Model_ResNet_FLOPs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model Resnet: modules & parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "\n",
    "torch.cuda.is_available()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch.nn as nn\n",
    "import numpy\n",
    "\n",
    "class channel_selection(nn.Module):\n",
    "    \"\"\"\n",
    "    Select channels from the output of BatchNorm2d layer. It should be put directly after BatchNorm2d layer.\n",
    "    The output shape of this layer is determined by the number of 1 in `self.indexes`.\n",
    "    \"\"\"\n",
    "    def __init__(self, num_channels):\n",
    "        \"\"\"\n",
    "        Initialize the `indexes` with all one vector with the length same as the number of channels.\n",
    "        During pruning, the places in `indexes` which correpond to the channels to be pruned will be set to 0.\n",
    "        \"\"\"\n",
    "        super(channel_selection, self).__init__()\n",
    "        self.indexes = nn.Parameter(torch.ones(num_channels))\n",
    "\n",
    "    def forward(self, input_tensor):\n",
    "        \"\"\"\n",
    "        Parameter\n",
    "        ---------\n",
    "        input_tensor: (N,C,H,W). It should be the output of BatchNorm2d layer.\n",
    "        \"\"\"\n",
    "        selected_index = np.squeeze(np.argwhere(self.indexes.data.cpu().numpy()))\n",
    "        if selected_index.size == 1:\n",
    "            selected_index = np.resize(selected_index, (1,)) \n",
    "        output = input_tensor[:, selected_index, :, :]\n",
    "        return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "import torch.nn as nn\n",
    "import numpy as np\n",
    "\n",
    "\"\"\"\n",
    "preactivation resnet with bottleneck design.\n",
    "\"\"\"\n",
    "\n",
    "\n",
    "class Bottleneck(nn.Module):\n",
    "    expansion = 4\n",
    "\n",
    "    def __init__(self, inplanes, planes, cfg, stride=1, downsample=None):\n",
    "        super(Bottleneck, self).__init__()\n",
    "        self.bn1 = nn.BatchNorm2d(inplanes)\n",
    "        self.select = channel_selection(inplanes)\n",
    "        self.conv1 = nn.Conv2d(cfg[0], cfg[1], kernel_size=1, bias=False)\n",
    "        self.bn2 = nn.BatchNorm2d(cfg[1])\n",
    "        self.conv2 = nn.Conv2d(cfg[1], cfg[2], kernel_size=3, stride=stride, padding=1, bias=False)\n",
    "        self.bn3 = nn.BatchNorm2d(cfg[2])\n",
    "        self.conv3 = nn.Conv2d(cfg[2], planes * self.expansion, kernel_size=1, bias=False)\n",
    "        self.relu = nn.ReLU(inplace=True)\n",
    "        self.downsample = downsample\n",
    "        self.stride = stride\n",
    "\n",
    "    def forward(self, x):\n",
    "        residual = x\n",
    "\n",
    "        # group1\n",
    "        out = self.bn1(x)\n",
    "        out = self.select(out)\n",
    "        out = self.relu(out)\n",
    "        out = self.conv1(out)\n",
    "\n",
    "        # group2\n",
    "        out = self.bn2(out)\n",
    "        out = self.relu(out)\n",
    "        out = self.conv2(out)\n",
    "\n",
    "        # group3\n",
    "        out = self.bn3(out)\n",
    "        out = self.relu(out)\n",
    "        out = self.conv3(out)\n",
    "\n",
    "        # down sample\n",
    "        if self.downsample is not None:\n",
    "            residual = self.downsample(x)\n",
    "\n",
    "        out += residual\n",
    "        return out\n",
    "\n",
    "    def forward_bn(self, x):\n",
    "        bn_value = []\n",
    "        residual = x\n",
    "\n",
    "        out = self.bn1(x)\n",
    "        bn_value.append(out.clone())\n",
    "        out = self.select(out)\n",
    "        out = self.relu(out)\n",
    "        out = self.conv1(out)\n",
    "\n",
    "        out = self.bn2(out)\n",
    "        bn_value.append(out.clone())\n",
    "        out = self.relu(out)\n",
    "        out = self.conv2(out)\n",
    "\n",
    "        out = self.bn3(out)\n",
    "        bn_value.append(out.clone())\n",
    "        out = self.relu(out)\n",
    "        out = self.conv3(out)\n",
    "\n",
    "        if self.downsample is not None:\n",
    "            residual = self.downsample(x)\n",
    "\n",
    "        out += residual\n",
    "        return out, bn_value\n",
    "\n",
    "    def mask_bn(self, index, cfg_mask):\n",
    "        if index == 0:\n",
    "            self.bn1.weight.data.mul_(cfg_mask)\n",
    "            self.bn1.bias.data.mul_(cfg_mask)\n",
    "        elif index == 1:\n",
    "            self.bn2.weight.data.mul_(cfg_mask)\n",
    "            self.bn2.bias.data.mul_(cfg_mask)\n",
    "        elif index == 2:\n",
    "            self.bn3.weight.data.mul_(cfg_mask)\n",
    "            self.bn3.bias.data.mul_(cfg_mask)\n",
    "        else:\n",
    "            raise ValueError(\"Index is not including.\")\n",
    "\n",
    "\n",
    "class resnet(nn.Module):\n",
    "    def __init__(self, depth=164, dataset='cifar10', cfg=None, conv_cfg=None):\n",
    "        \"\"\"\n",
    "        :param depth:\n",
    "            164 layers => 1 conv2d + 3 layers × 18 blocks (every layer)  × 3 conv2ds (every block)  + 1 avgPool2d\n",
    "            param n = (depth - 2) // 9:\n",
    "                n means how many blocks in every layer\n",
    "                9 = 3 layers × 3 conv2d (every block)\n",
    "        :param cfg:\n",
    "            if depth = 164, then len(cfg) = 164\n",
    "        :param conv_cfg:\n",
    "            layer block index examples (index starts at 1 & ≤ 18):\n",
    "                3 indexes / layer: [4, 9, 14] or [6, 12, 18]\n",
    "                2 indexes / layer: [9, 18]\n",
    "                1 index / layer: [18]\n",
    "\n",
    "        number of BatchNorm2d:\n",
    "            163 = 162 (3 layers × 18 Bottlenecks × 3 BatchNorm2ds) + 1 BatchNorm2d\n",
    "        \"\"\"\n",
    "        super(resnet, self).__init__()\n",
    "        assert (depth - 2) % 9 == 0, 'depth should be 9n+2'\n",
    "\n",
    "        n = (depth - 2) // 9  # depth = 164, n = 18\n",
    "        block = Bottleneck\n",
    "        self.block_cfg = conv_cfg\n",
    "        self.inplanes = 16\n",
    "\n",
    "        # model config\n",
    "        if cfg is None:\n",
    "            cfg = [[16, 16, 16], [64, 16, 16] * (n - 1),\n",
    "                   [64, 32, 32], [128, 32, 32] * (n - 1),\n",
    "                   [128, 64, 64], [256, 64, 64] * (n - 1), [256]]\n",
    "            cfg = [item for sub_list in cfg for item in sub_list]\n",
    "\n",
    "        # model feature\n",
    "        self.conv1 = nn.Conv2d(3, 16, kernel_size=3, padding=1, bias=False)\n",
    "        self.layer1 = self._make_layer(block, 16, n, cfg=cfg[0: 3 * n])\n",
    "        self.layer2 = self._make_layer(block, 32, n, cfg=cfg[3 * n: 6 * n], stride=2)\n",
    "        self.layer3 = self._make_layer(block, 64, n, cfg=cfg[6 * n:9 * n], stride=2)\n",
    "        self.bn = nn.BatchNorm2d(64 * block.expansion)\n",
    "        self.select = channel_selection(64 * block.expansion)\n",
    "        self.relu = nn.ReLU(inplace=True)\n",
    "        self.avgpool = nn.AvgPool2d(8)\n",
    "\n",
    "        # model classifier\n",
    "        if dataset == 'cifar10':\n",
    "            num_classes = 10\n",
    "        elif dataset == 'cifar100':\n",
    "            num_classes = 100\n",
    "        else:\n",
    "            raise ValueError('Model `dataset` parameter is Error!')\n",
    "        self.fc = nn.Linear(cfg[-1], num_classes)\n",
    "\n",
    "        # model initialize weight\n",
    "        for m in self.modules():\n",
    "            if isinstance(m, nn.Conv2d):\n",
    "                n = m.kernel_size[0] * m.kernel_size[1] * m.out_channels\n",
    "                m.weight.data.normal_(0, math.sqrt(2. / n))\n",
    "            elif isinstance(m, nn.BatchNorm2d):\n",
    "                m.weight.data.fill_(0.5)\n",
    "                m.bias.data.zero_()\n",
    "\n",
    "    def _make_layer(self, block, planes, blocks, cfg, stride=1):\n",
    "        \"\"\"\n",
    "        :param block: Bottleneck item\n",
    "        :param planes: record the layer's output channel size\n",
    "                        planes * expansion = output_planes_size,\n",
    "                        like 16 * 4 = 128 (the first block output)\n",
    "        :param blocks: number of Bottleneck in layer\n",
    "        :param cfg:  channel config of all blocks\n",
    "                        3 cfg items / Bottleneck\n",
    "        :param stride: default = 1\n",
    "        \"\"\"\n",
    "        downsample = None\n",
    "        if stride != 1 or self.inplanes != planes * block.expansion:\n",
    "            downsample = nn.Sequential(\n",
    "                nn.Conv2d(self.inplanes, planes * block.expansion,\n",
    "                          kernel_size=1, stride=stride, bias=False))\n",
    "        layers = [block(self.inplanes, planes, cfg[0:3], stride, downsample)]\n",
    "        self.inplanes = planes * block.expansion\n",
    "        for i in range(1, blocks):\n",
    "            layers.append(block(self.inplanes, planes, cfg[3 * i: 3 * (i + 1)]))\n",
    "        return nn.Sequential(*layers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        x = self.conv1(x)\n",
    "\n",
    "        block_value = []\n",
    "        if self.block_cfg:\n",
    "            for idx, item in enumerate(self.layer1):\n",
    "                x = item(x)\n",
    "                if idx + 1 in self.block_cfg:\n",
    "                    block_value.append(x)\n",
    "            for idx, item in enumerate(self.layer2):\n",
    "                x = item(x)\n",
    "                if idx + 1 in self.block_cfg:\n",
    "                    block_value.append(x)\n",
    "            for idx, item in enumerate(self.layer3):\n",
    "                x = item(x)\n",
    "                if idx + 1 in self.block_cfg:\n",
    "                    block_value.append(x)\n",
    "        else:\n",
    "            x = self.layer1(x)\n",
    "            x = self.layer2(x)\n",
    "            x = self.layer3(x)\n",
    "\n",
    "        x = self.bn(x)\n",
    "        x = self.select(x)\n",
    "        x = self.relu(x)\n",
    "\n",
    "        x = self.avgpool(x)\n",
    "        x = x.view(x.size(0), -1)\n",
    "        y = self.fc(x)\n",
    "\n",
    "        if len(block_value):\n",
    "            return y, block_value\n",
    "        return y\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=> loading checkpoint 'D:\\Project\\Gitee\\network-slimming\\logs\\at_prune_resnet164_cifar100_percent_0.4\\pruned.pt'\n",
      "-> model cfg is loading...\n",
      " cfg: [5, 13, 15, 13, 14, 15, 20, 15, 15, 13, 12, 13, 16, 13, 14, 16, 15, 14, 18, 13, 13, 21, 14, 16, 14, 12, 15, 23, 15, 14, 14, 13, 13, 16, 14, 16, 2, 8, 13, 7, 14, 14, 19, 13, 14, 15, 15, 16, 3, 8, 10, 10, 14, 16, 17, 26, 32, 43, 32, 32, 39, 31, 31, 46, 30, 32, 46, 31, 32, 42, 32, 32, 49, 28, 32, 45, 32, 32, 50, 30, 30, 55, 32, 32, 60, 30, 32, 44, 29, 31, 52, 29, 32, 46, 32, 31, 57, 32, 32, 57, 32, 32, 50, 31, 32, 52, 31, 31, 78, 60, 64, 107, 63, 64, 117, 64, 63, 122, 63, 64, 118, 63, 64, 110, 63, 64, 113, 63, 64, 121, 64, 64, 121, 63, 64, 127, 64, 64, 119, 64, 64, 131, 64, 64, 130, 64, 64, 130, 64, 64, 120, 64, 64, 119, 64, 64, 119, 64, 64, 109, 64, 64, 157]\n",
      "=>  epoch None Prec1: None\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "def resume_model(resume_file):\n",
    "    if not os.path.isfile(resume_file):\n",
    "        raise ValueError(\"Resume model file is not found at '{}'\".format(resume_file))\n",
    "    print(\"=> loading checkpoint '{}'\".format(resume_file))\n",
    "    checkpoint = torch.load(resume_file)\n",
    "    if 'epoch' in checkpoint:\n",
    "        start_epoch = checkpoint['epoch']\n",
    "    else:\n",
    "        start_epoch = None\n",
    "        \n",
    "    if 'best_prec1' in checkpoint:\n",
    "        best_prec1 = checkpoint['best_prec1']\n",
    "    else:\n",
    "        best_prec1 = None\n",
    "        \n",
    "    if 'state_dict' in checkpoint:\n",
    "        state_dict = checkpoint['state_dict']\n",
    "    else:\n",
    "        state_dict = None\n",
    "    \n",
    "    if 'optimizer' in checkpoint:\n",
    "        opti_dict = checkpoint['optimizer']\n",
    "    else:\n",
    "        opti_dict = None\n",
    "        \n",
    "    if 'cfg' in checkpoint:\n",
    "        cfg = checkpoint['cfg']\n",
    "        print(\"-> model cfg is loading...\\n cfg: {}\".format(list(cfg)))\n",
    "    else:\n",
    "        cfg = None\n",
    "        print(\"-> not found model cfg...\")\n",
    "    print(\"=>  epoch {} Prec1: {}\".format(start_epoch, best_prec1))\n",
    "    return state_dict, opti_dict, start_epoch, best_prec1, cfg\n",
    "\n",
    "\n",
    "data_path = {\n",
    "    'root': r'D:\\Project\\Pycharm\\network-slimming\\logs',\n",
    "    'root2': r'D:\\Project\\Gitee\\network-slimming\\logs',\n",
    "    'bn': [\n",
    "        'bn_prune_resnet164_cifar10_percent_0.4',\n",
    "        'bn_prune_resnet164_cifar10_percent_0.6',\n",
    "        'bn_prune_resnet164_cifar100_percent_0.4',\n",
    "        'bn_prune_resnet164_cifar100_percent_0.6',\n",
    "    ],\n",
    "    'at': [\n",
    "         'at_prune_resnet164_cifar10_percent_0.4',\n",
    "         'at_prune_resnet164_cifar10_percent_0.6',\n",
    "         'at_prune_resnet164_cifar100_percent_0.4',\n",
    "         'at_prune_resnet164_cifar100_percent_0.6',\n",
    "    ],\n",
    "    'flie': 'model_best.pt',\n",
    "    'file2': 'model_best.pth.tar',\n",
    "    'file3': 'pruned.pt',\n",
    "    'file4': 'pruned.pth.tar'\n",
    "}\n",
    "\n",
    "file_path = os.path.join(data_path['root2'], data_path['at'][2], data_path['file3'])\n",
    "state_dict, opti_dict, start_epoch, best_prec1, cfg = resume_model(file_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "resnet(\n",
       "  (conv1): Conv2d(3, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "  (layer1): Sequential(\n",
       "    (0): Bottleneck(\n",
       "      (bn1): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(5, 13, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(13, 15, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(15, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "      (downsample): Sequential(\n",
       "        (0): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      )\n",
       "    )\n",
       "    (1): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(13, 14, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(14, 15, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(15, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (2): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(20, 15, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(15, 15, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(15, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (3): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(13, 12, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(12, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(12, 13, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(13, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (4): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(16, 13, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(13, 14, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(14, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (5): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(16, 15, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(15, 14, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(14, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (6): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(18, 13, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(13, 13, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(13, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (7): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(21, 14, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(14, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (8): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(14, 12, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(12, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(12, 15, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(15, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (9): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(23, 15, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(15, 14, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(14, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (10): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(14, 13, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(13, 13, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(13, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (11): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(16, 14, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(14, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (12): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(2, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(8, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(8, 13, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(13, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (13): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(7, 14, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(14, 14, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(14, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (14): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(19, 13, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(13, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(13, 14, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(14, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (15): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(15, 15, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(15, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(15, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (16): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(3, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(8, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(8, 10, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(10, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(10, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (17): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(10, 14, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(14, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(14, 16, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (layer2): Sequential(\n",
       "    (0): Bottleneck(\n",
       "      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(17, 26, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(26, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(26, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "      (downsample): Sequential(\n",
       "        (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "      )\n",
       "    )\n",
       "    (1): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(43, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (2): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(39, 31, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(31, 31, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(31, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (3): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(46, 30, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(30, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(30, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (4): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(46, 31, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(31, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (5): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(42, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (6): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(49, 28, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(28, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(28, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (7): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(45, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (8): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(50, 30, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(30, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(30, 30, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(30, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(30, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (9): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(55, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (10): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(60, 30, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(30, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(30, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (11): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(44, 29, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(29, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(29, 31, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(31, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (12): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(52, 29, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(29, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(29, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (13): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(46, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 31, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(31, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (14): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(57, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (15): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(57, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (16): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(50, 31, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(31, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(32, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (17): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(52, 31, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(31, 31, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(31, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(31, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (layer3): Sequential(\n",
       "    (0): Bottleneck(\n",
       "      (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(78, 60, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(60, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(60, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "      (downsample): Sequential(\n",
       "        (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
       "      )\n",
       "    )\n",
       "    (1): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(107, 63, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(63, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (2): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(117, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 63, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(63, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (3): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(122, 63, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(63, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (4): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(118, 63, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(63, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (5): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(110, 63, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(63, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (6): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(113, 63, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(63, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (7): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(121, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (8): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(121, 63, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(63, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(63, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (9): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(127, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (10): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(119, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (11): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(131, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (12): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(130, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (13): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(130, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (14): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(120, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (15): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(119, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (16): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(119, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "    (17): Bottleneck(\n",
       "      (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (select): channel_selection()\n",
       "      (conv1): Conv2d(109, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn3): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "      (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (relu): ReLU(inplace=True)\n",
       "    )\n",
       "  )\n",
       "  (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  (select): channel_selection()\n",
       "  (relu): ReLU(inplace=True)\n",
       "  (avgpool): AvgPool2d(kernel_size=8, stride=8, padding=0)\n",
       "  (fc): Linear(in_features=157, out_features=100, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = resnet(depth=164, dataset='cifar100', cfg=cfg, conv_cfg=None)\n",
    "model.load_state_dict(state_dict)\n",
    "model.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "[MAdd]: channel_selection is not supported!\n",
      "[Flops]: channel_selection is not supported!\n",
      "[Memory]: channel_selection is not supported!\n",
      "                 module name  input shape output shape     params memory(MB)           MAdd          Flops  MemRead(B)  MemWrite(B) duration[%]   MemR+W(B)\n",
      "0                      conv1    3  32  32   16  32  32      432.0       0.06      868,352.0      442,368.0     14016.0      65536.0       1.69%     79552.0\n",
      "1               layer1.0.bn1   16  32  32   16  32  32       32.0       0.06       65,536.0       32,768.0     65664.0      65536.0       0.00%    131200.0\n",
      "2            layer1.0.select   16  32  32    5  32  32       16.0       0.02            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "3             layer1.0.conv1    5  32  32   13  32  32       65.0       0.05      119,808.0       66,560.0     20740.0      53248.0       0.00%     73988.0\n",
      "4               layer1.0.bn2   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "5             layer1.0.conv2   13  32  32   15  32  32     1755.0       0.06    3,578,880.0    1,797,120.0     60268.0      61440.0       0.85%    121708.0\n",
      "6               layer1.0.bn3   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "7             layer1.0.conv3   15  32  32   64  32  32      960.0       0.25    1,900,544.0      983,040.0     65280.0     262144.0       0.00%    327424.0\n",
      "8              layer1.0.relu   15  32  32   15  32  32        0.0       0.06       15,360.0       15,360.0     61440.0      61440.0       0.00%    122880.0\n",
      "9      layer1.0.downsample.0   16  32  32   64  32  32     1024.0       0.25    2,031,616.0    1,048,576.0     69632.0     262144.0       0.00%    331776.0\n",
      "10              layer1.1.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "11           layer1.1.select   64  32  32   13  32  32       64.0       0.05            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "12            layer1.1.conv1   13  32  32   14  32  32      182.0       0.05      358,400.0      186,368.0     53976.0      57344.0       0.84%    111320.0\n",
      "13              layer1.1.bn2   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "14            layer1.1.conv2   14  32  32   15  32  32     1890.0       0.06    3,855,360.0    1,935,360.0     64904.0      61440.0       0.84%    126344.0\n",
      "15              layer1.1.bn3   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "16            layer1.1.conv3   15  32  32   64  32  32      960.0       0.25    1,900,544.0      983,040.0     65280.0     262144.0       0.00%    327424.0\n",
      "17             layer1.1.relu   15  32  32   15  32  32        0.0       0.06       15,360.0       15,360.0     61440.0      61440.0       0.84%    122880.0\n",
      "18              layer1.2.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.84%    524800.0\n",
      "19           layer1.2.select   64  32  32   20  32  32       64.0       0.08            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "20            layer1.2.conv1   20  32  32   15  32  32      300.0       0.06      599,040.0      307,200.0     83120.0      61440.0       0.00%    144560.0\n",
      "21              layer1.2.bn2   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "22            layer1.2.conv2   15  32  32   15  32  32     2025.0       0.06    4,131,840.0    2,073,600.0     69540.0      61440.0       0.84%    130980.0\n",
      "23              layer1.2.bn3   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "24            layer1.2.conv3   15  32  32   64  32  32      960.0       0.25    1,900,544.0      983,040.0     65280.0     262144.0       0.00%    327424.0\n",
      "25             layer1.2.relu   15  32  32   15  32  32        0.0       0.06       15,360.0       15,360.0     61440.0      61440.0       0.00%    122880.0\n",
      "26              layer1.3.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "27           layer1.3.select   64  32  32   13  32  32       64.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "28            layer1.3.conv1   13  32  32   12  32  32      156.0       0.05      307,200.0      159,744.0     53872.0      49152.0       0.84%    103024.0\n",
      "29              layer1.3.bn2   12  32  32   12  32  32       24.0       0.05       49,152.0       24,576.0     49248.0      49152.0       0.00%     98400.0\n",
      "30            layer1.3.conv2   12  32  32   13  32  32     1404.0       0.05    2,862,080.0    1,437,696.0     54768.0      53248.0       0.00%    108016.0\n",
      "31              layer1.3.bn3   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "32            layer1.3.conv3   13  32  32   64  32  32      832.0       0.25    1,638,400.0      851,968.0     56576.0     262144.0       0.84%    318720.0\n",
      "33             layer1.3.relu   13  32  32   13  32  32        0.0       0.05       13,312.0       13,312.0     53248.0      53248.0       0.00%    106496.0\n",
      "34              layer1.4.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.84%    524800.0\n",
      "35           layer1.4.select   64  32  32   16  32  32       64.0       0.06            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "36            layer1.4.conv1   16  32  32   13  32  32      208.0       0.05      412,672.0      212,992.0     66368.0      53248.0       0.00%    119616.0\n",
      "37              layer1.4.bn2   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "38            layer1.4.conv2   13  32  32   14  32  32     1638.0       0.05    3,340,288.0    1,677,312.0     59800.0      57344.0       0.84%    117144.0\n",
      "39              layer1.4.bn3   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "40            layer1.4.conv3   14  32  32   64  32  32      896.0       0.25    1,769,472.0      917,504.0     60928.0     262144.0       0.00%    323072.0\n",
      "41             layer1.4.relu   14  32  32   14  32  32        0.0       0.05       14,336.0       14,336.0     57344.0      57344.0       0.00%    114688.0\n",
      "42              layer1.5.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "43           layer1.5.select   64  32  32   16  32  32       64.0       0.06            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "44            layer1.5.conv1   16  32  32   15  32  32      240.0       0.06      476,160.0      245,760.0     66496.0      61440.0       0.00%    127936.0\n",
      "45              layer1.5.bn2   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "46            layer1.5.conv2   15  32  32   14  32  32     1890.0       0.05    3,856,384.0    1,935,360.0     69000.0      57344.0       0.84%    126344.0\n",
      "47              layer1.5.bn3   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "48            layer1.5.conv3   14  32  32   64  32  32      896.0       0.25    1,769,472.0      917,504.0     60928.0     262144.0       0.84%    323072.0\n",
      "49             layer1.5.relu   14  32  32   14  32  32        0.0       0.05       14,336.0       14,336.0     57344.0      57344.0       0.00%    114688.0\n",
      "50              layer1.6.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.84%    524800.0\n",
      "51           layer1.6.select   64  32  32   18  32  32       64.0       0.07            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "52            layer1.6.conv1   18  32  32   13  32  32      234.0       0.05      465,920.0      239,616.0     74664.0      53248.0       0.42%    127912.0\n",
      "53              layer1.6.bn2   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "54            layer1.6.conv2   13  32  32   13  32  32     1521.0       0.05    3,101,696.0    1,557,504.0     59332.0      53248.0       0.00%    112580.0\n",
      "55              layer1.6.bn3   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "56            layer1.6.conv3   13  32  32   64  32  32      832.0       0.25    1,638,400.0      851,968.0     56576.0     262144.0       0.85%    318720.0\n",
      "57             layer1.6.relu   13  32  32   13  32  32        0.0       0.05       13,312.0       13,312.0     53248.0      53248.0       0.00%    106496.0\n",
      "58              layer1.7.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "59           layer1.7.select   64  32  32   21  32  32       64.0       0.08            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "60            layer1.7.conv1   21  32  32   14  32  32      294.0       0.05      587,776.0      301,056.0     87192.0      57344.0       4.22%    144536.0\n",
      "61              layer1.7.bn2   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "62            layer1.7.conv2   14  32  32   16  32  32     2016.0       0.06    4,112,384.0    2,064,384.0     65408.0      65536.0       0.00%    130944.0\n",
      "63              layer1.7.bn3   16  32  32   16  32  32       32.0       0.06       65,536.0       32,768.0     65664.0      65536.0       0.00%    131200.0\n",
      "64            layer1.7.conv3   16  32  32   64  32  32     1024.0       0.25    2,031,616.0    1,048,576.0     69632.0     262144.0       0.84%    331776.0\n",
      "65             layer1.7.relu   16  32  32   16  32  32        0.0       0.06       16,384.0       16,384.0     65536.0      65536.0       0.00%    131072.0\n",
      "66              layer1.8.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "67           layer1.8.select   64  32  32   14  32  32       64.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "68            layer1.8.conv1   14  32  32   12  32  32      168.0       0.05      331,776.0      172,032.0     58016.0      49152.0       0.00%    107168.0\n",
      "69              layer1.8.bn2   12  32  32   12  32  32       24.0       0.05       49,152.0       24,576.0     49248.0      49152.0       0.84%     98400.0\n",
      "70            layer1.8.conv2   12  32  32   15  32  32     1620.0       0.06    3,302,400.0    1,658,880.0     55632.0      61440.0       0.84%    117072.0\n",
      "71              layer1.8.bn3   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "72            layer1.8.conv3   15  32  32   64  32  32      960.0       0.25    1,900,544.0      983,040.0     65280.0     262144.0       0.84%    327424.0\n",
      "73             layer1.8.relu   15  32  32   15  32  32        0.0       0.06       15,360.0       15,360.0     61440.0      61440.0       0.00%    122880.0\n",
      "74              layer1.9.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "75           layer1.9.select   64  32  32   23  32  32       64.0       0.09            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "76            layer1.9.conv1   23  32  32   15  32  32      345.0       0.06      691,200.0      353,280.0     95588.0      61440.0       0.00%    157028.0\n",
      "77              layer1.9.bn2   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "78            layer1.9.conv2   15  32  32   14  32  32     1890.0       0.05    3,856,384.0    1,935,360.0     69000.0      57344.0       0.84%    126344.0\n",
      "79              layer1.9.bn3   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "80            layer1.9.conv3   14  32  32   64  32  32      896.0       0.25    1,769,472.0      917,504.0     60928.0     262144.0       0.00%    323072.0\n",
