAor4bLi0tNRdaPfFDkDE45S7wvxeSlCT4zP4V6Lhi4qR54C3yOfbKCbHvGMhw6cRXLeFDQPGqd5jLXTcA5SGLrXEtoghilzdyTcvvAsJn845rL23sphrRTpD0xQVF8Ms14PychpDGBCDqvtSw3NlEw4pCdIitaz8niXdcRq3uC2b13Mud9LUYdWscMYfN9plMp28TCs5hWb51U7nOlEdM9X/Mgld/GsaH/VkqdwFtCRcLqdMqNmQsUEQhPK6af9ndoIbLZxcjpwJpKX04WXfugTfPwE//ZkVl/gBAjMK17xCm666SauuOIK3vrWt/LLv/zL3Hzzzdx000286lWvOhn7eHowTmLKSoyQONW7+9naHJE53YvwjmolE2O/+8VpLqsaJUGIQgbnT+APDEJb4mmF1M6ZbPLhDG8tAwHNw0UrVepcxdSwENdrS94QCOtE/MbHtWR5bv9cOKYk6LlqDUK4fc1ztw9hgG1G2EaAboeYQJK1PKfXObCG6A8Ldxn9A+0O4JKVO/cssfz8WfoLHs2DOcJC1lGkbUkeCbzY0lgy+D2NCSS64TsnNSnIJjysBC82ZBMStEA3HLkIBeRtV8kxoXTtcqu99RffcSKpNSjfVVuMddYyZU+zEAy2R1jpzp/MBXlkUanLskk7Lhi0eVhjBehI0jhiEF2Px07CV6vGmYm/2P3fHvfxt+z6+VO8J0+OkxVgWeP4IIapu0aVC0DGFIntYpQDY+1o4ahsPy6r9FY7LWARIGyNGXUHFK6RoghQzKYbHHqex/OuvY/Xz32XlnTuZCu2yZpuYJCsaWfjWwr3gUobUrWHFaSl1KGUVRpZaEkAYuuRpB6RFOjIQ0cTDLeGHH6eJLsgZn7mCEnmMdfu0/Fj9vUm2bdnmuBgSGtfSHt/RLSYIOMcmWSQ5fhLMfPf9vnC3KWYywTPai26PBqZO22J8QkLl7LUKmITVee5fAyczbIpAjkjkbn2LWFICqeyzCr2JVPcsu88tnwTor290Zw2bnBTnmsoNDsF4fJ9eue1GWw3PKu1SCA0CM2KbjKlBkWWjaElUzSCzHpEIqOjhvTzTdKTXOO044kIVHPH4lP+7amuwjyd+eRkVl/gOAjMnXfeyeWXX85/+S//hTh2pdHf+Z3fwfd9vva1r/HmN7+Zd7/73SdtR08JdA5eKXR39smi6H+tWpaUco8L4VbNrLMsBgqHkkJ3MZ54L7wihwR3kQxDRBQSnz+HDgTRkYx0ykNlFhU7rQuAVQITKNTQVHkoVkE66eP3BcJYvKEla7kASOML/KFFpRavnyO1az8z3piPve9Shs1Ek/75HQZzCpmB8UHmoAOnT1HPCgjWLJMPDvD2Ljk3Fs9zK1FjxE4sd5n6vsehq6YYzHu0DmQYT9DfJvH6EKxZVFIcjwDrSWRukJkG6+ENDd5axnwOS0mANwBvqOnuColWNXnoHNya9x3BliFYaqw6Vi7CBcXnZpyWprKFlhLbjBjOSvKLhoRhhrxlEmEgDwV+3xB2tQvKHCN/QdfgDTdHBeaZjtNZfXki0vJ42zwZkTkTqjBncvvYZoQo3CmdJs8RDesprBIIVEFKRCUQt3E85q44nndlsKke3VBXGkwXoKinOxx+bkT04iP80Mz9rOoWh/MJ5rwuK9rpLtIx22FfaNoqxljhKiyIqprRlCmByGkWbVGRyMhwLmSRyIhUxmI2SZZ4BH2D9SXLzwpJXt3lHc/6OvPeWqEBCdjqrdKSKXuyGfZsneE7yzvYc3iK5I42054gXM7xuxKReSCh8+gAbmpyc34p8vmW7dEKW9UqGsmcNwo9jI1fuYspDAMbMDBhRbAy7bJtMhSzqseBfLIgZoLVvMEjvRnib88w/2AfESeFYY/FYorPTBZksZhcyuw0Y7FTDdZ2Kfzta0x7fabkgBXTJC1a8jLr0ZKJq8AU+puBCembkJVs8+XAPBNxOqsvT/Xe488/GZnZe9UNvPWG1/C1G35iw/btTMQxE5jnPve5XH311fzzf/7P+amf+ikApJT81m/91knbudOG4sZYlJNIeYGzFlFaIR7VWgast/OtbqQZObEUJX9wuhcTSBqLCTpSYMHrG2SR3ZLMePhrApUadEOSNQReYl1oZGJJJzyigwlCW/yBwYshjyTBao430OhQkk66j1dm1pXtjcE2QrLtkxx5ToTxBBN7cqwUJB2JMNBa1OhAYDxB2hEsXt1mYiGi+WgftdRFQBVQhnFhZfLwKnPfkRy8eoL+Np+sLVCJIy9ebEgmFSq1qMSlHAPkTd+1uCmBGkr8Xs78tzVWCXRDOvF/JMmagvlbl6HbGxkO6DKMc6zSpQ1gRm0ZfrHaVdwMyBx0N8DO5XgxhF23+pl2JCp17Xt5U5I1JcK6cybspolJesZis5OXx9v+iYjMqSAxdfVlE0Gbwsq90E5KgdAC4qyqwohSc1FiHXGx60iLHXP0EkU13zYjehe06b4g4Z+d9122+iss5W2yQndRCtYjkdIjcpkpatR6pTA0pbM49oVmQg6d6L9Itc8Ku2EsRcq9cL8L0L5g5aKQ6McXefP2u7g4XORgPsHABMx7ayhhK3K0JVjjBTN7uKBzhFujXexbmGDq+wFTDwm8nlsoksOcziMD8lta/H3nYl598d2cEywzIYfMqB5Luk1sXSUlksMqvJOyIw/LwAQMbFAdW78S01v2JzNkVnHft3ex45sZ3urQCferz0tXlTDXRqbcomO5GCnBthsMt1rmJ/oYK/BFTmx8WjKp9DYAsfWd8xiWvgmIrU9uN4cG5pmMzUxeHm/7JyMxH//Q5znnJBOYp6N9ORmuY0fjmO/QvvSlL3HZZZfx67/+62zbto23v/3tfOUrXzmZ+3bqYawT4GejKoMtBIi2sIB0JGZskim3G6vQYM3jExzhLCRFI2Jw3oQTkCuBjpS7mfcEIres7QpYO0cRz3jkDcVwVqJDVyHwYmdBbHzBcFtE1paooUYlFi8xWE+QNxXxrA/WCd/9ftGKEIUML5yle25EsOZsg0XuWtOCvqFxOCdYzQlXNVaCCQTCwmBOsXJZh/5lC9h2c+TwZcYmwsUVtn59lbQjGGx1ZCXsarKWRAeCrOkqQemEz3ChQfe8AOO7KlLeVI7EAbohGcwprITW/oT5ryzCgUPunJdON0qtX40cI47VJJ/nRauFE8RaCa2HPewdE0XApy3CPp3BQTLtVkZVasmaYHyXB1PjmYnjJS/H+rcnk2DU5GUTQ5ZVaxeSKJK0suitKi7lYkzZdiZEcb0r7PuFcAGKavR3NvBYvUDx/At2c3njMVoyKWyGjzDvdV0IpBrSkmkl0G/KhEiMfne2w6P2rEP5BKlVVQaMGVvIUcLSlCnWCIZzkpUfGfJPdt3KBeFBJKao3qSVqD02rnKzI1ji+a3dvHzyXn78/Dt42dV3s3KFYW2HT952lQphDCLRTN03YObzDT57+3P5/mA74MT5HTVkSg2YUn1XDSoyV/wiKyCzisT4ZMZjVTd5KNnCYjaJKrZZSlt8+rYr2f5lQ7R/gIhTN9d7CtGMRlbJ4MimkogorB4XnkI3fbyeC6Wc99ZoicyFVlamB5a+CQvSmFXtZGqd9UCNZxpOlDgNHtv6pIteG5HNcrJee8e3v7lBe/LEOOYKzMtf/nJe/vKX8wd/8Af8+Z//OR/96Ef5oR/6IS666CLe8Y538Pa3v/0JA4zOFNg8x3qFjgIKgaQ7RSVpEUI4TUtpS2wtWGexvC5UsbSN9LyR65h1Tlmm3aS/VWEVyCxAGCcex1riOZ/ViyFrG7yhwB8IGodN5ZRlPEEeyeJ3S7jqLJQtLhzSKoFRrjVKGIvxRGGzbEi3T7B0qY/QEHRdlcEqCFZzglVHCGSSI6xH44hAGNBFm5U/MCRTiuwFW5m4dxV5pDtyZsEZIMhDKyzcIjl4dQfjC0fKhLP5FAashGRKMdjqqj3NQ+64kxlFHrkqibCWaNnQ2jPA27dUGCs4++qq97s8v6U7HIwC06rnxla7lKvo6BBUAtGyJW1LgjVDuOoITh5KZG6r/fIGhuwYxI41Th5OR/Xll3dvjNf+k1VjNroSUxOXTQzzONeQoysupTaycIgUhVZx1Ko71j5WWt0riQhD0umI3sUZV03tBqBfZKYERUuYwtKUiXPfEoYZr8eM1yM2flFRkSic05hvc5SwrBkfrSVBQQzK9rI13aCjhhzOOmBh5fKcNzzrLnyh6ZoGGklqPXo6qjQnpZA9ko5wKGk4PzyELzSLl0xwn9iODn06j0nCwsJYppqJh4Zov8FnWlew5Yo1dvpH6MiYAJe1ooUgtr7TusgMZS2LyaQLsbSS2Pgs502aMiWxHn+77xJ6f7eV8+7IaOxeccRl3PGtIJi2rHpZg1XK3QvYIv5AKWSqCZdhpddkRTdJfVnpbAACkVcGA7H1aYqEGNfyFucnlBteY4Nwpgr3//g9t/PH73niasxGa2JOJinaaBz3iGq1Wvzcz/0cP/dzP8cDDzzARz7yET74wQ/yu7/7u7zmNa/hr/7qr07Gfp4SiDBEIAtL3uJBzZj9cFGJyYoWJjtykanISyX4L/4vM1XKaoUQ6ImQrC3w+5asJZC5S7AXxrJ6vqS1xxJ2IVzNMb57zt1cW1Rc2jZDsJI7S06c8Nx4wulNPIFIwHoC44MaZFhf0d8W4PUtMqeoNAikdm1ceUPhD9yEpQY5xpM0DhmyCY9gJcd6ApVY+guKeGqK+W8r1IFlsBk2zdwFH1B7D7Ntqcfwglm65wbkTUG0ZAiGhqwpyVpun/w1S3+LQmWQN0DF0NmTEDy27JKds6wiL851bCyTpjzfValfQFo48pREU8miKuY+yMYRgw4UQde6Frlisc1KULGrXokcVKxRhZ1yHtQEpsbTw1/s/m8njcTUxGWTI9cgc2yuEUFBRkqNizbYNB1tW1a0y8WscZTi/up1c4QKsI2Q3jkB23cd5ILwIFNyQNdEZMKrKigdNSyqKx4dORy9HS5fZWBCpDBEZK7ly4qqWlC2X8miFUsjWMwmuW1lF36Uc+l5e7mq/XAlWAdQ+OsCI4FKPF9WTJoy4fzwEHLeMhv1uaVxAfFsSGuvorGsCZcz0JaphxKEjfh/ln6Y71y5g6unHmFSjY6h1Oq0ZMKK9ohkxpp24v7FdIJb9p3HypE2atlj7nY45+5V5DBD9IejxS5rK3tna8x6R9HSZKHIPkMIRKbxBtY5RwvDwIQoLFNywJpxGpfYBmAoyFSDNRPxSDzL4lrnBL5ENc50bBRxerKWsr1X3cDMO+6k8YtfO6HXfumHPnFGzidPa0ngoosu4rd/+7c599xzede73sVnP/vZjdqv0wKb505gX1ZPiptjW9j1rmsdA7eKU/ydKO2Fi4lGHF2JKasCUiJTTbRk8YeGoKuJZzzSjkuxlzm0Fg3hSubyUZqF6DM3VZuVSlxlBQEy1ZiGh0oMWce1FcjMVC1pfi9HrcWkCx36C5LOHo3KLFa46kjSkchcIVOL8SSmEziRfVLYexZBk94wxxfg9yVpR7D/2gm2fU2g9h2pzg9aO6F9ltG4c0i0p0O8c5JswsP4LsPG+OANIOg5A4LmgQRveYDoD4vgtmz9BJ5m7tyV5GVsBZLcjLQw0k0+VmtEYbSAKMSYucYbGrK2KowKXKuYlUVVK5D0tyra+zQmdDcaKjP4a7WI/5mEsvrydNrHHg9PRmKA4yIyZ+Ik80yHUHJ9QGJZuX+86gyM2snGWmPXzT3SGchY3yOZkOxsDFjwVmnKhNQqTFFN6OqIQGgy6+GLnEiKKs1eYpDCIIX73bU9uffIrAeWwkVLMSAoCEjO4azNo6vTBEHOrtYSmfXQONviqHAJC2W2zuK4KVNHgKyswjPLn6+c3A3Pgnvn5jn82BTN3R6TD0uipRyvnzN9z4DmwZC7H30237zgQnZeeIhnTx1ka9hlzl9DltWjwhb6m8vn8sjSDMkDE8zcCRfuSfC6a875MnFRAqSZc9YsncXKcywLw54ibNqdKAlKQJY54phpZA6N0JGxrokwyKqVzReavgkJhKzOyYpusjeeon9ocwRZ1jhzUZKhz5nf+4E5Zem/Xw7/neOqxpTVlhO1ST4ZeNeVM/DdY9v2hAnMl7/8ZT784Q/zl3/5l0gpedvb3sY73vGOE325TQEhhCMlRYuYtYVOoizpg7tJVgq0RQTlMr6tdCHjE40theWA8INRa5pwgnyZW9KOQvuCrC0wyrlgldUYKAiEdDoZYR3x0KGonM9MoEg7/iiEERdqmTeVc/g6MoQsJ2t7tPY7wmQ9QTIp8RKnpUkmFNGSJm8oZGaQuXtd4ztBvUzc+8rM0jyYE/Qk3XMVh17QZtaX+I8eGjmEFS1zNsvgyDLR0iqNMCjO6VgfcEFMbOJWIS2M3F4Am2YVKaxElCVROfoGQJrK1rr8jNw2LghOpBnBUkrjsMfKs0BoS2ufa3ET2oJn6RRmBjoc9XuLQV2BqbExeCISA5uHlCysXlY7kW0kpHDuiEcTlVy7a5QU6+cLWzhVqrKNrCA95XWvrDYXGhnTDMg6EKms0LVolDA0SchweSipVazoFuByXKSwRGRVxosT+QsikWKEawGLjVfoWFzmS2YV2kp6NuJL+y9iac8U0fyQhspY1U18kTvRP9YFSQpbkSGnsckJina4shozMCGTasCUGhBN5Tyns5+vti7kvsYCuhEwfbdHKzWoQUZjcci2JUl+h8/KBQv8/XkL5FMa2cowsQe5AM8iUsn0dyXb7o3xDx5GDIrMsDJ4WpuqXUwEsjBWkFUYaIVyO2vdZzWmOQLwEsvBgx12nz9HEC4WttRhFfgJjqCleGBcxs6+3iSqV4v4n0l4++9dyR+/5/aT8to/Kt/zhHNKSUrGF+K2/tQ/BuADl7+Vf3Xnx3n51zZvNfBTH/3CMW97XARm3759fPSjH+WjH/0oDzzwAC996Uv5wAc+wNve9jZardZx7+img1JUWjulXBWluPCKMnCsEbmbazV2oxv4oypLYZPsyvyMVtKsAVwivBXuJtrraYSFxqIGJciaHiZwVRMrRPXpWAXe0GXF6FBifImKixUuJVi6xCNvwuxdGlEQIL+vnVg9zUBK4inlhOvakrdcJcJZL0O44lLorRJkbYVuSLQvSNsSHUHzkMEf5IjC3jlrKwrjGo5c0WRWbMF/6IAjLTDSn9giwRjcClbZb1z2fHtFa934iqOR1Qpj2RM+0hVJKt8JqSAQo9wdz3MraeNOcGXlJknxujFT9yvyRsRgwZK1IO1IZB6gUkM8qRDWfS4qdhWYXNUi/hobhycjMTXOQpQ3x5Kx1mJ3zbLWuhV/GLNOli77pdyuzIQptX7SjG6kjXEBvw1oeSkDE2IKYXuM79rApNOt9HSELBLrp2SPKTlACUNsnXtWJdg3smofK4MkV02zqqwcSdsc2jONv6Iws07IXt6wd2RMZhVNmYCBFG+dcL0kLuAsndd0xFZ/ldQqZrweHTXkBdMBM+GA28JdrA1aeIlPpC0qzvFWhvgHVokeEiwohW0EmEAhkxgRZ9jQZemIQeIcK7XGFiGUQoyFSBvjSGXx2dgowDR8TOA5a//i8xC5QcSZaxcHR3CK1whWc4KDPgfTDlc1H64yaGLjs6YbxNYjE86uOjEtJBYljbPor/GMgGv1+jx//J6Tp7v5UfmeJ31+/VxT/Pw1+Dibl7wcL455SL32ta/lC1/4AnNzc/zsz/4s/+yf/TOe/exnn8x9Oz0Yb/kqBeLFTbG1FgFV/gswWhUD978snitbnKDQaxisMIhcIwcZ3tAFNPq93KXTK4lPjlzW6IbnBPhSogY5aujcurAW4wcEq+5vTODay8JVy2CHJZ6SSA0qcYL01r7EWSe3G+QN8IaCvKVY2+G0IHno3L7Kio3xIJ6RJFMCoSGdtEgt8HuSSAinrbGW9u4BzUVXhYq3hKztiphanUIeXnbnqSQVld2yLkJgxgJBlRjZVlrr6viVJXIxkVT6oyLB2lOO9JTnuvzbXLvjLD+rsfaLykGmP8T3FZ3HfPKGon9xyrm7DnMk3U57L2QtQfOQxngCHUmEVlhd2yg/U7BR4v2nwqkkMWW7wbGEo5WoqzAbiPLapHURXOlW/Cvjk7Eb/Grx5ehqTUlqxg1LiteWqUYNYah9jug2C96Ky2CxIalVKGxlO1wSGCkMgdDVTXdHDquwyvKme16sEYmMA/mky47Rbts7l7cR7fcQOYRRSlu5qnup+YhtwKzqsaYb+CInsSGTql9kowxoFdkysfHpqBglTKW78YXmwuggW4IuK2mDe45EBCuSYEWiYirSJpIcm+fIvo8MfHdOsxzRHSMmvu/mAq0BBVGIbYTY0Md6EhN6LrS57TGcUaSTgryIaLESvCGEy67bIFxOkL3ULQR6CutJwsNDJu/3+fyFlzJ96YDLGi7uuFm0sg1MQFMN6ekIjaCpErY1uzw6W7eQ1dhYPJXV8kbirTe8ptJudl/5Ov73T/3SU/7Njm9/87jtlO9+3gu49LvfPqZtj5nA+L7PX/zFX/D6178epc7SUuh4n7HW6/uQ5ahtq5pMxl3GYFSZKYMvxcgCs2ozE8JdDIvVfgDT8FxLWmbIJgIwFr+foSzoUDmvegsyNwQrCVa5Koz1RKUXiRZdpoDMnT4mXNVOW5Ll6MgDAf7AoANHTowHg50CvwutAxqhcRkoxXN4oFIBxoVcmkA6v36LMw7wnQW00BZhBf0LJ+is9Z2ORRx141+EfpbtYngFeSkJjtauojIWGGq1cUTR8xCNCD03QToToQNJ3nD2zkHX6ZRUrFH9DLk2QPQG7gah/I6Wn2mWI7sDWo8KhGmBCNjTXSDyYDjnKk266wI48xZEhxXBY7UG5nTil3fffVpzYE4WThaJeSKx6OM9/mSTXk1iNgjltad0u4Kqdaz6ubThlxStS2WrWPEa1lQOlkWjbTGvKOQgpXHIsq83STznE4mcFZpjafSuMjKjegRFK5cvNAEFkbHOPhkJgXWZJQC+yJlVPbqmgVGSUGbsTmbZffcCUwcL4xlpiGRGU6ZMyKELkbQUhClH4/6udAjzRc6EjOlbl4kCrhKzopskxqetYjpyiC80WxtrPLqtR29tgtaihxrmCCVcxcoYp2GhaPkuMnascYuDRYDb6LwDNgww7Yh4LmI479E7RxDPG4KdfRamukxLTcPLMM7Ch1h7HOy12fPgNO1H20w9mNPY18f6bk4RiaazJ6V/R5uvzl3IhTsWeW64l47M2KLW6Bc5NHuzaQySvgk5r3mEB6ZbPLrx37IamwynilCUOFkk5vq37Vv3++oKXP829z+fgOvf9ubqud99rPOEbWknQmKOFcdMYM5kd7FjhtEgC12LsaO