heareval_evaluation_example.ipynb

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 "metadata": {
  "colab": {
   "name": "HEAR 2021 Evaluation Example.ipynb",
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   "collapsed_sections": []
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  "kernelspec": {
   "name": "python3",
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 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "# HEAR 2021 Evaluation Example\n",
    "\n",
    "This notebook provides an example of downloading a pre-processed task and running evaluation using the Wav2Vec2 baseline model."
   ],
   "metadata": {
    "id": "hhy8QGIJMqfT"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 1. Install Dependecies\n",
    "**Note: You may have to restart runtime after installation**"
   ],
   "metadata": {
    "id": "_Uoqui73M_P7"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "!pip install heareval\n",
    "!pip install hearbaseline"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "tZf_omv02xU4",
    "outputId": "b44b1676-556a-4163-8a67-22607a84ed7a"
   },
   "execution_count": 1,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
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      "Building wheels for collected packages: dcase-util, validators, sed-eval\n",
      "  Building wheel for dcase-util (setup.py) ... \u001B[?25l\u001B[?25hdone\n",
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      "  Stored in directory: /root/.cache/pip/wheels/38/a9/49/3dcce0c0b112670480e105a4a8e985e2ccddb7b77065b4aac2\n",
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      "  Created wheel for sed-eval: filename=sed_eval-0.2.1-py3-none-any.whl size=26124 sha256=f49b332664f995ceda9d9253de553ff3ecfe9e01c71c94583ddac6a18929347a\n",
      "  Stored in directory: /root/.cache/pip/wheels/96/19/00/a3ec89acfdbd2568185a1ae3020590e76ee73a47ac4ff83e84\n",
      "Successfully built dcase-util validators sed-eval\n",
      "Installing collected packages: urllib3, numpy, llvmlite, numba, multidict, jmespath, frozenlist, yarl, botocore, asynctest, async-timeout, aiosignal, validators, s3transfer, PyYAML, python-magic, fsspec, aiohttp, torchmetrics, tensorflow-estimator, schema, pyDeprecate, keras, gast, dcase-util, chevron, cfn-flip, boto3, torchinfo, tensorflow, spotty, sed-eval, pytorch-lightning, pynvml, heareval\n",
      "  Attempting uninstall: urllib3\n",
      "    Found existing installation: urllib3 1.24.3\n",
      "    Uninstalling urllib3-1.24.3:\n",
      "      Successfully uninstalled urllib3-1.24.3\n",
      "  Attempting uninstall: numpy\n",
      "    Found existing installation: numpy 1.21.6\n",
      "    Uninstalling numpy-1.21.6:\n",
      "      Successfully uninstalled numpy-1.21.6\n",
      "  Attempting uninstall: llvmlite\n",
      "    Found existing installation: llvmlite 0.34.0\n",
      "    Uninstalling llvmlite-0.34.0:\n",
      "      Successfully uninstalled llvmlite-0.34.0\n",
      "  Attempting uninstall: numba\n",
      "    Found existing installation: numba 0.51.2\n",
      "    Uninstalling numba-0.51.2:\n",
      "      Successfully uninstalled numba-0.51.2\n",
      "  Attempting uninstall: PyYAML\n",
      "    Found existing installation: PyYAML 3.13\n",
      "    Uninstalling PyYAML-3.13:\n",
      "      Successfully uninstalled PyYAML-3.13\n",
      "  Attempting uninstall: tensorflow-estimator\n",
      "    Found existing installation: tensorflow-estimator 2.8.0\n",
      "    Uninstalling tensorflow-estimator-2.8.0:\n",
      "      Successfully uninstalled tensorflow-estimator-2.8.0\n",
      "  Attempting uninstall: keras\n",
      "    Found existing installation: keras 2.8.0\n",
      "    Uninstalling keras-2.8.0:\n",
      "      Successfully uninstalled keras-2.8.0\n",
      "  Attempting uninstall: gast\n",
      "    Found existing installation: gast 0.5.3\n",
      "    Uninstalling gast-0.5.3:\n",
      "      Successfully uninstalled gast-0.5.3\n",
      "  Attempting uninstall: tensorflow\n",
      "    Found existing installation: tensorflow 2.8.2+zzzcolab20220527125636\n",
      "    Uninstalling tensorflow-2.8.2+zzzcolab20220527125636:\n",
      "      Successfully uninstalled tensorflow-2.8.2+zzzcolab20220527125636\n",
      "\u001B[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "xarray-einstats 0.2.2 requires numpy>=1.21, but you have numpy 1.19.2 which is incompatible.\n",
      "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\n",
      "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001B[0m\n",
      "Successfully installed PyYAML-6.0 aiohttp-3.8.1 aiosignal-1.2.0 async-timeout-4.0.2 asynctest-0.13.0 boto3-1.24.2 botocore-1.27.2 cfn-flip-1.3.0 chevron-0.14.0 dcase-util-0.2.19 frozenlist-1.3.0 fsspec-2022.5.0 gast-0.4.0 heareval-2021.1.2 jmespath-1.0.0 keras-2.7.0 llvmlite-0.31.0 multidict-6.0.2 numba-0.48.0 numpy-1.19.2 pyDeprecate-0.3.2 pynvml-11.4.1 python-magic-0.4.26 pytorch-lightning-1.6.4 s3transfer-0.6.0 schema-0.7.5 sed-eval-0.2.1 spotty-1.3.3 tensorflow-2.7.3+zzzcolab20220523111007 tensorflow-estimator-2.7.0 torchinfo-1.7.0 torchmetrics-0.9.0 urllib3-1.25.11 validators-0.19.0 yarl-1.7.2\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "application/vnd.colab-display-data+json": {
       "pip_warning": {
        "packages": [
         "numpy"
        ]
       }
      }
     },
     "metadata": {}
    },
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
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     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 2. Download the Dataset\n",
    "\n",
    "We download the Mridingham Tonic dataset with samplerate 16000 as an example."
   ],
   "metadata": {
    "id": "xoYuPUjYNHvB"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "!wget https://github.com/hearbenchmark/hear2021-sample-datasets/raw/main/hear2021-mridangam_tonic-v1.5-full-16000.tar.gz\n",
    "!tar -xzf hear2021-mridangam_tonic-v1.5-full-16000.tar.gz"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "cAnCDPdbzqIw",
    "outputId": "71515342-661c-47e4-df56-89cdeb714062"
   },
   "execution_count": 2,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "--2022-06-03 21:05:18--  https://github.com/hearbenchmark/hear2021-sample-datasets/raw/main/hear2021-mridangam_tonic-v1.5-full-16000.tar.gz\n",
      "Resolving github.com (github.com)... 140.82.113.4\n",
      "Connecting to github.com (github.com)|140.82.113.4|:443... connected.\n",
      "HTTP request sent, awaiting response... 302 Found\n",
      "Location: https://raw.githubusercontent.com/hearbenchmark/hear2021-sample-datasets/main/hear2021-mridangam_tonic-v1.5-full-16000.tar.gz [following]\n",
      "--2022-06-03 21:05:18--  https://raw.githubusercontent.com/hearbenchmark/hear2021-sample-datasets/main/hear2021-mridangam_tonic-v1.5-full-16000.tar.gz\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 62455362 (60M) [application/octet-stream]\n",
      "Saving to: ‘hear2021-mridangam_tonic-v1.5-full-16000.tar.gz’\n",
      "\n",
      "hear2021-mridangam_ 100%[===================>]  59.56M   256MB/s    in 0.2s    \n",
      "\n",
      "2022-06-03 21:05:19 (256 MB/s) - ‘hear2021-mridangam_tonic-v1.5-full-16000.tar.gz’ saved [62455362/62455362]\n",
      "\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 3. Compute embeddings using Wav2Vec2"
   ],
   "metadata": {
    "id": "3axotNriOngG"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "!python3 -m heareval.embeddings.runner hearbaseline.wav2vec2 --tasks-dir ./tasks/"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ksRdQkga0kau",
    "outputId": "e7181c9a-d6da-493f-dbff-061ac298fd53"
   },
   "execution_count": 3,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/heareval/embeddings/runner.py:22: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.config.list_physical_devices('GPU')` instead.\n",
      "2022-06-03 21:05:31.459094: W tensorflow/core/common_runtime/gpu/gpu_bfc_allocator.cc:39] Overriding allow_growth setting because the TF_FORCE_GPU_ALLOW_GROWTH environment variable is set. Original config value was 0.\n",
      "embeddings\n",
      "Importing hearbaseline.wav2vec2\n",
      "Downloading: 100% 212/212 [00:00<00:00, 361kB/s]\n",
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      "Some weights of the model checkpoint at facebook/wav2vec2-large-100k-voxpopuli were not used when initializing Wav2Vec2Model: ['quantizer.codevectors', 'project_q.bias', 'quantizer.weight_proj.bias', 'project_hid.bias', 'quantizer.weight_proj.weight', 'project_hid.weight', 'project_q.weight']\n",
      "- This IS expected if you are initializing Wav2Vec2Model from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
      "- This IS NOT expected if you are initializing Wav2Vec2Model from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
      "speechbrain.lobes.models.huggingface_wav2vec - wav2vec 2.0 is frozen.\n",
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      "100% 1395/1395 [00:00<00:00, 2707.67it/s]\n",
      "\n",
      "  0% 0/1395 [00:00<?, ?it/s]\u001B[A\n",
      " 20% 284/1395 [00:00<00:00, 2829.79it/s]\u001B[A\n",
      " 41% 578/1395 [00:00<00:00, 2893.04it/s]\u001B[A\n",
      " 62% 868/1395 [00:00<00:00, 2876.15it/s]\u001B[A\n",
      "100% 1395/1395 [00:00<00:00, 2834.81it/s]\n",
      "...computed embeddings in 75.6577308177948 sec (GPU max mem 4.63671875) for mridangam_tonic-v1.5-full using hearbaseline.wav2vec2 {}\n",
      "100% 1/1 [01:15<00:00, 75.67s/it]\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## 4. Evaluate\n",
    "Train and predict with a shallow downstream classifier using the computed embeddings."
   ],
   "metadata": {
    "id": "rdg7KDmsOudy"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "# Required for determinism\n",
    "%env CUBLAS_WORKSPACE_CONFIG=:4096:8\n",
    "\n",
    "# Train and evaluate classifier using hearbaseline embeddings\n",
    "!python3 -m heareval.predictions.runner embeddings/hearbaseline.wav2vec2/*"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "rIrjigvI1tjY",
    "outputId": "29b9ba24-6192-4f22-d64c-73dc09cbad34"
   },
   "execution_count": 4,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "\u001B[1;30;43mStreaming output truncated to the last 5000 lines.\u001B[0m\n",
      "Epoch 344: 100% 7/7 [00:00<00:00, 78.93it/s, loss=0.0451, v_num=8, val_loss=0.565, val_top1_acc=0.806, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.830] \n",
      "Epoch 347:   0% 0/7 [00:00<?, ?it/s, loss=0.045, v_num=8, val_loss=0.565, val_top1_acc=0.806, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.830]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 347: 100% 7/7 [00:00<00:00, 79.40it/s, loss=0.0444, v_num=8, val_loss=0.558, val_top1_acc=0.810, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.831]\n",
      "Epoch 350:   0% 0/7 [00:00<?, ?it/s, loss=0.0438, v_num=8, val_loss=0.558, val_top1_acc=0.810, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 350: 100% 7/7 [00:00<00:00, 51.18it/s, loss=0.0438, v_num=8, val_loss=0.570, val_top1_acc=0.801, val_d_prime=3.230, val_aucroc=0.958, val_mAP=0.830]\n",
      "Epoch 353:   0% 0/7 [00:00<?, ?it/s, loss=0.0439, v_num=8, val_loss=0.570, val_top1_acc=0.801, val_d_prime=3.230, val_aucroc=0.958, val_mAP=0.830]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 353: 100% 7/7 [00:00<00:00, 61.16it/s, loss=0.0443, v_num=8, val_loss=0.551, val_top1_acc=0.808, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.832]\n",
      "Epoch 356:   0% 0/7 [00:00<?, ?it/s, loss=0.0431, v_num=8, val_loss=0.551, val_top1_acc=0.808, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 356: 100% 7/7 [00:00<00:00, 66.36it/s, loss=0.0431, v_num=8, val_loss=0.565, val_top1_acc=0.807, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.831] \n",
      "Epoch 359:   0% 0/7 [00:00<?, ?it/s, loss=0.0429, v_num=8, val_loss=0.565, val_top1_acc=0.807, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 359: 100% 7/7 [00:00<00:00, 67.38it/s, loss=0.0427, v_num=8, val_loss=0.567, val_top1_acc=0.806, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.832] \n",
      "Epoch 362:   0% 0/7 [00:00<?, ?it/s, loss=0.0414, v_num=8, val_loss=0.567, val_top1_acc=0.806, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 362: 100% 7/7 [00:00<00:00, 59.81it/s, loss=0.0414, v_num=8, val_loss=0.568, val_top1_acc=0.805, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.831]\n",
      "Epoch 365:   0% 0/7 [00:00<?, ?it/s, loss=0.0409, v_num=8, val_loss=0.568, val_top1_acc=0.805, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 365: 100% 7/7 [00:00<00:00, 56.26it/s, loss=0.0407, v_num=8, val_loss=0.553, val_top1_acc=0.812, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 368:   0% 0/7 [00:00<?, ?it/s, loss=0.0395, v_num=8, val_loss=0.553, val_top1_acc=0.812, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 368: 100% 7/7 [00:00<00:00, 68.94it/s, loss=0.0396, v_num=8, val_loss=0.559, val_top1_acc=0.814, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.833] \n",
      "Epoch 371:   0% 0/7 [00:00<?, ?it/s, loss=0.0398, v_num=8, val_loss=0.559, val_top1_acc=0.814, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.833]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 371: 100% 7/7 [00:00<00:00, 56.16it/s, loss=0.0396, v_num=8, val_loss=0.570, val_top1_acc=0.809, val_d_prime=3.230, val_aucroc=0.958, val_mAP=0.832]\n",
      "Epoch 374:   0% 0/7 [00:00<?, ?it/s, loss=0.0391, v_num=8, val_loss=0.570, val_top1_acc=0.809, val_d_prime=3.230, val_aucroc=0.958, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 374: 100% 7/7 [00:00<00:00, 58.40it/s, loss=0.0389, v_num=8, val_loss=0.585, val_top1_acc=0.800, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.830]\n",
      "Epoch 377:   0% 0/7 [00:00<?, ?it/s, loss=0.0387, v_num=8, val_loss=0.585, val_top1_acc=0.800, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.830]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 377: 100% 7/7 [00:00<00:00, 61.88it/s, loss=0.0385, v_num=8, val_loss=0.557, val_top1_acc=0.814, val_d_prime=3.230, val_aucroc=0.960, val_mAP=0.834]\n",
      "Epoch 380:   0% 0/7 [00:00<?, ?it/s, loss=0.0378, v_num=8, val_loss=0.557, val_top1_acc=0.814, val_d_prime=3.230, val_aucroc=0.960, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 380: 100% 7/7 [00:00<00:00, 73.16it/s, loss=0.0379, v_num=8, val_loss=0.567, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.832] \n",
      "Epoch 383:   0% 0/7 [00:00<?, ?it/s, loss=0.0383, v_num=8, val_loss=0.567, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 383: 100% 7/7 [00:00<00:00, 23.99it/s, loss=0.0384, v_num=8, val_loss=0.588, val_top1_acc=0.806, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.833]\n",
      "Epoch 386:   0% 0/7 [00:00<?, ?it/s, loss=0.0379, v_num=8, val_loss=0.588, val_top1_acc=0.806, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.833]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 386: 100% 7/7 [00:00<00:00, 73.55it/s, loss=0.037, v_num=8, val_loss=0.567, val_top1_acc=0.809, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.832]  \n",
      "Epoch 389:   0% 0/7 [00:00<?, ?it/s, loss=0.0365, v_num=8, val_loss=0.567, val_top1_acc=0.809, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 389: 100% 7/7 [00:00<00:00, 76.64it/s, loss=0.0358, v_num=8, val_loss=0.561, val_top1_acc=0.814, val_d_prime=3.240, val_aucroc=0.960, val_mAP=0.834] \n",
      "Epoch 392:   0% 0/7 [00:00<?, ?it/s, loss=0.0354, v_num=8, val_loss=0.561, val_top1_acc=0.814, val_d_prime=3.240, val_aucroc=0.960, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 392: 100% 7/7 [00:00<00:00, 56.07it/s, loss=0.0352, v_num=8, val_loss=0.567, val_top1_acc=0.816, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 395:   0% 0/7 [00:00<?, ?it/s, loss=0.0349, v_num=8, val_loss=0.567, val_top1_acc=0.816, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 395: 100% 7/7 [00:00<00:00, 63.05it/s, loss=0.0348, v_num=8, val_loss=0.565, val_top1_acc=0.811, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834] \n",
      "Epoch 398:   0% 0/7 [00:00<?, ?it/s, loss=0.0344, v_num=8, val_loss=0.565, val_top1_acc=0.811, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 398: 100% 7/7 [00:00<00:00, 75.67it/s, loss=0.0348, v_num=8, val_loss=0.581, val_top1_acc=0.806, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.832] \n",
      "Epoch 401:   0% 0/7 [00:00<?, ?it/s, loss=0.0347, v_num=8, val_loss=0.581, val_top1_acc=0.806, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 401: 100% 7/7 [00:00<00:00, 67.95it/s, loss=0.0349, v_num=8, val_loss=0.594, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.958, val_mAP=0.832] \n",
      "Epoch 404:   0% 0/7 [00:00<?, ?it/s, loss=0.0347, v_num=8, val_loss=0.594, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.958, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 404: 100% 7/7 [00:00<00:00, 75.44it/s, loss=0.0351, v_num=8, val_loss=0.581, val_top1_acc=0.811, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.832] \n",
      "Epoch 407:   0% 0/7 [00:00<?, ?it/s, loss=0.0343, v_num=8, val_loss=0.581, val_top1_acc=0.811, val_d_prime=3.220, val_aucroc=0.958, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 407: 100% 7/7 [00:00<00:00, 61.72it/s, loss=0.0346, v_num=8, val_loss=0.583, val_top1_acc=0.811, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 410:   0% 0/7 [00:00<?, ?it/s, loss=0.035, v_num=8, val_loss=0.583, val_top1_acc=0.811, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 410: 100% 7/7 [00:00<00:00, 64.69it/s, loss=0.0351, v_num=8, val_loss=0.576, val_top1_acc=0.812, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.833]\n",
      "Epoch 413:   0% 0/7 [00:00<?, ?it/s, loss=0.0353, v_num=8, val_loss=0.576, val_top1_acc=0.812, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.833]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 413: 100% 7/7 [00:00<00:00, 79.18it/s, loss=0.0341, v_num=8, val_loss=0.601, val_top1_acc=0.801, val_d_prime=3.220, val_aucroc=0.959, val_mAP=0.832] \n",
      "Epoch 416:   0% 0/7 [00:00<?, ?it/s, loss=0.0332, v_num=8, val_loss=0.601, val_top1_acc=0.801, val_d_prime=3.220, val_aucroc=0.959, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 416: 100% 7/7 [00:00<00:00, 68.09it/s, loss=0.0329, v_num=8, val_loss=0.586, val_top1_acc=0.811, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 419:   0% 0/7 [00:00<?, ?it/s, loss=0.032, v_num=8, val_loss=0.586, val_top1_acc=0.811, val_d_prime=3.230, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 419: 100% 7/7 [00:00<00:00, 52.16it/s, loss=0.0317, v_num=8, val_loss=0.589, val_top1_acc=0.809, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 422:   0% 0/7 [00:00<?, ?it/s, loss=0.0311, v_num=8, val_loss=0.589, val_top1_acc=0.809, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 422: 100% 7/7 [00:00<00:00, 80.42it/s, loss=0.0307, v_num=8, val_loss=0.612, val_top1_acc=0.797, val_d_prime=3.210, val_aucroc=0.958, val_mAP=0.831] \n",
      "Epoch 425:   0% 0/7 [00:00<?, ?it/s, loss=0.0307, v_num=8, val_loss=0.612, val_top1_acc=0.797, val_d_prime=3.210, val_aucroc=0.958, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 425: 100% 7/7 [00:00<00:00, 68.66it/s, loss=0.0309, v_num=8, val_loss=0.586, val_top1_acc=0.809, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.835] \n",
      "Epoch 428:   0% 0/7 [00:00<?, ?it/s, loss=0.0307, v_num=8, val_loss=0.586, val_top1_acc=0.809, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.835]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 428: 100% 7/7 [00:00<00:00, 80.06it/s, loss=0.0303, v_num=8, val_loss=0.571, val_top1_acc=0.811, val_d_prime=3.250, val_aucroc=0.960, val_mAP=0.836] \n",
      "Epoch 431:   0% 0/7 [00:00<?, ?it/s, loss=0.03, v_num=8, val_loss=0.571, val_top1_acc=0.811, val_d_prime=3.250, val_aucroc=0.960, val_mAP=0.836]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 431: 100% 7/7 [00:00<00:00, 57.98it/s, loss=0.0298, v_num=8, val_loss=0.591, val_top1_acc=0.806, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 434:   0% 0/7 [00:00<?, ?it/s, loss=0.0297, v_num=8, val_loss=0.591, val_top1_acc=0.806, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 434: 100% 7/7 [00:00<00:00, 70.44it/s, loss=0.0296, v_num=8, val_loss=0.595, val_top1_acc=0.809, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.833] \n",
      "Epoch 437:   0% 0/7 [00:00<?, ?it/s, loss=0.029, v_num=8, val_loss=0.595, val_top1_acc=0.809, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.833]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 437: 100% 7/7 [00:00<00:00, 80.10it/s, loss=0.0289, v_num=8, val_loss=0.592, val_top1_acc=0.807, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 440:   0% 0/7 [00:00<?, ?it/s, loss=0.0284, v_num=8, val_loss=0.592, val_top1_acc=0.807, val_d_prime=3.240, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 440: 100% 7/7 [00:00<00:00, 60.08it/s, loss=0.0283, v_num=8, val_loss=0.575, val_top1_acc=0.814, val_d_prime=3.250, val_aucroc=0.960, val_mAP=0.836]\n",
      "Epoch 443:   0% 0/7 [00:00<?, ?it/s, loss=0.028, v_num=8, val_loss=0.575, val_top1_acc=0.814, val_d_prime=3.250, val_aucroc=0.960, val_mAP=0.836]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 443: 100% 7/7 [00:00<00:00, 53.81it/s, loss=0.0282, v_num=8, val_loss=0.578, val_top1_acc=0.812, val_d_prime=3.250, val_aucroc=0.960, val_mAP=0.836]\n",
      "Epoch 446:   0% 0/7 [00:00<?, ?it/s, loss=0.0279, v_num=8, val_loss=0.578, val_top1_acc=0.812, val_d_prime=3.250, val_aucroc=0.960, val_mAP=0.836]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 446: 100% 7/7 [00:00<00:00, 70.28it/s, loss=0.028, v_num=8, val_loss=0.591, val_top1_acc=0.811, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.834]  \n",
      "Epoch 449:   0% 0/7 [00:00<?, ?it/s, loss=0.0282, v_num=8, val_loss=0.591, val_top1_acc=0.811, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 449: 100% 7/7 [00:00<00:00, 54.82it/s, loss=0.0278, v_num=8, val_loss=0.595, val_top1_acc=0.808, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.834]\n",
      "Epoch 452:   0% 0/7 [00:00<?, ?it/s, loss=0.0269, v_num=8, val_loss=0.595, val_top1_acc=0.808, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 452: 100% 7/7 [00:00<00:00, 58.67it/s, loss=0.0271, v_num=8, val_loss=0.601, val_top1_acc=0.810, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.835]\n",
      "Epoch 452: 100% 7/7 [00:00<00:00, 55.76it/s, loss=0.0271, v_num=8, val_loss=0.601, val_top1_acc=0.810, val_d_prime=3.250, val_aucroc=0.959, val_mAP=0.835]\n",
      "FIT Profiler Report\n",
      "\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                              \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                               \t|  -              \t|  129115         \t|  37.259         \t|  100 %          \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                  \t|  0.08025        \t|  453            \t|  36.353         \t|  97.568         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                  \t|  0.0038716      \t|  2265           \t|  8.7691         \t|  23.535         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                \t|  0.003553       \t|  2265           \t|  8.0476         \t|  21.599         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                          \t|  0.031854       \t|  151            \t|  4.8099         \t|  12.909         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                        \t|  0.0015094      \t|  2265           \t|  3.4188         \t|  9.1758         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                             \t|  0.00086097     \t|  2265           \t|  1.9501         \t|  5.2339         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                 \t|  0.012299       \t|  151            \t|  1.8572         \t|  4.9845         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                  \t|  0.00031309     \t|  2265           \t|  0.70915        \t|  1.9033         \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                \t|  0.00018483     \t|  2265           \t|  0.41863        \t|  1.1236         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                      \t|  0.00010058     \t|  2567           \t|  0.25819        \t|  0.69296        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                           \t|  0.000109       \t|  2265           \t|  0.24688        \t|  0.66261        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                      \t|  0.00066784     \t|  302            \t|  0.20169        \t|  0.54131        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                        \t|  0.00036245     \t|  453            \t|  0.16419        \t|  0.44067        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                      \t|  0.00025083     \t|  453            \t|  0.11363        \t|  0.30497        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                         \t|  0.00059906     \t|  151            \t|  0.090458       \t|  0.24278        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                 \t|  0.00047375     \t|  151            \t|  0.071536       \t|  0.192          \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                   \t|  0.00017963     \t|  302            \t|  0.054247       \t|  0.14559        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                       \t|  0.00028195     \t|  151            \t|  0.042574       \t|  0.11426        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                 \t|  0.00013777     \t|  302            \t|  0.041607       \t|  0.11167        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                 \t|  6.9613e-06     \t|  2265           \t|  0.015767       \t|  0.042318       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                     \t|  8.3876e-05     \t|  151            \t|  0.012665       \t|  0.033992       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                               \t|  5.5301e-06     \t|  2265           \t|  0.012526       \t|  0.033617       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                \t|  2.6662e-05     \t|  453            \t|  0.012078       \t|  0.032416       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                    \t|  5.2053e-06     \t|  2265           \t|  0.01179        \t|  0.031643       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                      \t|  7.6136e-05     \t|  151            \t|  0.011497       \t|  0.030855       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                      \t|  4.6392e-06     \t|  2265           \t|  0.010508       \t|  0.028202       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                         \t|  4.3358e-06     \t|  2265           \t|  0.0098205      \t|  0.026357       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                          \t|  4.2763e-06     \t|  2265           \t|  0.0096857      \t|  0.025995       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                \t|  4.271e-06      \t|  2265           \t|  0.0096739      \t|  0.025964       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                            \t|  3.9924e-06     \t|  2265           \t|  0.0090428      \t|  0.02427        \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                           \t|  3.9917e-06     \t|  2265           \t|  0.0090413      \t|  0.024266       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                       \t|  3.9335e-06     \t|  2265           \t|  0.0089094      \t|  0.023912       \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                            \t|  3.9065e-06     \t|  2265           \t|  0.0088481      \t|  0.023747       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                    \t|  3.8711e-06     \t|  2265           \t|  0.0087679      \t|  0.023532       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                 \t|  3.8272e-06     \t|  2265           \t|  0.0086686      \t|  0.023266       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                  \t|  3.7877e-06     \t|  2265           \t|  0.008579       \t|  0.023025       \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                               \t|  3.7613e-06     \t|  2265           \t|  0.0085193      \t|  0.022865       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                          \t|  3.7538e-06     \t|  2265           \t|  0.0085023      \t|  0.022819       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step          \t|  3.7194e-06     \t|  2265           \t|  0.0084243      \t|  0.02261        \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                              \t|  3.7159e-06     \t|  2265           \t|  0.0084165      \t|  0.022589       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                    \t|  3.711e-06      \t|  2265           \t|  0.0084055      \t|  0.022559       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad               \t|  3.701e-06      \t|  2265           \t|  0.0083828      \t|  0.022498       \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                 \t|  3.6895e-06     \t|  2265           \t|  0.0083567      \t|  0.022429       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                        \t|  3.6812e-06     \t|  2265           \t|  0.0083379      \t|  0.022378       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                      \t|  3.6796e-06     \t|  2265           \t|  0.0083343      \t|  0.022368       \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                     \t|  3.6736e-06     \t|  2265           \t|  0.0083208      \t|  0.022332       \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                           \t|  3.5814e-06     \t|  2265           \t|  0.0081119      \t|  0.021771       \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                          \t|  3.5612e-06     \t|  2265           \t|  0.008066       \t|  0.021648       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                \t|  3.5247e-06     \t|  2265           \t|  0.0079835      \t|  0.021427       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                              \t|  3.5081e-06     \t|  2265           \t|  0.0079459      \t|  0.021326       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                \t|  3.4592e-06     \t|  2265           \t|  0.0078351      \t|  0.021028       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                         \t|  3.4344e-06     \t|  2265           \t|  0.0077789      \t|  0.020878       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                           \t|  1.1845e-05     \t|  453            \t|  0.0053656      \t|  0.014401       \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                             \t|  2.0733e-06     \t|  2265           \t|  0.004696       \t|  0.012604       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                            \t|  1.9694e-06     \t|  2265           \t|  0.0044607      \t|  0.011972       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                         \t|  9.5696e-06     \t|  453            \t|  0.004335       \t|  0.011635       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                             \t|  1.8986e-06     \t|  2265           \t|  0.0043004      \t|  0.011542       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                          \t|  1.8762e-06     \t|  2265           \t|  0.0042495      \t|  0.011405       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                        \t|  9.1898e-06     \t|  453            \t|  0.004163       \t|  0.011173       \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                 \t|  1.5273e-06     \t|  2265           \t|  0.0034593      \t|  0.0092844      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                           \t|  1.5197e-06     \t|  2265           \t|  0.0034422      \t|  0.0092384      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                    \t|  1.5144e-06     \t|  2265           \t|  0.0034301      \t|  0.0092061      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                            \t|  1.4164e-06     \t|  2265           \t|  0.0032082      \t|  0.0086103      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                      \t|  1.4131e-06     \t|  2265           \t|  0.0032007      \t|  0.0085904      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                    \t|  4.4802e-06     \t|  604            \t|  0.002706       \t|  0.0072627      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                      \t|  4.0706e-06     \t|  604            \t|  0.0024587      \t|  0.0065988      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                      \t|  8.0803e-06     \t|  302            \t|  0.0024402      \t|  0.0065494      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                \t|  5.3053e-06     \t|  453            \t|  0.0024033      \t|  0.0064503      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                            \t|  3.8064e-06     \t|  604            \t|  0.0022991      \t|  0.0061705      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                    \t|  3.6982e-06     \t|  604            \t|  0.0022337      \t|  0.005995       \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                    \t|  7.2857e-06     \t|  302            \t|  0.0022003      \t|  0.0059053      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                              \t|  3.5697e-06     \t|  604            \t|  0.0021561      \t|  0.0057867      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                      \t|  3.5533e-06     \t|  604            \t|  0.0021462      \t|  0.0057601      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                \t|  3.5452e-06     \t|  604            \t|  0.0021413      \t|  0.005747       \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                               \t|  3.5381e-06     \t|  604            \t|  0.002137       \t|  0.0057354      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                              \t|  3.5358e-06     \t|  604            \t|  0.0021356      \t|  0.0057319      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                 \t|  3.4882e-06     \t|  604            \t|  0.0021068      \t|  0.0056546      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                          \t|  4.4161e-06     \t|  453            \t|  0.0020005      \t|  0.0053691      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                            \t|  1.1965e-05     \t|  151            \t|  0.0018067      \t|  0.0048491      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start              \t|  3.9504e-06     \t|  453            \t|  0.0017895      \t|  0.0048029      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                         \t|  5.634e-06      \t|  302            \t|  0.0017015      \t|  0.0045666      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                              \t|  3.7351e-06     \t|  453            \t|  0.001692       \t|  0.0045412      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                           \t|  5.0958e-06     \t|  302            \t|  0.0015389      \t|  0.0041304      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                     \t|  4.7033e-06     \t|  302            \t|  0.0014204      \t|  0.0038122      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                          \t|  9.1426e-06     \t|  151            \t|  0.0013805      \t|  0.0037052      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                   \t|  4.4721e-06     \t|  302            \t|  0.0013506      \t|  0.0036248      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                   \t|  8.6388e-06     \t|  151            \t|  0.0013045      \t|  0.003501       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end           \t|  4.2239e-06     \t|  302            \t|  0.0012756      \t|  0.0034236      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start         \t|  3.8565e-06     \t|  302            \t|  0.0011647      \t|  0.0031258      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                               \t|  6.7227e-06     \t|  151            \t|  0.0010151      \t|  0.0027245      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                \t|  1.6333e-06     \t|  604            \t|  0.00098654     \t|  0.0026478      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                           \t|  6.2019e-06     \t|  151            \t|  0.00093649     \t|  0.0025134      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                  \t|  1.4733e-06     \t|  604            \t|  0.0008899      \t|  0.0023884      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                            \t|  1.8763e-06     \t|  453            \t|  0.00084995     \t|  0.0022812      \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                           \t|  2.7517e-06     \t|  302            \t|  0.000831       \t|  0.0022303      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                          \t|  1.6674e-06     \t|  453            \t|  0.00075535     \t|  0.0020273      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                           \t|  4.6342e-06     \t|  151            \t|  0.00069977     \t|  0.0018781      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                         \t|  4.2131e-06     \t|  151            \t|  0.00063618     \t|  0.0017075      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                      \t|  4.1096e-06     \t|  151            \t|  0.00062054     \t|  0.0016655      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                         \t|  4.0309e-06     \t|  151            \t|  0.00060867     \t|  0.0016336      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start               \t|  4.0051e-06     \t|  151            \t|  0.00060477     \t|  0.0016231      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                       \t|  1.9887e-06     \t|  302            \t|  0.0006006      \t|  0.0016119      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                 \t|  3.8187e-06     \t|  151            \t|  0.00057663     \t|  0.0015476      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                 \t|  0.00057489     \t|  1              \t|  0.00057489     \t|  0.0015429      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end           \t|  3.7125e-06     \t|  151            \t|  0.00056058     \t|  0.0015045      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                     \t|  3.563e-06      \t|  151            \t|  0.00053802     \t|  0.001444       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start         \t|  3.4822e-06     \t|  151            \t|  0.00052582     \t|  0.0014112      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                     \t|  1.7288e-06     \t|  302            \t|  0.00052209     \t|  0.0014012      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                    \t|  3.3934e-06     \t|  151            \t|  0.0005124      \t|  0.0013752      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                  \t|  1.6522e-06     \t|  302            \t|  0.00049897     \t|  0.0013392      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                   \t|  3.2978e-06     \t|  151            \t|  0.00049796     \t|  0.0013365      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                             \t|  3.0264e-06     \t|  151            \t|  0.00045699     \t|  0.0012265      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                    \t|  2.4578e-06     \t|  151            \t|  0.00037113     \t|  0.00099608     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                           \t|  1.946e-06      \t|  151            \t|  0.00029384     \t|  0.00078864     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                \t|  6.5843e-06     \t|  41             \t|  0.00026996     \t|  0.00072454     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                       \t|  1.7001e-06     \t|  151            \t|  0.00025672     \t|  0.00068901     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                  \t|  1.6805e-06     \t|  151            \t|  0.00025375     \t|  0.00068104     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                     \t|  1.6672e-06     \t|  151            \t|  0.00025175     \t|  0.00067568     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                           \t|  4.5613e-06     \t|  41             \t|  0.00018701     \t|  0.00050192     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                            \t|  0.00018631     \t|  1              \t|  0.00018631     \t|  0.00050005     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                        \t|  4.4585e-06     \t|  41             \t|  0.0001828      \t|  0.00049061     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                              \t|  0.00017526     \t|  1              \t|  0.00017526     \t|  0.00047039     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                \t|  4.1448e-06     \t|  41             \t|  0.00016994     \t|  0.0004561      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                          \t|  3.9217e-06     \t|  41             \t|  0.00016079     \t|  0.00043154     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                              \t|  0.00014216     \t|  1              \t|  0.00014216     \t|  0.00038154     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                          \t|  0.00010466     \t|  1              \t|  0.00010466     \t|  0.0002809      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                            \t|  1.9794e-06     \t|  41             \t|  8.1155e-05     \t|  0.00021781     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                \t|  1.2081e-05     \t|  1              \t|  1.2081e-05     \t|  3.2424e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                               \t|  8.659e-06      \t|  1              \t|  8.659e-06      \t|  2.324e-05      \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                 \t|  7.795e-06      \t|  1              \t|  7.795e-06      \t|  2.0921e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                        \t|  6.091e-06      \t|  1              \t|  6.091e-06      \t|  1.6348e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                     \t|  5.811e-06      \t|  1              \t|  5.811e-06      \t|  1.5596e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                         \t|  5.543e-06      \t|  1              \t|  5.543e-06      \t|  1.4877e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                    \t|  5.336e-06      \t|  1              \t|  5.336e-06      \t|  1.4321e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                      \t|  5.149e-06      \t|  1              \t|  5.149e-06      \t|  1.3819e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                           \t|  5.11e-06       \t|  1              \t|  5.11e-06       \t|  1.3715e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                   \t|  4.859e-06      \t|  1              \t|  4.859e-06      \t|  1.3041e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                               \t|  4.43e-06       \t|  1              \t|  4.43e-06       \t|  1.189e-05      \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                      \t|  4.331e-06      \t|  1              \t|  4.331e-06      \t|  1.1624e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                      \t|  4.274e-06      \t|  1              \t|  4.274e-06      \t|  1.1471e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                           \t|  4.217e-06      \t|  1              \t|  4.217e-06      \t|  1.1318e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                             \t|  4.127e-06      \t|  1              \t|  4.127e-06      \t|  1.1076e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                    \t|  4.041e-06      \t|  1              \t|  4.041e-06      \t|  1.0846e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                        \t|  4.018e-06      \t|  1              \t|  4.018e-06      \t|  1.0784e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                      \t|  3.839e-06      \t|  1              \t|  3.839e-06      \t|  1.0303e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                \t|  3.688e-06      \t|  1              \t|  3.688e-06      \t|  9.8982e-06     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                        \t|  3.588e-06      \t|  1              \t|  3.588e-06      \t|  9.6298e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                          \t|  3.534e-06      \t|  1              \t|  3.534e-06      \t|  9.4849e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                 \t|  3.493e-06      \t|  1              \t|  3.493e-06      \t|  9.3748e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                              \t|  3.449e-06      \t|  1              \t|  3.449e-06      \t|  9.2568e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                  \t|  3.344e-06      \t|  1              \t|  3.344e-06      \t|  8.9749e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                \t|  3.177e-06      \t|  1              \t|  3.177e-06      \t|  8.5267e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                              \t|  3.169e-06      \t|  1              \t|  3.169e-06      \t|  8.5053e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                             \t|  3.159e-06      \t|  1              \t|  3.159e-06      \t|  8.4784e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup\t|  3.113e-06      \t|  1              \t|  3.113e-06      \t|  8.355e-06      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                       \t|  3.103e-06      \t|  1              \t|  3.103e-06      \t|  8.3281e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start         \t|  3.103e-06      \t|  1              \t|  3.103e-06      \t|  8.3281e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                \t|  3.078e-06      \t|  1              \t|  3.078e-06      \t|  8.261e-06      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                      \t|  3.03e-06       \t|  1              \t|  3.03e-06       \t|  8.1322e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                     \t|  3.017e-06      \t|  1              \t|  3.017e-06      \t|  8.0973e-06     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                    \t|  2.994e-06      \t|  1              \t|  2.994e-06      \t|  8.0356e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                  \t|  2.994e-06      \t|  1              \t|  2.994e-06      \t|  8.0356e-06     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                   \t|  2.98e-06       \t|  1              \t|  2.98e-06       \t|  7.998e-06      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                         \t|  2.957e-06      \t|  1              \t|  2.957e-06      \t|  7.9363e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                       \t|  2.932e-06      \t|  1              \t|  2.932e-06      \t|  7.8692e-06     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                          \t|  2.889e-06      \t|  1              \t|  2.889e-06      \t|  7.7538e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                   \t|  2.858e-06      \t|  1              \t|  2.858e-06      \t|  7.6706e-06     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                     \t|  2.839e-06      \t|  1              \t|  2.839e-06      \t|  7.6196e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                  \t|  2.833e-06      \t|  1              \t|  2.833e-06      \t|  7.6035e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model        \t|  2.815e-06      \t|  1              \t|  2.815e-06      \t|  7.5552e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                  \t|  2.803e-06      \t|  1              \t|  2.803e-06      \t|  7.523e-06      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                        \t|  2.8e-06        \t|  1              \t|  2.8e-06        \t|  7.5149e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end           \t|  2.78e-06       \t|  1              \t|  2.78e-06       \t|  7.4612e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                          \t|  2.777e-06      \t|  1              \t|  2.777e-06      \t|  7.4532e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                    \t|  2.758e-06      \t|  1              \t|  2.758e-06      \t|  7.4022e-06     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                   \t|  2.701e-06      \t|  1              \t|  2.701e-06      \t|  7.2492e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                       \t|  2.611e-06      \t|  1              \t|  2.611e-06      \t|  7.0077e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                           \t|  2.283e-06      \t|  1              \t|  2.283e-06      \t|  6.1273e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                \t|  1.685e-06      \t|  1              \t|  1.685e-06      \t|  4.5224e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                  \t|  1.681e-06      \t|  1              \t|  1.681e-06      \t|  4.5116e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                         \t|  1.673e-06      \t|  1              \t|  1.673e-06      \t|  4.4902e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                    \t|  1.596e-06      \t|  1              \t|  1.596e-06      \t|  4.2835e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                      \t|  1.533e-06      \t|  1              \t|  1.533e-06      \t|  4.1144e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                     \t|  1.419e-06      \t|  1              \t|  1.419e-06      \t|  3.8084e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                  \t|  1.375e-06      \t|  1              \t|  1.375e-06      \t|  3.6904e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                       \t|  1.345e-06      \t|  1              \t|  1.345e-06      \t|  3.6098e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                         \t|  1.325e-06      \t|  1              \t|  1.325e-06      \t|  3.5562e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                       \t|  1.121e-06      \t|  1              \t|  1.121e-06      \t|  3.0086e-06     \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "predict - mridangam_stroke - 2022-06-03 21:09:31,020 - 20 - Validation Score for the Training Split: 0.8157706260681152\n",
      "\n",
      "split: 1it [00:37, 37.34s/it]\u001B[Apredict - mridangam_stroke - 2022-06-03 21:09:31,021 - 21 - Training split 3 of 5: {'train': ['fold00', 'fold01', 'fold04'], 'valid': ['fold03'], 'test': ['fold02']}\n",
      "/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "==========================================================================================\n",
      "Layer (type:depth-idx)                   Output Shape              Param #\n",
      "==========================================================================================\n",
      "FullyConnectedPrediction                 [64, 6]                   --\n",
      "├─Sequential: 1-1                        [64, 1024]                --\n",
      "│    └─Linear: 2-1                       [64, 1024]                1,049,600\n",
      "│    └─BatchNorm1d: 2-2                  [64, 1024]                2,048\n",
      "│    └─Dropout: 2-3                      [64, 1024]                --\n",
      "│    └─ReLU: 2-4                         [64, 1024]                --\n",
      "├─Linear: 1-2                            [64, 6]                   6,150\n",
      "├─Softmax: 1-3                           [64, 6]                   --\n",
      "├─OneHotToCrossEntropyLoss: 1-4          --                        --\n",
      "│    └─CrossEntropyLoss: 2-5             --                        --\n",
      "==========================================================================================\n",
      "Total params: 1,057,798\n",
      "Trainable params: 1,057,798\n",
      "Non-trainable params: 0\n",
      "Total mult-adds (M): 67.70\n",
      "==========================================================================================\n",
      "Input size (MB): 0.26\n",
      "Forward/backward pass size (MB): 1.05\n",
      "Params size (MB): 4.23\n",
      "Estimated Total Size (MB): 5.55\n",
      "==========================================================================================\n",
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 107605.55it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 33601.80it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 80158.37it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 26684.87it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 82512.64it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 33163.04it/s]\n",
      "Getting embeddings for split ['fold00', 'fold01', 'fold04'], which has 4187 instances.\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 107518.59it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 24561.66it/s]\n",
      "Getting embeddings for split ['fold03'], which has 1395 instances.\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name      | Type                     | Params\n",
      "-------------------------------------------------------\n",
      "0 | layernorm | Identity                 | 0     \n",
      "1 | predictor | FullyConnectedPrediction | 1.1 M \n",
      "-------------------------------------------------------\n",
      "1.1 M     Trainable params\n",
      "0         Non-trainable params\n",
      "1.1 M     Total params\n",
      "4.231     Total estimated model params size (MB)\n",
      "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py:1937: PossibleUserWarning: The number of training batches (5) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n",
      "  category=PossibleUserWarning,\n",
      "Epoch 0:   0% 0/5 [00:00<?, ?it/s] /usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Epoch 2:   0% 0/7 [00:00<?, ?it/s, loss=1.9, v_num=9]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Epoch 2: 100% 7/7 [00:00<00:00, 128.34it/s, loss=1.9, v_num=9]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Epoch 2: 100% 7/7 [00:00<00:00, 77.57it/s, loss=1.75, v_num=9, val_loss=1.640, val_top1_acc=0.278, val_d_prime=1.000, val_aucroc=0.748, val_mAP=0.416]\n",
      "Epoch 5:   0% 0/7 [00:00<?, ?it/s, loss=1.4, v_num=9, val_loss=1.640, val_top1_acc=0.278, val_d_prime=1.000, val_aucroc=0.748, val_mAP=0.416]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 5: 100% 7/7 [00:00<00:00, 69.20it/s, loss=1.28, v_num=9, val_loss=1.260, val_top1_acc=0.499, val_d_prime=1.590, val_aucroc=0.852, val_mAP=0.581]\n",
      "Epoch 8:   0% 0/7 [00:00<?, ?it/s, loss=1.12, v_num=9, val_loss=1.260, val_top1_acc=0.499, val_d_prime=1.590, val_aucroc=0.852, val_mAP=0.581]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 8: 100% 7/7 [00:00<00:00, 79.38it/s, loss=1.06, v_num=9, val_loss=1.070, val_top1_acc=0.573, val_d_prime=1.960, val_aucroc=0.890, val_mAP=0.656] \n",
      "Epoch 11:   0% 0/7 [00:00<?, ?it/s, loss=0.961, v_num=9, val_loss=1.070, val_top1_acc=0.573, val_d_prime=1.960, val_aucroc=0.890, val_mAP=0.656]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 11: 100% 7/7 [00:00<00:00, 79.94it/s, loss=0.919, v_num=9, val_loss=0.973, val_top1_acc=0.620, val_d_prime=2.130, val_aucroc=0.906, val_mAP=0.697] \n",
      "Epoch 14:   0% 0/7 [00:00<?, ?it/s, loss=0.845, v_num=9, val_loss=0.973, val_top1_acc=0.620, val_d_prime=2.130, val_aucroc=0.906, val_mAP=0.697]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 14: 100% 7/7 [00:00<00:00, 77.64it/s, loss=0.812, v_num=9, val_loss=0.889, val_top1_acc=0.686, val_d_prime=2.290, val_aucroc=0.916, val_mAP=0.723] \n",
      "Epoch 17:   0% 0/7 [00:00<?, ?it/s, loss=0.763, v_num=9, val_loss=0.889, val_top1_acc=0.686, val_d_prime=2.290, val_aucroc=0.916, val_mAP=0.723]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 17: 100% 7/7 [00:00<00:00, 61.12it/s, loss=0.738, v_num=9, val_loss=0.828, val_top1_acc=0.708, val_d_prime=2.410, val_aucroc=0.924, val_mAP=0.745]\n",
      "Epoch 20:   0% 0/7 [00:00<?, ?it/s, loss=0.695, v_num=9, val_loss=0.828, val_top1_acc=0.708, val_d_prime=2.410, val_aucroc=0.924, val_mAP=0.745]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 20: 100% 7/7 [00:00<00:00, 55.60it/s, loss=0.673, v_num=9, val_loss=0.794, val_top1_acc=0.726, val_d_prime=2.490, val_aucroc=0.930, val_mAP=0.759]\n",
      "Epoch 23:   0% 0/7 [00:00<?, ?it/s, loss=0.64, v_num=9, val_loss=0.794, val_top1_acc=0.726, val_d_prime=2.490, val_aucroc=0.930, val_mAP=0.759]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 23: 100% 7/7 [00:00<00:00, 66.48it/s, loss=0.627, v_num=9, val_loss=0.757, val_top1_acc=0.736, val_d_prime=2.570, val_aucroc=0.934, val_mAP=0.770]\n",
      "Epoch 26:   0% 0/7 [00:00<?, ?it/s, loss=0.598, v_num=9, val_loss=0.757, val_top1_acc=0.736, val_d_prime=2.570, val_aucroc=0.934, val_mAP=0.770]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 26: 100% 7/7 [00:00<00:00, 79.30it/s, loss=0.585, v_num=9, val_loss=0.726, val_top1_acc=0.748, val_d_prime=2.640, val_aucroc=0.937, val_mAP=0.780] \n",
      "Epoch 29:   0% 0/7 [00:00<?, ?it/s, loss=0.557, v_num=9, val_loss=0.726, val_top1_acc=0.748, val_d_prime=2.640, val_aucroc=0.937, val_mAP=0.780]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 29: 100% 7/7 [00:00<00:00, 63.57it/s, loss=0.547, v_num=9, val_loss=0.716, val_top1_acc=0.747, val_d_prime=2.690, val_aucroc=0.940, val_mAP=0.787] \n",
      "Epoch 32:   0% 0/7 [00:00<?, ?it/s, loss=0.527, v_num=9, val_loss=0.716, val_top1_acc=0.747, val_d_prime=2.690, val_aucroc=0.940, val_mAP=0.787]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 32: 100% 7/7 [00:00<00:00, 77.32it/s, loss=0.515, v_num=9, val_loss=0.708, val_top1_acc=0.746, val_d_prime=2.740, val_aucroc=0.942, val_mAP=0.794] \n",
      "Epoch 35:   0% 0/7 [00:00<?, ?it/s, loss=0.495, v_num=9, val_loss=0.708, val_top1_acc=0.746, val_d_prime=2.740, val_aucroc=0.942, val_mAP=0.794]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 35: 100% 7/7 [00:00<00:00, 69.77it/s, loss=0.484, v_num=9, val_loss=0.673, val_top1_acc=0.766, val_d_prime=2.790, val_aucroc=0.944, val_mAP=0.802]\n",
      "Epoch 38:   0% 0/7 [00:00<?, ?it/s, loss=0.465, v_num=9, val_loss=0.673, val_top1_acc=0.766, val_d_prime=2.790, val_aucroc=0.944, val_mAP=0.802]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 38: 100% 7/7 [00:00<00:00, 80.89it/s, loss=0.457, v_num=9, val_loss=0.658, val_top1_acc=0.771, val_d_prime=2.830, val_aucroc=0.946, val_mAP=0.805] \n",
      "Epoch 41:   0% 0/7 [00:00<?, ?it/s, loss=0.444, v_num=9, val_loss=0.658, val_top1_acc=0.771, val_d_prime=2.830, val_aucroc=0.946, val_mAP=0.805]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 41: 100% 7/7 [00:00<00:00, 69.83it/s, loss=0.437, v_num=9, val_loss=0.657, val_top1_acc=0.761, val_d_prime=2.870, val_aucroc=0.948, val_mAP=0.812]\n",
      "Epoch 44:   0% 0/7 [00:00<?, ?it/s, loss=0.424, v_num=9, val_loss=0.657, val_top1_acc=0.761, val_d_prime=2.870, val_aucroc=0.948, val_mAP=0.812]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 44: 100% 7/7 [00:00<00:00, 58.09it/s, loss=0.417, v_num=9, val_loss=0.642, val_top1_acc=0.769, val_d_prime=2.900, val_aucroc=0.950, val_mAP=0.818]\n",
      "Epoch 47:   0% 0/7 [00:00<?, ?it/s, loss=0.404, v_num=9, val_loss=0.642, val_top1_acc=0.769, val_d_prime=2.900, val_aucroc=0.950, val_mAP=0.818]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 47: 100% 7/7 [00:00<00:00, 80.23it/s, loss=0.396, v_num=9, val_loss=0.629, val_top1_acc=0.775, val_d_prime=2.920, val_aucroc=0.951, val_mAP=0.821] \n",
      "Epoch 50:   0% 0/7 [00:00<?, ?it/s, loss=0.384, v_num=9, val_loss=0.629, val_top1_acc=0.775, val_d_prime=2.920, val_aucroc=0.951, val_mAP=0.821]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 50: 100% 7/7 [00:00<00:00, 78.52it/s, loss=0.379, v_num=9, val_loss=0.617, val_top1_acc=0.777, val_d_prime=2.950, val_aucroc=0.952, val_mAP=0.825] \n",
      "Epoch 53:   0% 0/7 [00:00<?, ?it/s, loss=0.369, v_num=9, val_loss=0.617, val_top1_acc=0.777, val_d_prime=2.950, val_aucroc=0.952, val_mAP=0.825]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 53: 100% 7/7 [00:00<00:00, 60.27it/s, loss=0.364, v_num=9, val_loss=0.615, val_top1_acc=0.781, val_d_prime=2.980, val_aucroc=0.954, val_mAP=0.830]\n",
      "Epoch 56:   0% 0/7 [00:00<?, ?it/s, loss=0.355, v_num=9, val_loss=0.615, val_top1_acc=0.781, val_d_prime=2.980, val_aucroc=0.954, val_mAP=0.830]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 56: 100% 7/7 [00:00<00:00, 60.74it/s, loss=0.351, v_num=9, val_loss=0.605, val_top1_acc=0.786, val_d_prime=3.000, val_aucroc=0.954, val_mAP=0.831] \n",
      "Epoch 59:   0% 0/7 [00:00<?, ?it/s, loss=0.34, v_num=9, val_loss=0.605, val_top1_acc=0.786, val_d_prime=3.000, val_aucroc=0.954, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 59: 100% 7/7 [00:00<00:00, 64.79it/s, loss=0.336, v_num=9, val_loss=0.591, val_top1_acc=0.786, val_d_prime=3.020, val_aucroc=0.955, val_mAP=0.835]\n",
      "Epoch 62:   0% 0/7 [00:00<?, ?it/s, loss=0.326, v_num=9, val_loss=0.591, val_top1_acc=0.786, val_d_prime=3.020, val_aucroc=0.955, val_mAP=0.835]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 62: 100% 7/7 [00:00<00:00, 80.81it/s, loss=0.322, v_num=9, val_loss=0.601, val_top1_acc=0.789, val_d_prime=3.030, val_aucroc=0.956, val_mAP=0.839] \n",
      "Epoch 65:   0% 0/7 [00:00<?, ?it/s, loss=0.318, v_num=9, val_loss=0.601, val_top1_acc=0.789, val_d_prime=3.030, val_aucroc=0.956, val_mAP=0.839]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 65: 100% 7/7 [00:00<00:00, 73.52it/s, loss=0.316, v_num=9, val_loss=0.579, val_top1_acc=0.794, val_d_prime=3.050, val_aucroc=0.957, val_mAP=0.841] \n",
      "Epoch 68:   0% 0/7 [00:00<?, ?it/s, loss=0.308, v_num=9, val_loss=0.579, val_top1_acc=0.794, val_d_prime=3.050, val_aucroc=0.957, val_mAP=0.841]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 68: 100% 7/7 [00:00<00:00, 63.39it/s, loss=0.304, v_num=9, val_loss=0.585, val_top1_acc=0.792, val_d_prime=3.070, val_aucroc=0.958, val_mAP=0.843]\n",
      "Epoch 71:   0% 0/7 [00:00<?, ?it/s, loss=0.296, v_num=9, val_loss=0.585, val_top1_acc=0.792, val_d_prime=3.070, val_aucroc=0.958, val_mAP=0.843]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 71: 100% 7/7 [00:00<00:00, 71.47it/s, loss=0.293, v_num=9, val_loss=0.579, val_top1_acc=0.790, val_d_prime=3.090, val_aucroc=0.958, val_mAP=0.845] \n",
      "Epoch 74:   0% 0/7 [00:00<?, ?it/s, loss=0.286, v_num=9, val_loss=0.579, val_top1_acc=0.790, val_d_prime=3.090, val_aucroc=0.958, val_mAP=0.845]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Validation DataLoader 0: 100% 2/2 [00:00<00:00, 10.58it/s]\u001B[A\n",
      "Epoch 74: 100% 7/7 [00:00<00:00, 23.94it/s, loss=0.284, v_num=9, val_loss=0.576, val_top1_acc=0.795, val_d_prime=3.080, val_aucroc=0.959, val_mAP=0.846]\n",