      "81             layer1.9.relu   14  32  32   14  32  32        0.0       0.05       14,336.0       14,336.0     57344.0      57344.0       0.84%    114688.0\n",
      "82             layer1.10.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "83          layer1.10.select   64  32  32   14  32  32       64.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "84           layer1.10.conv1   14  32  32   13  32  32      182.0       0.05      359,424.0      186,368.0     58072.0      53248.0       0.00%    111320.0\n",
      "85             layer1.10.bn2   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "86           layer1.10.conv2   13  32  32   13  32  32     1521.0       0.05    3,101,696.0    1,557,504.0     59332.0      53248.0       0.86%    112580.0\n",
      "87             layer1.10.bn3   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.83%    106600.0\n",
      "88           layer1.10.conv3   13  32  32   64  32  32      832.0       0.25    1,638,400.0      851,968.0     56576.0     262144.0       0.84%    318720.0\n",
      "89            layer1.10.relu   13  32  32   13  32  32        0.0       0.05       13,312.0       13,312.0     53248.0      53248.0       0.00%    106496.0\n",
      "90             layer1.11.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.87%    524800.0\n",
      "91          layer1.11.select   64  32  32   16  32  32       64.0       0.06            0.0            0.0         0.0          0.0       0.39%         0.0\n",
      "92           layer1.11.conv1   16  32  32   14  32  32      224.0       0.05      444,416.0      229,376.0     66432.0      57344.0       0.00%    123776.0\n",
      "93             layer1.11.bn2   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "94           layer1.11.conv2   14  32  32   16  32  32     2016.0       0.06    4,112,384.0    2,064,384.0     65408.0      65536.0       0.84%    130944.0\n",
      "95             layer1.11.bn3   16  32  32   16  32  32       32.0       0.06       65,536.0       32,768.0     65664.0      65536.0       0.00%    131200.0\n",
      "96           layer1.11.conv3   16  32  32   64  32  32     1024.0       0.25    2,031,616.0    1,048,576.0     69632.0     262144.0       0.84%    331776.0\n",
      "97            layer1.11.relu   16  32  32   16  32  32        0.0       0.06       16,384.0       16,384.0     65536.0      65536.0       0.00%    131072.0\n",
      "98             layer1.12.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "99          layer1.12.select   64  32  32    2  32  32       64.0       0.01            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "100          layer1.12.conv1    2  32  32    8  32  32       16.0       0.03       24,576.0       16,384.0      8256.0      32768.0       0.00%     41024.0\n",
      "101            layer1.12.bn2    8  32  32    8  32  32       16.0       0.03       32,768.0       16,384.0     32832.0      32768.0       0.00%     65600.0\n",
      "102          layer1.12.conv2    8  32  32   13  32  32      936.0       0.05    1,903,616.0      958,464.0     36512.0      53248.0       0.84%     89760.0\n",
      "103            layer1.12.bn3   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "104          layer1.12.conv3   13  32  32   64  32  32      832.0       0.25    1,638,400.0      851,968.0     56576.0     262144.0       0.00%    318720.0\n",
      "105           layer1.12.relu   13  32  32   13  32  32        0.0       0.05       13,312.0       13,312.0     53248.0      53248.0       0.84%    106496.0\n",
      "106            layer1.13.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "107         layer1.13.select   64  32  32    7  32  32       64.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "108          layer1.13.conv1    7  32  32   14  32  32       98.0       0.05      186,368.0      100,352.0     29064.0      57344.0       0.00%     86408.0\n",
      "109            layer1.13.bn2   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "110          layer1.13.conv2   14  32  32   14  32  32     1764.0       0.05    3,598,336.0    1,806,336.0     64400.0      57344.0       0.84%    121744.0\n",
      "111            layer1.13.bn3   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.00%    114800.0\n",
      "112          layer1.13.conv3   14  32  32   64  32  32      896.0       0.25    1,769,472.0      917,504.0     60928.0     262144.0       0.00%    323072.0\n",
      "113           layer1.13.relu   14  32  32   14  32  32        0.0       0.05       14,336.0       14,336.0     57344.0      57344.0       0.00%    114688.0\n",
      "114            layer1.14.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "115         layer1.14.select   64  32  32   19  32  32       64.0       0.07            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "116          layer1.14.conv1   19  32  32   13  32  32      247.0       0.05      492,544.0      252,928.0     78812.0      53248.0       0.00%    132060.0\n",
      "117            layer1.14.bn2   13  32  32   13  32  32       26.0       0.05       53,248.0       26,624.0     53352.0      53248.0       0.00%    106600.0\n",
      "118          layer1.14.conv2   13  32  32   14  32  32     1638.0       0.05    3,340,288.0    1,677,312.0     59800.0      57344.0       0.87%    117144.0\n",
      "119            layer1.14.bn3   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.43%    114800.0\n",
      "120          layer1.14.conv3   14  32  32   64  32  32      896.0       0.25    1,769,472.0      917,504.0     60928.0     262144.0       0.84%    323072.0\n",
      "121           layer1.14.relu   14  32  32   14  32  32        0.0       0.05       14,336.0       14,336.0     57344.0      57344.0       0.00%    114688.0\n",
      "122            layer1.15.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "123         layer1.15.select   64  32  32   15  32  32       64.0       0.06            0.0            0.0         0.0          0.0       0.82%         0.0\n",
      "124          layer1.15.conv1   15  32  32   15  32  32      225.0       0.06      445,440.0      230,400.0     62340.0      61440.0       0.00%    123780.0\n",
      "125            layer1.15.bn2   15  32  32   15  32  32       30.0       0.06       61,440.0       30,720.0     61560.0      61440.0       0.00%    123000.0\n",
      "126          layer1.15.conv2   15  32  32   16  32  32     2160.0       0.06    4,407,296.0    2,211,840.0     70080.0      65536.0       0.87%    135616.0\n",
      "127            layer1.15.bn3   16  32  32   16  32  32       32.0       0.06       65,536.0       32,768.0     65664.0      65536.0       0.00%    131200.0\n",
      "128          layer1.15.conv3   16  32  32   64  32  32     1024.0       0.25    2,031,616.0    1,048,576.0     69632.0     262144.0       0.82%    331776.0\n",
      "129           layer1.15.relu   16  32  32   16  32  32        0.0       0.06       16,384.0       16,384.0     65536.0      65536.0       0.00%    131072.0\n",
      "130            layer1.16.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "131         layer1.16.select   64  32  32    3  32  32       64.0       0.01            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "132          layer1.16.conv1    3  32  32    8  32  32       24.0       0.03       40,960.0       24,576.0     12384.0      32768.0       0.00%     45152.0\n",
      "133            layer1.16.bn2    8  32  32    8  32  32       16.0       0.03       32,768.0       16,384.0     32832.0      32768.0       0.00%     65600.0\n",
      "134          layer1.16.conv2    8  32  32   10  32  32      720.0       0.04    1,464,320.0      737,280.0     35648.0      40960.0       0.87%     76608.0\n",
      "135            layer1.16.bn3   10  32  32   10  32  32       20.0       0.04       40,960.0       20,480.0     41040.0      40960.0       0.00%     82000.0\n",
      "136          layer1.16.conv3   10  32  32   64  32  32      640.0       0.25    1,245,184.0      655,360.0     43520.0     262144.0       0.00%    305664.0\n",
      "137           layer1.16.relu   10  32  32   10  32  32        0.0       0.04       10,240.0       10,240.0     40960.0      40960.0       0.42%     81920.0\n",
      "138            layer1.17.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.42%    524800.0\n",
      "139         layer1.17.select   64  32  32   10  32  32       64.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "140          layer1.17.conv1   10  32  32   14  32  32      140.0       0.05      272,384.0      143,360.0     41520.0      57344.0       0.00%     98864.0\n",
      "141            layer1.17.bn2   14  32  32   14  32  32       28.0       0.05       57,344.0       28,672.0     57456.0      57344.0       0.84%    114800.0\n",
      "142          layer1.17.conv2   14  32  32   16  32  32     2016.0       0.06    4,112,384.0    2,064,384.0     65408.0      65536.0       0.84%    130944.0\n",
      "143            layer1.17.bn3   16  32  32   16  32  32       32.0       0.06       65,536.0       32,768.0     65664.0      65536.0       0.00%    131200.0\n",
      "144          layer1.17.conv3   16  32  32   64  32  32     1024.0       0.25    2,031,616.0    1,048,576.0     69632.0     262144.0       0.00%    331776.0\n",
      "145           layer1.17.relu   16  32  32   16  32  32        0.0       0.06       16,384.0       16,384.0     65536.0      65536.0       0.00%    131072.0\n",
      "146             layer2.0.bn1   64  32  32   64  32  32      128.0       0.25      262,144.0      131,072.0    262656.0     262144.0       0.00%    524800.0\n",
      "147          layer2.0.select   64  32  32   17  32  32       64.0       0.07            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "148           layer2.0.conv1   17  32  32   26  32  32      442.0       0.10      878,592.0      452,608.0     71400.0     106496.0       0.00%    177896.0\n",
      "149             layer2.0.bn2   26  32  32   26  32  32       52.0       0.10      106,496.0       53,248.0    106704.0     106496.0       0.00%    213200.0\n",
      "150           layer2.0.conv2   26  32  32   32  16  16     7488.0       0.03    3,825,664.0    1,916,928.0    136448.0      32768.0       0.84%    169216.0\n",
      "151             layer2.0.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "152           layer2.0.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.84%    180224.0\n",
      "153            layer2.0.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "154    layer2.0.downsample.0   64  32  32  128  16  16     8192.0       0.12    4,161,536.0    2,097,152.0    294912.0     131072.0       0.84%    425984.0\n",
      "155             layer2.1.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "156          layer2.1.select  128  16  16   43  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "157           layer2.1.conv1   43  16  16   32  16  16     1376.0       0.03      696,320.0      352,256.0     49536.0      32768.0       0.00%     82304.0\n",
      "158             layer2.1.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "159           layer2.1.conv2   32  16  16   32  16  16     9216.0       0.03    4,710,400.0    2,359,296.0     69632.0      32768.0       0.84%    102400.0\n",
      "160             layer2.1.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "161           layer2.1.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.84%    180224.0\n",
      "162            layer2.1.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "163             layer2.2.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "164          layer2.2.select  128  16  16   39  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "165           layer2.2.conv1   39  16  16   31  16  16     1209.0       0.03      611,072.0      309,504.0     44772.0      31744.0       0.00%     76516.0\n",
      "166             layer2.2.bn2   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "167           layer2.2.conv2   31  16  16   31  16  16     8649.0       0.03    4,420,352.0    2,214,144.0     66340.0      31744.0       0.84%     98084.0\n",
      "168             layer2.2.bn3   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "169           layer2.2.conv3   31  16  16  128  16  16     3968.0       0.12    1,998,848.0    1,015,808.0     47616.0     131072.0       0.00%    178688.0\n",
      "170            layer2.2.relu   31  16  16   31  16  16        0.0       0.03        7,936.0        7,936.0     31744.0      31744.0       0.84%     63488.0\n",
      "171             layer2.3.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "172          layer2.3.select  128  16  16   46  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "173           layer2.3.conv1   46  16  16   30  16  16     1380.0       0.03      698,880.0      353,280.0     52624.0      30720.0       0.00%     83344.0\n",
      "174             layer2.3.bn2   30  16  16   30  16  16       60.0       0.03       30,720.0       15,360.0     30960.0      30720.0       0.00%     61680.0\n",
      "175           layer2.3.conv2   30  16  16   32  16  16     8640.0       0.03    4,415,488.0    2,211,840.0     65280.0      32768.0       0.85%     98048.0\n",
      "176             layer2.3.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.84%     65792.0\n",
      "177           layer2.3.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "178            layer2.3.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "179             layer2.4.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "180          layer2.4.select  128  16  16   46  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "181           layer2.4.conv1   46  16  16   31  16  16     1426.0       0.03      722,176.0      365,056.0     52808.0      31744.0       0.00%     84552.0\n",
      "182             layer2.4.bn2   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.84%     63736.0\n",
      "183           layer2.4.conv2   31  16  16   32  16  16     8928.0       0.03    4,562,944.0    2,285,568.0     67456.0      32768.0       0.84%    100224.0\n",
      "184             layer2.4.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "185           layer2.4.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "186            layer2.4.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "187             layer2.5.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "188          layer2.5.select  128  16  16   42  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "189           layer2.5.conv1   42  16  16   32  16  16     1344.0       0.03      679,936.0      344,064.0     48384.0      32768.0       0.00%     81152.0\n",
      "190             layer2.5.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "191           layer2.5.conv2   32  16  16   32  16  16     9216.0       0.03    4,710,400.0    2,359,296.0     69632.0      32768.0       0.84%    102400.0\n",
      "192             layer2.5.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "193           layer2.5.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "194            layer2.5.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "195             layer2.6.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.85%    263168.0\n",
      "196          layer2.6.select  128  16  16   49  16  16      128.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "197           layer2.6.conv1   49  16  16   28  16  16     1372.0       0.03      695,296.0      351,232.0     55664.0      28672.0       0.00%     84336.0\n",
      "198             layer2.6.bn2   28  16  16   28  16  16       56.0       0.03       28,672.0       14,336.0     28896.0      28672.0       0.00%     57568.0\n",
      "199           layer2.6.conv2   28  16  16   32  16  16     8064.0       0.03    4,120,576.0    2,064,384.0     60928.0      32768.0       0.00%     93696.0\n",
      "200             layer2.6.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "201           layer2.6.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.84%    180224.0\n",
      "202            layer2.6.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "203             layer2.7.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "204          layer2.7.select  128  16  16   45  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "205           layer2.7.conv1   45  16  16   32  16  16     1440.0       0.03      729,088.0      368,640.0     51840.0      32768.0       0.00%     84608.0\n",
      "206             layer2.7.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "207           layer2.7.conv2   32  16  16   32  16  16     9216.0       0.03    4,710,400.0    2,359,296.0     69632.0      32768.0       0.84%    102400.0\n",
      "208             layer2.7.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "209           layer2.7.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "210            layer2.7.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "211             layer2.8.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "212          layer2.8.select  128  16  16   50  16  16      128.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "213           layer2.8.conv1   50  16  16   30  16  16     1500.0       0.03      760,320.0      384,000.0     57200.0      30720.0       0.00%     87920.0\n",
      "214             layer2.8.bn2   30  16  16   30  16  16       60.0       0.03       30,720.0       15,360.0     30960.0      30720.0       0.00%     61680.0\n",
      "215           layer2.8.conv2   30  16  16   30  16  16     8100.0       0.03    4,139,520.0    2,073,600.0     63120.0      30720.0       0.85%     93840.0\n",
      "216             layer2.8.bn3   30  16  16   30  16  16       60.0       0.03       30,720.0       15,360.0     30960.0      30720.0       0.00%     61680.0\n",
      "217           layer2.8.conv3   30  16  16  128  16  16     3840.0       0.12    1,933,312.0      983,040.0     46080.0     131072.0       0.00%    177152.0\n",
      "218            layer2.8.relu   30  16  16   30  16  16        0.0       0.03        7,680.0        7,680.0     30720.0      30720.0       0.84%     61440.0\n",
      "219             layer2.9.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "220          layer2.9.select  128  16  16   55  16  16      128.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "221           layer2.9.conv1   55  16  16   32  16  16     1760.0       0.03      892,928.0      450,560.0     63360.0      32768.0       0.00%     96128.0\n",
      "222             layer2.9.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "223           layer2.9.conv2   32  16  16   32  16  16     9216.0       0.03    4,710,400.0    2,359,296.0     69632.0      32768.0       0.84%    102400.0\n",
      "224             layer2.9.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "225           layer2.9.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.84%    180224.0\n",
      "226            layer2.9.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "227            layer2.10.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "228         layer2.10.select  128  16  16   60  16  16      128.0       0.06            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "229          layer2.10.conv1   60  16  16   30  16  16     1800.0       0.03      913,920.0      460,800.0     68640.0      30720.0       0.84%     99360.0\n",
      "230            layer2.10.bn2   30  16  16   30  16  16       60.0       0.03       30,720.0       15,360.0     30960.0      30720.0       0.00%     61680.0\n",
      "231          layer2.10.conv2   30  16  16   32  16  16     8640.0       0.03    4,415,488.0    2,211,840.0     65280.0      32768.0       0.00%     98048.0\n",
      "232            layer2.10.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.84%     65792.0\n",
      "233          layer2.10.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "234           layer2.10.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "235            layer2.11.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "236         layer2.11.select  128  16  16   44  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "237          layer2.11.conv1   44  16  16   29  16  16     1276.0       0.03      645,888.0      326,656.0     50160.0      29696.0       0.00%     79856.0\n",
      "238            layer2.11.bn2   29  16  16   29  16  16       58.0       0.03       29,696.0       14,848.0     29928.0      29696.0       0.00%     59624.0\n",
      "239          layer2.11.conv2   29  16  16   31  16  16     8091.0       0.03    4,134,656.0    2,071,296.0     62060.0      31744.0       0.84%     93804.0\n",
      "240            layer2.11.bn3   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "241          layer2.11.conv3   31  16  16  128  16  16     3968.0       0.12    1,998,848.0    1,015,808.0     47616.0     131072.0       0.84%    178688.0\n",
      "242           layer2.11.relu   31  16  16   31  16  16        0.0       0.03        7,936.0        7,936.0     31744.0      31744.0       0.00%     63488.0\n",
      "243            layer2.12.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "244         layer2.12.select  128  16  16   52  16  16      128.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "245          layer2.12.conv1   52  16  16   29  16  16     1508.0       0.03      764,672.0      386,048.0     59280.0      29696.0       0.84%     88976.0\n",
      "246            layer2.12.bn2   29  16  16   29  16  16       58.0       0.03       29,696.0       14,848.0     29928.0      29696.0       0.00%     59624.0\n",
      "247          layer2.12.conv2   29  16  16   32  16  16     8352.0       0.03    4,268,032.0    2,138,112.0     63104.0      32768.0       0.84%     95872.0\n",
      "248            layer2.12.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.84%     65792.0\n",
      "249          layer2.12.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.84%    180224.0\n",
      "250           layer2.12.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "251            layer2.13.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "252         layer2.13.select  128  16  16   46  16  16      128.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "253          layer2.13.conv1   46  16  16   32  16  16     1472.0       0.03      745,472.0      376,832.0     52992.0      32768.0       0.00%     85760.0\n",
      "254            layer2.13.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "255          layer2.13.conv2   32  16  16   31  16  16     8928.0       0.03    4,563,200.0    2,285,568.0     68480.0      31744.0       0.84%    100224.0\n",
      "256            layer2.13.bn3   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "257          layer2.13.conv3   31  16  16  128  16  16     3968.0       0.12    1,998,848.0    1,015,808.0     47616.0     131072.0       0.84%    178688.0\n",
      "258           layer2.13.relu   31  16  16   31  16  16        0.0       0.03        7,936.0        7,936.0     31744.0      31744.0       0.00%     63488.0\n",
      "259            layer2.14.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "260         layer2.14.select  128  16  16   57  16  16      128.0       0.06            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "261          layer2.14.conv1   57  16  16   32  16  16     1824.0       0.03      925,696.0      466,944.0     65664.0      32768.0       0.00%     98432.0\n",
      "262            layer2.14.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "263          layer2.14.conv2   32  16  16   32  16  16     9216.0       0.03    4,710,400.0    2,359,296.0     69632.0      32768.0       0.84%    102400.0\n",
      "264            layer2.14.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "265          layer2.14.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.84%    180224.0\n",
      "266           layer2.14.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "267            layer2.15.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "268         layer2.15.select  128  16  16   57  16  16      128.0       0.06            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "269          layer2.15.conv1   57  16  16   32  16  16     1824.0       0.03      925,696.0      466,944.0     65664.0      32768.0       0.00%     98432.0\n",
      "270            layer2.15.bn2   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.85%     65792.0\n",
      "271          layer2.15.conv2   32  16  16   32  16  16     9216.0       0.03    4,710,400.0    2,359,296.0     69632.0      32768.0       0.84%    102400.0\n",
      "272            layer2.15.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.84%     65792.0\n",
      "273          layer2.15.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "274           layer2.15.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "275            layer2.16.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "276         layer2.16.select  128  16  16   50  16  16      128.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "277          layer2.16.conv1   50  16  16   31  16  16     1550.0       0.03      785,664.0      396,800.0     57400.0      31744.0       0.00%     89144.0\n",
      "278            layer2.16.bn2   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "279          layer2.16.conv2   31  16  16   32  16  16     8928.0       0.03    4,562,944.0    2,285,568.0     67456.0      32768.0       0.84%    100224.0\n",
      "280            layer2.16.bn3   32  16  16   32  16  16       64.0       0.03       32,768.0       16,384.0     33024.0      32768.0       0.00%     65792.0\n",
      "281          layer2.16.conv3   32  16  16  128  16  16     4096.0       0.12    2,064,384.0    1,048,576.0     49152.0     131072.0       0.00%    180224.0\n",
      "282           layer2.16.relu   32  16  16   32  16  16        0.0       0.03        8,192.0        8,192.0     32768.0      32768.0       0.00%     65536.0\n",
      "283            layer2.17.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "284         layer2.17.select  128  16  16   52  16  16      128.0       0.05            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "285          layer2.17.conv1   52  16  16   31  16  16     1612.0       0.03      817,408.0      412,672.0     59696.0      31744.0       0.00%     91440.0\n",
      "286            layer2.17.bn2   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "287          layer2.17.conv2   31  16  16   31  16  16     8649.0       0.03    4,420,352.0    2,214,144.0     66340.0      31744.0       0.00%     98084.0\n",
      "288            layer2.17.bn3   31  16  16   31  16  16       62.0       0.03       31,744.0       15,872.0     31992.0      31744.0       0.00%     63736.0\n",
      "289          layer2.17.conv3   31  16  16  128  16  16     3968.0       0.12    1,998,848.0    1,015,808.0     47616.0     131072.0       0.84%    178688.0\n",
      "290           layer2.17.relu   31  16  16   31  16  16        0.0       0.03        7,936.0        7,936.0     31744.0      31744.0       0.84%     63488.0\n",
      "291             layer3.0.bn1  128  16  16  128  16  16      256.0       0.12      131,072.0       65,536.0    132096.0     131072.0       0.00%    263168.0\n",
      "292          layer3.0.select  128  16  16   78  16  16      128.0       0.08            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "293           layer3.0.conv1   78  16  16   60  16  16     4680.0       0.06    2,380,800.0    1,198,080.0     98592.0      61440.0       0.84%    160032.0\n",
      "294             layer3.0.bn2   60  16  16   60  16  16      120.0       0.06       61,440.0       30,720.0     61920.0      61440.0       0.00%    123360.0\n",
      "295           layer3.0.conv2   60  16  16   64   8   8    34560.0       0.02    4,419,584.0    2,211,840.0    199680.0      16384.0       0.00%    216064.0\n",
      "296             layer3.0.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "297           layer3.0.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "298            layer3.0.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "299    layer3.0.downsample.0  128  16  16  256   8   8    32768.0       0.06    4,177,920.0    2,097,152.0    262144.0      65536.0       0.84%    327680.0\n",
      "300             layer3.1.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "301          layer3.1.select  256   8   8  107   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "302           layer3.1.conv1  107   8   8   63   8   8     6741.0       0.02      858,816.0      431,424.0     54356.0      16128.0       0.00%     70484.0\n",
      "303             layer3.1.bn2   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "304           layer3.1.conv2   63   8   8   64   8   8    36288.0       0.02    4,640,768.0    2,322,432.0    161280.0      16384.0       0.00%    177664.0\n",
      "305             layer3.1.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "306           layer3.1.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "307            layer3.1.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "308             layer3.2.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "309          layer3.2.select  256   8   8  117   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "310           layer3.2.conv1  117   8   8   64   8   8     7488.0       0.02      954,368.0      479,232.0     59904.0      16384.0       0.00%     76288.0\n",
      "311             layer3.2.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.84%     33280.0\n",
      "312           layer3.2.conv2   64   8   8   63   8   8    36288.0       0.02    4,640,832.0    2,322,432.0    161536.0      16128.0       0.84%    177664.0\n",
      "313             layer3.2.bn3   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "314           layer3.2.conv3   63   8   8  256   8   8    16128.0       0.06    2,048,000.0    1,032,192.0     80640.0      65536.0       0.00%    146176.0\n",
      "315            layer3.2.relu   63   8   8   63   8   8        0.0       0.02        4,032.0        4,032.0     16128.0      16128.0       0.00%     32256.0\n",
      "316             layer3.3.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.84%    133120.0\n",
      "317          layer3.3.select  256   8   8  122   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "318           layer3.3.conv1  122   8   8   63   8   8     7686.0       0.02      979,776.0      491,904.0     61976.0      16128.0       0.00%     78104.0\n",
      "319             layer3.3.bn2   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "320           layer3.3.conv2   63   8   8   64   8   8    36288.0       0.02    4,640,768.0    2,322,432.0    161280.0      16384.0       0.00%    177664.0\n",
      "321             layer3.3.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "322           layer3.3.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "323            layer3.3.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "324             layer3.4.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.84%    133120.0\n",
      "325          layer3.4.select  256   8   8  118   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "326           layer3.4.conv1  118   8   8   63   8   8     7434.0       0.02      947,520.0      475,776.0     59944.0      16128.0       0.84%     76072.0\n",
      "327             layer3.4.bn2   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "328           layer3.4.conv2   63   8   8   64   8   8    36288.0       0.02    4,640,768.0    2,322,432.0    161280.0      16384.0       0.00%    177664.0\n",
      "329             layer3.4.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "330           layer3.4.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "331            layer3.4.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "332             layer3.5.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "333          layer3.5.select  256   8   8  110   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "334           layer3.5.conv1  110   8   8   63   8   8     6930.0       0.02      883,008.0      443,520.0     55880.0      16128.0       0.00%     72008.0\n",
      "335             layer3.5.bn2   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "336           layer3.5.conv2   63   8   8   64   8   8    36288.0       0.02    4,640,768.0    2,322,432.0    161280.0      16384.0       0.00%    177664.0\n",
      "337             layer3.5.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "338           layer3.5.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "339            layer3.5.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "340             layer3.6.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "341          layer3.6.select  256   8   8  113   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "342           layer3.6.conv1  113   8   8   63   8   8     7119.0       0.02      907,200.0      455,616.0     57404.0      16128.0       0.00%     73532.0\n",
      "343             layer3.6.bn2   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "344           layer3.6.conv2   63   8   8   64   8   8    36288.0       0.02    4,640,768.0    2,322,432.0    161280.0      16384.0       0.00%    177664.0\n",
      "345             layer3.6.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "346           layer3.6.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "347            layer3.6.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "348             layer3.7.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "349          layer3.7.select  256   8   8  121   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "350           layer3.7.conv1  121   8   8   64   8   8     7744.0       0.02      987,136.0      495,616.0     61952.0      16384.0       0.00%     78336.0\n",
      "351             layer3.7.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "352           layer3.7.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.00%    180224.0\n",
      "353             layer3.7.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "354           layer3.7.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "355            layer3.7.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "356             layer3.8.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "357          layer3.8.select  256   8   8  121   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "358           layer3.8.conv1  121   8   8   63   8   8     7623.0       0.02      971,712.0      487,872.0     61468.0      16128.0       0.00%     77596.0\n",
      "359             layer3.8.bn2   63   8   8   63   8   8      126.0       0.02       16,128.0        8,064.0     16632.0      16128.0       0.00%     32760.0\n",
      "360           layer3.8.conv2   63   8   8   64   8   8    36288.0       0.02    4,640,768.0    2,322,432.0    161280.0      16384.0       0.00%    177664.0\n",
      "361             layer3.8.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "362           layer3.8.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "363            layer3.8.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "364             layer3.9.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "365          layer3.9.select  256   8   8  127   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "366           layer3.9.conv1  127   8   8   64   8   8     8128.0       0.02    1,036,288.0      520,192.0     65024.0      16384.0       0.00%     81408.0\n",
      "367             layer3.9.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "368           layer3.9.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "369             layer3.9.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "370           layer3.9.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "371            layer3.9.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "372            layer3.10.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "373         layer3.10.select  256   8   8  119   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "374          layer3.10.conv1  119   8   8   64   8   8     7616.0       0.02      970,752.0      487,424.0     60928.0      16384.0       0.00%     77312.0\n",
      "375            layer3.10.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "376          layer3.10.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "377            layer3.10.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.84%     33280.0\n",
      "378          layer3.10.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "379           layer3.10.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "380            layer3.11.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "381         layer3.11.select  256   8   8  131   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "382          layer3.11.conv1  131   8   8   64   8   8     8384.0       0.02    1,069,056.0      536,576.0     67072.0      16384.0       0.00%     83456.0\n",
      "383            layer3.11.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "384          layer3.11.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "385            layer3.11.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "386          layer3.11.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "387           layer3.11.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "388            layer3.12.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "389         layer3.12.select  256   8   8  130   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "390          layer3.12.conv1  130   8   8   64   8   8     8320.0       0.02    1,060,864.0      532,480.0     66560.0      16384.0       0.84%     82944.0\n",