+4zLbZUzcX4rFK5E5jPz5x92yyvYAcGXtNEX4HsFqStbxEZlhuDVCxYagmyEzg+pnqF6CafgII52+pdCPCCRCO71KMqlQmUXkThgvMxzBoHAtG7oVMh15CO0yZJIJF5oZrFnypnCuZJnFG2rSTkDYtYRdy9oOdyOvUkdojCec3mbSI48ka+dKZu/MQLjJdziraG6ZQu05SBUboArditGOvJTaFa1H50hTbQOMrEQ9DxFF5Dtmieci0gmJN3SaHeM5FzWjBPiiMBpQiKkQGU+gBilikCB6A/cRGOMmvyRFHda0coMVEwitiGetO6sa4ml3zMmcJlxSDLaepUS9xjqMV182WsB/qnAiIWlw6ifbZxSkAMYqxSWKCn+l8aOoWpfkxRqsEU8s8i+ry4OYzu6Uhx+b5dCODhcHB2iJFCUtEsOKGelTUuuE+5HI6NugEtmnKGe9bEfp9kDVXjYwAcZKHu7P0jggiZYNWUeQ5k4n0ylcwZxwPUdbgUY6G+UiMLMl3TwUiYwV46oQTZmghCFQOYdsxxEpXPjkjN/n2fMH+U4vpL8QEqx6eCuDkWbF80ZzSJmlYww2jkfnLPARzSb4Htlcm8FCyMGrJeGzV7l07iA7mits8dfoqJhJ1a80Qa51TnAon+D+c7Zy18o2Hnhggc59kzQOWhpLOcFKhtfPmPueYm+4gw+9+BW8Zee3ubrxEC2RkeKycyKZYayk48UMTMC2dvfpfZ9qnFF46w2v4e2/x0nTwZxMHE1engr/bscar/7YHxxTVWYjUXdljsFqA8IlHlfiSilGE4uiICsaIYtTV0w4R7vGVNUEGYweL2/ekxQ1yOjvcHVrb+gyW3TR0uWnbhXJhN5o0U07u0fd9lCDzOWqKIEcONF9tGSdKF+BPzSE+3oQJ6AUKs7RYUR/q4c3tHixs1AebLM097uWKYTT2vTnJN7AYgJoLFqiFctgTjqx/7Rf7Kegf65GaJ+JR131RqWWeEtEc7WNSFJsnLiqix5VsEbny6082jxfpyWq2vE8D6YmGJw3hdAWv5fjDQVeP0M3PLK25zJ0tIXMogr7Z9ceoNCNJsw28Xot1FqMWFkbGQjkILsD2vdbwuUma7tCkinIWuDnlmBZ0FiU+H3LypYN/XrVqLHheLoWnU9EZBZWLwOoKzFPB8V8grXuOljqMUoDEjWy5gdGxjHrLH4t2PwojWDx+rkmPDSg+cA0Dzx3K1c3HqpCHWPro7DO9cs62+QyGR6o3MiwqqqIlKnyEyomEhmzqofCcES3+fbunWx52BCuaHrnSEI/Z97rstM/gsLSNc6+eMU0Wcwn6ciYSKQu/6TIpenLhNj4zKqey07BVXFmijlgYEI0kgkvZnujywOTQ+KZiKyjCBelIyuBj8ARPmtM0XpnYRg7EliQHKE1NBvoyRYrFzc49BLNK5//PZ7f2VO1eilh6cghLZm4qlVxYlOrOMdfZsFb5ZLGfu6Z2sY9F2/l0SMzLD/QZvr7Hu29KUE3Y8u3Ybm/wB8890d43SXz/MT0t9iqekTCMK/61VdhSvURMwM+s/HfshrHiOaOxVOaBfNMIC7jsJ94M9e/7c3c8H/99Q90GJShlhtdiakJzBjKFbHSdUx4vpuECh9+obXTuFTuV2JdO4At26IAYbLCxSxZH3xZbCt6Q4Jui6yjCLoaNcjRkSLreAjbQA1z5DB3zmO+Qjd81CBF9V0blrCWcDlHpYZIulYu4wuUgOajfeRav7rAy0GK0JZ4VtDaZ51FZgTRIUFnj3YVlBlnBFCSl+EWg/ElwZolWjF4Q4NMjWtZE9B61MPvOZc2aS15JImnFVErQqVZMRnr0SRcGh1A4apTCPW1LiyQqcT4zEzSv2ga4wua+4aFA5p7LeEr/LXcta7lBlHaVucGMcywSqAbflWVMVva+EIglrvOUrk8J0CQpMwsh5iGT/+cBlnLEZfG4ZzlZ/mks3V68unGyW4jO1Xal6OxEW1kGzkZPxmRqUnMCUIbkMYRlHHHscIVa5y4VBUaM2b4AmOLXyNDGYx1iz9SIoYp0/drvvjIs7hm4gEWvBUX5Gh9F/hoRGWjHFvf2SxTPF+ETZYEIy3cwcBZMJftT5/YdyWtbzRpPTYAJZCZj6dcxeKIbnOOt8Ks6rvKhZ6gI2OksFU+TGZDQFctVWX+TEcNyaxXhVz2TcCaaRDJDE9qzpte5nu72vSWPJr7AmSSOsF+kTsGReVKa0doiq4IEfjgeZhOg9VLOqy8esAvXP41nh3tR1tZWC57FXEryUuZW+OsoQXGSqbUgKvbD/P81m4em5vh6/Pnc3fjXPyBR+NgSngkZes3c+IHA/7386/iGy88l2u3PsQL2o/SkUNH3ExIJMcyf2qctThdFe2NaCN7OuRlHB/612/g+re9gb/98+0/8NxGE5mawIzB5rlzLjHGZYkMY7eaoyRkekwYWCC3ozYA6XqpSscTm+cjIpTlrnJTWgfbDBGnhIsDjN9CDV3FZThfrIT1BVZJbKgQgxSRGLy+yzPBc/aZVrrQSitHrmVWKmcKsDaAJHUXdmORq31aBydZbTmnraBnSJRk5tGM6OCQdCok7QTIFLKOcFWgHuQNi1XQ2pe5trBi/k06zoXMG+DyY3yXq5I3BPlUiOwNiyDJMQJQ2CyX1S2bjybsqpolBXRaDM6fwhtovH6GHLpQM9MujjnOi/wXsEo657A0h0JPJDOLSDTCGKwnyWaa5JMNZMNHHe5iB8VKXaFXEr0BMvCZ3L+MmWqTTTfI2h7BqqUzqEX8ZzOOJi9nUvvYyVpJfLyJsKzGQF2ROS5YWyyajBm9HJ0ldjSk/EENIYweU3IUwgiIXNPcF3PonjbfuXAXb5g6QkukGCPpeE5TslZUR1KrUEKgraxIDkAgtLM/LkhBS6ZFBUdzd387e247hx13Jqh+hmm4dmQpLOd4zrRFYQmFZslEY5ksHkoY+jpiRvXcoVmfQ/kEiRkRB3CtbS019nfKQAB+R7P/nAlWl2aZuccnWGbUOla0I9u0cLcsK+zGuCy3VpOVS6c48COaX7j8a1zVfIjMeqyYJmsmQhctXpn1CIqwzvKsx4CxEo1zZSuJSEfGtOdjli9psJhsZfaOkMZhl1fTuX+V9iOK4a0zfPGCLXzikquY3rHKc+YWMVYwEwz4ykPbgK8c23enxknBqazCnEwb5Y3GRpGXo1/z8UgMbByRqQnMGISSCCHLri1HXoQoyv9ylAdT9uIa1xZgs3x0Ew5gTdUaJcq7fmtcJaZwRrFZhlrqEjZ98paHUYJ0QhB0LSK3yCRH2NF+gHM2Mw0fKwXGl2TTEm9g0KET8AerOcHeFVjtuWMohey5JjqUYkWA39PohqS9NydYTTGhh/UkjSOaPHIuZcJA44DABJC2QWx1E060XNogg8whmRJ4iZtIvNgFQw7nA7yVBmqtXziR5SNHNqXc2RBFib/UFJXnP4pIz5lCpgY1zFHd2LWFtQN05GGVwIl5ZNVmYQVVdcYWx2tDhcX97PXcypcJPcRUG5lmzu65DLsszg/WINOMsDsgBFqBT+Yb6tu1049TJeZ/y66fP6UkZrPaKj/Zat7RZGb89xpHQUmEFdiqD3hMC2PsSPdX6irL56xxF7bKelmuf1zJUTXHGLzlAbN3NfjEec/nwhce5JJwP0ClKyktjjWSrLguluSlb0Km1KAiE6u6xZppkBifewdbuembz2XH112rmogzZJoTrDXpxSErpklHDkmRpFbySDbPobyDsS5fRhctcmumUelgwLWvlSn2LmDTOZ75QlcVoGmvz6QakG1T/PVKi3gmIDgYYNf66ypUVUioLJw6fQ8m2uSzbVaeJXnxZfdxZeMRtJWs6CYr2hGYjoyJcPbQpfFA6dr2aDoH4EwIinNopPt/u7/Mjyzczx2NAd+b2snsN3za+wVeL0V2h7SX+7Tu99j69QbD7ZPctWOWtAN+HxqPjlrKapx9OPqa+fEPnVwb5aNxKh3JjhXXv23f47aUlSiJzImiJjDjELKYWEqyUbQnlUFYVetYQWZgndBynb2yUiN9TInyZt0UbVW5xltcxeycJm96dPbkYJ0o3jQ85DDHtEJknDvXL2sxgUfe8kgnnO0xVuL3NH43wzvUhbXiImkKC0kAY1BxTtqJ8GKDGrrMF5cLYwiWNLrpkzUD/DXXatZ5zOly8kgwnHfuZKXzV9jVDLZ4LkRtCecyZi0qtSRTEnlem4lDK2CzwqXNFMJLU52H0pK6aq/zPPTCNKvnRXiJpb1HYwPn8Ja3nPWxDgVSK2Rq8bsZKtGIYVa1+Tly5JzT8CRWUH1uMtXodgh6Crmy5rIYSgIlBaQGKzQMhu7z7q4hZN1CdjbidLWNbRROZR/3k6EmL08BUYj4rcHlWRWGLuXcUAr2y6wR+SSVlxLlwk8JaxFJRueRAYNvtvn4thfyS+fezLzqEomcuBDma+vIi49GCVvcsBvXDiwTOoWTWGY9FrNJPnvgcvZ9eQc7v53TWBy6JPvCFKV1oMOhvRPcdt75nB8e4opoT5Xx4gsNQldVlrI9LLMeCsus6hX5KD4DEzCp8qoaojB01BBtJS2Z0JQJHRXz0M459s2cT7sZICkdKovjV8pNc8Y6Q5cowrQi1s5tkl4y5CVTD5EVRgVHdJvE+MyoPh01rPRArq3MVaiO5G2W8haZVYXAf0gkM7SVKGGIRM5zm7vZFqzQ9hJukRfB1z38tRA/07C0Ct0Mb3WNzmJA6+E2JvRQq0P0ytLT/07VeNrY6CrMk5GGU627ORGcjOrLOD70r9/AX+w+OpdmY1ATmHFojdWjVS8hClGlkhVRKVe+KhcyKRAqGL1GuZKW5QjfcxfYsoWsRBFsaZMEYQzBwQCRN0lmCmFlubqUK3SkkGkOBtcO1VIkEwqVWtr7U1QvRa30XBUhy7AloSpW9fA8kBK53APbpr/FI1p15MSqwv2raG+wylkty1zgDdw2KhFVdah3jiRoOQ2M9RyhkTkgQPuCoGcYBIK1nYr2QxOIA0dcK5kVI6KQjZ3H0qc/8BG+TzrbQGpHmvrbQ5oHXbhnOlmkGwfuPbDWVafKFUtPVa0VIsuQQqD9AJnk1aqn9SRykKEnQoS1iKXVkdV12eJhjSMypVZp3E2uxmnFRlRhjoW4lBfZU1WJOR1VmHLCfbKJtXYp2wBoMxLcG7veKtmOFrdEOTeUi2TlNamyVC7bz2RlxW+tdWHJAKFADlJm7knZP7mD/+dVL+f/2PZ1ptTA5a5Yn0HhNDalBlVGDKJwJStu7vdlU3y/t50v3Xsxk7dG7PxOH281dvua5VWbVrjYZ+6bU/yvxou54sLHaC0kLHirwMhxzBQ6F4MkUk7fUmJCDuljkEUVRgrjzAYEFVFIrUIXlZtrZx7kQ5eeR3tfROtwY3RdHjtH5XxsZYYVgt4OycsvfIAroj3uWCXE0jmmdZQT7vvoscYxJ8PMrCKSGUnusZo3isyaYdVGVjq5zXtdfnjmXsIrcv5eX0rQC2lrgz9MKrtnO4iRxiI9BXGCTWsdzGbBRhGLzXZ9vPZvbuMfXnvV6d6NH8DJIjE1gRmD1RqQVSXFlhWT0h65FA5meRFIphGo9XbLUri2Mc8b9SuXrWOiyI7xvZH/f64RR1YI+kNUr0M+GZK3lAva8iQ6FBi/idfPSac8gpWcxt6+swkuqy2ly02er58EwR1HHCOEoL03ZflZIaxA1pCotocXC2TibJmNJ9CBqDJq/F6O9QReXzNY8OntkKSTgmDVEh2y+ANL0NNYIcibEpFbgq6r4GQzDcLVyOmIjiICFSmsWtxybKeFDiThisEEzpSgNAxQicseENqSTEjaPY1MNSI32MjDSIGMs1GLX65Rq0OXzgwuYwcD2iIlZNMN/CSF5XTU4jbe3qHLitET2JjWOC0oCcjxEJkTrbac6nayU4my1eBYJvHN2JZwxsCOifOrx8z6rKuyug/ueijs+nmmDMFUChEoRBCM8k2UckYtRWUnWIpZuMWye3A+77l6nqt27uG85hGm/T6Z8TAIVpTLXVnNGyTGY388yQMrcxx+YJbOI5JwybLrUE60uIrsDov8MukyVoobczFImLp/SDLV5HvxLr7WOsLrp75DJLLKhrgUy7dkSiQytnhrrOgmsiBNHTWkJVJWTJPUKiKROSMBqVzAJRaNYFb2mWn1+PwVz6F773YajzVdG3Cagc6qlm5nQ20Rvodu+axdlPOyyftpCUcaOjLGRzNlByhhaIm