      "Epoch 77:   0% 0/7 [00:00<?, ?it/s, loss=0.279, v_num=9, val_loss=0.576, val_top1_acc=0.795, val_d_prime=3.080, val_aucroc=0.959, val_mAP=0.846]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 77: 100% 7/7 [00:00<00:00, 80.76it/s, loss=0.275, v_num=9, val_loss=0.573, val_top1_acc=0.796, val_d_prime=3.110, val_aucroc=0.959, val_mAP=0.849] \n",
      "Epoch 80:   0% 0/7 [00:00<?, ?it/s, loss=0.269, v_num=9, val_loss=0.573, val_top1_acc=0.796, val_d_prime=3.110, val_aucroc=0.959, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 80: 100% 7/7 [00:00<00:00, 74.26it/s, loss=0.266, v_num=9, val_loss=0.566, val_top1_acc=0.796, val_d_prime=3.110, val_aucroc=0.960, val_mAP=0.851] \n",
      "Epoch 83:   0% 0/7 [00:00<?, ?it/s, loss=0.262, v_num=9, val_loss=0.566, val_top1_acc=0.796, val_d_prime=3.110, val_aucroc=0.960, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 83: 100% 7/7 [00:00<00:00, 59.49it/s, loss=0.258, v_num=9, val_loss=0.560, val_top1_acc=0.799, val_d_prime=3.140, val_aucroc=0.961, val_mAP=0.854]\n",
      "Epoch 86:   0% 0/7 [00:00<?, ?it/s, loss=0.254, v_num=9, val_loss=0.560, val_top1_acc=0.799, val_d_prime=3.140, val_aucroc=0.961, val_mAP=0.854]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 86: 100% 7/7 [00:00<00:00, 63.22it/s, loss=0.252, v_num=9, val_loss=0.562, val_top1_acc=0.799, val_d_prime=3.140, val_aucroc=0.961, val_mAP=0.855] \n",
      "Epoch 89:   0% 0/7 [00:00<?, ?it/s, loss=0.248, v_num=9, val_loss=0.562, val_top1_acc=0.799, val_d_prime=3.140, val_aucroc=0.961, val_mAP=0.855]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 89: 100% 7/7 [00:00<00:00, 76.57it/s, loss=0.245, v_num=9, val_loss=0.571, val_top1_acc=0.802, val_d_prime=3.160, val_aucroc=0.962, val_mAP=0.856] \n",
      "Epoch 92:   0% 0/7 [00:00<?, ?it/s, loss=0.239, v_num=9, val_loss=0.571, val_top1_acc=0.802, val_d_prime=3.160, val_aucroc=0.962, val_mAP=0.856]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 92: 100% 7/7 [00:00<00:00, 80.54it/s, loss=0.237, v_num=9, val_loss=0.565, val_top1_acc=0.801, val_d_prime=3.160, val_aucroc=0.962, val_mAP=0.858] \n",
      "Epoch 95:   0% 0/7 [00:00<?, ?it/s, loss=0.233, v_num=9, val_loss=0.565, val_top1_acc=0.801, val_d_prime=3.160, val_aucroc=0.962, val_mAP=0.858]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 95: 100% 7/7 [00:00<00:00, 63.42it/s, loss=0.231, v_num=9, val_loss=0.548, val_top1_acc=0.804, val_d_prime=3.180, val_aucroc=0.963, val_mAP=0.859]\n",
      "Epoch 98:   0% 0/7 [00:00<?, ?it/s, loss=0.226, v_num=9, val_loss=0.548, val_top1_acc=0.804, val_d_prime=3.180, val_aucroc=0.963, val_mAP=0.859]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 98: 100% 7/7 [00:00<00:00, 73.55it/s, loss=0.224, v_num=9, val_loss=0.556, val_top1_acc=0.804, val_d_prime=3.190, val_aucroc=0.963, val_mAP=0.861] \n",
      "Epoch 101:   0% 0/7 [00:00<?, ?it/s, loss=0.22, v_num=9, val_loss=0.556, val_top1_acc=0.804, val_d_prime=3.190, val_aucroc=0.963, val_mAP=0.861]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 101: 100% 7/7 [00:00<00:00, 63.74it/s, loss=0.219, v_num=9, val_loss=0.548, val_top1_acc=0.808, val_d_prime=3.200, val_aucroc=0.963, val_mAP=0.862]\n",
      "Epoch 104:   0% 0/7 [00:00<?, ?it/s, loss=0.215, v_num=9, val_loss=0.548, val_top1_acc=0.808, val_d_prime=3.200, val_aucroc=0.963, val_mAP=0.862]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 104: 100% 7/7 [00:00<00:00, 76.69it/s, loss=0.214, v_num=9, val_loss=0.549, val_top1_acc=0.806, val_d_prime=3.210, val_aucroc=0.964, val_mAP=0.864] \n",
      "Epoch 107:   0% 0/7 [00:00<?, ?it/s, loss=0.209, v_num=9, val_loss=0.549, val_top1_acc=0.806, val_d_prime=3.210, val_aucroc=0.964, val_mAP=0.864]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 107: 100% 7/7 [00:00<00:00, 57.61it/s, loss=0.207, v_num=9, val_loss=0.544, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.965, val_mAP=0.866]\n",
      "Epoch 110:   0% 0/7 [00:00<?, ?it/s, loss=0.204, v_num=9, val_loss=0.544, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.965, val_mAP=0.866]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 110: 100% 7/7 [00:00<00:00, 23.73it/s, loss=0.203, v_num=9, val_loss=0.540, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.965, val_mAP=0.866]\n",
      "Epoch 113:   0% 0/7 [00:00<?, ?it/s, loss=0.198, v_num=9, val_loss=0.540, val_top1_acc=0.806, val_d_prime=3.230, val_aucroc=0.965, val_mAP=0.866]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 113: 100% 7/7 [00:00<00:00, 78.19it/s, loss=0.197, v_num=9, val_loss=0.541, val_top1_acc=0.812, val_d_prime=3.250, val_aucroc=0.965, val_mAP=0.869] \n",
      "Epoch 116:   0% 0/7 [00:00<?, ?it/s, loss=0.194, v_num=9, val_loss=0.541, val_top1_acc=0.812, val_d_prime=3.250, val_aucroc=0.965, val_mAP=0.869]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 116: 100% 7/7 [00:00<00:00, 75.24it/s, loss=0.193, v_num=9, val_loss=0.538, val_top1_acc=0.810, val_d_prime=3.250, val_aucroc=0.965, val_mAP=0.868] \n",
      "Epoch 119:   0% 0/7 [00:00<?, ?it/s, loss=0.19, v_num=9, val_loss=0.538, val_top1_acc=0.810, val_d_prime=3.250, val_aucroc=0.965, val_mAP=0.868]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 119: 100% 7/7 [00:00<00:00, 64.94it/s, loss=0.189, v_num=9, val_loss=0.533, val_top1_acc=0.811, val_d_prime=3.260, val_aucroc=0.965, val_mAP=0.869]\n",
      "Epoch 122:   0% 0/7 [00:00<?, ?it/s, loss=0.187, v_num=9, val_loss=0.533, val_top1_acc=0.811, val_d_prime=3.260, val_aucroc=0.965, val_mAP=0.869]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 122: 100% 7/7 [00:00<00:00, 60.10it/s, loss=0.185, v_num=9, val_loss=0.536, val_top1_acc=0.815, val_d_prime=3.250, val_aucroc=0.966, val_mAP=0.870]\n",
      "Epoch 125:   0% 0/7 [00:00<?, ?it/s, loss=0.181, v_num=9, val_loss=0.536, val_top1_acc=0.815, val_d_prime=3.250, val_aucroc=0.966, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 125: 100% 7/7 [00:00<00:00, 70.31it/s, loss=0.179, v_num=9, val_loss=0.536, val_top1_acc=0.811, val_d_prime=3.270, val_aucroc=0.966, val_mAP=0.872] \n",
      "Epoch 128:   0% 0/7 [00:00<?, ?it/s, loss=0.177, v_num=9, val_loss=0.536, val_top1_acc=0.811, val_d_prime=3.270, val_aucroc=0.966, val_mAP=0.872]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 128: 100% 7/7 [00:00<00:00, 79.86it/s, loss=0.176, v_num=9, val_loss=0.532, val_top1_acc=0.817, val_d_prime=3.260, val_aucroc=0.966, val_mAP=0.871] \n",
      "Epoch 131:   0% 0/7 [00:00<?, ?it/s, loss=0.172, v_num=9, val_loss=0.532, val_top1_acc=0.817, val_d_prime=3.260, val_aucroc=0.966, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 131: 100% 7/7 [00:00<00:00, 78.91it/s, loss=0.171, v_num=9, val_loss=0.529, val_top1_acc=0.819, val_d_prime=3.270, val_aucroc=0.966, val_mAP=0.873] \n",
      "Epoch 134:   0% 0/7 [00:00<?, ?it/s, loss=0.169, v_num=9, val_loss=0.529, val_top1_acc=0.819, val_d_prime=3.270, val_aucroc=0.966, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 134: 100% 7/7 [00:00<00:00, 67.88it/s, loss=0.167, v_num=9, val_loss=0.526, val_top1_acc=0.822, val_d_prime=3.280, val_aucroc=0.967, val_mAP=0.874]\n",
      "Epoch 137:   0% 0/7 [00:00<?, ?it/s, loss=0.164, v_num=9, val_loss=0.526, val_top1_acc=0.822, val_d_prime=3.280, val_aucroc=0.967, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 137: 100% 7/7 [00:00<00:00, 53.34it/s, loss=0.163, v_num=9, val_loss=0.527, val_top1_acc=0.819, val_d_prime=3.290, val_aucroc=0.967, val_mAP=0.875]\n",
      "Epoch 140:   0% 0/7 [00:00<?, ?it/s, loss=0.161, v_num=9, val_loss=0.527, val_top1_acc=0.819, val_d_prime=3.290, val_aucroc=0.967, val_mAP=0.875]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 140: 100% 7/7 [00:00<00:00, 74.62it/s, loss=0.161, v_num=9, val_loss=0.540, val_top1_acc=0.816, val_d_prime=3.300, val_aucroc=0.967, val_mAP=0.876] \n",
      "Epoch 143:   0% 0/7 [00:00<?, ?it/s, loss=0.158, v_num=9, val_loss=0.540, val_top1_acc=0.816, val_d_prime=3.300, val_aucroc=0.967, val_mAP=0.876]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 143: 100% 7/7 [00:00<00:00, 62.67it/s, loss=0.157, v_num=9, val_loss=0.538, val_top1_acc=0.822, val_d_prime=3.290, val_aucroc=0.967, val_mAP=0.877]\n",
      "Epoch 146:   0% 0/7 [00:00<?, ?it/s, loss=0.155, v_num=9, val_loss=0.538, val_top1_acc=0.822, val_d_prime=3.290, val_aucroc=0.967, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 146: 100% 7/7 [00:00<00:00, 63.53it/s, loss=0.154, v_num=9, val_loss=0.532, val_top1_acc=0.819, val_d_prime=3.310, val_aucroc=0.968, val_mAP=0.877] \n",
      "Epoch 149:   0% 0/7 [00:00<?, ?it/s, loss=0.152, v_num=9, val_loss=0.532, val_top1_acc=0.819, val_d_prime=3.310, val_aucroc=0.968, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 149: 100% 7/7 [00:00<00:00, 74.90it/s, loss=0.151, v_num=9, val_loss=0.518, val_top1_acc=0.819, val_d_prime=3.320, val_aucroc=0.968, val_mAP=0.880] \n",
      "Epoch 152:   0% 0/7 [00:00<?, ?it/s, loss=0.149, v_num=9, val_loss=0.518, val_top1_acc=0.819, val_d_prime=3.320, val_aucroc=0.968, val_mAP=0.880]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 152: 100% 7/7 [00:00<00:00, 75.81it/s, loss=0.147, v_num=9, val_loss=0.528, val_top1_acc=0.821, val_d_prime=3.310, val_aucroc=0.968, val_mAP=0.880] \n",
      "Epoch 155:   0% 0/7 [00:00<?, ?it/s, loss=0.145, v_num=9, val_loss=0.528, val_top1_acc=0.821, val_d_prime=3.310, val_aucroc=0.968, val_mAP=0.880]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 155: 100% 7/7 [00:00<00:00, 57.81it/s, loss=0.144, v_num=9, val_loss=0.531, val_top1_acc=0.824, val_d_prime=3.330, val_aucroc=0.968, val_mAP=0.880]\n",
      "Epoch 158:   0% 0/7 [00:00<?, ?it/s, loss=0.143, v_num=9, val_loss=0.531, val_top1_acc=0.824, val_d_prime=3.330, val_aucroc=0.968, val_mAP=0.880]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 158: 100% 7/7 [00:00<00:00, 68.05it/s, loss=0.142, v_num=9, val_loss=0.522, val_top1_acc=0.822, val_d_prime=3.320, val_aucroc=0.968, val_mAP=0.881] \n",
      "Epoch 161:   0% 0/7 [00:00<?, ?it/s, loss=0.139, v_num=9, val_loss=0.522, val_top1_acc=0.822, val_d_prime=3.320, val_aucroc=0.968, val_mAP=0.881]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 161: 100% 7/7 [00:00<00:00, 76.72it/s, loss=0.138, v_num=9, val_loss=0.523, val_top1_acc=0.823, val_d_prime=3.310, val_aucroc=0.968, val_mAP=0.881] \n",
      "Epoch 164:   0% 0/7 [00:00<?, ?it/s, loss=0.137, v_num=9, val_loss=0.523, val_top1_acc=0.823, val_d_prime=3.310, val_aucroc=0.968, val_mAP=0.881]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 164: 100% 7/7 [00:00<00:00, 60.80it/s, loss=0.136, v_num=9, val_loss=0.518, val_top1_acc=0.827, val_d_prime=3.320, val_aucroc=0.968, val_mAP=0.882]\n",
      "Epoch 167:   0% 0/7 [00:00<?, ?it/s, loss=0.134, v_num=9, val_loss=0.518, val_top1_acc=0.827, val_d_prime=3.320, val_aucroc=0.968, val_mAP=0.882]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 167: 100% 7/7 [00:00<00:00, 80.52it/s, loss=0.135, v_num=9, val_loss=0.520, val_top1_acc=0.829, val_d_prime=3.320, val_aucroc=0.969, val_mAP=0.882] \n",
      "Epoch 170:   0% 0/7 [00:00<?, ?it/s, loss=0.132, v_num=9, val_loss=0.520, val_top1_acc=0.829, val_d_prime=3.320, val_aucroc=0.969, val_mAP=0.882]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 170: 100% 7/7 [00:00<00:00, 79.96it/s, loss=0.131, v_num=9, val_loss=0.518, val_top1_acc=0.827, val_d_prime=3.330, val_aucroc=0.969, val_mAP=0.884] \n",
      "Epoch 173:   0% 0/7 [00:00<?, ?it/s, loss=0.129, v_num=9, val_loss=0.518, val_top1_acc=0.827, val_d_prime=3.330, val_aucroc=0.969, val_mAP=0.884]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 173: 100% 7/7 [00:00<00:00, 64.04it/s, loss=0.128, v_num=9, val_loss=0.519, val_top1_acc=0.824, val_d_prime=3.330, val_aucroc=0.969, val_mAP=0.884]\n",
      "Epoch 176:   0% 0/7 [00:00<?, ?it/s, loss=0.127, v_num=9, val_loss=0.519, val_top1_acc=0.824, val_d_prime=3.330, val_aucroc=0.969, val_mAP=0.884]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 176: 100% 7/7 [00:00<00:00, 56.80it/s, loss=0.126, v_num=9, val_loss=0.527, val_top1_acc=0.827, val_d_prime=3.340, val_aucroc=0.969, val_mAP=0.883]\n",
      "Epoch 179:   0% 0/7 [00:00<?, ?it/s, loss=0.123, v_num=9, val_loss=0.527, val_top1_acc=0.827, val_d_prime=3.340, val_aucroc=0.969, val_mAP=0.883]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 179: 100% 7/7 [00:00<00:00, 74.76it/s, loss=0.123, v_num=9, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.350, val_aucroc=0.969, val_mAP=0.885] \n",
      "Epoch 182:   0% 0/7 [00:00<?, ?it/s, loss=0.123, v_num=9, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.350, val_aucroc=0.969, val_mAP=0.885]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 182: 100% 7/7 [00:00<00:00, 76.61it/s, loss=0.121, v_num=9, val_loss=0.524, val_top1_acc=0.823, val_d_prime=3.340, val_aucroc=0.970, val_mAP=0.885] \n",
      "Epoch 185:   0% 0/7 [00:00<?, ?it/s, loss=0.119, v_num=9, val_loss=0.524, val_top1_acc=0.823, val_d_prime=3.340, val_aucroc=0.970, val_mAP=0.885]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 185: 100% 7/7 [00:00<00:00, 56.29it/s, loss=0.119, v_num=9, val_loss=0.527, val_top1_acc=0.827, val_d_prime=3.340, val_aucroc=0.969, val_mAP=0.885]\n",
      "Epoch 188:   0% 0/7 [00:00<?, ?it/s, loss=0.118, v_num=9, val_loss=0.527, val_top1_acc=0.827, val_d_prime=3.340, val_aucroc=0.969, val_mAP=0.885]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 188: 100% 7/7 [00:00<00:00, 68.95it/s, loss=0.116, v_num=9, val_loss=0.510, val_top1_acc=0.827, val_d_prime=3.350, val_aucroc=0.970, val_mAP=0.887] \n",
      "Epoch 191:   0% 0/7 [00:00<?, ?it/s, loss=0.115, v_num=9, val_loss=0.510, val_top1_acc=0.827, val_d_prime=3.350, val_aucroc=0.970, val_mAP=0.887]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 191: 100% 7/7 [00:00<00:00, 61.97it/s, loss=0.114, v_num=9, val_loss=0.522, val_top1_acc=0.826, val_d_prime=3.350, val_aucroc=0.970, val_mAP=0.886]\n",
      "Epoch 194:   0% 0/7 [00:00<?, ?it/s, loss=0.113, v_num=9, val_loss=0.522, val_top1_acc=0.826, val_d_prime=3.350, val_aucroc=0.970, val_mAP=0.886]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 194: 100% 7/7 [00:00<00:00, 69.18it/s, loss=0.113, v_num=9, val_loss=0.521, val_top1_acc=0.827, val_d_prime=3.330, val_aucroc=0.970, val_mAP=0.886] \n",
      "Epoch 197:   0% 0/7 [00:00<?, ?it/s, loss=0.111, v_num=9, val_loss=0.521, val_top1_acc=0.827, val_d_prime=3.330, val_aucroc=0.970, val_mAP=0.886]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 197: 100% 7/7 [00:00<00:00, 80.86it/s, loss=0.111, v_num=9, val_loss=0.513, val_top1_acc=0.829, val_d_prime=3.360, val_aucroc=0.970, val_mAP=0.887] \n",
      "Epoch 200:   0% 0/7 [00:00<?, ?it/s, loss=0.109, v_num=9, val_loss=0.513, val_top1_acc=0.829, val_d_prime=3.360, val_aucroc=0.970, val_mAP=0.887]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 200: 100% 7/7 [00:00<00:00, 66.48it/s, loss=0.108, v_num=9, val_loss=0.518, val_top1_acc=0.829, val_d_prime=3.340, val_aucroc=0.970, val_mAP=0.888]\n",
      "Epoch 203:   0% 0/7 [00:00<?, ?it/s, loss=0.108, v_num=9, val_loss=0.518, val_top1_acc=0.829, val_d_prime=3.340, val_aucroc=0.970, val_mAP=0.888]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 203: 100% 7/7 [00:00<00:00, 69.07it/s, loss=0.107, v_num=9, val_loss=0.506, val_top1_acc=0.831, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.888]\n",
      "Epoch 206:   0% 0/7 [00:00<?, ?it/s, loss=0.106, v_num=9, val_loss=0.506, val_top1_acc=0.831, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.888]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 206: 100% 7/7 [00:00<00:00, 59.21it/s, loss=0.105, v_num=9, val_loss=0.520, val_top1_acc=0.829, val_d_prime=3.360, val_aucroc=0.970, val_mAP=0.888]\n",
      "Epoch 209:   0% 0/7 [00:00<?, ?it/s, loss=0.103, v_num=9, val_loss=0.520, val_top1_acc=0.829, val_d_prime=3.360, val_aucroc=0.970, val_mAP=0.888]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 209: 100% 7/7 [00:00<00:00, 70.52it/s, loss=0.103, v_num=9, val_loss=0.511, val_top1_acc=0.827, val_d_prime=3.360, val_aucroc=0.971, val_mAP=0.889] \n",
      "Epoch 212:   0% 0/7 [00:00<?, ?it/s, loss=0.102, v_num=9, val_loss=0.511, val_top1_acc=0.827, val_d_prime=3.360, val_aucroc=0.971, val_mAP=0.889]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 212: 100% 7/7 [00:00<00:00, 66.60it/s, loss=0.101, v_num=9, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.890] \n",
      "Epoch 215:   0% 0/7 [00:00<?, ?it/s, loss=0.0995, v_num=9, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.890]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 215: 100% 7/7 [00:00<00:00, 78.51it/s, loss=0.0988, v_num=9, val_loss=0.521, val_top1_acc=0.828, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.890] \n",
      "Epoch 218:   0% 0/7 [00:00<?, ?it/s, loss=0.0972, v_num=9, val_loss=0.521, val_top1_acc=0.828, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.890]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 218: 100% 7/7 [00:00<00:00, 69.62it/s, loss=0.0968, v_num=9, val_loss=0.514, val_top1_acc=0.832, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.890] \n",
      "Epoch 221:   0% 0/7 [00:00<?, ?it/s, loss=0.0959, v_num=9, val_loss=0.514, val_top1_acc=0.832, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.890]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 221: 100% 7/7 [00:00<00:00, 60.09it/s, loss=0.0952, v_num=9, val_loss=0.512, val_top1_acc=0.834, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.891]\n",
      "Epoch 224:   0% 0/7 [00:00<?, ?it/s, loss=0.0931, v_num=9, val_loss=0.512, val_top1_acc=0.834, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.891]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 224: 100% 7/7 [00:00<00:00, 67.06it/s, loss=0.0921, v_num=9, val_loss=0.506, val_top1_acc=0.832, val_d_prime=3.370, val_aucroc=0.972, val_mAP=0.893] \n",
      "Epoch 227:   0% 0/7 [00:00<?, ?it/s, loss=0.0915, v_num=9, val_loss=0.506, val_top1_acc=0.832, val_d_prime=3.370, val_aucroc=0.972, val_mAP=0.893]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 227: 100% 7/7 [00:00<00:00, 23.12it/s, loss=0.0916, v_num=9, val_loss=0.510, val_top1_acc=0.828, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893]\n",
      "Epoch 230:   0% 0/7 [00:00<?, ?it/s, loss=0.0922, v_num=9, val_loss=0.510, val_top1_acc=0.828, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 230: 100% 7/7 [00:00<00:00, 78.18it/s, loss=0.0916, v_num=9, val_loss=0.511, val_top1_acc=0.830, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893] \n",
      "Epoch 233:   0% 0/7 [00:00<?, ?it/s, loss=0.0908, v_num=9, val_loss=0.511, val_top1_acc=0.830, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 233: 100% 7/7 [00:00<00:00, 77.95it/s, loss=0.0898, v_num=9, val_loss=0.513, val_top1_acc=0.829, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893] \n",
      "Epoch 236:   0% 0/7 [00:00<?, ?it/s, loss=0.0887, v_num=9, val_loss=0.513, val_top1_acc=0.829, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 236: 100% 7/7 [00:00<00:00, 74.05it/s, loss=0.0873, v_num=9, val_loss=0.524, val_top1_acc=0.832, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.891] \n",
      "Epoch 239:   0% 0/7 [00:00<?, ?it/s, loss=0.0869, v_num=9, val_loss=0.524, val_top1_acc=0.832, val_d_prime=3.370, val_aucroc=0.971, val_mAP=0.891]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 239: 100% 7/7 [00:00<00:00, 57.43it/s, loss=0.0863, v_num=9, val_loss=0.508, val_top1_acc=0.831, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.895]\n",
      "Epoch 242:   0% 0/7 [00:00<?, ?it/s, loss=0.0856, v_num=9, val_loss=0.508, val_top1_acc=0.831, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.895]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 242: 100% 7/7 [00:00<00:00, 69.13it/s, loss=0.085, v_num=9, val_loss=0.514, val_top1_acc=0.833, val_d_prime=3.410, val_aucroc=0.972, val_mAP=0.894]  \n",
      "Epoch 245:   0% 0/7 [00:00<?, ?it/s, loss=0.0837, v_num=9, val_loss=0.514, val_top1_acc=0.833, val_d_prime=3.410, val_aucroc=0.972, val_mAP=0.894]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 245: 100% 7/7 [00:00<00:00, 80.53it/s, loss=0.0839, v_num=9, val_loss=0.520, val_top1_acc=0.831, val_d_prime=3.380, val_aucroc=0.971, val_mAP=0.893] \n",
      "Epoch 248:   0% 0/7 [00:00<?, ?it/s, loss=0.0838, v_num=9, val_loss=0.520, val_top1_acc=0.831, val_d_prime=3.380, val_aucroc=0.971, val_mAP=0.893]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 248: 100% 7/7 [00:00<00:00, 64.09it/s, loss=0.0837, v_num=9, val_loss=0.516, val_top1_acc=0.833, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893]\n",
      "Epoch 251:   0% 0/7 [00:00<?, ?it/s, loss=0.0824, v_num=9, val_loss=0.516, val_top1_acc=0.833, val_d_prime=3.390, val_aucroc=0.972, val_mAP=0.893]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 251: 100% 7/7 [00:00<00:00, 61.03it/s, loss=0.0819, v_num=9, val_loss=0.510, val_top1_acc=0.834, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.894] \n",
      "Epoch 254:   0% 0/7 [00:00<?, ?it/s, loss=0.0811, v_num=9, val_loss=0.510, val_top1_acc=0.834, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.894]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 254: 100% 7/7 [00:00<00:00, 64.90it/s, loss=0.0812, v_num=9, val_loss=0.518, val_top1_acc=0.836, val_d_prime=3.380, val_aucroc=0.972, val_mAP=0.895]\n",
      "Epoch 257:   0% 0/7 [00:00<?, ?it/s, loss=0.0808, v_num=9, val_loss=0.518, val_top1_acc=0.836, val_d_prime=3.380, val_aucroc=0.972, val_mAP=0.895]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 257: 100% 7/7 [00:00<00:00, 58.30it/s, loss=0.0796, v_num=9, val_loss=0.512, val_top1_acc=0.832, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.896]\n",
      "Epoch 260:   0% 0/7 [00:00<?, ?it/s, loss=0.077, v_num=9, val_loss=0.512, val_top1_acc=0.832, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.896]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 260: 100% 7/7 [00:00<00:00, 65.68it/s, loss=0.0764, v_num=9, val_loss=0.533, val_top1_acc=0.836, val_d_prime=3.380, val_aucroc=0.972, val_mAP=0.894]\n",
      "Epoch 263:   0% 0/7 [00:00<?, ?it/s, loss=0.077, v_num=9, val_loss=0.533, val_top1_acc=0.836, val_d_prime=3.380, val_aucroc=0.972, val_mAP=0.894]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 263: 100% 7/7 [00:00<00:00, 63.20it/s, loss=0.0768, v_num=9, val_loss=0.525, val_top1_acc=0.831, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.897]\n",
      "Epoch 266:   0% 0/7 [00:00<?, ?it/s, loss=0.0765, v_num=9, val_loss=0.525, val_top1_acc=0.831, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.897]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 266: 100% 7/7 [00:00<00:00, 78.92it/s, loss=0.0757, v_num=9, val_loss=0.519, val_top1_acc=0.835, val_d_prime=3.400, val_aucroc=0.973, val_mAP=0.897] \n",
      "Epoch 269:   0% 0/7 [00:00<?, ?it/s, loss=0.075, v_num=9, val_loss=0.519, val_top1_acc=0.835, val_d_prime=3.400, val_aucroc=0.973, val_mAP=0.897]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 269: 100% 7/7 [00:00<00:00, 67.95it/s, loss=0.074, v_num=9, val_loss=0.510, val_top1_acc=0.834, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.898]\n",
      "Epoch 272:   0% 0/7 [00:00<?, ?it/s, loss=0.0729, v_num=9, val_loss=0.510, val_top1_acc=0.834, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.898]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 272: 100% 7/7 [00:00<00:00, 58.16it/s, loss=0.0718, v_num=9, val_loss=0.516, val_top1_acc=0.834, val_d_prime=3.400, val_aucroc=0.973, val_mAP=0.897]\n",
      "Epoch 275:   0% 0/7 [00:00<?, ?it/s, loss=0.0708, v_num=9, val_loss=0.516, val_top1_acc=0.834, val_d_prime=3.400, val_aucroc=0.973, val_mAP=0.897]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 275: 100% 7/7 [00:00<00:00, 56.93it/s, loss=0.0713, v_num=9, val_loss=0.518, val_top1_acc=0.837, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.896]\n",
      "Epoch 278:   0% 0/7 [00:00<?, ?it/s, loss=0.071, v_num=9, val_loss=0.518, val_top1_acc=0.837, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.896]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 278: 100% 7/7 [00:00<00:00, 65.71it/s, loss=0.0706, v_num=9, val_loss=0.514, val_top1_acc=0.839, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.898]\n",
      "Epoch 281:   0% 0/7 [00:00<?, ?it/s, loss=0.0686, v_num=9, val_loss=0.514, val_top1_acc=0.839, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.898]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 281: 100% 7/7 [00:00<00:00, 62.67it/s, loss=0.0677, v_num=9, val_loss=0.520, val_top1_acc=0.835, val_d_prime=3.400, val_aucroc=0.973, val_mAP=0.897]\n",
      "Epoch 284:   0% 0/7 [00:00<?, ?it/s, loss=0.0672, v_num=9, val_loss=0.520, val_top1_acc=0.835, val_d_prime=3.400, val_aucroc=0.973, val_mAP=0.897]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 284: 100% 7/7 [00:00<00:00, 65.69it/s, loss=0.0671, v_num=9, val_loss=0.524, val_top1_acc=0.833, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.900] \n",
      "Epoch 287:   0% 0/7 [00:00<?, ?it/s, loss=0.0667, v_num=9, val_loss=0.524, val_top1_acc=0.833, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 287: 100% 7/7 [00:00<00:00, 80.97it/s, loss=0.0665, v_num=9, val_loss=0.528, val_top1_acc=0.829, val_d_prime=3.410, val_aucroc=0.974, val_mAP=0.900] \n",
      "Epoch 290:   0% 0/7 [00:00<?, ?it/s, loss=0.0661, v_num=9, val_loss=0.528, val_top1_acc=0.829, val_d_prime=3.410, val_aucroc=0.974, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 290: 100% 7/7 [00:00<00:00, 78.21it/s, loss=0.0652, v_num=9, val_loss=0.527, val_top1_acc=0.830, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.900] \n",
      "Epoch 293:   0% 0/7 [00:00<?, ?it/s, loss=0.0646, v_num=9, val_loss=0.527, val_top1_acc=0.830, val_d_prime=3.420, val_aucroc=0.973, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 293: 100% 7/7 [00:00<00:00, 72.42it/s, loss=0.0639, v_num=9, val_loss=0.514, val_top1_acc=0.837, val_d_prime=3.430, val_aucroc=0.973, val_mAP=0.899] \n",
      "Epoch 296:   0% 0/7 [00:00<?, ?it/s, loss=0.0632, v_num=9, val_loss=0.514, val_top1_acc=0.837, val_d_prime=3.430, val_aucroc=0.973, val_mAP=0.899]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 296: 100% 7/7 [00:00<00:00, 80.82it/s, loss=0.0627, v_num=9, val_loss=0.535, val_top1_acc=0.837, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.898] \n",
      "Epoch 299:   0% 0/7 [00:00<?, ?it/s, loss=0.0636, v_num=9, val_loss=0.535, val_top1_acc=0.837, val_d_prime=3.400, val_aucroc=0.972, val_mAP=0.898]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 299: 100% 7/7 [00:00<00:00, 57.57it/s, loss=0.0634, v_num=9, val_loss=0.520, val_top1_acc=0.834, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.897]\n",
      "Epoch 302:   0% 0/7 [00:00<?, ?it/s, loss=0.063, v_num=9, val_loss=0.520, val_top1_acc=0.834, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.897]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 302: 100% 7/7 [00:00<00:00, 60.43it/s, loss=0.0624, v_num=9, val_loss=0.509, val_top1_acc=0.839, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.900]\n",
      "Epoch 305:   0% 0/7 [00:00<?, ?it/s, loss=0.062, v_num=9, val_loss=0.509, val_top1_acc=0.839, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 305: 100% 7/7 [00:00<00:00, 81.05it/s, loss=0.0621, v_num=9, val_loss=0.511, val_top1_acc=0.839, val_d_prime=3.420, val_aucroc=0.974, val_mAP=0.901]\n",
      "Epoch 308:   0% 0/7 [00:00<?, ?it/s, loss=0.0622, v_num=9, val_loss=0.511, val_top1_acc=0.839, val_d_prime=3.420, val_aucroc=0.974, val_mAP=0.901]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 308: 100% 7/7 [00:00<00:00, 77.97it/s, loss=0.0619, v_num=9, val_loss=0.512, val_top1_acc=0.837, val_d_prime=3.450, val_aucroc=0.974, val_mAP=0.901] \n",
      "Epoch 311:   0% 0/7 [00:00<?, ?it/s, loss=0.06, v_num=9, val_loss=0.512, val_top1_acc=0.837, val_d_prime=3.450, val_aucroc=0.974, val_mAP=0.901]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 311: 100% 7/7 [00:00<00:00, 78.39it/s, loss=0.0603, v_num=9, val_loss=0.539, val_top1_acc=0.837, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.900]\n",
      "Epoch 314:   0% 0/7 [00:00<?, ?it/s, loss=0.0602, v_num=9, val_loss=0.539, val_top1_acc=0.837, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 314: 100% 7/7 [00:00<00:00, 62.81it/s, loss=0.0603, v_num=9, val_loss=0.514, val_top1_acc=0.840, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.901]\n",
      "Epoch 317:   0% 0/7 [00:00<?, ?it/s, loss=0.0586, v_num=9, val_loss=0.514, val_top1_acc=0.840, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.901]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 317: 100% 7/7 [00:00<00:00, 76.62it/s, loss=0.059, v_num=9, val_loss=0.524, val_top1_acc=0.841, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.901]  \n",
      "Epoch 320:   0% 0/7 [00:00<?, ?it/s, loss=0.0583, v_num=9, val_loss=0.524, val_top1_acc=0.841, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.901]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 320: 100% 7/7 [00:00<00:00, 61.80it/s, loss=0.0586, v_num=9, val_loss=0.525, val_top1_acc=0.837, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.900]\n",
      "Epoch 323:   0% 0/7 [00:00<?, ?it/s, loss=0.0566, v_num=9, val_loss=0.525, val_top1_acc=0.837, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 323: 100% 7/7 [00:00<00:00, 72.34it/s, loss=0.0572, v_num=9, val_loss=0.534, val_top1_acc=0.841, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.901] \n",
      "Epoch 326:   0% 0/7 [00:00<?, ?it/s, loss=0.0568, v_num=9, val_loss=0.534, val_top1_acc=0.841, val_d_prime=3.410, val_aucroc=0.973, val_mAP=0.901]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 326: 100% 7/7 [00:00<00:00, 73.86it/s, loss=0.0572, v_num=9, val_loss=0.535, val_top1_acc=0.834, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.900] \n",
      "Epoch 329:   0% 0/7 [00:00<?, ?it/s, loss=0.0557, v_num=9, val_loss=0.535, val_top1_acc=0.834, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.900]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 329: 100% 7/7 [00:00<00:00, 59.35it/s, loss=0.0566, v_num=9, val_loss=0.526, val_top1_acc=0.841, val_d_prime=3.420, val_aucroc=0.974, val_mAP=0.902]\n",
      "Epoch 332:   0% 0/7 [00:00<?, ?it/s, loss=0.0546, v_num=9, val_loss=0.526, val_top1_acc=0.841, val_d_prime=3.420, val_aucroc=0.974, val_mAP=0.902]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 332: 100% 7/7 [00:00<00:00, 65.19it/s, loss=0.0549, v_num=9, val_loss=0.522, val_top1_acc=0.837, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.901] \n",
      "Epoch 335:   0% 0/7 [00:00<?, ?it/s, loss=0.0532, v_num=9, val_loss=0.522, val_top1_acc=0.837, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.901]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 335: 100% 7/7 [00:00<00:00, 79.44it/s, loss=0.0538, v_num=9, val_loss=0.529, val_top1_acc=0.839, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903] \n",
      "Epoch 338:   0% 0/7 [00:00<?, ?it/s, loss=0.0531, v_num=9, val_loss=0.529, val_top1_acc=0.839, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 338: 100% 7/7 [00:00<00:00, 66.26it/s, loss=0.0526, v_num=9, val_loss=0.515, val_top1_acc=0.842, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.904]\n",
      "Epoch 341:   0% 0/7 [00:00<?, ?it/s, loss=0.0518, v_num=9, val_loss=0.515, val_top1_acc=0.842, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.904]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 341: 100% 7/7 [00:00<00:00, 55.25it/s, loss=0.0509, v_num=9, val_loss=0.522, val_top1_acc=0.836, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.902]\n",
      "Epoch 344:   0% 0/7 [00:00<?, ?it/s, loss=0.05, v_num=9, val_loss=0.522, val_top1_acc=0.836, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.902]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 344: 100% 7/7 [00:00<00:00, 69.05it/s, loss=0.0494, v_num=9, val_loss=0.511, val_top1_acc=0.846, val_d_prime=3.420, val_aucroc=0.974, val_mAP=0.903]\n",
      "Epoch 347:   0% 0/7 [00:00<?, ?it/s, loss=0.0491, v_num=9, val_loss=0.511, val_top1_acc=0.846, val_d_prime=3.420, val_aucroc=0.974, val_mAP=0.903]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 347: 100% 7/7 [00:00<00:00, 79.18it/s, loss=0.0489, v_num=9, val_loss=0.529, val_top1_acc=0.835, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.902] \n",
      "Epoch 350:   0% 0/7 [00:00<?, ?it/s, loss=0.0487, v_num=9, val_loss=0.529, val_top1_acc=0.835, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.902]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 350: 100% 7/7 [00:00<00:00, 79.75it/s, loss=0.0482, v_num=9, val_loss=0.523, val_top1_acc=0.843, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903] \n",
      "Epoch 353:   0% 0/7 [00:00<?, ?it/s, loss=0.0471, v_num=9, val_loss=0.523, val_top1_acc=0.843, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 353: 100% 7/7 [00:00<00:00, 77.24it/s, loss=0.047, v_num=9, val_loss=0.514, val_top1_acc=0.842, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903]  \n",
      "Epoch 356:   0% 0/7 [00:00<?, ?it/s, loss=0.0468, v_num=9, val_loss=0.514, val_top1_acc=0.842, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 356: 100% 7/7 [00:00<00:00, 80.74it/s, loss=0.0467, v_num=9, val_loss=0.521, val_top1_acc=0.840, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.904] \n",
      "Epoch 359:   0% 0/7 [00:00<?, ?it/s, loss=0.0464, v_num=9, val_loss=0.521, val_top1_acc=0.840, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.904]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 359: 100% 7/7 [00:00<00:00, 67.02it/s, loss=0.0462, v_num=9, val_loss=0.519, val_top1_acc=0.842, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903] \n",
      "Epoch 362:   0% 0/7 [00:00<?, ?it/s, loss=0.0454, v_num=9, val_loss=0.519, val_top1_acc=0.842, val_d_prime=3.440, val_aucroc=0.974, val_mAP=0.903]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 362: 100% 7/7 [00:00<00:00, 79.39it/s, loss=0.0452, v_num=9, val_loss=0.520, val_top1_acc=0.839, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.902] \n",
      "Epoch 365:   0% 0/7 [00:00<?, ?it/s, loss=0.0448, v_num=9, val_loss=0.520, val_top1_acc=0.839, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.902]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 365: 100% 7/7 [00:00<00:00, 59.11it/s, loss=0.0447, v_num=9, val_loss=0.530, val_top1_acc=0.844, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.903]\n",
      "Epoch 368:   0% 0/7 [00:00<?, ?it/s, loss=0.0444, v_num=9, val_loss=0.530, val_top1_acc=0.844, val_d_prime=3.430, val_aucroc=0.974, val_mAP=0.903]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 368: 100% 7/7 [00:00<00:00, 69.71it/s, loss=0.0438, v_num=9, val_loss=0.518, val_top1_acc=0.841, val_d_prime=3.440, val_aucroc=0.975, val_mAP=0.904] \n",
      "Epoch 371:   0% 0/7 [00:00<?, ?it/s, loss=0.0431, v_num=9, val_loss=0.518, val_top1_acc=0.841, val_d_prime=3.440, val_aucroc=0.975, val_mAP=0.904]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 371: 100% 7/7 [00:00<00:00, 66.56it/s, loss=0.043, v_num=9, val_loss=0.518, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]  \n",
      "Epoch 374:   0% 0/7 [00:00<?, ?it/s, loss=0.0425, v_num=9, val_loss=0.518, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 374: 100% 7/7 [00:00<00:00, 79.34it/s, loss=0.0423, v_num=9, val_loss=0.525, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905] \n",
      "Epoch 377:   0% 0/7 [00:00<?, ?it/s, loss=0.0423, v_num=9, val_loss=0.525, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 377: 100% 7/7 [00:00<00:00, 69.98it/s, loss=0.0423, v_num=9, val_loss=0.520, val_top1_acc=0.840, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905] \n",
      "Epoch 380:   0% 0/7 [00:00<?, ?it/s, loss=0.0423, v_num=9, val_loss=0.520, val_top1_acc=0.840, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 380: 100% 7/7 [00:00<00:00, 79.01it/s, loss=0.042, v_num=9, val_loss=0.549, val_top1_acc=0.845, val_d_prime=3.410, val_aucroc=0.974, val_mAP=0.902]  \n",
      "Epoch 383:   0% 0/7 [00:00<?, ?it/s, loss=0.0424, v_num=9, val_loss=0.549, val_top1_acc=0.845, val_d_prime=3.410, val_aucroc=0.974, val_mAP=0.902]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 383: 100% 7/7 [00:00<00:00, 56.82it/s, loss=0.0425, v_num=9, val_loss=0.526, val_top1_acc=0.838, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Epoch 386:   0% 0/7 [00:00<?, ?it/s, loss=0.0425, v_num=9, val_loss=0.526, val_top1_acc=0.838, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 386: 100% 7/7 [00:00<00:00, 58.35it/s, loss=0.0419, v_num=9, val_loss=0.537, val_top1_acc=0.843, val_d_prime=3.440, val_aucroc=0.975, val_mAP=0.904]\n",
      "Epoch 389:   0% 0/7 [00:00<?, ?it/s, loss=0.041, v_num=9, val_loss=0.537, val_top1_acc=0.843, val_d_prime=3.440, val_aucroc=0.975, val_mAP=0.904]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 389: 100% 7/7 [00:00<00:00, 69.06it/s, loss=0.0401, v_num=9, val_loss=0.527, val_top1_acc=0.837, val_d_prime=3.440, val_aucroc=0.975, val_mAP=0.906]\n",
      "Epoch 392:   0% 0/7 [00:00<?, ?it/s, loss=0.0398, v_num=9, val_loss=0.527, val_top1_acc=0.837, val_d_prime=3.440, val_aucroc=0.975, val_mAP=0.906]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 392: 100% 7/7 [00:00<00:00, 74.71it/s, loss=0.0394, v_num=9, val_loss=0.539, val_top1_acc=0.844, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905] \n",
      "Epoch 395:   0% 0/7 [00:00<?, ?it/s, loss=0.039, v_num=9, val_loss=0.539, val_top1_acc=0.844, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 395: 100% 7/7 [00:00<00:00, 64.47it/s, loss=0.0389, v_num=9, val_loss=0.524, val_top1_acc=0.842, val_d_prime=3.450, val_aucroc=0.975, val_mAP=0.906]\n",
      "Epoch 398:   0% 0/7 [00:00<?, ?it/s, loss=0.0378, v_num=9, val_loss=0.524, val_top1_acc=0.842, val_d_prime=3.450, val_aucroc=0.975, val_mAP=0.906]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 398: 100% 7/7 [00:00<00:00, 67.29it/s, loss=0.0375, v_num=9, val_loss=0.531, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.906] \n",
      "Epoch 401:   0% 0/7 [00:00<?, ?it/s, loss=0.0376, v_num=9, val_loss=0.531, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.906]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 401: 100% 7/7 [00:00<00:00, 62.38it/s, loss=0.0375, v_num=9, val_loss=0.533, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905] \n",
      "Epoch 404:   0% 0/7 [00:00<?, ?it/s, loss=0.0369, v_num=9, val_loss=0.533, val_top1_acc=0.842, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.905]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 404: 100% 7/7 [00:00<00:00, 58.74it/s, loss=0.0367, v_num=9, val_loss=0.539, val_top1_acc=0.843, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.906]\n",
      "Epoch 404: 100% 7/7 [00:00<00:00, 54.51it/s, loss=0.0367, v_num=9, val_loss=0.539, val_top1_acc=0.843, val_d_prime=3.430, val_aucroc=0.975, val_mAP=0.906]\n",
      "FIT Profiler Report\n",
      "\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                              \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                               \t|  -              \t|  115491         \t|  33.416         \t|  100 %          \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                  \t|  0.080348       \t|  405            \t|  32.541         \t|  97.382         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                  \t|  0.0038725      \t|  2025           \t|  7.8418         \t|  23.467         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                \t|  0.003557       \t|  2025           \t|  7.2029         \t|  21.555         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                          \t|  0.030745       \t|  135            \t|  4.1506         \t|  12.421         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                        \t|  0.0015038      \t|  2025           \t|  3.0452         \t|  9.113          \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                 \t|  0.014488       \t|  135            \t|  1.9559         \t|  5.8533         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                             \t|  0.00087417     \t|  2025           \t|  1.7702         \t|  5.2975         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                  \t|  0.00031427     \t|  2025           \t|  0.6364         \t|  1.9045         \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                \t|  0.00018404     \t|  2025           \t|  0.37267        \t|  1.1153         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                      \t|  9.9256e-05     \t|  2295           \t|  0.22779        \t|  0.68169        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                           \t|  0.00010875     \t|  2025           \t|  0.22022        \t|  0.65903        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                      \t|  0.00066298     \t|  270            \t|  0.179          \t|  0.53569        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                        \t|  0.00036892     \t|  405            \t|  0.14941        \t|  0.44713        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                      \t|  0.00024895     \t|  405            \t|  0.10082        \t|  0.30172        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                         \t|  0.0005788      \t|  135            \t|  0.078138       \t|  0.23384        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                 \t|  0.00047781     \t|  135            \t|  0.064504       \t|  0.19303        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                   \t|  0.00017172     \t|  270            \t|  0.046363       \t|  0.13875        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                 \t|  0.00013968     \t|  270            \t|  0.037713       \t|  0.11286        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                       \t|  0.00025505     \t|  135            \t|  0.034432       \t|  0.10304        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                 \t|  7.2477e-06     \t|  2025           \t|  0.014677       \t|  0.043921       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                     \t|  8.4255e-05     \t|  135            \t|  0.011374       \t|  0.034039       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                               \t|  5.3551e-06     \t|  2025           \t|  0.010844       \t|  0.032452       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                \t|  2.6657e-05     \t|  405            \t|  0.010796       \t|  0.032308       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                    \t|  5.1824e-06     \t|  2025           \t|  0.010494       \t|  0.031406       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                      \t|  7.5793e-05     \t|  135            \t|  0.010232       \t|  0.030621       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                      \t|  4.6794e-06     \t|  2025           \t|  0.0094759      \t|  0.028358       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                \t|  4.3791e-06     \t|  2025           \t|  0.0088677      \t|  0.026537       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                          \t|  4.2109e-06     \t|  2025           \t|  0.0085271      \t|  0.025518       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                         \t|  4.193e-06      \t|  2025           \t|  0.0084907      \t|  0.025409       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                           \t|  4.1232e-06     \t|  2025           \t|  0.0083495      \t|  0.024987       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                  \t|  4.0653e-06     \t|  2025           \t|  0.0082322      \t|  0.024636       \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                            \t|  4.0047e-06     \t|  2025           \t|  0.0081096      \t|  0.024269       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                            \t|  3.9541e-06     \t|  2025           \t|  0.008007       \t|  0.023962       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                       \t|  3.8949e-06     \t|  2025           \t|  0.0078872      \t|  0.023603       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                          \t|  3.8939e-06     \t|  2025           \t|  0.0078851      \t|  0.023597       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                 \t|  3.7847e-06     \t|  2025           \t|  0.0076641      \t|  0.022935       \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                               \t|  3.7538e-06     \t|  2025           \t|  0.0076014      \t|  0.022748       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                    \t|  3.7396e-06     \t|  2025           \t|  0.0075726      \t|  0.022662       \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                 \t|  3.7318e-06     \t|  2025           \t|  0.0075569      \t|  0.022615       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                              \t|  3.7165e-06     \t|  2025           \t|  0.007526       \t|  0.022522       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step          \t|  3.7058e-06     \t|  2025           \t|  0.0075042      \t|  0.022457       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                    \t|  3.6909e-06     \t|  2025           \t|  0.007474       \t|  0.022367       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                      \t|  3.6828e-06     \t|  2025           \t|  0.0074576      \t|  0.022318       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad               \t|  3.6682e-06     \t|  2025           \t|  0.0074282      \t|  0.02223        \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                          \t|  3.6627e-06     \t|  2025           \t|  0.0074169      \t|  0.022196       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                        \t|  3.6406e-06     \t|  2025           \t|  0.0073721      \t|  0.022062       \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                     \t|  3.6285e-06     \t|  2025           \t|  0.0073477      \t|  0.021989       \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                           \t|  3.592e-06      \t|  2025           \t|  0.0072739      \t|  0.021768       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                \t|  3.5771e-06     \t|  2025           \t|  0.0072435      \t|  0.021677       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                              \t|  3.5104e-06     \t|  2025           \t|  0.0071085      \t|  0.021273       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                         \t|  3.4943e-06     \t|  2025           \t|  0.007076       \t|  0.021176       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                \t|  3.4814e-06     \t|  2025           \t|  0.0070498      \t|  0.021097       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                           \t|  1.1731e-05     \t|  405            \t|  0.004751       \t|  0.014218       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                           \t|  2.288e-06      \t|  2025           \t|  0.0046332      \t|  0.013865       \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                             \t|  2.0628e-06     \t|  2025           \t|  0.0041772      \t|  0.012501       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                            \t|  1.9614e-06     \t|  2025           \t|  0.0039718      \t|  0.011886       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                          \t|  1.8941e-06     \t|  2025           \t|  0.0038355      \t|  0.011478       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                         \t|  9.3916e-06     \t|  405            \t|  0.0038036      \t|  0.011383       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                             \t|  1.8644e-06     \t|  2025           \t|  0.0037754      \t|  0.011298       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                        \t|  8.951e-06      \t|  405            \t|  0.0036251      \t|  0.010849       \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                    \t|  1.538e-06      \t|  2025           \t|  0.0031145      \t|  0.0093206      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                      \t|  1.4819e-06     \t|  2025           \t|  0.0030008      \t|  0.0089802      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                 \t|  1.4456e-06     \t|  2025           \t|  0.0029272      \t|  0.0087601      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                            \t|  1.4301e-06     \t|  2025           \t|  0.0028959      \t|  0.0086662      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                    \t|  4.4643e-06     \t|  540            \t|  0.0024107      \t|  0.0072143      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                \t|  5.4076e-06     \t|  405            \t|  0.0021901      \t|  0.006554       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                      \t|  3.9964e-06     \t|  540            \t|  0.0021581      \t|  0.0064582      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                      \t|  7.8475e-06     \t|  270            \t|  0.0021188      \t|  0.0063408      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                            \t|  3.6405e-06     \t|  540            \t|  0.0019659      \t|  0.0058831      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                    \t|  7.132e-06      \t|  270            \t|  0.0019257      \t|  0.0057627      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                    \t|  3.5538e-06     \t|  540            \t|  0.001919       \t|  0.0057429      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                      \t|  3.5393e-06     \t|  540            \t|  0.0019112      \t|  0.0057196      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                \t|  3.5354e-06     \t|  540            \t|  0.0019091      \t|  0.0057132      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                               \t|  3.514e-06      \t|  540            \t|  0.0018975      \t|  0.0056786      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                 \t|  3.4808e-06     \t|  540            \t|  0.0018797      \t|  0.0056251      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                              \t|  3.4641e-06     \t|  540            \t|  0.0018706      \t|  0.0055979      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                              \t|  3.4054e-06     \t|  540            \t|  0.0018389      \t|  0.0055031      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                          \t|  4.2872e-06     \t|  405            \t|  0.0017363      \t|  0.0051961      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                            \t|  1.2004e-05     \t|  135            \t|  0.0016205      \t|  0.0048495      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start              \t|  3.9786e-06     \t|  405            \t|  0.0016113      \t|  0.0048221      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                              \t|  3.7632e-06     \t|  405            \t|  0.0015241      \t|  0.004561       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                         \t|  5.5216e-06     \t|  270            \t|  0.0014908      \t|  0.0044615      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                           \t|  4.9707e-06     \t|  270            \t|  0.0013421      \t|  0.0040163      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                          \t|  9.3655e-06     \t|  135            \t|  0.0012643      \t|  0.0037837      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                     \t|  4.3798e-06     \t|  270            \t|  0.0011826      \t|  0.0035389      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                   \t|  4.2491e-06     \t|  270            \t|  0.0011473      \t|  0.0034333      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end           \t|  4.0355e-06     \t|  270            \t|  0.0010896      \t|  0.0032607      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start         \t|  3.7838e-06     \t|  270            \t|  0.0010216      \t|  0.0030573      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                               \t|  6.5417e-06     \t|  135            \t|  0.00088313     \t|  0.0026429      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                \t|  1.5787e-06     \t|  540            \t|  0.00085248     \t|  0.0025511      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                 \t|  0.0008341      \t|  1              \t|  0.0008341      \t|  0.0024961      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                           \t|  5.9331e-06     \t|  135            \t|  0.00080096     \t|  0.002397       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                  \t|  1.4577e-06     \t|  540            \t|  0.00078715     \t|  0.0023556      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                            \t|  1.9329e-06     \t|  405            \t|  0.00078283     \t|  0.0023427      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                          \t|  1.7417e-06     \t|  405            \t|  0.00070537     \t|  0.0021109      \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                           \t|  2.5468e-06     \t|  270            \t|  0.00068764     \t|  0.0020578      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                           \t|  4.5265e-06     \t|  135            \t|  0.00061108     \t|  0.0018287      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                         \t|  4.1001e-06     \t|  135            \t|  0.00055352     \t|  0.0016565      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                   \t|  3.914e-06      \t|  135            \t|  0.0005284      \t|  0.0015813      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                       \t|  1.9566e-06     \t|  270            \t|  0.00052828     \t|  0.0015809      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                      \t|  3.831e-06      \t|  135            \t|  0.00051719     \t|  0.0015477      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start               \t|  3.83e-06       \t|  135            \t|  0.00051704     \t|  0.0015473      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                         \t|  3.8056e-06     \t|  135            \t|  0.00051375     \t|  0.0015375      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end           \t|  3.6691e-06     \t|  135            \t|  0.00049532     \t|  0.0014823      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                 \t|  3.5105e-06     \t|  135            \t|  0.00047391     \t|  0.0014182      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                     \t|  3.4282e-06     \t|  135            \t|  0.0004628      \t|  0.001385       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start         \t|  3.403e-06      \t|  135            \t|  0.0004594      \t|  0.0013748      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                   \t|  3.3859e-06     \t|  135            \t|  0.0004571      \t|  0.0013679      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                     \t|  1.6778e-06     \t|  270            \t|  0.00045302     \t|  0.0013557      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                    \t|  3.3034e-06     \t|  135            \t|  0.00044596     \t|  0.0013346      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                             \t|  3.2504e-06     \t|  135            \t|  0.00043881     \t|  0.0013132      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                  \t|  1.5667e-06     \t|  270            \t|  0.00042302     \t|  0.0012659      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                    \t|  2.0979e-06     \t|  135            \t|  0.00028322     \t|  0.00084755     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                \t|  6.1042e-06     \t|  45             \t|  0.00027469     \t|  0.00082203     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                           \t|  1.8663e-06     \t|  135            \t|  0.00025195     \t|  0.00075399     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                  \t|  1.7926e-06     \t|  135            \t|  0.000242       \t|  0.00072422     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                     \t|  1.7733e-06     \t|  135            \t|  0.0002394      \t|  0.00071642     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                              \t|  0.0002377      \t|  1              \t|  0.0002377      \t|  0.00071134     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                       \t|  1.7107e-06     \t|  135            \t|  0.00023095     \t|  0.00069113     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                            \t|  0.00022308     \t|  1              \t|  0.00022308     \t|  0.00066759     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                              \t|  0.00020426     \t|  1              \t|  0.00020426     \t|  0.00061127     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                        \t|  4.0364e-06     \t|  45             \t|  0.00018164     \t|  0.00054356     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                           \t|  3.7016e-06     \t|  45             \t|  0.00016657     \t|  0.00049849     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                          \t|  3.4865e-06     \t|  45             \t|  0.00015689     \t|  0.00046952     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                \t|  3.4844e-06     \t|  45             \t|  0.0001568      \t|  0.00046923     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                          \t|  0.00011637     \t|  1              \t|  0.00011637     \t|  0.00034826     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                            \t|  1.7948e-06     \t|  45             \t|  8.0765e-05     \t|  0.0002417      \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                      \t|  1.9891e-05     \t|  1              \t|  1.9891e-05     \t|  5.9526e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                    \t|  1.8716e-05     \t|  1              \t|  1.8716e-05     \t|  5.6009e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                 \t|  1.6041e-05     \t|  1              \t|  1.6041e-05     \t|  4.8004e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                \t|  1.4124e-05     \t|  1              \t|  1.4124e-05     \t|  4.2267e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                    \t|  1.344e-05      \t|  1              \t|  1.344e-05      \t|  4.0221e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                     \t|  9.082e-06      \t|  1              \t|  9.082e-06      \t|  2.7179e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                               \t|  8.807e-06      \t|  1              \t|  8.807e-06      \t|  2.6356e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                         \t|  8.772e-06      \t|  1              \t|  8.772e-06      \t|  2.6251e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                      \t|  7.356e-06      \t|  1              \t|  7.356e-06      \t|  2.2014e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                             \t|  6.747e-06      \t|  1              \t|  6.747e-06      \t|  2.0191e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                               \t|  6.545e-06      \t|  1              \t|  6.545e-06      \t|  1.9587e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                        \t|  6.433e-06      \t|  1              \t|  6.433e-06      \t|  1.9251e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                        \t|  6.024e-06      \t|  1              \t|  6.024e-06      \t|  1.8027e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                      \t|  6.022e-06      \t|  1              \t|  6.022e-06      \t|  1.8021e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                      \t|  5.958e-06      \t|  1              \t|  5.958e-06      \t|  1.783e-05      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                \t|  5.87e-06       \t|  1              \t|  5.87e-06       \t|  1.7567e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                    \t|  5.774e-06      \t|  1              \t|  5.774e-06      \t|  1.7279e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                 \t|  5.478e-06      \t|  1              \t|  5.478e-06      \t|  1.6393e-05     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                        \t|  5.255e-06      \t|  1              \t|  5.255e-06      \t|  1.5726e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                      \t|  5.106e-06      \t|  1              \t|  5.106e-06      \t|  1.528e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                \t|  5.079e-06      \t|  1              \t|  5.079e-06      \t|  1.5199e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                     \t|  5.024e-06      \t|  1              \t|  5.024e-06      \t|  1.5035e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                              \t|  4.985e-06      \t|  1              \t|  4.985e-06      \t|  1.4918e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                         \t|  4.972e-06      \t|  1              \t|  4.972e-06      \t|  1.4879e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                       \t|  4.961e-06      \t|  1              \t|  4.961e-06      \t|  1.4846e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                              \t|  4.947e-06      \t|  1              \t|  4.947e-06      \t|  1.4804e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start         \t|  4.943e-06      \t|  1              \t|  4.943e-06      \t|  1.4792e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                           \t|  4.895e-06      \t|  1              \t|  4.895e-06      \t|  1.4649e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                   \t|  4.817e-06      \t|  1              \t|  4.817e-06      \t|  1.4415e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                       \t|  4.779e-06      \t|  1              \t|  4.779e-06      \t|  1.4302e-05     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                          \t|  4.724e-06      \t|  1              \t|  4.724e-06      \t|  1.4137e-05     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                   \t|  4.683e-06      \t|  1              \t|  4.683e-06      \t|  1.4014e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                           \t|  4.673e-06      \t|  1              \t|  4.673e-06      \t|  1.3984e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                  \t|  4.64e-06       \t|  1              \t|  4.64e-06       \t|  1.3886e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                   \t|  4.619e-06      \t|  1              \t|  4.619e-06      \t|  1.3823e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup\t|  4.566e-06      \t|  1              \t|  4.566e-06      \t|  1.3664e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model        \t|  4.55e-06       \t|  1              \t|  4.55e-06       \t|  1.3616e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end           \t|  4.55e-06       \t|  1              \t|  4.55e-06       \t|  1.3616e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                             \t|  3.939e-06      \t|  1              \t|  3.939e-06      \t|  1.1788e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                          \t|  3.666e-06      \t|  1              \t|  3.666e-06      \t|  1.0971e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                  \t|  3.602e-06      \t|  1              \t|  3.602e-06      \t|  1.0779e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                \t|  3.555e-06      \t|  1              \t|  3.555e-06      \t|  1.0639e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                  \t|  3.187e-06      \t|  1              \t|  3.187e-06      \t|  9.5374e-06     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                   \t|  3.162e-06      \t|  1              \t|  3.162e-06      \t|  9.4626e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                       \t|  3.017e-06      \t|  1              \t|  3.017e-06      \t|  9.0287e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                        \t|  2.932e-06      \t|  1              \t|  2.932e-06      \t|  8.7743e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                          \t|  2.88e-06       \t|  1              \t|  2.88e-06       \t|  8.6187e-06     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                     \t|  2.843e-06      \t|  1              \t|  2.843e-06      \t|  8.508e-06      \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                  \t|  2.812e-06      \t|  1              \t|  2.812e-06      \t|  8.4152e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                         \t|  2.802e-06      \t|  1              \t|  2.802e-06      \t|  8.3853e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                           \t|  2.769e-06      \t|  1              \t|  2.769e-06      \t|  8.2865e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                    \t|  2.704e-06      \t|  1              \t|  2.704e-06      \t|  8.092e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                \t|  2.569e-06      \t|  1              \t|  2.569e-06      \t|  7.688e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                     \t|  2.42e-06       \t|  1              \t|  2.42e-06       \t|  7.2421e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                  \t|  2.357e-06      \t|  1              \t|  2.357e-06      \t|  7.0536e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                  \t|  2.215e-06      \t|  1              \t|  2.215e-06      \t|  6.6286e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                         \t|  1.983e-06      \t|  1              \t|  1.983e-06      \t|  5.9343e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                       \t|  1.81e-06       \t|  1              \t|  1.81e-06       \t|  5.4166e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                       \t|  1.785e-06      \t|  1              \t|  1.785e-06      \t|  5.3418e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                    \t|  1.533e-06      \t|  1              \t|  1.533e-06      \t|  4.5877e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                      \t|  1.47e-06       \t|  1              \t|  1.47e-06       \t|  4.3991e-06     \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "predict - mridangam_stroke - 2022-06-03 21:10:04,568 - 568 - Validation Score for the Training Split: 0.8458781242370605\n",