      "391            layer3.12.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "392          layer3.12.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.00%    180224.0\n",
      "393            layer3.12.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "394          layer3.12.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "395           layer3.12.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "396            layer3.13.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "397         layer3.13.select  256   8   8  130   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "398          layer3.13.conv1  130   8   8   64   8   8     8320.0       0.02    1,060,864.0      532,480.0     66560.0      16384.0       0.00%     82944.0\n",
      "399            layer3.13.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.84%     33280.0\n",
      "400          layer3.13.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "401            layer3.13.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "402          layer3.13.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "403           layer3.13.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.84%     32768.0\n",
      "404            layer3.14.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "405         layer3.14.select  256   8   8  120   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "406          layer3.14.conv1  120   8   8   64   8   8     7680.0       0.02      978,944.0      491,520.0     61440.0      16384.0       0.00%     77824.0\n",
      "407            layer3.14.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "408          layer3.14.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "409            layer3.14.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "410          layer3.14.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "411           layer3.14.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "412            layer3.15.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "413         layer3.15.select  256   8   8  119   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "414          layer3.15.conv1  119   8   8   64   8   8     7616.0       0.02      970,752.0      487,424.0     60928.0      16384.0       0.00%     77312.0\n",
      "415            layer3.15.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "416          layer3.15.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "417            layer3.15.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "418          layer3.15.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.84%    147456.0\n",
      "419           layer3.15.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "420            layer3.16.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "421         layer3.16.select  256   8   8  119   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.84%         0.0\n",
      "422          layer3.16.conv1  119   8   8   64   8   8     7616.0       0.02      970,752.0      487,424.0     60928.0      16384.0       0.00%     77312.0\n",
      "423            layer3.16.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "424          layer3.16.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "425            layer3.16.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "426          layer3.16.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "427           layer3.16.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.00%     32768.0\n",
      "428            layer3.17.bn1  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "429         layer3.17.select  256   8   8  109   8   8      256.0       0.03            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "430          layer3.17.conv1  109   8   8   64   8   8     6976.0       0.02      888,832.0      446,464.0     55808.0      16384.0       0.00%     72192.0\n",
      "431            layer3.17.bn2   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "432          layer3.17.conv2   64   8   8   64   8   8    36864.0       0.02    4,714,496.0    2,359,296.0    163840.0      16384.0       0.84%    180224.0\n",
      "433            layer3.17.bn3   64   8   8   64   8   8      128.0       0.02       16,384.0        8,192.0     16896.0      16384.0       0.00%     33280.0\n",
      "434          layer3.17.conv3   64   8   8  256   8   8    16384.0       0.06    2,080,768.0    1,048,576.0     81920.0      65536.0       0.00%    147456.0\n",
      "435           layer3.17.relu   64   8   8   64   8   8        0.0       0.02        4,096.0        4,096.0     16384.0      16384.0       0.84%     32768.0\n",
      "436                       bn  256   8   8  256   8   8      512.0       0.06       65,536.0       32,768.0     67584.0      65536.0       0.00%    133120.0\n",
      "437                   select  256   8   8  157   8   8      256.0       0.04            0.0            0.0         0.0          0.0       0.00%         0.0\n",
      "438                     relu  157   8   8  157   8   8        0.0       0.04       10,048.0       10,048.0     40192.0      40192.0       0.00%     80384.0\n",
      "439                  avgpool  157   8   8  157   1   1        0.0       0.00       10,048.0       10,048.0     40192.0        628.0       0.00%     40820.0\n",
      "440                       fc          157          100    15800.0       0.00       31,300.0       15,700.0     63828.0        400.0       0.00%     64228.0\n",
      "total                                                   1482217.0      28.02  396,110,276.0  199,887,700.0     63828.0        400.0     100.00%  53781980.0\n",
      "===========================================================================================================================================================\n",
      "Total params: 1,482,217\n",
      "-----------------------------------------------------------------------------------------------------------------------------------------------------------\n",
      "Total memory: 28.02MB\n",
      "Total MAdd: 396.11MMAdd\n",
      "Total Flops: 199.89MFlops\n",
      "Total MemR+W: 51.29MB\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from torchstat import stat\n",
    "\n",
    "stat(model, (3, 32, 32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Files already downloaded and verified\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "from torchvision import datasets, transforms\n",
    "\n",
    "kwargs = {'num_workers': 1, 'pin_memory': True} if torch.cuda.is_available() else {}\n",
    "test_loader = torch.utils.data.DataLoader(\n",
    "            datasets.CIFAR100('./data.cifar100', train=True, download=True, transform=transforms.Compose([\n",
    "                transforms.ToTensor(),\n",
    "                transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010))])),\n",
    "            batch_size=32, shuffle=True, **kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 torch.Size([32, 3, 32, 32]) tensor([43, 58,  8, 44, 15, 96, 89, 93, 12, 48, 16, 35, 49,  3, 31, 72, 39, 80,\n",
      "        20, 70, 22, 27, 91, 10, 88, 12, 82, 29, 54, 13, 89, 96])\n",
      "1 torch.Size([32, 3, 32, 32]) tensor([79, 88, 72, 66, 91, 64,  3, 30, 47, 13,  7, 17,  5, 13, 66, 69, 37,  7,\n",
      "        25,  6, 52, 28, 17, 85, 82, 58, 78,  5, 34, 60,  8, 40])\n",
      "2 torch.Size([32, 3, 32, 32]) tensor([20, 92, 92, 41, 82, 90, 93,  1,  2, 71,  4, 68, 95, 27, 81, 63, 45,  1,\n",
      "        59, 88, 12, 62, 93, 64,  6, 59, 13,  5, 38, 26, 30, 12])\n",
      "3 torch.Size([32, 3, 32, 32]) tensor([28, 70, 46, 54, 28, 90, 72, 29, 76, 13,  7, 89, 75, 32, 28, 21, 84, 23,\n",
      "        49, 27, 69, 18, 29, 60, 94, 40, 51, 49, 80, 17, 27, 76])\n",
      "4 torch.Size([32, 3, 32, 32]) tensor([14, 57, 28, 69,  0, 24, 36, 36, 90, 78, 54, 21, 74, 46, 67, 91, 82, 54,\n",
      "        75, 38, 20, 35,  8, 75, 91, 33, 66, 54, 50, 26,  2, 33])\n",
      "5 torch.Size([32, 3, 32, 32]) tensor([64, 10, 91, 96, 87, 55, 68, 73, 19, 36, 16, 42, 28, 97, 17, 35, 31, 10,\n",
      "        17, 78, 59, 92, 95, 25, 12, 19, 18, 69, 66, 22, 33, 14])\n",
      "6 torch.Size([32, 3, 32, 32]) tensor([46, 51, 67, 85, 42,  0, 72,  5,  4, 19, 62, 95, 69, 66, 79, 97, 85, 37,\n",
      "        41, 78, 57, 58, 90, 96, 30, 98, 87, 75, 20, 83, 36, 50])\n",
      "7 torch.Size([32, 3, 32, 32]) tensor([90, 43, 77, 88, 75, 63, 75, 30, 98, 53, 18, 77, 49, 64, 16, 80, 64, 46,\n",
      "        97, 94, 99, 32,  3, 51,  2,  4, 96, 99, 81, 84, 97, 47])\n",
      "8 torch.Size([32, 3, 32, 32]) tensor([37, 26, 96,  6, 57,  8, 68, 42, 63, 54, 13, 41, 77, 86, 31, 46, 78, 67,\n",
      "        84, 71, 57, 84, 34, 34, 18, 77,  7, 78, 21,  1, 81, 47])\n",
      "9 torch.Size([32, 3, 32, 32]) tensor([18, 19, 94, 78, 55, 76, 15, 35, 65, 59, 55, 53, 50, 77, 99,  4, 43, 77,\n",
      "        63, 34, 98, 68, 13, 71, 81, 87, 58, 37,  8, 82, 55, 80])\n",
      "10 torch.Size([32, 3, 32, 32]) tensor([81, 24, 61, 11, 47, 79, 14,  8, 23, 46, 82, 63, 16, 90, 56, 83, 51, 57,\n",
      "        83, 30, 65, 71,  1, 43, 90, 94, 61, 83, 75, 32, 17, 73])\n",
      "11 torch.Size([32, 3, 32, 32]) tensor([43, 53, 31, 85,  1, 43,  9, 68,  8, 91, 88,  6, 93, 93, 37, 80, 15, 73,\n",
      "        16, 33, 79, 69, 51, 34,  8, 72, 13, 23, 33, 44, 65,  8])\n",
      "12 torch.Size([32, 3, 32, 32]) tensor([45,  6, 49, 15, 96, 58, 45, 93, 59, 92, 61, 67, 59, 67, 54, 55, 63, 89,\n",
      "        61, 81, 53, 26, 95, 27, 81, 37, 39,  5, 40, 38, 21,  8])\n",
      "13 torch.Size([32, 3, 32, 32]) tensor([45,  1, 63, 42, 23, 28, 56, 75, 22, 13, 81, 54, 31, 55,  5, 74, 10, 13,\n",
      "        81, 64, 54, 30, 81,  4, 72, 42, 80, 49, 97, 84, 60,  6])\n",
      "14 torch.Size([32, 3, 32, 32]) tensor([60, 75, 85, 25, 12, 78, 23, 98, 54, 69, 80, 34, 64, 68, 68, 53, 43, 38,\n",
      "        76, 91, 14, 76, 38,  4, 22, 88, 90, 73, 92, 45, 14, 28])\n",
      "15 torch.Size([32, 3, 32, 32]) tensor([13,  1, 15, 70, 21, 83, 96, 37, 53, 29, 50, 75, 29, 14, 35, 68, 44, 12,\n",
      "        52, 99,  5, 29, 79, 43, 48, 41, 41, 36, 28, 63, 93, 63])\n",
      "16 torch.Size([32, 3, 32, 32]) tensor([95,  0, 23, 60, 66, 44,  8, 20,  4,  6, 96,  0, 89, 16, 64, 23, 52, 42,\n",
      "        31, 59, 99,  5, 76, 68, 86, 11, 67, 46, 81, 90, 80,  9])\n",
      "17 torch.Size([32, 3, 32, 32]) tensor([78, 24, 54, 62, 19, 19, 34, 28, 13, 90, 67, 73, 65, 69, 20, 83, 42, 46,\n",
      "        54, 35, 28, 18, 29, 55, 68, 78, 12, 99, 54, 77, 17, 51])\n",
      "18 torch.Size([32, 3, 32, 32]) tensor([71, 36, 27, 58, 48, 74, 38, 17, 87, 70, 19, 59, 39, 76, 58, 65, 28, 10,\n",
      "         0, 43, 10, 53, 70, 28, 95, 41, 96, 20, 91, 63, 89, 34])\n",
      "19 torch.Size([32, 3, 32, 32]) tensor([95, 71, 66, 23,  7, 81, 47, 38, 79, 12, 57, 36, 34, 65, 92, 29, 45, 55,\n",
      "        16, 59, 73, 77, 12, 45, 50, 79, 70, 41, 43,  4, 38, 54])\n",
      "20 torch.Size([32, 3, 32, 32]) tensor([57, 22, 26, 81,  2, 78, 88, 96, 29, 55, 88, 37, 80, 64, 83, 78,  7, 56,\n",
      "        54, 29, 88, 23, 88,  4, 16, 46, 27, 57, 51, 60, 39, 29])\n",
      "21 torch.Size([32, 3, 32, 32]) tensor([54, 49, 94, 41, 65,  1, 73, 46, 18, 13, 25, 77, 74, 91,  6, 75, 44, 41,\n",
      "        87, 40, 15,  9, 64, 97,  9, 23, 25, 99, 94, 66, 79, 18])\n",
      "22 torch.Size([32, 3, 32, 32]) tensor([64, 94, 16, 22, 47, 78, 73, 76, 63, 32, 51,  3, 35, 28, 70, 81, 49, 73,\n",
      "        94, 35, 21, 67, 32, 42, 44, 42, 66, 66, 85, 22, 24, 27])\n",
      "23 torch.Size([32, 3, 32, 32]) tensor([34, 22, 22,  0, 43, 15, 83, 33, 20, 64, 32, 84,  8, 72, 18, 70, 22, 91,\n",
      "        85, 42, 59, 12, 19, 87, 29, 10, 53, 30, 70, 20, 73, 96])\n",
      "24 torch.Size([32, 3, 32, 32]) tensor([54, 42, 83, 55, 94, 90, 62, 99, 91, 90, 84, 12, 80, 57, 97, 97, 66, 64,\n",
      "         1, 20, 98, 61, 35,  4, 80, 20, 14, 74, 25,  3, 81, 97])\n",
      "25 torch.Size([32, 3, 32, 32]) tensor([66, 25, 84, 23, 16, 15, 36,  9, 17, 82, 63, 83, 16, 98, 29, 44, 55, 63,\n",
      "        13, 88, 31, 42, 84,  8, 46, 70, 29, 75, 25, 59, 28, 59])\n",
      "26 torch.Size([32, 3, 32, 32]) tensor([47, 99, 85,  0, 88, 95,  8, 55, 67, 80, 24, 94,  4, 73, 57, 90, 98, 67,\n",
      "        75, 74, 79, 93,  6, 66, 74, 80, 31, 56, 87, 38, 10, 71])\n",
      "27 torch.Size([32, 3, 32, 32]) tensor([99, 10, 26,  6, 14, 97, 92, 14, 19, 69, 49, 15, 46, 50, 12,  0, 64, 47,\n",
      "        49, 18,  1, 91, 80,  9, 26, 49, 17, 77, 92, 22, 20, 80])\n",
      "28 torch.Size([32, 3, 32, 32]) tensor([ 8, 63,  6,  9, 41, 12, 66, 49, 80, 54, 17, 57, 86, 60, 82, 31, 28, 78,\n",
      "        36, 15, 84, 58, 30, 22, 38, 89, 57, 43, 49, 34, 97, 84])\n",
      "29 torch.Size([32, 3, 32, 32]) tensor([93,  8, 99, 89, 80, 46, 24, 71, 71,  0, 15, 41, 46, 91, 65, 17, 13, 81,\n",
      "        59, 60, 19, 13, 79, 26, 37, 56, 52, 51, 56, 92,  5, 34])\n",
      "30 torch.Size([32, 3, 32, 32]) tensor([68, 42, 69, 60, 83, 39, 37, 88, 65,  0, 85, 84, 63, 66, 13, 13, 45, 42,\n",
      "        58, 41, 31, 76, 59, 50, 16, 22, 89, 94, 43, 32, 15, 21])\n",
      "31 torch.Size([32, 3, 32, 32]) tensor([ 5, 37, 58, 87, 50, 36, 27, 90, 57, 54, 55, 30, 82, 13, 80, 94, 46, 48,\n",
      "        10, 34, 40, 16, 55, 25, 22, 79, 93, 47, 81, 63, 10, 54])\n",
      "32 torch.Size([32, 3, 32, 32]) tensor([97, 76, 76, 79, 29, 13, 34, 76, 59,  9,  5, 81, 83, 15, 97, 80, 55, 44,\n",
      "        56, 51, 28, 84, 19, 72, 51, 89,  3, 62, 49, 80, 64, 73])\n",
      "33 torch.Size([32, 3, 32, 32]) tensor([23, 80, 71, 95, 68, 63, 14, 84, 68, 19, 57, 82, 97,  4, 37, 14, 87, 82,\n",
      "        12, 51, 61, 53, 56, 13, 99, 90, 11, 26, 20, 36, 35,  2])\n",
      "34 torch.Size([32, 3, 32, 32]) tensor([75, 49, 70, 50, 67, 90, 15, 64, 84, 45, 36, 70, 62, 30, 48, 57,  1, 37,\n",
      "        60, 61, 58, 10, 11, 25,  8,  2, 14, 70, 94, 25,  0, 39])\n",
      "35 torch.Size([32, 3, 32, 32]) tensor([92, 37, 11, 88, 88, 92, 11, 71, 83, 17, 42, 51, 53, 95, 50, 55,  6, 40,\n",
      "        55, 72, 35,  9, 66, 58, 96, 32,  9, 89,  9, 16, 54, 98])\n",
      "36 torch.Size([32, 3, 32, 32]) tensor([29, 28, 33, 61, 22, 89, 75, 96, 97, 16,  9, 88, 40, 90,  3, 28, 75, 34,\n",
      "        25,  6, 96, 66, 53, 76, 64, 25, 40, 14, 69, 21,  5, 92])\n",
      "37 torch.Size([32, 3, 32, 32]) tensor([43, 56, 70, 84, 58, 64, 94, 67, 52, 23, 70, 16, 40, 58, 85, 69, 56, 70,\n",
      "        94, 29, 56, 52,  9, 55, 33, 71, 67, 36, 12, 89, 79, 14])\n",
      "38 torch.Size([32, 3, 32, 32]) tensor([48, 24, 88, 13, 18, 25, 23, 59, 45, 29, 27, 30, 38, 63,  0, 10, 51, 87,\n",
      "        58, 26, 11, 15, 37,  9,  9,  5, 91, 81, 26, 72, 97, 74])\n",
      "39 torch.Size([32, 3, 32, 32]) tensor([ 1, 81, 21, 58, 99, 39,  1, 47, 66, 44, 71, 64, 16, 89, 35, 39, 31, 11,\n",
      "         3, 85, 96, 63,  5, 69, 85, 76, 73, 56, 72, 57, 26, 71])\n",
      "40 torch.Size([32, 3, 32, 32]) tensor([30, 84, 97,  0, 88, 77, 57, 91, 33, 18, 17, 67, 68, 27, 35, 28, 42, 19,\n",
      "        82, 28, 92, 10, 34, 20, 74, 63, 34, 66, 99, 27, 98, 91])\n",
      "41 torch.Size([32, 3, 32, 32]) tensor([71, 11, 99, 24, 36, 57, 49, 75, 76,  1, 24, 60, 86,  3, 68, 27,  6, 46,\n",
      "        85, 25, 57, 12, 60, 60, 75, 43, 67, 10, 13, 60, 29, 41])\n",
      "42 torch.Size([32, 3, 32, 32]) tensor([50, 66, 23, 20, 30, 70, 14, 90, 50, 10, 47, 45, 78, 99, 96, 85, 19, 43,\n",
      "        39, 12, 23, 54, 94, 58, 45, 61, 57, 88, 16, 34,  5, 99])\n",
      "43 torch.Size([32, 3, 32, 32]) tensor([34,  0, 42, 77, 32, 10,  2, 44, 23, 15, 23, 65, 68, 18, 66, 61, 55, 11,\n",
      "        53,  9, 33, 84, 84, 95, 65, 71, 14,  3, 13, 56, 59, 51])\n",
      "44 torch.Size([32, 3, 32, 32]) tensor([64, 68, 96, 31, 30, 44, 92, 28, 92, 83, 25, 35, 77, 87, 14, 77, 81, 60,\n",
      "        74, 30, 63, 21, 22, 78, 23, 33, 84, 25, 72, 60, 80, 88])\n",
      "45 torch.Size([32, 3, 32, 32]) tensor([ 6, 22, 87, 29, 17,  9, 75, 39, 69,  4, 99, 79, 14, 62, 91, 14, 95, 34,\n",
      "        53,  5, 61, 89, 95, 65, 87,  7,  0, 14, 84, 97, 96, 14])\n",
      "46 torch.Size([32, 3, 32, 32]) tensor([38, 61,  5, 12, 70, 85,  4, 83, 57,  3, 87, 91, 71, 25, 42,  8, 33, 39,\n",
      "         9,  7, 48, 93, 87, 23, 82, 18, 23,  1, 94, 41, 20, 17])\n",
      "47 torch.Size([32, 3, 32, 32]) tensor([47, 52, 14, 69, 91, 51, 48, 73, 47, 43, 33, 24, 53, 95, 13, 27, 87, 12,\n",
      "         2, 21, 27, 68, 62, 44,  0, 25, 45,  2, 37, 57, 87, 45])\n",
      "48 torch.Size([32, 3, 32, 32]) tensor([77, 67, 59, 15, 17, 59, 41, 50, 12, 64, 36, 14, 99, 98, 63, 90, 44, 63,\n",
      "        99, 66, 28, 97, 15, 20, 31, 89, 60, 85, 26, 88, 89, 86])\n",
      "49 torch.Size([32, 3, 32, 32]) tensor([22, 59, 10, 20, 34, 71, 36, 98, 70, 53, 38, 85, 66, 51, 75, 70, 70, 83,\n",
      "         3,  4, 44,  3, 34, 16, 81, 21, 51, 41, 54, 76, 23, 47])\n",
      "50 torch.Size([32, 3, 32, 32]) tensor([ 2, 51, 83, 51, 33, 33, 50, 91, 35, 66, 59, 73, 59,  0, 17, 89, 44, 26,\n",
      "        34, 23, 98, 98, 33, 89, 54, 53, 57, 95, 42, 40, 41, 92])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "51 torch.Size([32, 3, 32, 32]) tensor([62, 57, 93, 76, 34, 76,  4, 23, 62, 88, 94, 13, 75, 17, 32, 30, 49, 62,\n",
      "         1, 27, 48, 87, 55, 64, 42, 10, 17, 62, 79,  4, 87, 63])\n",
      "52 torch.Size([32, 3, 32, 32]) tensor([49, 46, 61, 62, 73, 74,  2, 53, 58, 56, 40, 95,  2, 25, 84, 11, 52, 66,\n",
      "        89, 64, 82, 21, 17, 15, 89, 43, 12, 50, 64, 88, 94, 59])\n",
      "53 torch.Size([32, 3, 32, 32]) tensor([79, 48,  2, 13,  7, 35, 39, 82, 19, 24, 67,  9, 64, 31, 50, 47, 58,  6,\n",
      "         9, 75,  2, 99, 48, 59, 16, 71, 51, 68, 39, 64,  2, 75])\n",
      "54 torch.Size([32, 3, 32, 32]) tensor([54, 80, 29, 37,  4, 57, 95, 75, 71,  4,  2,  7, 49, 65, 64, 28, 98, 11,\n",
      "        74, 89, 37,  6, 57, 67, 18, 29, 38, 27, 92, 71,  8, 85])\n",
      "55 torch.Size([32, 3, 32, 32]) tensor([44, 12, 65,  3, 60, 44, 48, 51, 74,  8, 85, 68, 74, 79, 24, 68,  5, 55,\n",
      "        43, 27, 20, 38, 48, 28, 59, 14, 73, 31, 27, 16, 10, 54])\n",
      "56 torch.Size([32, 3, 32, 32]) tensor([15, 47, 95, 12, 29, 32,  7, 20, 79, 63, 38, 90, 34, 60, 51,  4, 78,  1,\n",
      "        33, 72, 26,  6, 54, 82, 29, 14, 64, 70, 19, 65, 45, 33])\n",
      "57 torch.Size([32, 3, 32, 32]) tensor([37, 64, 65, 21, 60, 35, 34, 11, 59, 74, 16, 66, 57, 13, 95, 16, 10, 95,\n",
      "        41, 61, 19, 23, 72, 72, 31, 24, 77, 87,  3, 27, 54, 75])\n",
      "58 torch.Size([32, 3, 32, 32]) tensor([52, 27, 47, 34, 26, 24, 79, 10, 32, 58, 60, 78, 89, 10, 90,  5, 93, 39,\n",
      "        28, 19, 90, 49, 68, 30, 53, 85, 72, 15,  2, 34, 84, 97])\n",
      "59 torch.Size([32, 3, 32, 32]) tensor([60, 41, 59, 86, 42, 86, 43, 82, 78,  4, 63, 29, 19, 97, 31, 77, 45, 40,\n",
      "        76, 58, 19, 54, 45, 82, 46, 95, 43, 88,  0, 76, 54, 75])\n",
      "60 torch.Size([32, 3, 32, 32]) tensor([17, 10, 63, 68, 69, 57, 53, 13, 24, 86, 84, 30, 27, 21, 86, 74, 68, 81,\n",
      "        45, 94, 29, 98, 13, 91, 48, 13, 58, 30,  5, 79, 80, 11])\n",
      "61 torch.Size([32, 3, 32, 32]) tensor([38, 12, 46, 76, 29,  4, 96, 90, 60, 73, 76, 56, 11, 31, 43, 88, 47, 11,\n",
      "        41, 95, 58, 56, 80, 49, 88, 51, 83, 29, 22, 28, 96, 74])\n",
      "62 torch.Size([32, 3, 32, 32]) tensor([13, 95, 62,  0, 13,  0, 79, 38, 62,  3, 33, 43, 66, 44, 74, 69, 57, 63,\n",
      "        94, 31, 29, 35, 72, 26, 44, 64, 26, 36, 92, 97,  2, 54])\n",
      "63 torch.Size([32, 3, 32, 32]) tensor([91, 60,  5, 73, 29, 25, 47, 23, 85, 97, 92, 51, 91, 41, 38, 79, 70, 61,\n",
      "         8, 64,  4, 92, 86, 28, 44, 43,  0, 76, 19, 13, 58, 29])\n",
      "64 torch.Size([32, 3, 32, 32]) tensor([60, 93, 10, 26, 44, 54, 30, 92, 21, 59, 84, 89, 11, 44, 82, 93, 15, 74,\n",
      "        97, 14, 71, 49, 30, 87, 15, 81, 73, 83, 61, 56,  9, 40])\n",
      "65 torch.Size([32, 3, 32, 32]) tensor([79, 84, 33, 50,  5, 86, 28, 16, 73, 18, 28, 87, 87, 57, 90, 49, 85, 11,\n",
      "        38, 55, 77, 77, 72, 23,  2, 77, 81, 53, 45, 77, 91, 96])\n",
      "66 torch.Size([32, 3, 32, 32]) tensor([67,  3, 68, 34, 70, 87, 84, 39,  0, 56, 48, 63, 16, 54, 22,  2,  2, 98,\n",
      "        19, 68, 61, 38, 37, 90, 60, 31, 30, 61, 21,  4, 98, 66])\n",
      "67 torch.Size([32, 3, 32, 32]) tensor([38, 97, 86, 73, 67,  0, 78, 65, 75, 94, 28, 80,  4, 74, 52, 14, 75, 70,\n",
      "        31, 90, 83, 39, 96, 20, 42, 23, 29, 82, 96, 23, 50, 65])\n",
      "68 torch.Size([32, 3, 32, 32]) tensor([54, 67, 30, 17, 77, 98, 94, 53, 36, 36, 54, 91, 65, 92, 36, 27, 16,  2,\n",
      "        32, 76, 77, 52,  1, 46, 67, 32, 92, 66, 23, 84, 30, 15])\n",
      "69 torch.Size([32, 3, 32, 32]) tensor([74, 63, 81, 20, 10, 79, 87, 37, 61, 26, 13, 26, 11, 94, 82, 99, 66, 26,\n",
      "        25, 24, 95, 98, 19, 63, 66, 55, 16,  9, 75, 49, 48, 71])\n",
      "70 torch.Size([32, 3, 32, 32]) tensor([22, 98, 66, 43, 78, 23, 15, 88, 32, 29, 20, 82, 32, 50, 92, 91, 43, 78,\n",
      "        36, 52, 30, 17, 87, 99, 39, 49, 32, 92, 62,  8, 20, 57])\n",
      "71 torch.Size([32, 3, 32, 32]) tensor([65,  8, 87, 71, 89, 34, 56, 14, 23, 32, 61, 62, 53, 11, 82, 67,  9,  3,\n",
      "        59, 21,  6, 34, 19, 60,  0, 37, 86, 82, 48,  4, 49, 84])\n",
      "72 torch.Size([32, 3, 32, 32]) tensor([56, 93, 97, 29, 69, 78,  7, 34, 64, 36, 93, 33, 91, 79, 97, 59, 83, 92,\n",
      "         3, 16, 70, 38, 82,  2, 29, 69, 68, 80, 44, 71, 32, 96])\n",
      "73 torch.Size([32, 3, 32, 32]) tensor([57, 74, 83, 72, 70, 15, 32, 23, 60,  6, 57, 31, 29, 61, 39, 21, 86, 52,\n",
      "        47, 11,  6, 92, 42, 78, 48,  7, 50, 16, 97, 86, 80, 68])\n",
      "74 torch.Size([32, 3, 32, 32]) tensor([ 3, 31, 61, 21,  2, 97, 26, 46, 49, 70, 24, 51, 56,  5, 26, 20,  8, 89,\n",
      "        26, 64, 47, 86, 33, 21, 98,  9, 27, 91,  6, 62,  7, 47])\n",
      "75 torch.Size([32, 3, 32, 32]) tensor([48, 15, 79, 77, 32, 13,  1, 56, 47, 64, 70, 91,  2,  0, 48, 36, 13, 12,\n",
      "        69, 89, 20, 59, 18, 83, 21, 55, 94, 82,  1, 68, 54, 59])\n",
      "76 torch.Size([32, 3, 32, 32]) tensor([53, 36, 97, 62,  6, 82,  1, 58, 50, 52, 87, 54, 23, 72, 59,  8, 42, 38,\n",
      "        38, 56, 72, 17,  3, 74, 17, 89, 66, 20, 64, 98, 84, 21])\n",
      "77 torch.Size([32, 3, 32, 32]) tensor([88, 27,  6, 10, 17,  1, 72, 93, 36,  4, 97, 93,  7, 67, 82, 30, 83, 57,\n",
      "        72, 69, 36, 78, 86,  0, 14, 26, 38, 23,  7, 31, 46,  1])\n",
      "78 torch.Size([32, 3, 32, 32]) tensor([67, 87, 36, 39, 47, 38, 20, 97, 59, 28, 40, 88, 64, 37, 53, 20, 54, 91,\n",
      "        79, 86, 63, 44, 54,  5, 48, 23, 81, 43, 52, 35, 82, 15])\n",
      "79 torch.Size([32, 3, 32, 32]) tensor([64, 84, 21, 50, 43, 18, 12, 72,  8, 27, 81, 96, 64, 29, 95, 59,  0, 45,\n",
      "        31, 17, 26, 65, 31, 13, 11, 99, 98, 25, 10, 74, 19, 65])\n",
      "80 torch.Size([32, 3, 32, 32]) tensor([79, 76, 84,  2, 82, 58, 71, 62, 83, 75, 27, 19, 36, 40, 37, 46, 16, 98,\n",
      "        66,  4, 21, 53, 27, 28, 97, 47, 34, 27,  7,  6, 48, 15])\n",
      "81 torch.Size([32, 3, 32, 32]) tensor([45, 54,  3, 87, 22, 15, 36, 54, 73, 99, 38, 87,  3, 11, 99, 81, 88, 81,\n",
      "        86, 57, 25, 44, 11, 42, 14, 14, 37, 40, 47,  3, 67,  7])\n",
      "82 torch.Size([32, 3, 32, 32]) tensor([22, 28, 24, 98, 49, 62, 84, 67, 45, 34,  3, 83,  6, 36, 67, 86, 28, 62,\n",
      "        15, 64, 56, 39,  5, 71, 22, 22, 79, 76, 89, 27, 21, 52])\n",
      "83 torch.Size([32, 3, 32, 32]) tensor([31, 52, 30, 78, 46, 37, 38, 67, 95, 14, 55, 31, 62, 72,  6, 95, 32, 73,\n",
      "        20, 84,  2, 64, 58, 94, 28, 61, 65, 99,  2, 93, 26, 71])\n",
      "84 torch.Size([32, 3, 32, 32]) tensor([16, 71, 41, 80, 35, 69, 82, 61, 99, 87,  6, 31, 58,  9, 25,  3, 91, 60,\n",
      "        55,  1,  2, 62, 24, 92,  4, 79, 82, 53, 79, 37, 37, 71])\n",
      "85 torch.Size([32, 3, 32, 32]) tensor([40, 80, 31, 21, 64, 55, 94, 29, 61, 62, 82, 36, 62, 12, 86, 27, 16, 62,\n",
      "        25, 49, 76, 36, 79, 36, 33, 78, 92, 38, 94, 11,  8, 29])\n",
      "86 torch.Size([32, 3, 32, 32]) tensor([83,  0,  2, 74,  0, 22, 11,  3, 32, 77, 67, 94, 96, 98, 47, 23, 97,  1,\n",
      "        86, 19, 22, 21, 58,  6, 29, 56, 69, 65, 56, 14, 72, 72])\n",
      "87 torch.Size([32, 3, 32, 32]) tensor([39, 38, 25, 85, 13,  2, 59, 57, 21, 51, 27,  8, 21, 33, 91, 66, 40, 14,\n",
      "        78, 32, 34, 70, 58, 21, 43, 90, 98, 45, 50, 86,  6, 78])\n",
      "88 torch.Size([32, 3, 32, 32]) tensor([65, 25,  0, 33, 21, 52, 25, 88, 50, 72, 55, 52, 13, 83, 25, 73, 84, 63,\n",
      "        27, 64, 21, 15, 34, 80, 61, 69, 39, 53, 85, 55, 40,  5])\n",
      "89 torch.Size([32, 3, 32, 32]) tensor([32, 41, 17, 32, 69, 23, 76, 37, 96, 92, 45, 83, 20, 24, 73, 66, 78, 85,\n",
      "        48, 57, 16, 38,  4, 54, 92, 49,  6,  1, 23, 31, 41, 64])\n",
      "90 torch.Size([32, 3, 32, 32]) tensor([ 2, 20, 83,  2, 53, 89, 17, 95, 63,  4, 89, 79, 69, 26, 59, 53, 82, 81,\n",
      "        84, 25, 44, 34, 48, 85,  9, 33, 39, 28, 31, 60, 98, 36])\n",
      "91 torch.Size([32, 3, 32, 32]) tensor([46, 67, 88, 99, 12, 66,  1,  6, 28,  6, 73, 70, 62, 89, 30, 77, 34,  7,\n",
      "        26, 68, 25, 94, 10, 84, 73, 78, 44,  7, 83, 29, 19, 34])\n",
      "92 torch.Size([32, 3, 32, 32]) tensor([41, 18, 20, 60, 84, 72, 68, 27, 85, 80, 24, 89, 67, 46, 86, 99, 94, 28,\n",
      "        26, 51, 51, 14, 63, 72, 38, 50, 14, 47, 78, 90, 32, 43])\n",
      "93 torch.Size([32, 3, 32, 32]) tensor([45, 76, 18, 14,  0, 95, 80,  9, 52, 31, 14, 53, 44, 16, 77,  5,  2, 20,\n",
      "        66,  7, 79, 11, 67, 71, 22, 56, 36, 22, 79, 69, 65, 10])\n",
      "94 torch.Size([32, 3, 32, 32]) tensor([68, 79, 61, 62, 97,  8, 61, 15, 95, 33, 22, 43,  5, 92, 21, 13, 63, 45,\n",
      "        14, 33, 42, 87, 88, 27, 15, 78,  3, 37, 92, 34, 16, 97])\n",
      "95 torch.Size([32, 3, 32, 32]) tensor([23, 29, 34, 84, 92, 55, 94, 96, 58, 63, 38, 79, 47, 77, 30, 16, 99, 57,\n",
      "        41, 99,  7, 82, 62,  3, 23, 72, 68, 17, 60, 73, 11, 53])\n",
      "96 torch.Size([32, 3, 32, 32]) tensor([35, 53, 24, 90, 20, 56, 33, 20, 80, 28,  4, 96, 70,  8, 95, 73, 53, 61,\n",
      "        63, 72, 41, 30, 24, 72,  1, 11, 48, 23, 82, 86, 75, 66])\n",
      "97 torch.Size([32, 3, 32, 32]) tensor([25, 30, 20, 26, 53, 88, 23, 49,  7,  2,  5, 72, 87, 66,  8, 45,  9, 29,\n",
      "        81, 26,  5, 63, 45,  6, 26, 37, 65, 94, 73, 25,  7, 84])\n",
      "98 torch.Size([32, 3, 32, 32]) tensor([67, 37, 42, 35, 61, 52, 12, 57, 43, 35, 89, 14, 97, 15, 95, 32, 31, 29,\n",
      "        26, 32, 93, 96, 73, 43, 83, 47, 68,  0, 55, 95, 58, 83])\n",
      "99 torch.Size([32, 3, 32, 32]) tensor([66, 43, 79, 40, 22, 61, 80, 36, 13, 25, 68, 39, 87, 55,  2, 36, 66, 42,\n",
      "        38, 88, 56, 96, 68, 93, 33, 75, 41, 71,  3, 27, 63, 40])\n",
      "100 torch.Size([32, 3, 32, 32]) tensor([34, 51, 91, 64, 20, 75, 98,  4, 15, 15, 68, 41, 21, 99, 77, 65, 93,  7,\n",
      "        78, 14, 37, 91, 75, 42, 64,  1, 21, 38, 35, 76, 22, 24])\n",
      "101 torch.Size([32, 3, 32, 32]) tensor([60, 78, 73,  9, 34, 58, 46, 59, 63, 13, 74, 78, 26, 91, 80, 27, 73, 69,\n",
      "        92, 94, 50, 35, 69, 86, 18, 35, 87, 79, 96, 39, 44, 54])\n",
      "102 torch.Size([32, 3, 32, 32]) tensor([65, 99, 37, 43, 93, 73, 58, 30, 86, 11, 88, 94, 65, 63, 58, 68, 94, 16,\n",
      "        87, 95, 96, 69,  8, 90, 62, 63, 78, 13, 88, 22, 12, 31])\n",
      "103 torch.Size([32, 3, 32, 32]) tensor([72, 30,  5, 49, 34, 37, 42, 58, 48, 14, 13, 88, 82, 73, 12, 27,  1,  4,\n",
      "        60, 78,  6, 51, 21, 12, 96, 15, 61, 74, 93, 58, 16, 46])\n",
      "104 torch.Size([32, 3, 32, 32]) tensor([13, 43, 11, 61, 24, 20, 40, 70, 37, 60, 78, 51, 83, 47, 56, 56, 82, 86,\n",
      "        46, 95, 95, 11, 74, 43, 38, 34, 92, 69, 30, 58,  4, 37])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "105 torch.Size([32, 3, 32, 32]) tensor([62, 10, 40, 92, 87, 28, 90, 28, 64, 46, 31, 87, 45, 43, 35, 93, 33, 97,\n",
      "        40, 64, 35, 31, 37, 84, 25, 46,  4, 52, 36, 40, 67, 42])\n",
      "106 torch.Size([32, 3, 32, 32]) tensor([69, 33, 31,  2, 92, 19, 31, 55, 70, 10, 62, 50, 95, 15, 26, 38, 74,  5,\n",
      "        58, 17, 91, 81, 89, 12,  6, 19,  5, 88, 60, 46, 61, 88])\n",
      "107 torch.Size([32, 3, 32, 32]) tensor([22, 12, 33, 89, 92, 24, 80, 30, 71, 43, 84, 62, 76, 83,  0, 21, 37, 30,\n",
      "        39, 53, 24, 53, 34,  7, 30, 83, 62, 11,  9,  2, 26, 22])\n",
      "108 torch.Size([32, 3, 32, 32]) tensor([75, 10,  2, 94, 50, 67, 99, 55, 15, 53, 15, 62, 70, 43, 23, 40, 97, 64,\n",
      "        12, 89, 34, 64,  2, 14, 70, 78, 51, 13, 23, 41, 55, 34])\n",
      "109 torch.Size([32, 3, 32, 32]) tensor([89, 76, 97, 25, 50, 64, 64, 68,  3, 57, 15, 90, 55, 45, 89, 45, 46, 82,\n",
      "        16, 75, 83, 70, 66, 46,  6, 24, 75, 33, 48, 15, 25, 37])\n",
      "110 torch.Size([32, 3, 32, 32]) tensor([45, 76, 86, 41, 60,  1, 44, 43, 61, 61, 47, 34, 84, 86, 40, 65, 23, 13,\n",
      "        35,  5, 33, 22, 81, 95, 11, 20, 47, 91, 31, 23, 67, 59])\n",
      "111 torch.Size([32, 3, 32, 32]) tensor([49, 15, 99, 60,  2, 19, 20, 47, 32,  4, 46, 18, 33, 51, 49, 74, 32, 31,\n",
      "        13, 53, 23,  1, 12, 60, 70, 16, 97, 31, 41,  9, 83, 76])\n",
      "112 torch.Size([32, 3, 32, 32]) tensor([62, 88, 57, 15, 94,  0,  3, 68, 97, 31, 23, 61, 71, 82, 85, 20, 76, 75,\n",
      "         2, 20, 28, 45, 40, 16, 35, 12, 61, 55, 12, 39, 85, 76])\n",
      "113 torch.Size([32, 3, 32, 32]) tensor([33, 51, 73, 44, 55, 20, 76, 62, 34,  0, 87, 91, 11, 74, 89, 62, 43, 84,\n",
      "        26, 69, 48, 36, 29, 46,  9, 27, 44, 84, 77, 83, 82,  3])\n",
      "114 torch.Size([32, 3, 32, 32]) tensor([74, 99, 73, 59, 82, 73, 68, 91, 60, 88, 71,  6, 19, 59, 71, 28, 64, 13,\n",
      "        97, 25, 67, 81, 40, 35, 54, 94, 46, 12, 73, 15, 52, 72])\n",
      "115 torch.Size([32, 3, 32, 32]) tensor([38, 59, 87, 83, 99, 79, 67, 51, 38, 12, 10, 64, 72, 45, 46, 66, 68, 47,\n",
      "        93, 32, 60, 64, 64, 42, 23, 13, 85, 19, 79, 54, 17, 34])\n",
      "116 torch.Size([32, 3, 32, 32]) tensor([97, 82, 41, 20, 68, 94, 15,  1, 44, 18, 30, 37, 51, 27, 57, 63, 55,  1,\n",
      "        49, 26, 66, 83, 97, 76, 17, 27, 97, 33, 23, 18, 64, 78])\n",
      "117 torch.Size([32, 3, 32, 32]) tensor([12, 16,  6, 34, 34, 43, 52, 25, 93,  7, 20, 48, 28, 62, 22, 29, 57, 97,\n",
      "        74, 58, 35, 28, 57, 83,  0, 65, 59,  3, 96, 64, 85, 85])\n",
      "118 torch.Size([32, 3, 32, 32]) tensor([95, 30, 98, 50, 52, 57, 19, 85, 67, 70, 61, 96, 74, 46, 94, 87, 83, 49,\n",
      "        32, 98, 38, 34, 50, 82,  1,  0, 30, 61, 68, 76, 72, 96])\n",
      "119 torch.Size([32, 3, 32, 32]) tensor([84,  5, 40, 58, 52, 75, 20, 80, 93, 92, 48, 31, 82, 96, 86, 60, 69, 75,\n",
      "        27, 89, 88, 38, 75, 28, 43,  0, 65, 35, 62, 21, 63, 10])\n",
      "120 torch.Size([32, 3, 32, 32]) tensor([73, 15, 25, 52, 54, 83, 58, 64, 22, 59, 36, 17, 63, 92, 77, 69, 74,  3,\n",
      "        33, 95, 27, 58, 91, 17, 81, 71, 94, 85, 53, 20, 74, 95])\n",
      "121 torch.Size([32, 3, 32, 32]) tensor([91, 48, 80, 63, 50, 48,  1, 89, 33, 84, 91, 48, 90, 46, 34, 44, 34, 74,\n",
      "        83, 78, 37, 83, 28, 27, 97,  3, 97, 79, 43, 26, 63, 77])\n",
      "122 torch.Size([32, 3, 32, 32]) tensor([33, 53, 23, 64, 27, 74, 15, 39, 93, 68, 90,  3, 16, 82, 94, 69, 10, 53,\n",
      "        57, 17, 87, 29, 41, 42,  3,  2, 81, 81, 35, 56, 32, 96])\n",
      "123 torch.Size([32, 3, 32, 32]) tensor([52,  6, 64, 10, 36, 10, 29, 51, 97, 20, 88,  4, 44, 93, 94, 84, 60, 42,\n",
      "        77,  1, 69, 61, 16, 22, 29, 13, 95, 58, 62, 44,  3, 49])\n",
      "124 torch.Size([32, 3, 32, 32]) tensor([80, 16,  6,  7, 98, 49, 20, 60, 60, 96, 39, 21, 63, 57, 40, 46,  3, 60,\n",
      "        16, 89, 28, 90, 55, 82, 59, 17, 89, 18, 50, 62,  2, 12])\n",
      "125 torch.Size([32, 3, 32, 32]) tensor([89, 22, 80,  1, 40, 72, 37, 10, 44, 76, 18, 15, 21, 51, 53, 74,  3, 81,\n",
      "        64, 64, 96,  8, 93, 43, 80, 40, 14,  5,  8, 63, 72, 11])\n",
      "126 torch.Size([32, 3, 32, 32]) tensor([31, 29, 11, 35, 91,  5, 79, 20, 25, 47, 17, 56, 95, 65, 28, 50, 96, 56,\n",
      "        17, 27, 74, 29, 32, 73, 58,  4, 23, 19, 18,  2, 14,  7])\n",
      "127 torch.Size([32, 3, 32, 32]) tensor([37,  8, 81, 39, 26,  9, 72, 66, 80, 88, 45, 20, 38, 92, 26, 48, 43, 26,\n",
      "        36, 26, 41, 79,  2, 28, 37, 48, 44, 74, 80, 12,  5, 94])\n",
      "128 torch.Size([32, 3, 32, 32]) tensor([23, 69, 55, 83, 77, 39, 45, 99, 65, 10, 28, 37, 26, 90,  7, 41, 29, 31,\n",
      "        72, 54, 60, 61, 60, 16, 20, 60, 76, 98, 75, 68, 94, 29])\n",
      "129 torch.Size([32, 3, 32, 32]) tensor([73,  3, 21, 76, 14, 67, 27, 74, 17, 30, 21, 65,  3, 14, 60, 69, 96, 40,\n",
      "        88, 23, 87, 18, 83, 84, 17, 17, 89,  1, 49, 29,  8, 63])\n",
      "130 torch.Size([32, 3, 32, 32]) tensor([71,  4, 28, 97, 24, 84, 30, 23, 72, 99, 88,  9, 80,  3, 19, 41, 88, 96,\n",
      "        72, 22, 57, 95,  5, 12,  3, 81,  1, 22, 97, 83, 94, 70])\n",
      "131 torch.Size([32, 3, 32, 32]) tensor([81, 61, 59, 60, 33,  3, 61, 11, 33, 50, 18, 23, 19, 83, 76, 11, 31, 98,\n",
      "        48, 45, 44,  0, 46, 57, 38, 89, 38, 53, 22, 37, 85, 74])\n",
      "132 torch.Size([32, 3, 32, 32]) tensor([52, 69, 85, 87, 19, 46, 15, 76, 83, 24,  3, 67, 28, 16, 86, 57, 37, 28,\n",
      "        91, 56, 30, 67, 80, 45, 23, 17,  0, 37,  8, 34, 32, 57])\n",
      "133 torch.Size([32, 3, 32, 32]) tensor([32, 83, 46, 70, 49, 98, 78, 27, 98, 31, 65, 74, 58, 30,  7,  8, 46, 49,\n",
      "        86,  8,  9,  6, 42, 74, 95, 29, 69, 45, 74, 64,  7, 24])\n",
      "134 torch.Size([32, 3, 32, 32]) tensor([18, 63, 86, 10,  0,  9, 93, 13, 28,  6, 18, 68, 11, 52, 69, 41, 99, 91,\n",
      "        25, 66, 14, 64, 95, 10, 58, 35, 21, 30, 50, 11,  9, 53])\n",
      "135 torch.Size([32, 3, 32, 32]) tensor([ 5,  7, 85,  2, 63, 35, 17, 65, 47, 59,  9, 33, 17, 25, 38, 42, 35, 12,\n",
      "         6, 64, 88,  6, 24, 94, 44, 56, 55, 75, 89, 73, 84, 26])\n",
      "136 torch.Size([32, 3, 32, 32]) tensor([50, 46, 15, 72, 66,  6, 81, 42, 12, 93,  2, 35, 56, 53, 43, 80, 70, 67,\n",
      "        96,  3, 47, 18, 63, 69, 12, 85, 29, 20, 48, 47, 30, 45])\n",
      "137 torch.Size([32, 3, 32, 32]) tensor([23, 88, 92, 90,  3, 56, 87, 97, 59, 94, 88, 37, 18, 46, 30, 11, 46, 22,\n",
      "        45, 46, 65, 99, 82,  5, 35, 84, 82, 66, 61,  7, 79, 53])\n",
      "138 torch.Size([32, 3, 32, 32]) tensor([27, 89, 41, 40, 82, 32,  8, 57,  5, 59, 68, 53, 21,  5, 79, 26, 54, 87,\n",
      "        87, 18, 17, 68, 25, 89, 55, 50, 31, 36, 17, 58, 37, 63])\n",
      "139 torch.Size([32, 3, 32, 32]) tensor([10, 23, 76, 75, 58, 11, 18, 57, 92, 73, 87, 57, 39, 82, 60, 39, 94, 56,\n",
      "        92,  3, 73, 22, 12, 14, 89, 68,  3, 72, 79, 59, 84,  6])\n",
      "140 torch.Size([32, 3, 32, 32]) tensor([81, 77, 38, 77, 29, 46, 59, 97,  0, 20, 95, 10, 56, 60, 71, 49, 32, 96,\n",
      "        46,  7, 56, 80, 84, 92, 53, 75, 61, 10, 29,  4, 36, 29])\n",
      "141 torch.Size([32, 3, 32, 32]) tensor([39, 12, 19, 95, 17, 12, 29, 68, 46, 92, 72, 32, 94, 89, 84,  4, 18, 89,\n",
      "        31, 86, 99,  6, 50, 39, 39, 45, 34, 49, 63, 30, 25, 68])\n",
      "142 torch.Size([32, 3, 32, 32]) tensor([94, 12, 85, 33, 71, 62, 84, 84, 95, 17, 47, 34, 51, 90, 15, 19, 58, 80,\n",
      "        60, 31, 70, 72, 83, 87, 29, 62, 38, 26, 74, 54, 52, 15])\n",
      "143 torch.Size([32, 3, 32, 32]) tensor([55, 88, 76, 76, 20, 18, 60, 62, 83, 25, 89, 95, 58, 59, 63,  6, 17, 96,\n",
      "        12, 71, 26, 13, 60, 26, 49, 11, 94, 25,  2, 50, 77, 21])\n",
      "144 torch.Size([32, 3, 32, 32]) tensor([64, 14, 66, 58, 88, 75,  9, 76, 21, 78, 61, 48, 60,  0, 84, 37, 55, 76,\n",
      "        36, 78, 96,  4, 13, 55, 60, 69, 20, 29, 10, 34, 69, 38])\n",
      "145 torch.Size([32, 3, 32, 32]) tensor([82, 41, 53, 48, 32, 75, 28, 30, 40, 82, 10, 30, 77, 16, 51, 16, 56, 32,\n",
      "         3, 25, 90, 94,  4, 52, 61, 50, 12, 38, 66, 54, 13, 91])\n",
      "146 torch.Size([32, 3, 32, 32]) tensor([ 9, 93, 48, 88, 75, 73, 74, 92, 65, 93, 78, 70, 85, 44, 69, 99, 87, 39,\n",
      "        57, 20, 83, 61, 55, 71, 43, 96, 86, 13, 48, 54, 70, 58])\n",
      "147 torch.Size([32, 3, 32, 32]) tensor([ 8, 37,  5, 13, 79, 54, 75,  9, 95, 39,  7, 58, 54, 68, 44, 48, 60, 23,\n",
      "        76, 77, 43,  4, 63, 12, 58, 39, 56, 40, 15,  1, 42,  3])\n",
      "148 torch.Size([32, 3, 32, 32]) tensor([63, 84, 30, 56, 28, 59, 89, 94, 91,  0, 28, 89, 52, 94,  3, 26, 43, 53,\n",
      "        60, 49, 50, 29, 56, 94, 81, 14, 80,  6, 66, 50, 11, 37])\n",
      "149 torch.Size([32, 3, 32, 32]) tensor([20,  7, 70, 97, 53, 73, 66, 69,  5, 48, 79, 56, 57, 54, 84, 90, 83, 76,\n",
      "        80, 68, 77, 64, 15,  3, 35, 46, 23,  7, 80, 80, 77, 54])\n",
      "150 torch.Size([32, 3, 32, 32]) tensor([50, 94, 84, 52, 67,  8, 17, 44, 40,  6, 26, 12, 56, 47,  4, 27, 50, 14,\n",
      "        38, 45, 63, 67, 60, 90, 43, 48, 69,  1, 68, 15, 83, 72])\n",
      "151 torch.Size([32, 3, 32, 32]) tensor([11, 76, 55,  5, 69, 98, 15, 34, 23, 66, 76, 81, 55,  5, 59, 38, 80, 97,\n",
      "        94, 44, 75, 19, 32, 67, 23, 13, 48, 79,  7, 49, 42, 77])\n",
      "152 torch.Size([32, 3, 32, 32]) tensor([ 0,  7, 64, 79, 49, 82, 87,  6, 71, 65, 29,  2, 88, 13, 15, 68, 32, 76,\n",
      "        49,  3, 34, 32, 50, 44, 22, 13, 17,  3, 96, 44, 98, 68])\n",
      "153 torch.Size([32, 3, 32, 32]) tensor([94, 58, 44, 36, 55, 49, 79, 73, 54, 28, 95, 96, 86, 95,  0, 60, 93, 82,\n",
      "        94, 84, 79,  4, 36, 16, 56, 90, 46, 32, 70, 19,  1, 33])\n",
      "154 torch.Size([32, 3, 32, 32]) tensor([87, 61, 87, 52, 64, 98, 49, 84,  2, 34,  0, 15, 21, 25, 10, 54, 68, 26,\n",
      "        85, 82, 56, 44, 41,  0, 74, 60, 75, 93, 12, 46, 89,  7])\n",
      "155 torch.Size([32, 3, 32, 32]) tensor([60,  5, 17, 53, 34, 55, 16, 67, 78, 81, 54, 30, 86, 96, 84, 89, 17, 57,\n",