00txoRGV6EMmMOW8NgNW8wUrWZJ+chgDmvS5NmZEZRUsktGTCj812yZ6r+Nb+5xB0A7xl55JGVpBLYyDOXdtyvSC2qXAiJOZEroXHsmC0UbjpitdxPHGpJ7v6Mo4P/es38JWX/uMnzIs5EdQEZhyFvsNqzSjMZERYgPWBZLCO2FSPlRWNJHVkSCqQqgq5tFk22l4brJWwliF7fcKDIWHgYz1Xmaj2K8sJ9hpnF2lGzmgVyomwrLyU+6Upqj0p0e4V/HOcN3DQM2RthfElKlQuawaQucUKgW5IwmUNiateREsSmYMOwO9bVGLwhhrjS8AiM4PMLf7AkLUlw/mA8BGx/qJd2oSO5eJU51BKvKFGGEuG51zGMoP0JVkLwhVDuJxipUA3FHnLxz+cIUxxE2DABB5qmLhzB4gkd+nJQiByQz4ZYf2COLYbiNUemHz9PpYks8amxeORkpLUnOntYU+Fzd6OUOMJUF2LbaX9W2chD6N25DJXbNyaX0iE72M7LWwzxATKLdpkGuMrdDMAAd5QM397Qry7wV3nXMo3dhrMXIr0LJ32ECkNSeYz6IWw4tN5SNHeq7ngUIq3miC0Wxgiy13gspRYIVyFv7guijRDrcUEqw2CJcUj/VnWJhp05LDInFFk0kNbQVa4nkGhu7FghKSjhvgiZ7u3zIpuYpAVwVHWVlWYzHp05JArpvfxpcY5rq1YCFfZ9z2npRTCVbGUm2fzto+adASlWxgLSASRzMA40wJZpFL7IictdDdruoEuHNqaMgUPunnEkaxVbKvJrEdatMuVFZmLWwe5ZfoSTCDc/uUawdgCpiky5M7WAPAzGOOE5Nq/uY2brnjduuf/0fc+uykrGmcq/t2OtQ19vZrAjEF4HkJ4I2JQCvVhJNyv8mFk1QblLJe9UclfSCe0lD6i3UJvmSJv+4jcVu1MwlpEavC6MWK150iNsS6MK46L9xi74EkxqghpJ+ivJrzSYnOMEKzLWPED93O3x8wdEb0L22glsFIwmJcEfUm4kqMSy3BOIrSlccRgQoVRbl9VrAlzgzAU2hlnY2yFQA1zdNOJ7K0EHQniKbCB785XPmqhq9rxSpIFzvKyFZFOePhrOcFahvGcw5jXzytyhbV43QRhQozvXNrkIHWTq5RO9xL6bhLRrm0AKQvtkO9cyzKDyA0m8vDaTexKd2QmoBQ2zUbtbeopHINqbCiuzZInfO4f/PBJ//ZMJi6no42sJkKnBtba9RlhQhT5MHJULa9axcptXIVeBIUpSV603zYikp1TLF4Vkk5ZGovO9MWLLcGaGWWGGUu4qomWcua/azG+xCiBjiaxEpoG5ocGlWR4Kz1kko3s7o1xhEC7/48O4bTWIpIUuSZp7++QN3z2did4dHaO50R7SQtR/GI2yaQa0JKOSKwZ147lBPOarmkQF63XfRMQCM2+bJqBCVjTEZHM8IVmXzLF9nCFoQ4wvvMwAIoFumK/ikq78DwIfKwCz9OV61iGqrJqyoBJXzjtTRne2TcB9wy3cXd3gUwrnj25SChzhtpnwotRwrCUt4mLoOvY+hgryaziUNrBTmWkHZ9wIsKz1pnW5No5kJbGPzVOKX76340seP73I5al/375k27/D6+96nGqFzV52cyoCQyjILEsjyFU2MQFQAohsMKOWpMsiIJICBWMJh6APBsRGWFBKJhokW1tk7UhWO27DBcp0S0XCAmQTivM/JSrXiwPEQeXi1YwBVni3qOo4JQQgcKmydjkYnHWYLawmaTIqPHAasAirMRmGeLAAUI1S397w60YDQRiKYfVFKUDor50dsi5Jp6SGGVpHHaCeStwxMBaspaPlMbd8Mcpog94AkSDcI9EB4J4UuH3ZLGLbjWPPC3aEgSYDJSHQJCrjMzEYA2ZB8FyTO67CpHsa6ySxG0PPRvgr2XOQtrmKJ24FoIohDxGWIORlnwiQAcSv5thPYlVGq83hMygA4X1FaalECuZmxVtDkaBGmmIcp2t+34803GyzsOLjxwCIO9urqTqt+z6ef7krv/7dO/GOnTXTv2N0IG751m49NBTblePE4fyPOQmxQq7zujFoTRzqf5i/WKJMYVTo1sIwxfgSUxTsrzNMGwNEUPQsSD2QAUWMKjUOIvj3GCMRQ1zRD/D03q0yKOk07OUbWjWosc/t9JowIzNbda6ToF81GEgEo3/yCEmhi32d9r8t+UX8Kz5nUQq55HVGVYHEefNLnFR5zAzfo+DySQAq3nEPUeKLgClWelHKGWZag7pJSG91Qb0PWyo8ZsZQhlmO7McWWsy9cgAu9olz1xrm8uAyYFigQ6LlRIzHJLe5/En4fMAaPoZB/tttBH40jDIfGaaA+YafVLt0U1DlgZNeodaNB/xyRuWe7ZNudiAXDC5tcfOyRWkMCz2O4ReTqoVR1Zb5ElhRf2IRS4NsKsDdD92lSFjCs2TBavJydd9P57pONnn4c9+d3OZjDR3LHLg7vnq9x+76+MAfPqytz7h37zzf36G//J/vJ53/s/PIK59FW849//DXz/6bv7g/MYx/f1T4W//fDt/ctf/TUvu54O//c/o/8x+Wv9rGwD/5942//GcHje+98P0zbbqb372sl953Nf6/Iv28p9+4X9h//rHALjxvR/mns/9Fb/z63fz4r/4ewBufcsPH/O+Hcv3Q9h6NPHQQw9x4YUXnu7dqLFJsWfPHnbs2HG6d+O0ox4nNZ4M9ThxqMdJjSdDPU4c6nFS48lwLOOkrsAAMzMzAOzevZvJycnTvDdPH91ul507d7Jnzx4mJiZO9+5sCE7HMVlrWVtbY/v2xw9jeqahHiebH/U4Of0428YJnH1jpR4npx/1ONn82OzjpCYwgCwE+pOTk2fFl67ExMTEWXU8cOqP6Wy5sG4E6nFy5qAeJ6cPZ+s4gbNvrNTj5PShHidnDjbrOHmc5KwaNWrUqFGjRo0aNWrU2JyoCUyNGjVq1KhRo0aNGjXOGNQEBgjDkH/zb/4NYfjkVq1nCs6244Gz85jONJxtn8HZdjxwdh7TmYaz8TM4247pbDueMxFn42dwth3TZj+e2oWsRo0aNWrUqFGjRo0aZwzqCkyNGjVq1KhRo0aNGjXOGNQEpkaNGjVq1KhRo