      "\n",
      "split: 2it [01:10, 35.11s/it]\u001B[Apredict - mridangam_stroke - 2022-06-03 21:10:04,568 - 568 - Training split 4 of 5: {'train': ['fold00', 'fold01', 'fold02'], 'valid': ['fold04'], 'test': ['fold03']}\n",
      "/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "==========================================================================================\n",
      "Layer (type:depth-idx)                   Output Shape              Param #\n",
      "==========================================================================================\n",
      "FullyConnectedPrediction                 [64, 6]                   --\n",
      "├─Sequential: 1-1                        [64, 1024]                --\n",
      "│    └─Linear: 2-1                       [64, 1024]                1,049,600\n",
      "│    └─BatchNorm1d: 2-2                  [64, 1024]                2,048\n",
      "│    └─Dropout: 2-3                      [64, 1024]                --\n",
      "│    └─ReLU: 2-4                         [64, 1024]                --\n",
      "├─Linear: 1-2                            [64, 6]                   6,150\n",
      "├─Softmax: 1-3                           [64, 6]                   --\n",
      "├─OneHotToCrossEntropyLoss: 1-4          --                        --\n",
      "│    └─CrossEntropyLoss: 2-5             --                        --\n",
      "==========================================================================================\n",
      "Total params: 1,057,798\n",
      "Trainable params: 1,057,798\n",
      "Non-trainable params: 0\n",
      "Total mult-adds (M): 67.70\n",
      "==========================================================================================\n",
      "Input size (MB): 0.26\n",
      "Forward/backward pass size (MB): 1.05\n",
      "Params size (MB): 4.23\n",
      "Estimated Total Size (MB): 5.55\n",
      "==========================================================================================\n",
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 78484.38it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 31594.49it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 115693.51it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 30228.91it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 83522.06it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 26796.06it/s]\n",
      "Getting embeddings for split ['fold00', 'fold01', 'fold02'], which has 4187 instances.\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 82494.03it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 36533.70it/s]\n",
      "Getting embeddings for split ['fold04'], which has 1395 instances.\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name      | Type                     | Params\n",
      "-------------------------------------------------------\n",
      "0 | layernorm | Identity                 | 0     \n",
      "1 | predictor | FullyConnectedPrediction | 1.1 M \n",
      "-------------------------------------------------------\n",
      "1.1 M     Trainable params\n",
      "0         Non-trainable params\n",
      "1.1 M     Total params\n",
      "4.231     Total estimated model params size (MB)\n",
      "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py:1937: PossibleUserWarning: The number of training batches (5) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n",
      "  category=PossibleUserWarning,\n",
      "Epoch 0:   0% 0/5 [00:00<?, ?it/s] /usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Epoch 2:   0% 0/7 [00:00<?, ?it/s, loss=1.98, v_num=10]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Epoch 2: 100% 7/7 [00:00<00:00, 123.60it/s, loss=1.98, v_num=10]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Epoch 2: 100% 7/7 [00:00<00:00, 74.18it/s, loss=1.81, v_num=10, val_loss=1.670, val_top1_acc=0.320, val_d_prime=0.972, val_aucroc=0.733, val_mAP=0.421]\n",
      "Epoch 5:   0% 0/7 [00:00<?, ?it/s, loss=1.43, v_num=10, val_loss=1.670, val_top1_acc=0.320, val_d_prime=0.972, val_aucroc=0.733, val_mAP=0.421]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 5: 100% 7/7 [00:00<00:00, 23.05it/s, loss=1.28, v_num=10, val_loss=1.240, val_top1_acc=0.505, val_d_prime=1.630, val_aucroc=0.847, val_mAP=0.570]\n",
      "Epoch 8:   0% 0/7 [00:00<?, ?it/s, loss=1.11, v_num=10, val_loss=1.240, val_top1_acc=0.505, val_d_prime=1.630, val_aucroc=0.847, val_mAP=0.570]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 8: 100% 7/7 [00:00<00:00, 77.67it/s, loss=1.05, v_num=10, val_loss=1.040, val_top1_acc=0.613, val_d_prime=1.940, val_aucroc=0.884, val_mAP=0.664] \n",
      "Epoch 11:   0% 0/7 [00:00<?, ?it/s, loss=0.953, v_num=10, val_loss=1.040, val_top1_acc=0.613, val_d_prime=1.940, val_aucroc=0.884, val_mAP=0.664]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 11: 100% 7/7 [00:00<00:00, 80.56it/s, loss=0.914, v_num=10, val_loss=0.945, val_top1_acc=0.646, val_d_prime=2.110, val_aucroc=0.900, val_mAP=0.704] \n",
      "Epoch 14:   0% 0/7 [00:00<?, ?it/s, loss=0.843, v_num=10, val_loss=0.945, val_top1_acc=0.646, val_d_prime=2.110, val_aucroc=0.900, val_mAP=0.704]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 14: 100% 7/7 [00:00<00:00, 70.51it/s, loss=0.815, v_num=10, val_loss=0.879, val_top1_acc=0.667, val_d_prime=2.240, val_aucroc=0.912, val_mAP=0.734] \n",
      "Epoch 17:   0% 0/7 [00:00<?, ?it/s, loss=0.761, v_num=10, val_loss=0.879, val_top1_acc=0.667, val_d_prime=2.240, val_aucroc=0.912, val_mAP=0.734]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 17: 100% 7/7 [00:00<00:00, 66.11it/s, loss=0.739, v_num=10, val_loss=0.814, val_top1_acc=0.694, val_d_prime=2.350, val_aucroc=0.920, val_mAP=0.756]\n",
      "Epoch 20:   0% 0/7 [00:00<?, ?it/s, loss=0.7, v_num=10, val_loss=0.814, val_top1_acc=0.694, val_d_prime=2.350, val_aucroc=0.920, val_mAP=0.756]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 20: 100% 7/7 [00:00<00:00, 60.26it/s, loss=0.683, v_num=10, val_loss=0.786, val_top1_acc=0.710, val_d_prime=2.440, val_aucroc=0.925, val_mAP=0.768]\n",
      "Epoch 23:   0% 0/7 [00:00<?, ?it/s, loss=0.65, v_num=10, val_loss=0.786, val_top1_acc=0.710, val_d_prime=2.440, val_aucroc=0.925, val_mAP=0.768]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 23: 100% 7/7 [00:00<00:00, 58.92it/s, loss=0.636, v_num=10, val_loss=0.756, val_top1_acc=0.715, val_d_prime=2.520, val_aucroc=0.930, val_mAP=0.780]\n",
      "Epoch 26:   0% 0/7 [00:00<?, ?it/s, loss=0.606, v_num=10, val_loss=0.756, val_top1_acc=0.715, val_d_prime=2.520, val_aucroc=0.930, val_mAP=0.780]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 26: 100% 7/7 [00:00<00:00, 71.58it/s, loss=0.589, v_num=10, val_loss=0.720, val_top1_acc=0.730, val_d_prime=2.580, val_aucroc=0.935, val_mAP=0.792] \n",
      "Epoch 29:   0% 0/7 [00:00<?, ?it/s, loss=0.566, v_num=10, val_loss=0.720, val_top1_acc=0.730, val_d_prime=2.580, val_aucroc=0.935, val_mAP=0.792]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 29: 100% 7/7 [00:00<00:00, 71.40it/s, loss=0.555, v_num=10, val_loss=0.696, val_top1_acc=0.734, val_d_prime=2.630, val_aucroc=0.937, val_mAP=0.792] \n",
      "Epoch 32:   0% 0/7 [00:00<?, ?it/s, loss=0.534, v_num=10, val_loss=0.696, val_top1_acc=0.734, val_d_prime=2.630, val_aucroc=0.937, val_mAP=0.792]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 32: 100% 7/7 [00:00<00:00, 79.37it/s, loss=0.523, v_num=10, val_loss=0.676, val_top1_acc=0.748, val_d_prime=2.690, val_aucroc=0.941, val_mAP=0.805] \n",
      "Epoch 35:   0% 0/7 [00:00<?, ?it/s, loss=0.503, v_num=10, val_loss=0.676, val_top1_acc=0.748, val_d_prime=2.690, val_aucroc=0.941, val_mAP=0.805]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 35: 100% 7/7 [00:00<00:00, 74.62it/s, loss=0.493, v_num=10, val_loss=0.661, val_top1_acc=0.756, val_d_prime=2.740, val_aucroc=0.943, val_mAP=0.808] \n",
      "Epoch 38:   0% 0/7 [00:00<?, ?it/s, loss=0.474, v_num=10, val_loss=0.661, val_top1_acc=0.756, val_d_prime=2.740, val_aucroc=0.943, val_mAP=0.808]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 38: 100% 7/7 [00:00<00:00, 63.22it/s, loss=0.464, v_num=10, val_loss=0.654, val_top1_acc=0.759, val_d_prime=2.770, val_aucroc=0.944, val_mAP=0.810]\n",
      "Epoch 41:   0% 0/7 [00:00<?, ?it/s, loss=0.449, v_num=10, val_loss=0.654, val_top1_acc=0.759, val_d_prime=2.770, val_aucroc=0.944, val_mAP=0.810]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 41: 100% 7/7 [00:00<00:00, 55.09it/s, loss=0.442, v_num=10, val_loss=0.634, val_top1_acc=0.760, val_d_prime=2.810, val_aucroc=0.945, val_mAP=0.812]\n",
      "Epoch 44:   0% 0/7 [00:00<?, ?it/s, loss=0.429, v_num=10, val_loss=0.634, val_top1_acc=0.760, val_d_prime=2.810, val_aucroc=0.945, val_mAP=0.812]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 44: 100% 7/7 [00:00<00:00, 64.13it/s, loss=0.422, v_num=10, val_loss=0.620, val_top1_acc=0.766, val_d_prime=2.850, val_aucroc=0.948, val_mAP=0.817] \n",
      "Epoch 47:   0% 0/7 [00:00<?, ?it/s, loss=0.412, v_num=10, val_loss=0.620, val_top1_acc=0.766, val_d_prime=2.850, val_aucroc=0.948, val_mAP=0.817]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 47: 100% 7/7 [00:00<00:00, 80.80it/s, loss=0.405, v_num=10, val_loss=0.613, val_top1_acc=0.768, val_d_prime=2.880, val_aucroc=0.949, val_mAP=0.819] \n",
      "Epoch 50:   0% 0/7 [00:00<?, ?it/s, loss=0.396, v_num=10, val_loss=0.613, val_top1_acc=0.768, val_d_prime=2.880, val_aucroc=0.949, val_mAP=0.819]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 50: 100% 7/7 [00:00<00:00, 75.35it/s, loss=0.39, v_num=10, val_loss=0.603, val_top1_acc=0.774, val_d_prime=2.910, val_aucroc=0.950, val_mAP=0.820]  \n",
      "Epoch 53:   0% 0/7 [00:00<?, ?it/s, loss=0.38, v_num=10, val_loss=0.603, val_top1_acc=0.774, val_d_prime=2.910, val_aucroc=0.950, val_mAP=0.820]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 53: 100% 7/7 [00:00<00:00, 80.09it/s, loss=0.373, v_num=10, val_loss=0.596, val_top1_acc=0.776, val_d_prime=2.940, val_aucroc=0.952, val_mAP=0.824]\n",
      "Epoch 56:   0% 0/7 [00:00<?, ?it/s, loss=0.364, v_num=10, val_loss=0.596, val_top1_acc=0.776, val_d_prime=2.940, val_aucroc=0.952, val_mAP=0.824]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 56: 100% 7/7 [00:00<00:00, 81.40it/s, loss=0.358, v_num=10, val_loss=0.588, val_top1_acc=0.779, val_d_prime=2.970, val_aucroc=0.952, val_mAP=0.824] \n",
      "Epoch 59:   0% 0/7 [00:00<?, ?it/s, loss=0.349, v_num=10, val_loss=0.588, val_top1_acc=0.779, val_d_prime=2.970, val_aucroc=0.952, val_mAP=0.824]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 59: 100% 7/7 [00:00<00:00, 68.54it/s, loss=0.344, v_num=10, val_loss=0.582, val_top1_acc=0.776, val_d_prime=2.970, val_aucroc=0.952, val_mAP=0.824] \n",
      "Epoch 62:   0% 0/7 [00:00<?, ?it/s, loss=0.338, v_num=10, val_loss=0.582, val_top1_acc=0.776, val_d_prime=2.970, val_aucroc=0.952, val_mAP=0.824]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 62: 100% 7/7 [00:00<00:00, 73.88it/s, loss=0.332, v_num=10, val_loss=0.575, val_top1_acc=0.776, val_d_prime=3.000, val_aucroc=0.953, val_mAP=0.829] \n",
      "Epoch 65:   0% 0/7 [00:00<?, ?it/s, loss=0.325, v_num=10, val_loss=0.575, val_top1_acc=0.776, val_d_prime=3.000, val_aucroc=0.953, val_mAP=0.829]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 65: 100% 7/7 [00:00<00:00, 65.59it/s, loss=0.32, v_num=10, val_loss=0.561, val_top1_acc=0.779, val_d_prime=3.020, val_aucroc=0.955, val_mAP=0.831] \n",
      "Epoch 68:   0% 0/7 [00:00<?, ?it/s, loss=0.313, v_num=10, val_loss=0.561, val_top1_acc=0.779, val_d_prime=3.020, val_aucroc=0.955, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 68: 100% 7/7 [00:00<00:00, 62.61it/s, loss=0.309, v_num=10, val_loss=0.559, val_top1_acc=0.784, val_d_prime=3.040, val_aucroc=0.955, val_mAP=0.833] \n",
      "Epoch 71:   0% 0/7 [00:00<?, ?it/s, loss=0.303, v_num=10, val_loss=0.559, val_top1_acc=0.784, val_d_prime=3.040, val_aucroc=0.955, val_mAP=0.833]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 71: 100% 7/7 [00:00<00:00, 76.52it/s, loss=0.3, v_num=10, val_loss=0.562, val_top1_acc=0.786, val_d_prime=3.060, val_aucroc=0.957, val_mAP=0.839]   \n",
      "Epoch 74:   0% 0/7 [00:00<?, ?it/s, loss=0.294, v_num=10, val_loss=0.562, val_top1_acc=0.786, val_d_prime=3.060, val_aucroc=0.957, val_mAP=0.839]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 74: 100% 7/7 [00:00<00:00, 63.77it/s, loss=0.291, v_num=10, val_loss=0.552, val_top1_acc=0.785, val_d_prime=3.070, val_aucroc=0.957, val_mAP=0.839] \n",
      "Epoch 77:   0% 0/7 [00:00<?, ?it/s, loss=0.282, v_num=10, val_loss=0.552, val_top1_acc=0.785, val_d_prime=3.070, val_aucroc=0.957, val_mAP=0.839]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 77: 100% 7/7 [00:00<00:00, 81.96it/s, loss=0.279, v_num=10, val_loss=0.551, val_top1_acc=0.789, val_d_prime=3.080, val_aucroc=0.955, val_mAP=0.833] \n",
      "Epoch 80:   0% 0/7 [00:00<?, ?it/s, loss=0.273, v_num=10, val_loss=0.551, val_top1_acc=0.789, val_d_prime=3.080, val_aucroc=0.955, val_mAP=0.833]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 80: 100% 7/7 [00:00<00:00, 67.34it/s, loss=0.271, v_num=10, val_loss=0.550, val_top1_acc=0.791, val_d_prime=3.100, val_aucroc=0.957, val_mAP=0.837] \n",
      "Epoch 83:   0% 0/7 [00:00<?, ?it/s, loss=0.265, v_num=10, val_loss=0.550, val_top1_acc=0.791, val_d_prime=3.100, val_aucroc=0.957, val_mAP=0.837]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 83: 100% 7/7 [00:00<00:00, 71.40it/s, loss=0.263, v_num=10, val_loss=0.542, val_top1_acc=0.789, val_d_prime=3.100, val_aucroc=0.958, val_mAP=0.841] \n",
      "Epoch 86:   0% 0/7 [00:00<?, ?it/s, loss=0.259, v_num=10, val_loss=0.542, val_top1_acc=0.789, val_d_prime=3.100, val_aucroc=0.958, val_mAP=0.841]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 86: 100% 7/7 [00:00<00:00, 75.48it/s, loss=0.257, v_num=10, val_loss=0.549, val_top1_acc=0.786, val_d_prime=3.100, val_aucroc=0.958, val_mAP=0.841] \n",
      "Epoch 89:   0% 0/7 [00:00<?, ?it/s, loss=0.252, v_num=10, val_loss=0.549, val_top1_acc=0.786, val_d_prime=3.100, val_aucroc=0.958, val_mAP=0.841]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 89: 100% 7/7 [00:00<00:00, 58.73it/s, loss=0.249, v_num=10, val_loss=0.546, val_top1_acc=0.789, val_d_prime=3.110, val_aucroc=0.958, val_mAP=0.842]\n",
      "Epoch 92:   0% 0/7 [00:00<?, ?it/s, loss=0.244, v_num=10, val_loss=0.546, val_top1_acc=0.789, val_d_prime=3.110, val_aucroc=0.958, val_mAP=0.842]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 92: 100% 7/7 [00:00<00:00, 68.82it/s, loss=0.242, v_num=10, val_loss=0.542, val_top1_acc=0.792, val_d_prime=3.110, val_aucroc=0.959, val_mAP=0.842] \n",
      "Epoch 95:   0% 0/7 [00:00<?, ?it/s, loss=0.238, v_num=10, val_loss=0.542, val_top1_acc=0.792, val_d_prime=3.110, val_aucroc=0.959, val_mAP=0.842]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 95: 100% 7/7 [00:00<00:00, 75.46it/s, loss=0.236, v_num=10, val_loss=0.537, val_top1_acc=0.802, val_d_prime=3.120, val_aucroc=0.959, val_mAP=0.842] \n",
      "Epoch 98:   0% 0/7 [00:00<?, ?it/s, loss=0.231, v_num=10, val_loss=0.537, val_top1_acc=0.802, val_d_prime=3.120, val_aucroc=0.959, val_mAP=0.842]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 98: 100% 7/7 [00:00<00:00, 65.66it/s, loss=0.229, v_num=10, val_loss=0.533, val_top1_acc=0.801, val_d_prime=3.120, val_aucroc=0.960, val_mAP=0.847]\n",
      "Epoch 101:   0% 0/7 [00:00<?, ?it/s, loss=0.224, v_num=10, val_loss=0.533, val_top1_acc=0.801, val_d_prime=3.120, val_aucroc=0.960, val_mAP=0.847]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 101: 100% 7/7 [00:00<00:00, 66.26it/s, loss=0.222, v_num=10, val_loss=0.521, val_top1_acc=0.801, val_d_prime=3.150, val_aucroc=0.961, val_mAP=0.848] \n",
      "Epoch 104:   0% 0/7 [00:00<?, ?it/s, loss=0.217, v_num=10, val_loss=0.521, val_top1_acc=0.801, val_d_prime=3.150, val_aucroc=0.961, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 104: 100% 7/7 [00:00<00:00, 62.43it/s, loss=0.215, v_num=10, val_loss=0.523, val_top1_acc=0.806, val_d_prime=3.150, val_aucroc=0.961, val_mAP=0.848] \n",
      "Epoch 107:   0% 0/7 [00:00<?, ?it/s, loss=0.212, v_num=10, val_loss=0.523, val_top1_acc=0.806, val_d_prime=3.150, val_aucroc=0.961, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 107: 100% 7/7 [00:00<00:00, 80.95it/s, loss=0.211, v_num=10, val_loss=0.530, val_top1_acc=0.799, val_d_prime=3.160, val_aucroc=0.961, val_mAP=0.849] \n",
      "Epoch 110:   0% 0/7 [00:00<?, ?it/s, loss=0.209, v_num=10, val_loss=0.530, val_top1_acc=0.799, val_d_prime=3.160, val_aucroc=0.961, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 110: 100% 7/7 [00:00<00:00, 72.98it/s, loss=0.207, v_num=10, val_loss=0.529, val_top1_acc=0.799, val_d_prime=3.150, val_aucroc=0.960, val_mAP=0.847] \n",
      "Epoch 113:   0% 0/7 [00:00<?, ?it/s, loss=0.202, v_num=10, val_loss=0.529, val_top1_acc=0.799, val_d_prime=3.150, val_aucroc=0.960, val_mAP=0.847]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 113: 100% 7/7 [00:00<00:00, 65.16it/s, loss=0.2, v_num=10, val_loss=0.526, val_top1_acc=0.804, val_d_prime=3.160, val_aucroc=0.961, val_mAP=0.851]  \n",
      "Epoch 116:   0% 0/7 [00:00<?, ?it/s, loss=0.196, v_num=10, val_loss=0.526, val_top1_acc=0.804, val_d_prime=3.160, val_aucroc=0.961, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 116: 100% 7/7 [00:00<00:00, 74.45it/s, loss=0.194, v_num=10, val_loss=0.517, val_top1_acc=0.808, val_d_prime=3.160, val_aucroc=0.962, val_mAP=0.850] \n",
      "Epoch 119:   0% 0/7 [00:00<?, ?it/s, loss=0.192, v_num=10, val_loss=0.517, val_top1_acc=0.808, val_d_prime=3.160, val_aucroc=0.962, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 119: 100% 7/7 [00:00<00:00, 73.55it/s, loss=0.191, v_num=10, val_loss=0.523, val_top1_acc=0.805, val_d_prime=3.170, val_aucroc=0.961, val_mAP=0.849] \n",
      "Epoch 122:   0% 0/7 [00:00<?, ?it/s, loss=0.188, v_num=10, val_loss=0.523, val_top1_acc=0.805, val_d_prime=3.170, val_aucroc=0.961, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 122: 100% 7/7 [00:00<00:00, 76.11it/s, loss=0.186, v_num=10, val_loss=0.519, val_top1_acc=0.811, val_d_prime=3.170, val_aucroc=0.961, val_mAP=0.849] \n",
      "Epoch 125:   0% 0/7 [00:00<?, ?it/s, loss=0.183, v_num=10, val_loss=0.519, val_top1_acc=0.811, val_d_prime=3.170, val_aucroc=0.961, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 125: 100% 7/7 [00:00<00:00, 66.69it/s, loss=0.181, v_num=10, val_loss=0.519, val_top1_acc=0.806, val_d_prime=3.190, val_aucroc=0.962, val_mAP=0.852]\n",
      "Epoch 128:   0% 0/7 [00:00<?, ?it/s, loss=0.179, v_num=10, val_loss=0.519, val_top1_acc=0.806, val_d_prime=3.190, val_aucroc=0.962, val_mAP=0.852]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 128: 100% 7/7 [00:00<00:00, 70.39it/s, loss=0.177, v_num=10, val_loss=0.516, val_top1_acc=0.809, val_d_prime=3.200, val_aucroc=0.962, val_mAP=0.853] \n",
      "Epoch 131:   0% 0/7 [00:00<?, ?it/s, loss=0.174, v_num=10, val_loss=0.516, val_top1_acc=0.809, val_d_prime=3.200, val_aucroc=0.962, val_mAP=0.853]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 131: 100% 7/7 [00:00<00:00, 79.18it/s, loss=0.172, v_num=10, val_loss=0.512, val_top1_acc=0.814, val_d_prime=3.180, val_aucroc=0.962, val_mAP=0.853] \n",
      "Epoch 134:   0% 0/7 [00:00<?, ?it/s, loss=0.17, v_num=10, val_loss=0.512, val_top1_acc=0.814, val_d_prime=3.180, val_aucroc=0.962, val_mAP=0.853]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 134: 100% 7/7 [00:00<00:00, 58.75it/s, loss=0.168, v_num=10, val_loss=0.514, val_top1_acc=0.809, val_d_prime=3.200, val_aucroc=0.963, val_mAP=0.856]\n",
      "Epoch 137:   0% 0/7 [00:00<?, ?it/s, loss=0.166, v_num=10, val_loss=0.514, val_top1_acc=0.809, val_d_prime=3.200, val_aucroc=0.963, val_mAP=0.856]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 137: 100% 7/7 [00:00<00:00, 78.70it/s, loss=0.165, v_num=10, val_loss=0.508, val_top1_acc=0.809, val_d_prime=3.210, val_aucroc=0.963, val_mAP=0.855] \n",
      "Epoch 140:   0% 0/7 [00:00<?, ?it/s, loss=0.163, v_num=10, val_loss=0.508, val_top1_acc=0.809, val_d_prime=3.210, val_aucroc=0.963, val_mAP=0.855]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 140: 100% 7/7 [00:00<00:00, 76.24it/s, loss=0.161, v_num=10, val_loss=0.512, val_top1_acc=0.811, val_d_prime=3.210, val_aucroc=0.963, val_mAP=0.855] \n",
      "Epoch 143:   0% 0/7 [00:00<?, ?it/s, loss=0.159, v_num=10, val_loss=0.512, val_top1_acc=0.811, val_d_prime=3.210, val_aucroc=0.963, val_mAP=0.855]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 143: 100% 7/7 [00:00<00:00, 80.34it/s, loss=0.157, v_num=10, val_loss=0.506, val_top1_acc=0.812, val_d_prime=3.230, val_aucroc=0.964, val_mAP=0.857] \n",
      "Epoch 146:   0% 0/7 [00:00<?, ?it/s, loss=0.155, v_num=10, val_loss=0.506, val_top1_acc=0.812, val_d_prime=3.230, val_aucroc=0.964, val_mAP=0.857]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 146: 100% 7/7 [00:00<00:00, 56.08it/s, loss=0.154, v_num=10, val_loss=0.512, val_top1_acc=0.817, val_d_prime=3.200, val_aucroc=0.963, val_mAP=0.854]\n",
      "Epoch 149:   0% 0/7 [00:00<?, ?it/s, loss=0.152, v_num=10, val_loss=0.512, val_top1_acc=0.817, val_d_prime=3.200, val_aucroc=0.963, val_mAP=0.854]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 149: 100% 7/7 [00:00<00:00, 54.44it/s, loss=0.151, v_num=10, val_loss=0.500, val_top1_acc=0.808, val_d_prime=3.230, val_aucroc=0.965, val_mAP=0.861]\n",
      "Epoch 152:   0% 0/7 [00:00<?, ?it/s, loss=0.149, v_num=10, val_loss=0.500, val_top1_acc=0.808, val_d_prime=3.230, val_aucroc=0.965, val_mAP=0.861]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 152: 100% 7/7 [00:00<00:00, 80.24it/s, loss=0.148, v_num=10, val_loss=0.508, val_top1_acc=0.820, val_d_prime=3.200, val_aucroc=0.962, val_mAP=0.854] \n",
      "Epoch 155:   0% 0/7 [00:00<?, ?it/s, loss=0.146, v_num=10, val_loss=0.508, val_top1_acc=0.820, val_d_prime=3.200, val_aucroc=0.962, val_mAP=0.854]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 155: 100% 7/7 [00:00<00:00, 80.49it/s, loss=0.144, v_num=10, val_loss=0.511, val_top1_acc=0.809, val_d_prime=3.220, val_aucroc=0.964, val_mAP=0.859] \n",
      "Epoch 158:   0% 0/7 [00:00<?, ?it/s, loss=0.143, v_num=10, val_loss=0.511, val_top1_acc=0.809, val_d_prime=3.220, val_aucroc=0.964, val_mAP=0.859]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 158: 100% 7/7 [00:00<00:00, 67.89it/s, loss=0.141, v_num=10, val_loss=0.500, val_top1_acc=0.816, val_d_prime=3.210, val_aucroc=0.965, val_mAP=0.860]\n",
      "Epoch 161:   0% 0/7 [00:00<?, ?it/s, loss=0.139, v_num=10, val_loss=0.500, val_top1_acc=0.816, val_d_prime=3.210, val_aucroc=0.965, val_mAP=0.860]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 161: 100% 7/7 [00:00<00:00, 80.29it/s, loss=0.138, v_num=10, val_loss=0.507, val_top1_acc=0.822, val_d_prime=3.190, val_aucroc=0.964, val_mAP=0.859] \n",
      "Epoch 164:   0% 0/7 [00:00<?, ?it/s, loss=0.137, v_num=10, val_loss=0.507, val_top1_acc=0.822, val_d_prime=3.190, val_aucroc=0.964, val_mAP=0.859]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 164: 100% 7/7 [00:00<00:00, 77.80it/s, loss=0.137, v_num=10, val_loss=0.506, val_top1_acc=0.812, val_d_prime=3.220, val_aucroc=0.966, val_mAP=0.862] \n",
      "Epoch 167:   0% 0/7 [00:00<?, ?it/s, loss=0.135, v_num=10, val_loss=0.506, val_top1_acc=0.812, val_d_prime=3.220, val_aucroc=0.966, val_mAP=0.862]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 167: 100% 7/7 [00:00<00:00, 55.89it/s, loss=0.134, v_num=10, val_loss=0.527, val_top1_acc=0.812, val_d_prime=3.190, val_aucroc=0.963, val_mAP=0.859]\n",
      "Epoch 170:   0% 0/7 [00:00<?, ?it/s, loss=0.132, v_num=10, val_loss=0.527, val_top1_acc=0.812, val_d_prime=3.190, val_aucroc=0.963, val_mAP=0.859]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 170: 100% 7/7 [00:00<00:00, 75.79it/s, loss=0.131, v_num=10, val_loss=0.507, val_top1_acc=0.810, val_d_prime=3.210, val_aucroc=0.966, val_mAP=0.865] \n",
      "Epoch 173:   0% 0/7 [00:00<?, ?it/s, loss=0.128, v_num=10, val_loss=0.507, val_top1_acc=0.810, val_d_prime=3.210, val_aucroc=0.966, val_mAP=0.865]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 173: 100% 7/7 [00:00<00:00, 81.90it/s, loss=0.127, v_num=10, val_loss=0.511, val_top1_acc=0.823, val_d_prime=3.170, val_aucroc=0.964, val_mAP=0.861] \n",
      "Epoch 176:   0% 0/7 [00:00<?, ?it/s, loss=0.126, v_num=10, val_loss=0.511, val_top1_acc=0.823, val_d_prime=3.170, val_aucroc=0.964, val_mAP=0.861]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 176: 100% 7/7 [00:00<00:00, 71.77it/s, loss=0.125, v_num=10, val_loss=0.509, val_top1_acc=0.806, val_d_prime=3.220, val_aucroc=0.966, val_mAP=0.866] \n",
      "Epoch 179:   0% 0/7 [00:00<?, ?it/s, loss=0.124, v_num=10, val_loss=0.509, val_top1_acc=0.806, val_d_prime=3.220, val_aucroc=0.966, val_mAP=0.866]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 179: 100% 7/7 [00:00<00:00, 59.84it/s, loss=0.123, v_num=10, val_loss=0.513, val_top1_acc=0.827, val_d_prime=3.170, val_aucroc=0.965, val_mAP=0.864] \n",
      "Epoch 182:   0% 0/7 [00:00<?, ?it/s, loss=0.121, v_num=10, val_loss=0.513, val_top1_acc=0.827, val_d_prime=3.170, val_aucroc=0.965, val_mAP=0.864]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 182: 100% 7/7 [00:00<00:00, 80.11it/s, loss=0.121, v_num=10, val_loss=0.503, val_top1_acc=0.812, val_d_prime=3.200, val_aucroc=0.967, val_mAP=0.867] \n",
      "Epoch 185:   0% 0/7 [00:00<?, ?it/s, loss=0.12, v_num=10, val_loss=0.503, val_top1_acc=0.812, val_d_prime=3.200, val_aucroc=0.967, val_mAP=0.867]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 185: 100% 7/7 [00:00<00:00, 81.80it/s, loss=0.119, v_num=10, val_loss=0.527, val_top1_acc=0.822, val_d_prime=3.180, val_aucroc=0.964, val_mAP=0.862]\n",
      "Epoch 188:   0% 0/7 [00:00<?, ?it/s, loss=0.117, v_num=10, val_loss=0.527, val_top1_acc=0.822, val_d_prime=3.180, val_aucroc=0.964, val_mAP=0.862]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 188: 100% 7/7 [00:00<00:00, 56.30it/s, loss=0.115, v_num=10, val_loss=0.511, val_top1_acc=0.810, val_d_prime=3.220, val_aucroc=0.967, val_mAP=0.867]\n",
      "Epoch 191:   0% 0/7 [00:00<?, ?it/s, loss=0.114, v_num=10, val_loss=0.511, val_top1_acc=0.810, val_d_prime=3.220, val_aucroc=0.967, val_mAP=0.867]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 191: 100% 7/7 [00:00<00:00, 71.57it/s, loss=0.113, v_num=10, val_loss=0.524, val_top1_acc=0.821, val_d_prime=3.180, val_aucroc=0.965, val_mAP=0.864] \n",
      "Epoch 194:   0% 0/7 [00:00<?, ?it/s, loss=0.111, v_num=10, val_loss=0.524, val_top1_acc=0.821, val_d_prime=3.180, val_aucroc=0.965, val_mAP=0.864]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 194: 100% 7/7 [00:00<00:00, 78.40it/s, loss=0.111, v_num=10, val_loss=0.505, val_top1_acc=0.819, val_d_prime=3.200, val_aucroc=0.967, val_mAP=0.868] \n",
      "Epoch 197:   0% 0/7 [00:00<?, ?it/s, loss=0.11, v_num=10, val_loss=0.505, val_top1_acc=0.819, val_d_prime=3.200, val_aucroc=0.967, val_mAP=0.868]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 197: 100% 7/7 [00:00<00:00, 80.15it/s, loss=0.11, v_num=10, val_loss=0.509, val_top1_acc=0.822, val_d_prime=3.200, val_aucroc=0.966, val_mAP=0.866] \n",
      "Epoch 200:   0% 0/7 [00:00<?, ?it/s, loss=0.107, v_num=10, val_loss=0.509, val_top1_acc=0.822, val_d_prime=3.200, val_aucroc=0.966, val_mAP=0.866]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 200: 100% 7/7 [00:00<00:00, 68.71it/s, loss=0.107, v_num=10, val_loss=0.511, val_top1_acc=0.815, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.868] \n",
      "Epoch 203:   0% 0/7 [00:00<?, ?it/s, loss=0.105, v_num=10, val_loss=0.511, val_top1_acc=0.815, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.868]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 203: 100% 7/7 [00:00<00:00, 80.31it/s, loss=0.104, v_num=10, val_loss=0.512, val_top1_acc=0.820, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.869] \n",
      "Epoch 206:   0% 0/7 [00:00<?, ?it/s, loss=0.103, v_num=10, val_loss=0.512, val_top1_acc=0.820, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.869]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 206: 100% 7/7 [00:00<00:00, 65.22it/s, loss=0.103, v_num=10, val_loss=0.507, val_top1_acc=0.817, val_d_prime=3.220, val_aucroc=0.967, val_mAP=0.869]\n",
      "Epoch 209:   0% 0/7 [00:00<?, ?it/s, loss=0.101, v_num=10, val_loss=0.507, val_top1_acc=0.817, val_d_prime=3.220, val_aucroc=0.967, val_mAP=0.869]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 209: 100% 7/7 [00:00<00:00, 63.45it/s, loss=0.101, v_num=10, val_loss=0.514, val_top1_acc=0.816, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.870] \n",
      "Epoch 212:   0% 0/7 [00:00<?, ?it/s, loss=0.1, v_num=10, val_loss=0.514, val_top1_acc=0.816, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 212: 100% 7/7 [00:00<00:00, 80.03it/s, loss=0.0992, v_num=10, val_loss=0.527, val_top1_acc=0.820, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.868]\n",
      "Epoch 215:   0% 0/7 [00:00<?, ?it/s, loss=0.0972, v_num=10, val_loss=0.527, val_top1_acc=0.820, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.868]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 215: 100% 7/7 [00:00<00:00, 66.17it/s, loss=0.097, v_num=10, val_loss=0.511, val_top1_acc=0.817, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.870] \n",
      "Epoch 218:   0% 0/7 [00:00<?, ?it/s, loss=0.0964, v_num=10, val_loss=0.511, val_top1_acc=0.817, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 218: 100% 7/7 [00:00<00:00, 61.97it/s, loss=0.0958, v_num=10, val_loss=0.522, val_top1_acc=0.815, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.870] \n",
      "Epoch 221:   0% 0/7 [00:00<?, ?it/s, loss=0.0953, v_num=10, val_loss=0.522, val_top1_acc=0.815, val_d_prime=3.210, val_aucroc=0.967, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 221: 100% 7/7 [00:00<00:00, 78.84it/s, loss=0.0951, v_num=10, val_loss=0.521, val_top1_acc=0.826, val_d_prime=3.180, val_aucroc=0.966, val_mAP=0.869] \n",
      "Epoch 224:   0% 0/7 [00:00<?, ?it/s, loss=0.0939, v_num=10, val_loss=0.521, val_top1_acc=0.826, val_d_prime=3.180, val_aucroc=0.966, val_mAP=0.869]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 224: 100% 7/7 [00:00<00:00, 77.59it/s, loss=0.0932, v_num=10, val_loss=0.512, val_top1_acc=0.818, val_d_prime=3.210, val_aucroc=0.968, val_mAP=0.870] \n",
      "Epoch 227:   0% 0/7 [00:00<?, ?it/s, loss=0.0918, v_num=10, val_loss=0.512, val_top1_acc=0.818, val_d_prime=3.210, val_aucroc=0.968, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 227: 100% 7/7 [00:00<00:00, 62.25it/s, loss=0.0911, v_num=10, val_loss=0.524, val_top1_acc=0.824, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.870] \n",
      "Epoch 230:   0% 0/7 [00:00<?, ?it/s, loss=0.0896, v_num=10, val_loss=0.524, val_top1_acc=0.824, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 230: 100% 7/7 [00:00<00:00, 81.28it/s, loss=0.0888, v_num=10, val_loss=0.523, val_top1_acc=0.819, val_d_prime=3.210, val_aucroc=0.968, val_mAP=0.871] \n",
      "Epoch 233:   0% 0/7 [00:00<?, ?it/s, loss=0.0877, v_num=10, val_loss=0.523, val_top1_acc=0.819, val_d_prime=3.210, val_aucroc=0.968, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 233: 100% 7/7 [00:00<00:00, 74.77it/s, loss=0.0867, v_num=10, val_loss=0.521, val_top1_acc=0.824, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.871] \n",
      "Epoch 236:   0% 0/7 [00:00<?, ?it/s, loss=0.086, v_num=10, val_loss=0.521, val_top1_acc=0.824, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 236: 100% 7/7 [00:00<00:00, 61.46it/s, loss=0.0859, v_num=10, val_loss=0.516, val_top1_acc=0.827, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.871]\n",
      "Epoch 239:   0% 0/7 [00:00<?, ?it/s, loss=0.086, v_num=10, val_loss=0.516, val_top1_acc=0.827, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 239: 100% 7/7 [00:00<00:00, 64.89it/s, loss=0.0858, v_num=10, val_loss=0.517, val_top1_acc=0.820, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.871]\n",
      "Epoch 242:   0% 0/7 [00:00<?, ?it/s, loss=0.0837, v_num=10, val_loss=0.517, val_top1_acc=0.820, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 242: 100% 7/7 [00:00<00:00, 75.32it/s, loss=0.0831, v_num=10, val_loss=0.523, val_top1_acc=0.829, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.871] \n",
      "Epoch 245:   0% 0/7 [00:00<?, ?it/s, loss=0.0824, v_num=10, val_loss=0.523, val_top1_acc=0.829, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 245: 100% 7/7 [00:00<00:00, 79.42it/s, loss=0.0824, v_num=10, val_loss=0.526, val_top1_acc=0.817, val_d_prime=3.220, val_aucroc=0.968, val_mAP=0.873] \n",
      "Epoch 248:   0% 0/7 [00:00<?, ?it/s, loss=0.0819, v_num=10, val_loss=0.526, val_top1_acc=0.817, val_d_prime=3.220, val_aucroc=0.968, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 248: 100% 7/7 [00:00<00:00, 80.33it/s, loss=0.0817, v_num=10, val_loss=0.516, val_top1_acc=0.824, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.873] \n",
      "Epoch 251:   0% 0/7 [00:00<?, ?it/s, loss=0.0815, v_num=10, val_loss=0.516, val_top1_acc=0.824, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 251: 100% 7/7 [00:00<00:00, 55.72it/s, loss=0.0812, v_num=10, val_loss=0.539, val_top1_acc=0.829, val_d_prime=3.190, val_aucroc=0.966, val_mAP=0.870]\n",
      "Epoch 254:   0% 0/7 [00:00<?, ?it/s, loss=0.0794, v_num=10, val_loss=0.539, val_top1_acc=0.829, val_d_prime=3.190, val_aucroc=0.966, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 254: 100% 7/7 [00:00<00:00, 78.23it/s, loss=0.0789, v_num=10, val_loss=0.536, val_top1_acc=0.814, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.873] \n",
      "Epoch 257:   0% 0/7 [00:00<?, ?it/s, loss=0.078, v_num=10, val_loss=0.536, val_top1_acc=0.814, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 257: 100% 7/7 [00:00<00:00, 79.59it/s, loss=0.0783, v_num=10, val_loss=0.540, val_top1_acc=0.830, val_d_prime=3.180, val_aucroc=0.966, val_mAP=0.870]\n",
      "Epoch 260:   0% 0/7 [00:00<?, ?it/s, loss=0.0777, v_num=10, val_loss=0.540, val_top1_acc=0.830, val_d_prime=3.180, val_aucroc=0.966, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 260: 100% 7/7 [00:00<00:00, 75.06it/s, loss=0.0774, v_num=10, val_loss=0.517, val_top1_acc=0.824, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.873] \n",
      "Epoch 263:   0% 0/7 [00:00<?, ?it/s, loss=0.076, v_num=10, val_loss=0.517, val_top1_acc=0.824, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 263: 100% 7/7 [00:00<00:00, 63.86it/s, loss=0.075, v_num=10, val_loss=0.531, val_top1_acc=0.828, val_d_prime=3.200, val_aucroc=0.967, val_mAP=0.872] \n",
      "Epoch 266:   0% 0/7 [00:00<?, ?it/s, loss=0.0749, v_num=10, val_loss=0.531, val_top1_acc=0.828, val_d_prime=3.200, val_aucroc=0.967, val_mAP=0.872]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 266: 100% 7/7 [00:00<00:00, 60.76it/s, loss=0.075, v_num=10, val_loss=0.528, val_top1_acc=0.822, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874]  \n",
      "Epoch 269:   0% 0/7 [00:00<?, ?it/s, loss=0.0754, v_num=10, val_loss=0.528, val_top1_acc=0.822, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 269: 100% 7/7 [00:00<00:00, 76.87it/s, loss=0.075, v_num=10, val_loss=0.533, val_top1_acc=0.827, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.874]  \n",
      "Epoch 272:   0% 0/7 [00:00<?, ?it/s, loss=0.0738, v_num=10, val_loss=0.533, val_top1_acc=0.827, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 272: 100% 7/7 [00:00<00:00, 75.23it/s, loss=0.0731, v_num=10, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874] \n",
      "Epoch 275:   0% 0/7 [00:00<?, ?it/s, loss=0.0719, v_num=10, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 275: 100% 7/7 [00:00<00:00, 57.06it/s, loss=0.071, v_num=10, val_loss=0.534, val_top1_acc=0.829, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.873] \n",
      "Epoch 278:   0% 0/7 [00:00<?, ?it/s, loss=0.0706, v_num=10, val_loss=0.534, val_top1_acc=0.829, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 278: 100% 7/7 [00:00<00:00, 61.79it/s, loss=0.0707, v_num=10, val_loss=0.520, val_top1_acc=0.825, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874]\n",
      "Epoch 281:   0% 0/7 [00:00<?, ?it/s, loss=0.0707, v_num=10, val_loss=0.520, val_top1_acc=0.825, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 281: 100% 7/7 [00:00<00:00, 67.65it/s, loss=0.0699, v_num=10, val_loss=0.535, val_top1_acc=0.829, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.873] \n",
      "Epoch 284:   0% 0/7 [00:00<?, ?it/s, loss=0.0686, v_num=10, val_loss=0.535, val_top1_acc=0.829, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.873]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 284: 100% 7/7 [00:00<00:00, 80.86it/s, loss=0.0676, v_num=10, val_loss=0.537, val_top1_acc=0.820, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874] \n",
      "Epoch 287:   0% 0/7 [00:00<?, ?it/s, loss=0.0674, v_num=10, val_loss=0.537, val_top1_acc=0.820, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 287: 100% 7/7 [00:00<00:00, 79.29it/s, loss=0.0668, v_num=10, val_loss=0.547, val_top1_acc=0.833, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.874] \n",
      "Epoch 290:   0% 0/7 [00:00<?, ?it/s, loss=0.0662, v_num=10, val_loss=0.547, val_top1_acc=0.833, val_d_prime=3.190, val_aucroc=0.967, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 290: 100% 7/7 [00:00<00:00, 74.02it/s, loss=0.066, v_num=10, val_loss=0.534, val_top1_acc=0.819, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.874]  \n",
      "Epoch 293:   0% 0/7 [00:00<?, ?it/s, loss=0.066, v_num=10, val_loss=0.534, val_top1_acc=0.819, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 293: 100% 7/7 [00:00<00:00, 74.35it/s, loss=0.0657, v_num=10, val_loss=0.532, val_top1_acc=0.837, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.872]\n",
      "Epoch 296:   0% 0/7 [00:00<?, ?it/s, loss=0.0647, v_num=10, val_loss=0.532, val_top1_acc=0.837, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.872]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 296: 100% 7/7 [00:00<00:00, 69.53it/s, loss=0.0645, v_num=10, val_loss=0.516, val_top1_acc=0.826, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.874] \n",
      "Epoch 299:   0% 0/7 [00:00<?, ?it/s, loss=0.0642, v_num=10, val_loss=0.516, val_top1_acc=0.826, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 299: 100% 7/7 [00:00<00:00, 57.20it/s, loss=0.0639, v_num=10, val_loss=0.545, val_top1_acc=0.831, val_d_prime=3.170, val_aucroc=0.966, val_mAP=0.871]\n",
      "Epoch 302:   0% 0/7 [00:00<?, ?it/s, loss=0.0636, v_num=10, val_loss=0.545, val_top1_acc=0.831, val_d_prime=3.170, val_aucroc=0.966, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 302: 100% 7/7 [00:00<00:00, 80.24it/s, loss=0.0638, v_num=10, val_loss=0.540, val_top1_acc=0.819, val_d_prime=3.230, val_aucroc=0.969, val_mAP=0.874] \n",
      "Epoch 305:   0% 0/7 [00:00<?, ?it/s, loss=0.0631, v_num=10, val_loss=0.540, val_top1_acc=0.819, val_d_prime=3.230, val_aucroc=0.969, val_mAP=0.874]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 305: 100% 7/7 [00:00<00:00, 72.06it/s, loss=0.0638, v_num=10, val_loss=0.551, val_top1_acc=0.829, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.871] \n",
      "Epoch 308:   0% 0/7 [00:00<?, ?it/s, loss=0.0648, v_num=10, val_loss=0.551, val_top1_acc=0.829, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.871]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 308: 100% 7/7 [00:00<00:00, 72.35it/s, loss=0.0651, v_num=10, val_loss=0.551, val_top1_acc=0.814, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.870] \n",
      "Epoch 311:   0% 0/7 [00:00<?, ?it/s, loss=0.0657, v_num=10, val_loss=0.551, val_top1_acc=0.814, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 311: 100% 7/7 [00:00<00:00, 58.62it/s, loss=0.066, v_num=10, val_loss=0.553, val_top1_acc=0.824, val_d_prime=3.160, val_aucroc=0.967, val_mAP=0.869] \n",
      "Epoch 314:   0% 0/7 [00:00<?, ?it/s, loss=0.0671, v_num=10, val_loss=0.553, val_top1_acc=0.824, val_d_prime=3.160, val_aucroc=0.967, val_mAP=0.869]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 314: 100% 7/7 [00:00<00:00, 80.19it/s, loss=0.0679, v_num=10, val_loss=0.580, val_top1_acc=0.804, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.867] \n",
      "Epoch 317:   0% 0/7 [00:00<?, ?it/s, loss=0.0696, v_num=10, val_loss=0.580, val_top1_acc=0.804, val_d_prime=3.180, val_aucroc=0.967, val_mAP=0.867]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 317: 100% 7/7 [00:00<00:00, 78.18it/s, loss=0.0702, v_num=10, val_loss=0.567, val_top1_acc=0.820, val_d_prime=3.150, val_aucroc=0.966, val_mAP=0.865] \n",
      "Epoch 320:   0% 0/7 [00:00<?, ?it/s, loss=0.071, v_num=10, val_loss=0.567, val_top1_acc=0.820, val_d_prime=3.150, val_aucroc=0.966, val_mAP=0.865]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 320: 100% 7/7 [00:00<00:00, 76.30it/s, loss=0.0707, v_num=10, val_loss=0.563, val_top1_acc=0.814, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.870]\n",
      "Epoch 323:   0% 0/7 [00:00<?, ?it/s, loss=0.0701, v_num=10, val_loss=0.563, val_top1_acc=0.814, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.870]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 323: 100% 7/7 [00:00<00:00, 58.44it/s, loss=0.069, v_num=10, val_loss=0.545, val_top1_acc=0.830, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.876] \n",
      "Epoch 326:   0% 0/7 [00:00<?, ?it/s, loss=0.0637, v_num=10, val_loss=0.545, val_top1_acc=0.830, val_d_prime=3.200, val_aucroc=0.968, val_mAP=0.876]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 326: 100% 7/7 [00:00<00:00, 71.99it/s, loss=0.0606, v_num=10, val_loss=0.530, val_top1_acc=0.835, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.876] \n",
      "Epoch 329:   0% 0/7 [00:00<?, ?it/s, loss=0.0558, v_num=10, val_loss=0.530, val_top1_acc=0.835, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.876]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 329: 100% 7/7 [00:00<00:00, 74.80it/s, loss=0.0546, v_num=10, val_loss=0.540, val_top1_acc=0.829, val_d_prime=3.220, val_aucroc=0.970, val_mAP=0.877] \n",
      "Epoch 332:   0% 0/7 [00:00<?, ?it/s, loss=0.0538, v_num=10, val_loss=0.540, val_top1_acc=0.829, val_d_prime=3.220, val_aucroc=0.970, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 332: 100% 7/7 [00:00<00:00, 65.46it/s, loss=0.0535, v_num=10, val_loss=0.536, val_top1_acc=0.830, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.876]\n",
      "Epoch 335:   0% 0/7 [00:00<?, ?it/s, loss=0.0529, v_num=10, val_loss=0.536, val_top1_acc=0.830, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.876]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 335: 100% 7/7 [00:00<00:00, 67.77it/s, loss=0.0527, v_num=10, val_loss=0.531, val_top1_acc=0.833, val_d_prime=3.200, val_aucroc=0.969, val_mAP=0.877] \n",
      "Epoch 338:   0% 0/7 [00:00<?, ?it/s, loss=0.0518, v_num=10, val_loss=0.531, val_top1_acc=0.833, val_d_prime=3.200, val_aucroc=0.969, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 338: 100% 7/7 [00:00<00:00, 77.96it/s, loss=0.0516, v_num=10, val_loss=0.529, val_top1_acc=0.831, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.876] \n",
      "Epoch 341:   0% 0/7 [00:00<?, ?it/s, loss=0.0508, v_num=10, val_loss=0.529, val_top1_acc=0.831, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.876]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 341: 100% 7/7 [00:00<00:00, 76.20it/s, loss=0.0507, v_num=10, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.210, val_aucroc=0.970, val_mAP=0.877] \n",
      "Epoch 344:   0% 0/7 [00:00<?, ?it/s, loss=0.0497, v_num=10, val_loss=0.517, val_top1_acc=0.829, val_d_prime=3.210, val_aucroc=0.970, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 344: 100% 7/7 [00:00<00:00, 72.79it/s, loss=0.0497, v_num=10, val_loss=0.557, val_top1_acc=0.829, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.877] \n",
      "Epoch 347:   0% 0/7 [00:00<?, ?it/s, loss=0.0491, v_num=10, val_loss=0.557, val_top1_acc=0.829, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 347: 100% 7/7 [00:00<00:00, 74.57it/s, loss=0.0487, v_num=10, val_loss=0.544, val_top1_acc=0.834, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.879] \n",
      "Epoch 350:   0% 0/7 [00:00<?, ?it/s, loss=0.0483, v_num=10, val_loss=0.544, val_top1_acc=0.834, val_d_prime=3.220, val_aucroc=0.969, val_mAP=0.879]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 350: 100% 7/7 [00:00<00:00, 55.34it/s, loss=0.0485, v_num=10, val_loss=0.545, val_top1_acc=0.832, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.877]\n",
      "Epoch 353:   0% 0/7 [00:00<?, ?it/s, loss=0.0487, v_num=10, val_loss=0.545, val_top1_acc=0.832, val_d_prime=3.210, val_aucroc=0.969, val_mAP=0.877]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 353: 100% 7/7 [00:00<00:00, 66.62it/s, loss=0.0484, v_num=10, val_loss=0.548, val_top1_acc=0.833, val_d_prime=3.200, val_aucroc=0.969, val_mAP=0.879] \n",
      "Epoch 353: 100% 7/7 [00:00<00:00, 61.55it/s, loss=0.0484, v_num=10, val_loss=0.548, val_top1_acc=0.833, val_d_prime=3.200, val_aucroc=0.969, val_mAP=0.879]\n",
      "FIT Profiler Report\n",
      "\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                              \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                               \t|  -              \t|  100954         \t|  29.217         \t|  100 %          \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                  \t|  0.080284       \t|  354            \t|  28.421         \t|  97.275         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                  \t|  0.0038292      \t|  1770           \t|  6.7776         \t|  23.198         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                \t|  0.0035143      \t|  1770           \t|  6.2203         \t|  21.29          \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                          \t|  0.031879       \t|  118            \t|  3.7617         \t|  12.875         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                        \t|  0.0014987      \t|  1770           \t|  2.6527         \t|  9.0794         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                 \t|  0.014903       \t|  118            \t|  1.7585         \t|  6.019          \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                             \t|  0.00084921     \t|  1770           \t|  1.5031         \t|  5.1446         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                  \t|  0.00031222     \t|  1770           \t|  0.55262        \t|  1.8915         \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                \t|  0.00018363     \t|  1770           \t|  0.32502        \t|  1.1124         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                      \t|  9.9301e-05     \t|  2006           \t|  0.1992         \t|  0.68179        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                           \t|  0.00010619     \t|  1770           \t|  0.18795        \t|  0.64331        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                      \t|  0.00064095     \t|  236            \t|  0.15127        \t|  0.51773        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                        \t|  0.00036277     \t|  354            \t|  0.12842        \t|  0.43954        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                      \t|  0.00024587     \t|  354            \t|  0.087039       \t|  0.29791        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                         \t|  0.0005859      \t|  118            \t|  0.069136       \t|  0.23663        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                 \t|  0.00047805     \t|  118            \t|  0.05641        \t|  0.19307        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                   \t|  0.00016506     \t|  236            \t|  0.038953       \t|  0.13332        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                 \t|  0.00014104     \t|  236            \t|  0.033286       \t|  0.11393        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                       \t|  0.00025226     \t|  118            \t|  0.029767       \t|  0.10188        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                 \t|  6.8373e-06     \t|  1770           \t|  0.012102       \t|  0.041422       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                     \t|  8.3097e-05     \t|  118            \t|  0.0098055      \t|  0.033561       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                \t|  2.6624e-05     \t|  354            \t|  0.0094248      \t|  0.032258       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                               \t|  5.321e-06      \t|  1770           \t|  0.0094182      \t|  0.032235       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                    \t|  5.1777e-06     \t|  1770           \t|  0.0091646      \t|  0.031367       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                      \t|  7.393e-05      \t|  118            \t|  0.0087238      \t|  0.029859       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                      \t|  4.6222e-06     \t|  1770           \t|  0.0081813      \t|  0.028002       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                \t|  4.4009e-06     \t|  1770           \t|  0.0077897      \t|  0.026662       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                 \t|  4.2533e-06     \t|  1770           \t|  0.0075284      \t|  0.025767       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step          \t|  4.1645e-06     \t|  1770           \t|  0.0073711      \t|  0.025229       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                          \t|  4.1131e-06     \t|  1770           \t|  0.0072802      \t|  0.024918       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                         \t|  4.0877e-06     \t|  1770           \t|  0.0072353      \t|  0.024764       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                           \t|  3.9419e-06     \t|  1770           \t|  0.0069772      \t|  0.023881       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                            \t|  3.8655e-06     \t|  1770           \t|  0.006842       \t|  0.023418       \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                            \t|  3.8357e-06     \t|  1770           \t|  0.0067892      \t|  0.023237       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                       \t|  3.7767e-06     \t|  1770           \t|  0.0066848      \t|  0.02288        \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                              \t|  3.7045e-06     \t|  1770           \t|  0.006557       \t|  0.022443       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                  \t|  3.7036e-06     \t|  1770           \t|  0.0065554      \t|  0.022437       \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                               \t|  3.6962e-06     \t|  1770           \t|  0.0065423      \t|  0.022392       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                      \t|  3.6785e-06     \t|  1770           \t|  0.006511       \t|  0.022285       \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                 \t|  3.6606e-06     \t|  1770           \t|  0.0064793      \t|  0.022177       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                    \t|  3.6433e-06     \t|  1770           \t|  0.0064486      \t|  0.022072       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad               \t|  3.6266e-06     \t|  1770           \t|  0.0064191      \t|  0.021971       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                    \t|  3.6178e-06     \t|  1770           \t|  0.0064035      \t|  0.021917       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                        \t|  3.5966e-06     \t|  1770           \t|  0.006366       \t|  0.021789       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                          \t|  3.5939e-06     \t|  1770           \t|  0.0063611      \t|  0.021772       \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                     \t|  3.5854e-06     \t|  1770           \t|  0.0063462      \t|  0.021721       \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                           \t|  3.5256e-06     \t|  1770           \t|  0.0062404      \t|  0.021359       \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                          \t|  3.4934e-06     \t|  1770           \t|  0.0061833      \t|  0.021163       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                \t|  3.4855e-06     \t|  1770           \t|  0.0061693      \t|  0.021116       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                              \t|  3.4796e-06     \t|  1770           \t|  0.0061589      \t|  0.02108        \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                \t|  3.4647e-06     \t|  1770           \t|  0.0061325      \t|  0.02099        \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                         \t|  3.3913e-06     \t|  1770           \t|  0.0060025      \t|  0.020545       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                           \t|  1.2005e-05     \t|  354            \t|  0.0042498      \t|  0.014546       \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                             \t|  2.038e-06      \t|  1770           \t|  0.0036073      \t|  0.012347       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                        \t|  9.9214e-06     \t|  354            \t|  0.0035122      \t|  0.012021       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                            \t|  1.9214e-06     \t|  1770           \t|  0.0034009      \t|  0.01164        \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                          \t|  1.8806e-06     \t|  1770           \t|  0.0033286      \t|  0.011393       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                         \t|  9.3971e-06     \t|  354            \t|  0.0033266      \t|  0.011386       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                             \t|  1.8703e-06     \t|  1770           \t|  0.0033105      \t|  0.011331       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                            \t|  1.8269e-06     \t|  1770           \t|  0.0032337      \t|  0.011068       \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                    \t|  1.5399e-06     \t|  1770           \t|  0.0027257      \t|  0.0093292      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                           \t|  1.4968e-06     \t|  1770           \t|  0.0026494      \t|  0.0090681      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                 \t|  1.4461e-06     \t|  1770           \t|  0.0025596      \t|  0.0087608      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                      \t|  1.4234e-06     \t|  1770           \t|  0.0025195      \t|  0.0086235      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                    \t|  4.437e-06      \t|  472            \t|  0.0020943      \t|  0.0071681      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                      \t|  4.1003e-06     \t|  472            \t|  0.0019353      \t|  0.006624       \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                      \t|  8.0848e-06     \t|  236            \t|  0.001908       \t|  0.0065305      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                \t|  5.3005e-06     \t|  354            \t|  0.0018764      \t|  0.0064223      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                    \t|  7.3911e-06     \t|  236            \t|  0.0017443      \t|  0.0059702      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                            \t|  3.6912e-06     \t|  472            \t|  0.0017423      \t|  0.0059632      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                              \t|  3.6091e-06     \t|  472            \t|  0.0017035      \t|  0.0058305      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                    \t|  3.5567e-06     \t|  472            \t|  0.0016788      \t|  0.0057459      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                               \t|  3.4633e-06     \t|  472            \t|  0.0016347      \t|  0.005595       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                      \t|  3.4177e-06     \t|  472            \t|  0.0016132      \t|  0.0055213      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                \t|  3.4166e-06     \t|  472            \t|  0.0016126      \t|  0.0055195      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                 \t|  3.4012e-06     \t|  472            \t|  0.0016054      \t|  0.0054947      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                              \t|  3.3635e-06     \t|  472            \t|  0.0015876      \t|  0.0054337      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                          \t|  4.1193e-06     \t|  354            \t|  0.0014582      \t|  0.004991       \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                            \t|  1.1914e-05     \t|  118            \t|  0.0014059      \t|  0.0048118      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start              \t|  3.9278e-06     \t|  354            \t|  0.0013904      \t|  0.004759       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                              \t|  3.7164e-06     \t|  354            \t|  0.0013156      \t|  0.0045029      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                         \t|  5.4429e-06     \t|  236            \t|  0.0012845      \t|  0.0043965      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                           \t|  4.8364e-06     \t|  236            \t|  0.0011414      \t|  0.0039066      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                          \t|  9.068e-06      \t|  118            \t|  0.00107        \t|  0.0036623      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                     \t|  4.5051e-06     \t|  236            \t|  0.0010632      \t|  0.003639       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end           \t|  4.3951e-06     \t|  236            \t|  0.0010373      \t|  0.0035502      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                   \t|  4.3066e-06     \t|  236            \t|  0.0010164      \t|  0.0034787      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start         \t|  3.6971e-06     \t|  236            \t|  0.00087253     \t|  0.0029864      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                               \t|  6.4351e-06     \t|  118            \t|  0.00075934     \t|  0.002599       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                \t|  1.5615e-06     \t|  472            \t|  0.00073704     \t|  0.0025227      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                           \t|  6.1465e-06     \t|  118            \t|  0.00072528     \t|  0.0024824      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                  \t|  1.4121e-06     \t|  472            \t|  0.00066652     \t|  0.0022813      \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                           \t|  2.6976e-06     \t|  236            \t|  0.00063664     \t|  0.002179       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                            \t|  1.7823e-06     \t|  354            \t|  0.00063094     \t|  0.0021595      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                          \t|  1.6456e-06     \t|  354            \t|  0.00058255     \t|  0.0019939      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                 \t|  0.00055085     \t|  1              \t|  0.00055085     \t|  0.0018854      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                           \t|  4.5005e-06     \t|  118            \t|  0.00053106     \t|  0.0018177      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                      \t|  4.2229e-06     \t|  118            \t|  0.00049831     \t|  0.0017055      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                   \t|  4.0721e-06     \t|  118            \t|  0.00048051     \t|  0.0016446      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                         \t|  3.9355e-06     \t|  118            \t|  0.00046439     \t|  0.0015895      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                         \t|  3.8449e-06     \t|  118            \t|  0.0004537      \t|  0.0015529      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                     \t|  3.6615e-06     \t|  118            \t|  0.00043206     \t|  0.0014788      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                       \t|  1.821e-06      \t|  236            \t|  0.00042975     \t|  0.0014709      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start               \t|  3.6096e-06     \t|  118            \t|  0.00042594     \t|  0.0014578      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                 \t|  3.6049e-06     \t|  118            \t|  0.00042537     \t|  0.0014559      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end           \t|  3.5686e-06     \t|  118            \t|  0.0004211      \t|  0.0014413      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start         \t|  3.4044e-06     \t|  118            \t|  0.00040172     \t|  0.001375       \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                    \t|  3.2194e-06     \t|  118            \t|  0.00037989     \t|  0.0013002      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                   \t|  3.2065e-06     \t|  118            \t|  0.00037836     \t|  0.001295       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                     \t|  1.5798e-06     \t|  236            \t|  0.00037283     \t|  0.0012761      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                  \t|  1.5425e-06     \t|  236            \t|  0.00036402     \t|  0.0012459      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                             \t|  2.8808e-06     \t|  118            \t|  0.00033993     \t|  0.0011635      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                \t|  6.9074e-06     \t|  39             \t|  0.00026939     \t|  0.00092203     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                    \t|  2.1144e-06     \t|  118            \t|  0.0002495      \t|  0.00085396     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                           \t|  1.9173e-06     \t|  118            \t|  0.00022624     \t|  0.00077435     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                     \t|  1.6679e-06     \t|  118            \t|  0.00019681     \t|  0.00067363     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                       \t|  1.6528e-06     \t|  118            \t|  0.00019503     \t|  0.00066752     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                  \t|  1.6046e-06     \t|  118            \t|  0.00018935     \t|  0.00064808     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                              \t|  0.00018395     \t|  1              \t|  0.00018395     \t|  0.00062962     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                            \t|  0.00018018     \t|  1              \t|  0.00018018     \t|  0.00061671     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                        \t|  4.5089e-06     \t|  39             \t|  0.00017585     \t|  0.00060187     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                              \t|  0.00017563     \t|  1              \t|  0.00017563     \t|  0.00060113     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                \t|  3.8177e-06     \t|  39             \t|  0.00014889     \t|  0.00050961     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                          \t|  3.5898e-06     \t|  39             \t|  0.00014        \t|  0.00047918     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                           \t|  3.5094e-06     \t|  39             \t|  0.00013687     \t|  0.00046846     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                          \t|  9.0617e-05     \t|  1              \t|  9.0617e-05     \t|  0.00031015     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                            \t|  1.8697e-06     \t|  39             \t|  7.292e-05      \t|  0.00024958     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                             \t|  1.5511e-05     \t|  1              \t|  1.5511e-05     \t|  5.3089e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                  \t|  1.4202e-05     \t|  1              \t|  1.4202e-05     \t|  4.8609e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                \t|  1.1499e-05     \t|  1              \t|  1.1499e-05     \t|  3.9357e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                               \t|  8.848e-06      \t|  1              \t|  8.848e-06      \t|  3.0284e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                 \t|  8.111e-06      \t|  1              \t|  8.111e-06      \t|  2.7761e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                        \t|  8.022e-06      \t|  1              \t|  8.022e-06      \t|  2.7457e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                     \t|  6.355e-06      \t|  1              \t|  6.355e-06      \t|  2.1751e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                      \t|  6.041e-06      \t|  1              \t|  6.041e-06      \t|  2.0676e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                         \t|  6.032e-06      \t|  1              \t|  6.032e-06      \t|  2.0646e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                          \t|  5.581e-06      \t|  1              \t|  5.581e-06      \t|  1.9102e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                \t|  5.374e-06      \t|  1              \t|  5.374e-06      \t|  1.8394e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                \t|  5.326e-06      \t|  1              \t|  5.326e-06      \t|  1.8229e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                    \t|  5.322e-06      \t|  1              \t|  5.322e-06      \t|  1.8216e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                               \t|  4.989e-06      \t|  1              \t|  4.989e-06      \t|  1.7076e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                      \t|  4.977e-06      \t|  1              \t|  4.977e-06      \t|  1.7035e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                      \t|  4.647e-06      \t|  1              \t|  4.647e-06      \t|  1.5905e-05     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                   \t|  4.609e-06      \t|  1              \t|  4.609e-06      \t|  1.5775e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                        \t|  4.593e-06      \t|  1              \t|  4.593e-06      \t|  1.572e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                  \t|  4.523e-06      \t|  1              \t|  4.523e-06      \t|  1.5481e-05     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                     \t|  4.47e-06       \t|  1              \t|  4.47e-06       \t|  1.5299e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                          \t|  4.407e-06      \t|  1              \t|  4.407e-06      \t|  1.5084e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                    \t|  4.351e-06      \t|  1              \t|  4.351e-06      \t|  1.4892e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                           \t|  4.313e-06      \t|  1              \t|  4.313e-06      \t|  1.4762e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                      \t|  4.021e-06      \t|  1              \t|  4.021e-06      \t|  1.3763e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                        \t|  3.947e-06      \t|  1              \t|  3.947e-06      \t|  1.3509e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                    \t|  3.887e-06      \t|  1              \t|  3.887e-06      \t|  1.3304e-05     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                          \t|  3.763e-06      \t|  1              \t|  3.763e-06      \t|  1.288e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                       \t|  3.66e-06       \t|  1              \t|  3.66e-06       \t|  1.2527e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                         \t|  3.579e-06      \t|  1              \t|  3.579e-06      \t|  1.225e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                 \t|  3.525e-06      \t|  1              \t|  3.525e-06      \t|  1.2065e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                              \t|  3.469e-06      \t|  1              \t|  3.469e-06      \t|  1.1873e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup\t|  3.398e-06      \t|  1              \t|  3.398e-06      \t|  1.163e-05      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                              \t|  3.212e-06      \t|  1              \t|  3.212e-06      \t|  1.0994e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                \t|  3.206e-06      \t|  1              \t|  3.206e-06      \t|  1.0973e-05     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                        \t|  3.173e-06      \t|  1              \t|  3.173e-06      \t|  1.086e-05      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start         \t|  3.007e-06      \t|  1              \t|  3.007e-06      \t|  1.0292e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                             \t|  2.99e-06       \t|  1              \t|  2.99e-06       \t|  1.0234e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                   \t|  2.959e-06      \t|  1              \t|  2.959e-06      \t|  1.0128e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                       \t|  2.945e-06      \t|  1              \t|  2.945e-06      \t|  1.008e-05      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                           \t|  2.888e-06      \t|  1              \t|  2.888e-06      \t|  9.8847e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                  \t|  2.884e-06      \t|  1              \t|  2.884e-06      \t|  9.871e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                  \t|  2.837e-06      \t|  1              \t|  2.837e-06      \t|  9.7102e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model        \t|  2.799e-06      \t|  1              \t|  2.799e-06      \t|  9.5801e-06     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                    \t|  2.78e-06       \t|  1              \t|  2.78e-06       \t|  9.5151e-06     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                   \t|  2.772e-06      \t|  1              \t|  2.772e-06      \t|  9.4877e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end           \t|  2.735e-06      \t|  1              \t|  2.735e-06      \t|  9.361e-06      \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                      \t|  2.717e-06      \t|  1              \t|  2.717e-06      \t|  9.2994e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                   \t|  2.682e-06      \t|  1              \t|  2.682e-06      \t|  9.1796e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                     \t|  2.668e-06      \t|  1              \t|  2.668e-06      \t|  9.1317e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                      \t|  2.655e-06      \t|  1              \t|  2.655e-06      \t|  9.0872e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                           \t|  2.478e-06      \t|  1              \t|  2.478e-06      \t|  8.4814e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                  \t|  2.122e-06      \t|  1              \t|  2.122e-06      \t|  7.2629e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                         \t|  2.109e-06      \t|  1              \t|  2.109e-06      \t|  7.2184e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                       \t|  2.022e-06      \t|  1              \t|  2.022e-06      \t|  6.9207e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                    \t|  1.977e-06      \t|  1              \t|  1.977e-06      \t|  6.7667e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                         \t|  1.936e-06      \t|  1              \t|  1.936e-06      \t|  6.6263e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                \t|  1.506e-06      \t|  1              \t|  1.506e-06      \t|  5.1546e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                  \t|  1.473e-06      \t|  1              \t|  1.473e-06      \t|  5.0416e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                     \t|  1.431e-06      \t|  1              \t|  1.431e-06      \t|  4.8979e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                       \t|  1.261e-06      \t|  1              \t|  1.261e-06      \t|  4.316e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                       \t|  1.009e-06      \t|  1              \t|  1.009e-06      \t|  3.4535e-06     \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "predict - mridangam_stroke - 2022-06-03 21:10:33,967 - 967 - Validation Score for the Training Split: 0.8365591168403625\n",
      "\n",
      "split: 3it [01:40, 32.50s/it]\u001B[Apredict - mridangam_stroke - 2022-06-03 21:10:33,967 - 967 - Training split 5 of 5: {'train': ['fold01', 'fold02', 'fold03'], 'valid': ['fold00'], 'test': ['fold04']}\n",
      "/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "==========================================================================================\n",
      "Layer (type:depth-idx)                   Output Shape              Param #\n",
      "==========================================================================================\n",
      "FullyConnectedPrediction                 [64, 6]                   --\n",
      "├─Sequential: 1-1                        [64, 1024]                --\n",
      "│    └─Linear: 2-1                       [64, 1024]                1,049,600\n",
      "│    └─BatchNorm1d: 2-2                  [64, 1024]                2,048\n",
      "│    └─Dropout: 2-3                      [64, 1024]                --\n",
      "│    └─ReLU: 2-4                         [64, 1024]                --\n",
      "├─Linear: 1-2                            [64, 6]                   6,150\n",
      "├─Softmax: 1-3                           [64, 6]                   --\n",
      "├─OneHotToCrossEntropyLoss: 1-4          --                        --\n",
      "│    └─CrossEntropyLoss: 2-5             --                        --\n",
      "==========================================================================================\n",
      "Total params: 1,057,798\n",
      "Trainable params: 1,057,798\n",
      "Non-trainable params: 0\n",
      "Total mult-adds (M): 67.70\n",
      "==========================================================================================\n",
      "Input size (MB): 0.26\n",
      "Forward/backward pass size (MB): 1.05\n",
      "Params size (MB): 4.23\n",
      "Estimated Total Size (MB): 5.55\n",
      "==========================================================================================\n",
      "GPU available: True, used: True\n",
      "TPU available: False, using: 0 TPU cores\n",
      "IPU available: False, using: 0 IPUs\n",
      "HPU available: False, using: 0 HPUs\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 76374.47it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 26571.65it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 114470.67it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 28399.32it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 79578.03it/s]\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 27119.48it/s]\n",
      "Getting embeddings for split ['fold01', 'fold02', 'fold03'], which has 4186 instances.\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 81070.67it/s]\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 26063.99it/s]\n",
      "Getting embeddings for split ['fold00'], which has 1396 instances.\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "\n",
      "  | Name      | Type                     | Params\n",
      "-------------------------------------------------------\n",
      "0 | layernorm | Identity                 | 0     \n",
      "1 | predictor | FullyConnectedPrediction | 1.1 M \n",
      "-------------------------------------------------------\n",
      "1.1 M     Trainable params\n",
      "0         Non-trainable params\n",
      "1.1 M     Total params\n",
      "4.231     Total estimated model params size (MB)\n",
      "/usr/local/lib/python3.7/dist-packages/pytorch_lightning/trainer/trainer.py:1937: PossibleUserWarning: The number of training batches (5) is smaller than the logging interval Trainer(log_every_n_steps=50). Set a lower value for log_every_n_steps if you want to see logs for the training epoch.\n",
      "  category=PossibleUserWarning,\n",
      "Epoch 0:   0% 0/5 [00:00<?, ?it/s] /usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Epoch 2:   0% 0/7 [00:00<?, ?it/s, loss=1.78, v_num=11]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Epoch 2: 100% 7/7 [00:00<00:00, 93.02it/s, loss=1.78, v_num=11]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Epoch 2: 100% 7/7 [00:00<00:00, 58.79it/s, loss=1.65, v_num=11, val_loss=1.560, val_top1_acc=0.335, val_d_prime=1.090, val_aucroc=0.768, val_mAP=0.424]\n",
      "Epoch 5:   0% 0/7 [00:00<?, ?it/s, loss=1.36, v_num=11, val_loss=1.560, val_top1_acc=0.335, val_d_prime=1.090, val_aucroc=0.768, val_mAP=0.424]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 5: 100% 7/7 [00:00<00:00, 79.88it/s, loss=1.24, v_num=11, val_loss=1.250, val_top1_acc=0.502, val_d_prime=1.620, val_aucroc=0.852, val_mAP=0.567] \n",
      "Epoch 8:   0% 0/7 [00:00<?, ?it/s, loss=1.08, v_num=11, val_loss=1.250, val_top1_acc=0.502, val_d_prime=1.620, val_aucroc=0.852, val_mAP=0.567]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 8: 100% 7/7 [00:00<00:00, 80.61it/s, loss=1.03, v_num=11, val_loss=1.040, val_top1_acc=0.598, val_d_prime=1.960, val_aucroc=0.889, val_mAP=0.649] \n",
      "Epoch 11:   0% 0/7 [00:00<?, ?it/s, loss=0.935, v_num=11, val_loss=1.040, val_top1_acc=0.598, val_d_prime=1.960, val_aucroc=0.889, val_mAP=0.649]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 11: 100% 7/7 [00:00<00:00, 65.57it/s, loss=0.89, v_num=11, val_loss=0.948, val_top1_acc=0.632, val_d_prime=2.130, val_aucroc=0.904, val_mAP=0.685] \n",
      "Epoch 14:   0% 0/7 [00:00<?, ?it/s, loss=0.823, v_num=11, val_loss=0.948, val_top1_acc=0.632, val_d_prime=2.130, val_aucroc=0.904, val_mAP=0.685]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 14: 100% 7/7 [00:00<00:00, 56.53it/s, loss=0.795, v_num=11, val_loss=0.865, val_top1_acc=0.667, val_d_prime=2.280, val_aucroc=0.918, val_mAP=0.719]\n",
      "Epoch 17:   0% 0/7 [00:00<?, ?it/s, loss=0.75, v_num=11, val_loss=0.865, val_top1_acc=0.667, val_d_prime=2.280, val_aucroc=0.918, val_mAP=0.719]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 17: 100% 7/7 [00:00<00:00, 67.18it/s, loss=0.724, v_num=11, val_loss=0.819, val_top1_acc=0.698, val_d_prime=2.390, val_aucroc=0.925, val_mAP=0.738]\n",
      "Epoch 20:   0% 0/7 [00:00<?, ?it/s, loss=0.683, v_num=11, val_loss=0.819, val_top1_acc=0.698, val_d_prime=2.390, val_aucroc=0.925, val_mAP=0.738]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 20: 100% 7/7 [00:00<00:00, 22.87it/s, loss=0.663, v_num=11, val_loss=0.788, val_top1_acc=0.696, val_d_prime=2.460, val_aucroc=0.931, val_mAP=0.748]\n",
      "Epoch 23:   0% 0/7 [00:00<?, ?it/s, loss=0.629, v_num=11, val_loss=0.788, val_top1_acc=0.696, val_d_prime=2.460, val_aucroc=0.931, val_mAP=0.748]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 23: 100% 7/7 [00:00<00:00, 76.83it/s, loss=0.613, v_num=11, val_loss=0.750, val_top1_acc=0.719, val_d_prime=2.560, val_aucroc=0.936, val_mAP=0.764] \n",
      "Epoch 26:   0% 0/7 [00:00<?, ?it/s, loss=0.587, v_num=11, val_loss=0.750, val_top1_acc=0.719, val_d_prime=2.560, val_aucroc=0.936, val_mAP=0.764]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 26: 100% 7/7 [00:00<00:00, 79.85it/s, loss=0.574, v_num=11, val_loss=0.721, val_top1_acc=0.734, val_d_prime=2.600, val_aucroc=0.939, val_mAP=0.775] \n",
      "Epoch 29:   0% 0/7 [00:00<?, ?it/s, loss=0.549, v_num=11, val_loss=0.721, val_top1_acc=0.734, val_d_prime=2.600, val_aucroc=0.939, val_mAP=0.775]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 29: 100% 7/7 [00:00<00:00, 69.11it/s, loss=0.536, v_num=11, val_loss=0.700, val_top1_acc=0.737, val_d_prime=2.660, val_aucroc=0.942, val_mAP=0.784]\n",
      "Epoch 32:   0% 0/7 [00:00<?, ?it/s, loss=0.514, v_num=11, val_loss=0.700, val_top1_acc=0.737, val_d_prime=2.660, val_aucroc=0.942, val_mAP=0.784]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 32: 100% 7/7 [00:00<00:00, 71.35it/s, loss=0.503, v_num=11, val_loss=0.679, val_top1_acc=0.746, val_d_prime=2.700, val_aucroc=0.944, val_mAP=0.791] \n",
      "Epoch 35:   0% 0/7 [00:00<?, ?it/s, loss=0.481, v_num=11, val_loss=0.679, val_top1_acc=0.746, val_d_prime=2.700, val_aucroc=0.944, val_mAP=0.791]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 35: 100% 7/7 [00:00<00:00, 66.42it/s, loss=0.474, v_num=11, val_loss=0.661, val_top1_acc=0.751, val_d_prime=2.730, val_aucroc=0.946, val_mAP=0.798]\n",
      "Epoch 38:   0% 0/7 [00:00<?, ?it/s, loss=0.457, v_num=11, val_loss=0.661, val_top1_acc=0.751, val_d_prime=2.730, val_aucroc=0.946, val_mAP=0.798]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 38: 100% 7/7 [00:00<00:00, 80.09it/s, loss=0.448, v_num=11, val_loss=0.650, val_top1_acc=0.756, val_d_prime=2.750, val_aucroc=0.947, val_mAP=0.801] \n",
      "Epoch 41:   0% 0/7 [00:00<?, ?it/s, loss=0.431, v_num=11, val_loss=0.650, val_top1_acc=0.756, val_d_prime=2.750, val_aucroc=0.947, val_mAP=0.801]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 41: 100% 7/7 [00:00<00:00, 81.42it/s, loss=0.423, v_num=11, val_loss=0.639, val_top1_acc=0.762, val_d_prime=2.760, val_aucroc=0.948, val_mAP=0.805] \n",
      "Epoch 44:   0% 0/7 [00:00<?, ?it/s, loss=0.413, v_num=11, val_loss=0.639, val_top1_acc=0.762, val_d_prime=2.760, val_aucroc=0.948, val_mAP=0.805]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 44: 100% 7/7 [00:00<00:00, 77.94it/s, loss=0.408, v_num=11, val_loss=0.628, val_top1_acc=0.758, val_d_prime=2.790, val_aucroc=0.950, val_mAP=0.808] \n",
      "Epoch 47:   0% 0/7 [00:00<?, ?it/s, loss=0.395, v_num=11, val_loss=0.628, val_top1_acc=0.758, val_d_prime=2.790, val_aucroc=0.950, val_mAP=0.808]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 47: 100% 7/7 [00:00<00:00, 60.72it/s, loss=0.389, v_num=11, val_loss=0.627, val_top1_acc=0.759, val_d_prime=2.800, val_aucroc=0.950, val_mAP=0.808]\n",
      "Epoch 50:   0% 0/7 [00:00<?, ?it/s, loss=0.38, v_num=11, val_loss=0.627, val_top1_acc=0.759, val_d_prime=2.800, val_aucroc=0.950, val_mAP=0.808]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 50: 100% 7/7 [00:00<00:00, 73.70it/s, loss=0.375, v_num=11, val_loss=0.612, val_top1_acc=0.764, val_d_prime=2.830, val_aucroc=0.951, val_mAP=0.816]\n",
      "Epoch 53:   0% 0/7 [00:00<?, ?it/s, loss=0.363, v_num=11, val_loss=0.612, val_top1_acc=0.764, val_d_prime=2.830, val_aucroc=0.951, val_mAP=0.816]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 53: 100% 7/7 [00:00<00:00, 79.73it/s, loss=0.355, v_num=11, val_loss=0.611, val_top1_acc=0.771, val_d_prime=2.840, val_aucroc=0.952, val_mAP=0.817] \n",
      "Epoch 56:   0% 0/7 [00:00<?, ?it/s, loss=0.347, v_num=11, val_loss=0.611, val_top1_acc=0.771, val_d_prime=2.840, val_aucroc=0.952, val_mAP=0.817]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 56: 100% 7/7 [00:00<00:00, 72.65it/s, loss=0.344, v_num=11, val_loss=0.608, val_top1_acc=0.771, val_d_prime=2.860, val_aucroc=0.953, val_mAP=0.820] \n",
      "Epoch 59:   0% 0/7 [00:00<?, ?it/s, loss=0.336, v_num=11, val_loss=0.608, val_top1_acc=0.771, val_d_prime=2.860, val_aucroc=0.953, val_mAP=0.820]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 59: 100% 7/7 [00:00<00:00, 22.31it/s, loss=0.332, v_num=11, val_loss=0.608, val_top1_acc=0.768, val_d_prime=2.850, val_aucroc=0.952, val_mAP=0.817]\n",
      "Epoch 62:   0% 0/7 [00:00<?, ?it/s, loss=0.324, v_num=11, val_loss=0.608, val_top1_acc=0.768, val_d_prime=2.850, val_aucroc=0.952, val_mAP=0.817]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 62: 100% 7/7 [00:00<00:00, 81.27it/s, loss=0.321, v_num=11, val_loss=0.586, val_top1_acc=0.771, val_d_prime=2.860, val_aucroc=0.954, val_mAP=0.824] \n",
      "Epoch 65:   0% 0/7 [00:00<?, ?it/s, loss=0.314, v_num=11, val_loss=0.586, val_top1_acc=0.771, val_d_prime=2.860, val_aucroc=0.954, val_mAP=0.824]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 65: 100% 7/7 [00:00<00:00, 79.61it/s, loss=0.311, v_num=11, val_loss=0.579, val_top1_acc=0.774, val_d_prime=2.880, val_aucroc=0.955, val_mAP=0.829] \n",
      "Epoch 68:   0% 0/7 [00:00<?, ?it/s, loss=0.304, v_num=11, val_loss=0.579, val_top1_acc=0.774, val_d_prime=2.880, val_aucroc=0.955, val_mAP=0.829]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 68: 100% 7/7 [00:00<00:00, 63.85it/s, loss=0.301, v_num=11, val_loss=0.575, val_top1_acc=0.776, val_d_prime=2.900, val_aucroc=0.956, val_mAP=0.831]\n",
      "Epoch 71:   0% 0/7 [00:00<?, ?it/s, loss=0.291, v_num=11, val_loss=0.575, val_top1_acc=0.776, val_d_prime=2.900, val_aucroc=0.956, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 71: 100% 7/7 [00:00<00:00, 60.45it/s, loss=0.287, v_num=11, val_loss=0.577, val_top1_acc=0.777, val_d_prime=2.900, val_aucroc=0.956, val_mAP=0.831]\n",
      "Epoch 74:   0% 0/7 [00:00<?, ?it/s, loss=0.282, v_num=11, val_loss=0.577, val_top1_acc=0.777, val_d_prime=2.900, val_aucroc=0.956, val_mAP=0.831]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 74: 100% 7/7 [00:00<00:00, 63.80it/s, loss=0.278, v_num=11, val_loss=0.574, val_top1_acc=0.782, val_d_prime=2.920, val_aucroc=0.956, val_mAP=0.832] \n",
      "Epoch 77:   0% 0/7 [00:00<?, ?it/s, loss=0.269, v_num=11, val_loss=0.574, val_top1_acc=0.782, val_d_prime=2.920, val_aucroc=0.956, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 77: 100% 7/7 [00:00<00:00, 75.92it/s, loss=0.266, v_num=11, val_loss=0.578, val_top1_acc=0.780, val_d_prime=2.910, val_aucroc=0.956, val_mAP=0.829] \n",
      "Epoch 80:   0% 0/7 [00:00<?, ?it/s, loss=0.26, v_num=11, val_loss=0.578, val_top1_acc=0.780, val_d_prime=2.910, val_aucroc=0.956, val_mAP=0.829]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 80: 100% 7/7 [00:00<00:00, 74.17it/s, loss=0.258, v_num=11, val_loss=0.570, val_top1_acc=0.781, val_d_prime=2.920, val_aucroc=0.956, val_mAP=0.832]\n",
      "Epoch 83:   0% 0/7 [00:00<?, ?it/s, loss=0.253, v_num=11, val_loss=0.570, val_top1_acc=0.781, val_d_prime=2.920, val_aucroc=0.956, val_mAP=0.832]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 83: 100% 7/7 [00:00<00:00, 58.65it/s, loss=0.251, v_num=11, val_loss=0.563, val_top1_acc=0.785, val_d_prime=2.930, val_aucroc=0.957, val_mAP=0.834]\n",
      "Epoch 86:   0% 0/7 [00:00<?, ?it/s, loss=0.247, v_num=11, val_loss=0.563, val_top1_acc=0.785, val_d_prime=2.930, val_aucroc=0.957, val_mAP=0.834]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 86: 100% 7/7 [00:00<00:00, 23.19it/s, loss=0.245, v_num=11, val_loss=0.551, val_top1_acc=0.794, val_d_prime=2.940, val_aucroc=0.959, val_mAP=0.840]\n",
      "Epoch 89:   0% 0/7 [00:00<?, ?it/s, loss=0.24, v_num=11, val_loss=0.551, val_top1_acc=0.794, val_d_prime=2.940, val_aucroc=0.959, val_mAP=0.840]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 89: 100% 7/7 [00:00<00:00, 77.68it/s, loss=0.237, v_num=11, val_loss=0.555, val_top1_acc=0.791, val_d_prime=2.950, val_aucroc=0.959, val_mAP=0.842]\n",
      "Epoch 92:   0% 0/7 [00:00<?, ?it/s, loss=0.231, v_num=11, val_loss=0.555, val_top1_acc=0.791, val_d_prime=2.950, val_aucroc=0.959, val_mAP=0.842]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 92: 100% 7/7 [00:00<00:00, 78.13it/s, loss=0.229, v_num=11, val_loss=0.559, val_top1_acc=0.792, val_d_prime=2.950, val_aucroc=0.958, val_mAP=0.837] \n",
      "Epoch 95:   0% 0/7 [00:00<?, ?it/s, loss=0.225, v_num=11, val_loss=0.559, val_top1_acc=0.792, val_d_prime=2.950, val_aucroc=0.958, val_mAP=0.837]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 95: 100% 7/7 [00:00<00:00, 66.74it/s, loss=0.225, v_num=11, val_loss=0.557, val_top1_acc=0.794, val_d_prime=2.940, val_aucroc=0.958, val_mAP=0.839]\n",
      "Epoch 98:   0% 0/7 [00:00<?, ?it/s, loss=0.22, v_num=11, val_loss=0.557, val_top1_acc=0.794, val_d_prime=2.940, val_aucroc=0.958, val_mAP=0.839]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 98: 100% 7/7 [00:00<00:00, 54.82it/s, loss=0.217, v_num=11, val_loss=0.560, val_top1_acc=0.791, val_d_prime=2.960, val_aucroc=0.959, val_mAP=0.838]\n",
      "Epoch 101:   0% 0/7 [00:00<?, ?it/s, loss=0.212, v_num=11, val_loss=0.560, val_top1_acc=0.791, val_d_prime=2.960, val_aucroc=0.959, val_mAP=0.838]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 101: 100% 7/7 [00:00<00:00, 71.54it/s, loss=0.21, v_num=11, val_loss=0.540, val_top1_acc=0.800, val_d_prime=2.970, val_aucroc=0.960, val_mAP=0.847]  \n",
      "Epoch 104:   0% 0/7 [00:00<?, ?it/s, loss=0.207, v_num=11, val_loss=0.540, val_top1_acc=0.800, val_d_prime=2.970, val_aucroc=0.960, val_mAP=0.847]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 104: 100% 7/7 [00:00<00:00, 56.80it/s, loss=0.205, v_num=11, val_loss=0.541, val_top1_acc=0.802, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.844]\n",
      "Epoch 107:   0% 0/7 [00:00<?, ?it/s, loss=0.201, v_num=11, val_loss=0.541, val_top1_acc=0.802, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.844]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 107: 100% 7/7 [00:00<00:00, 65.59it/s, loss=0.199, v_num=11, val_loss=0.546, val_top1_acc=0.797, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.845]\n",
      "Epoch 110:   0% 0/7 [00:00<?, ?it/s, loss=0.194, v_num=11, val_loss=0.546, val_top1_acc=0.797, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.845]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 110: 100% 7/7 [00:00<00:00, 63.53it/s, loss=0.193, v_num=11, val_loss=0.548, val_top1_acc=0.806, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.842] \n",
      "Epoch 113:   0% 0/7 [00:00<?, ?it/s, loss=0.191, v_num=11, val_loss=0.548, val_top1_acc=0.806, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.842]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 113: 100% 7/7 [00:00<00:00, 23.61it/s, loss=0.189, v_num=11, val_loss=0.552, val_top1_acc=0.804, val_d_prime=2.970, val_aucroc=0.960, val_mAP=0.843]\n",
      "Epoch 116:   0% 0/7 [00:00<?, ?it/s, loss=0.185, v_num=11, val_loss=0.552, val_top1_acc=0.804, val_d_prime=2.970, val_aucroc=0.960, val_mAP=0.843]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 116: 100% 7/7 [00:00<00:00, 80.50it/s, loss=0.183, v_num=11, val_loss=0.542, val_top1_acc=0.801, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.847] \n",
      "Epoch 119:   0% 0/7 [00:00<?, ?it/s, loss=0.181, v_num=11, val_loss=0.542, val_top1_acc=0.801, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.847]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 119: 100% 7/7 [00:00<00:00, 62.01it/s, loss=0.178, v_num=11, val_loss=0.545, val_top1_acc=0.803, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.848]\n",
      "Epoch 122:   0% 0/7 [00:00<?, ?it/s, loss=0.175, v_num=11, val_loss=0.545, val_top1_acc=0.803, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 122: 100% 7/7 [00:00<00:00, 69.67it/s, loss=0.174, v_num=11, val_loss=0.547, val_top1_acc=0.801, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.843] \n",
      "Epoch 125:   0% 0/7 [00:00<?, ?it/s, loss=0.172, v_num=11, val_loss=0.547, val_top1_acc=0.801, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.843]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 125: 100% 7/7 [00:00<00:00, 79.61it/s, loss=0.17, v_num=11, val_loss=0.535, val_top1_acc=0.804, val_d_prime=2.960, val_aucroc=0.961, val_mAP=0.848]  \n",
      "Epoch 128:   0% 0/7 [00:00<?, ?it/s, loss=0.167, v_num=11, val_loss=0.535, val_top1_acc=0.804, val_d_prime=2.960, val_aucroc=0.961, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 128: 100% 7/7 [00:00<00:00, 69.80it/s, loss=0.166, v_num=11, val_loss=0.538, val_top1_acc=0.808, val_d_prime=2.980, val_aucroc=0.962, val_mAP=0.849] \n",
      "Epoch 131:   0% 0/7 [00:00<?, ?it/s, loss=0.163, v_num=11, val_loss=0.538, val_top1_acc=0.808, val_d_prime=2.980, val_aucroc=0.962, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 131: 100% 7/7 [00:00<00:00, 58.02it/s, loss=0.162, v_num=11, val_loss=0.542, val_top1_acc=0.806, val_d_prime=2.990, val_aucroc=0.961, val_mAP=0.848]\n",
      "Epoch 134:   0% 0/7 [00:00<?, ?it/s, loss=0.159, v_num=11, val_loss=0.542, val_top1_acc=0.806, val_d_prime=2.990, val_aucroc=0.961, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 134: 100% 7/7 [00:00<00:00, 63.44it/s, loss=0.158, v_num=11, val_loss=0.543, val_top1_acc=0.805, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.846]\n",
      "Epoch 137:   0% 0/7 [00:00<?, ?it/s, loss=0.155, v_num=11, val_loss=0.543, val_top1_acc=0.805, val_d_prime=2.960, val_aucroc=0.960, val_mAP=0.846]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 137: 100% 7/7 [00:00<00:00, 70.89it/s, loss=0.154, v_num=11, val_loss=0.540, val_top1_acc=0.807, val_d_prime=2.970, val_aucroc=0.961, val_mAP=0.847] \n",
      "Epoch 140:   0% 0/7 [00:00<?, ?it/s, loss=0.152, v_num=11, val_loss=0.540, val_top1_acc=0.807, val_d_prime=2.970, val_aucroc=0.961, val_mAP=0.847]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 140: 100% 7/7 [00:00<00:00, 77.75it/s, loss=0.151, v_num=11, val_loss=0.549, val_top1_acc=0.807, val_d_prime=2.970, val_aucroc=0.960, val_mAP=0.846] \n",
      "Epoch 143:   0% 0/7 [00:00<?, ?it/s, loss=0.149, v_num=11, val_loss=0.549, val_top1_acc=0.807, val_d_prime=2.970, val_aucroc=0.960, val_mAP=0.846]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 143: 100% 7/7 [00:00<00:00, 59.23it/s, loss=0.148, v_num=11, val_loss=0.542, val_top1_acc=0.804, val_d_prime=2.990, val_aucroc=0.961, val_mAP=0.848]\n",
      "Epoch 146:   0% 0/7 [00:00<?, ?it/s, loss=0.145, v_num=11, val_loss=0.542, val_top1_acc=0.804, val_d_prime=2.990, val_aucroc=0.961, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 146: 100% 7/7 [00:00<00:00, 69.74it/s, loss=0.143, v_num=11, val_loss=0.544, val_top1_acc=0.806, val_d_prime=2.990, val_aucroc=0.961, val_mAP=0.847]\n",
      "Epoch 149:   0% 0/7 [00:00<?, ?it/s, loss=0.141, v_num=11, val_loss=0.544, val_top1_acc=0.806, val_d_prime=2.990, val_aucroc=0.961, val_mAP=0.847]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 149: 100% 7/7 [00:00<00:00, 60.06it/s, loss=0.14, v_num=11, val_loss=0.535, val_top1_acc=0.809, val_d_prime=2.980, val_aucroc=0.962, val_mAP=0.850] \n",
      "Epoch 152:   0% 0/7 [00:00<?, ?it/s, loss=0.139, v_num=11, val_loss=0.535, val_top1_acc=0.809, val_d_prime=2.980, val_aucroc=0.962, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 152: 100% 7/7 [00:00<00:00, 77.81it/s, loss=0.138, v_num=11, val_loss=0.541, val_top1_acc=0.807, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.850] \n",
      "Epoch 155:   0% 0/7 [00:00<?, ?it/s, loss=0.135, v_num=11, val_loss=0.541, val_top1_acc=0.807, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 155: 100% 7/7 [00:00<00:00, 63.25it/s, loss=0.135, v_num=11, val_loss=0.534, val_top1_acc=0.810, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.851]\n",
      "Epoch 158:   0% 0/7 [00:00<?, ?it/s, loss=0.131, v_num=11, val_loss=0.534, val_top1_acc=0.810, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 158: 100% 7/7 [00:00<00:00, 61.50it/s, loss=0.13, v_num=11, val_loss=0.537, val_top1_acc=0.813, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.851]  \n",
      "Epoch 161:   0% 0/7 [00:00<?, ?it/s, loss=0.129, v_num=11, val_loss=0.537, val_top1_acc=0.813, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 161: 100% 7/7 [00:00<00:00, 70.16it/s, loss=0.128, v_num=11, val_loss=0.538, val_top1_acc=0.810, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.852] \n",
      "Epoch 164:   0% 0/7 [00:00<?, ?it/s, loss=0.126, v_num=11, val_loss=0.538, val_top1_acc=0.810, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.852]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 164: 100% 7/7 [00:00<00:00, 80.53it/s, loss=0.125, v_num=11, val_loss=0.540, val_top1_acc=0.807, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.849] \n",
      "Epoch 167:   0% 0/7 [00:00<?, ?it/s, loss=0.124, v_num=11, val_loss=0.540, val_top1_acc=0.807, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 167: 100% 7/7 [00:00<00:00, 59.15it/s, loss=0.123, v_num=11, val_loss=0.532, val_top1_acc=0.809, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.854]\n",
      "Epoch 170:   0% 0/7 [00:00<?, ?it/s, loss=0.121, v_num=11, val_loss=0.532, val_top1_acc=0.809, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.854]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 170: 100% 7/7 [00:00<00:00, 65.75it/s, loss=0.12, v_num=11, val_loss=0.541, val_top1_acc=0.809, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.850]  \n",
      "Epoch 173:   0% 0/7 [00:00<?, ?it/s, loss=0.119, v_num=11, val_loss=0.541, val_top1_acc=0.809, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 173: 100% 7/7 [00:00<00:00, 80.35it/s, loss=0.118, v_num=11, val_loss=0.539, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.853] \n",
      "Epoch 176:   0% 0/7 [00:00<?, ?it/s, loss=0.116, v_num=11, val_loss=0.539, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.853]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 176: 100% 7/7 [00:00<00:00, 71.62it/s, loss=0.116, v_num=11, val_loss=0.544, val_top1_acc=0.813, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.851] \n",
      "Epoch 179:   0% 0/7 [00:00<?, ?it/s, loss=0.114, v_num=11, val_loss=0.544, val_top1_acc=0.813, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 179: 100% 7/7 [00:00<00:00, 67.98it/s, loss=0.113, v_num=11, val_loss=0.554, val_top1_acc=0.804, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.848]\n",
      "Epoch 182:   0% 0/7 [00:00<?, ?it/s, loss=0.112, v_num=11, val_loss=0.554, val_top1_acc=0.804, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.848]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 182: 100% 7/7 [00:00<00:00, 61.37it/s, loss=0.112, v_num=11, val_loss=0.532, val_top1_acc=0.808, val_d_prime=3.010, val_aucroc=0.963, val_mAP=0.855] \n",
      "Epoch 185:   0% 0/7 [00:00<?, ?it/s, loss=0.109, v_num=11, val_loss=0.532, val_top1_acc=0.808, val_d_prime=3.010, val_aucroc=0.963, val_mAP=0.855]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 185: 100% 7/7 [00:00<00:00, 58.58it/s, loss=0.108, v_num=11, val_loss=0.542, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.851]\n",
      "Epoch 188:   0% 0/7 [00:00<?, ?it/s, loss=0.107, v_num=11, val_loss=0.542, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 188: 100% 7/7 [00:00<00:00, 79.25it/s, loss=0.107, v_num=11, val_loss=0.547, val_top1_acc=0.810, val_d_prime=3.010, val_aucroc=0.962, val_mAP=0.851] \n",
      "Epoch 191:   0% 0/7 [00:00<?, ?it/s, loss=0.105, v_num=11, val_loss=0.547, val_top1_acc=0.810, val_d_prime=3.010, val_aucroc=0.962, val_mAP=0.851]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 191: 100% 7/7 [00:00<00:00, 79.87it/s, loss=0.105, v_num=11, val_loss=0.543, val_top1_acc=0.811, val_d_prime=3.010, val_aucroc=0.963, val_mAP=0.854] \n",
      "Epoch 194:   0% 0/7 [00:00<?, ?it/s, loss=0.103, v_num=11, val_loss=0.543, val_top1_acc=0.811, val_d_prime=3.010, val_aucroc=0.963, val_mAP=0.854]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 194: 100% 7/7 [00:00<00:00, 53.42it/s, loss=0.103, v_num=11, val_loss=0.552, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.850]\n",
      "Epoch 197:   0% 0/7 [00:00<?, ?it/s, loss=0.102, v_num=11, val_loss=0.552, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 197: 100% 7/7 [00:00<00:00, 75.00it/s, loss=0.101, v_num=11, val_loss=0.549, val_top1_acc=0.809, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.852] \n",
      "Epoch 200:   0% 0/7 [00:00<?, ?it/s, loss=0.1, v_num=11, val_loss=0.549, val_top1_acc=0.809, val_d_prime=2.990, val_aucroc=0.962, val_mAP=0.852]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 200: 100% 7/7 [00:00<00:00, 80.15it/s, loss=0.0995, v_num=11, val_loss=0.548, val_top1_acc=0.812, val_d_prime=3.010, val_aucroc=0.963, val_mAP=0.852]\n",
      "Epoch 203:   0% 0/7 [00:00<?, ?it/s, loss=0.0984, v_num=11, val_loss=0.548, val_top1_acc=0.812, val_d_prime=3.010, val_aucroc=0.963, val_mAP=0.852]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Validation DataLoader 0: 100% 2/2 [00:00<00:00, 10.81it/s]\u001B[A\n",
      "Epoch 203: 100% 7/7 [00:00<00:00, 22.57it/s, loss=0.0977, v_num=11, val_loss=0.560, val_top1_acc=0.809, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.849]\n",
      "Epoch 206:   0% 0/7 [00:00<?, ?it/s, loss=0.0962, v_num=11, val_loss=0.560, val_top1_acc=0.809, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 206: 100% 7/7 [00:00<00:00, 80.05it/s, loss=0.0956, v_num=11, val_loss=0.550, val_top1_acc=0.809, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.850] \n",
      "Epoch 209:   0% 0/7 [00:00<?, ?it/s, loss=0.095, v_num=11, val_loss=0.550, val_top1_acc=0.809, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 209: 100% 7/7 [00:00<00:00, 62.82it/s, loss=0.0952, v_num=11, val_loss=0.571, val_top1_acc=0.813, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.850]\n",
      "Epoch 212:   0% 0/7 [00:00<?, ?it/s, loss=0.0955, v_num=11, val_loss=0.571, val_top1_acc=0.813, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 212: 100% 7/7 [00:00<00:00, 59.60it/s, loss=0.0952, v_num=11, val_loss=0.558, val_top1_acc=0.804, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.849]\n",
      "Epoch 215:   0% 0/7 [00:00<?, ?it/s, loss=0.0943, v_num=11, val_loss=0.558, val_top1_acc=0.804, val_d_prime=3.000, val_aucroc=0.963, val_mAP=0.849]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 215: 100% 7/7 [00:00<00:00, 57.20it/s, loss=0.0942, v_num=11, val_loss=0.566, val_top1_acc=0.809, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.850]\n",
      "Epoch 218:   0% 0/7 [00:00<?, ?it/s, loss=0.0935, v_num=11, val_loss=0.566, val_top1_acc=0.809, val_d_prime=2.980, val_aucroc=0.961, val_mAP=0.850]\n",
      "Validation: 0it [00:00, ?it/s]\u001B[A\n",
      "Validation:   0% 0/2 [00:00<?, ?it/s]\u001B[A\n",
      "Validation DataLoader 0:   0% 0/2 [00:00<?, ?it/s]\u001B[A/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "\n",
      "Epoch 218: 100% 7/7 [00:00<00:00, 80.31it/s, loss=0.0928, v_num=11, val_loss=0.561, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.848] \n",
      "Epoch 218: 100% 7/7 [00:00<00:00, 75.54it/s, loss=0.0928, v_num=11, val_loss=0.561, val_top1_acc=0.807, val_d_prime=3.000, val_aucroc=0.962, val_mAP=0.848]\n",
      "FIT Profiler Report\n",
      "\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                              \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                               \t|  -              \t|  62515          \t|  18.591         \t|  100 %          \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                  \t|  0.081875       \t|  219            \t|  17.931         \t|  96.448         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                  \t|  0.0038895      \t|  1095           \t|  4.259          \t|  22.909         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                \t|  0.0035726      \t|  1095           \t|  3.912          \t|  21.042         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                          \t|  0.03026        \t|  73             \t|  2.209          \t|  11.882         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                        \t|  0.0014985      \t|  1095           \t|  1.6408         \t|  8.8258         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                 \t|  0.018362       \t|  73             \t|  1.3405         \t|  7.2102         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                             \t|  0.00089156     \t|  1095           \t|  0.97626        \t|  5.2512         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                  \t|  0.00030713     \t|  1095           \t|  0.33631        \t|  1.809          \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                \t|  0.00018802     \t|  1095           \t|  0.20588        \t|  1.1074         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                      \t|  9.944e-05      \t|  1241           \t|  0.1234         \t|  0.66378        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                           \t|  0.00011182     \t|  1095           \t|  0.12244        \t|  0.65862        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                      \t|  0.00067164     \t|  146            \t|  0.098059       \t|  0.52745        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                        \t|  0.00036207     \t|  219            \t|  0.079294       \t|  0.42652        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                      \t|  0.00025274     \t|  219            \t|  0.05535        \t|  0.29772        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                         \t|  0.00056447     \t|  73             \t|  0.041206       \t|  0.22165        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                 \t|  0.00049209     \t|  73             \t|  0.035922       \t|  0.19322        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                   \t|  0.00017516     \t|  146            \t|  0.025573       \t|  0.13755        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                 \t|  0.0001391      \t|  146            \t|  0.020309       \t|  0.10924        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                       \t|  0.00025743     \t|  73             \t|  0.018793       \t|  0.10108        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                 \t|  7.0749e-06     \t|  1095           \t|  0.007747       \t|  0.041671       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                     \t|  8.6728e-05     \t|  73             \t|  0.0063311      \t|  0.034054       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                \t|  2.7015e-05     \t|  219            \t|  0.0059163      \t|  0.031823       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                               \t|  5.3548e-06     \t|  1095           \t|  0.0058635      \t|  0.031539       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                    \t|  5.1797e-06     \t|  1095           \t|  0.0056718      \t|  0.030508       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                      \t|  7.5406e-05     \t|  73             \t|  0.0055047      \t|  0.029609       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                      \t|  4.8526e-06     \t|  1095           \t|  0.0053136      \t|  0.028582       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                \t|  4.25e-06       \t|  1095           \t|  0.0046537      \t|  0.025032       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                         \t|  4.2378e-06     \t|  1095           \t|  0.0046404      \t|  0.02496        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                          \t|  4.1942e-06     \t|  1095           \t|  0.0045926      \t|  0.024703       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                           \t|  4.0198e-06     \t|  1095           \t|  0.0044017      \t|  0.023676       \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                     \t|  3.9013e-06     \t|  1095           \t|  0.0042719      \t|  0.022978       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                            \t|  3.823e-06      \t|  1095           \t|  0.0041862      \t|  0.022517       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                       \t|  3.8209e-06     \t|  1095           \t|  0.0041839      \t|  0.022505       \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                            \t|  3.786e-06      \t|  1095           \t|  0.0041457      \t|  0.022299       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step          \t|  3.7779e-06     \t|  1095           \t|  0.0041369      \t|  0.022252       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                  \t|  3.7681e-06     \t|  1095           \t|  0.0041261      \t|  0.022194       \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                               \t|  3.7534e-06     \t|  1095           \t|  0.0041099      \t|  0.022107       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                 \t|  3.7388e-06     \t|  1095           \t|  0.004094       \t|  0.022021       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                    \t|  3.6844e-06     \t|  1095           \t|  0.0040344      \t|  0.021701       \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                 \t|  3.6794e-06     \t|  1095           \t|  0.004029       \t|  0.021672       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                      \t|  3.6431e-06     \t|  1095           \t|  0.0039892      \t|  0.021458       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad               \t|  3.6367e-06     \t|  1095           \t|  0.0039822      \t|  0.02142        \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                              \t|  3.6351e-06     \t|  1095           \t|  0.0039804      \t|  0.02141        \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                    \t|  3.6311e-06     \t|  1095           \t|  0.0039761      \t|  0.021387       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                          \t|  3.5975e-06     \t|  1095           \t|  0.0039392      \t|  0.021189       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                        \t|  3.5759e-06     \t|  1095           \t|  0.0039156      \t|  0.021062       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                \t|  3.4913e-06     \t|  1095           \t|  0.0038229      \t|  0.020563       \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                          \t|  3.4662e-06     \t|  1095           \t|  0.0037955      \t|  0.020416       \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                           \t|  3.4662e-06     \t|  1095           \t|  0.0037955      \t|  0.020415       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                         \t|  3.4458e-06     \t|  1095           \t|  0.0037731      \t|  0.020295       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                              \t|  3.4256e-06     \t|  1095           \t|  0.003751       \t|  0.020177       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                \t|  3.4247e-06     \t|  1095           \t|  0.00375        \t|  0.020171       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                           \t|  1.1703e-05     \t|  219            \t|  0.002563       \t|  0.013786       \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                             \t|  2.0314e-06     \t|  1095           \t|  0.0022244      \t|  0.011965       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                            \t|  2.0057e-06     \t|  1095           \t|  0.0021962      \t|  0.011813       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                         \t|  9.5479e-06     \t|  219            \t|  0.002091       \t|  0.011247       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                          \t|  1.8731e-06     \t|  1095           \t|  0.0020511      \t|  0.011033       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                             \t|  1.8456e-06     \t|  1095           \t|  0.002021       \t|  0.010871       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                        \t|  8.8129e-06     \t|  219            \t|  0.00193        \t|  0.010381       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                           \t|  1.5583e-06     \t|  1095           \t|  0.0017064      \t|  0.0091784      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                    \t|  1.516e-06      \t|  1095           \t|  0.0016601      \t|  0.0089294      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                 \t|  1.4918e-06     \t|  1095           \t|  0.0016336      \t|  0.0087867      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                      \t|  1.4401e-06     \t|  1095           \t|  0.0015769      \t|  0.0084818      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                            \t|  1.4186e-06     \t|  1095           \t|  0.0015534      \t|  0.0083555      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                    \t|  4.3654e-06     \t|  292            \t|  0.0012747      \t|  0.0068564      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                      \t|  8.4069e-06     \t|  146            \t|  0.0012274      \t|  0.0066021      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                      \t|  3.9677e-06     \t|  292            \t|  0.0011586      \t|  0.0062319      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                \t|  5.2816e-06     \t|  219            \t|  0.0011567      \t|  0.0062217      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                      \t|  3.824e-06      \t|  292            \t|  0.0011166      \t|  0.0060062      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                    \t|  7.2545e-06     \t|  146            \t|  0.0010592      \t|  0.0056971      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                            \t|  3.5587e-06     \t|  292            \t|  0.0010391      \t|  0.0055894      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                               \t|  3.5122e-06     \t|  292            \t|  0.0010256      \t|  0.0055165      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                 \t|  3.4546e-06     \t|  292            \t|  0.0010088      \t|  0.005426       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                              \t|  3.4369e-06     \t|  292            \t|  0.0010036      \t|  0.0053981      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                    \t|  3.4363e-06     \t|  292            \t|  0.0010034      \t|  0.0053971      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                              \t|  3.4222e-06     \t|  292            \t|  0.0009993      \t|  0.0053751      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                \t|  3.3731e-06     \t|  292            \t|  0.00098495     \t|  0.0052979      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                          \t|  4.0257e-06     \t|  219            \t|  0.00088163     \t|  0.0047422      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                            \t|  1.1892e-05     \t|  73             \t|  0.00086812     \t|  0.0046695      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start              \t|  3.9229e-06     \t|  219            \t|  0.00085911     \t|  0.0046211      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                              \t|  3.6367e-06     \t|  219            \t|  0.00079643     \t|  0.0042839      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                 \t|  0.00079626     \t|  1              \t|  0.00079626     \t|  0.004283       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                         \t|  5.3339e-06     \t|  146            \t|  0.00077876     \t|  0.0041889      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                           \t|  5.0262e-06     \t|  146            \t|  0.00073382     \t|  0.0039471      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                          \t|  8.9478e-06     \t|  73             \t|  0.00065319     \t|  0.0035134      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                     \t|  4.4547e-06     \t|  146            \t|  0.00065038     \t|  0.0034983      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                   \t|  4.2379e-06     \t|  146            \t|  0.00061873     \t|  0.0033281      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end           \t|  3.9822e-06     \t|  146            \t|  0.0005814      \t|  0.0031273      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start         \t|  3.7857e-06     \t|  146            \t|  0.00055271     \t|  0.002973       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                               \t|  6.5307e-06     \t|  73             \t|  0.00047674     \t|  0.0025643      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                \t|  1.5997e-06     \t|  292            \t|  0.00046713     \t|  0.0025126      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                           \t|  6.0106e-06     \t|  73             \t|  0.00043877     \t|  0.0023601      \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                           \t|  2.7288e-06     \t|  146            \t|  0.00039841     \t|  0.002143       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                  \t|  1.3549e-06     \t|  292            \t|  0.00039563     \t|  0.0021281      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                            \t|  1.7049e-06     \t|  219            \t|  0.00037338     \t|  0.0020084      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                          \t|  1.622e-06      \t|  219            \t|  0.00035522     \t|  0.0019107      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                           \t|  4.4891e-06     \t|  73             \t|  0.0003277      \t|  0.0017627      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                         \t|  3.9863e-06     \t|  73             \t|  0.000291       \t|  0.0015653      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start               \t|  3.9764e-06     \t|  73             \t|  0.00029028     \t|  0.0015614      \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                            \t|  0.00028316     \t|  1              \t|  0.00028316     \t|  0.0015231      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                   \t|  3.8526e-06     \t|  73             \t|  0.00028124     \t|  0.0015128      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                      \t|  3.7896e-06     \t|  73             \t|  0.00027664     \t|  0.001488       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                       \t|  1.8873e-06     \t|  146            \t|  0.00027554     \t|  0.0014821      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                         \t|  3.7707e-06     \t|  73             \t|  0.00027526     \t|  0.0014806      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end           \t|  3.5032e-06     \t|  73             \t|  0.00025573     \t|  0.0013756      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                     \t|  1.6954e-06     \t|  146            \t|  0.00024753     \t|  0.0013314      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                 \t|  3.3765e-06     \t|  73             \t|  0.00024649     \t|  0.0013258      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                    \t|  3.3598e-06     \t|  73             \t|  0.00024527     \t|  0.0013193      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start         \t|  3.3428e-06     \t|  73             \t|  0.00024402     \t|  0.0013126      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                   \t|  3.3372e-06     \t|  73             \t|  0.00024361     \t|  0.0013104      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                     \t|  3.3217e-06     \t|  73             \t|  0.00024248     \t|  0.0013043      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                  \t|  1.6275e-06     \t|  146            \t|  0.00023761     \t|  0.0012781      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                              \t|  0.00023015     \t|  1              \t|  0.00023015     \t|  0.0012379      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                             \t|  2.7711e-06     \t|  73             \t|  0.00020229     \t|  0.0010881      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                \t|  6.2498e-06     \t|  30             \t|  0.0001875      \t|  0.0010085      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                    \t|  2.3326e-06     \t|  73             \t|  0.00017028     \t|  0.00091593     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                              \t|  0.00014244     \t|  1              \t|  0.00014244     \t|  0.00076616     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                           \t|  1.8657e-06     \t|  73             \t|  0.0001362      \t|  0.0007326      \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                        \t|  4.468e-06      \t|  30             \t|  0.00013404     \t|  0.00072098     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                     \t|  1.6844e-06     \t|  73             \t|  0.00012296     \t|  0.00066141     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                  \t|  1.6613e-06     \t|  73             \t|  0.00012128     \t|  0.00065233     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                       \t|  1.6063e-06     \t|  73             \t|  0.00011726     \t|  0.00063071     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                          \t|  3.7491e-06     \t|  30             \t|  0.00011247     \t|  0.00060499     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                \t|  3.5395e-06     \t|  30             \t|  0.00010619     \t|  0.00057116     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                           \t|  3.4166e-06     \t|  30             \t|  0.0001025      \t|  0.00055133     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                          \t|  0.00010159     \t|  1              \t|  0.00010159     \t|  0.00054644     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                            \t|  1.8636e-06     \t|  30             \t|  5.5908e-05     \t|  0.00030072     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                \t|  1.562e-05      \t|  1              \t|  1.562e-05      \t|  8.4018e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                               \t|  1.2051e-05     \t|  1              \t|  1.2051e-05     \t|  6.4821e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                     \t|  8.871e-06      \t|  1              \t|  8.871e-06      \t|  4.7716e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                         \t|  8.227e-06      \t|  1              \t|  8.227e-06      \t|  4.4252e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                        \t|  8.036e-06      \t|  1              \t|  8.036e-06      \t|  4.3225e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                 \t|  7.661e-06      \t|  1              \t|  7.661e-06      \t|  4.1208e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                               \t|  7.488e-06      \t|  1              \t|  7.488e-06      \t|  4.0277e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                    \t|  7.365e-06      \t|  1              \t|  7.365e-06      \t|  3.9616e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                    \t|  6.592e-06      \t|  1              \t|  6.592e-06      \t|  3.5458e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                             \t|  6.538e-06      \t|  1              \t|  6.538e-06      \t|  3.5167e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                      \t|  6.131e-06      \t|  1              \t|  6.131e-06      \t|  3.2978e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                        \t|  5.955e-06      \t|  1              \t|  5.955e-06      \t|  3.2031e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                      \t|  5.949e-06      \t|  1              \t|  5.949e-06      \t|  3.1999e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                  \t|  5.939e-06      \t|  1              \t|  5.939e-06      \t|  3.1945e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                           \t|  5.782e-06      \t|  1              \t|  5.782e-06      \t|  3.1101e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                          \t|  5.594e-06      \t|  1              \t|  5.594e-06      \t|  3.009e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                 \t|  5.347e-06      \t|  1              \t|  5.347e-06      \t|  2.8761e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                \t|  5.26e-06       \t|  1              \t|  5.26e-06       \t|  2.8293e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                           \t|  4.946e-06      \t|  1              \t|  4.946e-06      \t|  2.6604e-05     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                        \t|  4.938e-06      \t|  1              \t|  4.938e-06      \t|  2.6561e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                              \t|  4.92e-06       \t|  1              \t|  4.92e-06       \t|  2.6464e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                  \t|  4.807e-06      \t|  1              \t|  4.807e-06      \t|  2.5856e-05     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                   \t|  4.768e-06      \t|  1              \t|  4.768e-06      \t|  2.5647e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start         \t|  4.756e-06      \t|  1              \t|  4.756e-06      \t|  2.5582e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                    \t|  4.702e-06      \t|  1              \t|  4.702e-06      \t|  2.5292e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                   \t|  4.662e-06      \t|  1              \t|  4.662e-06      \t|  2.5076e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end           \t|  4.559e-06      \t|  1              \t|  4.559e-06      \t|  2.4522e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                       \t|  4.492e-06      \t|  1              \t|  4.492e-06      \t|  2.4162e-05     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                     \t|  4.477e-06      \t|  1              \t|  4.477e-06      \t|  2.4081e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                         \t|  4.473e-06      \t|  1              \t|  4.473e-06      \t|  2.406e-05      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                          \t|  4.464e-06      \t|  1              \t|  4.464e-06      \t|  2.4011e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                        \t|  4.44e-06       \t|  1              \t|  4.44e-06       \t|  2.3882e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                    \t|  4.42e-06       \t|  1              \t|  4.42e-06       \t|  2.3775e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                \t|  4.407e-06      \t|  1              \t|  4.407e-06      \t|  2.3705e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                     \t|  4.401e-06      \t|  1              \t|  4.401e-06      \t|  2.3673e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                      \t|  4.395e-06      \t|  1              \t|  4.395e-06      \t|  2.364e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                  \t|  4.375e-06      \t|  1              \t|  4.375e-06      \t|  2.3533e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                       \t|  4.371e-06      \t|  1              \t|  4.371e-06      \t|  2.3511e-05     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                          \t|  4.271e-06      \t|  1              \t|  4.271e-06      \t|  2.2973e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                   \t|  4.265e-06      \t|  1              \t|  4.265e-06      \t|  2.2941e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup\t|  4.233e-06      \t|  1              \t|  4.233e-06      \t|  2.2769e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                              \t|  4.152e-06      \t|  1              \t|  4.152e-06      \t|  2.2333e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                      \t|  3.965e-06      \t|  1              \t|  3.965e-06      \t|  2.1327e-05     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                   \t|  3.857e-06      \t|  1              \t|  3.857e-06      \t|  2.0746e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                             \t|  3.827e-06      \t|  1              \t|  3.827e-06      \t|  2.0585e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model        \t|  3.665e-06      \t|  1              \t|  3.665e-06      \t|  1.9714e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                  \t|  3.64e-06       \t|  1              \t|  3.64e-06       \t|  1.9579e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                       \t|  3.534e-06      \t|  1              \t|  3.534e-06      \t|  1.9009e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                      \t|  3.026e-06      \t|  1              \t|  3.026e-06      \t|  1.6277e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                \t|  3.026e-06      \t|  1              \t|  3.026e-06      \t|  1.6277e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                           \t|  2.8e-06        \t|  1              \t|  2.8e-06        \t|  1.5061e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                         \t|  2.633e-06      \t|  1              \t|  2.633e-06      \t|  1.4163e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                \t|  2.462e-06      \t|  1              \t|  2.462e-06      \t|  1.3243e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                      \t|  2.429e-06      \t|  1              \t|  2.429e-06      \t|  1.3065e-05     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                       \t|  2.247e-06      \t|  1              \t|  2.247e-06      \t|  1.2086e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                  \t|  2.147e-06      \t|  1              \t|  2.147e-06      \t|  1.1549e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                    \t|  2.055e-06      \t|  1              \t|  2.055e-06      \t|  1.1054e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                       \t|  1.879e-06      \t|  1              \t|  1.879e-06      \t|  1.0107e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                     \t|  1.866e-06      \t|  1              \t|  1.866e-06      \t|  1.0037e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                  \t|  1.484e-06      \t|  1              \t|  1.484e-06      \t|  7.9823e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                         \t|  1.245e-06      \t|  1              \t|  1.245e-06      \t|  6.6967e-06     \t|\n",