      "        61, 32, 83, 72, 69, 71, 44, 33, 68, 32, 22, 19, 58, 90])\n",
      "156 torch.Size([32, 3, 32, 32]) tensor([35, 43, 19, 82, 62, 89, 45, 59, 54, 37, 53, 34, 68, 44, 17,  1, 28, 93,\n",
      "         2, 90, 16,  1, 58, 92, 76, 21,  9, 23, 74, 63, 35, 99])\n",
      "157 torch.Size([32, 3, 32, 32]) tensor([87,  1, 93, 12,  4, 85, 11, 75, 38, 69, 58, 97, 21, 28, 46, 70, 76, 52,\n",
      "        62, 50, 59, 28, 59, 16, 21, 93, 30, 40, 27, 23, 74, 51])\n",
      "158 torch.Size([32, 3, 32, 32]) tensor([29, 20, 29, 51, 55, 34, 73,  5, 70, 98, 51, 68, 94, 29,  0, 17, 12, 98,\n",
      "         1, 78,  6, 58,  4, 62, 96, 80, 71, 34, 60, 46, 26, 20])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "159 torch.Size([32, 3, 32, 32]) tensor([25,  7, 25, 98, 39, 97, 97, 75, 83, 27, 53, 17, 22, 23, 27, 66, 23, 37,\n",
      "        38, 32,  0, 99, 47, 97, 10,  9, 73, 62, 81, 76, 87, 71])\n",
      "160 torch.Size([32, 3, 32, 32]) tensor([55, 49, 47, 74, 54, 82, 57, 61, 84, 35, 83, 27, 28,  5,  8, 87, 40, 57,\n",
      "        34, 15, 66, 34, 11, 17, 92, 44, 73,  1, 74, 45, 45, 35])\n",
      "161 torch.Size([32, 3, 32, 32]) tensor([67, 10,  3,  9, 16, 90, 55, 79, 55, 59, 61,  0, 76, 14, 76, 64, 43, 22,\n",
      "        17, 26, 98, 98, 52, 50, 87, 44, 32, 51, 19, 46, 24, 20])\n",
      "162 torch.Size([32, 3, 32, 32]) tensor([16, 66, 42, 63, 30, 75, 72, 47, 97,  5, 50, 85, 66, 10, 99, 16, 11, 63,\n",
      "        55,  0, 19, 98, 68, 95,  3, 48, 16, 34, 42, 88, 74, 43])\n",
      "163 torch.Size([32, 3, 32, 32]) tensor([20,  9, 87, 33, 44, 18, 71, 65, 33, 50, 84, 97,  8, 33, 65,  4,  0, 51,\n",
      "        81, 48, 70, 94, 20, 19, 37, 84, 71, 66, 31, 87, 43, 67])\n",
      "164 torch.Size([32, 3, 32, 32]) tensor([88, 18, 59, 60, 57, 60, 56, 78, 95, 18, 77, 47, 93, 89, 57, 37, 74, 75,\n",
      "        61, 85, 46, 53, 22, 19, 52, 59, 18, 73, 29, 91, 86, 90])\n",
      "165 torch.Size([32, 3, 32, 32]) tensor([86, 23, 43, 39, 69, 36, 21, 39, 68, 83, 72, 99, 24, 52, 92, 32, 76, 17,\n",
      "        25, 83,  2, 12, 40, 64, 43, 29, 97, 63, 19, 39, 73, 39])\n",
      "166 torch.Size([32, 3, 32, 32]) tensor([65, 25, 56, 97, 20, 87, 54, 31, 33, 71, 51, 94, 51, 52, 19, 44, 78, 29,\n",
      "        12, 47, 65, 81, 54, 17, 46, 33, 87, 66, 30, 65,  4, 11])\n",
      "167 torch.Size([32, 3, 32, 32]) tensor([75, 29, 97, 76, 79, 98, 57, 57, 11, 67, 70, 47, 48, 44, 28, 46, 13,  8,\n",
      "        99, 91,  2, 33, 54, 68, 33, 27, 95, 49,  7, 32, 82,  2])\n",
      "168 torch.Size([32, 3, 32, 32]) tensor([ 9,  8, 60, 98, 76,  8, 82, 92, 67, 11, 95, 89, 37, 45,  7, 83, 58, 29,\n",
      "        71,  2, 91, 19, 83, 86, 43, 58, 43,  9, 53, 74, 82,  8])\n",
      "169 torch.Size([32, 3, 32, 32]) tensor([ 9, 73,  2, 69, 54, 89, 31, 45, 40, 23, 73, 16, 98, 87, 77, 43, 63, 46,\n",
      "        36, 33, 10, 91, 91, 45, 20, 57, 98, 48, 33, 59, 27, 70])\n",
      "170 torch.Size([32, 3, 32, 32]) tensor([10, 93, 40, 40, 97, 55, 63, 73, 89,  1, 56,  1, 49,  9, 79, 30, 61, 76,\n",
      "        16, 30, 65, 96, 93, 81, 31, 29, 30, 83, 71, 81, 17, 69])\n",
      "171 torch.Size([32, 3, 32, 32]) tensor([39, 95, 60, 11, 86, 58, 11, 57, 90, 55, 23,  0, 47, 83, 79, 35, 18, 90,\n",
      "        42, 80, 15, 79, 62, 82, 57, 52, 60,  9, 94, 67, 40, 58])\n",
      "172 torch.Size([32, 3, 32, 32]) tensor([50,  7, 24, 80, 56,  1, 39, 97, 26, 50, 41, 54, 49, 39,  1, 82, 87, 71,\n",
      "        29, 58, 27, 11, 60, 44, 38, 92,  5, 88, 83, 52, 76, 61])\n",
      "173 torch.Size([32, 3, 32, 32]) tensor([43, 36, 88, 90, 29, 58, 15, 33, 91, 27, 65, 13, 96, 25, 12, 27, 75, 92,\n",
      "        67, 10, 81, 96, 52, 44, 92, 30, 24, 46, 23, 67, 22, 34])\n",
      "174 torch.Size([32, 3, 32, 32]) tensor([98, 87, 88, 37, 43, 11, 15, 30,  2, 30, 61, 21, 25, 35, 20, 30, 75, 82,\n",
      "        85, 55, 65,  7, 42, 84, 96, 74, 65, 20, 67,  3, 36, 55])\n",
      "175 torch.Size([32, 3, 32, 32]) tensor([76,  0, 94, 92,  3, 38, 60, 13, 10, 55, 39, 78, 75, 45, 20, 67, 36, 92,\n",
      "         2, 11, 97, 23, 70, 48, 23, 36, 23, 59, 23, 16, 20, 61])\n",
      "176 torch.Size([32, 3, 32, 32]) tensor([49, 64,  7, 89, 99, 34,  7, 16, 34, 80, 26, 44, 70, 83, 20, 26,  1, 96,\n",
      "        25, 24, 16, 95, 46, 25, 65,  5, 63, 75, 21, 70, 96, 12])\n",
      "177 torch.Size([32, 3, 32, 32]) tensor([86, 14, 25, 98, 87,  6, 56, 11, 22, 73, 96, 96, 47, 68, 79, 56, 40, 85,\n",
      "        33,  0, 94, 33, 29, 23, 29, 80, 53, 76, 96, 37, 46, 61])\n",
      "178 torch.Size([32, 3, 32, 32]) tensor([23,  4,  6, 84,  8, 13, 76, 15, 75, 20, 11, 61, 27, 68, 47, 38, 53, 42,\n",
      "        33,  8, 18, 49, 51, 30, 10,  4,  9, 95,  3, 17, 61, 22])\n",
      "179 torch.Size([32, 3, 32, 32]) tensor([77, 80, 25, 77, 56, 59, 58,  6, 60, 60, 66, 12, 48, 77, 78, 85, 30, 38,\n",
      "        36, 34,  7, 21, 67, 36, 33, 76, 94, 87, 63, 63, 64, 96])\n",
      "180 torch.Size([32, 3, 32, 32]) tensor([23, 51, 65, 50, 35, 49, 42, 25, 99, 93, 39, 55, 75, 44, 28, 70, 39, 97,\n",
      "        41, 21, 43, 47, 10, 26, 90, 71, 87, 76, 12, 36, 52, 71])\n",
      "181 torch.Size([32, 3, 32, 32]) tensor([57, 27, 68, 21, 63, 55, 56, 84, 58, 62,  1, 75, 91, 41, 99, 46, 80, 61,\n",
      "         2, 41, 22, 77, 35, 43, 70, 27, 50, 73,  1, 91, 19, 18])\n",
      "182 torch.Size([32, 3, 32, 32]) tensor([14, 16, 48, 45, 62, 69, 51,  0, 26,  5, 68, 42, 60, 26, 59, 80, 44,  0,\n",
      "        29, 60, 84, 31, 55, 47, 58, 86, 26, 87, 41, 87, 29, 91])\n",
      "183 torch.Size([32, 3, 32, 32]) tensor([40, 96, 69, 17, 39, 43, 61, 93, 91,  1, 79, 18, 19, 21, 73, 77, 76, 46,\n",
      "        42, 19, 19, 88, 67, 52, 79,  7, 26, 80, 19, 42, 80, 35])\n",
      "184 torch.Size([32, 3, 32, 32]) tensor([10,  2, 82, 77, 15, 81, 71, 65, 81,  6, 16, 87, 39, 71, 80, 97, 36,  6,\n",
      "        87, 55, 74, 78, 10, 52, 65, 24,  5, 42, 42, 10, 79, 83])\n",
      "185 torch.Size([32, 3, 32, 32]) tensor([66, 62, 14, 52, 63, 68, 96, 42, 46, 85, 42,  7, 87, 35, 95, 57,  6,  6,\n",
      "        57, 81, 17, 69, 31, 91, 94, 30, 33, 94, 12, 98,  1, 65])\n",
      "186 torch.Size([32, 3, 32, 32]) tensor([36, 27, 86, 30, 83,  6, 39, 52, 30, 11, 95,  1, 34, 48, 99, 39, 62, 98,\n",
      "        76, 21, 56, 70, 17, 75, 54, 96,  4, 70, 93, 33,  7, 90])\n",
      "187 torch.Size([32, 3, 32, 32]) tensor([ 5, 68, 23, 32, 37, 15, 75, 90, 18, 32, 74, 11, 71, 97,  1, 40,  4, 60,\n",
      "        91, 58,  2,  6, 49, 43, 96, 97,  3, 25, 46, 84, 41, 21])\n",
      "188 torch.Size([32, 3, 32, 32]) tensor([ 6, 20, 33, 74, 69, 47, 47, 58,  5, 56, 72, 70, 91, 94, 63, 42,  0, 52,\n",
      "        40, 87,  6, 55, 68, 89, 25, 16, 52, 17,  9, 76, 58, 82])\n",
      "189 torch.Size([32, 3, 32, 32]) tensor([42, 59,  5, 97, 18, 53, 73, 77, 29, 92, 89, 84, 56, 55, 97, 93, 66, 77,\n",
      "        92, 85, 27, 23, 28, 45,  0, 33, 44, 19, 20, 83, 16, 40])\n",
      "190 torch.Size([32, 3, 32, 32]) tensor([51, 70, 37, 66, 49, 58, 23, 14, 67, 99,  8, 79, 11, 24, 68, 81, 83, 52,\n",
      "        96, 47, 12, 27, 35, 73, 38,  9, 81, 82, 13, 81, 65,  2])\n",
      "191 torch.Size([32, 3, 32, 32]) tensor([75,  9, 27, 20, 43, 32,  6, 35, 82, 61, 72,  6, 63,  4,  7, 56, 29, 17,\n",
      "        74, 63, 41, 31, 13, 45, 78, 17, 63, 22, 51, 12, 18, 51])\n",
      "192 torch.Size([32, 3, 32, 32]) tensor([94, 52, 10,  4, 81, 97, 86,  2,  1, 48, 94, 99, 19, 47, 16, 10, 37, 13,\n",
      "        45,  2, 62, 86, 77, 90, 23, 18, 14, 46, 16, 19, 34, 12])\n",
      "193 torch.Size([32, 3, 32, 32]) tensor([44, 62, 56, 53, 89, 33, 78, 27, 16, 97, 59, 56, 91, 19, 99, 58,  8, 28,\n",
      "        29, 70, 39, 12, 85, 33, 75, 96, 75, 99,  4, 63, 70, 40])\n",
      "194 torch.Size([32, 3, 32, 32]) tensor([35, 41, 16, 81, 65, 56,  2, 94, 72, 69, 50, 53,  2, 25, 36, 76, 21, 17,\n",
      "        10, 49, 50, 61, 53, 55, 96, 27,  6, 37, 50, 99, 71, 25])\n",
      "195 torch.Size([32, 3, 32, 32]) tensor([76, 52, 95, 35, 52, 31, 11, 24, 38, 53, 77, 65, 73, 45, 71, 81, 24, 70,\n",
      "        20, 76, 49, 77, 20, 40, 57, 65, 22, 48,  1, 63, 81, 76])\n",
      "196 torch.Size([32, 3, 32, 32]) tensor([61, 34, 63, 16, 24, 30, 27, 12, 44, 69, 38, 69, 46, 46, 12, 72, 25, 63,\n",
      "         5, 68, 39, 64, 88, 55, 72, 34, 90, 56, 56, 43, 87, 74])\n",
      "197 torch.Size([32, 3, 32, 32]) tensor([84, 12, 88, 62, 50, 67, 30, 85, 69, 34, 25, 78, 24, 42, 19, 43, 27, 49,\n",
      "        44,  5, 22, 52, 17, 27, 36, 36,  3, 95, 28,  5, 78,  4])\n",
      "198 torch.Size([32, 3, 32, 32]) tensor([30, 50, 85, 25, 59, 29, 91, 58, 55, 29, 81,  0, 58, 31, 60, 70, 14, 42,\n",
      "        80, 81, 13, 82, 93, 32, 37, 63, 48, 12, 80, 94, 35, 99])\n",
      "199 torch.Size([32, 3, 32, 32]) tensor([28, 37, 22, 86, 40, 51, 18, 76, 74,  5, 15, 56, 74, 89, 91, 19, 46, 84,\n",
      "        34, 48, 27, 36, 26, 26, 28, 80,  9, 62, 81, 12, 42, 56])\n",
      "200 torch.Size([32, 3, 32, 32]) tensor([89,  7, 79, 45, 13, 62, 37, 53, 15, 83, 10, 56, 64,  6, 40,  2, 51, 17,\n",
      "        56, 92, 55, 52, 53, 11, 89, 64, 65, 84, 37, 54, 58,  6])\n",
      "201 torch.Size([32, 3, 32, 32]) tensor([18,  6, 46, 68, 12, 20, 50, 10, 28, 67, 72, 60, 30, 17, 35, 64, 20, 36,\n",
      "        86, 56, 72, 77, 73, 56, 25,  3, 10, 11, 20,  0,  9, 36])\n",
      "202 torch.Size([32, 3, 32, 32]) tensor([90, 31,  9, 93, 45, 62, 85, 35, 76, 37, 25, 30, 46,  5, 95,  0, 87, 20,\n",
      "        89,  6, 17, 57, 94, 58, 49, 98, 81, 21, 91, 29, 89, 44])\n",
      "203 torch.Size([32, 3, 32, 32]) tensor([15, 13, 36,  8, 79, 51, 55, 86, 58, 33, 93,  5, 16, 19, 90, 42,  5, 19,\n",
      "        99, 54, 20, 78, 91, 44, 20, 68, 60, 74, 76, 39, 92, 52])\n",
      "204 torch.Size([32, 3, 32, 32]) tensor([89, 55, 57, 24, 23, 56, 26, 40,  5, 64, 40, 55,  0, 97, 77, 65, 97, 38,\n",
      "        41,  8, 60, 55, 35, 70, 69, 58, 64, 39,  3,  2, 31, 29])\n",
      "205 torch.Size([32, 3, 32, 32]) tensor([38, 27, 60,  4, 47, 53, 99, 80, 44,  8, 44, 37, 56, 60, 93, 17,  4,  5,\n",
      "        41, 63, 21, 43, 68, 90, 56, 63, 98, 79, 18, 22, 47, 36])\n",
      "206 torch.Size([32, 3, 32, 32]) tensor([17, 42, 10, 83, 89, 95, 95, 45,  5, 80, 20, 19, 12, 81, 25, 34, 74,  3,\n",
      "        90, 13,  2, 72, 16,  6, 39, 69, 66, 32, 62, 65, 36, 62])\n",
      "207 torch.Size([32, 3, 32, 32]) tensor([49, 88, 22, 89, 86, 15, 23, 31, 17, 24, 28, 48, 43, 38, 76, 34, 83, 53,\n",
      "        10, 79, 78, 65, 38, 50, 22, 10, 97, 41, 15, 76, 24, 10])\n",
      "208 torch.Size([32, 3, 32, 32]) tensor([95, 66, 22, 25, 20, 43, 62, 14, 73, 66, 34, 13, 56, 51, 14, 34, 60, 63,\n",
      "        97, 15,  5, 34, 31, 39, 42, 51, 30, 53, 57, 91, 40, 56])\n",
      "209 torch.Size([32, 3, 32, 32]) tensor([64, 41, 98, 91, 10, 41, 85,  8, 18, 20, 68, 68, 24, 33, 59,  1, 60, 68,\n",
      "        87, 81, 58, 66, 72, 19, 55, 60, 16, 99,  2,  7, 51,  0])\n",
      "210 torch.Size([32, 3, 32, 32]) tensor([26, 57, 12, 58, 49, 34,  0, 79, 87, 51, 70, 60, 18,  1,  5, 91, 64, 33,\n",
      "         7, 41, 41, 25,  1, 45, 51, 94, 95, 61, 78, 75,  7, 64])\n",
      "211 torch.Size([32, 3, 32, 32]) tensor([12, 35, 32, 34, 45,  1, 41, 56,  6, 26, 88, 54, 82, 45, 49, 88, 45, 38,\n",
      "        96, 85, 62, 11, 58, 14, 66, 38, 26, 81, 60, 89, 39, 44])\n",
      "212 torch.Size([32, 3, 32, 32]) tensor([82,  7,  7, 78, 56, 50, 84, 74, 70, 27, 47, 36, 40, 29, 22, 68, 38, 85,\n",
      "        48, 33, 78, 44, 20, 16, 24,  3,  0, 74, 83, 18, 15, 58])\n",
      "213 torch.Size([32, 3, 32, 32]) tensor([24, 49, 54, 68,  0, 52, 67, 35, 15, 32, 12, 87, 76, 59, 49, 35, 82, 55,\n",
      "        74,  3, 46, 14, 39, 71, 41, 41, 16, 76, 14, 44, 59,  8])\n",
      "214 torch.Size([32, 3, 32, 32]) tensor([51, 21, 58, 25, 80, 89, 98, 25, 45, 84, 95, 30, 12, 19, 69, 38, 16, 93,\n",
      "        36, 81, 83, 84, 22, 63, 76, 28, 57, 84,  4, 83,  6, 52])\n",
      "215 torch.Size([32, 3, 32, 32]) tensor([70, 39, 80, 71,  3, 73,  7, 95, 54, 95, 57, 97, 52, 99, 25,  1, 35, 36,\n",
      "        21, 94, 97, 34, 68, 59, 79, 56, 18, 57, 76, 30, 60, 65])\n",
      "216 torch.Size([32, 3, 32, 32]) tensor([42, 87, 30,  7, 40, 34, 77, 77, 33, 46, 25, 10,  5, 55, 38, 64, 47, 97,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        11,  0, 27, 47, 57, 44, 86, 35, 82,  0, 21, 26, 93, 14])\n",
      "217 torch.Size([32, 3, 32, 32]) tensor([ 2, 31, 77, 37, 76, 51, 43, 23, 40, 28, 25, 53, 53, 98, 62,  4, 88,  7,\n",
      "        72, 40,  7, 21, 54, 27,  5, 33, 61, 39, 46, 46, 23, 82])\n",
      "218 torch.Size([32, 3, 32, 32]) tensor([40,  8, 11, 26,  3, 47, 69, 68, 92,  2, 70, 35, 51, 20, 19, 72, 92, 75,\n",
      "        76, 65,  2, 96, 49, 84, 14, 88, 52, 39, 45,  6,  2, 90])\n",
      "219 torch.Size([32, 3, 32, 32]) tensor([66, 48, 78, 11, 97, 87, 63, 19, 60, 82,  2, 50, 98,  8, 47, 57, 15, 74,\n",
      "        43, 49, 22, 69, 71, 12, 51, 71, 47, 58, 98, 31, 91, 68])\n",
      "220 torch.Size([32, 3, 32, 32]) tensor([71, 64, 59,  5, 94, 85, 21, 93, 17, 38, 38, 36, 41, 98, 20,  6, 96, 97,\n",
      "        80, 24, 68, 33, 26,  5, 86, 32, 55, 64, 81, 82,  8, 22])\n",
      "221 torch.Size([32, 3, 32, 32]) tensor([71,  3, 70, 88, 41, 54, 14, 45, 53, 89, 38, 73, 40, 76, 66, 88, 12, 86,\n",
      "         9,  7, 47, 47, 85,  7, 76, 13, 28, 94, 14, 47, 37, 63])\n",
      "222 torch.Size([32, 3, 32, 32]) tensor([ 0, 15,  1, 29, 67, 88, 56, 43, 75, 55, 34, 82, 92, 35, 79, 19, 59,  0,\n",
      "        91, 35, 93, 97, 34,  1,  6, 41,  8, 56, 23, 73, 36, 21])\n",
      "223 torch.Size([32, 3, 32, 32]) tensor([35, 61, 43, 98, 52, 61, 16, 67, 51, 79, 23, 72, 71, 90, 22, 38, 67,  7,\n",
      "        50, 53,  7, 61, 72, 56, 10, 69, 79, 74, 34, 61, 55,  5])\n",
      "224 torch.Size([32, 3, 32, 32]) tensor([88, 84, 32, 18, 26,  8, 66, 64,  6,  9, 12, 30, 13,  8, 81, 38, 19, 69,\n",
      "        83, 88, 12, 47, 84, 23, 80, 80, 36, 92, 47, 45, 49,  2])\n",
      "225 torch.Size([32, 3, 32, 32]) tensor([45, 83, 70, 17, 29, 58, 31, 94, 59, 12, 75, 74, 82,  5, 94,  6, 95, 99,\n",
      "        95, 35, 84, 64, 26, 38, 50, 96, 24, 20, 73,  0,  8, 36])\n",
      "226 torch.Size([32, 3, 32, 32]) tensor([68, 35, 49, 27, 25,  4, 97, 44,  4, 71,  0, 53, 37, 69, 79, 78, 25, 88,\n",
      "        53, 85, 21, 15, 21, 95, 77, 56, 79, 19, 10, 31, 20, 34])\n",
      "227 torch.Size([32, 3, 32, 32]) tensor([42, 49, 82, 68, 13, 49, 38, 46, 40, 14, 58, 80, 94, 78,  7,  1, 48, 47,\n",
      "        31, 51, 12, 49, 96, 91, 36, 32, 43, 84, 81, 94, 45, 98])\n",
      "228 torch.Size([32, 3, 32, 32]) tensor([61, 97, 51, 80, 32, 46, 99, 49, 70,  2,  9, 25, 16, 94, 72, 45, 24, 68,\n",
      "        63, 29, 78, 14, 54, 97, 32, 71, 19, 66, 98, 95, 62, 72])\n",
      "229 torch.Size([32, 3, 32, 32]) tensor([47, 11, 49, 18, 86, 53, 79, 68, 15, 38, 66, 63, 15, 56, 54, 27, 42, 73,\n",
      "        41, 36, 47, 94, 82, 28, 72, 44, 53, 53, 65, 43,  5, 39])\n",
      "230 torch.Size([32, 3, 32, 32]) tensor([97, 36, 16, 84, 97, 86, 89, 57, 79,  1, 69, 81, 87, 74, 46, 53, 61, 42,\n",
      "        88, 76, 23, 82, 16, 84, 84, 53, 10,  5, 40,  4, 43, 61])\n",
      "231 torch.Size([32, 3, 32, 32]) tensor([93, 45, 69, 38, 37, 69, 14, 76, 70, 38, 62, 52, 83, 93, 64, 22, 74, 50,\n",
      "        11, 68, 81, 30,  2, 62,  8, 63, 46, 99, 91, 34, 88, 20])\n",
      "232 torch.Size([32, 3, 32, 32]) tensor([27, 38, 88, 27, 81,  6, 83, 34, 20, 21, 74, 48, 34, 35, 46,  2, 88, 41,\n",
      "        93, 75, 26, 79, 61, 31, 75, 94, 51,  4, 90, 35, 15, 54])\n",
      "233 torch.Size([32, 3, 32, 32]) tensor([69, 59, 46, 78, 44, 15, 70,  9, 72,  2, 69, 60, 47, 16, 86, 97, 38, 21,\n",
      "        48,  9, 59, 87, 31, 45, 98, 34, 76, 59, 10, 57, 39, 14])\n",
      "234 torch.Size([32, 3, 32, 32]) tensor([ 1, 15, 86, 92, 30, 47, 22, 47, 55, 94,  6, 50, 30, 88, 88, 44, 95, 32,\n",
      "        38, 58, 20, 37, 65, 60, 76, 25, 70, 47, 30, 29, 79, 13])\n",
      "235 torch.Size([32, 3, 32, 32]) tensor([ 6, 97, 14,  4, 48, 12, 71, 43, 92, 92, 81, 14,  6, 13, 33, 43, 26, 85,\n",
      "        95, 52, 86,  2, 99, 52, 67, 99, 36, 54, 53, 63, 98, 11])\n",
      "236 torch.Size([32, 3, 32, 32]) tensor([62, 78, 18, 40, 61, 35, 48, 26, 70, 31, 31, 20, 70, 39, 72, 79, 55, 68,\n",
      "        58, 11, 26, 99, 18, 47, 52, 59, 23, 99, 15, 98,  6, 41])\n",
      "237 torch.Size([32, 3, 32, 32]) tensor([47, 29, 42,  5,  1, 77, 31, 80,  9, 28, 45, 37, 17, 41,  7, 92, 44,  3,\n",
      "        92, 65, 29,  8, 81, 90, 33, 98, 77, 11, 92, 44, 14, 56])\n",
      "238 torch.Size([32, 3, 32, 32]) tensor([99, 34, 77,  4, 65, 61, 49, 50, 58, 16, 97, 69, 90, 40, 95, 94, 43, 15,\n",
      "        74, 75, 19, 78, 84, 66, 87, 28, 13, 10, 19, 37, 17, 86])\n",
      "239 torch.Size([32, 3, 32, 32]) tensor([64, 25, 10, 78, 63, 87, 88, 32, 30, 15, 71, 37, 68, 87, 30,  9, 40, 29,\n",
      "        46, 81,  4,  9, 35, 76, 69, 22,  4, 84,  5, 70, 84, 24])\n",
      "240 torch.Size([32, 3, 32, 32]) tensor([21, 73, 54, 77, 76, 67,  4, 45, 18, 89, 65, 70, 22, 62, 72,  2,  1,  8,\n",
      "        77, 39, 77, 85, 39, 83, 85, 35, 99,  5, 25, 26,  6, 24])\n",
      "241 torch.Size([32, 3, 32, 32]) tensor([87, 10, 55, 52, 19, 53, 16, 84,  0, 72, 47, 74, 22, 29, 63, 70, 91,  5,\n",
      "        74, 43, 98, 36, 53, 71, 61, 82, 23,  7, 92, 89, 61, 13])\n",
      "242 torch.Size([32, 3, 32, 32]) tensor([96, 93, 41, 88, 59, 75, 42, 51,  0, 23, 83, 81, 96, 29, 48, 10, 34, 13,\n",
      "        21, 76, 86, 40, 57, 97, 42,  3, 57, 74, 42, 82, 12, 69])\n",
      "243 torch.Size([32, 3, 32, 32]) tensor([10, 76, 65, 85, 44, 72, 35, 61, 31, 51,  5, 37, 87, 45, 16,  6, 95, 27,\n",
      "         5, 45, 84, 42, 35, 82, 39,  3, 90, 75, 16, 86, 57, 96])\n",
      "244 torch.Size([32, 3, 32, 32]) tensor([ 9, 37, 71, 69, 22,  2, 78, 19, 54, 11, 96, 50, 64,  8, 15, 94, 62,  8,\n",
      "        68, 44, 72,  7, 79, 82, 89, 18, 26, 71, 62, 45, 88, 45])\n",
      "245 torch.Size([32, 3, 32, 32]) tensor([77, 40, 60, 33, 92, 72, 92, 52, 60, 43, 67, 44, 97, 66, 17, 98,  1,  1,\n",
      "        56, 83, 59, 65, 99, 83, 43, 58, 66, 92, 79, 84, 75, 45])\n",
      "246 torch.Size([32, 3, 32, 32]) tensor([75, 28, 88, 26, 40, 73, 84, 64, 88, 46, 82, 21, 16, 51, 27, 32, 18, 36,\n",
      "         1, 64, 44, 35, 17, 72, 10, 61,  5, 94, 76, 33, 63, 41])\n",
      "247 torch.Size([32, 3, 32, 32]) tensor([66, 87, 96, 85, 83, 17, 16, 84, 93,  5, 37,  8, 19, 64, 39, 45, 97, 66,\n",
      "        40, 74, 95, 82, 39, 12, 92, 70, 85, 32,  8, 54, 56, 58])\n",
      "248 torch.Size([32, 3, 32, 32]) tensor([79,  0, 12, 51, 68,  8, 28, 33, 35, 68, 75, 50, 47, 80, 48, 64, 57,  5,\n",
      "         5, 67, 65, 17, 95, 88,  9, 35, 16, 50, 48, 15,  2, 68])\n",
      "249 torch.Size([32, 3, 32, 32]) tensor([67,  5, 14, 18, 49, 64, 27, 17, 46, 19, 72, 98, 89, 30, 84, 16, 41, 91,\n",
      "        98, 19, 20, 46, 91, 77,  8, 25,  9, 69, 19, 28, 68, 65])\n",
      "250 torch.Size([32, 3, 32, 32]) tensor([72, 46, 96,  1, 59, 91, 72, 48, 99, 97, 43, 33, 10, 48, 96,  5, 45,  4,\n",
      "        98, 78, 22,  2, 13,  1, 13, 68, 26, 19, 89, 54, 89, 54])\n",
      "251 torch.Size([32, 3, 32, 32]) tensor([69, 21, 62, 24, 65, 87, 97,  7, 74, 41, 94, 66, 54, 20, 20, 92, 78, 64,\n",
      "         2, 83,  4, 72, 57, 89, 35, 31, 41,  1, 69, 29, 51, 88])\n",
      "252 torch.Size([32, 3, 32, 32]) tensor([48, 57, 63,  8, 43, 97, 77, 86, 72, 46, 88, 89, 58, 33, 20, 50, 15, 63,\n",
      "        43, 93, 15, 30, 62, 31, 58, 64, 46, 19,  7, 77, 28, 32])\n",
      "253 torch.Size([32, 3, 32, 32]) tensor([88, 33, 64, 88,  3,  0, 89, 61, 19, 20, 37, 73, 70, 10, 27, 29, 54, 85,\n",
      "        86, 72, 89, 23, 62, 89, 80, 23, 69, 10, 49,  7, 82, 71])\n",
      "254 torch.Size([32, 3, 32, 32]) tensor([44, 47, 62, 37, 15, 22, 29, 75, 38, 35, 95,  1, 45, 35, 90, 22, 66, 70,\n",
      "        68, 41, 47, 97, 65, 92, 35, 70, 88, 93, 13, 39, 37, 34])\n",
      "255 torch.Size([32, 3, 32, 32]) tensor([91, 30, 50, 20, 93, 97, 51, 39, 63, 43, 23, 57, 25, 48,  1,  1, 53, 47,\n",
      "        38, 23, 61,  6, 18,  7, 22, 28, 36, 28, 51, 81, 16, 45])\n",
      "256 torch.Size([32, 3, 32, 32]) tensor([19, 81, 19, 36, 11, 78, 45, 52, 97, 43, 68, 99, 78, 12, 38, 80,  9, 80,\n",
      "         6, 43, 81,  8, 35,  6, 32, 16, 52, 78, 36, 82, 68, 23])\n",
      "257 torch.Size([32, 3, 32, 32]) tensor([65, 21, 30, 84, 67, 31, 83, 27,  7, 70, 22, 66, 92, 22, 95, 17, 78, 12,\n",
      "        86, 22, 74, 46, 69, 67,  0, 77, 92, 55, 74, 32, 24, 41])\n",
      "258 torch.Size([32, 3, 32, 32]) tensor([97, 66, 51, 78,  9, 19, 91, 61, 35,  9, 93, 39, 34, 39, 69, 40, 37, 25,\n",
      "        41, 74, 77, 26,  9, 69, 78, 25, 52, 61, 99, 71,  8, 51])\n",
      "259 torch.Size([32, 3, 32, 32]) tensor([41, 91, 43, 70, 36, 39, 47, 42, 99, 70, 78, 30, 14, 52, 67, 39, 86, 67,\n",
      "        31, 44, 78, 48, 35, 48, 19, 61,  2, 97, 47, 18, 85, 65])\n",
      "260 torch.Size([32, 3, 32, 32]) tensor([46, 18, 39, 32, 47, 21,  6, 87, 16, 78, 78, 51, 17, 70, 44, 33, 38, 39,\n",
      "        44, 72, 26, 83, 85, 32, 90, 82, 68, 95, 57, 95, 74, 74])\n",
      "261 torch.Size([32, 3, 32, 32]) tensor([83, 69, 94, 55, 34, 38, 29, 61, 81,  4, 42, 59, 69,  9, 14, 29, 44, 99,\n",
      "        33, 74, 15, 80, 69,  7,  7, 31, 81, 20,  4, 99, 38, 91])\n",
      "262 torch.Size([32, 3, 32, 32]) tensor([52, 33, 43, 51, 85, 79, 29, 84, 35, 96, 36, 47, 22,  2, 92, 45, 36, 59,\n",
      "        35, 64, 57, 91, 39, 89, 13, 87, 61, 15, 32, 17, 78, 40])\n",
      "263 torch.Size([32, 3, 32, 32]) tensor([40, 52, 41, 99, 47, 80, 55, 70, 43, 58, 53,  1, 60,  8,  8, 36, 10,  1,\n",
      "        89,  2, 52,  0, 67,  0, 71,  9, 19, 62, 77,  5, 14, 45])\n",
      "264 torch.Size([32, 3, 32, 32]) tensor([68, 91, 43, 89, 92, 82, 26, 83,  9, 57, 51, 35,  2, 27,  4, 18, 55, 65,\n",
      "        92, 42, 54, 92, 94, 10, 80, 79, 13, 56, 11, 89, 10, 25])\n",
      "265 torch.Size([32, 3, 32, 32]) tensor([52, 32, 16, 33, 39, 64, 13, 12, 64, 79, 61, 30, 99, 91,  6, 81, 71, 27,\n",
      "         6, 86, 26, 98, 55, 38, 72, 82, 28, 84,  1, 22, 58, 82])\n",
      "266 torch.Size([32, 3, 32, 32]) tensor([34, 13, 10, 76, 99, 24, 82, 41, 62, 63,  6, 30, 97, 28, 48, 88, 38, 27,\n",
      "        11, 77, 35, 38, 26, 41, 72, 74, 81,  4, 51, 17, 62, 34])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "267 torch.Size([32, 3, 32, 32]) tensor([96, 54, 91, 85, 82, 61, 26, 30, 13, 54, 12, 65, 18, 74, 28, 93, 46, 20,\n",
      "        33, 28, 30, 84, 66, 83, 67, 51, 63, 75, 35,  4, 30, 24])\n",
      "268 torch.Size([32, 3, 32, 32]) tensor([65, 15, 43, 90, 81, 45, 53, 56, 40, 46,  8, 15,  2,  8, 74, 14, 10, 44,\n",
      "        17, 82,  2, 25, 95, 25, 59, 83, 74, 56, 49, 35, 41, 32])\n",
      "269 torch.Size([32, 3, 32, 32]) tensor([64, 70, 83, 10, 18, 25, 86, 95,  1, 59, 61, 45, 44, 86, 96, 96,  5, 13,\n",
      "        95, 20, 40, 43, 43, 96, 87, 13, 72, 14, 28, 42, 61, 83])\n",
      "270 torch.Size([32, 3, 32, 32]) tensor([24,  4, 28, 27, 67, 40, 77, 31, 79, 80,  0, 94, 84, 11,  6, 80, 44,  8,\n",
      "        71,  5, 57, 63, 24, 32, 22, 51, 22,  9, 22, 51, 66, 63])\n",
      "271 torch.Size([32, 3, 32, 32]) tensor([ 4, 32, 32, 52, 37, 37, 61, 27,  8, 80, 41, 94, 66, 11, 95, 82, 65, 95,\n",
      "        30, 49, 52, 96, 59, 48, 99, 66, 92, 46, 11,  8,  8, 41])\n",
      "272 torch.Size([32, 3, 32, 32]) tensor([67, 27, 17, 91, 89, 82, 40, 55, 91, 60, 12, 41, 69, 80, 14,  0, 58, 60,\n",
      "        68, 99, 53, 28, 26, 34, 98, 99, 68, 10, 49,  8,  6, 41])\n",
      "273 torch.Size([32, 3, 32, 32]) tensor([85, 95,  9, 63, 34, 11, 37, 53, 75, 52, 33, 87, 13, 78, 17, 69, 31, 43,\n",
      "        18, 50, 68, 71, 25, 21, 43, 28,  6, 31, 30, 93, 44, 42])\n",
      "274 torch.Size([32, 3, 32, 32]) tensor([10, 41,  5, 91, 27,  3,  1, 10, 14, 92, 85, 60, 21, 92,  9, 24, 11, 67,\n",
      "         4, 25, 88, 57, 43, 47, 38, 82,  7, 49, 14, 69, 25, 47])\n",
      "275 torch.Size([32, 3, 32, 32]) tensor([61, 41, 30, 96, 62, 55,  8, 72, 23, 52, 59, 61, 43,  2, 17, 93, 30, 26,\n",
      "        24, 95, 59, 84, 84, 15, 26, 74, 45, 65, 52, 66, 37, 83])\n",
      "276 torch.Size([32, 3, 32, 32]) tensor([75, 58, 96, 81, 45, 97, 43, 94, 37, 87, 77, 60, 89, 27, 51, 60, 15, 54,\n",
      "        18,  3, 12, 58, 27, 59, 45,  3, 74,  2, 81, 21, 86, 65])\n",
      "277 torch.Size([32, 3, 32, 32]) tensor([ 1, 96, 12, 88,  7, 72, 21, 55, 89, 71, 49,  2, 26, 63, 32, 31, 55, 98,\n",
      "        75, 66, 24,  2, 58, 70, 93, 73,  6, 20, 52, 60,  8, 27])\n",
      "278 torch.Size([32, 3, 32, 32]) tensor([99, 22, 55, 91, 13, 54, 55, 75, 51,  7, 61, 72,  0, 43, 55, 49, 63, 21,\n",
      "        94,  4, 25, 76, 85, 60, 58, 76, 28, 30, 69, 65, 24,  4])\n",
      "279 torch.Size([32, 3, 32, 32]) tensor([92, 24, 50, 33, 31, 64, 36, 85, 33, 86, 97, 95, 31, 66, 66, 70, 59, 67,\n",
      "        36, 19, 10, 33, 80, 48, 45,  1, 10,  5, 98, 49,  3, 73])\n",
      "280 torch.Size([32, 3, 32, 32]) tensor([41, 34, 74, 77, 43, 75, 15, 86, 97, 94, 12,  9, 91, 62, 85, 77, 56, 31,\n",
      "        38, 84, 44, 43, 10, 47, 29, 79, 99, 72, 55, 35, 85, 48])\n",
      "281 torch.Size([32, 3, 32, 32]) tensor([26, 40, 52, 20, 15, 96,  2, 92, 23, 78, 39, 52, 85, 48, 88, 58, 54, 72,\n",
      "        95, 65,  0,  5, 36, 39, 47, 78, 31, 53, 72, 86, 70, 89])\n",
      "282 torch.Size([32, 3, 32, 32]) tensor([37, 15,  2,  5, 28,  2, 45, 91, 70, 16, 59, 74, 71, 47, 82,  1, 80, 84,\n",
      "        75, 14, 56, 79, 97, 23, 70, 79, 61, 76, 10, 54, 15, 73])\n",
      "283 torch.Size([32, 3, 32, 32]) tensor([37, 28, 93, 65, 81, 47, 67, 70, 23, 94, 70, 25, 24, 76, 73,  1, 67, 60,\n",
      "        93, 44, 78, 33, 82, 22, 96, 69, 80, 64, 77, 35, 91, 26])\n",
      "284 torch.Size([32, 3, 32, 32]) tensor([45, 13, 74, 62, 63, 17, 39, 57,  2, 19, 41,  1, 24, 10, 47, 84, 82, 46,\n",
      "        38, 13, 23, 17, 14, 91, 51, 89, 25, 91, 91, 29, 31, 40])\n",
      "285 torch.Size([32, 3, 32, 32]) tensor([50, 80, 73, 66, 97, 49, 84, 83, 80, 46, 49, 75, 87,  4, 44, 42, 48, 18,\n",
      "        80, 51, 20, 53, 16,  5, 57, 56, 29,  0, 27, 40,  5,  7])\n",
      "286 torch.Size([32, 3, 32, 32]) tensor([74, 10, 56, 76, 12, 74, 68, 17, 11, 75, 51, 32,  4, 64, 80,  9, 73, 67,\n",
      "        11, 81, 80, 93, 78, 44, 59,  7, 60,  9, 16, 23, 44, 71])\n",
      "287 torch.Size([32, 3, 32, 32]) tensor([75, 62, 13, 86, 15, 54,  6, 40,  9,  7, 45, 22, 15, 15, 99, 81, 84, 42,\n",
      "        65,  4, 66, 97, 45, 14, 91, 31,  2, 24, 15, 20, 48, 59])\n",
      "288 torch.Size([32, 3, 32, 32]) tensor([69, 49, 73, 76, 26,  3, 84, 14, 93, 24,  2, 55, 97, 31, 32, 14, 15, 50,\n",
      "         7, 65, 87, 18, 21, 68, 60, 67, 14, 24, 92, 40, 42, 53])\n",
      "289 torch.Size([32, 3, 32, 32]) tensor([51, 68, 99, 73, 65, 98, 79, 90, 94, 36, 72, 25, 41, 57, 49, 73, 46, 63,\n",
      "        16, 82, 15, 46, 66, 35, 34, 53, 51, 42, 40, 58, 38, 83])\n",
      "290 torch.Size([32, 3, 32, 32]) tensor([46, 60, 55, 87, 82, 34, 25, 78, 29, 97, 57, 81,  9, 93, 35, 54, 41, 30,\n",
      "        86, 96,  9,  1, 52, 66, 11,  8, 51,  1,  4, 51, 28, 42])\n",
      "291 torch.Size([32, 3, 32, 32]) tensor([33, 90, 59, 78, 71, 12, 20,  0,  6, 48, 56, 55,  3, 82, 90, 53, 55, 67,\n",
      "        82, 49, 43, 80, 53, 97, 14, 77, 24, 65, 70, 86, 70,  3])\n",
      "292 torch.Size([32, 3, 32, 32]) tensor([64, 12, 50, 31, 92, 62, 34, 22, 24, 28, 37, 55,  5, 11, 71, 94, 11, 51,\n",
      "        58, 73, 62, 56, 41, 68, 45, 92, 97, 24, 12, 29, 95, 30])\n",
      "293 torch.Size([32, 3, 32, 32]) tensor([13, 25, 58, 82,  2, 88, 80, 75,  4, 55, 99,  5, 42, 67, 30, 91, 54,  8,\n",
      "        86, 12, 34, 55, 82, 35, 38, 35, 73, 32, 38,  8, 49,  8])\n",
      "294 torch.Size([32, 3, 32, 32]) tensor([44, 29, 33, 91, 35, 11, 84, 62, 13, 76, 17, 92, 76, 29, 90, 45, 81,  1,\n",
      "        96, 29, 72, 53, 73, 96, 59, 14, 17, 13, 60, 48, 22, 68])\n",
      "295 torch.Size([32, 3, 32, 32]) tensor([62, 47, 63, 53, 47, 26, 22, 49, 86, 87, 24, 72, 24, 92, 86, 29, 15, 67,\n",
      "         5, 19, 19, 46, 16, 97, 36, 89,  7, 87, 71, 71, 43, 71])\n",
      "296 torch.Size([32, 3, 32, 32]) tensor([98, 86, 14, 53, 64, 71,  5, 58, 93,  3, 32, 46,  0, 99, 91, 63, 87, 33,\n",
      "        47, 51, 35,  9, 57, 54,  9, 75,  9, 18, 62, 72, 92, 84])\n",
      "297 torch.Size([32, 3, 32, 32]) tensor([20, 51, 16, 46, 37,  5,  9, 17, 48, 93, 67, 54, 55, 20, 38, 66, 29, 92,\n",
      "        65, 30, 11, 46, 13, 60, 76, 28,  7, 40, 11, 36,  0, 31])\n",
      "298 torch.Size([32, 3, 32, 32]) tensor([41, 72, 33,  0, 80, 62, 59, 24, 20, 69, 16, 92, 88, 40, 55, 61, 30, 53,\n",
      "        37, 92, 20, 51, 57, 67, 24, 59, 71, 21, 19, 14,  8, 59])\n",
      "299 torch.Size([32, 3, 32, 32]) tensor([59, 91, 61, 35, 14, 45, 20, 50,  1, 59, 93, 98, 53, 21, 19, 35, 85,  1,\n",
      "         0,  5,  3, 68, 66, 93, 14, 96, 33, 85, 24, 49, 22, 71])\n",
      "300 torch.Size([32, 3, 32, 32]) tensor([14, 29, 69, 68, 58, 99, 28, 28, 90,  7, 56, 71, 72, 98, 11, 68, 11, 48,\n",
      "        25, 82, 64, 55,  7, 88, 35, 51, 59, 76, 30, 34, 83, 41])\n",
      "301 torch.Size([32, 3, 32, 32]) tensor([91, 58, 70, 60,  4, 80, 94, 31, 81, 17, 48, 75, 70, 84, 94, 77, 29, 18,\n",
      "        14, 31, 35, 74, 34,  7, 51, 50, 75, 39, 56, 58, 43, 19])\n",
      "302 torch.Size([32, 3, 32, 32]) tensor([58, 88, 82, 17, 67, 56, 75, 74, 30, 91, 19, 90, 67, 29, 24, 43, 86,  6,\n",
      "        61, 87, 46, 70, 55, 66, 78, 41, 45, 64, 62, 42,  4,  1])\n",
      "303 torch.Size([32, 3, 32, 32]) tensor([63, 93, 93, 62, 40, 60, 24, 11, 54, 74, 11, 92, 84, 47, 86, 32,  5, 23,\n",
      "        33, 34, 15,  4, 79, 60, 12,  8, 75, 98, 23,  0, 13, 22])\n",
      "304 torch.Size([32, 3, 32, 32]) tensor([51, 38, 80,  8, 68, 99, 99, 15, 39, 73, 91, 29, 72, 37, 36, 12, 76, 42,\n",
      "        89, 96, 15, 37, 83, 85, 78, 26, 92, 21, 84, 81, 58, 59])\n",
      "305 torch.Size([32, 3, 32, 32]) tensor([16, 19,  4, 96, 41, 89, 25, 67, 27, 34, 72, 12, 83, 47,  4, 60, 88, 26,\n",
      "         1, 58, 43, 12, 91,  1,  7, 30, 61,  4, 58, 97, 41, 22])\n",
      "306 torch.Size([32, 3, 32, 32]) tensor([90, 10, 80, 65, 56, 77, 70, 26, 44, 80, 27, 83, 21, 91, 15, 64, 87, 28,\n",
      "        95, 55, 87, 47, 39, 70, 65, 77, 47, 23,  1, 76, 86, 25])\n",
      "307 torch.Size([32, 3, 32, 32]) tensor([77, 10, 44, 93, 17, 11, 67, 84, 50, 51, 87, 84, 91, 62, 91, 59, 75,  0,\n",
      "        80, 38, 68, 88, 89, 99, 97, 70,  5, 45, 96,  3, 80,  2])\n",
      "308 torch.Size([32, 3, 32, 32]) tensor([18, 41,  5, 15,  0, 44, 10, 60, 17, 27, 42, 62, 64, 23, 73, 84, 22, 87,\n",
      "        69, 81, 74, 22, 10, 94, 35, 13, 35, 14, 26, 61, 63,  7])\n",
      "309 torch.Size([32, 3, 32, 32]) tensor([42, 76, 62, 31, 88, 56, 42, 32, 24, 31, 37, 20, 78, 11, 66, 16, 10, 63,\n",
      "        49, 53, 70, 27, 98, 34, 83, 87, 39, 73, 77, 93, 95, 48])\n",
      "310 torch.Size([32, 3, 32, 32]) tensor([14, 28,  9, 32, 73,  2, 93, 29, 11, 77, 60, 71, 26, 94, 50, 62, 78, 17,\n",
      "        50, 40, 93, 36, 70, 42,  8, 78, 78, 66, 26, 28, 77, 88])\n",
      "311 torch.Size([32, 3, 32, 32]) tensor([18, 94, 69, 94, 95, 68, 58, 77, 71, 35, 87, 99, 18, 36, 95, 90,  0, 27,\n",
      "        24, 38, 34, 41, 70, 99, 54, 72, 93, 86, 29, 22, 38, 32])\n",
      "312 torch.Size([32, 3, 32, 32]) tensor([12, 58, 28, 15,  4, 96, 66, 50, 42, 83, 98, 79, 24, 99, 35, 93, 25, 20,\n",
      "         4, 16, 26, 70,  0, 27, 62, 42, 72, 13, 89, 85, 41,  6])\n",
      "313 torch.Size([32, 3, 32, 32]) tensor([81, 96, 61, 56, 50, 16, 11, 66, 25, 58, 56, 99, 96, 83, 58, 47, 13, 73,\n",
      "        32, 63, 36, 13, 95, 61,  7,  9, 93, 77, 85,  3, 53, 17])\n",
      "314 torch.Size([32, 3, 32, 32]) tensor([70, 75, 98, 76, 40, 37, 51, 95, 54, 54, 15, 13, 38, 68, 66, 71, 10, 85,\n",
      "        38, 85, 61, 56, 44, 49, 31, 65, 13, 31, 22, 14, 53, 60])\n",
      "315 torch.Size([32, 3, 32, 32]) tensor([62, 44,  6, 41, 98, 95, 40,  9, 50, 96,  2, 71, 64, 34,  7, 44, 28, 46,\n",
      "        10, 14,  9, 98, 20, 42, 52, 66, 30, 15, 41, 78, 67, 48])\n",
      "316 torch.Size([32, 3, 32, 32]) tensor([73, 53, 40, 33, 96, 18, 58, 92, 10,  5, 87, 88, 96, 29, 86, 84, 98,  3,\n",
      "        11, 72, 19, 91, 26, 34, 68, 85, 26, 80, 44, 92, 14,  4])\n",
      "317 torch.Size([32, 3, 32, 32]) tensor([25, 78, 88, 59, 64, 93,  0, 61, 24,  6, 12, 17, 38, 52, 95, 83, 59, 15,\n",
      "        96,  3,  0, 91,  7, 99, 86, 25, 41, 62, 27, 42, 92, 13])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "318 torch.Size([32, 3, 32, 32]) tensor([84, 86, 56, 55, 11, 80, 69, 45, 80, 74,  5, 37, 36, 71, 86, 63, 65, 55,\n",
      "        54, 77, 50, 20, 81, 18, 72, 77, 47,  8, 49, 79, 38,  7])\n",
      "319 torch.Size([32, 3, 32, 32]) tensor([23,  4, 39, 85,  0, 88, 43, 48,  6, 36, 13, 88, 67, 70, 15, 65, 86, 39,\n",
      "        26, 64, 60,  9, 33, 42, 74, 77, 58, 36, 49, 26, 73, 89])\n",
      "320 torch.Size([32, 3, 32, 32]) tensor([72, 10,  8, 88, 73, 95, 57, 25, 11,  3, 93, 28, 73, 94,  8, 42, 85,  6,\n",
      "        14, 33, 30, 31, 10,  3, 52, 29, 74, 16, 77, 99, 67, 75])\n",
      "321 torch.Size([32, 3, 32, 32]) tensor([50, 51, 76, 87, 82, 51,  4, 71, 87, 22, 45, 24,  0, 87, 73, 81, 66, 27,\n",
      "        18, 28, 67, 22, 38, 20, 71, 58, 15, 28, 82, 21, 83,  5])\n",
      "322 torch.Size([32, 3, 32, 32]) tensor([85, 16,  8, 37, 55, 93, 30,  9, 25, 34, 50, 28, 17, 18, 84, 32, 24, 44,\n",
      "        29, 29, 85, 20,  1, 82, 62, 33, 66,  2, 93, 74, 55, 12])\n",
      "323 torch.Size([32, 3, 32, 32]) tensor([50, 21, 23, 98,  7, 69, 42, 98, 27, 33, 75, 52, 40, 81, 90, 30, 97, 30,\n",
      "         0, 18,  1, 45, 40, 18,  1, 69, 17,  0, 43, 11,  2, 25])\n",
      "324 torch.Size([32, 3, 32, 32]) tensor([28, 13, 59, 25, 25, 67, 80, 39, 59, 98, 69, 49,  8, 17, 92, 77, 65, 49,\n",
      "        25, 72, 81, 99, 61, 62,  7, 81, 11, 96, 70, 18, 30, 63])\n",
      "325 torch.Size([32, 3, 32, 32]) tensor([11, 97, 74, 43, 48, 90, 35, 36, 74, 65, 76, 58, 12, 84, 82, 45, 92, 20,\n",
      "        75, 78, 92,  7, 57, 66, 80, 56, 50,  3, 45, 65, 24, 26])\n",
      "326 torch.Size([32, 3, 32, 32]) tensor([56, 35, 50,  0, 79, 58, 74, 74, 99, 86, 17, 73, 53,  7, 19, 87, 24, 27,\n",
      "        60, 67, 28, 49, 64, 47, 84,  4, 28, 34, 42, 36,  5, 28])\n",
      "327 torch.Size([32, 3, 32, 32]) tensor([32, 80, 86, 77, 72, 95, 85, 14, 37, 32, 34, 99, 86, 58, 76, 11, 94, 85,\n",
      "        71, 17, 76, 38, 65, 46, 61, 42, 73, 87, 49, 80, 89, 48])\n",
      "328 torch.Size([32, 3, 32, 32]) tensor([72, 59, 42, 71, 36, 40,  8, 59, 68, 78, 30, 83, 94, 46, 17, 80, 77, 90,\n",
      "        18, 68, 21, 10, 49, 73, 40, 58, 53, 15, 20, 54, 74, 73])\n",
      "329 torch.Size([32, 3, 32, 32]) tensor([74, 31, 11, 89, 25, 75, 27, 18,  3, 94, 40,  6, 11, 12,  6, 99, 18, 61,\n",
      "        48, 19, 94, 56, 51, 60, 70, 30, 51, 90, 20, 56, 35, 43])\n",
      "330 torch.Size([32, 3, 32, 32]) tensor([71, 45, 89, 50, 39, 81, 19, 98,  4, 21, 91, 98, 94, 64, 18, 58, 66, 18,\n",
      "        50, 72, 36, 66, 11, 59, 15, 77, 42, 50, 90, 20, 10, 50])\n",
      "331 torch.Size([32, 3, 32, 32]) tensor([74, 55, 43,  8, 87, 45, 80, 63, 60, 93, 26, 60, 35, 87, 48, 77, 69, 87,\n",
      "         5, 44, 35, 51, 64, 25, 68, 83, 31, 44,  8, 36,  2, 52])\n",
      "332 torch.Size([32, 3, 32, 32]) tensor([61,  3, 55, 55, 94, 23, 70, 69, 53, 38, 24, 26, 34, 96, 31, 15, 66, 50,\n",
      "        34, 95, 73, 66, 41, 20, 27, 87, 97, 35, 84, 86, 88,  6])\n",
      "333 torch.Size([32, 3, 32, 32]) tensor([81, 90, 10, 99, 80,  5, 21, 81, 90, 11, 79, 96, 41, 35, 39, 75, 26, 76,\n",
      "        64, 46, 21, 96, 76, 33, 45, 46, 23, 91, 94,  4, 50, 79])\n",
      "334 torch.Size([32, 3, 32, 32]) tensor([58, 57, 81, 17,  6, 28, 51, 75, 28, 14, 96, 31, 92, 92, 69, 74, 67, 75,\n",
      "        56, 92,  9, 79, 89, 15, 23, 24, 72, 48, 70, 45, 80, 79])\n",
      "335 torch.Size([32, 3, 32, 32]) tensor([ 9,  1, 22, 72, 60, 73, 54, 75, 92, 97, 17, 78, 58, 83,  1, 44, 97, 99,\n",
      "        87,  4, 62, 74, 13, 44, 56, 29, 53, 33, 91, 94, 98,  2])\n",
      "336 torch.Size([32, 3, 32, 32]) tensor([66, 66, 76, 98, 74, 87, 72, 42, 70, 58, 14, 33, 44, 49, 74, 35, 61, 98,\n",
      "        20, 11, 38, 81, 75,  6, 55, 43, 37, 14, 47, 76, 12, 48])\n",
      "337 torch.Size([32, 3, 32, 32]) tensor([14, 49, 62, 49, 93, 76, 54, 14, 54, 80, 44, 12, 66, 97, 96, 77, 98, 81,\n",
      "        14, 54, 87, 16, 38, 50, 83, 56, 55, 58,  9, 94, 10, 17])\n",
      "338 torch.Size([32, 3, 32, 32]) tensor([31, 97, 61,  0, 98, 72,  1, 81, 27, 78, 70, 99, 21, 10, 42, 29, 19, 58,\n",
      "        71, 54, 43, 42,  9, 63, 63,  7, 76,  3, 98, 75, 89,  2])\n",
      "339 torch.Size([32, 3, 32, 32]) tensor([13, 28, 99, 72, 53, 32, 68, 90, 72, 31, 55, 62, 30,  8, 24, 37,  6, 86,\n",
      "        25, 73, 51, 24, 21, 88, 25, 61, 52, 69, 77, 35, 96, 44])\n",
      "340 torch.Size([32, 3, 32, 32]) tensor([62, 95, 31, 30, 19, 60, 52, 54, 42, 76, 48, 49, 38, 36, 33, 75, 83, 29,\n",
      "         3,  9, 95, 31,  4, 63, 15, 89, 27,  6, 88, 99, 18, 65])\n",
      "341 torch.Size([32, 3, 32, 32]) tensor([46, 63, 45, 43, 29, 55, 56, 32, 15, 79, 45, 82, 98,  3, 98, 92, 79, 22,\n",
      "        91, 77, 48, 22, 64, 44,  5, 87, 73, 36, 44, 68, 75, 87])\n",
      "342 torch.Size([32, 3, 32, 32]) tensor([67, 22, 75, 80, 32, 36, 41, 20, 49, 18, 91, 15, 77, 42, 78,  3, 84, 80,\n",
      "        27, 40, 21, 92, 88, 99, 91, 26, 99, 36,  9, 58, 25, 56])\n",
      "343 torch.Size([32, 3, 32, 32]) tensor([52, 25,  8, 65, 39, 79, 42, 96, 48, 76, 45, 23, 38, 22,  4,  4, 53, 80,\n",
      "        13, 21, 43, 55, 67, 38, 69, 12, 82, 96, 17, 56,  5, 13])\n",
      "344 torch.Size([32, 3, 32, 32]) tensor([81, 71, 95, 86, 17, 56, 79, 86, 39, 86, 27, 79,  3,  7, 64, 23, 17, 68,\n",
      "        96, 16, 12, 73, 50, 63, 13, 47, 21, 17, 98, 39, 47,  5])\n",
      "345 torch.Size([32, 3, 32, 32]) tensor([73, 57, 52, 18, 72, 21, 76, 71, 20, 68, 47, 97, 22,  1,  2, 66, 22,  5,\n",