0aNGmcMagJTo0aNGjVq1KhRo0aNMwY1galRo0aNGjVq1KhRo8YZg2c8gfngBz/IeeedRxRFvPjFL+Yb3/jG6d6lJ8SXv/xl3vCGN7B9+3aEEHzqU59a97y1lve85z1s27aNRqPBddddx/33379um6WlJX7mZ36GiYkJpqameMc73kGv1zuFR+Hwvve9j6uvvppOp8OWLVt405vexL333rtumziOufHGG5mdnaXdbvPmN7+ZxcXFddvs3r2b173udTSbTbZs2cJv/MZvkOf5qTyUZwzOlLFyNo0TqMfKmYZ6nNTjpMZTox4n9Th52rDPYHzsYx+zQRDYD3/4w/auu+6y/+Jf/As7NTVlFxcXT/euPS4+97nP2d/5nd+xn/jEJyxgP/nJT657/t//+39vJycn7ac+9Sn73e9+177xjW+0559/vh0Oh9U2r3nNa+zznvc8+/Wvf91+5StfsRdddJH96Z/+6VN8JNa++tWvth/5yEfsnXfeab/zne/YH/3RH7W7du2yvV6v2uYXfuEX7M6dO+0Xv/hFe9ttt9mXvOQl9qUvfWn1fJ7n9vLLL7fXXXedvf322+3nPvc5Ozc3Z9/1rned8uM523EmjZWzaZxYW4+VMwn1OKnHSY2nRj1O6nGyEXhGE5gXvehF9sYbb6x+11rb7du32/e9732nca+ODUcPJGOMXVhYsP/pP/2n6rGVlRUbhqH9sz/7M2uttd///vctYL/5zW9W2/zN3/yNFULYvXv3nrJ9fzwcPHjQAvZLX/qStdbtu+/79uMf/3i1zd13320Be8stt1hr3YVFSmkPHDhQbfOHf/iHdmJiwiZJcmoP4CzHmTpWzrZxYm09VjYz6nFSj5MaT416nNTjZCPwjG0hS9OUb33rW1x33XXVY1JKrrvuOm655ZbTuGcnhocffpgDBw6sO57JyUle/OIXV8dzyy23MDU1xVVXXVVtc9111yGl5NZbbz3l+zyO1dVVAGZmZgD41re+RZZl647nkksuYdeuXeuO54orrmDr1q3VNq9+9avpdrvcddddp3Dvz26cTWPlTB8nUI+VzYp6nNTjpMZTox4n9TjZKDxjCczhw4fRWq/7AAC2bt3KgQMHTtNenTjKfX6y4zlw4ABbtmxZ97zneczMzJzWYzbG8Cu/8itce+21XH755YDb1yAImJqaWrft0cfzeMdbPldjY3A2jZUzeZxAPVY2M+pxUo+TGk+NepzU42Sj4J2yd6pR4wlw4403cuedd/LVr371dO9KjRqbGvVYqVHjqVGPkxo1nhpn+jh5xlZg5ubmUEr9gLPC4uIiCwsLp2mvThzlPj/Z8SwsLHDw4MF1z+d5ztLS0mk75ne+85185jOf4e/+7u/YsWNH9fjCwgJpmrKysrJu+6OP5/GOt3yuxsbgbBorZ+o4gXqsbHbU46QeJzWeGvU4qcfJRuEZS2CCIOCFL3whX/ziF6vHjDF88Ytf5JprrjmNe3ZiOP/881lYWFh3PN1ul1tvvbU6nmuuuYaVlRW+9a1vVdvcfPPNGGN48YtffEr311rLO9/5Tj75yU9y8803c/755697/oUvfCG+7687nnvvvZfdu3evO57vfe976y4ON910ExMTEzznOc85NQfyDMDZNFbOtHEC9Vg5U1CPk3qc1Hhq1OOkHicbhlNmF7AJ8bGPfcyGYWg/+tGP2u9///v2hhtusFNTU+ucFTYT1tbW7O23325vv/12C9jf//3ft7fffrt99NFHrbXOzm9qasp++tOftnfccYf9sR/7sce187vyyivtrbfear/61a/aiy+++LTY+f3iL/6inZyctH//939v9+/fX/0bDAbVNr/wC79gd+3aZW+++WZ722232WuuucZec8011fOlld/1119vv/Od79jPf/7zdn5+vra8PAk4k8bK2TROrK3HypmEepzU46TGU6MeJ/U42Qg8owmMtdb+wR/8gd21a5cNgsC+6EUvsl//+tdP9y49If7u7/7OAj/w7+1vf7u11ln6/e7v/q7dunWrDcPQvupVr7L33nvvutc4cuSI/emf/mnbbrftxMSE/bmf+zm7trZ2yo/l8Y4DsB/5yEeqbYbDof2X//Jf2unpadtsNu2P//iP2/379697nUceecS+9rWvtY1Gw87Nzdlf//Vft1mWneKjeWbgTBkrZ9M4sbYeK2ca6nFSj5MaT416nNTj5OlCFAdUo0aNGjVq1KhRo0aNGpsez1gNTI0aNWrUqFGjRo0aNc481ASmRo0aNWrUqFGjRo0aZwxqAlOjRo0aNWrUqFGjRo0zBjWBqVGjRo0aNWrUqFGjxhmDmsDUqFGjRo0aNWrUqFHjjEFNYGrUqFGjRo0aNWrUqHHGoCYwNWrUqFGjRo0aNWrUOGNQE5gaNWrUqFGjRo0aNWqcMagJTI0aNWrUqFGjRo0aNc4Y1ASmRo0aNWrUqFGjRo0aZwxqAlOjRo0aNWrUqFGjRo0zBjWBqVGjRo0aNWrUqFGjxhmD/xeMcOO7tIjeNwAAAABJRU5ErkJggg==", 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", "text/plain": [ "
" ] @@ -80182,7 +80050,7 @@ { "cell_type": "code", "execution_count": null, - "id": "90625096", + "id": "f92c9561", "metadata": {}, "outputs": [], "source": [] diff --git a/autoapi/dacapo/experiments/architectures/cnnectome_unet/index.html b/autoapi/dacapo/experiments/architectures/cnnectome_unet/index.html index 3682966a5..61a02fc80 100644 --- a/autoapi/dacapo/experiments/architectures/cnnectome_unet/index.html +++ b/autoapi/dacapo/experiments/architectures/cnnectome_unet/index.html @@ -400,7 +400,7 @@