      "--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "predict - mridangam_stroke - 2022-06-03 21:10:52,695 - 695 - Validation Score for the Training Split: 0.8130372762680054\n",
      "\n",
      "split: 4it [01:59, 29.75s/it]\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 108861.94it/s]\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 36570.62it/s]\n",
      "Getting embeddings for split ['fold00'], which has 1396 instances.\n",
      "Restoring states from the checkpoint path at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_0/checkpoints/epoch=104-step=525.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_0/checkpoints/epoch=104-step=525.ckpt\n",
      "Testing DataLoader 0:   0% 0/2 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 419.22it/s]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 49.11it/s] \n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       Test metric             DataLoader 0\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       test_aucroc          0.9667379178924649\n",
      "      test_d_prime          3.0656446952202114\n",
      "        test_loss           0.48911142349243164\n",
      "        test_mAP            0.8648800803555511\n",
      "       test_score           0.8202005624771118\n",
      "      test_top1_acc         0.8202005624771118\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "TEST Profiler Report\n",
      "\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                               \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                                \t|  -              \t|  47226          \t|  194.96         \t|  100 %          \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                   \t|  0.072129       \t|  165            \t|  11.901         \t|  6.1045         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                   \t|  0.0036649      \t|  825            \t|  3.0235         \t|  1.5508         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                 \t|  0.0033731      \t|  825            \t|  2.7828         \t|  1.4274         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                           \t|  0.026831       \t|  55             \t|  1.4757         \t|  0.75694        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                         \t|  0.0014713      \t|  825            \t|  1.2138         \t|  0.62259        \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                  \t|  0.017298       \t|  55             \t|  0.95139        \t|  0.48799        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                              \t|  0.00082456     \t|  825            \t|  0.68027        \t|  0.34893        \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                   \t|  0.00027265     \t|  825            \t|  0.22494        \t|  0.11538        \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                 \t|  0.00015812     \t|  825            \t|  0.13045        \t|  0.066911       \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                       \t|  9.3228e-05     \t|  937            \t|  0.087355       \t|  0.044807       \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                            \t|  9.9557e-05     \t|  825            \t|  0.082135       \t|  0.042129       \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                       \t|  0.00060438     \t|  110            \t|  0.066481       \t|  0.0341         \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                         \t|  0.00034464     \t|  165            \t|  0.056865       \t|  0.029168       \t|\n",
      "|  run_test_evaluation                                                                                                                                                                                                  \t|  0.049329       \t|  1              \t|  0.049329       \t|  0.025302       \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                       \t|  0.00022853     \t|  165            \t|  0.037708       \t|  0.019341       \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_epoch_end                                                                                                                                                                 \t|  0.031856       \t|  1              \t|  0.031856       \t|  0.01634        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                          \t|  0.00053633     \t|  55             \t|  0.029498       \t|  0.01513        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                  \t|  0.00046779     \t|  55             \t|  0.025728       \t|  0.013197       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                    \t|  0.00015905     \t|  110            \t|  0.017495       \t|  0.0089737      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                  \t|  0.00012941     \t|  110            \t|  0.014235       \t|  0.0073016      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                        \t|  0.00024201     \t|  55             \t|  0.01331        \t|  0.0068273      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                  \t|  6.1053e-06     \t|  825            \t|  0.0050368      \t|  0.0025835      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                      \t|  7.7288e-05     \t|  55             \t|  0.0042508      \t|  0.0021804      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                 \t|  2.5399e-05     \t|  165            \t|  0.0041908      \t|  0.0021496      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                                \t|  4.7927e-06     \t|  825            \t|  0.0039539      \t|  0.0020281      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                     \t|  4.5306e-06     \t|  825            \t|  0.0037377      \t|  0.0019172      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                       \t|  6.495e-05      \t|  55             \t|  0.0035723      \t|  0.0018323      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                       \t|  3.9719e-06     \t|  825            \t|  0.0032768      \t|  0.0016808      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                 \t|  3.7072e-06     \t|  825            \t|  0.0030585      \t|  0.0015688      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                           \t|  3.698e-06      \t|  825            \t|  0.0030509      \t|  0.0015649      \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                          \t|  3.5141e-06     \t|  825            \t|  0.0028992      \t|  0.0014871      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad                \t|  3.5051e-06     \t|  825            \t|  0.0028917      \t|  0.0014832      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                            \t|  3.4331e-06     \t|  825            \t|  0.0028323      \t|  0.0014528      \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                             \t|  3.3514e-06     \t|  825            \t|  0.0027649      \t|  0.0014182      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                        \t|  3.34e-06       \t|  825            \t|  0.0027555      \t|  0.0014134      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                     \t|  3.2855e-06     \t|  825            \t|  0.0027106      \t|  0.0013903      \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                             \t|  3.2519e-06     \t|  825            \t|  0.0026828      \t|  0.0013761      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                  \t|  3.2335e-06     \t|  825            \t|  0.0026676      \t|  0.0013683      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                   \t|  3.2155e-06     \t|  825            \t|  0.0026528      \t|  0.0013607      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step           \t|  3.2088e-06     \t|  825            \t|  0.0026472      \t|  0.0013578      \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                               \t|  3.2014e-06     \t|  825            \t|  0.0026411      \t|  0.0013547      \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                                \t|  3.1819e-06     \t|  825            \t|  0.0026251      \t|  0.0013465      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                       \t|  3.1676e-06     \t|  825            \t|  0.0026133      \t|  0.0013404      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                     \t|  3.1394e-06     \t|  825            \t|  0.00259        \t|  0.0013285      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                           \t|  3.1354e-06     \t|  825            \t|  0.0025867      \t|  0.0013268      \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                      \t|  3.1114e-06     \t|  825            \t|  0.0025669      \t|  0.0013166      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                         \t|  3.0987e-06     \t|  825            \t|  0.0025564      \t|  0.0013113      \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                  \t|  3.0794e-06     \t|  825            \t|  0.0025405      \t|  0.0013031      \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                            \t|  3.0237e-06     \t|  825            \t|  0.0024946      \t|  0.0012795      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                 \t|  3.0046e-06     \t|  825            \t|  0.0024788      \t|  0.0012715      \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                           \t|  3.0032e-06     \t|  825            \t|  0.0024777      \t|  0.0012709      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                          \t|  2.979e-06      \t|  825            \t|  0.0024577      \t|  0.0012606      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                 \t|  2.9254e-06     \t|  825            \t|  0.0024134      \t|  0.0012379      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                               \t|  2.9112e-06     \t|  825            \t|  0.0024017      \t|  0.0012319      \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                            \t|  1.1789e-05     \t|  165            \t|  0.0019452      \t|  0.00099775     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                       \t|  1.9782e-06     \t|  825            \t|  0.001632       \t|  0.0008371      \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                          \t|  9.6715e-06     \t|  165            \t|  0.0015958      \t|  0.00081853     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step                                                                                                                                                                             \t|  0.00079523     \t|  2              \t|  0.0015905      \t|  0.0008158      \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                              \t|  1.9267e-06     \t|  825            \t|  0.0015896      \t|  0.00081533     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                         \t|  8.8618e-06     \t|  165            \t|  0.0014622      \t|  0.00075001     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                             \t|  1.7657e-06     \t|  825            \t|  0.0014567      \t|  0.00074718     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                           \t|  1.6841e-06     \t|  825            \t|  0.0013894      \t|  0.00071267     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                              \t|  1.6222e-06     \t|  825            \t|  0.0013383      \t|  0.00068644     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                     \t|  1.4175e-06     \t|  825            \t|  0.0011694      \t|  0.00059982     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                            \t|  1.3697e-06     \t|  825            \t|  0.00113        \t|  0.0005796      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                  \t|  1.2949e-06     \t|  825            \t|  0.0010683      \t|  0.00054796     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                             \t|  1.2629e-06     \t|  825            \t|  0.0010419      \t|  0.0005344      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                     \t|  4.0134e-06     \t|  221            \t|  0.00088696     \t|  0.00045495     \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                       \t|  7.7648e-06     \t|  110            \t|  0.00085413     \t|  0.00043811     \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                     \t|  7.0685e-06     \t|  110            \t|  0.00077754     \t|  0.00039882     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                 \t|  4.6375e-06     \t|  165            \t|  0.00076519     \t|  0.00039249     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                       \t|  3.427e-06      \t|  221            \t|  0.00075737     \t|  0.00038848     \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                             \t|  3.2976e-06     \t|  221            \t|  0.00072877     \t|  0.00037381     \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                               \t|  3.0772e-06     \t|  221            \t|  0.00068006     \t|  0.00034882     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                     \t|  3.0267e-06     \t|  221            \t|  0.00066891     \t|  0.0003431      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                                \t|  2.9782e-06     \t|  221            \t|  0.00065819     \t|  0.0003376      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                 \t|  2.9573e-06     \t|  221            \t|  0.00065355     \t|  0.00033523     \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                  \t|  0.00065336     \t|  1              \t|  0.00065336     \t|  0.00033513     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                       \t|  2.9442e-06     \t|  221            \t|  0.00065067     \t|  0.00033375     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                               \t|  2.9223e-06     \t|  221            \t|  0.00064582     \t|  0.00033126     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                           \t|  3.9079e-06     \t|  165            \t|  0.00064481     \t|  0.00033074     \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                  \t|  2.8592e-06     \t|  221            \t|  0.00063188     \t|  0.00032411     \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                             \t|  1.1387e-05     \t|  55             \t|  0.00062627     \t|  0.00032123     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start               \t|  3.4981e-06     \t|  165            \t|  0.00057719     \t|  0.00029606     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                          \t|  4.7011e-06     \t|  110            \t|  0.00051712     \t|  0.00026525     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                               \t|  3.1138e-06     \t|  165            \t|  0.00051378     \t|  0.00026353     \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                           \t|  8.711e-06      \t|  55             \t|  0.0004791      \t|  0.00024575     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                            \t|  4.3528e-06     \t|  110            \t|  0.00047881     \t|  0.0002456      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                      \t|  4.0773e-06     \t|  110            \t|  0.00044851     \t|  0.00023005     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                    \t|  3.8332e-06     \t|  110            \t|  0.00042165     \t|  0.00021628     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end            \t|  3.6062e-06     \t|  110            \t|  0.00039668     \t|  0.00020347     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start          \t|  3.2442e-06     \t|  110            \t|  0.00035687     \t|  0.00018305     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                            \t|  5.9597e-06     \t|  55             \t|  0.00032778     \t|  0.00016813     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                                \t|  5.7055e-06     \t|  55             \t|  0.0003138      \t|  0.00016096     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                 \t|  1.2848e-06     \t|  221            \t|  0.00028395     \t|  0.00014564     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                   \t|  1.2657e-06     \t|  221            \t|  0.00027973     \t|  0.00014348     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                             \t|  1.6925e-06     \t|  165            \t|  0.00027927     \t|  0.00014325     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                           \t|  1.5693e-06     \t|  165            \t|  0.00025894     \t|  0.00013282     \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                            \t|  2.2993e-06     \t|  110            \t|  0.00025292     \t|  0.00012973     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                             \t|  0.00024561     \t|  1              \t|  0.00024561     \t|  0.00012598     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                            \t|  4.1541e-06     \t|  55             \t|  0.00022848     \t|  0.00011719     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_start                                                                                                                                                                              \t|  0.00020407     \t|  1              \t|  0.00020407     \t|  0.00010467     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_start                                                                                                                                                                        \t|  0.00010182     \t|  2              \t|  0.00020364     \t|  0.00010445     \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                    \t|  3.5781e-06     \t|  55             \t|  0.0001968      \t|  0.00010094     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                        \t|  1.788e-06      \t|  110            \t|  0.00019667     \t|  0.00010088     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                          \t|  3.5065e-06     \t|  55             \t|  0.00019286     \t|  9.8923e-05     \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                       \t|  3.4901e-06     \t|  55             \t|  0.00019195     \t|  9.8458e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                               \t|  0.0001898      \t|  1              \t|  0.0001898      \t|  9.7354e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                          \t|  3.4275e-06     \t|  55             \t|  0.00018852     \t|  9.6695e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end            \t|  3.1829e-06     \t|  55             \t|  0.00017506     \t|  8.9792e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start                \t|  3.182e-06      \t|  55             \t|  0.00017501     \t|  8.9768e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_end                                                                                                                                                                                \t|  0.00016951     \t|  1              \t|  0.00016951     \t|  8.6945e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                      \t|  3.0291e-06     \t|  55             \t|  0.0001666      \t|  8.5454e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                    \t|  2.9724e-06     \t|  55             \t|  0.00016348     \t|  8.3856e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                  \t|  2.8964e-06     \t|  55             \t|  0.0001593      \t|  8.171e-05      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                      \t|  1.4375e-06     \t|  110            \t|  0.00015813     \t|  8.111e-05      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                     \t|  2.8741e-06     \t|  55             \t|  0.00015808     \t|  8.1082e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start          \t|  2.8284e-06     \t|  55             \t|  0.00015556     \t|  7.9792e-05     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                   \t|  1.3765e-06     \t|  110            \t|  0.00015141     \t|  7.7665e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_end                                                                                                                                                                          \t|  7.4779e-05     \t|  2              \t|  0.00014956     \t|  7.6713e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                               \t|  0.00014641     \t|  1              \t|  0.00014641     \t|  7.5099e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                 \t|  6.073e-06      \t|  24             \t|  0.00014575     \t|  7.4761e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                              \t|  2.6035e-06     \t|  55             \t|  0.00014319     \t|  7.3446e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                           \t|  0.0001359      \t|  1              \t|  0.0001359      \t|  6.9709e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                         \t|  5.5964e-06     \t|  24             \t|  0.00013431     \t|  6.8894e-05     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                     \t|  1.982e-06      \t|  55             \t|  0.00010901     \t|  5.5915e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                        \t|  1.7552e-06     \t|  55             \t|  9.6536e-05     \t|  4.9516e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                      \t|  1.7402e-06     \t|  55             \t|  9.5711e-05     \t|  4.9093e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                           \t|  3.8552e-06     \t|  24             \t|  9.2525e-05     \t|  4.7459e-05     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                   \t|  1.6727e-06     \t|  55             \t|  9.2e-05        \t|  4.719e-05      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                            \t|  1.6401e-06     \t|  55             \t|  9.0208e-05     \t|  4.627e-05      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                 \t|  3.2435e-06     \t|  24             \t|  7.7845e-05     \t|  3.9929e-05     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                            \t|  3.0239e-06     \t|  24             \t|  7.2573e-05     \t|  3.7225e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_eval                                                                                                                                                             \t|  5.9927e-05     \t|  1              \t|  5.9927e-05     \t|  3.0738e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_train                                                                                                                                                            \t|  5.5505e-05     \t|  1              \t|  5.5505e-05     \t|  2.847e-05      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                             \t|  2.2858e-06     \t|  24             \t|  5.486e-05      \t|  2.8139e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                      \t|  6.6795e-06     \t|  2              \t|  1.3359e-05     \t|  6.8522e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_start                                                                                                                                                                           \t|  6.639e-06      \t|  2              \t|  1.3278e-05     \t|  6.8107e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_end                                                                                                                                                                             \t|  6.0785e-06     \t|  2              \t|  1.2157e-05     \t|  6.2357e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                 \t|  1.1852e-05     \t|  1              \t|  1.1852e-05     \t|  6.0792e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                            \t|  5.513e-06      \t|  2              \t|  1.1026e-05     \t|  5.6556e-06     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                                \t|  1.0151e-05     \t|  1              \t|  1.0151e-05     \t|  5.2067e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                           \t|  4.9655e-06     \t|  2              \t|  9.931e-06      \t|  5.0939e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                              \t|  4.741e-06      \t|  2              \t|  9.482e-06      \t|  4.8636e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_start                                                                                                                                \t|  4.619e-06      \t|  2              \t|  9.238e-06      \t|  4.7384e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_end                                                                                                                                                                                   \t|  8.917e-06      \t|  1              \t|  8.917e-06      \t|  4.5738e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                                \t|  4.449e-06      \t|  2              \t|  8.898e-06      \t|  4.564e-06      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                         \t|  4.291e-06      \t|  2              \t|  8.582e-06      \t|  4.402e-06      \t|\n",
      "|  [Callback]ModelSummary.on_test_start                                                                                                                                                                                 \t|  8.479e-06      \t|  1              \t|  8.479e-06      \t|  4.3491e-06     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                  \t|  8.23e-06       \t|  1              \t|  8.23e-06       \t|  4.2214e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.setup                              \t|  8.044e-06      \t|  1              \t|  8.044e-06      \t|  4.126e-06      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_end                                                                                                                                  \t|  3.9905e-06     \t|  2              \t|  7.981e-06      \t|  4.0937e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_end                                                                                                                                                            \t|  3.6505e-06     \t|  2              \t|  7.301e-06      \t|  3.7449e-06     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                         \t|  3.641e-06      \t|  2              \t|  7.282e-06      \t|  3.7352e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                 \t|  3.6095e-06     \t|  2              \t|  7.219e-06      \t|  3.7028e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_start                                                                                                                                                          \t|  3.499e-06      \t|  2              \t|  6.998e-06      \t|  3.5895e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                          \t|  6.804e-06      \t|  1              \t|  6.804e-06      \t|  3.49e-06       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                        \t|  3.391e-06      \t|  2              \t|  6.782e-06      \t|  3.4787e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                   \t|  3.334e-06      \t|  2              \t|  6.668e-06      \t|  3.4202e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_end                                                                                                                                        \t|  6.606e-06      \t|  1              \t|  6.606e-06      \t|  3.3884e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                        \t|  3.257e-06      \t|  2              \t|  6.514e-06      \t|  3.3412e-06     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                           \t|  3.2365e-06     \t|  2              \t|  6.473e-06      \t|  3.3202e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                          \t|  3.178e-06      \t|  2              \t|  6.356e-06      \t|  3.2602e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model         \t|  3.1715e-06     \t|  2              \t|  6.343e-06      \t|  3.2535e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                         \t|  6.226e-06      \t|  1              \t|  6.226e-06      \t|  3.1935e-06     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                      \t|  3.0895e-06     \t|  2              \t|  6.179e-06      \t|  3.1694e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                   \t|  3.076e-06      \t|  2              \t|  6.152e-06      \t|  3.1555e-06     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                    \t|  3.0725e-06     \t|  2              \t|  6.145e-06      \t|  3.152e-06      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                     \t|  3.059e-06      \t|  2              \t|  6.118e-06      \t|  3.1381e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_start                \t|  3.036e-06      \t|  2              \t|  6.072e-06      \t|  3.1145e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                           \t|  3.011e-06      \t|  2              \t|  6.022e-06      \t|  3.0889e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                     \t|  5.984e-06      \t|  1              \t|  5.984e-06      \t|  3.0694e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                   \t|  2.979e-06      \t|  2              \t|  5.958e-06      \t|  3.056e-06      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_end                  \t|  2.9765e-06     \t|  2              \t|  5.953e-06      \t|  3.0535e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                       \t|  5.801e-06      \t|  1              \t|  5.801e-06      \t|  2.9755e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                        \t|  2.8735e-06     \t|  2              \t|  5.747e-06      \t|  2.9478e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_end                                                                                                                                  \t|  5.232e-06      \t|  1              \t|  5.232e-06      \t|  2.6836e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_load_checkpoint                                                                                                                                                             \t|  4.965e-06      \t|  1              \t|  4.965e-06      \t|  2.5467e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start          \t|  4.868e-06      \t|  1              \t|  4.868e-06      \t|  2.4969e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_start                                                                                                                                      \t|  4.8e-06        \t|  1              \t|  4.8e-06        \t|  2.4621e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                       \t|  4.584e-06      \t|  1              \t|  4.584e-06      \t|  2.3513e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                 \t|  4.572e-06      \t|  1              \t|  4.572e-06      \t|  2.3451e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                            \t|  4.298e-06      \t|  1              \t|  4.298e-06      \t|  2.2046e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_step_end                                                                                                                                                                  \t|  2.145e-06      \t|  2              \t|  4.29e-06       \t|  2.2005e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                              \t|  4.202e-06      \t|  1              \t|  4.202e-06      \t|  2.1553e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                     \t|  4.171e-06      \t|  1              \t|  4.171e-06      \t|  2.1394e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                       \t|  4.169e-06      \t|  1              \t|  4.169e-06      \t|  2.1384e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                  \t|  4.115e-06      \t|  1              \t|  4.115e-06      \t|  2.1107e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                               \t|  4.112e-06      \t|  1              \t|  4.112e-06      \t|  2.1092e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                 \t|  3.858e-06      \t|  1              \t|  3.858e-06      \t|  1.9789e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                      \t|  3.853e-06      \t|  1              \t|  3.853e-06      \t|  1.9763e-06     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                       \t|  3.848e-06      \t|  1              \t|  3.848e-06      \t|  1.9738e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                       \t|  1.895e-06      \t|  2              \t|  3.79e-06       \t|  1.944e-06      \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                    \t|  3.777e-06      \t|  1              \t|  3.777e-06      \t|  1.9373e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_start                                                                                                                                                            \t|  1.8705e-06     \t|  2              \t|  3.741e-06      \t|  1.9189e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end            \t|  3.73e-06       \t|  1              \t|  3.73e-06       \t|  1.9132e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_end                                                                                                                                                                  \t|  3.655e-06      \t|  1              \t|  3.655e-06      \t|  1.8748e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                          \t|  1.786e-06      \t|  2              \t|  3.572e-06      \t|  1.8322e-06     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                     \t|  3.523e-06      \t|  1              \t|  3.523e-06      \t|  1.8071e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup \t|  3.367e-06      \t|  1              \t|  3.367e-06      \t|  1.727e-06      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_start                                                                                                                                \t|  3.365e-06      \t|  1              \t|  3.365e-06      \t|  1.726e-06      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                    \t|  3.359e-06      \t|  1              \t|  3.359e-06      \t|  1.7229e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                               \t|  3.352e-06      \t|  1              \t|  3.352e-06      \t|  1.7193e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_end                                                                                                                                                                          \t|  3.325e-06      \t|  1              \t|  3.325e-06      \t|  1.7055e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_start                                                                                                                                                                \t|  3.295e-06      \t|  1              \t|  3.295e-06      \t|  1.6901e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_end                                                                                                                                                            \t|  3.245e-06      \t|  1              \t|  3.245e-06      \t|  1.6645e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_dataloader                                                                                                                                                             \t|  3.235e-06      \t|  1              \t|  3.235e-06      \t|  1.6593e-06     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                    \t|  3.188e-06      \t|  1              \t|  3.188e-06      \t|  1.6352e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                   \t|  3.172e-06      \t|  1              \t|  3.172e-06      \t|  1.627e-06      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_end                        \t|  3.148e-06      \t|  1              \t|  3.148e-06      \t|  1.6147e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_end                                                                                                                                                                             \t|  3.146e-06      \t|  1              \t|  3.146e-06      \t|  1.6137e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                         \t|  3.128e-06      \t|  1              \t|  3.128e-06      \t|  1.6044e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                       \t|  3.077e-06      \t|  1              \t|  3.077e-06      \t|  1.5783e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_end                  \t|  3.059e-06      \t|  1              \t|  3.059e-06      \t|  1.5691e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_start                      \t|  3.009e-06      \t|  1              \t|  3.009e-06      \t|  1.5434e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_accelerator_backend_setup\t|  2.963e-06      \t|  1              \t|  2.963e-06      \t|  1.5198e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_end                                                                                                                                                              \t|  1.386e-06      \t|  2              \t|  2.772e-06      \t|  1.4218e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_start                                                                                                                                                                           \t|  2.729e-06      \t|  1              \t|  2.729e-06      \t|  1.3998e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_start                                                                                                                                                                        \t|  2.722e-06      \t|  1              \t|  2.722e-06      \t|  1.3962e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_start                \t|  2.655e-06      \t|  1              \t|  2.655e-06      \t|  1.3618e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_start                                                                                                                                                          \t|  2.652e-06      \t|  1              \t|  2.652e-06      \t|  1.3603e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step_end                                                                                                                                                                         \t|  1.2225e-06     \t|  2              \t|  2.445e-06      \t|  1.2541e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                   \t|  2.284e-06      \t|  1              \t|  2.284e-06      \t|  1.1715e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                            \t|  2.055e-06      \t|  1              \t|  2.055e-06      \t|  1.0541e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                 \t|  1.712e-06      \t|  1              \t|  1.712e-06      \t|  8.7814e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_start                                                                                                                                                                  \t|  1.679e-06      \t|  1              \t|  1.679e-06      \t|  8.6121e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                      \t|  1.674e-06      \t|  1              \t|  1.674e-06      \t|  8.5864e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_end                                                                                                                                                                    \t|  1.651e-06      \t|  1              \t|  1.651e-06      \t|  8.4685e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                     \t|  1.577e-06      \t|  1              \t|  1.577e-06      \t|  8.0889e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                        \t|  1.477e-06      \t|  1              \t|  1.477e-06      \t|  7.576e-07      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                   \t|  1.47e-06       \t|  1              \t|  1.47e-06       \t|  7.5401e-07     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_start                                                                                                                                                                         \t|  1.453e-06      \t|  1              \t|  1.453e-06      \t|  7.4529e-07     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                        \t|  1.393e-06      \t|  1              \t|  1.393e-06      \t|  7.1451e-07     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_end                                                                                                                                                                           \t|  1.357e-06      \t|  1              \t|  1.357e-06      \t|  6.9605e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_end                                                                                                                                                              \t|  1.344e-06      \t|  1              \t|  1.344e-06      \t|  6.8938e-07     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_start                                                                                                                                                            \t|  1.31e-06       \t|  1              \t|  1.31e-06       \t|  6.7194e-07     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                          \t|  1.18e-06       \t|  1              \t|  1.18e-06       \t|  6.0526e-07     \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 109119.60it/s]\n",
      "\n",
      "100% 1396/1396 [00:00<00:00, 34621.65it/s]\n",
      "Getting embeddings for split ['fold01'], which has 1396 instances.\n",
      "Restoring states from the checkpoint path at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_8/checkpoints/epoch=392-step=1965.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_8/checkpoints/epoch=392-step=1965.ckpt\n",
      "Testing DataLoader 0:   0% 0/2 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 282.55it/s]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 29.65it/s] \n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       Test metric             DataLoader 0\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       test_aucroc          0.9709770413252347\n",
      "      test_d_prime          3.4191566852319224\n",
      "        test_loss           0.5804157257080078\n",
      "        test_mAP            0.8939131893403549\n",
      "       test_score           0.8502865433692932\n",
      "      test_top1_acc         0.8502865433692932\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "TEST Profiler Report\n",
      "\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                               \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                                \t|  -              \t|  129216         \t|  119.47         \t|  100 %          \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                   \t|  0.08025        \t|  453            \t|  36.353         \t|  30.428         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                   \t|  0.0038716      \t|  2265           \t|  8.7691         \t|  7.3397         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                 \t|  0.003553       \t|  2265           \t|  8.0476         \t|  6.7358         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                           \t|  0.031854       \t|  151            \t|  4.8099         \t|  4.0259         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                         \t|  0.0015094      \t|  2265           \t|  3.4188         \t|  2.8616         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                              \t|  0.00086097     \t|  2265           \t|  1.9501         \t|  1.6322         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                  \t|  0.012299       \t|  151            \t|  1.8572         \t|  1.5545         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                   \t|  0.00031309     \t|  2265           \t|  0.70915        \t|  0.59356        \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                 \t|  0.00018483     \t|  2265           \t|  0.41863        \t|  0.3504         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                       \t|  0.0001006      \t|  2569           \t|  0.25843        \t|  0.21631        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                            \t|  0.000109       \t|  2265           \t|  0.24688        \t|  0.20664        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                       \t|  0.00066784     \t|  302            \t|  0.20169        \t|  0.16881        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                         \t|  0.00036245     \t|  453            \t|  0.16419        \t|  0.13743        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                       \t|  0.00025083     \t|  453            \t|  0.11363        \t|  0.095107       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                          \t|  0.00059906     \t|  151            \t|  0.090458       \t|  0.075713       \t|\n",