      "        67, 60, 86, 23,  3, 74, 93, 79, 71, 27, 21, 21, 41, 67])\n",
      "346 torch.Size([32, 3, 32, 32]) tensor([ 2, 99, 59, 60,  7, 44, 77, 36, 49, 13, 12, 71, 63, 33, 87, 42, 38, 77,\n",
      "        46, 72, 74, 76, 69,  9, 77, 45, 16, 79, 53,  7, 16, 63])\n",
      "347 torch.Size([32, 3, 32, 32]) tensor([22, 43, 45, 13, 32, 36, 71, 69, 47, 52, 41, 26,  1, 79,  4,  2, 74, 94,\n",
      "        92, 62, 59,  0, 99, 86, 48, 11, 25, 82,  4, 93, 91, 23])\n",
      "348 torch.Size([32, 3, 32, 32]) tensor([14, 52, 57, 93, 46, 27,  7, 22, 79, 38, 33,  2, 49, 30,  0, 33, 56,  6,\n",
      "        59, 81, 20, 48, 16, 94, 75,  4, 56, 88, 56, 37, 79, 14])\n",
      "349 torch.Size([32, 3, 32, 32]) tensor([36, 75, 56, 60, 53, 35, 99, 47, 63, 84, 81, 61, 74, 66, 61, 40, 60, 56,\n",
      "        55, 67, 14, 82, 57, 85, 70, 30, 10, 15,  9, 44, 82, 82])\n",
      "350 torch.Size([32, 3, 32, 32]) tensor([14,  6, 29, 12, 86, 73,  1, 73, 50, 63, 94, 43, 66,  4, 80, 53, 81, 32,\n",
      "        20, 19, 31, 72, 98, 78, 29, 29, 18, 47, 67, 29, 33, 31])\n",
      "351 torch.Size([32, 3, 32, 32]) tensor([56, 99, 26, 49,  5, 50, 40,  8, 21, 87, 95, 24, 36, 11, 98, 93, 91, 92,\n",
      "        95,  4, 71, 87, 98, 46, 14, 82, 83, 76, 97,  0, 24, 99])\n",
      "352 torch.Size([32, 3, 32, 32]) tensor([98, 23, 51, 70, 94, 53, 45, 69, 31, 95, 50, 32, 81, 64, 98, 81, 17, 87,\n",
      "        78, 82, 12,  0, 72, 58, 99, 46, 34, 78, 71, 18, 39, 95])\n",
      "353 torch.Size([32, 3, 32, 32]) tensor([90, 80, 55, 53, 71, 28, 92, 90,  8, 41, 55, 64, 63,  3, 12, 10, 36, 42,\n",
      "        90, 80, 17, 16,  0, 48, 97,  3, 97, 71, 30, 14, 91, 75])\n",
      "354 torch.Size([32, 3, 32, 32]) tensor([83, 72, 52, 44, 86, 56, 30, 53, 25, 14, 85, 88, 67, 48,  7, 74, 51, 65,\n",
      "        18, 53, 55, 56,  3, 59, 73, 51, 70,  7, 87, 41, 72, 64])\n",
      "355 torch.Size([32, 3, 32, 32]) tensor([37, 20, 73, 32,  2, 76, 44, 60, 81, 94, 72, 41, 17, 69, 10, 15, 68, 74,\n",
      "        97, 40, 11, 72, 89, 12, 94, 10, 17, 13, 24, 95, 63, 31])\n",
      "356 torch.Size([32, 3, 32, 32]) tensor([21, 12, 11, 35, 14, 77,  6, 91, 54, 87,  1, 78, 57, 23, 61, 37, 12, 62,\n",
      "        82, 53, 92, 55, 33, 18, 63, 64, 83, 80, 77, 65, 46, 52])\n",
      "357 torch.Size([32, 3, 32, 32]) tensor([32, 77, 99, 81, 21, 51, 64, 57,  0,  0, 33, 99,  8, 85, 71, 33, 85, 11,\n",
      "        62,  1, 92, 91, 63, 24, 68, 64, 23, 98, 99, 56, 82, 64])\n",
      "358 torch.Size([32, 3, 32, 32]) tensor([65,  8, 47, 97, 21, 10, 22, 49, 69, 24,  2, 66, 98, 56, 67, 62, 25, 39,\n",
      "        27, 40, 31, 11, 27, 74, 91, 71, 16, 95, 77, 78, 88, 86])\n",
      "359 torch.Size([32, 3, 32, 32]) tensor([38, 36, 65, 63, 60,  4, 78, 70, 23, 82, 28, 33, 90, 51, 46, 28, 35, 94,\n",
      "        44, 71, 64, 14,  2, 92, 24, 41, 54, 17,  6, 84, 79, 68])\n",
      "360 torch.Size([32, 3, 32, 32]) tensor([ 6, 62, 83, 38, 47, 14, 60, 16, 78, 10, 32, 61, 60,  1, 71, 33,  0, 87,\n",
      "        94, 51,  9, 12, 17, 31, 31, 38, 35, 19, 22, 13,  3, 22])\n",
      "361 torch.Size([32, 3, 32, 32]) tensor([11, 27, 59, 26, 90, 25, 97, 39, 21, 22,  6, 46, 64, 53, 43, 68, 53, 50,\n",
      "        57, 43, 76, 50, 56, 78, 79, 90, 13, 24, 33,  6, 42, 54])\n",
      "362 torch.Size([32, 3, 32, 32]) tensor([ 7, 24, 65, 97, 37, 28, 27, 21, 42, 90, 60, 58, 70, 42, 98, 48, 28,  7,\n",
      "        76, 47, 11, 84, 85, 42,  6, 12, 66, 35, 84, 35, 40, 22])\n",
      "363 torch.Size([32, 3, 32, 32]) tensor([71, 47, 89, 55, 62, 52, 95,  7, 54, 51, 85, 14, 56, 22, 62, 96, 69, 95,\n",
      "        89, 80, 76, 83, 73, 30, 91, 52, 90, 96, 58,  6, 98, 40])\n",
      "364 torch.Size([32, 3, 32, 32]) tensor([32, 91, 16, 73, 33, 13, 76, 99, 72, 58, 32, 67, 57, 36, 13, 66, 41, 25,\n",
      "        38, 64, 56, 91, 25,  0, 13, 23, 48, 18, 32, 55, 85, 83])\n",
      "365 torch.Size([32, 3, 32, 32]) tensor([62, 28, 76, 41, 55, 77, 74, 26, 68, 63, 91, 36, 59, 96,  2, 13,  7, 84,\n",
      "         9, 22, 16, 98, 48, 13, 79, 25, 61,  1, 82, 31, 69,  1])\n",
      "366 torch.Size([32, 3, 32, 32]) tensor([14, 81, 15, 33, 32, 11, 37, 52, 13, 32, 64, 33, 92, 72, 88, 11, 94, 93,\n",
      "        93, 37, 73, 36, 60,  4, 96, 87, 68, 93, 23, 95, 16, 58])\n",
      "367 torch.Size([32, 3, 32, 32]) tensor([94, 12,  5, 26, 24, 39, 96, 19, 11,  9, 41, 74, 42, 69, 93, 93, 53, 34,\n",
      "        14, 41, 89, 84, 84, 40, 91, 66, 15, 71, 71, 93, 50, 84])\n",
      "368 torch.Size([32, 3, 32, 32]) tensor([62, 60, 68,  2, 18, 37, 92, 72,  6, 90, 65, 25, 50,  1, 93, 98, 32, 93,\n",
      "        72, 43, 35, 10, 73, 43, 56, 82, 83, 84, 87, 21,  0, 18])\n",
      "369 torch.Size([32, 3, 32, 32]) tensor([72, 84, 82, 31, 97, 90, 42, 46, 60, 17, 99,  3, 71, 46, 73, 29, 61, 99,\n",
      "        86, 45,  3, 18, 37, 97, 15, 85, 61, 38, 43, 55, 96, 53])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "370 torch.Size([32, 3, 32, 32]) tensor([46, 99, 49, 92, 31, 41,  6, 34, 87, 54, 69, 62, 67, 49, 14, 84, 60, 13,\n",
      "        69, 20, 57, 98, 46, 59, 75, 96, 27, 65, 49, 55, 93, 14])\n",
      "371 torch.Size([32, 3, 32, 32]) tensor([71, 90, 75, 91, 99, 64, 52, 69, 67, 12,  6, 46,  9,  9, 15, 78, 51, 25,\n",
      "        57, 21, 82, 31, 88,  2, 93, 63, 64, 83, 73, 40, 25, 95])\n",
      "372 torch.Size([32, 3, 32, 32]) tensor([72, 46, 90, 73, 63, 83, 85, 36, 56, 85,  4, 70, 76, 54, 55, 75, 70, 17,\n",
      "        58, 42, 87, 55, 26, 70, 39, 87, 85, 31, 28, 45, 12, 63])\n",
      "373 torch.Size([32, 3, 32, 32]) tensor([74, 83, 53,  0, 35, 33, 97, 47, 89,  8, 45, 71, 38, 77, 37, 13, 35, 63,\n",
      "        99, 70, 52, 85,  1, 99, 44, 93, 50, 75, 17, 25,  9, 90])\n",
      "374 torch.Size([32, 3, 32, 32]) tensor([91, 48, 39, 55, 77, 49, 51, 24, 38, 21, 10,  7, 82, 16, 43, 35, 25, 75,\n",
      "        89, 64, 27, 44, 94, 48, 91,  8, 51, 79, 24, 68, 38, 53])\n",
      "375 torch.Size([32, 3, 32, 32]) tensor([52, 10, 51, 53, 40, 53, 44, 48, 86, 75, 13, 60, 80, 52, 69, 64, 58, 39,\n",
      "         6, 79, 43, 77, 41, 14, 75, 21, 99, 63, 12, 85, 28, 51])\n",
      "376 torch.Size([32, 3, 32, 32]) tensor([31, 61, 23, 17,  5, 57, 82, 49, 97, 23, 71, 15,  3, 65, 68, 16, 90,  9,\n",
      "        64, 56, 72, 30, 33, 92, 93, 13, 66, 82, 17, 68, 11, 53])\n",
      "377 torch.Size([32, 3, 32, 32]) tensor([60,  4, 16, 47, 76, 26, 24, 89, 19,  5, 56, 81, 90, 72,  2, 69, 76, 93,\n",
      "        37, 34,  3, 87, 40, 24, 50, 92, 25,  8, 87, 79, 97, 48])\n",
      "378 torch.Size([32, 3, 32, 32]) tensor([ 7, 18, 93, 49, 32, 68, 44, 44, 78, 53, 53, 67, 74, 50, 15, 23, 52, 94,\n",
      "        53, 96, 89, 67, 33, 67, 36, 60, 69, 96, 12, 45, 41, 58])\n",
      "379 torch.Size([32, 3, 32, 32]) tensor([49, 90, 97, 49, 58, 87, 51, 74, 38, 23, 59, 82, 71, 74, 21, 69, 57, 41,\n",
      "        68, 56,  2,  3, 20, 41, 97, 38, 80, 29, 18,  4, 64, 39])\n",
      "380 torch.Size([32, 3, 32, 32]) tensor([43, 55, 39, 14, 63, 85, 16, 57,  5, 19, 62, 28, 58, 48, 62, 27,  0, 16,\n",
      "        39, 67, 97, 22,  9, 72, 71, 26, 80, 50, 66, 70, 13,  2])\n",
      "381 torch.Size([32, 3, 32, 32]) tensor([41, 20, 66,  3, 45, 44, 77, 22, 33, 26, 16, 18,  9,  7, 88,  8, 31, 61,\n",
      "         0, 95, 75, 34, 55,  4, 57, 51, 69, 48, 21, 80, 76, 45])\n",
      "382 torch.Size([32, 3, 32, 32]) tensor([ 9, 80,  3, 78, 82, 33, 75, 91, 85, 97, 75, 90, 68, 45, 78, 40,  7, 70,\n",
      "        36, 92, 48, 22, 35,  8, 97, 98, 36, 69, 33,  1, 19, 79])\n",
      "383 torch.Size([32, 3, 32, 32]) tensor([56, 28, 93, 33, 73, 98, 66, 54, 12,  4, 96, 48, 80,  1, 70, 49, 27, 19,\n",
      "        53, 17, 57, 76, 72, 19, 82, 75, 38,  9, 93, 29,  3, 94])\n",
      "384 torch.Size([32, 3, 32, 32]) tensor([83, 53, 76, 61, 40, 17, 46, 92, 15, 97, 53, 96, 58, 10, 22, 21, 70, 75,\n",
      "        40,  1, 75, 93, 60, 37, 91, 31, 54, 18, 23, 42, 36, 72])\n",
      "385 torch.Size([32, 3, 32, 32]) tensor([19, 16, 45, 97, 67, 46, 54, 86, 31, 55,  9, 65, 22, 92, 99, 90,  8, 77,\n",
      "        72, 49, 17, 35, 89, 92,  1, 43, 25, 19, 56, 62,  0, 55])\n",
      "386 torch.Size([32, 3, 32, 32]) tensor([73,  7,  2, 62, 24, 53, 14, 94,  1,  0, 29, 71, 33, 41, 46, 86, 79, 74,\n",
      "        47, 18,  8, 50,  3,  9, 63, 22, 11, 28,  1, 20, 32, 24])\n",
      "387 torch.Size([32, 3, 32, 32]) tensor([53, 10, 30, 79,  7, 21, 46, 97, 72, 61, 57, 94, 47, 27,  0, 65, 57, 45,\n",
      "        86, 93, 20, 62, 85, 52, 48, 16, 26, 38, 13, 16,  6, 75])\n",
      "388 torch.Size([32, 3, 32, 32]) tensor([21, 52, 16, 78, 92,  0, 64, 84, 52, 31, 44, 41, 86, 26, 10, 98, 96,  9,\n",
      "        38, 79, 61, 16, 50, 56, 50,  1, 88, 39, 99,  8,  8, 32])\n",
      "389 torch.Size([32, 3, 32, 32]) tensor([21, 73, 27, 35, 18, 53, 54, 62,  2, 57, 75, 98,  0, 57, 85, 53, 24, 72,\n",
      "        52, 16, 44, 50, 21, 58, 24, 80, 60, 96,  3,  5, 91, 16])\n",
      "390 torch.Size([32, 3, 32, 32]) tensor([33, 97, 71, 15, 21, 79, 41, 57, 36, 53, 94, 72, 61, 72, 51, 81, 43, 41,\n",
      "        85, 23, 29, 29, 51, 83, 38, 61, 83, 37, 97, 83, 76, 41])\n",
      "391 torch.Size([32, 3, 32, 32]) tensor([50, 32, 12, 68, 38, 28, 49, 12, 63, 30,  7, 58, 23, 62, 12, 85, 39,  7,\n",
      "        52, 96, 29, 92, 40, 46, 98, 11, 68, 14, 20, 31, 31, 43])\n",
      "392 torch.Size([32, 3, 32, 32]) tensor([72, 42, 25, 98, 23, 39, 49, 41, 15, 66, 55, 68,  6, 94, 65, 27,  9, 83,\n",
      "        20, 10, 83, 60, 37, 55, 95, 87, 54, 84, 70,  0, 60, 60])\n",
      "393 torch.Size([32, 3, 32, 32]) tensor([91, 43, 33,  1, 50, 52, 18, 61, 92, 88, 64, 81, 65,  0,  5, 68, 83, 78,\n",
      "        16, 33, 81, 68, 36,  0, 48, 83, 11, 86, 75,  6, 97, 36])\n",
      "394 torch.Size([32, 3, 32, 32]) tensor([25, 92, 20, 66, 18, 51, 75, 83, 34, 52, 10, 77, 13, 79, 98, 81, 78, 24,\n",
      "        63, 77, 86, 71, 86, 49, 57, 71, 57, 86,  7, 24, 41, 61])\n",
      "395 torch.Size([32, 3, 32, 32]) tensor([68, 39, 15, 89, 94, 87, 57, 89, 48, 10, 89, 62, 67, 75, 40, 20, 78, 13,\n",
      "        75, 18, 95, 84, 66, 62, 35, 49, 85, 63,  2, 98, 18, 66])\n",
      "396 torch.Size([32, 3, 32, 32]) tensor([19, 48, 19, 45, 84, 65, 96, 12, 92, 75, 11,  7, 67, 52, 13,  2,  9, 74,\n",
      "        52, 28, 66, 12, 66, 99, 26, 67, 83, 46, 84, 98, 80, 90])\n",
      "397 torch.Size([32, 3, 32, 32]) tensor([58, 45, 38, 57, 61, 15, 91, 54, 33, 48, 42, 33, 12, 96, 22, 14,  1, 55,\n",
      "        17, 78, 79, 66, 42,  9, 29, 74, 35,  1, 14, 51, 34, 92])\n",
      "398 torch.Size([32, 3, 32, 32]) tensor([97, 42, 83, 16, 79, 73, 88, 63, 98, 28, 13, 78, 23, 44,  6, 50, 94, 23,\n",
      "        42, 45,  2, 63, 11,  0, 99, 71, 82, 96, 45, 63, 20, 15])\n",
      "399 torch.Size([32, 3, 32, 32]) tensor([ 0, 39, 29, 54, 66, 48, 22, 41, 48, 14, 99,  4, 14,  5, 38, 86, 36, 74,\n",
      "        45, 44, 45, 40, 84, 46, 61,  4, 23,  7, 84, 54, 29, 44])\n",
      "400 torch.Size([32, 3, 32, 32]) tensor([59,  5, 60, 73, 84, 73, 79, 21, 83, 63, 36, 33, 25, 16, 84, 91, 75, 32,\n",
      "        78, 93, 35, 62,  7, 26, 49,  1, 85, 32, 21, 30, 12, 42])\n",
      "401 torch.Size([32, 3, 32, 32]) tensor([56, 97, 99, 75,  8,  3, 48, 55, 59, 42, 53,  1, 99, 34, 43, 18, 81, 73,\n",
      "        71, 13, 10, 93, 43, 93, 68, 81, 13, 56, 83, 77,  8, 94])\n",
      "402 torch.Size([32, 3, 32, 32]) tensor([ 3, 81, 20, 66, 73, 36, 46, 11, 13, 28, 30, 39, 81, 81, 86, 38, 66, 45,\n",
      "        95, 91,  8, 15, 87, 32, 94, 30, 83, 99, 32, 81, 70, 67])\n",
      "403 torch.Size([32, 3, 32, 32]) tensor([57, 38, 63, 87, 25, 72, 72,  7, 27, 15, 82, 31, 84, 74, 26, 90, 37, 43,\n",
      "        26, 96, 74, 24, 83, 53, 56, 31, 94, 31, 92,  6, 89,  1])\n",
      "404 torch.Size([32, 3, 32, 32]) tensor([40, 92, 85, 13, 92,  5, 30, 97, 64, 58, 37, 86, 45,  9, 85, 25, 83, 57,\n",
      "        88, 49, 26, 24, 39, 93, 16, 72, 30, 90, 36, 78, 87, 89])\n",
      "405 torch.Size([32, 3, 32, 32]) tensor([ 9, 85, 99, 99, 91, 45, 10,  8,  2, 46, 86, 69, 57, 53, 20, 72, 70, 97,\n",
      "        46, 86, 87, 47, 64, 43, 48, 82,  5, 14, 76, 45, 30, 21])\n",
      "406 torch.Size([32, 3, 32, 32]) tensor([20, 50, 24, 97, 18, 98, 72, 25,  8, 36, 79, 61, 23, 11, 73, 13, 47, 83,\n",
      "        77, 74, 21,  9, 76, 99,  0, 63, 39, 24, 16,  5, 31, 57])\n",
      "407 torch.Size([32, 3, 32, 32]) tensor([19, 19, 87, 53, 42, 42, 94, 27, 13, 75, 68, 95,  6,  9, 77,  5, 86,  7,\n",
      "        24, 95, 46, 99, 62,  6, 51, 81, 43,  7, 83, 93, 45, 89])\n",
      "408 torch.Size([32, 3, 32, 32]) tensor([22, 83, 35, 43, 39, 20,  5,  9, 22, 63, 51, 46, 60, 48, 27, 82, 37, 56,\n",
      "         6, 57,  1, 48, 66, 53, 30, 46, 85, 34, 60, 79, 70, 32])\n",
      "409 torch.Size([32, 3, 32, 32]) tensor([41, 76, 47,  6, 69, 24,  3, 86, 71, 33,  7, 95, 75, 63,  4, 17, 53, 23,\n",
      "        62, 91,  7, 29, 99, 59, 76, 82, 24, 61, 10, 24, 64, 49])\n",
      "410 torch.Size([32, 3, 32, 32]) tensor([66, 80, 92, 82, 15, 95, 53, 89, 33, 49, 26, 79, 69, 60, 58, 23, 99, 76,\n",
      "        63, 79, 55, 29, 52, 38, 17,  5, 15,  1, 71, 39, 29, 42])\n",
      "411 torch.Size([32, 3, 32, 32]) tensor([90, 15, 32, 94, 24,  2, 67, 18, 39, 72, 69,  0, 71, 23, 26, 21, 69, 69,\n",
      "        66, 31, 64, 53, 79, 41, 43, 30,  7,  2, 43, 51,  1, 95])\n",
      "412 torch.Size([32, 3, 32, 32]) tensor([20, 78, 20, 51, 41, 29, 71, 36, 95, 36, 89, 11,  6, 28, 69, 38, 39, 92,\n",
      "        55, 13, 45, 46, 70, 30, 19, 66, 84, 81, 89, 14,  8, 61])\n",
      "413 torch.Size([32, 3, 32, 32]) tensor([97, 15, 58, 20, 71,  3, 37, 93, 66, 37, 80, 97, 61, 25, 16,  5, 12, 42,\n",
      "        55, 42,  7,  0, 86, 84, 62, 14, 74, 74, 81, 54,  9, 66])\n",
      "414 torch.Size([32, 3, 32, 32]) tensor([53, 64,  6, 34, 31, 96, 89, 97, 84, 11, 17, 21, 43, 36, 29, 33, 31, 86,\n",
      "        80, 89, 81, 22, 55, 12, 51, 18,  0,  8, 47, 19, 79, 93])\n",
      "415 torch.Size([32, 3, 32, 32]) tensor([60, 53, 35, 15, 31, 88, 96, 74, 85,  0,  3, 79, 27, 70, 36, 32, 30, 71,\n",
      "        52,  0, 33, 58, 82, 96, 38, 27, 58, 36, 91, 13, 40, 28])\n",
      "416 torch.Size([32, 3, 32, 32]) tensor([34, 21, 94, 89, 24,  7, 29, 56, 90, 26, 40, 29, 48, 59, 73, 88, 42, 40,\n",
      "        34, 86, 55, 14, 66, 72, 89, 52, 43, 41, 94, 11, 78, 90])\n",
      "417 torch.Size([32, 3, 32, 32]) tensor([43,  1, 95, 55, 94, 42,  4, 77, 61,  3,  1, 33, 30, 91, 74, 93, 16, 79,\n",
      "        10, 82, 13, 66, 40, 47,  8, 63, 13, 94, 61, 34, 30, 45])\n",
      "418 torch.Size([32, 3, 32, 32]) tensor([94, 98, 32, 18, 96, 51, 36, 11, 90, 22, 12, 45, 14,  6, 73, 45, 26, 14,\n",
      "        47, 18, 11, 33, 39,  0, 29, 82, 62, 39, 54, 74, 12, 55])\n",
      "419 torch.Size([32, 3, 32, 32]) tensor([86, 10, 78, 45, 80,  8, 18, 27,  4, 34,  9, 86, 49, 79, 33, 90, 17, 43,\n",
      "        23, 24, 33, 12, 50, 18, 84, 97, 20,  4, 62,  3, 47, 16])\n",
      "420 torch.Size([32, 3, 32, 32]) tensor([93, 84, 52, 47, 93, 85, 13, 37, 34, 25, 14, 24, 50, 76, 93, 60, 43, 60,\n",
      "        18, 77, 49, 70, 74, 55, 41, 42, 60, 28, 37, 15, 33, 82])\n",
      "421 torch.Size([32, 3, 32, 32]) tensor([39, 34, 60,  3, 39, 26, 67, 98, 10, 12, 90, 60, 76,  2, 92, 20,  1, 19,\n",
      "        35, 84, 60, 93, 58,  3, 69, 69, 64, 72, 81, 16, 14, 42])\n",
      "422 torch.Size([32, 3, 32, 32]) tensor([58, 89, 22, 34, 79, 96, 33, 14, 71, 75, 34, 31, 39, 28, 69, 97, 86, 47,\n",
      "        12, 87, 66, 29, 79,  1,  2, 83, 19, 90, 16, 57,  4, 98])\n",
      "423 torch.Size([32, 3, 32, 32]) tensor([ 7, 91, 14, 87, 13, 98, 82, 87, 24, 53, 96, 85, 85, 71, 46, 95, 19, 46,\n",
      "        25, 88,  6, 95,  7, 67, 98,  2, 77, 32, 64, 95, 65, 85])\n",
      "424 torch.Size([32, 3, 32, 32]) tensor([89, 67, 62, 77, 32, 84, 50, 61, 16, 27, 53, 76, 68, 97, 57, 14, 27, 31,\n",
      "        25, 92, 61, 84, 50, 53, 96, 79, 42, 24,  3, 34, 32, 66])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "425 torch.Size([32, 3, 32, 32]) tensor([24, 41, 95, 75, 77, 63, 67, 37, 71, 92,  9, 88, 50, 24, 43, 40, 14, 59,\n",
      "        76, 20,  1, 46, 97, 81, 10, 72,  0, 53, 37, 75, 56, 41])\n",
      "426 torch.Size([32, 3, 32, 32]) tensor([74, 61, 85, 32,  2, 77, 21, 14, 37, 13, 89, 62, 61, 43, 57, 18, 76, 58,\n",
      "        56,  1, 25, 68, 32, 53, 97,  8, 82, 72,  4, 37, 22, 92])\n",
      "427 torch.Size([32, 3, 32, 32]) tensor([68, 24, 22, 40, 80, 13, 11, 75, 21, 72, 59, 60, 39, 94, 33, 27, 30,  6,\n",
      "        99, 37, 96, 36, 23, 81, 26, 40, 52, 31, 12,  5, 10, 31])\n",
      "428 torch.Size([32, 3, 32, 32]) tensor([95, 55,  2, 99, 49, 44, 95, 88, 26, 37, 21, 42,  7, 17, 16, 91, 87, 90,\n",
      "        49,  1, 22, 70,  3,  3, 15, 97, 80, 98, 52, 79, 59, 84])\n",
      "429 torch.Size([32, 3, 32, 32]) tensor([12, 75,  1, 76, 30, 41, 42, 75, 40, 23, 31,  0, 28, 55, 10, 24, 93, 97,\n",
      "        52, 54, 68, 31, 63, 21, 79, 15, 46, 28, 49, 87, 45, 42])\n",
      "430 torch.Size([32, 3, 32, 32]) tensor([45, 75, 50,  4, 45, 23, 19, 93, 94, 53, 56, 92,  9, 47, 91, 10, 55,  2,\n",
      "        52, 22, 98, 56, 49, 14, 83, 59, 88,  8, 37, 46, 99, 25])\n",
      "431 torch.Size([32, 3, 32, 32]) tensor([38, 64, 54, 91, 75, 32, 32, 82, 48, 86, 36, 14, 71, 23, 34, 52, 62, 82,\n",
      "        39, 22, 44, 15, 13, 12,  7, 79, 92, 58, 48, 88,  9, 26])\n",
      "432 torch.Size([32, 3, 32, 32]) tensor([ 6, 74, 13, 56, 53, 27, 93, 64, 75, 79, 88, 23,  6, 10, 19, 59, 82, 36,\n",
      "        73,  4, 69, 70, 58,  3, 92, 66, 72, 89, 87, 35,  8, 71])\n",
      "433 torch.Size([32, 3, 32, 32]) tensor([61, 89, 32, 58, 83, 32, 74, 39,  1, 80, 64, 89,  8,  2, 55, 64, 43, 86,\n",
      "        32, 16, 67, 65, 93, 94,  8, 89, 90, 94, 16, 76, 74, 27])\n",
      "434 torch.Size([32, 3, 32, 32]) tensor([60, 54, 49, 17, 56, 86, 75, 86,  5, 67, 36, 12,  0, 54, 95, 99, 32, 28,\n",
      "        89, 62, 48,  5, 56, 27,  7, 61, 43, 26, 52,  8, 95, 26])\n",
      "435 torch.Size([32, 3, 32, 32]) tensor([99, 48, 87, 22, 46, 78,  2, 28, 76, 55, 42, 90, 66, 90, 60,  9, 19, 86,\n",
      "        41, 96, 27, 84, 57, 70, 11, 24, 13, 33, 12,  2, 15, 55])\n",
      "436 torch.Size([32, 3, 32, 32]) tensor([26, 13, 65, 63,  5, 11, 77, 22,  0, 83, 27, 69, 39, 26, 58, 48, 86, 12,\n",
      "        47, 96, 22,  8, 90,  4, 37,  7, 53, 31, 27, 59, 72, 75])\n",
      "437 torch.Size([32, 3, 32, 32]) tensor([89, 31, 91, 73, 51, 46, 46, 39, 15, 32, 39, 56, 59,  4, 28, 57, 81, 31,\n",
      "        92,  3, 29, 58, 84, 61, 90, 62, 49, 52, 48, 27, 51, 99])\n",
      "438 torch.Size([32, 3, 32, 32]) tensor([27, 43, 47, 52, 19, 79, 29, 27, 69, 91, 17, 70, 52, 76, 37,  9,  3, 92,\n",
      "        17, 66, 54, 53, 70, 59, 60,  5, 85, 36, 63, 65, 22, 17])\n",
      "439 torch.Size([32, 3, 32, 32]) tensor([73,  5, 67, 61, 74, 52, 94, 46, 38, 11, 77, 11, 78, 80, 28, 90, 44, 74,\n",
      "        16, 51, 40, 15, 31, 45, 78, 84, 20, 62, 97, 44, 11, 57])\n",
      "440 torch.Size([32, 3, 32, 32]) tensor([79, 68, 19, 56, 50, 19, 32, 57, 72, 52, 97, 44, 15, 90, 86, 18, 82,  6,\n",
      "        19, 67, 62, 30, 60, 92, 71, 67,  7, 81, 40,  6, 63, 22])\n",
      "441 torch.Size([32, 3, 32, 32]) tensor([ 0, 92, 46, 71, 39, 17, 30, 93, 18, 94, 97, 41, 84, 12, 17, 95, 59,  7,\n",
      "        94, 66, 56, 58, 27, 25, 33, 51, 23, 39, 69, 14, 25, 56])\n",
      "442 torch.Size([32, 3, 32, 32]) tensor([77, 48, 51, 33, 68, 72, 69, 12, 72, 81, 91, 73, 32, 56, 30, 47, 92,  7,\n",
      "        47, 66, 27, 95, 89, 55, 58, 93, 42, 50, 55, 16, 75, 45])\n",
      "443 torch.Size([32, 3, 32, 32]) tensor([94, 80, 18, 24, 33, 11, 65, 59, 32, 21, 98, 64, 74, 63, 33, 10, 23, 90,\n",
      "        82, 23,  1, 73, 43, 17, 43, 26, 72, 99, 51, 93, 19, 54])\n",
      "444 torch.Size([32, 3, 32, 32]) tensor([35, 93,  1, 35, 34, 52, 77, 54, 76, 89, 20,  8, 32, 17, 20, 11, 12, 22,\n",
      "        14, 66, 14, 27, 75, 11, 82,  1, 26, 44, 46, 44, 82, 61])\n",
      "445 torch.Size([32, 3, 32, 32]) tensor([84,  9, 92, 13, 57, 77, 53, 62, 21, 57, 43, 29, 87,  4, 27, 48, 75, 62,\n",
      "        38, 35, 13, 88, 95,  8, 27, 64, 51, 35, 78,  8, 52, 90])\n",
      "446 torch.Size([32, 3, 32, 32]) tensor([29, 62, 23, 29, 52, 61, 80, 54, 19, 69,  5, 11, 99, 15,  4, 29, 54, 51,\n",
      "        21,  8, 61, 84, 86, 22, 51, 29, 34, 45, 73, 16, 98, 31])\n",
      "447 torch.Size([32, 3, 32, 32]) tensor([26, 56, 19, 30, 70, 27, 20, 54, 69, 49, 15, 55, 35, 58, 98, 98, 52, 21,\n",
      "        52, 32, 56, 62, 15, 23, 88,  4, 43, 58, 69, 75, 87, 88])\n",
      "448 torch.Size([32, 3, 32, 32]) tensor([98, 93, 28, 47, 93, 72, 29, 73, 72,  5,  1, 50, 54, 79, 14, 13, 39, 26,\n",
      "        41, 64, 43,  9,  7, 41, 87, 33, 28, 42, 85, 47, 60, 13])\n",
      "449 torch.Size([32, 3, 32, 32]) tensor([59, 82, 74, 65, 28, 31, 63, 43, 67, 98, 96,  1, 81, 78, 60,  6, 74,  4,\n",
      "        14, 84, 93, 35, 79,  7, 18, 88, 49, 32, 13, 50, 34, 68])\n",
      "450 torch.Size([32, 3, 32, 32]) tensor([11, 97, 79, 80, 82, 31, 87, 21, 76, 21, 39, 25, 98, 62, 77, 31, 82, 49,\n",
      "        18, 29, 85, 83, 43, 51,  3, 47,  1, 31, 54,  6, 62, 18])\n",
      "451 torch.Size([32, 3, 32, 32]) tensor([54, 91, 51, 72, 62, 40, 57, 79, 64, 57,  6, 47, 96, 39, 33, 32, 66, 26,\n",
      "        22, 58, 91, 98, 63, 79, 46, 82, 84, 91, 95, 44, 67, 19])\n",
      "452 torch.Size([32, 3, 32, 32]) tensor([ 8, 66, 81, 31, 36, 60, 22, 42,  8, 71, 31, 11, 32, 76,  9,  9, 71, 72,\n",
      "        73, 47, 75, 50, 21, 30, 94, 11, 14, 24, 28, 58, 57, 81])\n",
      "453 torch.Size([32, 3, 32, 32]) tensor([16, 81, 84, 69, 20, 79, 43, 39, 62, 40, 71, 10, 70, 64, 16, 94, 97, 24,\n",
      "        91, 26, 31, 53, 46, 93, 43, 81, 30, 17, 97, 89, 79, 45])\n",
      "454 torch.Size([32, 3, 32, 32]) tensor([71, 59, 39, 75, 91,  9, 24, 94, 56, 54, 23, 44, 75, 82, 73, 31, 32, 84,\n",
      "        16, 38, 13,  5, 58, 17, 48,  8, 57, 69, 99, 93, 54, 98])\n",
      "455 torch.Size([32, 3, 32, 32]) tensor([ 0, 28,  0, 40, 97, 86,  0,  3, 39,  2, 79, 44, 28, 87, 86, 26,  6, 53,\n",
      "        65, 95, 95, 77, 56, 35, 39, 57, 48, 49, 86, 80, 99, 88])\n",
      "456 torch.Size([32, 3, 32, 32]) tensor([ 1, 54, 39, 99, 67, 89, 85, 85, 42, 10,  0, 16, 51, 80, 70, 61, 41, 23,\n",
      "         6,  1, 47, 44, 49, 53, 71, 47, 10, 37, 92,  4,  5, 22])\n",
      "457 torch.Size([32, 3, 32, 32]) tensor([27, 33, 38, 96,  2, 12, 86, 25, 64, 61, 49, 24, 28, 59, 19, 60, 58, 26,\n",
      "        71, 10, 25, 86, 72, 73, 25, 82, 23, 26, 99, 74, 39, 48])\n",
      "458 torch.Size([32, 3, 32, 32]) tensor([72, 35, 37, 37,  2, 54, 87, 33, 21, 39, 72, 41, 39, 94, 33, 40,  6,  3,\n",
      "        40,  6, 74, 86, 87, 28, 32, 89, 99, 27, 18, 71, 71, 83])\n",
      "459 torch.Size([32, 3, 32, 32]) tensor([35, 87, 66, 14, 16, 39, 64, 92, 72, 63, 50, 59, 66, 60, 94, 18, 17, 62,\n",
      "        29, 45, 48,  4,  7, 54, 82, 82, 85, 16, 21, 95, 35, 15])\n",
      "460 torch.Size([32, 3, 32, 32]) tensor([85,  9, 22, 30, 52, 35, 66, 23, 24, 85, 99,  1, 30, 20, 12, 92, 67, 36,\n",
      "         7, 72, 65, 88, 24, 29, 23,  6, 12, 67,  1, 49, 97, 87])\n",
      "461 torch.Size([32, 3, 32, 32]) tensor([ 6, 74, 83, 33, 22, 52, 81, 93, 24, 14, 68,  6, 53, 46,  0, 83, 37, 89,\n",
      "        49, 59, 16, 20, 24, 84, 40, 81, 68, 62, 91, 57, 47, 11])\n",
      "462 torch.Size([32, 3, 32, 32]) tensor([61, 63, 25, 69, 74,  2, 46, 75, 88, 62, 85, 21, 41, 11,  3, 95, 46,  1,\n",
      "        94, 51, 89, 26, 52, 11, 94, 20, 60,  0, 54, 52, 82, 56])\n",
      "463 torch.Size([32, 3, 32, 32]) tensor([66, 73, 32, 63, 29, 35, 30, 55, 24, 94, 50, 32, 58, 55, 40, 54, 53, 31,\n",
      "        66, 27, 76,  4, 99, 37,  5, 30, 48, 58, 51, 40, 65, 15])\n",
      "464 torch.Size([32, 3, 32, 32]) tensor([69, 34, 39, 60, 53, 90, 60, 91,  2, 93, 50, 14, 91, 80, 41, 49,  3, 30,\n",
      "        31,  2, 68, 63, 45, 33, 59, 48, 18, 69, 55, 36, 70,  6])\n",
      "465 torch.Size([32, 3, 32, 32]) tensor([32, 54,  9, 23,  4, 42, 11, 86, 32, 78, 79, 84, 90, 95, 39,  6, 42, 36,\n",
      "        27, 83, 70, 60,  1, 83, 61, 46,  4,  9,  0, 41,  7, 10])\n",
      "466 torch.Size([32, 3, 32, 32]) tensor([53, 73, 76, 15, 16, 76, 63,  5, 10, 35, 31, 33, 91, 25, 52, 22, 83, 63,\n",
      "        64, 46, 15,  1, 60, 99, 90, 85, 72, 62, 41, 94, 16, 16])\n",
      "467 torch.Size([32, 3, 32, 32]) tensor([72, 81, 29, 95, 55, 51, 54, 58,  4, 85, 23, 77, 10, 34,  0, 28, 24, 71,\n",
      "         1, 25, 37, 34, 48, 78, 70,  7, 18, 15, 84, 25, 50,  7])\n",
      "468 torch.Size([32, 3, 32, 32]) tensor([74, 32, 53,  8, 98, 94, 38, 10, 14,  3, 84, 81, 53, 79, 60, 15, 13,  8,\n",
      "        30, 29, 31, 24, 76, 27, 59, 81, 42, 87, 90, 69, 92, 78])\n",
      "469 torch.Size([32, 3, 32, 32]) tensor([ 9,  0, 28, 68, 10, 54, 74, 72, 28, 24, 41,  7, 23, 43, 47, 77, 10, 70,\n",
      "        20,  0,  5, 85, 86, 67, 34, 83,  1, 50,  4, 81, 35, 78])\n",
      "470 torch.Size([32, 3, 32, 32]) tensor([88, 83, 68, 28,  1, 54, 87, 98, 10, 42, 88, 76, 22, 69, 97,  5, 18, 82,\n",
      "        81, 85, 14, 85, 15, 50, 66, 65, 11, 18, 26,  0, 87, 30])\n",
      "471 torch.Size([32, 3, 32, 32]) tensor([65, 60, 55, 89, 82, 33, 85, 19, 84, 13,  2,  1, 53, 15, 88, 63, 59,  7,\n",
      "        22, 24,  7, 23, 71, 31, 41, 82, 87,  4, 27, 89, 92, 22])\n",
      "472 torch.Size([32, 3, 32, 32]) tensor([40, 82, 99, 94, 41, 80, 13, 76, 34, 83, 29, 42, 49, 13, 28, 61, 65, 99,\n",
      "        22, 16, 41, 37,  6, 14, 36, 48,  0,  7, 74, 29, 57, 69])\n",
      "473 torch.Size([32, 3, 32, 32]) tensor([68, 30,  2,  5, 83, 70, 40, 70,  1, 82, 74, 95, 35, 12, 49, 88, 82, 11,\n",
      "        15, 20, 99, 48, 83, 49, 19, 13, 14, 49, 85, 27, 68,  3])\n",
      "474 torch.Size([32, 3, 32, 32]) tensor([89, 15, 43, 27, 60, 11, 17, 67, 64, 19, 77, 91, 11, 49, 49, 50, 78, 97,\n",
      "        78, 27, 33,  0, 80,  7, 18, 16, 96, 16, 39, 93, 37, 80])\n",
      "475 torch.Size([32, 3, 32, 32]) tensor([12, 71, 30, 94, 46, 47, 68, 88, 86, 50, 71, 79, 60, 29, 22, 61, 72, 34,\n",
      "        47, 72, 27, 14, 13, 18, 75, 74, 10,  4, 36, 93, 18, 82])\n",
      "476 torch.Size([32, 3, 32, 32]) tensor([77, 89, 78, 66, 32, 88,  5, 92, 72, 70, 15, 66, 96, 50, 39, 37, 10, 82,\n",
      "        92, 62, 35, 78,  6, 20, 11, 90, 87, 36, 54, 69, 29, 90])\n",
      "477 torch.Size([32, 3, 32, 32]) tensor([96, 77, 46, 25, 14, 16, 69, 22, 95, 98, 48, 27, 65, 49, 43, 53, 19, 26,\n",
      "        23, 36, 35, 22,  8, 68, 71, 71, 36,  9, 49, 99, 20,  0])\n",
      "478 torch.Size([32, 3, 32, 32]) tensor([99, 64, 90,  1,  3, 79, 74, 80, 48,  7, 74, 86, 26,  2, 27, 58,  1, 59,\n",
      "        13, 72, 23, 44, 29, 54, 99, 31, 38, 33, 45, 93, 72, 29])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "479 torch.Size([32, 3, 32, 32]) tensor([71, 70, 23, 35, 23,  2, 81, 19, 22, 51, 83, 54, 62, 91, 73, 29, 28, 70,\n",
      "        13, 30, 45, 14, 56, 22, 71, 38, 65,  2, 30, 81, 62, 79])\n",
      "480 torch.Size([32, 3, 32, 32]) tensor([98, 46, 44, 47, 90, 54,  2, 21, 16, 70, 95, 13, 75, 62, 83, 64, 28, 50,\n",
      "        57, 38, 81, 35, 64, 29, 45, 87, 47, 77, 79, 99,  8, 58])\n",
      "481 torch.Size([32, 3, 32, 32]) tensor([41, 51, 41,  2, 93, 54, 22, 19,  3, 98, 12, 75, 16, 61, 57, 59, 56, 23,\n",
      "        64, 63, 25, 28, 42, 88, 74, 14, 23,  3, 22,  2,  3, 18])\n",
      "482 torch.Size([32, 3, 32, 32]) tensor([81, 85, 94, 53, 71, 62, 95, 90, 32, 80, 76, 72, 13, 53,  9, 75, 11, 27,\n",
      "        62, 26, 53, 49, 54, 29,  9,  3,  0, 67, 25, 45, 31, 95])\n",
      "483 torch.Size([32, 3, 32, 32]) tensor([45, 96, 20, 95, 40, 90, 11, 13, 69, 81, 43, 97, 38, 70, 97, 97,  6, 68,\n",
      "        46, 70, 28, 27, 37, 25, 51, 13, 10, 64, 95, 10,  5,  4])\n",
      "484 torch.Size([32, 3, 32, 32]) tensor([ 6, 62, 69, 94, 54, 49, 80, 23, 98, 76, 13,  0, 15, 15, 11, 25,  2,  3,\n",
      "        28,  9, 92, 46, 53, 53, 39, 22, 63, 91, 83, 85, 68, 40])\n",
      "485 torch.Size([32, 3, 32, 32]) tensor([83, 99, 93, 65, 24, 55, 44, 53, 67, 12, 27, 78, 76, 40,  1, 60, 64, 62,\n",
      "        67, 69, 92, 49, 57, 31,  8, 68, 48, 89,  1, 68, 26, 80])\n",
      "486 torch.Size([32, 3, 32, 32]) tensor([13, 41, 28, 48,  6, 32, 48, 45, 21, 79, 92, 28, 14, 19, 94, 49, 24,  0,\n",
      "        40, 86, 74, 86,  7, 52, 29, 58, 81, 25, 42, 71, 77, 30])\n",
      "487 torch.Size([32, 3, 32, 32]) tensor([29, 24, 96, 49, 34, 22, 64, 68, 46,  0, 17, 14, 41, 83, 68, 39, 11, 94,\n",
      "        65, 95, 87, 14, 48, 18, 67, 68, 44, 30, 14, 84, 34, 37])\n",
      "488 torch.Size([32, 3, 32, 32]) tensor([41, 99, 44, 82,  9, 15, 38, 59, 61, 17, 64, 18, 14, 65, 88, 61, 47, 46,\n",
      "        54, 89, 21, 93, 91, 37, 99, 18, 32, 26, 68, 57, 21, 68])\n",
      "489 torch.Size([32, 3, 32, 32]) tensor([92, 18, 65,  1,  8, 46, 19, 40, 83, 74, 81, 42, 73, 87, 20, 11, 54, 97,\n",
      "        60,  3, 67, 56, 41,  8, 30, 87, 57, 60, 65, 88, 22, 94])\n",
      "490 torch.Size([32, 3, 32, 32]) tensor([71, 77, 18, 16, 99, 69, 18, 21, 77, 76, 57, 62, 78, 88, 97, 91,  7, 91,\n",
      "        35, 47, 97, 81, 97, 92, 97, 88,  4, 47, 35, 84, 72, 52])\n",
      "491 torch.Size([32, 3, 32, 32]) tensor([27, 49, 50, 58, 12, 24, 99,  2, 36, 20, 45,  3, 88, 47, 62, 65, 55, 69,\n",
      "        63, 25, 93,  8, 68, 72, 85, 69, 26,  2, 61, 65, 57, 12])\n",
      "492 torch.Size([32, 3, 32, 32]) tensor([53, 31, 10,  5,  0, 72, 51, 61, 11, 63, 70, 23, 32, 65, 96,  1, 74, 84,\n",
      "         1, 92,  4, 31, 48, 40, 53, 64, 71, 72, 70, 85, 36, 84])\n",
      "493 torch.Size([32, 3, 32, 32]) tensor([94, 10, 22, 47, 94, 87,  9, 63,  1, 27,  0, 54, 25, 42, 92, 25,  8, 86,\n",
      "        38, 17, 74, 10, 52, 18, 76,  9, 68, 90,  1, 76, 28, 78])\n",
      "494 torch.Size([32, 3, 32, 32]) tensor([35, 98, 71, 39, 52, 43, 35, 91, 95, 40, 61, 96, 21, 18, 88, 73, 93, 84,\n",
      "        93, 59, 21, 41, 21, 14, 73, 57, 35,  2, 51, 20, 22, 59])\n",
      "495 torch.Size([32, 3, 32, 32]) tensor([61, 25,  7, 96, 54, 37, 58, 92, 83,  7, 19, 78, 73, 50, 50,  1,  8, 55,\n",
      "        57, 37, 45, 13, 58,  5, 48, 15, 47, 25, 92, 87, 18, 95])\n",
      "496 torch.Size([32, 3, 32, 32]) tensor([17, 69, 87, 41, 98, 95, 19, 99, 19, 96, 17, 51, 84, 12, 56, 44, 90, 85,\n",
      "        11, 71, 56, 40, 21, 35, 40, 32,  8, 78, 52, 91, 19, 14])\n",
      "497 torch.Size([32, 3, 32, 32]) tensor([11,  1, 11, 43, 74, 62, 22, 94, 85, 37, 25, 93, 40, 30, 52, 53, 16,  5,\n",
      "        42, 79, 62, 97, 87, 90, 68, 13, 13, 23, 14, 45, 63, 30])\n",
      "498 torch.Size([32, 3, 32, 32]) tensor([38,  0, 33, 34,  4, 35, 74, 44, 16, 36, 39, 31,  0, 73, 39, 68, 52, 59,\n",
      "        78, 58, 66, 19, 48, 14, 71, 87, 40, 61, 53, 77, 28, 36])\n",
      "499 torch.Size([32, 3, 32, 32]) tensor([87, 73, 31, 31, 73, 11, 23, 50, 48, 44, 26, 44, 60, 82, 70, 96, 79, 20,\n",
      "        71, 11, 53, 99, 40, 37, 14, 59, 18, 20, 38, 12, 40, 82])\n",
      "500 torch.Size([32, 3, 32, 32]) tensor([45, 25,  6, 66, 56, 58, 68, 35, 80, 39, 93, 63,  0, 60, 13, 69,  6, 71,\n",
      "        81, 68, 25, 76, 88, 41, 77, 98, 65,  4,  3, 44, 42, 54])\n",
      "501 torch.Size([32, 3, 32, 32]) tensor([69, 80, 31, 34, 65, 67, 31, 26, 16, 89, 81, 58, 78, 86, 29, 50, 50, 96,\n",
      "         2,  5,  6, 79,  1, 86, 47, 80, 28, 56, 96, 65, 39, 91])\n",
      "502 torch.Size([32, 3, 32, 32]) tensor([47, 77, 17, 34, 39, 25, 91, 13, 11, 42, 59, 89, 82, 10, 35, 79, 13, 28,\n",
      "        26,  1, 61,  0, 71, 96, 74, 72, 77, 43, 14, 37, 38, 16])\n",
      "503 torch.Size([32, 3, 32, 32]) tensor([ 5, 47, 82, 35, 41, 11, 19, 29,  0, 23, 54, 59, 13, 91, 74, 15, 30, 55,\n",
      "         5, 34, 59, 67,  9, 45, 48, 86, 28, 80, 31, 36, 34, 51])\n",
      "504 torch.Size([32, 3, 32, 32]) tensor([35, 73, 51,  5, 27, 16, 26, 89, 31, 75, 85, 43, 63, 41,  5,  5, 88, 75,\n",
      "        17, 22, 85, 76, 37, 58,  5, 32, 22, 43, 49, 61, 23, 39])\n",
      "505 torch.Size([32, 3, 32, 32]) tensor([64, 84, 74, 88, 93, 52, 57,  5, 92, 47, 30, 81, 12, 69, 29, 74, 80, 58,\n",
      "        53, 78, 60,  8, 87, 28, 53, 12,  4, 27, 53, 78, 53, 98])\n",
      "506 torch.Size([32, 3, 32, 32]) tensor([15, 99, 43, 55, 18, 27, 47, 69, 84, 60,  2, 65, 88,  2, 61,  9, 35, 67,\n",
      "         5, 95, 92, 10, 34,  2,  4, 60, 82, 19, 69, 17, 23, 33])\n",
      "507 torch.Size([32, 3, 32, 32]) tensor([56, 72,  9, 60, 49, 76, 39, 26, 48,  3, 18, 27, 81, 96, 56, 30, 49, 61,\n",
      "        51, 34, 53, 42,  2, 28,  6, 46, 20, 65, 72, 53, 64, 56])\n",
      "508 torch.Size([32, 3, 32, 32]) tensor([90, 51, 58, 85, 98, 99, 29, 28, 83,  2, 71, 54, 45, 25, 29, 37, 78, 74,\n",
      "        57,  0, 46, 51, 50, 94, 43,  4, 33, 25, 63, 21, 24,  0])\n",
      "509 torch.Size([32, 3, 32, 32]) tensor([53, 64, 55, 99, 51, 67, 93, 36, 91, 71, 19,  4, 70, 55, 49, 55, 47, 72,\n",
      "        56, 32, 97, 80,  5, 29, 76,  7, 23, 68, 38, 61, 23, 70])\n",
      "510 torch.Size([32, 3, 32, 32]) tensor([94, 48, 17, 49, 80, 47, 95, 75, 25, 31,  2, 55, 26,  1, 55, 17, 38, 47,\n",
      "         7, 77, 76, 46, 73, 39, 63, 86, 48,  4,  5, 28, 51, 85])\n",
      "511 torch.Size([32, 3, 32, 32]) tensor([26, 80, 24, 80, 11, 26, 33, 36, 35, 46, 61, 24, 73,  9, 44, 81, 52, 40,\n",
      "        94, 95, 15, 67, 77, 63, 89, 89, 29, 19, 19, 89, 21, 62])\n",
      "512 torch.Size([32, 3, 32, 32]) tensor([79, 55, 36, 57,  3, 93, 98, 32, 19, 98, 84, 72, 18, 82, 56, 81, 10, 74,\n",
      "        51, 50,  8, 13, 26, 29, 94,  5, 67, 73, 24, 65, 77, 92])\n",
      "513 torch.Size([32, 3, 32, 32]) tensor([ 0, 84, 85, 80, 67, 99, 28, 62, 59, 58, 63, 54, 38, 38, 59, 22, 76, 69,\n",
      "        13, 95, 86, 84, 73, 64, 69, 70, 42, 95, 80, 22, 37, 46])\n",
      "514 torch.Size([32, 3, 32, 32]) tensor([36, 21, 41, 22, 52, 58, 54, 38, 90, 33, 88, 96, 84, 44, 11, 87, 85, 23,\n",
      "        68, 20, 64, 20, 14,  8, 86, 96,  0, 45, 90, 84, 12, 59])\n",
      "515 torch.Size([32, 3, 32, 32]) tensor([93, 26, 13, 19, 64, 29, 39,  0, 81, 95, 69, 48, 64, 60, 55, 20, 31, 42,\n",
      "        42, 37, 10, 67,  1, 43, 28, 39, 13, 68, 40,  1, 64, 15])\n",
      "516 torch.Size([32, 3, 32, 32]) tensor([82,  8, 41, 50, 26, 82, 32, 76, 71, 46, 85, 87, 18, 58, 59,  6, 79, 73,\n",
      "         0, 11, 71, 94, 73, 95, 67, 48, 39, 43, 62, 66, 51, 36])\n",
      "517 torch.Size([32, 3, 32, 32]) tensor([41, 77, 19, 11, 24, 99, 12, 82, 50, 14, 54, 22,  6, 99, 26, 18, 40, 85,\n",
      "        73, 10, 31, 24, 23,  9, 18, 56, 84, 50, 86, 15, 81, 26])\n",
      "518 torch.Size([32, 3, 32, 32]) tensor([50, 69, 71, 63, 20, 75,  7,  8, 90, 89, 93,  1, 46,  3, 73, 17, 83, 49,\n",
      "        26, 57, 94, 39, 71, 16,  0, 41, 45, 98, 80, 83, 99,  1])\n",
      "519 torch.Size([32, 3, 32, 32]) tensor([80, 89, 20, 56, 83, 47, 64, 28, 16, 34,  2,  2, 96, 83, 44, 77, 18, 71,\n",
      "         4, 99, 53,  5, 76, 90, 34, 20, 83, 84, 75, 56, 62, 99])\n",
      "520 torch.Size([32, 3, 32, 32]) tensor([93, 27, 97, 27, 58, 90, 42, 17, 87, 10, 63, 50,  9, 42, 87, 85,  1, 37,\n",
      "        90, 63, 50, 79,  3, 98, 69, 43, 50, 91, 94, 47, 12, 96])\n",
      "521 torch.Size([32, 3, 32, 32]) tensor([19, 42, 48, 23, 10, 58, 73, 92, 40, 21, 57, 64, 12, 83, 12, 58, 84, 76,\n",
      "         9, 38, 60, 53, 80, 14, 88, 18, 12, 57, 26, 52, 44,  4])\n",
      "522 torch.Size([32, 3, 32, 32]) tensor([54, 83, 51, 94, 58, 20,  6, 45, 50, 86, 48, 87, 47, 82, 68, 62, 83, 74,\n",
      "        77, 34, 99,  5, 17, 81, 91, 81, 50, 84, 73, 68,  2, 22])\n",
      "523 torch.Size([32, 3, 32, 32]) tensor([10,  9, 39, 93,  9, 90, 77, 99, 81,  4, 55, 73,  9, 37, 22, 71, 99, 72,\n",
      "        11, 50, 39, 27, 24, 45, 85,  9,  1, 69, 63, 93, 54,  6])\n",
      "524 torch.Size([32, 3, 32, 32]) tensor([29, 68, 89, 70, 71, 79, 93, 35, 74, 72, 93, 59, 10, 43, 21,  9, 50, 15,\n",
      "        41, 65, 47, 39, 66, 42, 55,  8, 78, 44,  3, 79, 44, 78])\n",
      "525 torch.Size([32, 3, 32, 32]) tensor([77, 28, 87, 25, 69, 25, 12, 51, 95, 36, 58, 18, 47, 92, 68, 64, 90, 26,\n",
      "        17, 27,  0, 75, 37, 78, 28, 83, 11, 38, 38, 23, 55, 34])\n",
      "526 torch.Size([32, 3, 32, 32]) tensor([61, 75,  3, 59, 72, 48, 16, 95, 98, 53, 43, 35, 84, 64, 90,  4, 30,  8,\n",
      "        53, 99,  1, 57, 96, 55, 62, 82, 75, 50, 17, 97, 39, 52])\n",
      "527 torch.Size([32, 3, 32, 32]) tensor([90, 49, 42, 69, 37, 12, 78, 70, 29, 33, 26, 40, 62, 36, 49, 55,  5, 30,\n",
      "        44,  6,  6, 28, 63, 86, 47,  1, 44, 56, 85, 89, 65, 11])\n",
      "528 torch.Size([32, 3, 32, 32]) tensor([54, 67, 79,  7, 49, 76, 16, 51, 93, 51, 45, 83, 16, 28, 90, 94, 24, 24,\n",
      "        19, 28, 44, 57, 74, 34, 98, 48, 17, 80, 28, 29, 60, 99])\n",
      "529 torch.Size([32, 3, 32, 32]) tensor([84, 36, 20, 68, 40, 56, 11, 69, 59,  6, 32, 50, 73, 86, 34, 87, 97, 59,\n",
      "        59, 47, 41, 28,  0, 12, 24, 31, 66, 32, 74, 63, 44, 83])\n",
      "530 torch.Size([32, 3, 32, 32]) tensor([21,  8,  2, 87, 85, 80, 95, 23, 77, 88, 79, 26, 62, 43, 17, 25, 40, 16,\n",
      "        50, 52, 44, 29, 91, 21, 62, 26, 98, 54, 34, 28,  3, 29])\n",
      "531 torch.Size([32, 3, 32, 32]) tensor([95, 67, 52, 77, 65, 17, 79, 83, 23, 34,  9, 41, 45, 29, 87, 29, 21, 57,\n",
      "        38, 65, 72, 64, 19, 42,  2, 52, 86, 57, 92, 64, 90, 29])\n",
      "532 torch.Size([32, 3, 32, 32]) tensor([40, 88, 24, 72, 20, 38, 75, 34,  0, 36, 16, 79, 92, 14, 45, 18, 54, 31,\n",
      "        86, 55, 42,  1, 74, 15,  6, 74, 11, 39, 78, 22, 72, 45])\n",
      "533 torch.Size([32, 3, 32, 32]) tensor([86,  7, 44, 34, 42, 93, 68,  5, 93, 44, 34, 84, 25, 34, 92, 96,  9,  4,\n",
      "        60, 59, 42, 32, 44, 47, 30, 78, 13, 33, 88, 42, 60, 34])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "534 torch.Size([32, 3, 32, 32]) tensor([96, 28, 42, 24, 49, 18, 81, 55, 11, 67, 30, 60, 95, 15, 21, 97, 17, 57,\n",
      "        39, 25, 60,  2, 96, 43, 63, 12, 78, 24, 90, 75, 40, 67])\n",
      "535 torch.Size([32, 3, 32, 32]) tensor([63, 84, 80, 91, 49, 31, 68, 32, 47, 21, 53, 80, 87, 13, 92, 58, 74, 87,\n",