Module Contents
-property eval_shape_increase
+property eval_shape_increase: funlib.geometry.Coordinate

The increase in shape due to the U-Net.

Returns:
@@ -498,7 +498,7 @@

Module Contents
-property input_shape
+property input_shape: funlib.geometry.Coordinate

Return the input shape of the U-Net.

Returns:
diff --git a/autoapi/dacapo/experiments/architectures/index.html b/autoapi/dacapo/experiments/architectures/index.html index 975d7e2c8..c46f01f5e 100644 --- a/autoapi/dacapo/experiments/architectures/index.html +++ b/autoapi/dacapo/experiments/architectures/index.html @@ -1168,7 +1168,7 @@

Package Contents
-property eval_shape_increase
+property eval_shape_increase: funlib.geometry.Coordinate

The increase in shape due to the U-Net.

Returns:
@@ -1266,7 +1266,7 @@

Package Contents
-property input_shape
+property input_shape: funlib.geometry.Coordinate

Return the input shape of the U-Net.

Returns:
diff --git a/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.html b/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.html index 214e38ae0..bb7a6f191 100644 --- a/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.html +++ b/autoapi/dacapo/experiments/tasks/hot_distance_task_config/index.html @@ -239,6 +239,11 @@

Module Contentsmask_distances: bool

+
+
+kernel_size: int | None
+
+

diff --git a/autoapi/dacapo/experiments/tasks/index.html b/autoapi/dacapo/experiments/tasks/index.html index 18248c7d1..19312f9dc 100644 --- a/autoapi/dacapo/experiments/tasks/index.html +++ b/autoapi/dacapo/experiments/tasks/index.html @@ -653,6 +653,11 @@

Package Contentsclasses: List[str]

+
+
+kernel_size: int | None
+
+

@@ -1256,6 +1261,11 @@

Package Contentsmask_distances: bool

+
+
+kernel_size: int | None
+
+
diff --git a/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.html b/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.html index 9b757787d..fe1295366 100644 --- a/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.html +++ b/autoapi/dacapo/experiments/tasks/one_hot_task_config/index.html @@ -165,6 +165,11 @@

Module Contentsclasses: List[str]

+
+
+kernel_size: int | None
+
+ diff --git a/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.html b/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.html index 5a2e994c5..e063a5605 100644 --- a/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.html +++ b/autoapi/dacapo/experiments/tasks/post_processors/threshold_post_processor/index.html @@ -119,6 +119,16 @@

dacapo.experiments.tasks.post_processors.threshold_post_processor

+
+

Attributes

+ + + + + + +

logger

+

Classes

@@ -131,6 +141,11 @@

Classes

Module Contents

+
+
+dacapo.experiments.tasks.post_processors.threshold_post_processor.logger
+
+
class dacapo.experiments.tasks.post_processors.threshold_post_processor.ThresholdPostProcessor
diff --git a/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.html b/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.html index 2b1dd3ee3..eeddabf14 100644 --- a/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.html +++ b/autoapi/dacapo/experiments/tasks/predictors/hot_distance_predictor/index.html @@ -148,7 +148,7 @@

Module Contents
-class dacapo.experiments.tasks.predictors.hot_distance_predictor.HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool)
+class dacapo.experiments.tasks.predictors.hot_distance_predictor.HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool, kernel_size: int)

Predict signed distances and one hot embedding (as a proxy task) for a binary segmentation task. Distances deep within background are pushed to -inf, distances deep within the foreground object are pushed to inf. After distances have been @@ -254,6 +254,11 @@

Module ContentsNotes

This is a subclass of Predictor.

+
+
+kernel_size
+
+
channels
diff --git a/autoapi/dacapo/experiments/tasks/predictors/index.html b/autoapi/dacapo/experiments/tasks/predictors/index.html index b390eb2cd..e5971c4a7 100644 --- a/autoapi/dacapo/experiments/tasks/predictors/index.html +++ b/autoapi/dacapo/experiments/tasks/predictors/index.html @@ -696,7 +696,7 @@

Package Contents
-class dacapo.experiments.tasks.predictors.OneHotPredictor(classes: List[str])
+class dacapo.experiments.tasks.predictors.OneHotPredictor(classes: List[str], kernel_size: int)

A predictor that uses one-hot encoding for classification tasks.

@@ -752,6 +752,11 @@

Package Contentsclasses

+
+
+kernel_size
+
+
property embedding_dims
@@ -1817,7 +1822,7 @@

Package Contents
-class dacapo.experiments.tasks.predictors.HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool)
+class dacapo.experiments.tasks.predictors.HotDistancePredictor(channels: List[str], scale_factor: float, mask_distances: bool, kernel_size: int)

Predict signed distances and one hot embedding (as a proxy task) for a binary segmentation task. Distances deep within background are pushed to -inf, distances deep within the foreground object are pushed to inf. After distances have been @@ -1923,6 +1928,11 @@

Package ContentsNotes

This is a subclass of Predictor.

+
+
+kernel_size
+
+
channels
diff --git a/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.html b/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.html index 1437e6682..adbb83141 100644 --- a/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.html +++ b/autoapi/dacapo/experiments/tasks/predictors/one_hot_predictor/index.html @@ -148,7 +148,7 @@

Module Contents
-class dacapo.experiments.tasks.predictors.one_hot_predictor.OneHotPredictor(classes: List[str])
+class dacapo.experiments.tasks.predictors.one_hot_predictor.OneHotPredictor(classes: List[str], kernel_size: int)

A predictor that uses one-hot encoding for classification tasks.

@@ -204,6 +204,11 @@

Module Contentsclasses

+
+
+kernel_size
+
+
property embedding_dims
diff --git a/genindex.html b/genindex.html index 79d42bebe..5d40c4b43 100644 --- a/genindex.html +++ b/genindex.html @@ -5209,6 +5209,24 @@

J

K

+ -