      "|  run_test_evaluation                                                                                                                                                                                                  \t|  0.076127       \t|  1              \t|  0.076127       \t|  0.063719       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                  \t|  0.00047375     \t|  151            \t|  0.071536       \t|  0.059876       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                    \t|  0.00017963     \t|  302            \t|  0.054247       \t|  0.045405       \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_epoch_end                                                                                                                                                                 \t|  0.051966       \t|  1              \t|  0.051966       \t|  0.043496       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                        \t|  0.00028195     \t|  151            \t|  0.042574       \t|  0.035634       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                  \t|  0.00013777     \t|  302            \t|  0.041607       \t|  0.034825       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                  \t|  6.9613e-06     \t|  2265           \t|  0.015767       \t|  0.013197       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                      \t|  8.3876e-05     \t|  151            \t|  0.012665       \t|  0.010601       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                                \t|  5.5301e-06     \t|  2265           \t|  0.012526       \t|  0.010484       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                 \t|  2.6662e-05     \t|  453            \t|  0.012078       \t|  0.010109       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                     \t|  5.2053e-06     \t|  2265           \t|  0.01179        \t|  0.0098683      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                       \t|  7.6136e-05     \t|  151            \t|  0.011497       \t|  0.0096226      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                       \t|  4.6392e-06     \t|  2265           \t|  0.010508       \t|  0.0087951      \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                          \t|  4.3358e-06     \t|  2265           \t|  0.0098205      \t|  0.0082198      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                           \t|  4.2763e-06     \t|  2265           \t|  0.0096857      \t|  0.008107       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                 \t|  4.271e-06      \t|  2265           \t|  0.0096739      \t|  0.0080971      \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                             \t|  3.9924e-06     \t|  2265           \t|  0.0090428      \t|  0.0075689      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                            \t|  3.9917e-06     \t|  2265           \t|  0.0090413      \t|  0.0075676      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                        \t|  3.9335e-06     \t|  2265           \t|  0.0089094      \t|  0.0074572      \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                             \t|  3.9065e-06     \t|  2265           \t|  0.0088481      \t|  0.0074059      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                     \t|  3.8711e-06     \t|  2265           \t|  0.0087679      \t|  0.0073388      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                  \t|  3.8272e-06     \t|  2265           \t|  0.0086686      \t|  0.0072557      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                   \t|  3.7877e-06     \t|  2265           \t|  0.008579       \t|  0.0071807      \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                                \t|  3.7613e-06     \t|  2265           \t|  0.0085193      \t|  0.0071307      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                           \t|  3.7538e-06     \t|  2265           \t|  0.0085023      \t|  0.0071164      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step           \t|  3.7194e-06     \t|  2265           \t|  0.0084243      \t|  0.0070512      \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                               \t|  3.7159e-06     \t|  2265           \t|  0.0084165      \t|  0.0070447      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                     \t|  3.711e-06      \t|  2265           \t|  0.0084055      \t|  0.0070354      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad                \t|  3.701e-06      \t|  2265           \t|  0.0083828      \t|  0.0070164      \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                  \t|  3.6895e-06     \t|  2265           \t|  0.0083567      \t|  0.0069946      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                         \t|  3.6812e-06     \t|  2265           \t|  0.0083379      \t|  0.0069788      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                       \t|  3.6796e-06     \t|  2265           \t|  0.0083343      \t|  0.0069759      \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                      \t|  3.6736e-06     \t|  2265           \t|  0.0083208      \t|  0.0069645      \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                            \t|  3.5814e-06     \t|  2265           \t|  0.0081119      \t|  0.0067897      \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                           \t|  3.5612e-06     \t|  2265           \t|  0.008066       \t|  0.0067513      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                 \t|  3.5247e-06     \t|  2265           \t|  0.0079835      \t|  0.0066822      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                               \t|  3.5081e-06     \t|  2265           \t|  0.0079459      \t|  0.0066508      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                 \t|  3.4592e-06     \t|  2265           \t|  0.0078351      \t|  0.006558       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                          \t|  3.4344e-06     \t|  2265           \t|  0.0077789      \t|  0.006511       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                            \t|  1.1845e-05     \t|  453            \t|  0.0053656      \t|  0.0044911      \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                              \t|  2.0733e-06     \t|  2265           \t|  0.004696       \t|  0.0039306      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                             \t|  1.9694e-06     \t|  2265           \t|  0.0044607      \t|  0.0037336      \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                          \t|  9.5696e-06     \t|  453            \t|  0.004335       \t|  0.0036284      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                              \t|  1.8986e-06     \t|  2265           \t|  0.0043004      \t|  0.0035995      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                           \t|  1.8762e-06     \t|  2265           \t|  0.0042495      \t|  0.0035569      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                         \t|  9.1898e-06     \t|  453            \t|  0.004163       \t|  0.0034844      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                  \t|  1.5273e-06     \t|  2265           \t|  0.0034593      \t|  0.0028955      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                            \t|  1.5197e-06     \t|  2265           \t|  0.0034422      \t|  0.0028811      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                     \t|  1.5144e-06     \t|  2265           \t|  0.0034301      \t|  0.002871       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                             \t|  1.4164e-06     \t|  2265           \t|  0.0032082      \t|  0.0026852      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                       \t|  1.4131e-06     \t|  2265           \t|  0.0032007      \t|  0.002679       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                     \t|  4.4789e-06     \t|  605            \t|  0.0027098      \t|  0.0022681      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                       \t|  4.0723e-06     \t|  605            \t|  0.0024638      \t|  0.0020622      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                       \t|  8.0803e-06     \t|  302            \t|  0.0024402      \t|  0.0020425      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                 \t|  5.3053e-06     \t|  453            \t|  0.0024033      \t|  0.0020116      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                             \t|  3.805e-06      \t|  605            \t|  0.002302       \t|  0.0019268      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                     \t|  3.6972e-06     \t|  605            \t|  0.0022368      \t|  0.0018722      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                     \t|  7.2857e-06     \t|  302            \t|  0.0022003      \t|  0.0018416      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step                                                                                                                                                                             \t|  0.0010895      \t|  2              \t|  0.0021789      \t|  0.0018238      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                               \t|  3.5686e-06     \t|  605            \t|  0.002159       \t|  0.0018071      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                       \t|  3.5546e-06     \t|  605            \t|  0.0021505      \t|  0.0018         \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                 \t|  3.5464e-06     \t|  605            \t|  0.0021456      \t|  0.0017959      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                               \t|  3.5375e-06     \t|  605            \t|  0.0021402      \t|  0.0017913      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                                \t|  3.5373e-06     \t|  605            \t|  0.0021401      \t|  0.0017912      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                  \t|  3.4896e-06     \t|  605            \t|  0.0021112      \t|  0.0017671      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                           \t|  4.4161e-06     \t|  453            \t|  0.0020005      \t|  0.0016744      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                             \t|  1.1965e-05     \t|  151            \t|  0.0018067      \t|  0.0015122      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start               \t|  3.9504e-06     \t|  453            \t|  0.0017895      \t|  0.0014978      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                          \t|  5.634e-06      \t|  302            \t|  0.0017015      \t|  0.0014241      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                               \t|  3.7351e-06     \t|  453            \t|  0.001692       \t|  0.0014162      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                            \t|  5.0958e-06     \t|  302            \t|  0.0015389      \t|  0.0012881      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                      \t|  4.7033e-06     \t|  302            \t|  0.0014204      \t|  0.0011889      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                           \t|  9.1426e-06     \t|  151            \t|  0.0013805      \t|  0.0011555      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                    \t|  4.4721e-06     \t|  302            \t|  0.0013506      \t|  0.0011304      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                    \t|  8.6388e-06     \t|  151            \t|  0.0013045      \t|  0.0010918      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end            \t|  4.2239e-06     \t|  302            \t|  0.0012756      \t|  0.0010677      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start          \t|  3.8565e-06     \t|  302            \t|  0.0011647      \t|  0.00097482     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                                \t|  6.7227e-06     \t|  151            \t|  0.0010151      \t|  0.00084966     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                 \t|  1.6329e-06     \t|  605            \t|  0.00098789     \t|  0.00082687     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                            \t|  6.2019e-06     \t|  151            \t|  0.00093649     \t|  0.00078385     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                   \t|  1.4741e-06     \t|  605            \t|  0.00089183     \t|  0.00074646     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                             \t|  1.8763e-06     \t|  453            \t|  0.00084995     \t|  0.00071141     \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                            \t|  2.7517e-06     \t|  302            \t|  0.000831       \t|  0.00069555     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                           \t|  1.6674e-06     \t|  453            \t|  0.00075535     \t|  0.00063223     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                            \t|  4.6342e-06     \t|  151            \t|  0.00069977     \t|  0.00058571     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                          \t|  4.2131e-06     \t|  151            \t|  0.00063618     \t|  0.00053249     \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                       \t|  4.1096e-06     \t|  151            \t|  0.00062054     \t|  0.0005194      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                          \t|  4.0309e-06     \t|  151            \t|  0.00060867     \t|  0.00050946     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start                \t|  4.0051e-06     \t|  151            \t|  0.00060477     \t|  0.0005062      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                        \t|  1.9887e-06     \t|  302            \t|  0.0006006      \t|  0.0005027      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                  \t|  3.8187e-06     \t|  151            \t|  0.00057663     \t|  0.00048264     \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                  \t|  0.00057489     \t|  1              \t|  0.00057489     \t|  0.00048119     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end            \t|  3.7125e-06     \t|  151            \t|  0.00056058     \t|  0.00046921     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                      \t|  3.563e-06      \t|  151            \t|  0.00053802     \t|  0.00045032     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start          \t|  3.4822e-06     \t|  151            \t|  0.00052582     \t|  0.00044011     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                      \t|  1.7288e-06     \t|  302            \t|  0.00052209     \t|  0.000437       \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                     \t|  3.3934e-06     \t|  151            \t|  0.0005124      \t|  0.00042888     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                   \t|  1.6522e-06     \t|  302            \t|  0.00049897     \t|  0.00041764     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                    \t|  3.2978e-06     \t|  151            \t|  0.00049796     \t|  0.0004168      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                              \t|  3.0264e-06     \t|  151            \t|  0.00045699     \t|  0.0003825      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                     \t|  2.4578e-06     \t|  151            \t|  0.00037113     \t|  0.00031064     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                            \t|  1.946e-06      \t|  151            \t|  0.00029384     \t|  0.00024595     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                 \t|  6.5843e-06     \t|  41             \t|  0.00026996     \t|  0.00022596     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                        \t|  1.7001e-06     \t|  151            \t|  0.00025672     \t|  0.00021487     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                   \t|  1.6805e-06     \t|  151            \t|  0.00025375     \t|  0.00021239     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                      \t|  1.6672e-06     \t|  151            \t|  0.00025175     \t|  0.00021072     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_start                                                                                                                                                                        \t|  0.00012391     \t|  2              \t|  0.00024783     \t|  0.00020743     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_end                                                                                                                                                                          \t|  9.95e-05       \t|  2              \t|  0.000199       \t|  0.00016656     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_end                                                                                                                                                                                \t|  0.00019538     \t|  1              \t|  0.00019538     \t|  0.00016354     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_start                                                                                                                                                                              \t|  0.00018743     \t|  1              \t|  0.00018743     \t|  0.00015688     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                            \t|  4.5613e-06     \t|  41             \t|  0.00018701     \t|  0.00015653     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                             \t|  0.00018631     \t|  1              \t|  0.00018631     \t|  0.00015595     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                         \t|  4.4585e-06     \t|  41             \t|  0.0001828      \t|  0.000153       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                               \t|  0.00017526     \t|  1              \t|  0.00017526     \t|  0.0001467      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                 \t|  4.1448e-06     \t|  41             \t|  0.00016994     \t|  0.00014224     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                           \t|  3.9217e-06     \t|  41             \t|  0.00016079     \t|  0.00013458     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                               \t|  0.00014216     \t|  1              \t|  0.00014216     \t|  0.00011899     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                           \t|  0.00010466     \t|  1              \t|  0.00010466     \t|  8.7602e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_train                                                                                                                                                            \t|  9.0664e-05     \t|  1              \t|  9.0664e-05     \t|  7.5886e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                             \t|  1.9794e-06     \t|  41             \t|  8.1155e-05     \t|  6.7927e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_eval                                                                                                                                                             \t|  7.45e-05       \t|  1              \t|  7.45e-05       \t|  6.2357e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                                \t|  1.5878e-05     \t|  2              \t|  3.1756e-05     \t|  2.658e-05      \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_start                                                                                                                                                                           \t|  8.9205e-06     \t|  2              \t|  1.7841e-05     \t|  1.4933e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_end                                                                                                                                                                             \t|  8.45e-06       \t|  2              \t|  1.69e-05       \t|  1.4145e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_start                                                                                                                                \t|  7.131e-06      \t|  2              \t|  1.4262e-05     \t|  1.1937e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_end                                                                                                                                  \t|  6.9975e-06     \t|  2              \t|  1.3995e-05     \t|  1.1714e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                           \t|  6.143e-06      \t|  2              \t|  1.2286e-05     \t|  1.0283e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                      \t|  6.058e-06      \t|  2              \t|  1.2116e-05     \t|  1.0141e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                 \t|  1.2081e-05     \t|  1              \t|  1.2081e-05     \t|  1.0112e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_end                  \t|  5.326e-06      \t|  2              \t|  1.0652e-05     \t|  8.9158e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_end                                                                                                                                                            \t|  5.3e-06        \t|  2              \t|  1.06e-05       \t|  8.8722e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_start                                                                                                                                                          \t|  5.095e-06      \t|  2              \t|  1.019e-05      \t|  8.5291e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_start                \t|  4.9295e-06     \t|  2              \t|  9.859e-06      \t|  8.252e-06      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                         \t|  4.8725e-06     \t|  2              \t|  9.745e-06      \t|  8.1566e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_start                                                                                                                                                                                 \t|  9.736e-06      \t|  1              \t|  9.736e-06      \t|  8.1491e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_end                                                                                                                                        \t|  8.661e-06      \t|  1              \t|  8.661e-06      \t|  7.2493e-06     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                                \t|  8.659e-06      \t|  1              \t|  8.659e-06      \t|  7.2476e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                            \t|  4.175e-06      \t|  2              \t|  8.35e-06       \t|  6.989e-06      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                              \t|  4.139e-06      \t|  2              \t|  8.278e-06      \t|  6.9287e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_end                                                                                                                                                                                   \t|  8.262e-06      \t|  1              \t|  8.262e-06      \t|  6.9153e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                   \t|  4.095e-06      \t|  2              \t|  8.19e-06       \t|  6.8551e-06     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                  \t|  7.795e-06      \t|  1              \t|  7.795e-06      \t|  6.5244e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                 \t|  3.884e-06      \t|  2              \t|  7.768e-06      \t|  6.5018e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.setup                              \t|  7.671e-06      \t|  1              \t|  7.671e-06      \t|  6.4207e-06     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                      \t|  3.807e-06      \t|  2              \t|  7.614e-06      \t|  6.3729e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                     \t|  3.725e-06      \t|  2              \t|  7.45e-06       \t|  6.2357e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                   \t|  3.6875e-06     \t|  2              \t|  7.375e-06      \t|  6.1729e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                           \t|  3.6685e-06     \t|  2              \t|  7.337e-06      \t|  6.1411e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model         \t|  3.5865e-06     \t|  2              \t|  7.173e-06      \t|  6.0038e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_end                                                                                                                                  \t|  7.133e-06      \t|  1              \t|  7.133e-06      \t|  5.9703e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_step_end                                                                                                                                                                  \t|  3.5395e-06     \t|  2              \t|  7.079e-06      \t|  5.9252e-06     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                         \t|  3.423e-06      \t|  2              \t|  6.846e-06      \t|  5.7301e-06     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                    \t|  3.4225e-06     \t|  2              \t|  6.845e-06      \t|  5.7293e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                        \t|  3.225e-06      \t|  2              \t|  6.45e-06       \t|  5.3987e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                         \t|  6.091e-06      \t|  1              \t|  6.091e-06      \t|  5.0982e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                          \t|  3.007e-06      \t|  2              \t|  6.014e-06      \t|  5.0337e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                        \t|  2.9395e-06     \t|  2              \t|  5.879e-06      \t|  4.9207e-06     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                           \t|  2.895e-06      \t|  2              \t|  5.79e-06       \t|  4.8463e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                        \t|  2.888e-06      \t|  2              \t|  5.776e-06      \t|  4.8345e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                   \t|  2.8315e-06     \t|  2              \t|  5.663e-06      \t|  4.74e-06       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                          \t|  5.543e-06      \t|  1              \t|  5.543e-06      \t|  4.6395e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                     \t|  5.336e-06      \t|  1              \t|  5.336e-06      \t|  4.4663e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_start                                                                                                                                \t|  5.283e-06      \t|  1              \t|  5.283e-06      \t|  4.4219e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_end                                                                                                                                                                  \t|  5.213e-06      \t|  1              \t|  5.213e-06      \t|  4.3633e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                       \t|  5.149e-06      \t|  1              \t|  5.149e-06      \t|  4.3097e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                            \t|  5.11e-06       \t|  1              \t|  5.11e-06       \t|  4.2771e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_end                                                                                                                                                                          \t|  5.019e-06      \t|  1              \t|  5.019e-06      \t|  4.2009e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                    \t|  4.859e-06      \t|  1              \t|  4.859e-06      \t|  4.067e-06      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_end                        \t|  4.775e-06      \t|  1              \t|  4.775e-06      \t|  3.9967e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_end                                                                                                                                                            \t|  4.69e-06       \t|  1              \t|  4.69e-06       \t|  3.9255e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_end                  \t|  4.63e-06       \t|  1              \t|  4.63e-06       \t|  3.8753e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_end                                                                                                                                                                             \t|  4.563e-06      \t|  1              \t|  4.563e-06      \t|  3.8192e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_start                                                                                                                                      \t|  4.551e-06      \t|  1              \t|  4.551e-06      \t|  3.8092e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_start                                                                                                                                                            \t|  2.2595e-06     \t|  2              \t|  4.519e-06      \t|  3.7824e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_start                                                                                                                                                                        \t|  4.417e-06      \t|  1              \t|  4.417e-06      \t|  3.697e-06      \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                       \t|  4.331e-06      \t|  1              \t|  4.331e-06      \t|  3.6251e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_load_checkpoint                                                                                                                                                             \t|  4.288e-06      \t|  1              \t|  4.288e-06      \t|  3.5891e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                       \t|  4.274e-06      \t|  1              \t|  4.274e-06      \t|  3.5774e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step_end                                                                                                                                                                         \t|  2.137e-06      \t|  2              \t|  4.274e-06      \t|  3.5774e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_start                                                                                                                                                                           \t|  4.135e-06      \t|  1              \t|  4.135e-06      \t|  3.461e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_end                                                                                                                                                              \t|  2.055e-06      \t|  2              \t|  4.11e-06       \t|  3.4401e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                     \t|  4.041e-06      \t|  1              \t|  4.041e-06      \t|  3.3823e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                       \t|  1.998e-06      \t|  2              \t|  3.996e-06      \t|  3.3447e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                       \t|  3.839e-06      \t|  1              \t|  3.839e-06      \t|  3.2133e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_dataloader                                                                                                                                                             \t|  3.716e-06      \t|  1              \t|  3.716e-06      \t|  3.1103e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                 \t|  3.688e-06      \t|  1              \t|  3.688e-06      \t|  3.0869e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                  \t|  3.493e-06      \t|  1              \t|  3.493e-06      \t|  2.9237e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                               \t|  3.449e-06      \t|  1              \t|  3.449e-06      \t|  2.8868e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_start                                                                                                                                                                \t|  3.406e-06      \t|  1              \t|  3.406e-06      \t|  2.8508e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                               \t|  3.169e-06      \t|  1              \t|  3.169e-06      \t|  2.6525e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                              \t|  3.159e-06      \t|  1              \t|  3.159e-06      \t|  2.6441e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup \t|  3.113e-06      \t|  1              \t|  3.113e-06      \t|  2.6056e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                          \t|  1.5555e-06     \t|  2              \t|  3.111e-06      \t|  2.6039e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start          \t|  3.103e-06      \t|  1              \t|  3.103e-06      \t|  2.5972e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_start                      \t|  3.091e-06      \t|  1              \t|  3.091e-06      \t|  2.5872e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                 \t|  3.078e-06      \t|  1              \t|  3.078e-06      \t|  2.5763e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                       \t|  3.03e-06       \t|  1              \t|  3.03e-06       \t|  2.5361e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                      \t|  3.017e-06      \t|  1              \t|  3.017e-06      \t|  2.5252e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_accelerator_backend_setup\t|  3.012e-06      \t|  1              \t|  3.012e-06      \t|  2.5211e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_start                \t|  3.006e-06      \t|  1              \t|  3.006e-06      \t|  2.516e-06      \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                     \t|  2.994e-06      \t|  1              \t|  2.994e-06      \t|  2.506e-06      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                   \t|  2.994e-06      \t|  1              \t|  2.994e-06      \t|  2.506e-06      \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                    \t|  2.98e-06       \t|  1              \t|  2.98e-06       \t|  2.4943e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_start                                                                                                                                                          \t|  2.924e-06      \t|  1              \t|  2.924e-06      \t|  2.4474e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                    \t|  2.858e-06      \t|  1              \t|  2.858e-06      \t|  2.3922e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                         \t|  2.8e-06        \t|  1              \t|  2.8e-06        \t|  2.3436e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end            \t|  2.78e-06       \t|  1              \t|  2.78e-06       \t|  2.3269e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                            \t|  2.283e-06      \t|  1              \t|  2.283e-06      \t|  1.9109e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_end                                                                                                                                                              \t|  2.161e-06      \t|  1              \t|  2.161e-06      \t|  1.8088e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_end                                                                                                                                                                    \t|  1.989e-06      \t|  1              \t|  1.989e-06      \t|  1.6648e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_end                                                                                                                                                                           \t|  1.87e-06       \t|  1              \t|  1.87e-06       \t|  1.5652e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_start                                                                                                                                                                  \t|  1.839e-06      \t|  1              \t|  1.839e-06      \t|  1.5393e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                 \t|  1.685e-06      \t|  1              \t|  1.685e-06      \t|  1.4104e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                   \t|  1.681e-06      \t|  1              \t|  1.681e-06      \t|  1.407e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                     \t|  1.596e-06      \t|  1              \t|  1.596e-06      \t|  1.3359e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_start                                                                                                                                                            \t|  1.572e-06      \t|  1              \t|  1.572e-06      \t|  1.3158e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_start                                                                                                                                                                         \t|  1.466e-06      \t|  1              \t|  1.466e-06      \t|  1.227e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                      \t|  1.419e-06      \t|  1              \t|  1.419e-06      \t|  1.1877e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                   \t|  1.375e-06      \t|  1              \t|  1.375e-06      \t|  1.1509e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                        \t|  1.345e-06      \t|  1              \t|  1.345e-06      \t|  1.1258e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                          \t|  1.325e-06      \t|  1              \t|  1.325e-06      \t|  1.109e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                        \t|  1.121e-06      \t|  1              \t|  1.121e-06      \t|  9.3828e-07     \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 64257.05it/s]\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 25707.05it/s]\n",
      "Getting embeddings for split ['fold02'], which has 1395 instances.\n",
      "Restoring states from the checkpoint path at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_9/checkpoints/epoch=344-step=1725.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_9/checkpoints/epoch=344-step=1725.ckpt\n",
      "Testing DataLoader 0:   0% 0/2 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 395.89it/s]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 46.93it/s] \n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       Test metric             DataLoader 0\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       test_aucroc          0.9591241195762334\n",
      "      test_d_prime           3.180630890263927\n",
      "        test_loss           0.5754764080047607\n",
      "        test_mAP            0.8422802671924309\n",
      "       test_score           0.8035842180252075\n",
      "      test_top1_acc         0.8035842180252075\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "TEST Profiler Report\n",
      "\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                               \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                                \t|  -              \t|  115592         \t|  82.45          \t|  100 %          \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                   \t|  0.080348       \t|  405            \t|  32.541         \t|  39.467         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                   \t|  0.0038725      \t|  2025           \t|  7.8418         \t|  9.5109         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                 \t|  0.003557       \t|  2025           \t|  7.2029         \t|  8.736          \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                           \t|  0.030745       \t|  135            \t|  4.1506         \t|  5.0341         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                         \t|  0.0015038      \t|  2025           \t|  3.0452         \t|  3.6934         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                  \t|  0.014488       \t|  135            \t|  1.9559         \t|  2.3722         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                              \t|  0.00087417     \t|  2025           \t|  1.7702         \t|  2.147          \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                   \t|  0.00031427     \t|  2025           \t|  0.6364         \t|  0.77185        \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                 \t|  0.00018404     \t|  2025           \t|  0.37267        \t|  0.452          \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                       \t|  9.927e-05      \t|  2297           \t|  0.22802        \t|  0.27656        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                            \t|  0.00010875     \t|  2025           \t|  0.22022        \t|  0.26709        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                       \t|  0.00066298     \t|  270            \t|  0.179          \t|  0.2171         \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                         \t|  0.00036892     \t|  405            \t|  0.14941        \t|  0.18121        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                       \t|  0.00024895     \t|  405            \t|  0.10082        \t|  0.12228        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                          \t|  0.0005788      \t|  135            \t|  0.078138       \t|  0.094769       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                  \t|  0.00047781     \t|  135            \t|  0.064504       \t|  0.078234       \t|\n",
      "|  run_test_evaluation                                                                                                                                                                                                  \t|  0.054319       \t|  1              \t|  0.054319       \t|  0.065881       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                    \t|  0.00017172     \t|  270            \t|  0.046363       \t|  0.056232       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                  \t|  0.00013968     \t|  270            \t|  0.037713       \t|  0.04574        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                        \t|  0.00025505     \t|  135            \t|  0.034432       \t|  0.041761       \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_epoch_end                                                                                                                                                                 \t|  0.032363       \t|  1              \t|  0.032363       \t|  0.039252       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                  \t|  7.2477e-06     \t|  2025           \t|  0.014677       \t|  0.017801       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                      \t|  8.4255e-05     \t|  135            \t|  0.011374       \t|  0.013796       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                                \t|  5.3551e-06     \t|  2025           \t|  0.010844       \t|  0.013152       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                 \t|  2.6657e-05     \t|  405            \t|  0.010796       \t|  0.013094       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                     \t|  5.1824e-06     \t|  2025           \t|  0.010494       \t|  0.012728       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                       \t|  7.5793e-05     \t|  135            \t|  0.010232       \t|  0.01241        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                       \t|  4.6794e-06     \t|  2025           \t|  0.0094759      \t|  0.011493       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                 \t|  4.3791e-06     \t|  2025           \t|  0.0088677      \t|  0.010755       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                           \t|  4.2109e-06     \t|  2025           \t|  0.0085271      \t|  0.010342       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                          \t|  4.193e-06      \t|  2025           \t|  0.0084907      \t|  0.010298       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                            \t|  4.1232e-06     \t|  2025           \t|  0.0083495      \t|  0.010127       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                   \t|  4.0653e-06     \t|  2025           \t|  0.0082322      \t|  0.0099845      \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                             \t|  4.0047e-06     \t|  2025           \t|  0.0081096      \t|  0.0098357      \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                             \t|  3.9541e-06     \t|  2025           \t|  0.008007       \t|  0.0097113      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                        \t|  3.8949e-06     \t|  2025           \t|  0.0078872      \t|  0.0095659      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                           \t|  3.8939e-06     \t|  2025           \t|  0.0078851      \t|  0.0095634      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                  \t|  3.7847e-06     \t|  2025           \t|  0.0076641      \t|  0.0092953      \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                                \t|  3.7538e-06     \t|  2025           \t|  0.0076014      \t|  0.0092194      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                     \t|  3.7396e-06     \t|  2025           \t|  0.0075726      \t|  0.0091844      \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                  \t|  3.7318e-06     \t|  2025           \t|  0.0075569      \t|  0.0091654      \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                               \t|  3.7165e-06     \t|  2025           \t|  0.007526       \t|  0.0091279      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step           \t|  3.7058e-06     \t|  2025           \t|  0.0075042      \t|  0.0091015      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                     \t|  3.6909e-06     \t|  2025           \t|  0.007474       \t|  0.0090648      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                       \t|  3.6828e-06     \t|  2025           \t|  0.0074576      \t|  0.009045       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad                \t|  3.6682e-06     \t|  2025           \t|  0.0074282      \t|  0.0090093      \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                           \t|  3.6627e-06     \t|  2025           \t|  0.0074169      \t|  0.0089956      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                         \t|  3.6406e-06     \t|  2025           \t|  0.0073721      \t|  0.0089413      \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                      \t|  3.6285e-06     \t|  2025           \t|  0.0073477      \t|  0.0089116      \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                            \t|  3.592e-06      \t|  2025           \t|  0.0072739      \t|  0.0088221      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                 \t|  3.5771e-06     \t|  2025           \t|  0.0072435      \t|  0.0087853      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                               \t|  3.5104e-06     \t|  2025           \t|  0.0071085      \t|  0.0086215      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                          \t|  3.4943e-06     \t|  2025           \t|  0.007076       \t|  0.0085821      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                 \t|  3.4814e-06     \t|  2025           \t|  0.0070498      \t|  0.0085504      \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                            \t|  1.1731e-05     \t|  405            \t|  0.004751       \t|  0.0057622      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                            \t|  2.288e-06      \t|  2025           \t|  0.0046332      \t|  0.0056194      \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                              \t|  2.0628e-06     \t|  2025           \t|  0.0041772      \t|  0.0050663      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                             \t|  1.9614e-06     \t|  2025           \t|  0.0039718      \t|  0.0048172      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                           \t|  1.8941e-06     \t|  2025           \t|  0.0038355      \t|  0.0046518      \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                          \t|  9.3916e-06     \t|  405            \t|  0.0038036      \t|  0.0046132      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                              \t|  1.8644e-06     \t|  2025           \t|  0.0037754      \t|  0.004579       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                         \t|  8.951e-06      \t|  405            \t|  0.0036251      \t|  0.0043968      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                     \t|  1.538e-06      \t|  2025           \t|  0.0031145      \t|  0.0037775      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                       \t|  1.4819e-06     \t|  2025           \t|  0.0030008      \t|  0.0036395      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                  \t|  1.4456e-06     \t|  2025           \t|  0.0029272      \t|  0.0035503      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                             \t|  1.4301e-06     \t|  2025           \t|  0.0028959      \t|  0.0035123      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                     \t|  4.4654e-06     \t|  541            \t|  0.0024158      \t|  0.00293        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                 \t|  5.4076e-06     \t|  405            \t|  0.0021901      \t|  0.0026562      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                       \t|  3.9953e-06     \t|  541            \t|  0.0021615      \t|  0.0026216      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                       \t|  7.8475e-06     \t|  270            \t|  0.0021188      \t|  0.0025698      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                             \t|  3.6416e-06     \t|  541            \t|  0.0019701      \t|  0.0023894      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                     \t|  7.132e-06      \t|  270            \t|  0.0019257      \t|  0.0023355      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                     \t|  3.5552e-06     \t|  541            \t|  0.0019233      \t|  0.0023327      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                       \t|  3.5378e-06     \t|  541            \t|  0.0019139      \t|  0.0023213      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                 \t|  3.534e-06      \t|  541            \t|  0.0019119      \t|  0.0023188      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                                \t|  3.5152e-06     \t|  541            \t|  0.0019017      \t|  0.0023065      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                  \t|  3.4795e-06     \t|  541            \t|  0.0018824      \t|  0.0022831      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                               \t|  3.4633e-06     \t|  541            \t|  0.0018737      \t|  0.0022725      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                               \t|  3.4066e-06     \t|  541            \t|  0.001843       \t|  0.0022353      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step                                                                                                                                                                             \t|  0.00088676     \t|  2              \t|  0.0017735      \t|  0.002151       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                           \t|  4.2872e-06     \t|  405            \t|  0.0017363      \t|  0.0021059      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                             \t|  1.2004e-05     \t|  135            \t|  0.0016205      \t|  0.0019654      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start               \t|  3.9786e-06     \t|  405            \t|  0.0016113      \t|  0.0019543      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                               \t|  3.7632e-06     \t|  405            \t|  0.0015241      \t|  0.0018485      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                          \t|  5.5216e-06     \t|  270            \t|  0.0014908      \t|  0.0018082      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                            \t|  4.9707e-06     \t|  270            \t|  0.0013421      \t|  0.0016277      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                           \t|  9.3655e-06     \t|  135            \t|  0.0012643      \t|  0.0015335      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                      \t|  4.3798e-06     \t|  270            \t|  0.0011826      \t|  0.0014343      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                    \t|  4.2491e-06     \t|  270            \t|  0.0011473      \t|  0.0013914      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end            \t|  4.0355e-06     \t|  270            \t|  0.0010896      \t|  0.0013215      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start          \t|  3.7838e-06     \t|  270            \t|  0.0010216      \t|  0.0012391      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                                \t|  6.5417e-06     \t|  135            \t|  0.00088313     \t|  0.0010711      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                 \t|  1.5791e-06     \t|  541            \t|  0.00085432     \t|  0.0010362      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                  \t|  0.0008341      \t|  1              \t|  0.0008341      \t|  0.0010116      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                            \t|  5.9331e-06     \t|  135            \t|  0.00080096     \t|  0.00097145     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                   \t|  1.4574e-06     \t|  541            \t|  0.00078847     \t|  0.0009563      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                             \t|  1.9329e-06     \t|  405            \t|  0.00078283     \t|  0.00094946     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                           \t|  1.7417e-06     \t|  405            \t|  0.00070537     \t|  0.00085551     \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                            \t|  2.5468e-06     \t|  270            \t|  0.00068764     \t|  0.000834       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                            \t|  4.5265e-06     \t|  135            \t|  0.00061108     \t|  0.00074114     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                          \t|  4.1001e-06     \t|  135            \t|  0.00055352     \t|  0.00067133     \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                    \t|  3.914e-06      \t|  135            \t|  0.0005284      \t|  0.00064086     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                        \t|  1.9566e-06     \t|  270            \t|  0.00052828     \t|  0.00064072     \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                       \t|  3.831e-06      \t|  135            \t|  0.00051719     \t|  0.00062727     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start                \t|  3.83e-06       \t|  135            \t|  0.00051704     \t|  0.0006271      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                          \t|  3.8056e-06     \t|  135            \t|  0.00051375     \t|  0.0006231      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end            \t|  3.6691e-06     \t|  135            \t|  0.00049532     \t|  0.00060075     \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                  \t|  3.5105e-06     \t|  135            \t|  0.00047391     \t|  0.00057479     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                      \t|  3.4282e-06     \t|  135            \t|  0.0004628      \t|  0.00056131     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start          \t|  3.403e-06      \t|  135            \t|  0.0004594      \t|  0.00055719     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                    \t|  3.3859e-06     \t|  135            \t|  0.0004571      \t|  0.00055439     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                      \t|  1.6778e-06     \t|  270            \t|  0.00045302     \t|  0.00054944     \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                     \t|  3.3034e-06     \t|  135            \t|  0.00044596     \t|  0.00054089     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                              \t|  3.2504e-06     \t|  135            \t|  0.00043881     \t|  0.00053221     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                   \t|  1.5667e-06     \t|  270            \t|  0.00042302     \t|  0.00051306     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                     \t|  2.0979e-06     \t|  135            \t|  0.00028322     \t|  0.0003435      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                 \t|  6.1042e-06     \t|  45             \t|  0.00027469     \t|  0.00033316     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_start                                                                                                                                                                        \t|  0.00012665     \t|  2              \t|  0.0002533      \t|  0.00030721     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                            \t|  1.8663e-06     \t|  135            \t|  0.00025195     \t|  0.00030558     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                   \t|  1.7926e-06     \t|  135            \t|  0.000242       \t|  0.00029352     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                      \t|  1.7733e-06     \t|  135            \t|  0.0002394      \t|  0.00029035     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                               \t|  0.0002377      \t|  1              \t|  0.0002377      \t|  0.00028829     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                        \t|  1.7107e-06     \t|  135            \t|  0.00023095     \t|  0.0002801      \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_start                                                                                                                                                                              \t|  0.00022551     \t|  1              \t|  0.00022551     \t|  0.00027351     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                             \t|  0.00022308     \t|  1              \t|  0.00022308     \t|  0.00027056     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                               \t|  0.00020426     \t|  1              \t|  0.00020426     \t|  0.00024774     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                         \t|  4.0364e-06     \t|  45             \t|  0.00018164     \t|  0.0002203      \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_end                                                                                                                                                                          \t|  8.5186e-05     \t|  2              \t|  0.00017037     \t|  0.00020664     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                            \t|  3.7016e-06     \t|  45             \t|  0.00016657     \t|  0.00020203     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                           \t|  3.4865e-06     \t|  45             \t|  0.00015689     \t|  0.00019029     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                 \t|  3.4844e-06     \t|  45             \t|  0.0001568      \t|  0.00019017     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_end                                                                                                                                                                                \t|  0.00015116     \t|  1              \t|  0.00015116     \t|  0.00018333     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                           \t|  0.00011637     \t|  1              \t|  0.00011637     \t|  0.00014114     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_eval                                                                                                                                                             \t|  9.3727e-05     \t|  1              \t|  9.3727e-05     \t|  0.00011368     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                             \t|  1.7948e-06     \t|  45             \t|  8.0765e-05     \t|  9.7956e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_train                                                                                                                                                            \t|  7.3248e-05     \t|  1              \t|  7.3248e-05     \t|  8.8839e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                       \t|  1.9891e-05     \t|  1              \t|  1.9891e-05     \t|  2.4125e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                     \t|  1.8716e-05     \t|  1              \t|  1.8716e-05     \t|  2.27e-05       \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                      \t|  8.733e-06      \t|  2              \t|  1.7466e-05     \t|  2.1184e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                  \t|  1.6041e-05     \t|  1              \t|  1.6041e-05     \t|  1.9455e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                 \t|  1.4124e-05     \t|  1              \t|  1.4124e-05     \t|  1.713e-05      \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_start                                                                                                                                                                           \t|  7.0535e-06     \t|  2              \t|  1.4107e-05     \t|  1.711e-05      \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_end                                                                                                                                                                             \t|  6.83e-06       \t|  2              \t|  1.366e-05      \t|  1.6568e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                     \t|  1.344e-05      \t|  1              \t|  1.344e-05      \t|  1.6301e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                         \t|  6.1095e-06     \t|  2              \t|  1.2219e-05     \t|  1.482e-05      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                                \t|  6.07e-06       \t|  2              \t|  1.214e-05      \t|  1.4724e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                              \t|  5.8605e-06     \t|  2              \t|  1.1721e-05     \t|  1.4216e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                            \t|  5.0355e-06     \t|  2              \t|  1.0071e-05     \t|  1.2215e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                 \t|  5.0035e-06     \t|  2              \t|  1.0007e-05     \t|  1.2137e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                           \t|  4.9635e-06     \t|  2              \t|  9.927e-06      \t|  1.204e-05      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_start                                                                                                                                \t|  4.938e-06      \t|  2              \t|  9.876e-06      \t|  1.1978e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.setup                              \t|  9.803e-06      \t|  1              \t|  9.803e-06      \t|  1.189e-05      \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                         \t|  4.7875e-06     \t|  2              \t|  9.575e-06      \t|  1.1613e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_end                                                                                                                                                                                   \t|  9.407e-06      \t|  1              \t|  9.407e-06      \t|  1.1409e-05     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                    \t|  4.536e-06      \t|  2              \t|  9.072e-06      \t|  1.1003e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                        \t|  4.4685e-06     \t|  2              \t|  8.937e-06      \t|  1.0839e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                   \t|  4.4395e-06     \t|  2              \t|  8.879e-06      \t|  1.0769e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model         \t|  4.432e-06      \t|  2              \t|  8.864e-06      \t|  1.0751e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                                \t|  8.807e-06      \t|  1              \t|  8.807e-06      \t|  1.0682e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                          \t|  8.772e-06      \t|  1              \t|  8.772e-06      \t|  1.0639e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_end                                                                                                                                  \t|  4.3675e-06     \t|  2              \t|  8.735e-06      \t|  1.0594e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                          \t|  4.3565e-06     \t|  2              \t|  8.713e-06      \t|  1.0568e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                        \t|  4.261e-06      \t|  2              \t|  8.522e-06      \t|  1.0336e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_end                                                                                                                                        \t|  8.521e-06      \t|  1              \t|  8.521e-06      \t|  1.0335e-05     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                           \t|  4.1815e-06     \t|  2              \t|  8.363e-06      \t|  1.0143e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_start                                                                                                                                                                                 \t|  8.231e-06      \t|  1              \t|  8.231e-06      \t|  9.983e-06      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                       \t|  7.356e-06      \t|  1              \t|  7.356e-06      \t|  8.9217e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                        \t|  3.669e-06      \t|  2              \t|  7.338e-06      \t|  8.8999e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                   \t|  3.5955e-06     \t|  2              \t|  7.191e-06      \t|  8.7216e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_start                                                                                                                                                          \t|  3.405e-06      \t|  2              \t|  6.81e-06       \t|  8.2595e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_start                                                                                                                                      \t|  6.675e-06      \t|  1              \t|  6.675e-06      \t|  8.0958e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_end                                                                                                                                                            \t|  3.3305e-06     \t|  2              \t|  6.661e-06      \t|  8.0788e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_end                  \t|  3.2645e-06     \t|  2              \t|  6.529e-06      \t|  7.9187e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                   \t|  3.2415e-06     \t|  2              \t|  6.483e-06      \t|  7.8629e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                         \t|  6.433e-06      \t|  1              \t|  6.433e-06      \t|  7.8023e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_start                \t|  3.1905e-06     \t|  2              \t|  6.381e-06      \t|  7.7392e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                       \t|  6.022e-06      \t|  1              \t|  6.022e-06      \t|  7.3038e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                       \t|  5.958e-06      \t|  1              \t|  5.958e-06      \t|  7.2262e-06     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                      \t|  2.9595e-06     \t|  2              \t|  5.919e-06      \t|  7.1789e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                 \t|  5.87e-06       \t|  1              \t|  5.87e-06       \t|  7.1194e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                           \t|  2.9305e-06     \t|  2              \t|  5.861e-06      \t|  7.1085e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                     \t|  2.917e-06      \t|  2              \t|  5.834e-06      \t|  7.0758e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                     \t|  5.774e-06      \t|  1              \t|  5.774e-06      \t|  7.003e-06      \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                  \t|  5.478e-06      \t|  1              \t|  5.478e-06      \t|  6.644e-06      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                       \t|  5.106e-06      \t|  1              \t|  5.106e-06      \t|  6.1928e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_end                                                                                                                                  \t|  5.094e-06      \t|  1              \t|  5.094e-06      \t|  6.1783e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                      \t|  5.024e-06      \t|  1              \t|  5.024e-06      \t|  6.0934e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                               \t|  4.985e-06      \t|  