      "        39, 23, 80, 44, 53, 19, 16,  7, 26, 62,  5,  6, 57, 16])\n",
      "536 torch.Size([32, 3, 32, 32]) tensor([57, 50, 68, 83, 60, 26, 39, 20, 87, 53, 31, 19, 49, 84, 81, 90, 32, 36,\n",
      "        78, 98, 75, 73, 53, 86, 84, 82, 35, 13, 44, 82, 79, 69])\n",
      "537 torch.Size([32, 3, 32, 32]) tensor([30, 99, 10, 72,  9, 81, 77, 80, 97, 72, 39, 66, 84,  6, 67,  1, 16, 34,\n",
      "        18, 98, 42, 52, 74, 78, 56, 68, 72, 74, 19, 37, 44, 55])\n",
      "538 torch.Size([32, 3, 32, 32]) tensor([16, 63, 40, 10, 53,  1, 27, 68, 77, 35, 61, 51, 65, 13, 78, 78, 90, 85,\n",
      "        53,  1, 39, 94, 70, 46, 54, 35, 82, 26, 87,  9, 40, 86])\n",
      "539 torch.Size([32, 3, 32, 32]) tensor([96,  6, 55, 99, 11, 24, 95, 76,  1, 11, 50,  7, 70, 40, 32, 46, 57, 77,\n",
      "        95, 22, 67, 96, 63, 17,  4, 43,  2, 37, 50, 22, 24, 55])\n",
      "540 torch.Size([32, 3, 32, 32]) tensor([30, 34, 15, 43, 47, 18, 17, 95, 32, 38, 94,  7, 55, 78, 20, 63, 89,  8,\n",
      "        44, 96, 78, 48, 54, 27, 78, 20, 51, 72, 13, 93, 15, 62])\n",
      "541 torch.Size([32, 3, 32, 32]) tensor([60, 45, 56, 85, 87, 69, 67, 15, 26, 75, 31, 28, 90, 84, 59, 84, 60, 62,\n",
      "        55, 24, 76, 54,  3, 28, 77, 71, 41, 31, 26, 49, 64, 38])\n",
      "542 torch.Size([32, 3, 32, 32]) tensor([58,  9, 68, 72, 72, 98,  1, 16, 66,  5, 71, 45, 36, 42, 70, 20, 38, 71,\n",
      "        60, 18, 20, 37, 93, 90, 17,  7, 60, 60, 12, 16, 81, 78])\n",
      "543 torch.Size([32, 3, 32, 32]) tensor([37, 62, 11, 13, 35, 70, 31, 62, 39, 77, 29,  4, 22, 23,  3, 30, 73,  5,\n",
      "        70, 68, 98, 93, 79, 24, 80, 67,  0, 17, 85, 49, 94, 41])\n",
      "544 torch.Size([32, 3, 32, 32]) tensor([24, 83, 18, 99, 80,  3, 78, 66, 15, 88, 32, 64, 52, 62, 90,  2, 29, 11,\n",
      "        56, 34, 84, 91, 75, 50,  1,  4, 29, 57, 48, 50, 96, 13])\n",
      "545 torch.Size([32, 3, 32, 32]) tensor([75, 69, 56, 21, 57, 37, 89, 75, 15, 53, 71, 60, 10, 63, 83, 44, 97, 45,\n",
      "        40, 19, 71, 98, 30, 88, 48, 18, 39, 92, 20, 69,  7, 11])\n",
      "546 torch.Size([32, 3, 32, 32]) tensor([ 9, 83, 81,  7, 95, 77, 26, 52, 93, 46, 45, 88, 42, 16, 13, 43, 29, 19,\n",
      "        91, 44, 38, 89, 98, 63,  6, 76, 84, 21,  7, 93, 32, 11])\n",
      "547 torch.Size([32, 3, 32, 32]) tensor([33, 77, 47, 79, 82, 23, 92, 38, 77, 58, 19, 43,  6,  8, 54, 42, 65, 33,\n",
      "        35, 65, 41, 14, 95, 68, 12, 55, 23, 38,  3, 23, 16, 20])\n",
      "548 torch.Size([32, 3, 32, 32]) tensor([29, 14, 26, 42, 27, 90, 35, 20, 67, 43, 75, 64, 34, 78, 11, 48,  0,  1,\n",
      "        49, 63, 61,  9, 96, 51, 26, 13,  9, 84, 57, 42, 94, 77])\n",
      "549 torch.Size([32, 3, 32, 32]) tensor([93,  9,  2, 87, 65, 88, 73, 55, 48, 97, 65, 43, 48,  8, 16, 92, 62, 11,\n",
      "         9, 48, 68, 78, 12,  9, 60, 34, 82, 91, 43, 14, 95,  0])\n",
      "550 torch.Size([32, 3, 32, 32]) tensor([26, 65, 24, 30, 87, 38, 14, 98, 89, 85, 31, 92, 23, 29, 66, 54,  8, 79,\n",
      "        37, 39, 87, 96, 71, 95, 52, 58, 58, 76, 93, 46, 12, 14])\n",
      "551 torch.Size([32, 3, 32, 32]) tensor([75, 67, 14, 79, 97, 13, 69, 51, 57, 30, 18, 27, 91,  5, 44, 33, 71, 81,\n",
      "        55, 68,  5, 69, 17, 12, 34, 97, 31,  0, 51, 73, 39, 71])\n",
      "552 torch.Size([32, 3, 32, 32]) tensor([46, 39, 27, 44, 92, 48, 40, 94, 37, 95, 51, 50, 30, 84, 95, 65, 71, 12,\n",
      "        70, 88, 94, 99, 97, 28, 20, 44, 96, 92, 31, 80, 93, 40])\n",
      "553 torch.Size([32, 3, 32, 32]) tensor([83, 91, 57, 95, 53, 24, 42, 42, 48, 45, 12,  6, 79, 51, 31, 77, 62, 98,\n",
      "        28, 25, 41, 42, 43, 59, 75, 35, 95, 80, 34, 92, 75, 70])\n",
      "554 torch.Size([32, 3, 32, 32]) tensor([44, 22, 92, 13, 94, 76, 51, 67, 25, 41, 19, 61,  2, 55, 14, 42, 24, 75,\n",
      "        11, 14, 13,  1, 53, 84, 60, 14, 63, 12, 88, 77, 46, 85])\n",
      "555 torch.Size([32, 3, 32, 32]) tensor([88, 19, 34, 52, 50, 72, 59, 54, 21, 27, 94,  2, 14, 17, 78, 75, 67, 82,\n",
      "        83, 13, 73, 21, 68, 51, 40, 20, 18, 18, 42, 24,  4, 77])\n",
      "556 torch.Size([32, 3, 32, 32]) tensor([51, 61, 15,  1, 95,  2, 24, 96, 96, 52, 56, 66, 49, 27, 95, 90, 92, 98,\n",
      "        94, 19, 80, 64, 65,  1, 76, 29, 79, 74, 91, 63, 57, 86])\n",
      "557 torch.Size([32, 3, 32, 32]) tensor([38,  4, 21,  1, 93, 30,  4, 82, 48, 31, 33, 34, 11, 63, 10, 73, 98, 66,\n",
      "        71, 25, 90, 44, 88, 86, 27, 57, 46, 73, 70, 66, 92, 38])\n",
      "558 torch.Size([32, 3, 32, 32]) tensor([49, 42, 88, 39, 60, 29, 14,  4, 37, 37, 86, 40, 64, 86, 79, 89, 68, 55,\n",
      "        21, 88,  2, 91,  4, 39, 54,  6, 93, 77, 13, 64, 43, 52])\n",
      "559 torch.Size([32, 3, 32, 32]) tensor([89, 33, 78, 14, 47, 15, 73,  3, 23, 18,  7, 49, 20, 31, 74, 87,  0, 47,\n",
      "        52, 89, 37, 95, 89, 57,  0, 23, 31, 98,  2, 18, 17, 15])\n",
      "560 torch.Size([32, 3, 32, 32]) tensor([ 1, 66, 52, 30, 68, 83, 55, 73, 51, 21, 88, 62,  6, 30, 33, 30, 89, 31,\n",
      "        42, 96, 77, 30, 60, 54, 34, 62, 73, 60, 32, 12,  5, 56])\n",
      "561 torch.Size([32, 3, 32, 32]) tensor([ 0, 22, 50, 24, 63, 77, 84, 63, 60, 98, 57, 41, 17, 22, 83,  8, 45, 21,\n",
      "         7, 64, 55,  7,  3, 80, 34, 76, 81, 55, 51, 17, 68, 77])\n",
      "562 torch.Size([32, 3, 32, 32]) tensor([90, 22, 85, 66, 84, 53,  8, 45, 67, 70, 88, 61,  1,  0, 29, 73, 97, 54,\n",
      "        22, 47, 48, 26, 38, 93, 67, 46, 68, 85, 93, 73, 24, 47])\n",
      "563 torch.Size([32, 3, 32, 32]) tensor([ 0, 72, 23, 89, 62, 67,  9, 62, 94, 69, 27, 21, 25, 26, 23, 99, 57, 19,\n",
      "        45, 58, 59, 94,  7, 64, 69, 95, 19, 64, 27, 98,  1, 53])\n",
      "564 torch.Size([32, 3, 32, 32]) tensor([67, 34, 39, 88, 78, 77, 36, 86, 35, 25, 95, 53, 70, 50, 96, 67, 79, 57,\n",
      "         5, 34, 54, 18, 53, 63, 84, 82, 21, 63, 69, 97, 28, 80])\n",
      "565 torch.Size([32, 3, 32, 32]) tensor([17, 85,  9, 86,  2, 25, 45, 82, 73, 87,  5, 91, 10, 82, 42, 46, 79, 15,\n",
      "         2, 62, 80, 94,  8, 15, 24,  8, 39, 32, 68, 38, 13, 25])\n",
      "566 torch.Size([32, 3, 32, 32]) tensor([94, 69, 69, 30,  8, 48, 84, 30, 13, 62, 91, 79, 51, 21, 55, 59, 92, 35,\n",
      "        96, 69, 89, 88, 45, 78, 17, 65,  8, 71, 90, 36,  2, 79])\n",
      "567 torch.Size([32, 3, 32, 32]) tensor([ 1, 48,  6, 53, 43,  5, 88, 62, 67, 23, 25, 24, 63, 24, 92, 33, 66, 40,\n",
      "        44, 67, 90, 21, 69, 98, 24, 87, 39, 42, 30, 55, 27, 72])\n",
      "568 torch.Size([32, 3, 32, 32]) tensor([89, 20, 40,  0,  3, 41,  4, 96, 61, 35, 66,  1, 37, 44, 94, 19,  5, 28,\n",
      "        37, 74, 36, 72, 32, 82,  4, 16,  6, 96,  3, 27, 90, 64])\n",
      "569 torch.Size([32, 3, 32, 32]) tensor([65, 86,  5, 63,  6, 33, 18, 82, 49,  4, 56, 36, 97, 95, 28, 18, 15, 30,\n",
      "        46, 77, 97, 10,  6, 30, 16, 26, 41, 73, 15, 91,  6,  9])\n",
      "570 torch.Size([32, 3, 32, 32]) tensor([ 7, 53,  2, 53, 85, 88, 86, 79, 73, 65, 54, 52, 41, 55, 20, 61, 82, 85,\n",
      "        38, 18, 30, 89, 45, 40, 26, 50, 19, 77, 62,  5, 61, 92])\n",
      "571 torch.Size([32, 3, 32, 32]) tensor([85, 65, 54, 95, 45,  4, 13, 81, 16,  2,  4,  3, 85,  0, 88, 14, 81,  8,\n",
      "        71, 48, 64, 68, 44, 25, 14, 59, 56, 52, 91, 63, 29, 98])\n",
      "572 torch.Size([32, 3, 32, 32]) tensor([79, 75, 98, 90, 82, 55,  3, 15, 71, 36, 88, 43, 69, 48, 39, 42, 52, 22,\n",
      "        23,  6, 73, 26, 69, 73, 38, 66, 11, 95, 83,  3, 39, 87])\n",
      "573 torch.Size([32, 3, 32, 32]) tensor([70, 13, 70, 70, 15, 14, 79, 63, 93, 30, 35, 59, 14,  8, 60, 71, 78, 96,\n",
      "        98, 89, 76, 33, 31, 67, 91, 94, 91, 73, 48, 68, 32,  9])\n",
      "574 torch.Size([32, 3, 32, 32]) tensor([80, 87, 34, 14, 16, 66,  2, 38, 77, 46, 40, 83,  6, 68,  0, 72, 55, 96,\n",
      "        92, 62, 42, 31, 93, 86, 83, 40, 47, 59, 84, 37, 17, 12])\n",
      "575 torch.Size([32, 3, 32, 32]) tensor([48, 54, 81, 93, 92,  9,  3, 73, 67, 80,  1, 18, 44, 92, 23, 71, 77, 22,\n",
      "        58, 77, 76, 81, 24, 89, 80, 77, 97, 84, 61, 30, 65, 14])\n",
      "576 torch.Size([32, 3, 32, 32]) tensor([83, 53, 58, 84, 64, 48,  7, 35, 78,  6, 17, 18, 52, 53, 49,  1, 90, 92,\n",
      "        82, 77, 51, 63, 56,  7, 80, 94, 48, 64, 59, 36, 35, 25])\n",
      "577 torch.Size([32, 3, 32, 32]) tensor([68, 94, 49, 41, 91, 40,  2, 18, 86, 46, 47, 99, 20, 96, 66, 13, 16, 65,\n",
      "        11, 84, 52, 28, 34, 41, 28, 11, 98,  1, 26, 70, 64, 43])\n",
      "578 torch.Size([32, 3, 32, 32]) tensor([ 5, 17,  7,  7, 30, 99, 73,  5, 65, 14, 17, 70, 55, 22, 43, 13, 56, 15,\n",
      "        43, 49, 93, 74, 13, 52, 27, 78, 74, 55, 12,  2, 74, 93])\n",
      "579 torch.Size([32, 3, 32, 32]) tensor([58, 74, 42, 15, 86, 11, 78, 68, 67, 53,  8, 71, 21, 17, 20,  9, 94, 64,\n",
      "        84, 90,  6, 24, 85, 35, 26, 71, 14, 64, 91, 67, 39, 79])\n",
      "580 torch.Size([32, 3, 32, 32]) tensor([18, 50, 71, 74, 34, 78, 83, 10, 29,  1, 50, 28, 79,  3, 89, 48,  2, 40,\n",
      "        92, 66, 42, 25, 61, 88, 70, 35, 39, 26, 84, 13, 83, 65])\n",
      "581 torch.Size([32, 3, 32, 32]) tensor([85, 69, 67,  5, 89,  6, 45, 50, 54, 66, 39, 72, 77, 16, 21, 19, 84, 89,\n",
      "        59, 91, 52, 88, 78, 90, 93, 26, 17, 67, 15, 99, 26, 18])\n",
      "582 torch.Size([32, 3, 32, 32]) tensor([46, 98, 64, 57, 51,  3, 99, 19, 88, 73,  0, 49, 10, 94, 71,  8, 47, 45,\n",
      "        90, 93, 51, 60, 93, 43,  9, 13, 85, 12, 64, 78, 69, 62])\n",
      "583 torch.Size([32, 3, 32, 32]) tensor([26, 38, 12, 12, 10, 32, 29, 34, 74, 25, 63, 39, 61, 85, 62, 30, 20, 66,\n",
      "        99, 29, 26, 61, 58, 57, 85, 45, 32, 78, 65, 79,  5, 72])\n",
      "584 torch.Size([32, 3, 32, 32]) tensor([72, 44, 76, 31, 50,  7, 16, 50, 51, 13, 89, 59, 48, 29, 13, 56, 25, 21,\n",
      "        49, 53, 39, 37, 15, 61, 90, 56, 91, 80, 39, 38, 18, 90])\n",
      "585 torch.Size([32, 3, 32, 32]) tensor([41, 71, 45,  2,  6, 78, 10, 91,  9, 31, 62, 98, 67,  4, 15, 40, 21, 28,\n",
      "        40, 26, 82,  7, 95, 87, 97, 84, 29, 32, 83, 23, 61, 34])\n",
      "586 torch.Size([32, 3, 32, 32]) tensor([69, 18, 22, 74, 60, 77, 91, 63,  9, 29, 15, 82, 67, 52, 56, 95, 65, 61,\n",
      "        47, 50, 44, 99, 26, 77, 59,  9, 79,  2, 82, 98, 68,  5])\n",
      "587 torch.Size([32, 3, 32, 32]) tensor([58, 16, 35,  7, 89,  8, 77, 98, 49, 53, 87, 53, 40, 39, 59, 39,  4, 38,\n",
      "        75, 90, 31, 18, 14, 20, 37, 83, 28,  9,  4, 42, 20, 57])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "588 torch.Size([32, 3, 32, 32]) tensor([ 8, 99, 56, 15, 16, 10, 98, 32,  2, 57, 38, 17, 45, 58, 52, 68, 30, 31,\n",
      "        58, 28, 24, 67, 24, 23, 34, 88, 39, 35,  2, 53, 92, 43])\n",
      "589 torch.Size([32, 3, 32, 32]) tensor([ 2, 28, 51, 92, 20, 92, 52, 54, 79, 68, 57, 72, 29, 27, 61, 83, 14, 33,\n",
      "        37, 64, 27, 17, 95, 65,  6, 78, 41, 11, 89, 47, 90, 53])\n",
      "590 torch.Size([32, 3, 32, 32]) tensor([77, 24, 93, 43, 18, 19, 88, 70, 50, 54, 52, 74, 63, 31, 23, 50, 65, 55,\n",
      "        68, 72, 97, 57, 29, 82, 63,  2, 72, 79, 95, 49, 55, 39])\n",
      "591 torch.Size([32, 3, 32, 32]) tensor([70, 96, 63, 71, 36, 75, 47,  3, 69, 26, 27, 51, 65, 49,  5, 40, 80, 93,\n",
      "        16, 99, 91, 99,  4, 14, 67, 72,  3, 38, 37, 23, 10,  7])\n",
      "592 torch.Size([32, 3, 32, 32]) tensor([11, 78, 95, 96, 56, 20, 68, 47, 62, 57, 55, 65, 79, 29, 61, 11, 21, 40,\n",
      "        64, 88, 24, 67, 88, 59,  9, 64, 76, 79, 84, 50, 77, 35])\n",
      "593 torch.Size([32, 3, 32, 32]) tensor([93, 97, 75, 47, 89, 22, 84, 61, 22, 62,  5, 40, 29, 54, 65, 37, 59, 53,\n",
      "        18,  2, 26, 69, 28, 79, 10,  0, 36, 16,  6, 33, 49, 94])\n",
      "594 torch.Size([32, 3, 32, 32]) tensor([29, 94, 46, 64, 25, 48, 47, 45,  4, 11, 14, 45, 26, 19, 10, 63, 11, 89,\n",
      "        10, 91, 75, 68, 92, 33, 66, 18, 34, 17, 50, 96, 10, 46])\n",
      "595 torch.Size([32, 3, 32, 32]) tensor([56, 79, 41, 74,  4, 52, 30, 12, 27, 57, 83, 11,  1, 65, 37,  9, 18, 67,\n",
      "         6, 46, 42, 62, 34, 46, 40, 94, 13, 43, 67, 78, 53,  1])\n",
      "596 torch.Size([32, 3, 32, 32]) tensor([81, 98, 36, 38, 71, 89,  5, 39,  3,  5,  0, 75, 26, 89, 25, 45,  8, 56,\n",
      "        90, 80, 93, 48, 16, 31,  8, 31, 84, 23, 90, 31, 75, 49])\n",
      "597 torch.Size([32, 3, 32, 32]) tensor([23, 99, 66, 69, 35, 80, 46, 93, 78, 59, 24, 94, 34, 10, 14, 62, 31, 46,\n",
      "        49, 55, 88, 51, 22, 18, 89, 49, 54, 66, 10, 27, 79, 81])\n",
      "598 torch.Size([32, 3, 32, 32]) tensor([55, 11, 30, 86, 21, 88, 60, 52, 74, 33, 61, 55, 74, 27, 12, 80, 36, 63,\n",
      "        68, 70, 47,  0, 43, 90, 93, 45, 47, 48, 47, 71, 86, 27])\n",
      "599 torch.Size([32, 3, 32, 32]) tensor([33, 25, 85, 30, 90, 27, 32, 24, 60, 75, 19, 20,  5, 98, 38, 15, 28, 51,\n",
      "        31,  0, 19, 37, 96, 78, 58, 89, 74, 92, 54, 21, 23, 12])\n",
      "600 torch.Size([32, 3, 32, 32]) tensor([82, 65, 41, 29, 13, 71, 34, 13, 23, 57, 76, 28, 79, 10, 91, 28, 71, 47,\n",
      "        26, 18, 98, 89, 44, 20, 61, 46, 20, 43, 76,  0, 12, 64])\n",
      "601 torch.Size([32, 3, 32, 32]) tensor([ 4, 77, 17, 21, 62, 37, 22, 28, 47, 14, 73, 50, 23, 67, 23, 85, 59, 92,\n",
      "        46, 69, 21, 76, 10, 16, 91, 44, 66,  9, 73, 10, 16, 66])\n",
      "602 torch.Size([32, 3, 32, 32]) tensor([94, 74, 68, 52, 46, 37, 61, 70, 99, 30, 20, 93,  4, 97, 50, 62, 55, 42,\n",
      "        28, 13, 89, 83, 24, 70, 90, 16, 57,  6, 80, 99, 95, 29])\n",
      "603 torch.Size([32, 3, 32, 32]) tensor([90, 67, 88,  9, 40,  3, 12, 85, 35, 99, 84, 38, 69, 34, 90, 91, 27,  3,\n",
      "        36, 25, 63, 39, 67, 55, 68, 42, 73, 79,  5, 73, 93, 31])\n",
      "604 torch.Size([32, 3, 32, 32]) tensor([41, 78, 68, 92, 29, 23, 33, 96, 27, 63, 81, 68, 75, 18, 70, 62, 78, 19,\n",
      "        72, 47, 98, 16, 60,  4, 73, 48, 76,  8,  0, 27, 54, 99])\n",
      "605 torch.Size([32, 3, 32, 32]) tensor([17, 86, 50,  5, 71, 58, 10, 21, 21, 18, 79, 92, 44, 32, 14, 63, 63, 58,\n",
      "        42, 97, 83, 39, 89,  7, 97, 72, 78, 81, 90, 34, 95, 26])\n",
      "606 torch.Size([32, 3, 32, 32]) tensor([77,  5, 53, 87, 22, 45, 29, 47, 63,  1, 67, 74, 78, 91,  6,  4, 57, 87,\n",
      "        53, 78, 56,  1, 25, 94, 57, 96, 74, 32, 15, 82, 86, 25])\n",
      "607 torch.Size([32, 3, 32, 32]) tensor([62,  6, 64, 38, 21, 17,  7, 51, 93, 97, 10, 74, 35, 25, 78, 38, 39, 66,\n",
      "        86, 52, 70, 42, 97, 22, 56, 49, 73, 34, 16, 24, 14, 33])\n",
      "608 torch.Size([32, 3, 32, 32]) tensor([24, 79, 20, 78, 15, 70,  6, 89, 37, 97, 32, 62,  3, 50, 33, 73, 52, 90,\n",
      "        40, 16, 47, 84, 81, 31, 72, 29, 76, 27, 81, 19, 41, 76])\n",
      "609 torch.Size([32, 3, 32, 32]) tensor([43, 60, 50, 59, 14, 96,  6, 35,  1, 59,  7, 41, 19, 17, 61, 50, 15, 48,\n",
      "        26, 34, 96, 32, 63, 57, 32, 74, 99, 55, 98, 49, 71, 23])\n",
      "610 torch.Size([32, 3, 32, 32]) tensor([ 4,  9, 45, 38, 99, 97, 44, 17, 38, 56, 97, 54, 21, 24, 71, 60, 20, 30,\n",
      "        42, 73, 51, 92,  3, 70, 73, 14, 84, 18, 42, 49, 36, 39])\n",
      "611 torch.Size([32, 3, 32, 32]) tensor([36,  9, 19, 12, 13, 69, 45, 44, 38, 40, 23, 37,  8,  7, 87, 82, 83, 36,\n",
      "        64, 15, 35, 13, 64, 51, 70, 11, 95, 99, 84, 85, 21, 41])\n",
      "612 torch.Size([32, 3, 32, 32]) tensor([18, 75, 44, 65, 66, 76, 35, 26, 26, 58, 85,  0,  3, 49, 72, 26, 92, 34,\n",
      "        32, 90, 50, 95, 54, 52, 57, 28,  0, 77, 90, 67, 85, 64])\n",
      "613 torch.Size([32, 3, 32, 32]) tensor([58, 92, 81, 41, 61, 19, 69, 67, 48, 19, 78, 33, 30, 83, 35, 17, 38, 50,\n",
      "        68,  3, 11, 53, 20, 78, 23, 81, 13, 37, 13, 38, 74, 99])\n",
      "614 torch.Size([32, 3, 32, 32]) tensor([50, 75, 55, 82, 52, 62, 85,  1, 28, 29, 34, 12, 51, 60, 33, 14, 75, 14,\n",
      "        28, 12, 66, 81, 52, 39, 55, 27,  3, 48, 65, 97, 97, 51])\n",
      "615 torch.Size([32, 3, 32, 32]) tensor([ 8, 31,  7, 39, 21, 84, 71, 97, 73, 80, 25, 48, 78, 89, 90, 42, 66, 75,\n",
      "        80, 86, 25, 11, 35,  1, 10, 93, 52, 79, 82, 34, 32, 59])\n",
      "616 torch.Size([32, 3, 32, 32]) tensor([51,  2, 39, 62,  8, 98, 51, 22, 70, 18, 87, 19, 21, 76, 25, 69, 51, 74,\n",
      "        51, 32, 14, 88, 68, 60, 90, 20,  7, 41, 12, 81, 70, 90])\n",
      "617 torch.Size([32, 3, 32, 32]) tensor([ 9, 43, 17, 86, 43, 25, 69, 25, 63, 42, 90, 39, 97, 61, 32, 27, 65, 28,\n",
      "        56, 15, 82, 19, 70,  2, 82, 93, 98, 12, 89, 34, 63, 72])\n",
      "618 torch.Size([32, 3, 32, 32]) tensor([13, 24, 34, 51, 32, 14, 93, 38, 33, 12, 40, 62, 86, 91,  8, 92, 99, 51,\n",
      "         0, 70,  5, 18,  7, 73, 84,  9, 12, 65, 89, 10, 24, 74])\n",
      "619 torch.Size([32, 3, 32, 32]) tensor([80,  0, 85, 72, 40, 78, 62, 71, 97, 55, 84,  4, 61, 17, 54, 89, 62, 63,\n",
      "        77, 64, 64, 31, 75, 77, 49, 53, 36, 15, 94, 10, 73, 27])\n",
      "620 torch.Size([32, 3, 32, 32]) tensor([37, 11, 88, 73, 63, 23, 42, 79, 75,  8, 12, 33, 78, 68, 14, 76, 86, 65,\n",
      "        48, 86, 65, 82, 16, 99, 47,  3, 57, 49, 83, 89, 64, 29])\n",
      "621 torch.Size([32, 3, 32, 32]) tensor([59,  1, 89,  3, 61, 11, 52, 49, 98, 61, 29, 32, 77, 78, 69, 94, 82, 56,\n",
      "        16, 21, 40, 60, 23, 35, 90, 56, 65, 56,  1, 19, 15, 17])\n",
      "622 torch.Size([32, 3, 32, 32]) tensor([88, 48,  3, 85, 34, 41, 58, 65, 21, 25, 11, 13, 75, 62, 43, 25, 54, 39,\n",
      "        79, 38, 45, 85, 39, 76, 79, 38, 98, 54, 46, 85, 70, 36])\n",
      "623 torch.Size([32, 3, 32, 32]) tensor([32, 59, 57, 44, 22, 30, 32, 65, 18, 20, 41, 65, 75, 51, 16,  2, 55, 89,\n",
      "         0, 14, 59, 82,  9, 76, 21, 30, 12, 22, 33,  4, 60, 26])\n",
      "624 torch.Size([32, 3, 32, 32]) tensor([14, 18, 12, 71, 93, 33, 55, 34,  3, 78, 91, 39, 37, 19, 29, 13, 70, 52,\n",
      "        24, 81, 29, 19, 53, 53, 18, 59, 39, 37,  7, 60, 62, 57])\n",
      "625 torch.Size([32, 3, 32, 32]) tensor([31, 11, 38, 18, 70,  2, 90, 41, 16, 13, 96, 54, 88, 14, 20, 35,  6, 69,\n",
      "         7, 34, 95, 53, 28,  8, 48, 29, 97, 71,  0, 49, 54, 14])\n",
      "626 torch.Size([32, 3, 32, 32]) tensor([48, 60, 72, 82, 44, 90, 19, 65, 51, 80, 13, 33,  0, 83, 55, 35, 49, 46,\n",
      "        24, 79,  8, 91, 96, 87, 16, 87, 92, 45, 40, 55, 28, 79])\n",
      "627 torch.Size([32, 3, 32, 32]) tensor([58, 17, 49, 30, 50, 49, 74, 92, 23, 64, 37,  9,  4,  6, 86, 54, 38, 60,\n",
      "        50, 45, 21, 23, 84,  5, 92, 19, 70, 42, 45, 38, 70, 39])\n",
      "628 torch.Size([32, 3, 32, 32]) tensor([47,  8, 69, 55, 42, 19, 44, 93, 37, 10,  6, 32, 27, 93, 89,  7, 22, 53,\n",
      "        37, 72, 60,  2, 40, 60, 62, 64, 33, 88, 61, 95, 18, 61])\n",
      "629 torch.Size([32, 3, 32, 32]) tensor([91, 22,  1, 37, 56, 87, 99, 88, 13, 26, 47, 95, 37, 32, 24, 55, 59, 51,\n",
      "        39, 95, 36, 97,  1, 55, 41, 10, 25, 57, 58, 44, 67, 98])\n",
      "630 torch.Size([32, 3, 32, 32]) tensor([16, 31, 20, 93, 46, 62, 25, 50, 69, 85, 70, 42, 42, 79, 57, 56, 28, 17,\n",
      "        26, 55, 67, 56,  9, 88, 96, 87, 50, 85, 65, 13, 46, 13])\n",
      "631 torch.Size([32, 3, 32, 32]) tensor([10, 19, 76, 83, 74, 75, 19, 44, 89, 94,  9, 36, 64,  2, 90, 50, 83, 60,\n",
      "        32, 31,  8,  2, 82, 18,  0,  1, 91, 35, 67, 14, 29, 66])\n",
      "632 torch.Size([32, 3, 32, 32]) tensor([78, 33, 71, 23, 23,  7, 87, 97, 70, 23, 84, 54, 21, 15, 93, 13,  0, 83,\n",
      "        20, 74, 48, 28, 41, 27, 61, 59, 97, 76, 30, 52, 23, 24])\n",
      "633 torch.Size([32, 3, 32, 32]) tensor([64, 95, 82,  4, 21, 22, 74, 83, 82, 12,  3, 73, 78, 84, 56, 85, 33, 88,\n",
      "        22,  7, 67, 90, 48, 42, 22, 93, 28, 33, 17,  0, 31, 39])\n",
      "634 torch.Size([32, 3, 32, 32]) tensor([71, 12,  5,  1, 25, 20, 56, 57, 12, 80, 57, 46,  2, 42, 96, 95, 50, 11,\n",
      "        96, 83, 98, 73, 10, 94, 40,  1, 41, 33, 57, 97, 80, 70])\n",
      "635 torch.Size([32, 3, 32, 32]) tensor([83, 71, 67, 99,  5, 11, 12, 18,  0, 86,  3, 87, 50, 66, 18, 43, 51, 83,\n",
      "        68, 48, 53, 74, 95,  4, 79, 87, 55, 76,  8, 46, 47, 69])\n",
      "636 torch.Size([32, 3, 32, 32]) tensor([ 0,  0, 87, 99, 18, 83, 24, 96, 51, 21, 43, 47, 25, 78, 95, 62, 29, 29,\n",
      "        55, 37, 71, 34, 36, 85, 55, 64,  8, 57, 67, 99, 14,  4])\n",
      "637 torch.Size([32, 3, 32, 32]) tensor([13, 51, 51, 10,  4, 80, 58, 46, 42, 51, 24, 33, 52, 52, 91, 63, 65, 58,\n",
      "        87, 83, 23, 39, 23, 33, 14, 87, 89, 98, 84, 19, 89, 14])\n",
      "638 torch.Size([32, 3, 32, 32]) tensor([48,  1, 58, 55, 10, 89,  3, 82, 97, 32, 68, 11, 68,  3, 81, 46, 19,  9,\n",
      "        21, 21, 65, 84,  5, 71, 12, 46, 83, 14, 98, 55, 57, 98])\n",
      "639 torch.Size([32, 3, 32, 32]) tensor([40, 54, 41, 61, 82, 54, 63, 42, 69, 16,  8, 16, 95, 41, 33, 78, 29, 40,\n",
      "        38, 38, 57, 28, 55, 42, 40, 53, 60, 67, 82, 92, 50, 32])\n",
      "640 torch.Size([32, 3, 32, 32]) tensor([39, 35,  9, 99,  7, 57, 92, 89, 23,  9, 94, 33, 72, 77, 88, 35, 46, 10,\n",
      "        16, 22, 47, 83, 61, 16, 30, 51, 18, 31,  3, 58, 45, 55])\n",
      "641 torch.Size([32, 3, 32, 32]) tensor([54, 33, 25, 57, 21, 85,  5, 82, 13, 64, 94,  5, 31, 85, 25, 79, 32, 40,\n",
      "        81, 64, 77,  8, 28, 99, 18, 23, 85, 62,  5, 48, 16, 57])\n",
      "642 torch.Size([32, 3, 32, 32]) tensor([18, 60, 38, 82,  5, 86, 88, 65, 59, 49, 65, 21, 22, 61, 41, 36, 49, 21,\n",
      "        67, 43, 87, 11, 67, 50, 38, 93, 69, 61, 75, 68, 20, 10])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "643 torch.Size([32, 3, 32, 32]) tensor([15, 94, 29, 53, 52, 48, 43, 50, 94, 70, 14, 58, 98, 95, 36, 17, 82, 33,\n",
      "        81, 22, 62,  2, 88, 25,  4, 14, 44, 28, 35,  4, 65, 14])\n",
      "644 torch.Size([32, 3, 32, 32]) tensor([79, 82, 14, 62, 46, 10, 97, 56, 36, 40, 34, 60, 66, 10, 49, 88, 11, 16,\n",
      "        88, 82, 73, 98, 91, 57, 51, 41, 87, 78, 44, 37, 24, 73])\n",
      "645 torch.Size([32, 3, 32, 32]) tensor([67, 89,  5, 12, 60, 53, 10,  5,  2,  7, 70, 28, 27, 67, 78, 96,  7, 60,\n",
      "        42, 59, 75, 49,  4, 22, 97, 53, 30, 70, 32, 83, 88, 44])\n",
      "646 torch.Size([32, 3, 32, 32]) tensor([87, 46, 41, 33, 81, 53, 52, 97, 82, 14, 49, 82, 40, 31, 54, 85,  9, 35,\n",
      "        25, 55, 26, 92, 41, 76,  9, 50, 21, 36, 81, 61,  7, 76])\n",
      "647 torch.Size([32, 3, 32, 32]) tensor([70, 65, 26, 95, 22, 43, 56, 64, 23, 94, 27, 16, 43, 16, 73,  3, 76, 80,\n",
      "        15, 45, 48, 71, 81, 94, 35, 82, 63, 60, 45,  5,  6, 20])\n",
      "648 torch.Size([32, 3, 32, 32]) tensor([30, 33,  6, 83,  9, 32, 23, 62, 23,  2, 22, 23, 89,  4, 60, 55, 71, 98,\n",
      "         8, 79, 58, 76, 69, 99, 94, 86, 57, 35, 63,  6, 38, 33])\n",
      "649 torch.Size([32, 3, 32, 32]) tensor([87, 53, 18, 54, 15, 71, 53, 26, 90, 56, 75, 75, 51, 23, 14, 32, 89, 46,\n",
      "        41, 74, 72, 52, 94, 83, 60, 46, 67, 71, 38, 34, 49, 30])\n",
      "650 torch.Size([32, 3, 32, 32]) tensor([ 2, 27, 92, 40, 82, 12, 25, 77, 95, 19, 70, 23,  4, 65, 65, 47, 79, 55,\n",
      "        30,  7, 76, 61, 52, 33, 49, 82, 77, 58,  8, 64, 91,  9])\n",
      "651 torch.Size([32, 3, 32, 32]) tensor([61, 61, 22, 44, 29, 82, 82,  2, 29, 33,  6, 75, 11, 16, 67, 14, 67, 37,\n",
      "        76,  3, 83, 46, 24, 69, 16, 79, 56, 14, 11, 87,  7, 80])\n",
      "652 torch.Size([32, 3, 32, 32]) tensor([56, 91,  6, 84, 10, 72, 96, 41, 26,  9, 88, 74, 93, 32, 81, 60, 66, 45,\n",
      "         8, 83, 44, 72, 41, 25, 23, 38, 30, 31, 35, 24, 54, 73])\n",
      "653 torch.Size([32, 3, 32, 32]) tensor([15, 61, 17, 58, 51,  4, 19, 40, 27, 84,  1, 77, 63, 19, 30,  9, 24, 85,\n",
      "        78, 63, 82,  7, 65, 36, 18, 65, 45, 86, 64, 90, 56, 22])\n",
      "654 torch.Size([32, 3, 32, 32]) tensor([96, 52, 12, 68, 22, 34, 48, 20, 12, 69, 71, 54, 78, 22, 55, 43, 83, 81,\n",
      "        73, 97, 85, 97, 15, 16, 15,  3, 60, 32, 24,  8, 33,  5])\n",
      "655 torch.Size([32, 3, 32, 32]) tensor([72, 61, 13,  7, 94, 40, 20, 89, 67, 38, 82, 68, 65, 27, 66, 40, 71, 19,\n",
      "        35, 91, 62, 78, 99, 57, 22, 67, 17, 11,  7,  9, 43, 86])\n",
      "656 torch.Size([32, 3, 32, 32]) tensor([78, 50, 42,  4, 79, 88, 13, 50, 80, 71, 46, 88, 39, 39,  5, 99, 27, 51,\n",
      "        22, 42, 67,  2, 15, 65, 52, 36, 75, 22, 99, 88, 27, 51])\n",
      "657 torch.Size([32, 3, 32, 32]) tensor([38, 20,  7,  7, 50, 72, 41,  2, 30, 27, 26, 40, 37, 77, 54, 90, 52,  4,\n",
      "        27, 40, 88,  1,  0,  4, 83, 96, 88, 79, 78, 19, 13, 18])\n",
      "658 torch.Size([32, 3, 32, 32]) tensor([14, 43, 21, 96, 65, 41,  8, 69, 96, 30, 38, 22, 27, 69, 72, 10, 95, 74,\n",
      "        95,  3, 46, 44, 37, 73, 47, 13, 17, 70,  3, 67, 60, 98])\n",
      "659 torch.Size([32, 3, 32, 32]) tensor([70, 50, 14, 14, 97, 73, 23, 94, 24, 63,  6,  9, 62, 49, 57, 43, 12,  3,\n",
      "        44, 38, 66, 95, 59, 81, 62, 76, 73, 49, 97, 39, 24, 30])\n",
      "660 torch.Size([32, 3, 32, 32]) tensor([ 5, 87, 35, 67, 19, 78, 70, 24,  0, 75, 75, 97, 30, 26, 84, 78, 71, 10,\n",
      "        75, 77, 28, 31, 96, 97, 61, 92,  6, 39,  1, 23, 70, 99])\n",
      "661 torch.Size([32, 3, 32, 32]) tensor([84, 71, 44, 91, 49, 12, 50,  2, 52, 22, 52, 96, 19, 59, 28,  5, 90, 51,\n",
      "        21, 36, 91, 36, 49, 70, 87, 51, 50, 97,  0, 14, 89, 85])\n",
      "662 torch.Size([32, 3, 32, 32]) tensor([44, 93, 13,  2, 35, 11, 38, 53, 33, 48, 12, 52, 36, 22, 14, 20,  1, 97,\n",
      "        11, 94, 89, 97, 66, 35, 28, 37, 57, 21, 10, 31,  4, 18])\n",
      "663 torch.Size([32, 3, 32, 32]) tensor([36, 52, 83, 84, 62,  4, 60, 94, 32, 71, 30,  3, 52, 40, 62, 13, 53, 58,\n",
      "        81, 22, 33,  1, 97, 90, 31, 38, 47, 83, 22, 30,  5, 66])\n",
      "664 torch.Size([32, 3, 32, 32]) tensor([49, 62, 73, 24, 29, 40, 31, 75, 89, 75, 37, 66, 51, 73, 66, 36, 27, 93,\n",
      "        37, 57, 93, 22, 43, 64, 45, 27,  4, 90, 93, 22, 21, 32])\n",
      "665 torch.Size([32, 3, 32, 32]) tensor([89, 89, 88, 83, 89, 78, 56, 79, 48, 48, 88, 80, 45, 93, 38, 64, 52, 68,\n",
      "        22, 61, 65, 88, 63, 50, 78, 65, 22, 52, 43, 80, 55, 96])\n",
      "666 torch.Size([32, 3, 32, 32]) tensor([ 7, 48, 40, 96, 55, 21, 17, 28, 60, 86,  5, 22, 76,  8, 13, 47, 73, 90,\n",
      "         2, 95,  0, 45, 90,  6, 97, 34, 25, 17, 50, 41, 45, 75])\n",
      "667 torch.Size([32, 3, 32, 32]) tensor([88, 17, 51, 40, 89,  4,  9, 31, 72, 51, 34,  0, 76, 20, 61, 30, 22, 16,\n",
      "        80,  5, 32, 77, 57, 74, 32, 93, 55, 90, 39, 44, 98, 13])\n",
      "668 torch.Size([32, 3, 32, 32]) tensor([76, 39, 73,  3, 70, 30, 24,  9,  2,  2, 50, 68, 84, 15, 79, 46, 77, 70,\n",
      "        68, 71, 67, 49, 85, 13, 42, 72,  1, 99,  6, 33,  8, 87])\n",
      "669 torch.Size([32, 3, 32, 32]) tensor([65, 12, 19,  5,  0, 52,  2, 95, 39, 44, 48, 55, 81, 90, 91, 47, 54, 77,\n",
      "        73, 15, 80, 26, 61, 40, 14, 22,  8, 68, 81, 67, 73, 61])\n",
      "670 torch.Size([32, 3, 32, 32]) tensor([40, 73, 97, 27, 79, 24, 90, 14, 74,  5, 66, 95, 95, 19, 53, 71, 62, 81,\n",
      "        45,  6, 74, 37, 35, 13, 88,  7, 21, 40, 93, 81, 88,  9])\n",
      "671 torch.Size([32, 3, 32, 32]) tensor([43, 41, 74, 81, 25, 98, 73, 48, 24, 12, 24, 88, 35, 42, 39, 31, 48, 62,\n",
      "        92, 52, 38, 10, 90, 90, 89,  9, 57, 33, 28, 14, 52, 92])\n",
      "672 torch.Size([32, 3, 32, 32]) tensor([13, 87, 95, 47, 26, 65, 35, 74, 56, 50, 51, 77,  9,  5, 94, 72, 62, 56,\n",
      "         4,  2, 89, 31, 67, 50,  5, 24, 16, 42,  1, 98, 12, 64])\n",
      "673 torch.Size([32, 3, 32, 32]) tensor([98, 87, 52, 25, 70,  0, 84, 40, 32, 24, 52, 80, 71, 65, 21, 10, 91, 16,\n",
      "        42, 44, 61, 74, 66, 31, 99,  2, 10, 84, 91, 32, 42,  4])\n",
      "674 torch.Size([32, 3, 32, 32]) tensor([91, 51, 65, 18, 18, 41, 40, 31, 26, 94, 45, 34, 65, 95, 25, 26, 96, 71,\n",
      "        79, 64, 51, 65, 12, 25, 12, 68, 83,  9, 13, 86, 80, 95])\n",
      "675 torch.Size([32, 3, 32, 32]) tensor([20, 26, 97, 15, 41, 98, 13, 78, 29,  3, 35, 11, 47, 67, 78, 72, 24, 70,\n",
      "        88, 94, 27, 51, 84, 24, 82, 25, 84, 22, 43, 19,  9,  5])\n",
      "676 torch.Size([32, 3, 32, 32]) tensor([14, 27, 58, 69, 89, 35, 22, 95, 89, 44,  4,  3, 89, 22,  5, 39, 54, 70,\n",
      "        46, 24, 30, 14, 84,  7,  0, 86, 72, 90, 89, 14, 47, 32])\n",
      "677 torch.Size([32, 3, 32, 32]) tensor([86, 59, 17, 44, 95, 87, 21, 70, 41,  6, 48, 57, 82, 49, 44, 11, 69,  8,\n",
      "        16, 49, 76, 88, 72, 80, 49, 29, 59, 71, 17, 19, 32, 82])\n",
      "678 torch.Size([32, 3, 32, 32]) tensor([43,  7, 19, 80,  1, 18, 63, 13,  1, 39,  6, 67, 40, 11, 37, 38, 48, 67,\n",
      "        74, 62, 63, 21, 96, 37, 44, 79, 43, 10, 79, 50, 39, 37])\n",
      "679 torch.Size([32, 3, 32, 32]) tensor([96, 76, 66, 56, 76, 22,  5, 62,  4, 32,  4, 11,  7,  1, 19, 45, 21, 34,\n",
      "        27, 21, 67, 47, 99, 92, 90, 55, 35, 65, 31, 32, 29, 45])\n",
      "680 torch.Size([32, 3, 32, 32]) tensor([35, 61, 30, 24, 63, 51, 26, 20, 22, 21, 45, 59, 73,  9, 41, 54, 76, 81,\n",
      "        15, 52, 69, 87, 16, 79, 22, 52, 67, 75,  0, 40, 74, 77])\n",
      "681 torch.Size([32, 3, 32, 32]) tensor([57, 45, 97, 64, 65, 97,  4,  5, 70, 47, 82, 36, 99, 76, 61, 99, 19, 91,\n",
      "        42, 48,  6, 79, 56, 32, 54, 46, 69, 98, 82, 70, 32, 98])\n",
      "682 torch.Size([32, 3, 32, 32]) tensor([76, 25, 93, 98, 86, 34, 77,  3, 67, 73, 44, 44, 53, 68, 33, 86, 89, 23,\n",
      "        19, 84,  4,  9, 31, 54, 70,  2, 93, 51, 90, 77, 12, 63])\n",
      "683 torch.Size([32, 3, 32, 32]) tensor([51, 17, 56, 64, 14, 82, 29, 62, 79, 25, 77, 59, 97,  9,  8, 43, 78, 50,\n",
      "        21, 29, 17, 70, 91, 96, 59, 57, 52, 57, 29, 93, 23, 61])\n",
      "684 torch.Size([32, 3, 32, 32]) tensor([54, 82, 51, 42, 46, 77,  4,  7, 34, 15, 56, 66, 95, 26, 21, 70, 29, 29,\n",
      "        67,  1,  8, 56, 90, 71, 11, 42, 25, 34, 99, 18, 92,  3])\n",
      "685 torch.Size([32, 3, 32, 32]) tensor([56,  3, 79,  4, 71, 98, 19, 14, 89, 68,  8,  4, 17, 74,  8, 62, 98, 36,\n",
      "         3, 93, 89, 42, 12, 39, 10, 61, 91, 66,  1, 78, 15, 49])\n",
      "686 torch.Size([32, 3, 32, 32]) tensor([93, 21, 87, 47, 35, 94, 33,  4, 58, 79, 69, 60, 32, 13, 20, 26, 29,  6,\n",
      "        53, 46, 57, 85, 83, 12, 75, 25, 83, 42, 42, 93, 32, 99])\n",
      "687 torch.Size([32, 3, 32, 32]) tensor([ 5, 21,  0, 96,  2, 74, 85, 21, 10, 67, 41, 14, 31,  3, 72, 12, 95, 22,\n",
      "        99, 20, 57, 48, 44, 27, 98, 55, 29, 14, 92, 80,  6, 80])\n",
      "688 torch.Size([32, 3, 32, 32]) tensor([28, 16, 31, 11, 71, 28, 66, 31, 24,  5, 32, 80, 48, 31, 80, 10, 68, 10,\n",
      "        69, 90, 25, 76, 63, 90, 41, 30, 31, 32, 49, 83, 70, 66])\n",
      "689 torch.Size([32, 3, 32, 32]) tensor([68, 93, 55, 71, 20, 43, 63,  3, 52, 45, 51, 75, 68, 78, 83,  0, 97, 62,\n",
      "        75, 89, 25, 74, 77, 76, 39, 69,  0, 83, 54, 79, 27, 82])\n",
      "690 torch.Size([32, 3, 32, 32]) tensor([58, 54, 23,  8, 68, 58, 75, 54, 41, 55, 82, 57, 30, 87, 59, 51, 14, 18,\n",
      "         9, 52, 69, 14,  3, 46,  8, 52, 29, 75, 26, 31, 36,  5])\n",
      "691 torch.Size([32, 3, 32, 32]) tensor([76,  6, 92, 64, 75, 97, 64,  9, 81, 43, 16, 93,  4, 40, 32, 23, 59, 53,\n",
      "         9, 64, 74, 37, 19, 66, 44, 81, 31, 21, 41, 77, 44, 12])\n",
      "692 torch.Size([32, 3, 32, 32]) tensor([23, 91, 81, 37, 30, 84,  6, 41, 68, 65, 18, 71, 49, 12, 37, 82, 28, 26,\n",
      "        83, 49, 14, 44, 99, 92, 34, 79, 55, 42, 66, 52, 66, 64])\n",
      "693 torch.Size([32, 3, 32, 32]) tensor([69, 42, 99, 66, 32,  6, 70, 59,  3, 41, 36, 99, 68,  4, 97, 18, 36, 47,\n",
      "        27, 27, 70, 58, 11,  1, 22, 34, 67, 90, 81, 22, 60, 49])\n",
      "694 torch.Size([32, 3, 32, 32]) tensor([31, 39, 22, 85, 88, 81, 97, 99, 94, 99, 52, 40, 77, 94, 82, 60, 46, 80,\n",
      "        39, 60, 37, 70, 84, 67, 51, 14, 20, 63, 80, 20, 66, 23])\n",
      "695 torch.Size([32, 3, 32, 32]) tensor([61, 70, 43, 38, 20, 73, 80, 38, 52, 13,  1,  9, 44,  4, 74,  7, 31, 36,\n",
      "        48, 95, 96, 16, 44,  7, 82,  6,  1,  3, 34, 14, 78, 94])\n",
      "696 torch.Size([32, 3, 32, 32]) tensor([55, 16, 80,  7, 71, 98, 70, 93, 81, 12, 23,  7, 30, 11, 36, 53, 56, 59,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        50,  8, 58, 82, 59, 44, 12,  7, 37, 70, 91, 90, 98, 80])\n",
      "697 torch.Size([32, 3, 32, 32]) tensor([90, 20, 23, 15, 94,  3, 38, 94, 48, 87,  3, 99, 46, 83, 13, 69, 53, 78,\n",
      "        74, 34, 90, 45,  9, 94, 47,  8, 79, 44, 54, 98, 59, 20])\n",
      "698 torch.Size([32, 3, 32, 32]) tensor([ 6,  3, 57, 77, 58, 67, 33,  3,  4, 88, 15, 14, 44, 46, 38, 38, 16, 15,\n",
      "        80,  6, 77, 77, 75, 28, 57, 91, 33, 56,  1, 67, 59, 11])\n",
      "699 torch.Size([32, 3, 32, 32]) tensor([46, 42,  3, 91, 11, 62, 59, 96, 79, 51, 61, 64, 20,  4, 14, 77, 86, 48,\n",
      "        13, 54, 67, 36, 52,  3, 66, 54, 49, 17, 41, 26, 87, 15])\n",
      "700 torch.Size([32, 3, 32, 32]) tensor([87,  6, 69, 85, 32, 50,  3, 36, 50, 55, 97, 48, 99, 46, 52, 32, 63, 60,\n",
      "        57, 14, 54, 24, 25, 30, 22, 51,  7, 98, 38, 43, 56, 51])\n",
      "701 torch.Size([32, 3, 32, 32]) tensor([64, 76, 48, 65, 69, 32, 33, 95, 58, 96, 87, 64, 80, 50, 12, 97, 10, 67,\n",
      "        83, 91, 13, 56,  5, 41, 38, 43,  2, 19, 34, 27, 13,  2])\n",
      "702 torch.Size([32, 3, 32, 32]) tensor([26, 33, 30, 21, 79, 70, 29, 35, 66, 97, 88, 78, 29, 83, 45,  5, 28, 73,\n",
      "        94, 77,  9, 60, 83,  9, 55, 41, 14, 86, 42, 22, 80, 98])\n",
      "703 torch.Size([32, 3, 32, 32]) tensor([23, 14, 85, 16, 34, 54, 90,  5, 97, 54, 15, 72, 64,  5, 24, 38, 86, 85,\n",
      "        42, 45,  9, 92, 90,  9,  1, 30, 34, 43, 59, 67,  9, 57])\n",
      "704 torch.Size([32, 3, 32, 32]) tensor([85, 54, 22, 52, 10, 11, 83, 39,  1, 86, 91, 58, 59, 13, 11, 66, 11, 26,\n",
      "        24, 88, 72, 32, 62, 93, 88, 79, 27, 73, 65, 15, 89, 10])\n",
      "705 torch.Size([32, 3, 32, 32]) tensor([44, 83,  0, 28, 40,  4, 10, 84, 86, 39, 52,  8, 44, 70, 30, 67, 98, 88,\n",
      "        42, 46, 68,  8, 12, 56, 68, 33, 88, 99,  4, 74, 79, 12])\n",
      "706 torch.Size([32, 3, 32, 32]) tensor([ 0, 99, 49, 92, 95, 39, 20, 42, 43, 37, 24, 32, 58, 55, 65, 47, 88, 63,\n",
      "         7, 72, 22, 90, 49, 19, 63, 14, 45, 26, 43, 87, 76,  6])\n",
      "707 torch.Size([32, 3, 32, 32]) tensor([73, 42, 50, 30, 36, 75, 70, 34,  4, 16, 55, 49, 18, 50, 19, 51, 55,  8,\n",
      "        88, 86,  9, 50, 42,  1, 92, 26, 99, 29, 83, 51, 85, 76])\n",
      "708 torch.Size([32, 3, 32, 32]) tensor([ 6, 27, 21, 61, 81, 17,  7, 87,  3, 56, 76, 73, 79, 33, 79, 88, 94, 84,\n",
      "        95, 74, 54,  2, 18, 50, 88, 81, 81, 85, 23,  0, 45, 21])\n",
      "709 torch.Size([32, 3, 32, 32]) tensor([58, 20, 44, 59, 54, 95, 53, 91, 82, 18, 44, 50,  5, 42, 74, 99, 34, 64,\n",
      "        96, 27, 86, 59, 92, 36, 24, 11, 38, 24, 15, 33, 40, 18])\n",
      "710 torch.Size([32, 3, 32, 32]) tensor([81, 31, 82, 65, 89, 43, 33, 50, 39,  6,  4, 68,  9, 29, 60, 28, 10, 79,\n",
      "        41,  2, 38, 99, 39, 96, 73, 51, 67, 66, 20, 75, 33, 46])\n",
      "711 torch.Size([32, 3, 32, 32]) tensor([95,  7, 27, 21, 36, 32, 77, 76, 42, 49, 62,  2, 67, 94, 43, 37, 14, 66,\n",
      "        53, 42, 86, 47, 13, 60, 10, 75, 10, 61, 94, 67, 43, 52])\n",
      "712 torch.Size([32, 3, 32, 32]) tensor([49, 68, 27, 19, 32, 64, 29,  0, 53, 60, 37,  5, 63, 80, 37, 23, 46, 71,\n",
      "         8, 61, 89, 30, 91, 59,  1, 96, 39, 93, 11, 85, 11, 89])\n",
      "713 torch.Size([32, 3, 32, 32]) tensor([94, 21, 21,  9,  1, 20, 26, 90, 67, 49, 83,  4, 62, 21, 65, 26, 89,  5,\n",
      "        17, 79, 12, 85, 60, 46,  2, 32, 34, 88, 92, 15, 44, 77])\n",
      "714 torch.Size([32, 3, 32, 32]) tensor([81, 53, 27, 94, 34, 36, 39, 99, 46, 93, 69, 91,  0, 42, 42, 66, 76, 67,\n",
      "        61, 20, 79, 13, 85, 46,  7, 96, 58, 11, 79, 76, 38, 31])\n",
      "715 torch.Size([32, 3, 32, 32]) tensor([81, 19, 97,  1, 44, 66, 61, 36, 74, 97, 96, 91, 22, 46, 80, 64, 13, 14,\n",
      "        85, 73, 70, 21, 86, 53, 39, 79, 37, 23, 92, 36, 74, 81])\n",
      "716 torch.Size([32, 3, 32, 32]) tensor([ 8, 57, 49, 67, 66, 80, 24, 95, 95, 80, 56, 55, 69, 91, 55, 41, 73, 90,\n",
      "        24, 50, 18, 84, 40, 27, 35, 70,  2, 48, 59, 17, 98, 45])\n",
      "717 torch.Size([32, 3, 32, 32]) tensor([24, 95, 80, 11, 53, 49, 92, 37, 59, 30, 50, 48, 36, 37, 85, 42, 78, 75,\n",
      "        62, 87, 93, 60, 37,  4, 73, 69, 76, 61, 77, 32, 64, 74])\n",
      "718 torch.Size([32, 3, 32, 32]) tensor([43, 78, 37, 52, 27, 45,  0, 38, 40, 22,  6, 28, 78, 59, 48, 27, 61, 17,\n",
      "        13, 40, 57, 20, 72, 66, 72, 72, 55, 44, 64, 81, 54, 58])\n",
      "719 torch.Size([32, 3, 32, 32]) tensor([14, 78, 61, 93, 54, 46, 78, 74, 42, 43, 76, 35, 20, 86, 27, 68, 19, 75,\n",
      "        36, 18, 63, 37, 37, 31, 87, 15, 14, 72, 71, 36, 47, 96])\n",
      "720 torch.Size([32, 3, 32, 32]) tensor([25, 29, 29, 82,  4, 18, 87, 24, 69, 83, 20, 40,  2,  1, 86, 99, 24, 78,\n",
      "        27,  8, 41, 33, 13, 49, 98, 73,  2, 32, 17, 49, 27,  1])\n",
      "721 torch.Size([32, 3, 32, 32]) tensor([85,  2, 49, 95,  1, 18,  3, 34, 55, 12, 21, 94,  4,  8, 10, 45, 38, 84,\n",
      "        66, 50, 75, 51, 67, 33,  8, 84, 33, 70,  6,  8, 68, 34])\n",
      "722 torch.Size([32, 3, 32, 32]) tensor([36, 40, 69, 75, 76, 76, 83, 48, 72, 49, 80, 37, 54, 92, 78, 12, 90, 37,\n",
      "        45, 86, 19,  4, 89, 70, 82, 84, 24, 64, 83, 87, 61, 32])\n",
      "723 torch.Size([32, 3, 32, 32]) tensor([51, 93, 87, 49, 81, 42, 42, 15,  4, 42, 72, 44, 64, 83, 46, 91, 64, 24,\n",
      "        29,  5, 40, 99, 27, 49, 57, 87, 67, 80, 61, 89, 57, 92])\n",
      "724 torch.Size([32, 3, 32, 32]) tensor([52, 81, 71,  1, 46,  6, 46, 10, 43, 27, 42, 98, 10, 78, 86, 53, 86, 60,\n",
      "        87, 47, 81,  6, 59, 31, 49, 92, 57, 87, 42, 46, 99, 29])\n",
      "725 torch.Size([32, 3, 32, 32]) tensor([70, 98, 53, 77, 55, 37, 81, 64, 83, 16, 18,  3, 39, 68, 86, 70,  4, 49,\n",
      "        45, 38,  0, 44,  4, 64, 23, 99, 61, 15, 85, 63, 91, 74])\n",
      "726 torch.Size([32, 3, 32, 32]) tensor([ 3, 54, 90, 34, 14, 84, 13, 87, 20, 78, 64, 39,  3, 86,  6,  3, 49, 95,\n",
      "        35, 45, 90, 72, 25, 57, 10, 36, 71, 56, 66,  8, 77, 69])\n",
      "727 torch.Size([32, 3, 32, 32]) tensor([85, 38, 93,  4, 60, 47, 29, 28, 12, 70, 16, 61, 29, 38, 80, 95, 61, 47,\n",
      "        72, 37, 83, 36, 88, 49, 61, 21, 24, 81, 52, 58, 89, 11])\n",
      "728 torch.Size([32, 3, 32, 32]) tensor([54,  8, 26, 22, 55, 25, 32, 22, 67, 52, 65,  2, 88, 51, 84, 49, 30,  4,\n",
      "        53, 18, 13, 72,  3, 74, 21, 21, 96, 18, 62, 96, 54, 67])\n",
      "729 torch.Size([32, 3, 32, 32]) tensor([37, 87, 39, 76, 93, 33, 88,  9, 55, 38, 91, 51,  6, 97, 94, 30,  1, 25,\n",
      "        77, 20, 34, 71, 83, 41, 35,  9, 74, 72, 76, 42, 27,  5])\n",
      "730 torch.Size([32, 3, 32, 32]) tensor([97, 94, 52, 52,  3, 61, 33, 99, 52, 83, 40, 31, 81, 11, 90, 51, 67,  2,\n",
      "        27, 24, 81, 34, 94, 79, 11, 76, 70, 30, 79, 92, 52, 29])\n",
      "731 torch.Size([32, 3, 32, 32]) tensor([14, 61, 17, 66, 50, 70,  2, 46, 34, 43, 57, 70, 54,  7, 25, 80, 40, 91,\n",
      "        71, 30, 41, 42, 27, 29,  6, 53, 69, 96, 73, 78, 96, 26])\n",
      "732 torch.Size([32, 3, 32, 32]) tensor([63, 34, 38, 90, 52, 45,  6,  8, 63, 65, 73, 38, 40, 79, 40, 64, 70,  1,\n",
      "        83,  6, 96, 22, 64, 70, 33, 71, 20,  7, 20, 12, 21, 63])\n",
      "733 torch.Size([32, 3, 32, 32]) tensor([84, 39, 98, 33, 38, 15, 16, 69,  5, 98, 30, 35, 17, 92, 57, 63, 45, 41,\n",
      "        98, 65, 67, 48, 55, 62, 47, 36, 32, 47, 58, 37, 59, 62])\n",
      "734 torch.Size([32, 3, 32, 32]) tensor([93, 99, 10, 84, 58, 32, 20, 78, 67, 75, 65, 23, 18, 17, 48, 67, 62, 63,\n",
      "        20, 59, 20, 50, 21, 68, 33, 50, 98, 50, 80, 15, 92, 54])\n",
      "735 torch.Size([32, 3, 32, 32]) tensor([ 3, 20, 47, 69, 59, 15, 17, 49, 10, 94, 28, 87, 37, 19, 45,  2, 21,  8,\n",
      "         6, 83, 36, 98, 48, 33,  0, 27, 66, 41, 30, 97, 15, 24])\n",
      "736 torch.Size([32, 3, 32, 32]) tensor([25,  0, 15, 46, 29, 65, 42,  7, 78, 95, 71, 43, 65, 52, 69, 18, 26, 12,\n",
      "        85, 19, 74, 29, 74, 50, 43, 32, 65, 30, 35, 47, 63, 44])\n",
      "737 torch.Size([32, 3, 32, 32]) tensor([66, 31, 82, 36, 30, 46, 70,  9, 61, 79,  6, 46, 74, 23, 92, 30, 29, 50,\n",
      "        21, 52, 44, 40, 94, 48, 25, 90, 72, 41, 81, 25, 57, 10])\n",
      "738 torch.Size([32, 3, 32, 32]) tensor([12, 31, 21, 25, 75, 84, 73, 80, 87, 15,  6, 11, 70, 99, 85, 39, 24, 20,\n",
      "        99, 98, 19, 93, 42, 87, 91, 96, 38, 19, 75, 52, 34, 26])\n",
      "739 torch.Size([32, 3, 32, 32]) tensor([95,  6,  8, 85, 81, 82, 83, 71, 90, 81, 20, 96, 60, 81, 86, 62, 53, 83,\n",
      "        21, 35, 32, 31, 47, 35, 26, 89, 39, 55, 97, 29, 20, 13])\n",
      "740 torch.Size([32, 3, 32, 32]) tensor([66, 38, 21, 45, 19, 38, 57,  1, 77, 63, 61, 82, 88, 48, 75,  7, 70, 15,\n",
      "        33, 78,  0, 38, 83, 53, 11,  2, 96, 57, 85, 70, 10, 11])\n",
      "741 torch.Size([32, 3, 32, 32]) tensor([92, 23, 86, 93, 16, 60, 16, 35, 23, 92, 92, 77, 12, 85, 30, 81, 70, 71,\n",
      "        83, 97,  6, 86, 27,  1,  3, 12, 99, 15, 48, 87, 86, 32])\n",
      "742 torch.Size([32, 3, 32, 32]) tensor([25, 90, 45, 54, 50, 13, 62, 58, 60, 71, 93, 73, 30, 83, 31, 10, 18, 24,\n",
      "        63, 27, 85, 81, 76, 53, 45, 67, 94, 99, 51, 10,  3, 68])\n",
      "743 torch.Size([32, 3, 32, 32]) tensor([49, 22, 78, 87, 56,  7, 92, 82, 90, 96, 26, 34, 54, 85, 85, 74, 37, 72,\n",
      "        24, 74, 48, 34, 62, 13, 95, 65, 97, 36,  6,  1, 12, 70])\n",
      "744 torch.Size([32, 3, 32, 32]) tensor([91, 44, 50, 63, 11, 61, 14, 92, 87,  1, 65, 62, 95, 56, 42, 75, 25, 40,\n",
      "        35, 88, 58, 75, 80, 64, 15, 76,  1, 51, 66, 10, 81, 51])\n",
      "745 torch.Size([32, 3, 32, 32]) tensor([11,  7, 90, 65, 17, 83, 27, 29, 67,  5, 13, 71, 55, 64, 79, 62, 40,  7,\n",
      "         2, 17, 79,  1,  9, 32, 19, 65, 37, 82, 48, 76, 23, 68])\n",
      "746 torch.Size([32, 3, 32, 32]) tensor([20, 99, 84, 32, 24, 87, 12,  2, 29, 21, 82, 53, 64, 26, 67, 73, 75, 63,\n",
      "        11, 21, 34, 54, 23, 47, 88,  1, 75, 66,  3, 79, 80, 44])\n",
      "747 torch.Size([32, 3, 32, 32]) tensor([ 4, 24, 24, 77, 38, 89, 16, 21,  7, 87,  4, 20, 30, 14, 36, 89, 83, 76,\n",
      "        59, 32, 66,  5, 41, 52, 22, 82, 75, 74, 90, 99, 42, 45])\n",
      "748 torch.Size([32, 3, 32, 32]) tensor([86, 36,  7, 24, 78, 32, 70, 79, 31, 92, 82, 83, 85, 67, 89,  4, 11, 35,\n",
      "        77, 90, 22, 99, 99, 29, 20, 64, 93, 50,  7,  7, 95, 20])\n",
      "749 torch.Size([32, 3, 32, 32]) tensor([36, 56, 72, 99, 62, 58, 15,  3, 92, 26, 54, 41, 36, 25,  5, 40,  4, 27,\n",
      "        27, 67, 72, 26, 81, 33, 99, 38, 21, 78, 24, 93, 31, 20])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "750 torch.Size([32, 3, 32, 32]) tensor([44, 41, 20, 17, 27, 95, 76, 88, 90, 52, 71,  9, 52, 23, 17, 99, 94, 33,\n",
      "        79, 47, 68, 40, 54, 11, 42, 19, 82,  7,  5, 87,  7,  1])\n",
      "751 torch.Size([32, 3, 32, 32]) tensor([44, 77, 33, 67, 73, 46, 50, 91, 10, 36, 50, 66, 23, 10, 88, 49,  5,  7,\n",
      "        59, 18, 84, 56, 55, 67, 93,  6, 83, 35, 76, 78,  5, 88])\n",
      "752 torch.Size([32, 3, 32, 32]) tensor([32, 68, 48, 34, 96, 75,  2, 61, 56, 83, 32, 33, 44, 34, 10, 38, 39, 92,\n",
      "         0, 14, 26, 43, 94, 84, 79, 56, 36, 25, 51, 42, 21, 34])\n",
      "753 torch.Size([32, 3, 32, 32]) tensor([74, 67, 33, 12, 82, 38, 47, 62,  1, 89, 97, 17, 81, 51, 12, 77, 93, 34,\n",
      "         4, 87, 52, 12, 57, 22, 35, 47, 39, 55, 98, 25, 72,  4])\n",
      "754 torch.Size([32, 3, 32, 32]) tensor([19, 47, 13, 59, 78, 89, 42,  3, 73, 24, 50, 60, 39, 32, 29,  8, 96, 50,\n",
      "        56,  4, 27, 95, 25, 86, 59, 27,  9, 47,  8, 73, 32, 43])\n",
      "755 torch.Size([32, 3, 32, 32]) tensor([91, 26, 83, 59, 98, 29, 85,  7, 64,  1, 12, 79, 57, 57, 79, 52, 74, 59,\n",
      "        90, 25, 79, 93,  7, 96, 16, 93, 54, 83, 64, 28, 38, 69])\n",
      "756 torch.Size([32, 3, 32, 32]) tensor([26, 69, 36, 10, 69, 33, 54, 45, 74, 43, 51, 68, 78, 27, 66, 15, 55, 17,\n",
      "        82, 25, 56, 18, 12, 88, 68, 33, 64, 50, 58, 11, 43, 32])\n",
      "757 torch.Size([32, 3, 32, 32]) tensor([61, 59, 21, 87, 80, 52, 63, 83, 14,  6, 63, 55, 85, 59, 54, 81, 53, 32,\n",
      "        90, 99, 94, 71, 56, 81, 50, 30, 57,  0, 43, 53,  3, 30])\n",
      "758 torch.Size([32, 3, 32, 32]) tensor([31, 47, 18, 64, 20, 25,  9, 47, 78, 68, 85, 63, 52,  6, 75, 67, 88, 92,\n",
      "        51, 22, 80,  3,  9, 91, 67, 93, 33, 27, 17, 20, 47,  0])\n",
      "759 torch.Size([32, 3, 32, 32]) tensor([43, 12, 44, 47, 85, 77, 76, 55, 31, 39, 56, 77, 96, 32, 69, 85, 81,  9,\n",
      "        30, 37,  0, 54, 23, 20, 49, 25, 31, 34, 31, 49, 93, 13])\n",
      "760 torch.Size([32, 3, 32, 32]) tensor([59, 93,  4, 21, 69, 63,  0, 65, 66, 48, 67,  0, 67, 90, 54, 42, 53, 64,\n",
      "        39, 58, 84, 15, 43, 45, 92, 50, 82,  2,  7, 51, 57, 50])\n",
      "761 torch.Size([32, 3, 32, 32]) tensor([58, 35, 71, 62, 71,  2, 64, 34, 28, 88, 25, 34, 26, 48, 69, 23, 50, 91,\n",
      "        14, 28, 95, 29, 98, 34, 46, 68, 44, 34, 20, 38, 37, 47])\n",
      "762 torch.Size([32, 3, 32, 32]) tensor([27, 98, 47, 12, 41, 94, 14, 33, 86,  6, 97, 20, 51, 60, 41, 14, 73, 16,\n",
      "        90, 75,  1, 37, 36, 44, 48, 32, 84, 51, 57, 11, 60,  2])\n",
      "763 torch.Size([32, 3, 32, 32]) tensor([10,  0, 34, 90, 68, 40,  4, 49, 38, 50, 94, 70,  4, 11, 33, 76, 64, 88,\n",
      "        87, 34, 55, 91, 22, 96, 59, 21, 21, 28, 96, 85, 36, 39])\n",
      "764 torch.Size([32, 3, 32, 32]) tensor([57, 83, 48, 28, 11, 60, 84, 37, 99, 94, 37,  9, 15,  3, 92, 16, 56, 31,\n",
      "        91, 52,  3,  2, 89, 57, 99, 55, 33,  3, 19, 37,  2, 16])\n",
      "765 torch.Size([32, 3, 32, 32]) tensor([12, 10, 50, 33, 22, 17, 71, 66, 78, 92, 87,  0, 73, 93,  2, 82, 35, 90,\n",
      "        62, 78, 24, 51, 27, 27, 80, 71, 53, 73, 42, 29, 82, 37])\n",
      "766 torch.Size([32, 3, 32, 32]) tensor([81, 27, 53, 94, 50, 30, 17, 73, 98, 74, 73, 42, 48, 29, 96, 42, 12, 58,\n",
      "        98, 95, 40, 90, 93, 13, 95, 10, 40,  1, 93, 86,  1, 13])\n",
      "767 torch.Size([32, 3, 32, 32]) tensor([21, 63, 29, 25,  9, 90,  7, 55, 80,  1, 42, 74, 49, 74, 37, 30,  8, 91,\n",
      "        33, 32, 63, 83, 12, 56,  7, 92, 23, 93, 19,  7, 36, 47])\n",
      "768 torch.Size([32, 3, 32, 32]) tensor([23, 37, 38, 38, 28,  5, 51,  0,  8, 75, 77, 26, 89, 22,  0, 81, 59, 30,\n",
      "        90, 27, 95, 85, 63, 82, 91, 27, 51,  6, 96, 48, 85, 85])\n",
      "769 torch.Size([32, 3, 32, 32]) tensor([64, 29,  0, 70, 30,  4, 41, 52, 47, 44, 43, 58, 36, 63, 67, 28, 40, 64,\n",
      "         5, 61, 36, 35, 15, 30, 82, 28, 28, 64, 94, 84, 82, 40])\n",
      "770 torch.Size([32, 3, 32, 32]) tensor([30, 71, 65, 68,  9, 25, 50,  5, 67, 61, 27, 94, 93, 69, 97, 20, 41, 18,\n",
      "        73,  3, 28, 69, 35, 69,  4, 17, 68, 63, 61, 58, 73, 40])\n",
      "771 torch.Size([32, 3, 32, 32]) tensor([66, 70, 20, 20, 86, 39, 90, 40,  0, 61, 75, 74,  4, 73, 27, 64, 45, 37,\n",
      "        37, 53, 15, 19, 19, 86, 50, 30,  5, 45, 47, 67, 74, 23])\n",
      "772 torch.Size([32, 3, 32, 32]) tensor([ 0, 95, 55, 18, 16, 78, 89,  6, 93, 86, 85, 87, 19, 39, 31, 17, 18, 89,\n",
      "        16, 61, 86, 33, 46, 94, 52, 82, 68, 32, 41, 78, 83, 38])\n",
      "773 torch.Size([32, 3, 32, 32]) tensor([65, 52, 19, 51, 16, 68, 17, 70, 51,  7, 97, 12, 22, 77, 34, 65, 11, 35,\n",
      "        89, 57, 87, 94,  7, 77, 77, 54, 49, 51, 12, 42, 31, 91])\n",
      "774 torch.Size([32, 3, 32, 32]) tensor([55, 23, 61, 42, 66, 97, 29, 78, 32, 19, 17, 28, 26, 72, 15, 65, 72, 33,\n",
      "        22, 44, 12, 12,  8, 49, 71, 16, 24, 70, 67,  0, 84, 97])\n",
      "775 torch.Size([32, 3, 32, 32]) tensor([19,  1, 74, 44, 57,  4, 16, 30, 47,  1, 33, 50, 87, 54,  1, 26, 37,  2,\n",
      "        15, 50, 52, 56, 49, 22, 33, 10, 65,  5, 95, 74, 55,  7])\n",
      "776 torch.Size([32, 3, 32, 32]) tensor([60, 15,  7, 80, 54,  3, 19, 49, 38, 47, 70, 26, 24, 66, 77, 82, 81, 85,\n",
      "        38, 23, 15, 18, 99, 16, 77,  5, 76, 11, 49, 33, 35, 60])\n",
      "777 torch.Size([32, 3, 32, 32]) tensor([94, 93, 38, 86, 95, 14, 58,  0, 99, 86, 35, 15, 38, 60, 81, 64, 18, 14,\n",
      "        49, 50, 28, 63, 28, 17, 36, 60, 52, 75,  9, 89,  2, 41])\n",
      "778 torch.Size([32, 3, 32, 32]) tensor([24, 50,  9, 77, 35, 27, 68, 65,  2, 28, 15, 72, 93, 63, 79, 64, 73, 29,\n",
      "        55, 92, 48, 72, 74, 75, 29, 86, 25, 31,  2, 75, 88, 66])\n",
      "779 torch.Size([32, 3, 32, 32]) tensor([63, 81, 47, 14,  6, 88, 57,  9, 22, 43, 89, 88, 14, 71, 24, 15, 18, 90,\n",
      "        59, 61, 56, 27, 75, 35, 16, 65, 41, 84, 14, 60, 30, 71])\n",
      "780 torch.Size([32, 3, 32, 32]) tensor([84, 39, 54, 71, 73, 24, 50, 86, 46, 15, 78, 82, 66, 98, 13, 86, 19, 85,\n",
      "        22,  5, 77, 45, 75, 29,  5, 67, 18, 59, 91, 54, 65, 22])\n",
      "781 torch.Size([32, 3, 32, 32]) tensor([62, 95, 58, 52, 25, 20, 31, 98, 27, 81, 68, 64, 56, 59, 42, 27,  6, 54,\n",
      "        45, 19, 67, 95,  4, 59, 48, 33, 68,  7, 23, 41, 63, 55])\n",
      "782 torch.Size([32, 3, 32, 32]) tensor([69, 31, 67, 34, 16, 79, 95, 30,  4, 79, 12, 42, 86, 76, 16, 88,  3, 85,\n",
      "        11, 52,  7, 90, 39,  5, 54, 60, 30, 61, 37, 66, 83, 71])\n",
      "783 torch.Size([32, 3, 32, 32]) tensor([19, 20, 37, 18, 45,  7, 77,  0, 87, 91, 78,  4, 21,  6, 47, 14, 14, 73,\n",
      "        94, 83, 49, 95, 62, 93,  3, 21, 29,  3, 73, 86, 73, 62])\n",
      "784 torch.Size([32, 3, 32, 32]) tensor([24,  1,  4, 60, 74, 28, 39, 61,  2, 95, 64, 80, 85, 57,  7, 29, 76, 25,\n",
      "        79, 10, 83, 74, 82, 94, 10, 29, 99, 43, 66, 83, 44, 89])\n",
      "785 torch.Size([32, 3, 32, 32]) tensor([51, 20, 65, 13, 88, 80, 11, 54, 90, 10, 26, 88, 32, 73, 21, 31, 37, 94,\n",
      "        28, 76, 29, 36, 99,  5, 55, 43, 12, 44, 65, 64, 49, 40])\n",
      "786 torch.Size([32, 3, 32, 32]) tensor([55, 71, 24, 41, 92, 25, 91, 97, 77,  7,  1, 47,  1, 51, 42, 50, 81, 22,\n",
      "         3, 94, 49, 52, 17, 14, 69, 41, 20, 23,  3, 15, 37, 38])\n",
      "787 torch.Size([32, 3, 32, 32]) tensor([74, 71, 76, 82, 28, 73, 29, 29, 98, 48, 69, 94, 35, 46, 92, 90, 69, 44,\n",
      "        99,  0, 32, 65, 56, 76, 24, 96, 67,  6, 99, 22, 98, 20])\n",
      "788 torch.Size([32, 3, 32, 32]) tensor([37, 74, 45, 54, 55, 68,  5, 87, 47, 97,  4, 56, 13, 86, 50, 73, 66, 27,\n",
      "        79, 70, 28, 49, 19, 83, 14, 67,  6, 32, 47, 35, 86, 81])\n",
      "789 torch.Size([32, 3, 32, 32]) tensor([18, 95, 76, 22, 45, 24, 96, 95, 91, 11, 99, 26,  9, 78, 26, 92,  0, 48,\n",
      "        34, 49, 78, 11, 48, 28, 37, 14, 23, 58, 53, 84,  7, 12])\n",
      "790 torch.Size([32, 3, 32, 32]) tensor([ 7, 45, 37, 84, 21, 65,  5, 71, 12, 17, 57, 11, 10, 27, 90, 33, 73,  4,\n",
      "        68, 45, 15, 43, 74,  7, 82, 11, 67, 38, 30, 20,  6, 44])\n",
      "791 torch.Size([32, 3, 32, 32]) tensor([95, 50, 86, 31, 36, 28, 93, 28, 36, 55, 26, 16, 47, 21,  8, 63,  2, 20,\n",
      "        78, 97, 83, 64, 44, 50,  8, 62, 69, 52, 31, 96,  0, 71])\n",
      "792 torch.Size([32, 3, 32, 32]) tensor([ 8, 38, 76, 66, 68, 71, 76, 15, 50, 31, 30, 71,  4, 73, 89, 14, 77, 59,\n",
      "        99, 32, 41, 22, 50, 36, 36, 87, 30, 17, 23, 30, 43, 55])\n",
      "793 torch.Size([32, 3, 32, 32]) tensor([33, 59, 36, 93, 74, 26, 42, 94, 74, 77, 34, 82, 48, 75, 97, 45, 85, 51,\n",
      "        11, 54, 38, 56, 23, 44, 21, 19, 39, 84, 61, 41, 64, 88])\n",
      "794 torch.Size([32, 3, 32, 32]) tensor([49,  6, 25, 51, 82, 76,  9, 83, 89, 88, 10, 44, 83, 62,  1, 24, 48, 44,\n",
      "        78, 82, 94, 82, 46, 42, 96, 33, 40, 39, 49, 12, 18, 74])\n",
      "795 torch.Size([32, 3, 32, 32]) tensor([64, 54, 84, 20, 75, 98, 55, 82, 15, 85, 13, 39, 71, 23, 52, 65, 41, 40,\n",
      "        49, 58,  7, 24, 24, 12, 22, 31, 14, 23, 24, 47,  5, 70])\n",
      "796 torch.Size([32, 3, 32, 32]) tensor([89, 35, 68, 40, 56, 41, 19, 52, 31, 72, 24, 93, 51, 16, 15, 96, 54, 20,\n",
      "        65, 84,  3, 62, 82, 33, 55, 77,  5, 60, 84, 73, 29, 79])\n",
      "797 torch.Size([32, 3, 32, 32]) tensor([62, 42, 37, 63, 11, 42, 52, 98, 90, 86, 86, 85, 43, 76, 85, 79, 59, 35,\n",
      "        34, 74, 14, 41, 88,  3, 49, 35, 64,  6, 52, 53, 56, 65])\n",
      "798 torch.Size([32, 3, 32, 32]) tensor([31,  8, 42,  8, 24,  9, 86, 66, 52,  1, 41, 44,  4,  4, 75, 15, 45, 99,\n",
      "        75, 20,  5, 70, 25, 98, 39,  7, 59, 58, 49, 85, 46, 33])\n",
      "799 torch.Size([32, 3, 32, 32]) tensor([78, 57, 86, 97, 56,  5, 44, 42, 29,  5, 96, 60, 54, 26, 29, 17, 98, 24,\n",
      "        75, 78, 74, 49, 86, 84, 33, 70, 93, 47, 10,  8,  9, 36])\n",
      "800 torch.Size([32, 3, 32, 32]) tensor([62, 66, 89, 23, 94, 20,  0, 89, 26, 15, 21, 69, 41, 49,  1, 83, 27, 88,\n",
      "        41, 16, 67, 79, 57,  6, 70, 70, 46, 26, 85, 13, 21,  4])\n",
      "801 torch.Size([32, 3, 32, 32]) tensor([92,  9, 19, 16, 26, 55, 32, 82, 91, 72, 13, 29, 56, 76, 24, 91, 53, 29,\n",
      "        62, 53, 32,  5,  4, 91, 99,  0, 56,  0, 13, 78, 52, 58])\n",
      "802 torch.Size([32, 3, 32, 32]) tensor([54, 93, 47,  0, 98, 56, 27, 47, 94, 60, 72, 18, 51, 52, 76,  1, 48, 71,\n",
      "        88, 47, 58, 60, 81, 12, 67, 22, 67,  7, 90, 22,  3,  4])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "803 torch.Size([32, 3, 32, 32]) tensor([99, 77, 67, 24, 18, 79, 17, 27,  3, 32, 29, 64, 77, 94, 73, 76, 52,  9,\n",
      "        47, 26, 13, 57,  1, 55, 61, 35, 38, 66, 95, 61, 35, 62])\n",
      "804 torch.Size([32, 3, 32, 32]) tensor([79, 27, 66, 70, 64, 70, 46,  3, 77, 75, 36, 60, 10, 91, 45, 74, 17, 89,\n",
      "        69, 16, 43, 92, 39, 49, 77, 65, 50, 87, 46, 74, 57, 93])\n",
      "805 torch.Size([32, 3, 32, 32]) tensor([38, 71, 87, 40, 98, 33, 64, 58, 40, 77,  4, 78,  1, 61, 22, 28, 18,  4,\n",
      "        17,  2, 61, 48, 66, 58, 33, 64, 13, 40, 53, 96, 66, 33])\n",
      "806 torch.Size([32, 3, 32, 32]) tensor([97, 50, 10, 48, 50, 91, 45, 36, 24, 86, 85,  8, 54, 55, 11,  4, 87, 44,\n",
      "        78,  5, 51,  2,  5, 68, 47,  0, 85, 89,  8, 30, 80, 38])\n",
      "807 torch.Size([32, 3, 32, 32]) tensor([87, 12, 48, 82, 25,  7, 55, 30, 72, 15, 16, 99, 90, 96, 62,  3,  8, 67,\n",
      "        98, 97, 68, 87, 54, 56, 79, 67, 61, 32, 85, 23, 59, 24])\n",
      "808 torch.Size([32, 3, 32, 32]) tensor([98, 50, 46, 79, 73, 85, 82, 83, 89, 34, 66,  4, 84, 94, 76, 38, 57, 15,\n",
      "        54, 10, 43, 15, 19, 42, 39, 75, 65, 96, 86, 96, 57, 50])\n",
      "809 torch.Size([32, 3, 32, 32]) tensor([46, 40, 14, 58, 28, 94, 87, 39, 35, 71, 22, 77, 53, 54, 55,  7, 43, 51,\n",
      "        77, 43, 88, 22, 40, 49, 79, 73, 13, 40, 77, 16, 23, 96])\n",
      "810 torch.Size([32, 3, 32, 32]) tensor([85, 39, 17, 13, 78, 82, 43, 32, 29, 76, 56, 32, 44, 33, 66, 53, 33, 23,\n",
      "        15, 25,  8, 87,  5, 85, 44, 71, 66,  4, 74, 29, 44, 12])\n",
      "811 torch.Size([32, 3, 32, 32]) tensor([45, 86, 22, 95, 97,  4,  7, 80, 48, 72, 64, 17,  7, 19, 38, 53, 25, 75,\n",
      "        68, 99, 98,  9, 51, 75, 32, 26, 91, 61, 47, 62, 43, 46])\n",
      "812 torch.Size([32, 3, 32, 32]) tensor([81, 82, 68, 87, 59, 25,  3, 19, 73, 14, 26, 36, 25, 87, 69, 41, 46, 28,\n",
      "        22, 83, 16, 53, 56, 46, 92, 48, 67, 31, 96, 99, 10, 58])\n",
      "813 torch.Size([32, 3, 32, 32]) tensor([16, 50, 60, 52, 46, 12, 80,  7, 47, 53, 18, 65, 69, 27, 87, 29, 72, 61,\n",
      "        15, 29, 15, 26, 75, 17, 20, 44, 63, 16, 13, 95, 14, 23])\n",
      "814 torch.Size([32, 3, 32, 32]) tensor([25, 70,  4, 57, 18, 55, 48,  6, 20, 76, 42, 52, 59, 90, 24, 34,  2, 23,\n",
      "        20, 33, 21, 30,  1, 75,  6, 98, 12, 60, 22, 14, 22, 42])\n",
      "815 torch.Size([32, 3, 32, 32]) tensor([54,  5, 28, 98,  7, 58, 53, 50,  6, 60, 93,  3, 55, 14, 41,  0, 94, 28,\n",
      "        27, 66, 26, 65, 14, 46, 98,  6, 98, 96, 76, 34, 49, 78])\n",
      "816 torch.Size([32, 3, 32, 32]) tensor([60,  3, 18, 83, 35, 27, 22, 88, 44, 43, 21, 83, 14, 87,  2,  0, 76, 10,\n",
      "        28, 53, 38, 14,  2, 14, 43, 99, 32, 93, 34, 44, 69, 97])\n",
      "817 torch.Size([32, 3, 32, 32]) tensor([81, 30, 98, 62, 83, 33, 23, 31, 14, 58, 55, 56, 22, 86, 34, 96, 34, 83,\n",
      "        28, 75, 25, 87, 25, 16, 58, 56, 54, 83, 63, 77, 98, 26])\n",
      "818 torch.Size([32, 3, 32, 32]) tensor([72, 61, 62, 25,  0, 25, 27, 85, 59, 59, 78, 61, 82, 71, 36, 47,  3, 30,\n",
      "         3, 50, 43,  1, 35, 54, 70,  2, 58, 37, 40, 84, 15, 80])\n",
      "819 torch.Size([32, 3, 32, 32]) tensor([78, 53, 18, 69,  2, 26, 47, 90, 84, 75,  6, 53, 33, 53, 75, 67, 50, 36,\n",
      "        15, 29,  3,  8,  5, 63, 33, 28, 74, 45,  6, 62, 69, 94])\n",
      "820 torch.Size([32, 3, 32, 32]) tensor([45,  8, 11, 77, 78, 65, 31, 63, 16, 60, 13,  3, 19, 36, 32, 56, 38,  3,\n",
      "        49, 45, 80, 88, 63, 67, 12, 70,  1, 83, 30, 62, 43, 31])\n",
      "821 torch.Size([32, 3, 32, 32]) tensor([61,  0, 98, 93, 95, 98,  7, 56, 73, 43,  2, 31,  8, 91, 86, 54, 56, 89,\n",
      "        62, 56, 73, 72,  5, 94, 59, 80, 96,  6, 36, 58, 55,  2])\n",
      "822 torch.Size([32, 3, 32, 32]) tensor([48, 86, 27, 97, 41, 67, 38,  5, 68, 65, 13, 44, 32, 65, 91, 94, 46, 49,\n",
      "        82, 96, 30, 42,  9, 55, 35, 97, 62, 67, 79, 86, 95, 46])\n",
      "823 torch.Size([32, 3, 32, 32]) tensor([18, 41, 75, 21, 32, 84, 59, 28, 30, 59, 70, 62, 12, 96,  6, 59, 19, 44,\n",
      "        40, 37, 96, 10, 91, 96, 26,  8, 19, 50, 71, 75, 95, 37])\n",
      "824 torch.Size([32, 3, 32, 32]) tensor([ 2, 61, 71, 41,  9, 97, 89, 73,  1,  9,  8, 68, 89,  6, 39, 68, 23, 58,\n",
      "        59, 80, 39, 49,  0, 79, 42, 36, 17,  9,  5, 31, 43, 54])\n",
      "825 torch.Size([32, 3, 32, 32]) tensor([45, 79, 92, 85, 96, 56, 88,  4, 57, 80,  6, 79, 46, 45, 88, 84, 36, 45,\n",
      "        99, 46, 34, 69, 52, 97, 10, 56, 39,  5, 34, 29, 64, 29])\n",
      "826 torch.Size([32, 3, 32, 32]) tensor([43, 26, 50,  6, 41, 34,  2, 51, 49, 43, 79, 51, 38, 77, 32, 10, 40, 30,\n",
      "        10, 51, 38, 38, 85, 72, 41, 59, 31, 90, 72, 12, 91, 52])\n",
      "827 torch.Size([32, 3, 32, 32]) tensor([94, 81, 63, 34, 21,  5, 19, 49, 86,  5, 13, 24, 79, 12, 47, 36, 78, 37,\n",
      "        78, 69, 85,  7,  0, 20,  0, 48, 67, 34, 97, 95, 34, 53])\n",
      "828 torch.Size([32, 3, 32, 32]) tensor([71, 37, 78, 20, 71, 38, 79,  8, 40, 35, 37, 66, 72,  4,  8, 94,  6, 61,\n",
      "        80, 19, 46, 40, 86, 96, 20, 32,  3, 88, 18, 34, 51, 39])\n",
      "829 torch.Size([32, 3, 32, 32]) tensor([72, 77, 32, 90, 93,  1, 87, 18, 68, 61, 17, 71, 15, 45, 61,  1, 46, 78,\n",
      "         2, 10, 11, 20, 55, 16, 41,  4, 69, 51, 70, 68,  8, 81])\n",
      "830 torch.Size([32, 3, 32, 32]) tensor([31, 83, 69, 53, 86,  5, 49, 25, 11, 42, 73, 27,  6, 56, 79, 85, 53, 30,\n",
      "        17, 94, 59, 87, 92, 35, 92, 66, 34, 81, 80, 53,  0, 90])\n",
      "831 torch.Size([32, 3, 32, 32]) tensor([71, 76, 13, 24, 57, 41, 56, 11, 56, 38, 24,  6, 46, 90, 50, 11, 96, 81,\n",
      "        38, 16, 91, 94, 29, 51, 61, 27, 22, 12, 65, 63, 46, 98])\n",
      "832 torch.Size([32, 3, 32, 32]) tensor([60, 50, 55, 59, 85, 70,  2, 24, 90, 66, 24, 76,  1,  7, 65, 91, 12, 29,\n",
      "        52, 49, 39,  2, 81, 39, 49, 51, 30, 17, 43, 16, 23, 18])\n",
      "833 torch.Size([32, 3, 32, 32]) tensor([37, 23, 49, 53, 54,  9, 99, 84, 82, 49, 54, 16, 61, 95, 74,  4, 30, 39,\n",
      "        72, 50, 80, 93, 65, 53, 14, 78, 24, 44, 22, 91, 99, 85])\n",
      "834 torch.Size([32, 3, 32, 32]) tensor([48, 90, 68, 52, 27, 57, 89, 62, 63, 72,  1, 33, 17, 53, 68, 23, 32, 81,\n",
      "        10, 80, 51, 20, 22, 94, 16, 82, 92, 70, 35, 14, 38,  5])\n",
      "835 torch.Size([32, 3, 32, 32]) tensor([32, 37, 56, 23, 10, 78, 85, 54, 16,  4, 30, 22, 35,  1, 91, 90, 68, 53,\n",
      "        84, 72, 57, 74,  8, 26, 66, 19, 13, 79, 54, 11, 79, 74])\n",
      "836 torch.Size([32, 3, 32, 32]) tensor([29, 89, 88,  9, 40, 38,  1, 66,  6, 82, 91, 41, 85, 68, 85, 27, 90, 49,\n",
      "        61, 45, 55, 58, 30, 87, 30, 66, 69, 51, 92, 69,  6, 71])\n",
      "837 torch.Size([32, 3, 32, 32]) tensor([46, 90, 34, 93, 66, 37, 86, 44, 30, 52,  7, 51,  4, 52, 42, 64, 17, 36,\n",
      "        58, 83, 11, 27, 94,  9, 19, 43,  4, 77, 82, 11, 11, 89])\n",
      "838 torch.Size([32, 3, 32, 32]) tensor([16, 96,  6, 40, 15, 69,  9, 75, 16, 82, 24, 19, 67, 22, 59, 77, 19,  1,\n",
      "        42, 12, 42, 15, 24,  8, 81, 54, 30, 73,  6, 44,  1, 63])\n",
      "839 torch.Size([32, 3, 32, 32]) tensor([91, 99,  4, 94, 40, 51, 35, 46, 28, 62, 61, 51, 14, 92, 62, 73,  3,  6,\n",
      "        31, 20, 73, 38, 34,  3,  1, 92, 21,  3, 25, 84, 67, 96])\n",
      "840 torch.Size([32, 3, 32, 32]) tensor([18,  9,  9,  0, 32,  6, 70, 87,  7, 10, 90, 29,  6, 94, 53, 70, 32, 11,\n",
      "        63, 86, 55, 33, 46, 71,  3, 34, 96, 29, 24, 57, 47, 49])\n",
      "841 torch.Size([32, 3, 32, 32]) tensor([67, 57, 79, 56,  0, 13, 56, 83, 49, 63, 15, 29, 31, 40, 29,  9, 32, 51,\n",
      "        37, 53, 84, 96, 31, 93, 22, 99, 68, 78, 11, 12, 54,  2])\n",
      "842 torch.Size([32, 3, 32, 32]) tensor([44, 50, 91, 54, 95, 84, 45, 47, 94, 44, 91, 31, 19, 96, 18,  6, 72, 79,\n",
      "        86, 93,  9, 90, 97, 29, 16, 91, 42, 95, 96, 56, 65, 39])\n",
      "843 torch.Size([32, 3, 32, 32]) tensor([40, 68, 97, 82, 34, 41, 64, 38,  6,  0, 41, 65, 81, 40,  7, 24, 91, 85,\n",
      "        42, 86, 43, 27, 90, 24, 56, 77, 88, 27, 85, 86, 42, 13])\n",
      "844 torch.Size([32, 3, 32, 32]) tensor([35, 37, 23, 40,  4, 40, 71, 81, 85, 35, 68, 72, 44, 40, 63, 57, 38, 56,\n",
      "        18,  3,  3, 94, 89, 81, 86, 55, 21, 38, 82, 16, 59, 31])\n",
      "845 torch.Size([32, 3, 32, 32]) tensor([37, 55, 84, 44, 89, 20, 25, 53, 11, 51, 38, 69, 74, 47, 52, 78, 48, 64,\n",
      "        82, 30, 31, 11, 70, 33, 44, 56, 27,  3,  9, 61, 19, 10])\n",
      "846 torch.Size([32, 3, 32, 32]) tensor([ 6, 20, 45,  6,  2, 18, 79, 14, 60, 76, 54, 95, 80, 39, 48, 63, 64, 65,\n",
      "        91, 30, 33, 98, 63, 37, 16, 31, 41, 81, 57, 12, 99, 13])\n",
      "847 torch.Size([32, 3, 32, 32]) tensor([47, 58,  2, 65,  8, 19,  2, 86, 32, 77, 51,  9, 78, 13, 14, 26, 75, 99,\n",
      "        81, 45, 70, 40, 64, 58, 23, 35, 30, 84, 38, 43, 69, 68])\n",
      "848 torch.Size([32, 3, 32, 32]) tensor([93, 33, 82, 34, 73,  3,  1, 46,  8, 76, 82, 99, 86, 91, 52, 84, 50,  2,\n",
      "        58, 62, 95,  4, 62, 92, 19,  7, 30, 75, 30, 98, 44, 75])\n",
      "849 torch.Size([32, 3, 32, 32]) tensor([83,  7, 79, 44, 21, 47, 68,  0, 29, 89, 45, 62, 70, 51, 15, 20, 32, 44,\n",
      "        50, 50, 76, 75, 92, 96,  6, 47, 78, 91,  2, 33,  5, 28])\n",
      "850 torch.Size([32, 3, 32, 32]) tensor([19, 37, 78, 16, 57, 77, 82, 55, 86, 61, 21, 39, 71, 92, 56, 50, 67, 38,\n",
      "        91, 44, 58, 89, 20, 81, 85, 69, 40, 41, 25, 61, 31, 44])\n",
      "851 torch.Size([32, 3, 32, 32]) tensor([87, 43, 70, 83, 72, 75, 97, 29, 92, 85, 30, 37,  2,  1, 64, 14,  3, 66,\n",
      "        15, 43, 84, 80, 66, 15, 22, 14, 41,  2, 48, 12,  7, 36])\n",
      "852 torch.Size([32, 3, 32, 32]) tensor([45, 29, 57, 71, 14, 24, 32, 97, 38, 50,  4, 34, 13, 90, 64, 55, 82, 93,\n",
      "        35, 65, 66, 29, 69, 64, 58, 50, 12, 41, 14, 99, 24, 57])\n",
      "853 torch.Size([32, 3, 32, 32]) tensor([38, 22, 80, 79, 36, 97, 52, 52, 12, 46, 14, 16, 59,  3, 85, 35, 36, 71,\n",
      "        86, 24, 76, 63, 86, 38, 88, 26, 46, 18, 65, 98, 59, 92])\n",
      "854 torch.Size([32, 3, 32, 32]) tensor([82, 65, 58, 58, 50, 26, 47,  2,  8, 44, 95, 37, 61, 70, 35, 14, 41, 49,\n",
      "        92, 24, 61, 49, 38,  2, 52, 73, 79, 33, 45, 50, 49, 72])\n",
      "855 torch.Size([32, 3, 32, 32]) tensor([23, 92, 12, 85, 12, 31, 75, 52, 96, 65, 34,  2, 85, 16, 50, 80, 32, 62,\n",
      "        32, 19, 15, 85, 36, 96, 82, 50, 24, 56, 35,  4,  4, 95])\n",
      "856 torch.Size([32, 3, 32, 32]) tensor([12, 88, 16, 80, 75, 67,  7, 81, 51, 25, 14, 70, 59, 99, 73, 80, 44,  6,\n",
      "        91, 13, 39, 50, 64, 21,  9, 76, 92, 35, 32, 10, 87, 34])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "857 torch.Size([32, 3, 32, 32]) tensor([15, 96, 54, 21, 40, 66, 81, 41, 30,  3, 56, 37, 79, 80, 93,  0, 32, 33,\n",
      "        71, 26, 64, 52, 29, 76,  3, 52, 81, 88, 52, 67, 43, 35])\n",
      "858 torch.Size([32, 3, 32, 32]) tensor([85, 88,  7, 55, 88, 80, 57, 48, 96, 12, 10, 93, 34, 49, 14, 76, 64, 98,\n",
      "        86, 18, 13, 93, 10, 59, 99, 82, 81, 59, 13, 62, 93, 15])\n",
      "859 torch.Size([32, 3, 32, 32]) tensor([65, 58, 59, 40, 65, 46, 12, 53, 88, 83, 21, 50, 97, 34, 10, 69, 62, 56,\n",
      "        43, 25, 61, 39, 56, 14, 45, 55, 60, 86, 66, 60, 50, 76])\n",
      "860 torch.Size([32, 3, 32, 32]) tensor([48, 92, 42, 90, 28, 46, 61, 26,  7, 86, 96, 14, 35, 63, 41, 54, 83, 25,\n",
      "        96, 15, 24, 33, 19,  3, 74, 43, 72, 66, 88, 18, 34, 55])\n",
      "861 torch.Size([32, 3, 32, 32]) tensor([71, 40, 59, 40, 90, 73, 48, 89, 31, 65, 75, 42, 63, 55, 75, 66, 58, 63,\n",
      "        75, 34, 83, 19, 63, 72, 92, 15, 79, 26, 24, 53, 64, 71])\n",
      "862 torch.Size([32, 3, 32, 32]) tensor([86, 33, 32, 31, 58, 34, 64, 31, 20, 62, 36, 78, 33, 26, 36, 17, 70, 81,\n",
      "        53, 21, 84, 59, 28,  0,  7, 93, 72, 49, 92, 45, 56, 97])\n",
      "863 torch.Size([32, 3, 32, 32]) tensor([45, 29, 86, 47, 40, 39, 82, 72,  3, 81, 69, 49,  8, 97, 63, 25, 79, 59,\n",
      "        19, 38, 89, 23,  9, 59, 40, 89, 58, 31, 73, 38, 15, 99])\n",
      "864 torch.Size([32, 3, 32, 32]) tensor([26, 62, 27, 39, 10, 58, 42, 68, 77, 16,  9, 79, 70, 76, 87, 97, 41, 80,\n",
      "        92, 25, 90, 31, 89, 12, 51,  2, 69, 50,  5, 90, 86, 82])\n",
      "865 torch.Size([32, 3, 32, 32]) tensor([67,  6, 30, 19,  8, 33, 61, 60, 90, 48, 33, 95, 46,  9, 79,  0, 61, 53,\n",
      "        95, 87,  9, 75, 46, 75, 23,  7, 96, 48, 50, 66, 68, 11])\n",
      "866 torch.Size([32, 3, 32, 32]) tensor([36, 75, 62, 29, 40, 39, 56, 74, 84, 28, 33, 54, 76,  4, 62, 52, 84, 36,\n",
      "        50, 87, 87, 22, 77, 35, 47, 55, 69, 50, 63, 99, 86, 27])\n",
      "867 torch.Size([32, 3, 32, 32]) tensor([50, 52,  1, 98, 65, 92, 90, 78, 11, 83, 62, 97, 89, 90, 88, 97, 70, 62,\n",
      "         9, 64,  0, 41, 89, 89, 35, 90, 24, 16, 53,  1, 38, 25])\n",
      "868 torch.Size([32, 3, 32, 32]) tensor([68, 17, 71, 24, 48, 67,  7, 15, 88,  9, 77, 27, 84, 47, 45, 18, 29, 67,\n",
      "        52, 27, 55, 21, 37, 69,  9, 84, 88, 93, 38, 90, 67, 31])\n",
      "869 torch.Size([32, 3, 32, 32]) tensor([57, 73, 17, 80, 98, 21, 63, 76, 47, 54, 97, 65, 36, 84, 36,  0, 93, 15,\n",
      "        67, 45, 38, 93,  8, 19, 86,  6, 42, 21,  9,  1, 51, 45])\n",
      "870 torch.Size([32, 3, 32, 32]) tensor([65, 44, 35, 50, 26,  1, 98, 99, 29, 71, 74,  6, 59, 59, 42, 88, 61, 19,\n",
      "         8, 49,  3, 45, 22, 48, 82, 90, 47,  6, 90, 68, 17, 34])\n",
      "871 torch.Size([32, 3, 32, 32]) tensor([87,  9, 99,  8, 49, 36,  5, 36, 26, 98, 75, 74, 32, 96, 16, 92,  6, 80,\n",
      "        15, 54, 16, 45,  8,  2, 72, 59, 72, 63, 90, 39, 73, 91])\n",
      "872 torch.Size([32, 3, 32, 32]) tensor([58, 61, 15, 86, 74, 44,  6, 69, 67, 59,  5, 45, 34, 36, 70, 38, 91, 74,\n",
      "        29, 31, 31, 73, 28, 78, 34, 11, 44, 87, 68, 39,  8, 12])\n",
      "873 torch.Size([32, 3, 32, 32]) tensor([57, 64, 50, 46, 70, 51,  0, 78, 94, 77,  3, 41, 39, 30, 80, 75, 41, 64,\n",
      "        43, 46, 92, 21, 32, 53, 75, 63, 65, 42, 18, 79,  3, 71])\n",
      "874 torch.Size([32, 3, 32, 32]) tensor([75, 19, 31, 66, 28, 75, 77, 21,  7, 21, 64, 39, 23, 69, 57, 70, 88, 97,\n",
      "        33, 42, 20, 21, 19, 41,  5, 62, 23, 49, 13, 66, 41, 42])\n",
      "875 torch.Size([32, 3, 32, 32]) tensor([28, 52, 50, 61, 16, 26, 41, 83, 83,  5, 51, 90, 28,  3, 93, 25, 57, 17,\n",
      "        26, 17, 45, 38, 25, 86, 75, 48, 26,  5, 41, 13, 65, 90])\n",
      "876 torch.Size([32, 3, 32, 32]) tensor([44, 58, 98, 67, 72, 94, 92, 18, 49,  2,  3, 55, 65, 51, 17, 41, 11, 91,\n",
      "        88, 25, 30,  4, 76, 79, 64, 50, 17, 29, 70, 34, 51, 92])\n",
      "877 torch.Size([32, 3, 32, 32]) tensor([15, 26, 96, 96, 83, 56,  1, 59, 36, 95, 92, 61,  7, 75, 11, 54, 58, 17,\n",
      "        95, 68, 35, 55, 45, 61, 68, 98, 90, 21,  7, 74, 92, 13])\n",
      "878 torch.Size([32, 3, 32, 32]) tensor([80, 78, 36, 46, 24, 51, 88, 90, 10, 87, 75, 45, 29, 78, 23, 55,  3,  0,\n",
      "        13, 61, 11, 80, 13, 73, 36, 29, 26, 36, 32, 28, 57, 43])\n",
      "879 torch.Size([32, 3, 32, 32]) tensor([58,  2, 88,  3, 80, 61, 68, 91, 47, 69, 15, 66, 57, 95, 87, 17, 31, 96,\n",
      "         0, 61, 72, 62, 70, 40, 85,  5, 23,  4, 81, 51, 92, 26])\n",
      "880 torch.Size([32, 3, 32, 32]) tensor([11, 83,  3, 55, 20, 22, 71, 96,  1, 27, 13, 93, 76, 91, 50, 80, 24, 64,\n",
      "        23, 35, 52, 54, 68, 85,  1, 32, 58, 37,  6, 87, 83, 34])\n",
      "881 torch.Size([32, 3, 32, 32]) tensor([42,  5, 62, 32, 93,  8, 17, 80, 32, 11, 21, 72, 10, 30, 86, 88, 31, 45,\n",
      "        24, 50, 66, 97, 44, 92,  4, 15, 77,  0, 97, 48, 93, 21])\n",
      "882 torch.Size([32, 3, 32, 32]) tensor([39, 98, 61,  6, 66,  3, 70, 65, 81, 32, 54, 12, 21, 17, 94, 53, 16, 99,\n",
      "        53, 22, 71, 80, 37, 47, 94, 16, 31, 18, 18, 99, 92, 56])\n",
      "883 torch.Size([32, 3, 32, 32]) tensor([10,  8, 58, 85, 87,  8, 77, 96, 11, 87, 17, 68, 58, 95, 19, 56, 26, 72,\n",
      "        35, 26, 63, 74, 36, 58, 79, 41, 62, 81, 47, 63,  2, 69])\n",
      "884 torch.Size([32, 3, 32, 32]) tensor([13, 96,  6, 38, 88,  0, 87, 64, 64, 38, 98,  0, 27, 63, 69, 50, 35, 74,\n",
      "        18, 53, 46, 50, 80, 84, 93, 61, 89, 87, 77, 57, 46,  2])\n",
      "885 torch.Size([32, 3, 32, 32]) tensor([69, 51, 37, 14,  5, 58, 81, 42,  9, 35,  1, 94, 55,  0, 19, 14, 62, 26,\n",
      "         8, 31, 70, 92, 22, 11, 88,  8, 26, 54, 35, 85, 81, 62])\n",
      "886 torch.Size([32, 3, 32, 32]) tensor([79, 56, 57, 65,  9, 87, 82, 63, 81, 31, 54, 90, 39, 61, 78, 82, 83,  8,\n",
      "        59, 78, 29, 31, 36, 50, 43, 45, 69, 42, 46, 16, 44, 19])\n",
      "887 torch.Size([32, 3, 32, 32]) tensor([75, 88, 51, 22,  5, 22,  3, 99, 92, 77, 19, 45, 28, 88, 28, 14, 29, 30,\n",
      "         8, 60, 41, 27, 73, 14,  4,  4, 51, 80, 85, 12, 29, 16])\n",
      "888 torch.Size([32, 3, 32, 32]) tensor([19, 16, 80, 62, 39, 93, 74, 19, 91, 34, 15, 67, 15, 71, 76,  2, 68, 70,\n",
      "        57, 24, 71,  3, 40, 54, 16, 24, 20, 44, 91, 98,  5, 62])\n",
      "889 torch.Size([32, 3, 32, 32]) tensor([ 4, 53, 34, 78, 14, 22, 40, 55, 59, 27, 66, 16, 24, 19,  7, 56, 16, 58,\n",
      "        18, 58, 20, 24, 56, 18, 76, 71, 72, 47, 96,  5, 65, 62])\n",
      "890 torch.Size([32, 3, 32, 32]) tensor([88, 52, 96, 86, 67, 71, 40, 76, 30, 70, 95, 25, 23, 25, 10, 22, 56, 64,\n",
      "        32, 32,  8, 98, 38, 84, 58, 34, 47, 39, 92, 93, 15,  9])\n",
      "891 torch.Size([32, 3, 32, 32]) tensor([94, 26, 32, 80, 42, 17, 98, 17,  1, 52, 28, 63,  3, 39, 10, 78, 63, 55,\n",
      "        59, 65, 64, 30, 31, 66,  0, 12, 77, 89, 24, 37, 30, 20])\n",
      "892 torch.Size([32, 3, 32, 32]) tensor([28, 50, 71, 51, 98, 24,  6, 30, 75, 28, 78, 68, 68, 83, 29, 63, 43, 35,\n",
      "        79, 54,  2, 23,  0, 29, 86, 78, 77, 94, 38, 17, 60, 84])\n",
      "893 torch.Size([32, 3, 32, 32]) tensor([82, 88, 31,  4, 85, 23, 78, 16,  5, 87, 25, 32, 63, 64, 56, 46, 69, 82,\n",
      "        88, 42, 47, 20, 80, 54, 88, 76, 60, 53, 46, 11, 69, 99])\n",
      "894 torch.Size([32, 3, 32, 32]) tensor([79, 40, 40, 87, 42, 67, 91, 38,  4, 22, 82, 98, 48, 62, 64, 40, 97, 79,\n",
      "        90, 36, 85, 90, 35, 28, 34, 55, 63, 84, 56, 50, 16, 48])\n",
      "895 torch.Size([32, 3, 32, 32]) tensor([68, 13, 91, 58, 70, 42, 66,  9, 73, 69,  2, 97, 53, 59,  3, 48,  1, 37,\n",
      "        59, 26, 83, 42, 47, 88, 70, 39, 56, 40, 66, 78, 59, 90])\n",
      "896 torch.Size([32, 3, 32, 32]) tensor([26, 22, 58, 18, 99, 58, 61,  1, 54,  2, 50, 17, 38, 15, 63, 17, 67, 95,\n",
      "        98, 28, 31, 51, 97, 74, 21, 65, 94, 17, 36, 21, 89, 87])\n",
      "897 torch.Size([32, 3, 32, 32]) tensor([90,  7, 94, 22, 55, 62, 10, 95, 75, 53,  0, 80, 68, 20, 83, 87, 15, 42,\n",
      "        74, 69, 66, 72, 60, 42, 94, 65, 28, 65, 44, 70, 49, 87])\n",
      "898 torch.Size([32, 3, 32, 32]) tensor([69, 37, 44,  1, 98, 67,  6, 64, 60, 32, 69,  8, 64, 32, 47, 21, 72, 50,\n",
      "        12, 77, 33, 90,  3, 17, 74, 98, 26, 60,  1, 67, 23, 61])\n",
      "899 torch.Size([32, 3, 32, 32]) tensor([ 9, 76, 39, 41, 89, 15, 32, 76, 90, 33, 20, 87, 60,  4, 48, 60, 53, 59,\n",
      "        28, 73, 41, 93,  8, 59, 75, 97, 34, 10, 54, 22, 29, 53])\n",
      "900 torch.Size([32, 3, 32, 32]) tensor([ 3, 90, 34, 24, 47, 35, 99, 39, 50, 96, 86, 51, 86, 62, 68, 46, 92, 92,\n",
      "         4, 11, 74, 67, 74, 68, 42, 33, 58, 95, 67, 88, 36, 28])\n",
      "901 torch.Size([32, 3, 32, 32]) tensor([39, 24, 47, 75, 97, 20, 46, 16, 11, 31, 85, 68, 62,  8,  4,  4,  8, 70,\n",
      "         9, 70, 98,  3, 44, 14,  2, 81, 50, 66, 81, 14, 63, 31])\n",
      "902 torch.Size([32, 3, 32, 32]) tensor([35, 95, 15, 30, 12, 18, 68, 86, 68, 54, 27, 94, 32,  5, 22, 57, 76, 28,\n",
      "        13, 48, 98, 68, 20, 96, 12, 39, 94, 39, 20, 88, 37, 22])\n",
      "903 torch.Size([32, 3, 32, 32]) tensor([79,  9,  8, 96, 80, 20, 91, 23,  7, 16,  3, 80, 87, 45, 66, 92, 44, 75,\n",
      "         0, 56, 15, 69, 44, 73, 90, 22, 39, 40,  2, 80, 60, 53])\n",
      "904 torch.Size([32, 3, 32, 32]) tensor([52, 31, 27, 11, 68, 80, 94, 31, 14, 44, 26, 63, 45,  7, 45, 95, 75,  2,\n",
      "        88, 64, 31, 15, 92, 25, 54,  1, 58, 46, 69, 42, 46,  6])\n",
      "905 torch.Size([32, 3, 32, 32]) tensor([96, 12, 44,  0, 50, 47,  2, 25, 23,  2, 16,  1, 56, 87, 39, 31, 91, 66,\n",
      "        41, 28, 21, 12, 47, 40, 29, 93, 72, 89, 80, 91, 15, 11])\n",
      "906 torch.Size([32, 3, 32, 32]) tensor([34, 30, 68, 14, 76, 35, 27, 85, 70,  1, 40, 77, 39, 22,  1, 25, 81,  5,\n",
      "        87, 79,  6, 72, 19, 25, 38, 57, 75, 21, 39,  8, 49, 97])\n",
      "907 torch.Size([32, 3, 32, 32]) tensor([81, 17, 56, 48, 94, 24, 45, 93, 20, 65, 84, 11, 62,  2, 41, 12, 42, 86,\n",
      "         2, 83, 78, 42, 73, 31, 85, 68, 70, 78, 76, 23,  8, 81])\n",
      "908 torch.Size([32, 3, 32, 32]) tensor([85, 20, 36, 91, 71, 70, 56, 68, 57, 67,  6, 50, 98, 42, 52,  3, 98, 47,\n",
      "        23, 90,  5, 97, 64, 49,  0, 62,  3, 94, 17, 35, 79, 21])\n",
      "909 torch.Size([32, 3, 32, 32]) tensor([28, 76,  8, 80, 32, 89, 57,  3, 11, 43, 59,  1,  4, 51, 52, 95, 41, 37,\n",
      "        70,  4, 38, 89, 40, 91,  3, 23, 11, 35, 48, 19, 39, 53])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "910 torch.Size([32, 3, 32, 32]) tensor([20, 13, 54, 42, 86, 23, 90, 50, 84, 28, 69, 54, 19, 15, 54, 68, 19, 32,\n",
      "        12, 47, 96, 99,  1, 66, 46, 93,  9, 95, 95, 12, 47, 71])\n",
      "911 torch.Size([32, 3, 32, 32]) tensor([92, 12, 98, 33, 95, 76, 47, 26, 27, 57, 86, 30, 24, 81, 89, 93, 32, 55,\n",
      "        19, 12, 41, 94, 43,  9, 42,  6, 56, 79, 19, 73, 77,  5])\n",
      "912 torch.Size([32, 3, 32, 32]) tensor([57, 91, 94, 70, 73, 97, 33, 69, 48, 18, 28, 36, 47, 58,  4, 52, 12, 51,\n",
      "        90, 19, 14, 35, 62, 11, 21, 38, 42, 65, 75, 19, 74, 85])\n",
      "913 torch.Size([32, 3, 32, 32]) tensor([29, 79, 44,  2, 90, 35, 39, 51,  3,  4,  8, 90, 40, 72, 51,  5, 40, 66,\n",
      "        46, 87, 77, 62, 83, 15, 37, 14, 23, 54, 35, 43, 56, 39])\n",
      "914 torch.Size([32, 3, 32, 32]) tensor([17, 87, 25, 94, 73, 74, 95, 36, 76, 55, 64, 15, 93, 74, 20, 58, 72, 28,\n",
      "         2, 96, 33,  8,  0, 16, 42, 73, 24,  2, 60, 75, 64, 21])\n",
      "915 torch.Size([32, 3, 32, 32]) tensor([ 5, 72, 82, 61, 91, 28, 21, 18,  7, 43, 55, 88, 91, 74, 15, 47, 76, 13,\n",