1              \t|  4.985e-06      \t|  6.0461e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_step_end                                                                                                                                                                  \t|  2.478e-06      \t|  2              \t|  4.956e-06      \t|  6.0109e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                               \t|  4.947e-06      \t|  1              \t|  4.947e-06      \t|  6e-06          \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start          \t|  4.943e-06      \t|  1              \t|  4.943e-06      \t|  5.9951e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                            \t|  4.895e-06      \t|  1              \t|  4.895e-06      \t|  5.9369e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_start                                                                                                                                                                \t|  4.895e-06      \t|  1              \t|  4.895e-06      \t|  5.9369e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                    \t|  4.817e-06      \t|  1              \t|  4.817e-06      \t|  5.8423e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_load_checkpoint                                                                                                                                                             \t|  4.768e-06      \t|  1              \t|  4.768e-06      \t|  5.7829e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_start                                                                                                                                \t|  4.72e-06       \t|  1              \t|  4.72e-06       \t|  5.7247e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_start                      \t|  4.647e-06      \t|  1              \t|  4.647e-06      \t|  5.6361e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                    \t|  4.619e-06      \t|  1              \t|  4.619e-06      \t|  5.6022e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup \t|  4.566e-06      \t|  1              \t|  4.566e-06      \t|  5.5379e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                          \t|  2.277e-06      \t|  2              \t|  4.554e-06      \t|  5.5233e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end            \t|  4.55e-06       \t|  1              \t|  4.55e-06       \t|  5.5185e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_dataloader                                                                                                                                                             \t|  4.549e-06      \t|  1              \t|  4.549e-06      \t|  5.5173e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_start                                                                                                                                                                           \t|  4.166e-06      \t|  1              \t|  4.166e-06      \t|  5.0527e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_start                \t|  4.117e-06      \t|  1              \t|  4.117e-06      \t|  4.9933e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_start                                                                                                                                                                        \t|  4.103e-06      \t|  1              \t|  4.103e-06      \t|  4.9763e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_start                                                                                                                                                          \t|  4.016e-06      \t|  1              \t|  4.016e-06      \t|  4.8708e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                              \t|  3.939e-06      \t|  1              \t|  3.939e-06      \t|  4.7774e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_accelerator_backend_setup\t|  3.761e-06      \t|  1              \t|  3.761e-06      \t|  4.5615e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                 \t|  3.555e-06      \t|  1              \t|  3.555e-06      \t|  4.3117e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_end                                                                                                                                                                  \t|  3.491e-06      \t|  1              \t|  3.491e-06      \t|  4.2341e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_end                                                                                                                                                                          \t|  3.447e-06      \t|  1              \t|  3.447e-06      \t|  4.1807e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                       \t|  1.7155e-06     \t|  2              \t|  3.431e-06      \t|  4.1613e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_end                        \t|  3.264e-06      \t|  1              \t|  3.264e-06      \t|  3.9587e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                   \t|  3.187e-06      \t|  1              \t|  3.187e-06      \t|  3.8654e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_end                                                                                                                                                            \t|  3.182e-06      \t|  1              \t|  3.182e-06      \t|  3.8593e-06     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                    \t|  3.162e-06      \t|  1              \t|  3.162e-06      \t|  3.835e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_end                                                                                                                                                              \t|  1.5495e-06     \t|  2              \t|  3.099e-06      \t|  3.7586e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_end                  \t|  3.035e-06      \t|  1              \t|  3.035e-06      \t|  3.681e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_start                                                                                                                                                            \t|  1.4805e-06     \t|  2              \t|  2.961e-06      \t|  3.5912e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_end                                                                                                                                                                             \t|  2.952e-06      \t|  1              \t|  2.952e-06      \t|  3.5803e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                         \t|  2.932e-06      \t|  1              \t|  2.932e-06      \t|  3.5561e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step_end                                                                                                                                                                         \t|  1.4075e-06     \t|  2              \t|  2.815e-06      \t|  3.4142e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                            \t|  2.769e-06      \t|  1              \t|  2.769e-06      \t|  3.3584e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                 \t|  2.569e-06      \t|  1              \t|  2.569e-06      \t|  3.1158e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                      \t|  2.42e-06       \t|  1              \t|  2.42e-06       \t|  2.9351e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                   \t|  2.357e-06      \t|  1              \t|  2.357e-06      \t|  2.8587e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                   \t|  2.215e-06      \t|  1              \t|  2.215e-06      \t|  2.6865e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_start                                                                                                                                                                         \t|  2.103e-06      \t|  1              \t|  2.103e-06      \t|  2.5506e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_start                                                                                                                                                                  \t|  2.014e-06      \t|  1              \t|  2.014e-06      \t|  2.4427e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                          \t|  1.983e-06      \t|  1              \t|  1.983e-06      \t|  2.4051e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                        \t|  1.81e-06       \t|  1              \t|  1.81e-06       \t|  2.1953e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_start                                                                                                                                                            \t|  1.809e-06      \t|  1              \t|  1.809e-06      \t|  2.194e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                        \t|  1.785e-06      \t|  1              \t|  1.785e-06      \t|  2.1649e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_end                                                                                                                                                              \t|  1.776e-06      \t|  1              \t|  1.776e-06      \t|  2.154e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_end                                                                                                                                                                    \t|  1.616e-06      \t|  1              \t|  1.616e-06      \t|  1.96e-06       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                     \t|  1.533e-06      \t|  1              \t|  1.533e-06      \t|  1.8593e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_end                                                                                                                                                                           \t|  1.273e-06      \t|  1              \t|  1.273e-06      \t|  1.544e-06      \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 108230.59it/s]\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 35382.24it/s]\n",
      "Getting embeddings for split ['fold03'], which has 1395 instances.\n",
      "Restoring states from the checkpoint path at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_10/checkpoints/epoch=293-step=1470.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_10/checkpoints/epoch=293-step=1470.ckpt\n",
      "Testing DataLoader 0:   0% 0/2 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 292.69it/s]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 33.80it/s] \n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       Test metric             DataLoader 0\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       test_aucroc          0.9735389632829503\n",
      "      test_d_prime           3.476533598795452\n",
      "        test_loss           0.4557825028896332\n",
      "        test_mAP            0.8980638408963632\n",
      "       test_score           0.8451613187789917\n",
      "      test_top1_acc         0.8451613187789917\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "TEST Profiler Report\n",
      "\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                               \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                                \t|  -              \t|  101055         \t|  49.197         \t|  100 %          \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                   \t|  0.080284       \t|  354            \t|  28.421         \t|  57.77          \t|\n",
      "|  run_training_batch                                                                                                                                                                                                   \t|  0.0038292      \t|  1770           \t|  6.7776         \t|  13.777         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                 \t|  0.0035143      \t|  1770           \t|  6.2203         \t|  12.644         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                           \t|  0.031879       \t|  118            \t|  3.7617         \t|  7.6463         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                         \t|  0.0014987      \t|  1770           \t|  2.6527         \t|  5.3921         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                  \t|  0.014903       \t|  118            \t|  1.7585         \t|  3.5745         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                              \t|  0.00084921     \t|  1770           \t|  1.5031         \t|  3.0553         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                   \t|  0.00031222     \t|  1770           \t|  0.55262        \t|  1.1233         \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                 \t|  0.00018363     \t|  1770           \t|  0.32502        \t|  0.66065        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                       \t|  9.9327e-05     \t|  2008           \t|  0.19945        \t|  0.40541        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                            \t|  0.00010619     \t|  1770           \t|  0.18795        \t|  0.38205        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                       \t|  0.00064095     \t|  236            \t|  0.15127        \t|  0.30747        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                         \t|  0.00036277     \t|  354            \t|  0.12842        \t|  0.26103        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                       \t|  0.00024587     \t|  354            \t|  0.087039       \t|  0.17692        \t|\n",
      "|  run_test_evaluation                                                                                                                                                                                                  \t|  0.072781       \t|  1              \t|  0.072781       \t|  0.14794        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                          \t|  0.0005859      \t|  118            \t|  0.069136       \t|  0.14053        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                  \t|  0.00047805     \t|  118            \t|  0.05641        \t|  0.11466        \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_epoch_end                                                                                                                                                                 \t|  0.044748       \t|  1              \t|  0.044748       \t|  0.090958       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                    \t|  0.00016506     \t|  236            \t|  0.038953       \t|  0.079178       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                  \t|  0.00014104     \t|  236            \t|  0.033286       \t|  0.067659       \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                        \t|  0.00025226     \t|  118            \t|  0.029767       \t|  0.060506       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                  \t|  6.8373e-06     \t|  1770           \t|  0.012102       \t|  0.024599       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                      \t|  8.3097e-05     \t|  118            \t|  0.0098055      \t|  0.019931       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                 \t|  2.6624e-05     \t|  354            \t|  0.0094248      \t|  0.019158       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                                \t|  5.321e-06      \t|  1770           \t|  0.0094182      \t|  0.019144       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                     \t|  5.1777e-06     \t|  1770           \t|  0.0091646      \t|  0.018628       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                       \t|  7.393e-05      \t|  118            \t|  0.0087238      \t|  0.017732       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                       \t|  4.6222e-06     \t|  1770           \t|  0.0081813      \t|  0.01663        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                 \t|  4.4009e-06     \t|  1770           \t|  0.0077897      \t|  0.015834       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                  \t|  4.2533e-06     \t|  1770           \t|  0.0075284      \t|  0.015303       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step           \t|  4.1645e-06     \t|  1770           \t|  0.0073711      \t|  0.014983       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                           \t|  4.1131e-06     \t|  1770           \t|  0.0072802      \t|  0.014798       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                          \t|  4.0877e-06     \t|  1770           \t|  0.0072353      \t|  0.014707       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                            \t|  3.9419e-06     \t|  1770           \t|  0.0069772      \t|  0.014182       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                             \t|  3.8655e-06     \t|  1770           \t|  0.006842       \t|  0.013907       \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                             \t|  3.8357e-06     \t|  1770           \t|  0.0067892      \t|  0.0138         \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                        \t|  3.7767e-06     \t|  1770           \t|  0.0066848      \t|  0.013588       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                               \t|  3.7045e-06     \t|  1770           \t|  0.006557       \t|  0.013328       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                   \t|  3.7036e-06     \t|  1770           \t|  0.0065554      \t|  0.013325       \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                                \t|  3.6962e-06     \t|  1770           \t|  0.0065423      \t|  0.013298       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                       \t|  3.6785e-06     \t|  1770           \t|  0.006511       \t|  0.013235       \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                  \t|  3.6606e-06     \t|  1770           \t|  0.0064793      \t|  0.01317        \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                     \t|  3.6433e-06     \t|  1770           \t|  0.0064486      \t|  0.013108       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad                \t|  3.6266e-06     \t|  1770           \t|  0.0064191      \t|  0.013048       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                     \t|  3.6178e-06     \t|  1770           \t|  0.0064035      \t|  0.013016       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                         \t|  3.5966e-06     \t|  1770           \t|  0.006366       \t|  0.01294        \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                           \t|  3.5939e-06     \t|  1770           \t|  0.0063611      \t|  0.01293        \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                      \t|  3.5854e-06     \t|  1770           \t|  0.0063462      \t|  0.0129         \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                            \t|  3.5256e-06     \t|  1770           \t|  0.0062404      \t|  0.012685       \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                           \t|  3.4934e-06     \t|  1770           \t|  0.0061833      \t|  0.012569       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                 \t|  3.4855e-06     \t|  1770           \t|  0.0061693      \t|  0.01254        \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                               \t|  3.4796e-06     \t|  1770           \t|  0.0061589      \t|  0.012519       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                 \t|  3.4647e-06     \t|  1770           \t|  0.0061325      \t|  0.012465       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                          \t|  3.3913e-06     \t|  1770           \t|  0.0060025      \t|  0.012201       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                            \t|  1.2005e-05     \t|  354            \t|  0.0042498      \t|  0.0086384      \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                              \t|  2.038e-06      \t|  1770           \t|  0.0036073      \t|  0.0073324      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                         \t|  9.9214e-06     \t|  354            \t|  0.0035122      \t|  0.0071391      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                             \t|  1.9214e-06     \t|  1770           \t|  0.0034009      \t|  0.0069128      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                           \t|  1.8806e-06     \t|  1770           \t|  0.0033286      \t|  0.0067659      \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                          \t|  9.3971e-06     \t|  354            \t|  0.0033266      \t|  0.0067618      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                              \t|  1.8703e-06     \t|  1770           \t|  0.0033105      \t|  0.0067291      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                             \t|  1.8269e-06     \t|  1770           \t|  0.0032337      \t|  0.006573       \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                     \t|  1.5399e-06     \t|  1770           \t|  0.0027257      \t|  0.0055404      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                            \t|  1.4968e-06     \t|  1770           \t|  0.0026494      \t|  0.0053853      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                  \t|  1.4461e-06     \t|  1770           \t|  0.0025596      \t|  0.0052029      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                       \t|  1.4234e-06     \t|  1770           \t|  0.0025195      \t|  0.0051213      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step                                                                                                                                                                             \t|  0.0010948      \t|  2              \t|  0.0021895      \t|  0.0044506      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                     \t|  4.4393e-06     \t|  473            \t|  0.0020998      \t|  0.0042681      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                       \t|  4.1015e-06     \t|  473            \t|  0.00194        \t|  0.0039433      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                       \t|  8.0848e-06     \t|  236            \t|  0.001908       \t|  0.0038783      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                 \t|  5.3005e-06     \t|  354            \t|  0.0018764      \t|  0.003814       \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                             \t|  3.6928e-06     \t|  473            \t|  0.0017467      \t|  0.0035505      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                     \t|  7.3911e-06     \t|  236            \t|  0.0017443      \t|  0.0035456      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                               \t|  3.6111e-06     \t|  473            \t|  0.001708       \t|  0.0034719      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                     \t|  3.5598e-06     \t|  473            \t|  0.0016838      \t|  0.0034226      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                                \t|  3.4647e-06     \t|  473            \t|  0.0016388      \t|  0.0033312      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                       \t|  3.4193e-06     \t|  473            \t|  0.0016173      \t|  0.0032875      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                 \t|  3.4183e-06     \t|  473            \t|  0.0016168      \t|  0.0032865      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                  \t|  3.4031e-06     \t|  473            \t|  0.0016096      \t|  0.0032719      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                               \t|  3.3652e-06     \t|  473            \t|  0.0015918      \t|  0.0032355      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                           \t|  4.1193e-06     \t|  354            \t|  0.0014582      \t|  0.0029641      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                             \t|  1.1914e-05     \t|  118            \t|  0.0014059      \t|  0.0028577      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start               \t|  3.9278e-06     \t|  354            \t|  0.0013904      \t|  0.0028263      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                               \t|  3.7164e-06     \t|  354            \t|  0.0013156      \t|  0.0026742      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                          \t|  5.4429e-06     \t|  236            \t|  0.0012845      \t|  0.002611       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                            \t|  4.8364e-06     \t|  236            \t|  0.0011414      \t|  0.00232        \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                           \t|  9.068e-06      \t|  118            \t|  0.00107        \t|  0.002175       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                      \t|  4.5051e-06     \t|  236            \t|  0.0010632      \t|  0.0021611      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end            \t|  4.3951e-06     \t|  236            \t|  0.0010373      \t|  0.0021084      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                    \t|  4.3066e-06     \t|  236            \t|  0.0010164      \t|  0.0020659      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start          \t|  3.6971e-06     \t|  236            \t|  0.00087253     \t|  0.0017735      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                                \t|  6.4351e-06     \t|  118            \t|  0.00075934     \t|  0.0015435      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                 \t|  1.5627e-06     \t|  473            \t|  0.00073917     \t|  0.0015025      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                            \t|  6.1465e-06     \t|  118            \t|  0.00072528     \t|  0.0014743      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                   \t|  1.4132e-06     \t|  473            \t|  0.00066846     \t|  0.0013588      \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                            \t|  2.6976e-06     \t|  236            \t|  0.00063664     \t|  0.0012941      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                             \t|  1.7823e-06     \t|  354            \t|  0.00063094     \t|  0.0012825      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                           \t|  1.6456e-06     \t|  354            \t|  0.00058255     \t|  0.0011841      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                  \t|  0.00055085     \t|  1              \t|  0.00055085     \t|  0.0011197      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                            \t|  4.5005e-06     \t|  118            \t|  0.00053106     \t|  0.0010795      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                       \t|  4.2229e-06     \t|  118            \t|  0.00049831     \t|  0.0010129      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                    \t|  4.0721e-06     \t|  118            \t|  0.00048051     \t|  0.00097671     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                          \t|  3.9355e-06     \t|  118            \t|  0.00046439     \t|  0.00094395     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                          \t|  3.8449e-06     \t|  118            \t|  0.0004537      \t|  0.00092221     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                      \t|  3.6615e-06     \t|  118            \t|  0.00043206     \t|  0.00087823     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                        \t|  1.821e-06      \t|  236            \t|  0.00042975     \t|  0.00087353     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start                \t|  3.6096e-06     \t|  118            \t|  0.00042594     \t|  0.00086578     \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                  \t|  3.6049e-06     \t|  118            \t|  0.00042537     \t|  0.00086464     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end            \t|  3.5686e-06     \t|  118            \t|  0.0004211      \t|  0.00085595     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start          \t|  3.4044e-06     \t|  118            \t|  0.00040172     \t|  0.00081657     \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                     \t|  3.2194e-06     \t|  118            \t|  0.00037989     \t|  0.00077218     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                    \t|  3.2065e-06     \t|  118            \t|  0.00037836     \t|  0.00076909     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                      \t|  1.5798e-06     \t|  236            \t|  0.00037283     \t|  0.00075784     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                   \t|  1.5425e-06     \t|  236            \t|  0.00036402     \t|  0.00073994     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                              \t|  2.8808e-06     \t|  118            \t|  0.00033993     \t|  0.00069097     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                 \t|  6.9074e-06     \t|  39             \t|  0.00026939     \t|  0.00054757     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_start                                                                                                                                                                        \t|  0.0001285      \t|  2              \t|  0.000257       \t|  0.0005224      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                     \t|  2.1144e-06     \t|  118            \t|  0.0002495      \t|  0.00050715     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_start                                                                                                                                                                              \t|  0.0002475      \t|  1              \t|  0.0002475      \t|  0.00050309     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                            \t|  1.9173e-06     \t|  118            \t|  0.00022624     \t|  0.00045987     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_end                                                                                                                                                                          \t|  0.00010088     \t|  2              \t|  0.00020175     \t|  0.0004101      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                      \t|  1.6679e-06     \t|  118            \t|  0.00019681     \t|  0.00040006     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                        \t|  1.6528e-06     \t|  118            \t|  0.00019503     \t|  0.00039643     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_end                                                                                                                                                                                \t|  0.00019152     \t|  1              \t|  0.00019152     \t|  0.0003893      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                   \t|  1.6046e-06     \t|  118            \t|  0.00018935     \t|  0.00038488     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                               \t|  0.00018395     \t|  1              \t|  0.00018395     \t|  0.00037392     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                             \t|  0.00018018     \t|  1              \t|  0.00018018     \t|  0.00036625     \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                         \t|  4.5089e-06     \t|  39             \t|  0.00017585     \t|  0.00035744     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                               \t|  0.00017563     \t|  1              \t|  0.00017563     \t|  0.000357       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                 \t|  3.8177e-06     \t|  39             \t|  0.00014889     \t|  0.00030265     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                           \t|  3.5898e-06     \t|  39             \t|  0.00014        \t|  0.00028458     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                            \t|  3.5094e-06     \t|  39             \t|  0.00013687     \t|  0.00027821     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_eval                                                                                                                                                             \t|  9.3721e-05     \t|  1              \t|  9.3721e-05     \t|  0.0001905      \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                           \t|  9.0617e-05     \t|  1              \t|  9.0617e-05     \t|  0.00018419     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_train                                                                                                                                                            \t|  8.4715e-05     \t|  1              \t|  8.4715e-05     \t|  0.0001722      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                             \t|  1.8697e-06     \t|  39             \t|  7.292e-05      \t|  0.00014822     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                              \t|  9.721e-06      \t|  2              \t|  1.9442e-05     \t|  3.9519e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_start                                                                                                                                                                                 \t|  1.7149e-05     \t|  1              \t|  1.7149e-05     \t|  3.4858e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_start                                                                                                                                                                           \t|  8.319e-06      \t|  2              \t|  1.6638e-05     \t|  3.3819e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_end                                                                                                                                                                             \t|  7.159e-06      \t|  2              \t|  1.4318e-05     \t|  2.9104e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                   \t|  1.4202e-05     \t|  1              \t|  1.4202e-05     \t|  2.8868e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                           \t|  7.0035e-06     \t|  2              \t|  1.4007e-05     \t|  2.8471e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_start                                                                                                                                \t|  6.953e-06      \t|  2              \t|  1.3906e-05     \t|  2.8266e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                      \t|  6.3115e-06     \t|  2              \t|  1.2623e-05     \t|  2.5658e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_end                                                                                                                                  \t|  5.9145e-06     \t|  2              \t|  1.1829e-05     \t|  2.4044e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                 \t|  1.1499e-05     \t|  1              \t|  1.1499e-05     \t|  2.3374e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                   \t|  4.9235e-06     \t|  2              \t|  9.847e-06      \t|  2.0016e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_start                                                                                                                                                          \t|  4.9085e-06     \t|  2              \t|  9.817e-06      \t|  1.9955e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_end                                                                                                                                                            \t|  4.6425e-06     \t|  2              \t|  9.285e-06      \t|  1.8873e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_start                \t|  4.5865e-06     \t|  2              \t|  9.173e-06      \t|  1.8646e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                     \t|  4.5725e-06     \t|  2              \t|  9.145e-06      \t|  1.8589e-05     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                      \t|  4.5385e-06     \t|  2              \t|  9.077e-06      \t|  1.845e-05      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                                \t|  4.502e-06      \t|  2              \t|  9.004e-06      \t|  1.8302e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                           \t|  4.455e-06      \t|  2              \t|  8.91e-06       \t|  1.8111e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_start                                                                                                                                      \t|  8.866e-06      \t|  1              \t|  8.866e-06      \t|  1.8022e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                                \t|  8.848e-06      \t|  1              \t|  8.848e-06      \t|  1.7985e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_end                                                                                                                                                                                   \t|  8.727e-06      \t|  1              \t|  8.727e-06      \t|  1.7739e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_end                  \t|  4.3605e-06     \t|  2              \t|  8.721e-06      \t|  1.7727e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                            \t|  4.3575e-06     \t|  2              \t|  8.715e-06      \t|  1.7715e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_end                                                                                                                                        \t|  8.668e-06      \t|  1              \t|  8.668e-06      \t|  1.7619e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                         \t|  4.163e-06      \t|  2              \t|  8.326e-06      \t|  1.6924e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                  \t|  8.111e-06      \t|  1              \t|  8.111e-06      \t|  1.6487e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                         \t|  8.022e-06      \t|  1              \t|  8.022e-06      \t|  1.6306e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.setup                              \t|  7.995e-06      \t|  1              \t|  7.995e-06      \t|  1.6251e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_step_end                                                                                                                                                                  \t|  3.596e-06      \t|  2              \t|  7.192e-06      \t|  1.4619e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_end                                                                                                                                  \t|  7.165e-06      \t|  1              \t|  7.165e-06      \t|  1.4564e-05     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                           \t|  3.355e-06      \t|  2              \t|  6.71e-06       \t|  1.3639e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                        \t|  3.315e-06      \t|  2              \t|  6.63e-06       \t|  1.3477e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                          \t|  3.245e-06      \t|  2              \t|  6.49e-06       \t|  1.3192e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                 \t|  3.2335e-06     \t|  2              \t|  6.467e-06      \t|  1.3145e-05     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                         \t|  3.1555e-06     \t|  2              \t|  6.311e-06      \t|  1.2828e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                       \t|  6.041e-06      \t|  1              \t|  6.041e-06      \t|  1.2279e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                          \t|  6.032e-06      \t|  1              \t|  6.032e-06      \t|  1.2261e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_start                                                                                                                                                                \t|  6.009e-06      \t|  1              \t|  6.009e-06      \t|  1.2214e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                   \t|  2.87e-06       \t|  2              \t|  5.74e-06       \t|  1.1667e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                        \t|  2.8545e-06     \t|  2              \t|  5.709e-06      \t|  1.1604e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                        \t|  2.837e-06      \t|  2              \t|  5.674e-06      \t|  1.1533e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                   \t|  2.8315e-06     \t|  2              \t|  5.663e-06      \t|  1.1511e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model         \t|  2.8115e-06     \t|  2              \t|  5.623e-06      \t|  1.143e-05      \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                    \t|  2.808e-06      \t|  2              \t|  5.616e-06      \t|  1.1415e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_start                                                                                                                                \t|  5.511e-06      \t|  1              \t|  5.511e-06      \t|  1.1202e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                 \t|  5.374e-06      \t|  1              \t|  5.374e-06      \t|  1.0924e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                 \t|  5.326e-06      \t|  1              \t|  5.326e-06      \t|  1.0826e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                     \t|  5.322e-06      \t|  1              \t|  5.322e-06      \t|  1.0818e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_end                                                                                                                                                                  \t|  5.249e-06      \t|  1              \t|  5.249e-06      \t|  1.0669e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                       \t|  2.572e-06      \t|  2              \t|  5.144e-06      \t|  1.0456e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_end                                                                                                                                                                          \t|  4.994e-06      \t|  1              \t|  4.994e-06      \t|  1.0151e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                       \t|  4.977e-06      \t|  1              \t|  4.977e-06      \t|  1.0117e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_end                        \t|  4.944e-06      \t|  1              \t|  4.944e-06      \t|  1.0049e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_start                      \t|  4.795e-06      \t|  1              \t|  4.795e-06      \t|  9.7466e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_start                                                                                                                                                                           \t|  4.772e-06      \t|  1              \t|  4.772e-06      \t|  9.6999e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_start                                                                                                                                                          \t|  4.765e-06      \t|  1              \t|  4.765e-06      \t|  9.6856e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_start                \t|  4.737e-06      \t|  1              \t|  4.737e-06      \t|  9.6287e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_end                                                                                                                                                            \t|  4.717e-06      \t|  1              \t|  4.717e-06      \t|  9.5881e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_start                                                                                                                                                                        \t|  4.659e-06      \t|  1              \t|  4.659e-06      \t|  9.4702e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                       \t|  4.647e-06      \t|  1              \t|  4.647e-06      \t|  9.4458e-06     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                    \t|  4.609e-06      \t|  1              \t|  4.609e-06      \t|  9.3685e-06     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_end                                                                                                                                                                             \t|  4.605e-06      \t|  1              \t|  4.605e-06      \t|  9.3604e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                         \t|  4.593e-06      \t|  1              \t|  4.593e-06      \t|  9.336e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_load_checkpoint                                                                                                                                                             \t|  4.482e-06      \t|  1              \t|  4.482e-06      \t|  9.1104e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_end                  \t|  4.46e-06       \t|  1              \t|  4.46e-06       \t|  9.0657e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_dataloader                                                                                                                                                             \t|  4.281e-06      \t|  1              \t|  4.281e-06      \t|  8.7018e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                       \t|  4.021e-06      \t|  1              \t|  4.021e-06      \t|  8.1733e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step_end                                                                                                                                                                         \t|  1.98e-06       \t|  2              \t|  3.96e-06       \t|  8.0493e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_start                                                                                                                                                            \t|  1.95e-06       \t|  2              \t|  3.9e-06        \t|  7.9274e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                     \t|  3.887e-06      \t|  1              \t|  3.887e-06      \t|  7.901e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_end                                                                                                                                                              \t|  1.939e-06      \t|  2              \t|  3.878e-06      \t|  7.8827e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                  \t|  3.525e-06      \t|  1              \t|  3.525e-06      \t|  7.1651e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                               \t|  3.469e-06      \t|  1              \t|  3.469e-06      \t|  7.0513e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup \t|  3.398e-06      \t|  1              \t|  3.398e-06      \t|  6.907e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                          \t|  1.633e-06      \t|  2              \t|  3.266e-06      \t|  6.6387e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                               \t|  3.212e-06      \t|  1              \t|  3.212e-06      \t|  6.5289e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_accelerator_backend_setup\t|  3.017e-06      \t|  1              \t|  3.017e-06      \t|  6.1325e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start          \t|  3.007e-06      \t|  1              \t|  3.007e-06      \t|  6.1122e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                              \t|  2.99e-06       \t|  1              \t|  2.99e-06       \t|  6.0777e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                    \t|  2.959e-06      \t|  1              \t|  2.959e-06      \t|  6.0146e-06     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                            \t|  2.888e-06      \t|  1              \t|  2.888e-06      \t|  5.8703e-06     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                     \t|  2.78e-06       \t|  1              \t|  2.78e-06       \t|  5.6508e-06     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end            \t|  2.735e-06      \t|  1              \t|  2.735e-06      \t|  5.5593e-06     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                       \t|  2.717e-06      \t|  1              \t|  2.717e-06      \t|  5.5227e-06     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                    \t|  2.682e-06      \t|  1              \t|  2.682e-06      \t|  5.4516e-06     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                      \t|  2.668e-06      \t|  1              \t|  2.668e-06      \t|  5.4231e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_start                                                                                                                                                                  \t|  2.534e-06      \t|  1              \t|  2.534e-06      \t|  5.1508e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                            \t|  2.478e-06      \t|  1              \t|  2.478e-06      \t|  5.0369e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_end                                                                                                                                                                    \t|  2.193e-06      \t|  1              \t|  2.193e-06      \t|  4.4576e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_end                                                                                                                                                              \t|  2.184e-06      \t|  1              \t|  2.184e-06      \t|  4.4393e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                   \t|  2.122e-06      \t|  1              \t|  2.122e-06      \t|  4.3133e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                          \t|  2.109e-06      \t|  1              \t|  2.109e-06      \t|  4.2869e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_start                                                                                                                                                            \t|  2.096e-06      \t|  1              \t|  2.096e-06      \t|  4.2605e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_end                                                                                                                                                                           \t|  1.996e-06      \t|  1              \t|  1.996e-06      \t|  4.0572e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                     \t|  1.977e-06      \t|  1              \t|  1.977e-06      \t|  4.0186e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_start                                                                                                                                                                         \t|  1.867e-06      \t|  1              \t|  1.867e-06      \t|  3.795e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                 \t|  1.506e-06      \t|  1              \t|  1.506e-06      \t|  3.0612e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                   \t|  1.473e-06      \t|  1              \t|  1.473e-06      \t|  2.9941e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                      \t|  1.431e-06      \t|  1              \t|  1.431e-06      \t|  2.9087e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                        \t|  1.261e-06      \t|  1              \t|  1.261e-06      \t|  2.5632e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                        \t|  1.009e-06      \t|  1              \t|  1.009e-06      \t|  2.051e-06      \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 102093.04it/s]\n",
      "\n",
      "100% 1395/1395 [00:00<00:00, 37348.50it/s]\n",
      "Getting embeddings for split ['fold04'], which has 1395 instances.\n",
      "Restoring states from the checkpoint path at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_11/checkpoints/epoch=158-step=795.ckpt\n",
      "LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]\n",
      "Loaded model weights from checkpoint at logs/embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/lightning_logs/version_11/checkpoints/epoch=158-step=795.ckpt\n",
      "Testing DataLoader 0:   0% 0/2 [00:00<?, ?it/s]/usr/local/lib/python3.7/dist-packages/heareval/predictions/task_predictions.py:193: UserWarning: Implicit dimension choice for softmax has been deprecated. Change the call to include dim=X as an argument.\n",
      "  x = self.activation(x)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 370.55it/s]/usr/local/lib/python3.7/dist-packages/torchmetrics/utilities/prints.py:36: UserWarning: Torchmetrics v0.9 introduced a new argument class property called `full_state_update` that has\n",
      "                not been set for this class (_ResultMetric). The property determines if `update` by\n",
      "                default needs access to the full metric state. If this is not the case, significant speedups can be\n",
      "                achieved and we recommend setting this to `False`.\n",
      "                We provide an checking function\n",
      "                `from torchmetrics.utilities import check_forward_no_full_state`\n",
      "                that can be used to check if the `full_state_update=True` (old and potential slower behaviour,\n",
      "                default for now) or if `full_state_update=False` can be used safely.\n",
      "                \n",
      "  warnings.warn(*args, **kwargs)\n",
      "Testing DataLoader 0: 100% 2/2 [00:00<00:00, 32.92it/s] \n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       Test metric             DataLoader 0\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "       test_aucroc          0.9675760111946247\n",
      "      test_d_prime           3.154527975746111\n",
      "        test_loss           0.5104941725730896\n",
      "        test_mAP            0.8840364782336843\n",
      "       test_score           0.8258064389228821\n",
      "      test_top1_acc         0.8258064389228821\n",
      "────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────\n",
      "TEST Profiler Report\n",
      "\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Action                                                                                                                                                                                                               \t|  Mean duration (s)\t|  Num calls      \t|  Total time (s) \t|  Percentage %   \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  Total                                                                                                                                                                                                                \t|  -              \t|  62616          \t|  20.192         \t|  100 %          \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "|  run_training_epoch                                                                                                                                                                                                   \t|  0.081875       \t|  219            \t|  17.931         \t|  88.799         \t|\n",
      "|  run_training_batch                                                                                                                                                                                                   \t|  0.0038895      \t|  1095           \t|  4.259          \t|  21.092         \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_step                                                                                                                                                                 \t|  0.0035726      \t|  1095           \t|  3.912          \t|  19.373         \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_epoch_end                                                                                                                                                           \t|  0.03026        \t|  73             \t|  2.209          \t|  10.94          \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step                                                                                                                                                                         \t|  0.0014985      \t|  1095           \t|  1.6408         \t|  8.1259         \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_end                  \t|  0.018362       \t|  73             \t|  1.3405         \t|  6.6384         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.backward                                                                                                                                                                              \t|  0.00089156     \t|  1095           \t|  0.97626        \t|  4.8347         \t|\n",
      "|  on_train_batch_end                                                                                                                                                                                                   \t|  0.00030713     \t|  1095           \t|  0.33631        \t|  1.6655         \t|\n",
      "|  on_train_batch_start                                                                                                                                                                                                 \t|  0.00018802     \t|  1095           \t|  0.20588        \t|  1.0196         \t|\n",
      "|  [Strategy]SingleDeviceStrategy.batch_to_device                                                                                                                                                                       \t|  9.9454e-05     \t|  1243           \t|  0.12362        \t|  0.61221        \t|\n",
      "|  [LightningModule]ScenePredictionModel.optimizer_zero_grad                                                                                                                                                            \t|  0.00011182     \t|  1095           \t|  0.12244        \t|  0.60639        \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step                                                                                                                                                                       \t|  0.00067164     \t|  146            \t|  0.098059       \t|  0.48562        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_end                                                                                                                                                                         \t|  0.00036207     \t|  219            \t|  0.079294       \t|  0.39269        \t|\n",
      "|  run_test_evaluation                                                                                                                                                                                                  \t|  0.069049       \t|  1              \t|  0.069049       \t|  0.34195        \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_epoch_start                                                                                                                                                                       \t|  0.00025274     \t|  219            \t|  0.05535        \t|  0.27411        \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_epoch_end                                                                                                                                                                 \t|  0.048563       \t|  1              \t|  0.048563       \t|  0.2405         \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_end                                                                                                                                                                          \t|  0.00056447     \t|  73             \t|  0.041206       \t|  0.20407        \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_end                                                                                                                                  \t|  0.00049209     \t|  73             \t|  0.035922       \t|  0.1779         \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_end                                                                                                                                                                    \t|  0.00017516     \t|  146            \t|  0.025573       \t|  0.12664        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_batch_start                                                                                                                                                                  \t|  0.0001391      \t|  146            \t|  0.020309       \t|  0.10058        \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_start                                                                                                                                                                        \t|  0.00025743     \t|  73             \t|  0.018793       \t|  0.093067       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_after_backward                                                                                                                                  \t|  7.0749e-06     \t|  1095           \t|  0.007747       \t|  0.038366       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_train                                                                                                                                                      \t|  8.6728e-05     \t|  73             \t|  0.0063311      \t|  0.031354       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_end                 \t|  2.7015e-05     \t|  219            \t|  0.0059163      \t|  0.029299       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_zero_grad                                                                                                                                \t|  5.3548e-06     \t|  1095           \t|  0.0058635      \t|  0.029038       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_start                                                                                                                                     \t|  5.1797e-06     \t|  1095           \t|  0.0056718      \t|  0.028089       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_model_eval                                                                                                                                                       \t|  7.5406e-05     \t|  73             \t|  0.0055047      \t|  0.027261       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_batch_end                                                                                                                                       \t|  4.8526e-06     \t|  1095           \t|  0.0053136      \t|  0.026315       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_backward                                                                                                                                 \t|  4.25e-06       \t|  1095           \t|  0.0046537      \t|  0.023047       \t|\n",
      "|  [Callback]TQDMProgressBar.on_after_backward                                                                                                                                                                          \t|  4.2378e-06     \t|  1095           \t|  0.0046404      \t|  0.022981       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_optimizer_step                                                                                                                           \t|  4.1942e-06     \t|  1095           \t|  0.0045926      \t|  0.022744       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_after_backward                                                                                                                                                            \t|  4.0198e-06     \t|  1095           \t|  0.0044017      \t|  0.021799       \t|\n",
      "|  [Callback]ModelSummary.on_before_optimizer_step                                                                                                                                                                      \t|  3.9013e-06     \t|  1095           \t|  0.0042719      \t|  0.021156       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_start                                                                                                                                                                             \t|  3.823e-06      \t|  1095           \t|  0.0041862      \t|  0.020732       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_zero_grad                                                                                                                                                                        \t|  3.8209e-06     \t|  1095           \t|  0.0041839      \t|  0.02072        \t|\n",
      "|  [Callback]ModelSummary.on_after_backward                                                                                                                                                                             \t|  3.786e-06      \t|  1095           \t|  0.0041457      \t|  0.020531       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_optimizer_step           \t|  3.7779e-06     \t|  1095           \t|  0.0041369      \t|  0.020487       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_optimizer_step                                                                                                                                                                   \t|  3.7681e-06     \t|  1095           \t|  0.0041261      \t|  0.020434       \t|\n",
      "|  [Callback]ModelSummary.on_batch_start                                                                                                                                                                                \t|  3.7534e-06     \t|  1095           \t|  0.0041099      \t|  0.020354       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_after_backward                  \t|  3.7388e-06     \t|  1095           \t|  0.004094       \t|  0.020275       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_optimizer_step                                                                                                                                                     \t|  3.6844e-06     \t|  1095           \t|  0.0040344      \t|  0.01998        \t|\n",
      "|  [Callback]ModelSummary.on_batch_end                                                                                                                                                                                  \t|  3.6794e-06     \t|  1095           \t|  0.004029       \t|  0.019953       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_end                       \t|  3.6431e-06     \t|  1095           \t|  0.0039892      \t|  0.019756       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_zero_grad                \t|  3.6367e-06     \t|  1095           \t|  0.0039822      \t|  0.019721       \t|\n",
      "|  [Callback]TQDMProgressBar.on_batch_end                                                                                                                                                                               \t|  3.6351e-06     \t|  1095           \t|  0.0039804      \t|  0.019712       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_batch_start                     \t|  3.6311e-06     \t|  1095           \t|  0.0039761      \t|  0.019691       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_backward                                                                                                                                                           \t|  3.5975e-06     \t|  1095           \t|  0.0039392      \t|  0.019508       \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_backward                                                                                                                                                                         \t|  3.5759e-06     \t|  1095           \t|  0.0039156      \t|  0.019391       \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_backward                 \t|  3.4913e-06     \t|  1095           \t|  0.0038229      \t|  0.018932       \t|\n",
      "|  [Callback]ModelSummary.on_before_zero_grad                                                                                                                                                                           \t|  3.4662e-06     \t|  1095           \t|  0.0037955      \t|  0.018797       \t|\n",
      "|  [Callback]ModelSummary.on_before_backward                                                                                                                                                                            \t|  3.4662e-06     \t|  1095           \t|  0.0037955      \t|  0.018796       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_zero_grad                                                                                                                                                          \t|  3.4458e-06     \t|  1095           \t|  0.0037731      \t|  0.018686       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_start                                                                                                                                                               \t|  3.4256e-06     \t|  1095           \t|  0.003751       \t|  0.018576       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_batch_end                                                                                                                                                                 \t|  3.4247e-06     \t|  1095           \t|  0.00375        \t|  0.018571       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_end                                                                                                                                                                            \t|  1.1703e-05     \t|  219            \t|  0.002563       \t|  0.012693       \t|\n",
      "|  [LightningModule]ScenePredictionModel.training_step_end                                                                                                                                                              \t|  2.0314e-06     \t|  1095           \t|  0.0022244      \t|  0.011016       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_end                                                                                                                                                             \t|  2.0057e-06     \t|  1095           \t|  0.0021962      \t|  0.010876       \t|\n",
      "|  [Callback]ModelSummary.on_train_epoch_start                                                                                                                                                                          \t|  9.5479e-06     \t|  219            \t|  0.002091       \t|  0.010355       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_batch_start                                                                                                                                                           \t|  1.8731e-06     \t|  1095           \t|  0.0020511      \t|  0.010158       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_after_backward                                                                                                                                                              \t|  1.8456e-06     \t|  1095           \t|  0.002021       \t|  0.010009       \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_start                                                                                                                                                         \t|  8.8129e-06     \t|  219            \t|  0.00193        \t|  0.0095581      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step                                                                                                                                                                             \t|  0.00095931     \t|  2              \t|  0.0019186      \t|  0.0095017      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_zero_grad                                                                                                                                                            \t|  1.5583e-06     \t|  1095           \t|  0.0017064      \t|  0.0084505      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.training_step_end                                                                                                                                                                     \t|  1.516e-06      \t|  1095           \t|  0.0016601      \t|  0.0082212      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_batch_start                                                                                                                                                                  \t|  1.4918e-06     \t|  1095           \t|  0.0016336      \t|  0.0080899      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_optimizer_step                                                                                                                                                       \t|  1.4401e-06     \t|  1095           \t|  0.0015769      \t|  0.0078091      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_before_backward                                                                                                                                                             \t|  1.4186e-06     \t|  1095           \t|  0.0015534      \t|  0.0076929      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_start                                                                                                                                     \t|  4.362e-06      \t|  293            \t|  0.0012781      \t|  0.0063294      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_end                                                                                                                                                                       \t|  8.4069e-06     \t|  146            \t|  0.0012274      \t|  0.0060785      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_epoch_end                                                                                                                                       \t|  3.9709e-06     \t|  293            \t|  0.0011635      \t|  0.005762       \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_end                                                                                                                                 \t|  5.2816e-06     \t|  219            \t|  0.0011567      \t|  0.0057283      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_end                       \t|  3.8259e-06     \t|  293            \t|  0.001121       \t|  0.0055515      \t|\n",
      "|  [Callback]ModelSummary.on_validation_batch_start                                                                                                                                                                     \t|  7.2545e-06     \t|  146            \t|  0.0010592      \t|  0.0052453      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_start                                                                                                                                                                             \t|  3.556e-06      \t|  293            \t|  0.0010419      \t|  0.0051599      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_start                                                                                                                                                                                \t|  3.5095e-06     \t|  293            \t|  0.0010283      \t|  0.0050925      \t|\n",
      "|  [Callback]ModelSummary.on_epoch_end                                                                                                                                                                                  \t|  3.4577e-06     \t|  293            \t|  0.0010131      \t|  0.0050173      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_start                                                                                                                                                               \t|  3.4349e-06     \t|  293            \t|  0.0010064      \t|  0.0049841      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_epoch_start                     \t|  3.4344e-06     \t|  293            \t|  0.0010063      \t|  0.0049835      \t|\n",
      "|  [Callback]TQDMProgressBar.on_epoch_end                                                                                                                                                                               \t|  3.426e-06      \t|  293            \t|  0.0010038      \t|  0.0049712      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_epoch_end                                                                                                                                                                 \t|  3.376e-06      \t|  293            \t|  0.00098916     \t|  0.0048987      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_epoch_end                                                                                                                                                           \t|  4.0257e-06     \t|  219            \t|  0.00088163     \t|  0.0043661      \t|\n",
      "|  [Callback]ModelSummary.on_validation_end                                                                                                                                                                             \t|  1.1892e-05     \t|  73             \t|  0.00086812     \t|  0.0042992      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_epoch_start               \t|  3.9229e-06     \t|  219            \t|  0.00085911     \t|  0.0042546      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_epoch_start                                                                                                                               \t|  3.6367e-06     \t|  219            \t|  0.00079643     \t|  0.0039442      \t|\n",
      "|  [Callback]ModelSummary.on_fit_start                                                                                                                                                                                  \t|  0.00079626     \t|  1              \t|  0.00079626     \t|  0.0039434      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_start                                                                                                                          \t|  5.3339e-06     \t|  146            \t|  0.00077876     \t|  0.0038567      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_batch_end                                                                                                                            \t|  5.0262e-06     \t|  146            \t|  0.00073382     \t|  0.0036341      \t|\n",
      "|  [Callback]ModelSummary.on_validation_start                                                                                                                                                                           \t|  8.9478e-06     \t|  73             \t|  0.00065319     \t|  0.0032348      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_end                                                                                                                                                      \t|  4.4547e-06     \t|  146            \t|  0.00065038     \t|  0.0032209      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_batch_start                                                                                                                                                    \t|  4.2379e-06     \t|  146            \t|  0.00061873     \t|  0.0030642      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_end            \t|  3.9822e-06     \t|  146            \t|  0.0005814      \t|  0.0028793      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_batch_start          \t|  3.7857e-06     \t|  146            \t|  0.00055271     \t|  0.0027372      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_start                                                                                                                                \t|  6.5307e-06     \t|  73             \t|  0.00047674     \t|  0.002361       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_start                                                                                                                                                                 \t|  1.5988e-06     \t|  293            \t|  0.00046845     \t|  0.0023199      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_end                                                                                                                            \t|  6.0106e-06     \t|  73             \t|  0.00043877     \t|  0.002173       \t|\n",
      "|  [LightningModule]ScenePredictionModel.validation_step_end                                                                                                                                                            \t|  2.7288e-06     \t|  146            \t|  0.00039841     \t|  0.001973       \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_epoch_end                                                                                                                                                                   \t|  1.3568e-06     \t|  293            \t|  0.00039754     \t|  0.0019687      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_end                                                                                                                                                             \t|  1.7049e-06     \t|  219            \t|  0.00037338     \t|  0.0018491      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_epoch_start                                                                                                                                                           \t|  1.622e-06      \t|  219            \t|  0.00035522     \t|  0.0017591      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_end                                                                                                                                                            \t|  4.4891e-06     \t|  73             \t|  0.0003277      \t|  0.0016229      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_start                                                                                                                                                          \t|  3.9863e-06     \t|  73             \t|  0.000291       \t|  0.0014411      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_start                \t|  3.9764e-06     \t|  73             \t|  0.00029028     \t|  0.0014375      \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_start                                                                                                                                                                             \t|  0.00028316     \t|  1              \t|  0.00028316     \t|  0.0014023      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_end                                                                                                                                                                    \t|  3.8526e-06     \t|  73             \t|  0.00028124     \t|  0.0013928      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_end                                                                                                                                                                       \t|  3.7896e-06     \t|  73             \t|  0.00027664     \t|  0.00137        \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_end                                                                                                                                                        \t|  1.8873e-06     \t|  146            \t|  0.00027554     \t|  0.0013646      \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_validation_epoch_start                                                                                                                          \t|  3.7707e-06     \t|  73             \t|  0.00027526     \t|  0.0013632      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_end            \t|  3.5032e-06     \t|  73             \t|  0.00025573     \t|  0.0012665      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_batch_start                                                                                                                                                      \t|  1.6954e-06     \t|  146            \t|  0.00024753     \t|  0.0012258      \t|\n",
      "|  [Callback]TQDMProgressBar.on_validation_epoch_start                                                                                                                                                                  \t|  3.3765e-06     \t|  73             \t|  0.00024649     \t|  0.0012207      \t|\n",
      "|  [Callback]ModelSummary.on_validation_epoch_start                                                                                                                                                                     \t|  3.3598e-06     \t|  73             \t|  0.00024527     \t|  0.0012146      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_validation_epoch_start          \t|  3.3428e-06     \t|  73             \t|  0.00024402     \t|  0.0012085      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_start                                                                                                                                                    \t|  3.3372e-06     \t|  73             \t|  0.00024361     \t|  0.0012064      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_validation_epoch_end                                                                                                                                                      \t|  3.3217e-06     \t|  73             \t|  0.00024248     \t|  0.0012009      \t|\n",
      "|  [Strategy]SingleDeviceStrategy.validation_step_end                                                                                                                                                                   \t|  1.6275e-06     \t|  146            \t|  0.00023761     \t|  0.0011767      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.setup                               \t|  0.00023015     \t|  1              \t|  0.00023015     \t|  0.0011398      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_end                                                                                                                                                              \t|  2.7711e-06     \t|  73             \t|  0.00020229     \t|  0.0010018      \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_start                                                                                                                                                                        \t|  9.6938e-05     \t|  2              \t|  0.00019388     \t|  0.00096014     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_end                                                                                                                                                                                \t|  0.00019324     \t|  1              \t|  0.00019324     \t|  0.00095699     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_save_checkpoint                                                                                                                                 \t|  6.2498e-06     \t|  30             \t|  0.0001875      \t|  0.00092854     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_start                                                                                                                                                                              \t|  0.00018378     \t|  1              \t|  0.00018378     \t|  0.00091014     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_batch_end                                                                                                                                                                          \t|  8.9845e-05     \t|  2              \t|  0.00017969     \t|  0.00088989     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_end                                                                                                                                                                     \t|  2.3326e-06     \t|  73             \t|  0.00017028     \t|  0.00084329     \t|\n",
      "|  [Callback]TQDMProgressBar.on_train_end                                                                                                                                                                               \t|  0.00014244     \t|  1              \t|  0.00014244     \t|  0.0007054      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_start                                                                                                                                                            \t|  1.8657e-06     \t|  73             \t|  0.0001362      \t|  0.0006745      \t|\n",
      "|  [Callback]TQDMProgressBar.on_save_checkpoint                                                                                                                                                                         \t|  4.468e-06      \t|  30             \t|  0.00013404     \t|  0.00066381     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_start                                                                                                                                                      \t|  1.6844e-06     \t|  73             \t|  0.00012296     \t|  0.00060895     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_validation_start                                                                                                                                                                   \t|  1.6613e-06     \t|  73             \t|  0.00012128     \t|  0.00060059     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_validation_epoch_end                                                                                                                                                        \t|  1.6063e-06     \t|  73             \t|  0.00011726     \t|  0.0005807      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_save_checkpoint                                                                                                                                                           \t|  3.7491e-06     \t|  30             \t|  0.00011247     \t|  0.00055701     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_save_checkpoint                 \t|  3.5395e-06     \t|  30             \t|  0.00010619     \t|  0.00052586     \t|\n",
      "|  [Callback]ModelSummary.on_save_checkpoint                                                                                                                                                                            \t|  3.4166e-06     \t|  30             \t|  0.0001025      \t|  0.0005076      \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_optimizers                                                                                                                                                           \t|  0.00010159     \t|  1              \t|  0.00010159     \t|  0.0005031      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_train                                                                                                                                                            \t|  8.5547e-05     \t|  1              \t|  8.5547e-05     \t|  0.00042366     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_model_eval                                                                                                                                                             \t|  6.7487e-05     \t|  1              \t|  6.7487e-05     \t|  0.00033422     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_save_checkpoint                                                                                                                                                             \t|  1.8636e-06     \t|  30             \t|  5.5908e-05     \t|  0.00027688     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_end                  \t|  1.2617e-05     \t|  2              \t|  2.5234e-05     \t|  0.00012497     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_start                                                                                                                                                                 \t|  1.562e-05      \t|  1              \t|  1.562e-05      \t|  7.7355e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_start                                                                                                                                                                           \t|  7.6985e-06     \t|  2              \t|  1.5397e-05     \t|  7.6251e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.setup                                                                                                                                                                                      \t|  7.567e-06      \t|  2              \t|  1.5134e-05     \t|  7.4949e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_batch_end                                                                                                                                                                             \t|  7.259e-06      \t|  2              \t|  1.4518e-05     \t|  7.1898e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.teardown                                                                                                                                           \t|  7.0645e-06     \t|  2              \t|  1.4129e-05     \t|  6.9972e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_start                                                                                                                                                                                \t|  1.2051e-05     \t|  1              \t|  1.2051e-05     \t|  5.9681e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_start                                                                                                                                \t|  5.85e-06       \t|  2              \t|  1.17e-05       \t|  5.7942e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_before_accelerator_backend_setup                                                                                                                \t|  5.8085e-06     \t|  2              \t|  1.1617e-05     \t|  5.7531e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.setup                                                                                                                                              \t|  5.432e-06      \t|  2              \t|  1.0864e-05     \t|  5.3802e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_configure_sharded_model                                                                                                                         \t|  5.216e-06      \t|  2              \t|  1.0432e-05     \t|  5.1663e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_batch_end                                                                                                                                  \t|  5.1455e-06     \t|  2              \t|  1.0291e-05     \t|  5.0964e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_start                                                                                                                                                                                 \t|  1.0011e-05     \t|  1              \t|  1.0011e-05     \t|  4.9578e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_callbacks                                                                                                                                                            \t|  4.949e-06      \t|  2              \t|  9.898e-06      \t|  4.9018e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.teardown                                                                                                                                                                                   \t|  4.886e-06      \t|  2              \t|  9.772e-06      \t|  4.8394e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.prepare_data                                                                                                                                                                   \t|  4.5955e-06     \t|  2              \t|  9.191e-06      \t|  4.5517e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.teardown                                                                                                                                                                     \t|  4.5835e-06     \t|  2              \t|  9.167e-06      \t|  4.5398e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.teardown                           \t|  4.494e-06      \t|  2              \t|  8.988e-06      \t|  4.4512e-05     \t|\n",
      "|  [Callback]ModelSummary.teardown                                                                                                                                                                                      \t|  4.4735e-06     \t|  2              \t|  8.947e-06      \t|  4.4309e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_start                                                                                                                                                          \t|  4.3215e-06     \t|  2              \t|  8.643e-06      \t|  4.2803e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_end                                                                                                                                        \t|  8.533e-06      \t|  1              \t|  8.533e-06      \t|  4.2258e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_batch_end                                                                                                                                                            \t|  4.204e-06      \t|  2              \t|  8.408e-06      \t|  4.1639e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_start                                                                                                                          \t|  8.227e-06      \t|  1              \t|  8.227e-06      \t|  4.0743e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_end                                                                                                                                         \t|  8.036e-06      \t|  1              \t|  8.036e-06      \t|  3.9797e-05     \t|\n",
      "|  [Callback]ModelSummary.setup                                                                                                                                                                                         \t|  3.983e-06      \t|  2              \t|  7.966e-06      \t|  3.945e-05      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.setup                              \t|  7.959e-06      \t|  1              \t|  7.959e-06      \t|  3.9416e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_batch_start                \t|  3.954e-06      \t|  2              \t|  7.908e-06      \t|  3.9163e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_end                                                                                                                                                                                   \t|  7.825e-06      \t|  1              \t|  7.825e-06      \t|  3.8752e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_configure_sharded_model                                                                                                                                                                 \t|  3.9085e-06     \t|  2              \t|  7.817e-06      \t|  3.8712e-05     \t|\n",
      "|  [Callback]ModelSummary.on_train_end                                                                                                                                                                                  \t|  7.661e-06      \t|  1              \t|  7.661e-06      \t|  3.794e-05      \t|\n",
      "|  [Callback]TQDMProgressBar.on_before_accelerator_backend_setup                                                                                                                                                        \t|  3.816e-06      \t|  2              \t|  7.632e-06      \t|  3.7796e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_end                                                                                                                                  \t|  7.421e-06      \t|  1              \t|  7.421e-06      \t|  3.6751e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_before_accelerator_backend_setup                                                                                                                                          \t|  3.703e-06      \t|  2              \t|  7.406e-06      \t|  3.6677e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_start                                                                                                                                     \t|  7.365e-06      \t|  1              \t|  7.365e-06      \t|  3.6474e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.setup                                                                                                                                                                        \t|  3.588e-06      \t|  2              \t|  7.176e-06      \t|  3.5538e-05     \t|\n",
      "|  [Callback]ModelSummary.on_before_accelerator_backend_setup                                                                                                                                                           \t|  3.5835e-06     \t|  2              \t|  7.167e-06      \t|  3.5493e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.configure_sharded_model                                                                                                                                                        \t|  3.493e-06      \t|  2              \t|  6.986e-06      \t|  3.4597e-05     \t|\n",
      "|  [Callback]ModelSummary.on_configure_sharded_model                                                                                                                                                                    \t|  3.469e-06      \t|  2              \t|  6.938e-06      \t|  3.4359e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_configure_sharded_model         \t|  3.2995e-06     \t|  2              \t|  6.599e-06      \t|  3.268e-05      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_start                     \t|  6.592e-06      \t|  1              \t|  6.592e-06      \t|  3.2646e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_configure_sharded_model                                                                                                                                                   \t|  3.241e-06      \t|  2              \t|  6.482e-06      \t|  3.2101e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_fit_start                                                                                                                                       \t|  6.131e-06      \t|  1              \t|  6.131e-06      \t|  3.0363e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_start                       \t|  5.949e-06      \t|  1              \t|  5.949e-06      \t|  2.9461e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_start                                                                                                                                                                  \t|  5.347e-06      \t|  1              \t|  5.347e-06      \t|  2.648e-05      \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_end                                                                                                                                                                  \t|  5.312e-06      \t|  1              \t|  5.312e-06      \t|  2.6307e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_end                                                                                                                                                                                 \t|  5.26e-06       \t|  1              \t|  5.26e-06       \t|  2.6049e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_end                                                                                                                                                                          \t|  5.232e-06      \t|  1              \t|  5.232e-06      \t|  2.5911e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.test_step_end                                                                                                                                                                  \t|  2.5285e-06     \t|  2              \t|  5.057e-06      \t|  2.5044e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_pretrain_routine_end                                                                                                                            \t|  4.946e-06      \t|  1              \t|  4.946e-06      \t|  2.4494e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_start                                                                                                                                                               \t|  4.92e-06       \t|  1              \t|  4.92e-06       \t|  2.4365e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_end                        \t|  4.843e-06      \t|  1              \t|  4.843e-06      \t|  2.3984e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.teardown                                                                                                                                                                       \t|  2.404e-06      \t|  2              \t|  4.808e-06      \t|  2.3811e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_fit_end                                                                                                                                                                   \t|  4.807e-06      \t|  1              \t|  4.807e-06      \t|  2.3806e-05     \t|\n",
      "|  [Callback]ModelSummary.on_fit_end                                                                                                                                                                                    \t|  4.768e-06      \t|  1              \t|  4.768e-06      \t|  2.3613e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_end                                                                                                                                                                             \t|  4.768e-06      \t|  1              \t|  4.768e-06      \t|  2.3613e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_start          \t|  4.756e-06      \t|  1              \t|  4.756e-06      \t|  2.3553e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_start                                                                                                                                                                     \t|  4.702e-06      \t|  1              \t|  4.702e-06      \t|  2.3286e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_start                                                                                                                                                    \t|  4.662e-06      \t|  1              \t|  4.662e-06      \t|  2.3088e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_end                                                                                                                                                            \t|  4.587e-06      \t|  1              \t|  4.587e-06      \t|  2.2716e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_start                                                                                                                                      \t|  4.585e-06      \t|  1              \t|  4.585e-06      \t|  2.2706e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_pretrain_routine_end            \t|  4.559e-06      \t|  1              \t|  4.559e-06      \t|  2.2578e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_end                  \t|  4.521e-06      \t|  1              \t|  4.521e-06      \t|  2.239e-05      \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_fit_end                         \t|  4.44e-06       \t|  1              \t|  4.44e-06       \t|  2.1988e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_pretrain_routine_end                                                                                                                                                      \t|  4.401e-06      \t|  1              \t|  4.401e-06      \t|  2.1795e-05     \t|\n",
      "|  [Callback]ModelSummary.on_pretrain_routine_end                                                                                                                                                                       \t|  4.395e-06      \t|  1              \t|  4.395e-06      \t|  2.1766e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_pretrain_routine_end                                                                                                                                                                    \t|  4.265e-06      \t|  1              \t|  4.265e-06      \t|  2.1122e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': None}.on_before_accelerator_backend_setup \t|  4.233e-06      \t|  1              \t|  4.233e-06      \t|  2.0963e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_fit_start                                                                                                                                                                               \t|  4.152e-06      \t|  1              \t|  4.152e-06      \t|  2.0562e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_start                                                                                                                                                            \t|  2.0375e-06     \t|  2              \t|  4.075e-06      \t|  2.0181e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_load_checkpoint                                                                                                                                                             \t|  4.024e-06      \t|  1              \t|  4.024e-06      \t|  1.9928e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.setup                                                                                                                                                                          \t|  1.9995e-06     \t|  2              \t|  3.999e-06      \t|  1.9804e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_train_end                                                                                                                                       \t|  3.965e-06      \t|  1              \t|  3.965e-06      \t|  1.9636e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_val_dataloader                                                                                                                                                              \t|  3.827e-06      \t|  1              \t|  3.827e-06      \t|  1.8953e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_dataloader                                                                                                                                                             \t|  3.699e-06      \t|  1              \t|  3.699e-06      \t|  1.8319e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_batch_end                                                                                                                                                              \t|  1.7645e-06     \t|  2              \t|  3.529e-06      \t|  1.7477e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_start                                                                                                                                                                \t|  3.436e-06      \t|  1              \t|  3.436e-06      \t|  1.7016e-05     \t|\n",
      "|  [Callback]EarlyStopping{'monitor': 'val_top1_acc', 'mode': 'max'}.on_test_epoch_start                                                                                                                                \t|  3.333e-06      \t|  1              \t|  3.333e-06      \t|  1.6506e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_epoch_start                \t|  3.054e-06      \t|  1              \t|  3.054e-06      \t|  1.5124e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_test_start                      \t|  3.054e-06      \t|  1              \t|  3.054e-06      \t|  1.5124e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_train_end                       \t|  3.026e-06      \t|  1              \t|  3.026e-06      \t|  1.4986e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_train_end                                                                                                                                                                 \t|  3.026e-06      \t|  1              \t|  3.026e-06      \t|  1.4986e-05     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.test_step_end                                                                                                                                                                         \t|  1.511e-06      \t|  2              \t|  3.022e-06      \t|  1.4966e-05     \t|\n",
      "|  [Callback]ModelCheckpoint{'monitor': 'val_top1_acc', 'mode': 'max', 'every_n_train_steps': 0, 'every_n_epochs': 1, 'train_time_interval': None, 'save_on_train_epoch_end': False}.on_before_accelerator_backend_setup\t|  2.973e-06      \t|  1              \t|  2.973e-06      \t|  1.4723e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_dataloader                                                                                                                                                            \t|  2.8e-06        \t|  1              \t|  2.8e-06        \t|  1.3867e-05     \t|\n",
      "|  [Callback]ModelSummary.on_test_epoch_start                                                                                                                                                                           \t|  2.739e-06      \t|  1              \t|  2.739e-06      \t|  1.3564e-05     \t|\n",
      "|  [Callback]GradientAccumulationScheduler.on_test_epoch_start                                                                                                                                                          \t|  2.703e-06      \t|  1              \t|  2.703e-06      \t|  1.3386e-05     \t|\n",
      "|  [Callback]TQDMProgressBar.on_test_epoch_start                                                                                                                                                                        \t|  2.674e-06      \t|  1              \t|  2.674e-06      \t|  1.3243e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_start                                                                                                                                                                 \t|  2.462e-06      \t|  1              \t|  2.462e-06      \t|  1.2193e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_end                                                                                                                                                                    \t|  2.252e-06      \t|  1              \t|  2.252e-06      \t|  1.1153e-05     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_start                                                                                                                                                                        \t|  2.247e-06      \t|  1              \t|  2.247e-06      \t|  1.1128e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_start                                                                                                                                                                   \t|  2.147e-06      \t|  1              \t|  2.147e-06      \t|  1.0633e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_fit_end                                                                                                                                                                     \t|  2.055e-06      \t|  1              \t|  2.055e-06      \t|  1.0177e-05     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_end                                                                                                                                                              \t|  1.99e-06       \t|  1              \t|  1.99e-06       \t|  9.8551e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_end                                                                                                                                                                           \t|  1.946e-06      \t|  1              \t|  1.946e-06      \t|  9.6372e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_end                                                                                                                                                        \t|  1.879e-06      \t|  1              \t|  1.879e-06      \t|  9.3054e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_pretrain_routine_start                                                                                                                                                      \t|  1.866e-06      \t|  1              \t|  1.866e-06      \t|  9.2411e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_train_end                                                                                                                                                                   \t|  1.484e-06      \t|  1              \t|  1.484e-06      \t|  7.3493e-06     \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_start                                                                                                                                                                  \t|  1.479e-06      \t|  1              \t|  1.479e-06      \t|  7.3245e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_test_start                                                                                                                                                                         \t|  1.321e-06      \t|  1              \t|  1.321e-06      \t|  6.542e-06      \t|\n",
      "|  [LightningModule]ScenePredictionModel.on_test_epoch_start                                                                                                                                                            \t|  1.318e-06      \t|  1              \t|  1.318e-06      \t|  6.5272e-06     \t|\n",
      "|  [Strategy]SingleDeviceStrategy.on_train_end                                                                                                                                                                          \t|  1.245e-06      \t|  1              \t|  1.245e-06      \t|  6.1657e-06     \t|\n",
      "----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "predict - mridangam_stroke - 2022-06-03 21:10:54,435 - 435 - Final Test Results: {\"fold00\": {\"test_loss\": 0.48911142349243164, \"test_score\": 0.8202005624771118, \"test_top1_acc\": 0.8202005624771118, \"test_d_prime\": 3.0656446952202114, \"test_aucroc\": 0.9667379178924649, \"test_mAP\": 0.8648800803555511, \"validation_score\": 0.8388252258300781, \"epoch\": 104, \"time_in_min\": 0.28741658131281533}, \"fold01\": {\"test_loss\": 0.5804157257080078, \"test_score\": 0.8502865433692932, \"test_top1_acc\": 0.8502865433692932, \"test_d_prime\": 3.4191566852319224, \"test_aucroc\": 0.9709770413252347, \"test_mAP\": 0.8939131893403549, \"validation_score\": 0.8157706260681152, \"epoch\": 392, \"time_in_min\": 0.6220560510953267}, \"fold02\": {\"test_loss\": 0.5754764080047607, \"test_score\": 0.8035842180252075, \"test_top1_acc\": 0.8035842180252075, \"test_d_prime\": 3.180630890263927, \"test_aucroc\": 0.9591241195762334, \"test_mAP\": 0.8422802671924309, \"validation_score\": 0.8458781242370605, \"epoch\": 344, \"time_in_min\": 0.5587012489636739}, \"fold03\": {\"test_loss\": 0.4557825028896332, \"test_score\": 0.8451613187789917, \"test_top1_acc\": 0.8451613187789917, \"test_d_prime\": 3.476533598795452, \"test_aucroc\": 0.9735389632829503, \"test_mAP\": 0.8980638408963632, \"validation_score\": 0.8365591168403625, \"epoch\": 293, \"time_in_min\": 0.48952928781509397}, \"fold04\": {\"test_loss\": 0.5104941725730896, \"test_score\": 0.8258064389228821, \"test_top1_acc\": 0.8258064389228821, \"test_d_prime\": 3.154527975746111, \"test_aucroc\": 0.9675760111946247, \"test_mAP\": 0.8840364782336843, \"validation_score\": 0.8130372762680054, \"epoch\": 158, \"time_in_min\": 0.3118036468823751}, \"aggregated_scores\": {\"test_loss_mean\": 0.5222560465335846, \"test_loss_std\": 0.05447612981155485, \"test_score_mean\": 0.8290078163146972, \"test_score_std\": 0.01902561269892375, \"test_top1_acc_mean\": 0.8290078163146972, \"test_top1_acc_std\": 0.01902561269892375, \"test_d_prime_mean\": 3.2592987690515245, \"test_d_prime_std\": 0.1784747735771514, \"test_aucroc_mean\": 0.9675908106543016, \"test_aucroc_std\": 0.005460301748738511, \"test_mAP_mean\": 0.8766347712036768, \"test_mAP_std\": 0.0230810459628224, \"validation_score_mean\": 0.8300140738487244, \"validation_score_std\": 0.014690384121085987, \"epoch_mean\": 258.2, \"epoch_std\": 122.77296119260137, \"time_in_min_mean\": 0.453901363213857, \"time_in_min_std\": 0.1486920540179773}, \"hparams\": {\"batch_size\": 1024, \"check_val_every_n_epoch\": 3, \"dropout\": 0.1, \"embedding_norm\": \"<class 'torch.nn.modules.linear.Identity'>\", \"hidden_dim\": 1024, \"hidden_layers\": 1, \"hidden_norm\": \"<class 'torch.nn.modules.batchnorm.BatchNorm1d'>\", \"initialization\": \"<function xavier_normal_ at 0x7fc4a4e26e60>\", \"lr\": 0.0001, \"max_epochs\": 500, \"norm_after_activation\": false, \"optim\": \"<class 'torch.optim.adam.Adam'>\", \"patience\": 20}, \"postprocessing\": [], \"score_mode\": \"max\", \"embedding_path\": \"embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full\"}\n",
      "predict - mridangam_stroke - 2022-06-03 21:10:54,441 - 441 - DONE took 200.98609924316406 seconds to complete task_predictions(embedding_path=embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full, embedding_size=1024, grid_points=8, gpus=[0], gpu_max_mem_used=1.44140625, gpu_device_name=Tesla T4, in_memory=True, deterministic=True, grid=default)\n",
      "100% 1/1 [03:20<00:00, 200.99s/it]\n"
     ]
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Results"
   ],
   "metadata": {
    "id": "9PY-gHrBPoAe"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "import json\n",
    "results = json.load(open(\"embeddings/hearbaseline.wav2vec2/mridangam_tonic-v1.5-full/test.predicted-scores.json\"))\n",
    "results[\"aggregated_scores\"]"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "SeJIxTDP3dtO",
    "outputId": "2b880f95-4bfc-4cf3-c07a-a7446074aadd"
   },
   "execution_count": 5,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "{'epoch_mean': 258.2,\n",
       " 'epoch_std': 122.77296119260137,\n",
       " 'test_aucroc_mean': 0.9675908106543016,\n",
       " 'test_aucroc_std': 0.005460301748738511,\n",
       " 'test_d_prime_mean': 3.2592987690515245,\n",
       " 'test_d_prime_std': 0.1784747735771514,\n",
       " 'test_loss_mean': 0.5222560465335846,\n",
       " 'test_loss_std': 0.05447612981155485,\n",
       " 'test_mAP_mean': 0.8766347712036768,\n",
       " 'test_mAP_std': 0.0230810459628224,\n",
       " 'test_score_mean': 0.8290078163146972,\n",
       " 'test_score_std': 0.01902561269892375,\n",
       " 'test_top1_acc_mean': 0.8290078163146972,\n",
       " 'test_top1_acc_std': 0.01902561269892375,\n",
       " 'time_in_min_mean': 0.453901363213857,\n",
       " 'time_in_min_std': 0.1486920540179773,\n",
       " 'validation_score_mean': 0.8300140738487244,\n",
       " 'validation_score_std': 0.014690384121085987}"
      ]
     },
     "metadata": {},
     "execution_count": 5
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "results[\"aggregated_scores\"]['test_score_mean']"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "HCXjSFBnaufE",
    "outputId": "1ab3340f-cfdb-4560-969c-a1c3549405a3"
   },
   "execution_count": 6,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "0.8290078163146972"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    ""
   ],
   "metadata": {
    "id": "WMMaiICpa4QM"
   },
   "execution_count": 6,
   "outputs": []
  }
 ]
}