      "        16, 32, 94, 76, 19, 92, 97, 16, 76, 25, 30, 13, 57, 60])\n",
      "916 torch.Size([32, 3, 32, 32]) tensor([46, 11, 84, 40, 67, 33, 50,  5, 88, 61, 37, 11, 59, 35, 37, 28, 47, 90,\n",
      "        38, 86, 95, 38, 45, 55, 46, 31, 93, 18, 29,  0, 84, 31])\n",
      "917 torch.Size([32, 3, 32, 32]) tensor([47, 10, 66, 58, 24, 49, 26, 73, 90, 18, 90, 71,  2, 59, 73, 17, 10, 51,\n",
      "        55, 62, 37, 93, 90, 66, 34, 35, 49, 40, 67, 29, 52, 45])\n",
      "918 torch.Size([32, 3, 32, 32]) tensor([34, 36, 19, 15, 48, 27, 54, 55, 30,  6, 82, 11, 79, 79, 47, 63, 39, 89,\n",
      "        24, 10, 69,  7, 90, 30, 69, 51, 99, 29, 25, 68, 15, 13])\n",
      "919 torch.Size([32, 3, 32, 32]) tensor([63, 43, 27,  9, 60, 71, 28, 25, 42, 75, 90, 40, 43, 42, 88, 95,  8, 47,\n",
      "        36, 84, 30, 16, 99,  9,  6, 83, 37, 38, 37, 28, 55, 10])\n",
      "920 torch.Size([32, 3, 32, 32]) tensor([29, 83, 80, 48, 55, 60, 31, 20, 20, 93, 66,  0,  9, 87, 82, 67,  3, 37,\n",
      "        32, 88, 99,  2, 69, 66, 64, 57, 43, 47, 96, 37,  1, 76])\n",
      "921 torch.Size([32, 3, 32, 32]) tensor([91, 60, 52, 39, 14,  8, 52, 95, 75, 22, 65, 19,  7, 29, 60, 91,  0, 30,\n",
      "        53, 23, 62, 88,  0,  5, 71, 69, 17, 55, 87, 61, 72, 15])\n",
      "922 torch.Size([32, 3, 32, 32]) tensor([17, 14, 22, 18, 55, 90, 50, 17, 36, 69, 55, 67, 49, 90,  4, 97, 47, 38,\n",
      "        11, 85, 73, 77, 57, 75, 87, 90, 87, 61, 89, 97, 80, 15])\n",
      "923 torch.Size([32, 3, 32, 32]) tensor([27, 36,  5, 49,  2, 60, 57, 16,  6, 87, 58, 72, 22, 10, 25, 93, 95, 65,\n",
      "        74, 93, 63, 10, 95, 85, 76, 16, 64, 68,  4, 44, 26, 37])\n",
      "924 torch.Size([32, 3, 32, 32]) tensor([76, 34, 25, 21,  8, 41, 97, 71, 15,  0, 48, 40, 74, 38, 90, 77, 73,  3,\n",
      "        56, 84, 13, 68, 63, 40, 57, 85, 62, 58, 94, 39, 28, 67])\n",
      "925 torch.Size([32, 3, 32, 32]) tensor([33, 62, 90, 47, 95, 82, 41, 19,  2, 16, 34, 10, 66,  8, 63, 63, 71, 40,\n",
      "        42, 62, 36, 46, 57, 59, 45, 93, 23, 15, 93, 70, 12, 70])\n",
      "926 torch.Size([32, 3, 32, 32]) tensor([46, 62, 57, 62, 32, 97, 12, 39, 14, 65, 62, 48, 79, 30, 40,  2, 86, 59,\n",
      "        99, 75, 61, 19, 99,  9, 86, 59,  2, 55, 52, 34, 60, 12])\n",
      "927 torch.Size([32, 3, 32, 32]) tensor([79, 53, 35, 26, 47, 74, 87, 69, 92, 19, 53, 55,  4, 31, 73, 53,  7, 10,\n",
      "        18, 48, 57, 38, 38, 87, 69, 42, 43, 32,  8, 57,  9, 96])\n",
      "928 torch.Size([32, 3, 32, 32]) tensor([46, 64, 71, 11, 41, 42, 69, 69, 70, 63, 50, 98, 42, 41, 58, 41, 36, 43,\n",
      "        19, 44, 37, 49, 76, 76, 38, 11, 93, 35, 72, 11, 17, 71])\n",
      "929 torch.Size([32, 3, 32, 32]) tensor([38, 33, 49,  1, 16, 47,  5, 34, 16, 83, 62, 58, 47, 14,  6, 56, 51, 18,\n",
      "         1,  4, 65, 65, 68, 52, 58, 93, 80, 65, 77, 43, 12, 25])\n",
      "930 torch.Size([32, 3, 32, 32]) tensor([46, 76, 96, 56, 92, 30, 59, 15, 68, 94,  5, 36, 32, 32, 17, 32, 82,  2,\n",
      "         7, 11, 68, 59, 96, 14, 43, 74,  1, 26, 80, 41, 24, 33])\n",
      "931 torch.Size([32, 3, 32, 32]) tensor([38, 23, 29, 18,  1, 51, 31,  1, 41, 22, 30, 10, 83, 58, 43, 77, 47, 81,\n",
      "        85,  0, 89, 55, 95,  1, 30, 19, 67, 84, 94, 50,  1, 40])\n",
      "932 torch.Size([32, 3, 32, 32]) tensor([21, 59, 16, 49,  1, 69, 57, 73, 43, 75, 35, 15, 36, 46, 24, 40, 86, 86,\n",
      "        22, 84, 21, 77, 74,  5, 90, 11, 35,  3, 32, 10, 77, 47])\n",
      "933 torch.Size([32, 3, 32, 32]) tensor([59, 54, 47,  6, 74,  5,  6,  4, 50, 98,  4, 88, 21, 48, 54, 43, 53, 80,\n",
      "        43, 56, 48, 86, 26, 17, 98, 92, 81, 61, 81, 64, 28, 78])\n",
      "934 torch.Size([32, 3, 32, 32]) tensor([24, 79, 88, 83, 83, 95, 39, 11, 18, 67, 11, 74, 63, 87,  8, 99, 10, 84,\n",
      "        78,  1, 31, 37, 57, 22, 68, 79, 52, 81, 27, 64, 91, 41])\n",
      "935 torch.Size([32, 3, 32, 32]) tensor([11, 32,  9, 63, 31, 25, 91, 33, 44, 70, 48, 16, 16, 18, 46,  2, 97, 46,\n",
      "        77,  1, 90, 43, 16, 60, 88, 49, 27,  3, 11, 80, 39, 24])\n",
      "936 torch.Size([32, 3, 32, 32]) tensor([21, 80, 41, 24, 59, 37, 99, 35,  6, 74, 30, 46, 73, 84, 87, 30, 11, 59,\n",
      "        55, 61, 77, 93, 98, 58, 89, 13, 57, 18, 77,  7, 20, 47])\n",
      "937 torch.Size([32, 3, 32, 32]) tensor([71, 96, 88, 89,  9, 24, 79, 97, 54,  5, 75,  9, 79, 56,  3, 95, 64, 98,\n",
      "        78, 51, 59, 92, 14, 94,  5, 96, 97,  4,  0, 25, 96, 79])\n",
      "938 torch.Size([32, 3, 32, 32]) tensor([18, 19, 82, 40, 47, 79, 85, 77, 93, 64, 50, 64, 73, 80, 39, 86, 74, 41,\n",
      "        78, 69, 19, 60, 36, 18, 25, 61, 68, 87, 13,  7, 83, 96])\n",
      "939 torch.Size([32, 3, 32, 32]) tensor([93, 89, 74, 72, 45, 69,  4, 86, 23, 61, 93, 36, 39, 93, 63, 69, 22, 20,\n",
      "         3,  6,  9, 29,  9, 43, 82, 48, 38, 98, 80, 33, 69, 75])\n",
      "940 torch.Size([32, 3, 32, 32]) tensor([49, 94, 93, 45, 65, 56, 32, 32, 22, 81, 50, 27, 52, 69, 55, 70, 56,  5,\n",
      "        63, 40, 92, 50, 82, 36, 33, 87, 95, 52,  7, 87, 22, 83])\n",
      "941 torch.Size([32, 3, 32, 32]) tensor([47, 18,  1, 85, 88, 16, 55, 77, 49, 54, 98, 18, 24, 20, 40, 26, 53, 33,\n",
      "        15, 36, 83, 18, 15, 30, 92, 83, 84, 57, 35, 69, 29, 88])\n",
      "942 torch.Size([32, 3, 32, 32]) tensor([12, 54, 89,  1, 21, 44, 95, 21, 19, 22, 25, 28, 97,  4, 69, 27, 44, 23,\n",
      "        31,  2, 19, 11,  4, 33, 80, 90, 16, 30, 52, 39, 68, 96])\n",
      "943 torch.Size([32, 3, 32, 32]) tensor([12, 48, 15, 99, 86, 34, 70, 83, 96, 15, 96, 83, 85, 81, 20, 34, 84, 86,\n",
      "        85, 51, 94, 41, 94,  1, 59, 63, 52, 26, 63, 36, 39, 93])\n",
      "944 torch.Size([32, 3, 32, 32]) tensor([71, 84, 66, 56, 18, 29, 17, 75,  9, 58, 68, 69, 56, 24, 79, 69, 19, 10,\n",
      "        61,  3, 93, 88, 87, 47, 90, 10, 37, 43, 25, 59, 81, 52])\n",
      "945 torch.Size([32, 3, 32, 32]) tensor([40, 77, 63, 25, 84, 80, 85, 20,  1, 21, 67, 59,  8, 92, 96, 87, 14, 73,\n",
      "        40, 15, 92, 13, 95, 59,  4, 57, 59, 41, 34, 26, 12, 54])\n",
      "946 torch.Size([32, 3, 32, 32]) tensor([52, 74, 49, 21, 74,  4, 25,  3, 41, 49,  0, 11, 36, 65, 56, 18, 49, 87,\n",
      "         5, 30, 50, 24, 32, 93, 89, 15, 24,  2, 87, 72, 50, 55])\n",
      "947 torch.Size([32, 3, 32, 32]) tensor([99,  5, 77, 46, 92, 57, 13, 65, 98, 45,  7, 75, 38, 51, 13, 79,  7, 79,\n",
      "        52, 35, 33, 55,  7, 12,  5, 14, 23, 79,  7, 45, 17, 88])\n",
      "948 torch.Size([32, 3, 32, 32]) tensor([63, 20, 43, 64, 71, 73,  9, 97, 22,  2, 97, 91, 83, 73, 79, 40, 48, 15,\n",
      "        53, 73,  9, 80, 51, 62, 87, 33, 54, 19, 38,  2, 23, 54])\n",
      "949 torch.Size([32, 3, 32, 32]) tensor([18, 67, 86, 82, 40, 20, 78, 50, 26, 31, 48, 48, 29, 13, 49, 81, 33, 65,\n",
      "         5, 78, 99, 17, 19, 33,  3, 89, 15, 32, 64, 48, 27, 41])\n",
      "950 torch.Size([32, 3, 32, 32]) tensor([72, 10, 25, 75, 14, 42, 76, 66, 90, 11, 72, 34,  6, 61, 10, 90, 17, 43,\n",
      "         7, 70, 54,  4, 19, 88, 57, 65, 16, 62, 72, 23, 45, 46])\n",
      "951 torch.Size([32, 3, 32, 32]) tensor([ 6, 91, 28, 10, 67, 91,  0, 40, 78, 69, 56, 76, 17, 47, 28, 11, 95, 86,\n",
      "        81, 52, 33, 21, 39, 92, 51, 95, 52, 57, 41, 77, 56, 72])\n",
      "952 torch.Size([32, 3, 32, 32]) tensor([71, 50, 78, 75, 16, 78, 76, 75, 73, 93, 53, 58, 13, 37, 79, 30,  8, 40,\n",
      "        64, 37, 22, 21,  4, 83, 35, 36, 36, 62,  0, 94,  7, 47])\n",
      "953 torch.Size([32, 3, 32, 32]) tensor([23,  6, 38, 94, 20, 80, 22, 72, 54, 74, 29, 26, 62, 43, 15, 34, 92, 25,\n",
      "        31, 48, 15, 70, 12, 33, 78, 82, 89, 20, 67, 93, 45, 61])\n",
      "954 torch.Size([32, 3, 32, 32]) tensor([99, 49, 40, 54, 68, 89, 89,  9, 62, 96, 49, 72, 11, 66, 80, 23, 49, 31,\n",
      "        74, 72, 40, 56, 89, 20, 95, 75, 67, 32, 40, 37, 80, 26])\n",
      "955 torch.Size([32, 3, 32, 32]) tensor([25, 95, 94, 37, 85, 86, 17, 31, 63, 88, 82, 42, 13, 14, 57, 50, 76, 62,\n",
      "        73, 40, 22, 60, 80, 52, 22, 31,  0, 65, 86, 17, 61, 12])\n",
      "956 torch.Size([32, 3, 32, 32]) tensor([83, 67,  3, 89,  3, 34, 34, 75, 62, 29, 33, 44, 66, 92, 64,  8, 10, 66,\n",
      "        94, 56, 59, 96, 98, 23, 38, 94, 18, 60, 84, 74, 26, 98])\n",
      "957 torch.Size([32, 3, 32, 32]) tensor([18, 91, 89, 71, 87, 47, 87,  5,  9, 92, 55, 73, 29, 87, 11, 86,  1, 19,\n",
      "         6, 98,  3, 72, 92,  3, 93, 18, 35, 55, 99,  0, 56, 95])\n",
      "958 torch.Size([32, 3, 32, 32]) tensor([14, 86, 16, 32,  6, 86, 89, 50, 45, 89, 72, 11,  6, 12, 93, 42,  2, 42,\n",
      "         6, 84, 55,  8, 37, 77, 80, 35, 87, 90, 39, 51, 82,  2])\n",
      "959 torch.Size([32, 3, 32, 32]) tensor([53, 53, 18, 82,  2, 51, 87, 79, 23, 72, 27, 48,  1, 42, 68, 90,  8, 72,\n",
      "         4, 83, 67,  4, 95, 19, 18,  4, 86, 95, 62, 58, 70, 64])\n",
      "960 torch.Size([32, 3, 32, 32]) tensor([45, 81, 44, 57, 51, 81, 96, 25, 54, 29, 15, 58, 42, 42, 73, 87, 92, 92,\n",
      "        50, 98, 32, 78, 92, 42, 39, 27, 98, 82, 59, 57, 70, 62])\n",
      "961 torch.Size([32, 3, 32, 32]) tensor([50, 10, 20, 74, 20,  3, 19, 75, 87, 94, 71, 47,  3, 42, 80, 77,  3, 66,\n",
      "        51, 34, 81, 81,  0, 85, 93, 90, 54, 15, 16, 15, 68, 98])\n",
      "962 torch.Size([32, 3, 32, 32]) tensor([19, 98, 61, 42, 81, 98,  9, 15, 77, 90, 62, 26, 61,  8, 36,  0, 62, 15,\n",
      "        30, 76, 30, 79, 18,  9, 15,  4, 31, 54, 28,  2, 35, 89])\n",
      "963 torch.Size([32, 3, 32, 32]) tensor([24, 27, 83,  5, 98, 27, 22, 91, 96, 76, 22, 77, 25, 75, 88, 50, 65, 96,\n",
      "        39, 90, 19, 23, 18, 10, 32, 79, 64, 57, 16, 96, 93, 66])\n",
      "964 torch.Size([32, 3, 32, 32]) tensor([97, 26, 55, 50, 18, 60, 36,  9, 36, 40, 48, 91, 39, 38, 26, 69, 92, 89,\n",
      "        87, 36, 37, 32, 95, 78, 28, 96, 46, 54, 79, 52, 31, 53])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "965 torch.Size([32, 3, 32, 32]) tensor([63, 32, 26, 78, 23, 13, 56,  6, 33, 10, 65,  8, 38,  6, 59, 88, 20, 26,\n",
      "        95, 80, 23, 80, 74, 70, 30,  2, 42, 13, 33,  7, 47,  9])\n",
      "966 torch.Size([32, 3, 32, 32]) tensor([25, 37, 38, 20, 51, 25, 96, 65, 65, 78, 39, 80, 65, 11, 41, 24, 63, 56,\n",
      "         2, 71, 27, 55, 61, 47, 48, 91,  8, 14, 53, 95, 61, 44])\n",
      "967 torch.Size([32, 3, 32, 32]) tensor([36, 92, 53, 90, 45, 76, 48, 78, 59, 95, 25,  9, 28, 37, 31, 33, 85, 44,\n",
      "        52, 37,  1, 26, 33, 84, 76, 35,  9, 84, 62, 19, 45, 36])\n",
      "968 torch.Size([32, 3, 32, 32]) tensor([28, 27, 50, 17, 84,  6, 11, 18, 62, 79, 73, 91, 58, 12, 93, 76, 69, 34,\n",
      "        20, 28, 13, 46, 23, 86, 15, 80, 71, 94, 46, 71, 90, 90])\n",
      "969 torch.Size([32, 3, 32, 32]) tensor([12, 98, 76, 58, 59, 57, 58, 35, 75, 51,  7, 65, 66, 71, 54, 79, 91, 15,\n",
      "        66, 18, 70, 84, 31, 92, 13, 37, 56, 17, 44, 64, 50, 10])\n",
      "970 torch.Size([32, 3, 32, 32]) tensor([62, 30, 96, 17, 53, 22, 92, 75, 94,  4, 68, 58, 44, 17, 29,  7, 15, 29,\n",
      "        52, 98, 55, 56, 24, 18, 10, 49, 83, 40, 25, 39, 10, 64])\n",
      "971 torch.Size([32, 3, 32, 32]) tensor([10, 56, 61, 26,  6, 58, 69, 35, 99, 93, 85, 50, 72, 71, 44, 47, 35,  5,\n",
      "        73, 14, 96, 89, 31, 20, 12,  7, 67, 37, 61,  3, 77, 25])\n",
      "972 torch.Size([32, 3, 32, 32]) tensor([75, 44, 99, 53,  7, 36, 49, 24, 71, 65, 20, 97, 30, 35, 91, 30, 56, 16,\n",
      "         0, 11, 40,  8, 52, 35,  3, 86, 18, 35, 94, 44, 29, 75])\n",
      "973 torch.Size([32, 3, 32, 32]) tensor([80, 48, 34, 65, 26, 97, 92, 19, 99, 77, 94, 72, 85, 80, 48, 20, 69, 37,\n",
      "        16, 83, 43, 71, 92, 28, 46, 72, 58, 11, 46, 62, 52, 92])\n",
      "974 torch.Size([32, 3, 32, 32]) tensor([87, 13, 68, 62, 77, 28, 19, 43, 53, 31, 49, 77, 11, 68, 82, 85, 33, 86,\n",
      "        72, 44, 25, 63, 64, 51,  0, 39, 87, 71, 32, 35, 97, 15])\n",
      "975 torch.Size([32, 3, 32, 32]) tensor([25, 97, 41, 33,  9, 94, 83, 40, 97, 30, 75, 58, 63, 36, 96, 58, 66, 46,\n",
      "        57, 55, 54, 25, 74, 75, 62, 81, 74, 25, 80, 67, 51, 12])\n",
      "976 torch.Size([32, 3, 32, 32]) tensor([61, 69, 33, 83,  3, 78, 94, 39, 62, 11, 85, 14, 88, 91, 43, 48, 85,  5,\n",
      "         0,  0,  1, 29, 86, 63, 54, 71, 84, 43, 11, 89,  7, 62])\n",
      "977 torch.Size([32, 3, 32, 32]) tensor([72, 20, 41, 93, 11, 72, 47, 79, 52, 81, 54, 27, 61,  4,  9, 96, 83,  5,\n",
      "        58, 65, 73, 65, 35, 87,  7, 96, 44, 19, 16, 23, 65, 29])\n",
      "978 torch.Size([32, 3, 32, 32]) tensor([62, 44, 15, 69, 87, 68, 66, 29, 46, 37, 10,  4, 35, 75, 76, 50,  3,  0,\n",
      "        89, 15, 91,  8, 91, 60, 89,  8, 77, 28, 32, 88, 50, 28])\n",
      "979 torch.Size([32, 3, 32, 32]) tensor([51, 29, 23, 56, 91, 50,  4, 52, 30, 98, 38, 35, 21, 51, 10, 29, 64,  7,\n",
      "         5, 43, 81, 31, 13, 30, 35, 37, 23, 54, 37, 81, 39, 56])\n",
      "980 torch.Size([32, 3, 32, 32]) tensor([44,  5, 86, 36, 47, 12, 52, 40, 61,  5, 62, 98, 45, 50, 59, 49, 49, 92,\n",
      "        92, 74, 97, 63,  9, 60, 84,  3, 57, 10, 60, 63, 19, 50])\n",
      "981 torch.Size([32, 3, 32, 32]) tensor([ 3, 67, 24, 88, 94, 73, 66, 66, 22,  5, 37, 97,  8, 40, 56, 94, 55, 70,\n",
      "        36, 86, 82, 52,  6, 86, 11, 33, 34, 42, 16, 47, 19, 89])\n",
      "982 torch.Size([32, 3, 32, 32]) tensor([87, 98, 59, 55, 91, 92, 87, 78, 75, 96, 28, 79, 13, 61, 97, 77, 41, 57,\n",
      "        61, 65, 36,  0,  4, 21, 10,  4, 77, 36, 94, 85, 53, 52])\n",
      "983 torch.Size([32, 3, 32, 32]) tensor([35, 84, 60, 74, 69,  9, 85, 19, 71, 40, 57,  4, 85, 14,  9, 34, 24, 51,\n",
      "        76, 15,  3, 58, 23, 69, 38, 53, 49, 37,  5, 13, 21, 90])\n",
      "984 torch.Size([32, 3, 32, 32]) tensor([28, 84, 66, 28, 38, 91, 58, 39, 76, 38, 21, 79, 16, 77, 96, 77, 85, 12,\n",
      "        73, 99, 92,  7, 74,  2, 39, 63, 79,  8, 67, 63, 22, 60])\n",
      "985 torch.Size([32, 3, 32, 32]) tensor([15, 13, 53, 16, 71, 22, 91, 61,  3, 39, 67, 33, 28, 50, 37, 10, 27, 81,\n",
      "        57,  2,  8, 43, 59, 33, 62, 65, 73, 38, 69, 80, 65, 40])\n",
      "986 torch.Size([32, 3, 32, 32]) tensor([76, 50, 32, 36, 95, 50, 38, 49, 56, 36, 70, 60, 42,  4, 82,  1, 41, 37,\n",
      "         0, 56, 41, 88, 20, 69,  3, 12, 52, 93, 89, 99, 18, 58])\n",
      "987 torch.Size([32, 3, 32, 32]) tensor([77,  7, 84, 75, 98, 93, 66, 84, 58, 38, 52, 70, 14, 13, 95, 46,  8, 28,\n",
      "        82, 63, 23,  7, 65, 73, 15, 33,  0, 42, 54, 22, 65, 21])\n",
      "988 torch.Size([32, 3, 32, 32]) tensor([79, 45, 34, 97, 67, 22, 69, 38, 11, 88, 31, 76, 91, 92, 32, 93,  1, 36,\n",
      "        63, 78, 20, 10, 80, 21,  7, 88,  8, 88, 98, 67, 63,  3])\n",
      "989 torch.Size([32, 3, 32, 32]) tensor([59, 88, 11, 18, 35, 28, 82, 99, 51, 14,  5, 60, 36, 10, 65, 89, 70, 57,\n",
      "        44, 55, 93, 84, 91, 74, 86,  8, 34, 37, 25, 24,  7, 22])\n",
      "990 torch.Size([32, 3, 32, 32]) tensor([27, 66, 72,  4, 10, 44, 54,  3, 10, 92, 50, 88, 80, 85, 55, 19, 35,  5,\n",
      "        16, 66, 13,  6, 96, 82, 30, 65, 40, 85, 50, 92, 76, 29])\n",
      "991 torch.Size([32, 3, 32, 32]) tensor([60, 32, 37, 28, 98, 18, 19, 20, 14, 33, 95, 31, 34, 83, 99, 53, 20, 51,\n",
      "        75, 80, 85, 12,  7, 39, 92, 23, 85, 32, 28, 83, 46, 41])\n",
      "992 torch.Size([32, 3, 32, 32]) tensor([76, 21, 93, 56, 81, 58, 44,  7, 55, 13, 85, 47, 94, 78, 99, 23, 14, 67,\n",
      "        59, 35, 42, 69, 42, 36,  9, 89, 79, 42, 28, 14, 24,  2])\n",
      "993 torch.Size([32, 3, 32, 32]) tensor([34, 37, 68, 53, 66, 85, 13, 96, 46,  7, 23, 70, 98, 36, 43, 60, 17,  7,\n",
      "        42, 94, 21, 42, 21, 12, 80, 40, 97, 79, 98, 33, 93, 57])\n",
      "994 torch.Size([32, 3, 32, 32]) tensor([65, 35, 78, 15, 22, 97, 40,  2, 44, 23, 83, 80, 54, 83, 43,  5, 19, 63,\n",
      "        23, 48, 68, 72, 87, 16, 45, 89, 39,  4, 79, 19, 22, 25])\n",
      "995 torch.Size([32, 3, 32, 32]) tensor([95,  2,  8, 61, 13, 28, 79, 24, 85, 35,  5, 49, 63, 47, 27, 91, 89,  4,\n",
      "        94, 20, 98, 75, 42, 49,  2, 60, 27, 51, 38, 35, 38, 90])\n",
      "996 torch.Size([32, 3, 32, 32]) tensor([19,  9, 84, 38, 56, 48, 42, 19, 66, 58, 16, 76, 82,  5,  5, 70, 55, 87,\n",
      "        43, 69, 52, 77, 94, 52, 58, 60, 30, 40,  8, 53,  1, 83])\n",
      "997 torch.Size([32, 3, 32, 32]) tensor([59, 76, 31, 87, 69, 78, 40, 36, 87, 87, 61, 77,  6,  9, 85,  5, 63, 69,\n",
      "        54, 72, 86, 38, 47,  3, 99,  8, 28, 60, 32, 22, 11, 68])\n",
      "998 torch.Size([32, 3, 32, 32]) tensor([51, 26, 29,  1,  9, 78, 19, 85, 13, 89, 95, 15, 45, 66, 80, 30,  4, 16,\n",
      "        14, 59, 10, 69, 38, 69, 34, 60, 71, 90, 90, 85, 92, 53])\n",
      "999 torch.Size([32, 3, 32, 32]) tensor([74, 28, 47,  2, 87, 25, 61, 40,  3, 27,  4, 96, 55,  6, 46, 31, 74, 34,\n",
      "        38, 52,  6, 37, 79, 64, 67, 30, 98, 72, 32, 94, 48, 62])\n",
      "1000 torch.Size([32, 3, 32, 32]) tensor([49, 26, 33, 17, 50, 48, 35, 70, 78, 25, 86, 15, 86, 29, 44, 17,  1, 90,\n",
      "        80, 10, 14,  4, 58, 78, 92, 60, 96, 29, 32, 99, 72, 22])\n",
      "1001 torch.Size([32, 3, 32, 32]) tensor([60, 47,  5, 92, 50, 10, 29, 37, 32,  9, 96,  3, 69,  5, 34,  6, 10, 42,\n",
      "         6, 49, 13, 19, 73, 38, 46, 80, 69, 96, 79, 17, 23, 30])\n",
      "1002 torch.Size([32, 3, 32, 32]) tensor([92, 46,  8, 57, 20, 47, 16, 61, 37,  5, 42, 11, 48, 85, 74, 37, 68, 99,\n",
      "         3, 80, 86, 73, 45, 94, 85, 59, 81, 46, 58,  1,  1, 73])\n",
      "1003 torch.Size([32, 3, 32, 32]) tensor([98, 99, 67, 69, 82,  0, 41, 14, 41, 33,  1, 78, 52, 53, 44, 12, 29, 45,\n",
      "        72, 63, 59, 19, 21, 80, 76, 44, 12, 82, 92, 55, 27, 93])\n",
      "1004 torch.Size([32, 3, 32, 32]) tensor([35, 76, 98,  4, 19, 24, 36,  5, 38, 69, 77, 41, 41, 14, 96, 54, 36, 91,\n",
      "        38, 10, 86, 11, 98, 56, 18, 94, 49, 19, 91, 87, 92, 82])\n",
      "1005 torch.Size([32, 3, 32, 32]) tensor([73, 60, 63,  3, 44, 36, 99, 23, 75, 29,  9, 77, 11,  4, 57, 51, 61, 91,\n",
      "        42, 44, 56, 70, 78, 65, 94, 23, 15, 98, 55, 65, 14, 74])\n",
      "1006 torch.Size([32, 3, 32, 32]) tensor([38, 97, 52, 66, 23,  9, 52,  5, 73, 98, 52, 44, 60, 24, 52, 60, 53, 83,\n",
      "        43, 87, 76,  5, 44, 94, 80, 75, 28, 89, 18, 76, 12, 60])\n",
      "1007 torch.Size([32, 3, 32, 32]) tensor([70,  4, 82, 13, 51, 56, 63, 52, 13, 61, 87, 23, 14, 34, 54, 98, 45, 81,\n",
      "        22, 84, 66,  9, 85, 46, 84, 30, 10, 32, 84, 59, 74, 80])\n",
      "1008 torch.Size([32, 3, 32, 32]) tensor([70, 61,  3, 90, 98, 24, 37, 87, 51, 92, 98, 96, 69, 56, 34, 23, 32, 63,\n",
      "        79, 42,  2, 91, 47, 76, 34, 51, 27,  2, 98, 68, 84, 90])\n",
      "1009 torch.Size([32, 3, 32, 32]) tensor([96, 39, 30, 10, 42, 62, 24,  0, 63, 80, 50, 95, 83,  4, 65, 78, 24,  9,\n",
      "        85, 94, 40, 57, 39, 70, 88, 47, 91,  3, 92, 96, 39, 81])\n",
      "1010 torch.Size([32, 3, 32, 32]) tensor([51, 81, 69, 92,  6, 23, 50, 12, 95,  4, 76, 46, 51, 47, 23, 18, 92, 84,\n",
      "        60, 86, 25, 19, 35, 12,  1, 70, 59, 65, 51, 26, 18, 24])\n",
      "1011 torch.Size([32, 3, 32, 32]) tensor([39, 16, 10, 12, 39, 54, 88, 46, 82, 47, 41, 28, 63, 67, 41, 31, 30, 41,\n",
      "        15, 10, 38, 22, 44, 47, 75, 66, 10, 30, 11, 31,  6, 98])\n",
      "1012 torch.Size([32, 3, 32, 32]) tensor([47, 98, 99, 52, 78, 55, 70, 86, 83, 68, 62, 30, 78, 60, 58, 38, 89, 30,\n",
      "        91, 57, 75, 64, 60, 74, 66, 83, 17, 56, 59, 74, 97, 71])\n",
      "1013 torch.Size([32, 3, 32, 32]) tensor([66, 91, 99, 13, 37, 90,  8, 14, 18, 43,  1, 19, 11, 47, 95,  5, 36, 35,\n",
      "        88, 59, 43, 73, 55, 52, 75, 38, 65, 38, 20, 14, 99, 51])\n",
      "1014 torch.Size([32, 3, 32, 32]) tensor([42, 76, 97, 43, 62, 55, 62, 35, 86, 16, 90, 48, 64, 17, 24, 51, 98, 81,\n",
      "        63, 81, 87, 31,  8, 23, 53, 72, 37, 28, 96, 82, 19, 67])\n",
      "1015 torch.Size([32, 3, 32, 32]) tensor([20, 49, 22, 61, 38, 94, 70,  9, 51, 90, 29, 45, 13, 30, 12, 52, 63, 44,\n",
      "        79, 59, 41, 39, 22, 80, 22, 56, 20, 60,  2, 84, 61, 98])\n",
      "1016 torch.Size([32, 3, 32, 32]) tensor([16, 54, 80, 53, 56, 75, 93, 16,  8, 68, 19,  8,  9, 11, 81, 91, 57, 14,\n",
      "        88, 34, 24, 94, 24, 32,  2, 79, 91, 84,  6, 31, 37, 28])\n",
      "1017 torch.Size([32, 3, 32, 32]) tensor([87, 70, 48, 96, 69, 81, 40, 50, 67, 99, 87, 94, 17, 90, 69,  2, 64, 73,\n",
      "        40, 25,  0, 27, 24,  0, 98, 13, 64, 30, 90, 96, 93, 33])\n",
      "1018 torch.Size([32, 3, 32, 32]) tensor([75, 44, 30, 20, 68, 76, 74, 39, 42, 10, 47, 62, 50, 85, 12,  3, 47, 88,\n",
      "        76, 95, 48, 14, 73, 77, 20, 17, 69, 92, 60, 96, 19, 32])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1019 torch.Size([32, 3, 32, 32]) tensor([ 7, 36, 83, 45, 94, 61, 97,  9, 41, 51, 92, 54, 52, 57, 70, 56,  7, 65,\n",
      "        86, 97, 45, 95, 52,  1, 57, 11, 21, 45, 74, 40, 38, 85])\n",
      "1020 torch.Size([32, 3, 32, 32]) tensor([ 3, 85, 99, 96, 95, 72, 82, 91, 64, 80, 54, 72, 90, 88, 41, 39, 57,  4,\n",
      "        86, 84,  7, 39, 57, 25, 56, 28, 21, 28, 31, 22, 67,  4])\n",
      "1021 torch.Size([32, 3, 32, 32]) tensor([20, 21, 41, 13, 65,  3, 98, 92, 53, 37, 10, 30, 54,  1, 40, 18, 25, 94,\n",
      "        42, 82, 10, 31, 37,  6, 16, 64, 67, 53, 42, 36, 95,  0])\n",
      "1022 torch.Size([32, 3, 32, 32]) tensor([99,  8, 65, 95, 35, 97,  5, 68, 46, 79, 85, 45, 90, 88, 66, 89, 46, 13,\n",
      "        58, 38, 81, 75, 47, 90, 54, 93, 97, 32, 24, 87, 35, 10])\n",
      "1023 torch.Size([32, 3, 32, 32]) tensor([99, 80, 12, 76,  7, 15, 62,  7, 83, 49, 52, 66, 39, 27, 87, 88, 95, 65,\n",
      "        56, 37, 82, 86, 87,  1, 58, 51, 88, 46, 31, 88, 62,  5])\n",
      "1024 torch.Size([32, 3, 32, 32]) tensor([41, 76, 85, 32, 50, 56, 34,  4, 13, 85, 30, 67, 63, 86, 68, 42, 28,  6,\n",
      "         2, 62,  0, 34, 34, 34,  5, 77, 51, 50, 82, 79, 14, 63])\n",
      "1025 torch.Size([32, 3, 32, 32]) tensor([74, 47, 51, 86,  3, 93, 72, 26, 10, 38, 28, 24,  8, 32, 71, 35, 48, 53,\n",
      "        80, 21, 17, 24, 85, 34, 52, 44, 98,  4, 70, 18, 27, 29])\n",
      "1026 torch.Size([32, 3, 32, 32]) tensor([60, 99, 94, 94, 43, 25, 65, 94, 22, 86, 75, 73, 31, 64, 40, 37, 31, 45,\n",
      "        48, 95, 72, 16, 27,  7, 87, 24, 19, 67, 79, 45,  6, 15])\n",
      "1027 torch.Size([32, 3, 32, 32]) tensor([65, 81, 73, 70, 15, 53, 96, 20, 95,  9, 19,  9, 65, 41, 20, 89, 37, 48,\n",
      "        43, 24, 10, 43, 80, 83,  3, 16, 26, 72, 69, 42, 60, 94])\n",
      "1028 torch.Size([32, 3, 32, 32]) tensor([59, 34, 83, 62, 46, 38, 57, 36, 91, 39, 50, 48, 83,  1, 90, 62, 82, 19,\n",
      "        11, 54, 55, 12, 18,  2, 76, 81, 50, 27, 41, 53, 82, 94])\n",
      "1029 torch.Size([32, 3, 32, 32]) tensor([ 6, 58, 81, 19, 27, 80, 80,  1, 44, 87,  5, 78, 98, 63, 89, 36, 74, 20,\n",
      "        79, 29, 32, 66, 49,  7, 49, 42, 21, 59,  0, 41, 76, 85])\n",
      "1030 torch.Size([32, 3, 32, 32]) tensor([57, 29, 48, 45, 99, 89, 66, 46,  6, 32, 86, 53, 23, 28, 72, 96, 74,  3,\n",
      "        25, 58, 78, 89, 76, 56,  8, 15, 64, 43, 98,  3, 23, 36])\n",
      "1031 torch.Size([32, 3, 32, 32]) tensor([98, 64, 34, 11, 72, 47, 33, 70, 12, 91,  2, 57, 20,  4, 47, 15, 82, 90,\n",
      "        58, 62, 50,  7, 93,  8, 21, 58, 24, 75, 94, 15, 14, 44])\n",
      "1032 torch.Size([32, 3, 32, 32]) tensor([75, 14, 94, 58, 43, 81, 11, 77, 12, 97, 64, 82,  6, 78, 85, 73, 23, 94,\n",
      "        70, 26, 80, 31, 22, 22, 94, 76, 86,  7,  7, 89,  9, 14])\n",
      "1033 torch.Size([32, 3, 32, 32]) tensor([57, 35,  2, 85, 58, 88, 81, 37, 15, 74, 19, 65, 74, 92, 11, 64, 90,  1,\n",
      "        67, 61, 21, 50, 92,  5,  6, 54, 39, 97, 75, 72, 70, 64])\n",
      "1034 torch.Size([32, 3, 32, 32]) tensor([89, 64,  4, 54, 72, 90, 81, 97, 96, 59, 22,  7, 12, 81, 52, 54, 47, 23,\n",
      "        73, 75, 42, 72, 54, 14, 23, 86, 51, 34, 59,  0, 98, 96])\n",
      "1035 torch.Size([32, 3, 32, 32]) tensor([77, 33, 17, 90, 58, 59, 75,  3, 86,  3,  3, 43, 25,  8, 88,  1, 68, 24,\n",
      "        62, 53, 26, 95, 31, 79, 30, 40, 74,  2, 44, 92, 33, 28])\n",
      "1036 torch.Size([32, 3, 32, 32]) tensor([23,  5, 40, 74, 77, 93, 44,  1, 71, 83, 41, 59, 73, 70, 17, 25, 91, 63,\n",
      "        76, 88, 60, 38, 36, 11, 49, 75,  6, 14, 61, 49, 64, 88])\n",
      "1037 torch.Size([32, 3, 32, 32]) tensor([52, 65, 49, 86, 21, 38, 52, 93, 45, 43, 86, 12,  7, 76, 64, 22, 75, 38,\n",
      "        39, 59, 48, 46, 33, 67, 41, 19, 51, 24, 64, 71, 77, 96])\n",
      "1038 torch.Size([32, 3, 32, 32]) tensor([80,  1, 85, 14, 19, 22,  5, 49, 45, 90, 40, 45, 85, 84, 22,  0, 45, 86,\n",
      "        41, 43, 11, 79, 79, 14, 37, 51, 95, 29, 26, 85, 81, 97])\n",
      "1039 torch.Size([32, 3, 32, 32]) tensor([ 6, 80, 90, 89, 43, 67, 68, 13, 55, 18, 55,  8, 92, 47, 92,  4,  8, 27,\n",
      "        92, 49, 49,  8, 68,  7, 71, 81, 58, 44, 83, 19, 62, 72])\n",
      "1040 torch.Size([32, 3, 32, 32]) tensor([18, 16, 28, 45, 92, 35,  1, 31,  8, 81, 15, 64,  4, 38, 76, 92, 95, 14,\n",
      "        56, 73, 11, 30, 24, 93, 90, 28, 32, 59, 70,  9, 98, 39])\n",
      "1041 torch.Size([32, 3, 32, 32]) tensor([46, 80, 16, 98, 23, 17, 83, 23, 27, 23, 64, 23, 42, 13, 81, 95, 15, 60,\n",
      "         1, 44,  7, 82, 99,  8, 93, 52, 63, 33, 95, 61, 86, 66])\n",
      "1042 torch.Size([32, 3, 32, 32]) tensor([86,  3, 15, 79, 96, 37, 40, 43,  8, 17, 97, 48, 18, 24, 29, 79, 13, 29,\n",
      "        21, 38, 43, 62, 33,  8, 74, 19, 44,  9,  1, 76, 47, 31])\n",
      "1043 torch.Size([32, 3, 32, 32]) tensor([65, 46, 12,  7, 82, 57, 10, 47, 18,  6, 15,  7, 26, 16, 81, 29,  2,  6,\n",
      "        78, 84,  8, 23, 81, 78, 93, 84,  2, 36, 22, 38,  5, 54])\n",
      "1044 torch.Size([32, 3, 32, 32]) tensor([45, 54, 51, 75, 46, 30, 37, 16, 33, 24, 64, 22, 98,  8, 42, 71, 29, 41,\n",
      "        58, 49, 96, 66, 65,  9, 59, 35, 76, 98, 33,  7, 27, 27])\n",
      "1045 torch.Size([32, 3, 32, 32]) tensor([ 9, 65, 79, 86,  2, 20, 10, 42, 93, 83, 77, 34, 46, 26, 43,  0,  7, 67,\n",
      "        31, 69, 61, 12, 18, 25, 52, 42, 93, 28, 81, 61,  7, 33])\n",
      "1046 torch.Size([32, 3, 32, 32]) tensor([72, 11, 49, 43,  6, 76,  0, 59, 79, 42, 25, 55,  0,  4, 90,  7, 45,  4,\n",
      "        72, 51, 19, 46, 42, 41, 13, 86, 95, 26, 53, 46, 55, 71])\n",
      "1047 torch.Size([32, 3, 32, 32]) tensor([ 8, 96, 78, 46,  1, 77,  4, 71, 57, 65, 35, 23, 51, 92, 17, 98, 96, 53,\n",
      "        66, 88, 10, 57, 78, 60, 34, 57, 18, 92, 72, 79, 12,  8])\n",
      "1048 torch.Size([32, 3, 32, 32]) tensor([79, 11, 44, 28, 92, 67, 64, 57, 32,  3, 64, 25, 59, 77, 48, 96, 86, 72,\n",
      "        95, 43,  7, 29,  3, 66, 90, 24, 87, 83, 22, 12, 35, 60])\n",
      "1049 torch.Size([32, 3, 32, 32]) tensor([90, 84, 38, 60, 68, 20, 73, 34, 75, 64, 82, 51, 87, 51, 99,  6, 64, 24,\n",
      "        29, 28,  8, 24,  1,  4, 62, 11, 50, 55, 63, 52, 78, 67])\n",
      "1050 torch.Size([32, 3, 32, 32]) tensor([98, 46, 57, 41,  6,  0, 88, 39, 79, 71, 27, 54, 71, 52, 13, 20, 60, 95,\n",
      "        67, 72, 85, 48, 98,  8, 98, 42, 31, 77, 17, 95, 32, 13])\n",
      "1051 torch.Size([32, 3, 32, 32]) tensor([ 5, 91, 63, 96, 38, 16, 16, 28, 94, 69, 43, 78, 94, 91, 26,  5, 37, 46,\n",
      "        27, 41, 68, 67, 63, 64, 65, 84, 61, 39, 78, 17, 90, 74])\n",
      "1052 torch.Size([32, 3, 32, 32]) tensor([59, 63, 96, 59, 60, 90, 50, 56, 14, 84, 72, 10, 63, 94, 43, 67, 95, 29,\n",
      "        88,  5, 88,  2, 28, 91,  1,  2,  9,  0, 90, 97, 34, 17])\n",
      "1053 torch.Size([32, 3, 32, 32]) tensor([21, 71, 60, 56,  4, 31, 50, 16, 93,  6, 62, 87, 78, 65, 60, 60, 22,  1,\n",
      "        78, 15,  7, 70, 74, 49, 51,  5, 30, 82, 42, 92, 29, 18])\n",
      "1054 torch.Size([32, 3, 32, 32]) tensor([81, 64, 10, 70, 25, 63, 80, 34, 72, 75, 20, 70, 87, 54, 47,  1, 54, 89,\n",
      "        79, 15, 93, 78, 39, 74, 72, 24, 48, 67, 86, 76, 91,  4])\n",
      "1055 torch.Size([32, 3, 32, 32]) tensor([66, 24, 99, 96, 61, 36, 77,  3, 57, 85, 61, 46, 97, 32, 65, 39, 68,  8,\n",
      "        78,  5, 83, 30, 42, 25, 15, 78, 63, 91, 34, 83, 41, 95])\n",
      "1056 torch.Size([32, 3, 32, 32]) tensor([54, 24, 85, 64, 17, 35, 97, 98, 92, 87, 12, 52,  4, 31, 88, 32, 59, 82,\n",
      "        35, 64, 68,  7, 76, 32, 17,  6, 15, 96, 67, 93, 84, 13])\n",
      "1057 torch.Size([32, 3, 32, 32]) tensor([16, 82, 28, 34, 55, 38, 61, 62, 14,  9,  6, 63, 35, 53, 11,  3, 50, 96,\n",
      "        39, 28, 73, 93,  0, 60, 61, 21, 13, 35, 69, 79, 27, 76])\n",
      "1058 torch.Size([32, 3, 32, 32]) tensor([41, 90, 19, 92, 26, 40, 23, 95, 98, 48, 15, 53, 62, 22, 21, 93, 39, 15,\n",
      "        74, 73,  3, 70, 74, 53, 19,  9, 38, 65,  4, 67, 36, 19])\n",
      "1059 torch.Size([32, 3, 32, 32]) tensor([94, 87, 88, 88, 98,  8, 12, 31, 30, 28, 71, 52, 61, 66, 33, 83,  3, 90,\n",
      "         3, 89, 52, 27, 15, 38, 98, 33, 67, 41, 68, 51, 51, 63])\n",
      "1060 torch.Size([32, 3, 32, 32]) tensor([41, 97, 40, 43, 91, 44, 61, 46, 38, 66, 13,  7, 33, 90, 71, 54, 13, 70,\n",
      "        83, 81, 15, 45, 50, 10, 52, 11, 77, 30, 51, 84, 35, 34])\n",
      "1061 torch.Size([32, 3, 32, 32]) tensor([67, 25, 64, 60,  9, 39, 15, 25, 25, 30, 52, 50,  4,  9, 49,  0, 25, 11,\n",
      "        77, 24, 86, 43, 58, 87, 30, 71, 28, 23, 37, 38, 67, 91])\n",
      "1062 torch.Size([32, 3, 32, 32]) tensor([63, 27, 34, 77, 96, 99, 39, 62, 65, 22, 98, 37, 90, 13, 80, 99,  3, 70,\n",
      "        70, 59, 33, 96, 18, 61, 52, 71, 77, 93, 27, 17, 80, 40])\n",
      "1063 torch.Size([32, 3, 32, 32]) tensor([17, 34, 93,  4, 40, 82, 13, 22, 97, 22, 31,  2, 90, 32, 45, 72,  9, 87,\n",
      "        43, 21, 53, 44, 84, 55, 71, 54, 85, 34, 85, 16, 39, 60])\n",
      "1064 torch.Size([32, 3, 32, 32]) tensor([72, 62, 19, 12,  6, 40, 12, 48, 68, 74,  8, 28, 16, 37, 87, 10,  4, 59,\n",
      "        74, 71, 78, 56, 52, 44, 67, 57, 12, 72, 58,  6, 87, 83])\n",
      "1065 torch.Size([32, 3, 32, 32]) tensor([14, 29, 46,  1, 25, 51, 55, 50, 51, 25, 48, 65, 49, 24, 84, 71, 21, 52,\n",
      "        92, 31, 64, 84, 21, 14, 42, 67, 38, 87, 52, 89, 42, 30])\n",
      "1066 torch.Size([32, 3, 32, 32]) tensor([34, 68, 24, 95, 50,  4, 26, 48,  7, 56, 33, 51, 81, 22, 63, 79, 85, 90,\n",
      "        63, 26, 98, 90, 54, 32, 56, 14, 77, 79, 56, 97, 43,  8])\n",
      "1067 torch.Size([32, 3, 32, 32]) tensor([38, 18, 33, 74, 89, 56, 62, 94, 13, 45, 17, 94,  2, 62, 61, 78, 93, 60,\n",
      "        45, 92, 22, 76, 69, 48, 48, 16, 76, 47,  3, 47, 76, 84])\n",
      "1068 torch.Size([32, 3, 32, 32]) tensor([25, 78, 41, 75, 43,  2, 58,  7, 36, 56, 11, 67, 32, 67, 14, 30,  2, 74,\n",
      "        45, 92, 48, 20, 87, 49, 13, 94, 29, 93,  2, 53, 38, 26])\n",
      "1069 torch.Size([32, 3, 32, 32]) tensor([20, 97, 16, 23, 53, 62, 97, 16, 60, 15, 63, 93, 64, 20, 31, 84, 73, 14,\n",
      "        79, 99, 96, 34, 29, 90, 22, 53, 37, 79, 63,  0, 36, 77])\n",
      "1070 torch.Size([32, 3, 32, 32]) tensor([76,  0, 69, 98,  9,  6,  2, 13, 21, 39, 86, 96, 22, 79, 46, 91, 97, 32,\n",
      "        53,  7, 74, 19, 60,  8,  9,  7, 19, 86, 24, 54, 14, 37])\n",
      "1071 torch.Size([32, 3, 32, 32]) tensor([51, 77, 36, 47, 93, 80, 62, 85, 86,  0,  0, 53, 48,  9, 20, 93, 58, 71,\n",
      "        17,  3, 90, 59, 48, 28, 62, 12, 62, 70, 54, 62, 83, 91])\n",
      "1072 torch.Size([32, 3, 32, 32]) tensor([51, 88, 41, 62, 74, 57,  6, 61, 53, 22,  2,  7, 92, 90, 89, 68, 18, 97,\n",
      "        33, 63, 96, 97, 52, 50, 90, 22,  0, 59, 43, 70, 18, 52])\n",
      "1073 torch.Size([32, 3, 32, 32]) tensor([79,  2, 88, 40, 71, 87, 81, 93, 98, 89, 73, 45, 85, 98, 17, 61, 50, 31,\n",
      "        45, 77, 39, 48, 57, 39, 13, 33, 80, 46, 87, 96, 11, 10])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1074 torch.Size([32, 3, 32, 32]) tensor([33, 69, 33, 25, 75, 13, 48, 46, 11, 41, 37, 46,  0, 77,  4, 36, 18, 92,\n",
      "        31, 27, 17, 93, 18, 33, 49, 29, 83, 81, 54, 20, 37, 69])\n",
      "1075 torch.Size([32, 3, 32, 32]) tensor([62, 10, 14, 60, 29, 66, 58, 81, 29, 37, 23, 98, 77, 10,  7, 99, 57, 45,\n",
      "        47, 28, 96, 96, 91, 75, 90, 54, 51, 66, 59, 29, 74, 59])\n",
      "1076 torch.Size([32, 3, 32, 32]) tensor([61, 27, 55, 67, 27, 95, 21, 58, 62, 90, 82, 99, 60, 82, 96, 74,  6, 96,\n",
      "        26, 59, 69, 74, 51,  5, 53, 70, 79, 46, 36, 72, 65, 48])\n",
      "1077 torch.Size([32, 3, 32, 32]) tensor([31,  4, 61, 93, 43, 56, 78, 23, 71, 95, 42, 78, 91, 15, 79, 68, 61,  5,\n",
      "        92, 53, 64, 21, 44, 38, 76,  3, 84,  1, 47,  7, 23, 87])\n",
      "1078 torch.Size([32, 3, 32, 32]) tensor([12, 90, 16, 97, 55, 79, 42, 63, 65, 27, 13, 96, 53, 80, 21, 43, 80, 80,\n",
      "        26, 60, 12, 56, 52, 42, 55, 15, 11, 85, 49, 76, 62, 77])\n",
      "1079 torch.Size([32, 3, 32, 32]) tensor([49, 84, 43,  1, 85, 86, 75, 32, 36, 53, 31, 10, 12, 72, 22, 60, 88, 83,\n",
      "        56, 24, 63, 54, 41, 50, 34, 46,  6, 30, 79, 28, 50, 52])\n",
      "1080 torch.Size([32, 3, 32, 32]) tensor([ 4, 44, 54, 32, 84, 97, 50, 46,  3, 76, 81, 88, 96, 87, 58, 98, 85, 38,\n",
      "         3, 98, 21, 46, 81, 50, 48, 93, 95,  5, 77, 74, 61, 13])\n",
      "1081 torch.Size([32, 3, 32, 32]) tensor([19, 59, 47, 83, 12, 19, 19, 24, 94, 93, 23, 69, 77, 74, 62, 31, 22, 20,\n",
      "        71, 69, 63, 78, 85, 17, 46, 43, 86, 77, 77, 47, 39, 84])\n",
      "1082 torch.Size([32, 3, 32, 32]) tensor([87, 28,  6, 30, 49, 98, 72, 18, 37, 90, 46, 88, 55, 69, 77, 27, 68, 24,\n",
      "        68, 49, 47, 17, 28, 67, 93, 43, 86, 94, 65, 82,  9, 55])\n",
      "1083 torch.Size([32, 3, 32, 32]) tensor([83, 18, 38,  1, 44, 21, 51, 45, 33, 63, 92, 40, 46, 72, 18, 24, 69, 85,\n",
      "        68, 13, 22, 75, 44, 50, 20, 80, 66, 61, 73, 23, 11, 21])\n",
      "1084 torch.Size([32, 3, 32, 32]) tensor([26,  7, 89, 49, 24,  4, 78, 95, 47, 14, 62, 75, 46, 82, 94,  5, 41, 61,\n",
      "        72, 18, 53, 80, 34, 43, 70, 20, 36, 42, 12, 40, 45, 72])\n",
      "1085 torch.Size([32, 3, 32, 32]) tensor([18, 25, 49,  0, 90, 86, 95, 69, 69, 66, 91, 68, 26, 30, 65, 26,  6, 62,\n",
      "        97, 50, 35, 41, 63, 83, 51, 23, 68,  6, 35,  3,  6, 19])\n",
      "1086 torch.Size([32, 3, 32, 32]) tensor([ 6, 28, 26, 73, 31, 25, 56,  5, 74, 25, 76, 40,  3, 25, 73, 29, 18, 71,\n",
      "        93, 79, 83, 43, 50, 99, 23, 68, 89, 66, 96, 96, 64,  1])\n",
      "1087 torch.Size([32, 3, 32, 32]) tensor([69, 71, 24,  0, 40, 72, 13, 34, 11, 68, 56, 23, 64,  4, 30, 70, 23, 25,\n",
      "        80, 57, 92, 11, 80, 25, 84,  1, 20,  7, 91, 33, 55, 24])\n",
      "1088 torch.Size([32, 3, 32, 32]) tensor([57,  1, 70,  2, 67, 64, 23, 50, 19, 53, 60, 10, 83, 50, 99, 82,  0,  2,\n",
      "        43, 27, 88, 55, 24, 44, 47, 41, 20, 43,  7, 27, 50, 97])\n",
      "1089 torch.Size([32, 3, 32, 32]) tensor([ 4, 60, 45, 20,  1, 47,  8, 32,  6, 99, 77,  3, 81, 80,  5,  5, 38, 10,\n",
      "        11, 27, 86, 99, 30, 68, 38, 72,  5, 83, 59, 13, 65, 27])\n",
      "1090 torch.Size([32, 3, 32, 32]) tensor([90, 44, 85, 76, 30, 69, 28, 97, 64, 63,  3, 28, 15, 34, 22, 80, 13, 69,\n",
      "        59, 16, 42, 47, 75, 90,  8, 61,  3, 60, 19, 64, 90, 80])\n",
      "1091 torch.Size([32, 3, 32, 32]) tensor([90, 96, 72, 36, 80, 43, 75,  3, 32, 82, 73,  8, 80, 61, 49, 29, 87, 57,\n",
      "        54, 99, 58, 93, 24, 59, 84, 80, 82, 96, 22, 76, 30, 59])\n",
      "1092 torch.Size([32, 3, 32, 32]) tensor([24, 97, 19,  9, 78, 18, 23, 37, 82, 35, 44, 98, 21,  0, 14, 26, 18, 36,\n",
      "        21,  0, 32, 31, 86, 71, 52, 22, 28, 11, 36, 87, 64, 82])\n",
      "1093 torch.Size([32, 3, 32, 32]) tensor([40, 56, 87, 74, 12, 16, 79, 78,  5, 53, 15, 90, 79, 85,  6, 18, 43, 78,\n",
      "        61, 10, 83, 98, 24, 89, 76, 58, 71, 90, 70,  8, 12, 43])\n",
      "1094 torch.Size([32, 3, 32, 32]) tensor([66, 27, 89, 93, 78, 96, 70, 10, 79, 44, 91, 11, 82, 83,  8, 78, 85,  9,\n",
      "        62, 68, 49, 33, 67, 12, 84, 18, 35,  9, 72, 66, 40, 77])\n",
      "1095 torch.Size([32, 3, 32, 32]) tensor([42, 36, 51, 85, 59, 56, 38, 73, 10, 59, 40, 65, 47, 20, 26, 37, 40, 76,\n",
      "        86, 71, 50, 10, 17, 24, 42, 47, 90, 42, 28, 61, 97, 40])\n",
      "1096 torch.Size([32, 3, 32, 32]) tensor([86, 91, 56, 52, 54, 83, 24, 20, 27, 22,  4, 29, 51, 61, 61,  0, 65, 10,\n",
      "        54, 55, 51, 21, 48, 18, 61, 82, 16, 13,  1, 91, 60, 12])\n",
      "1097 torch.Size([32, 3, 32, 32]) tensor([27, 55, 83, 53, 77,  3, 14, 52, 72, 48, 76, 62, 80, 54, 17, 99, 14, 49,\n",
      "        99, 15, 17, 58, 84, 29, 17, 30, 54, 83, 67, 92, 91, 29])\n",
      "1098 torch.Size([32, 3, 32, 32]) tensor([46, 50, 19,  1,  8, 10, 93, 96, 43, 40, 88, 67, 97, 70, 51, 70, 90,  4,\n",
      "        43, 13, 71, 20, 85, 49, 68, 52, 28, 34, 35, 41, 57, 79])\n",
      "1099 torch.Size([32, 3, 32, 32]) tensor([93,  4,  9, 74, 47, 73, 16, 34, 63, 28, 89, 26, 59, 52, 79, 78, 65, 18,\n",
      "        93, 34, 55,  8,  2, 91, 37, 46, 66,  4, 69, 17,  0, 52])\n",
      "1100 torch.Size([32, 3, 32, 32]) tensor([99, 35, 87, 12, 59, 43, 88, 71,  8, 97, 72, 62,  5, 63,  6, 86, 46, 34,\n",
      "        99, 57, 87, 88, 48, 54, 27, 27, 15, 75, 24, 14, 85, 63])\n",
      "1101 torch.Size([32, 3, 32, 32]) tensor([90, 47, 22, 79, 87, 77, 53, 58, 12, 83, 44, 19, 94, 52,  5, 93, 69, 48,\n",
      "        20, 80, 35, 57, 40, 25, 36, 30, 21, 82, 44, 89, 25, 93])\n",
      "1102 torch.Size([32, 3, 32, 32]) tensor([26, 73, 44, 19, 24, 28, 43, 46, 62,  6, 12, 98, 67, 49, 75, 55, 59, 64,\n",
      "        65, 12, 77, 77, 86, 77, 87, 61, 33, 21,  3, 91, 82, 91])\n",
      "1103 torch.Size([32, 3, 32, 32]) tensor([12, 60, 23, 52, 61,  4, 60, 68, 42, 62, 48, 17, 39, 92, 57, 31,  7, 35,\n",
      "         5, 25, 21, 28, 45, 48, 69, 23, 25,  6, 76, 76, 63, 63])\n",
      "1104 torch.Size([32, 3, 32, 32]) tensor([31, 22, 51, 32, 30, 27, 81, 35, 74, 35, 98, 56, 61, 38, 69, 50, 73, 57,\n",
      "        32,  0, 40, 27, 31, 31, 52, 97, 95, 32, 88, 68, 55, 21])\n",
      "1105 torch.Size([32, 3, 32, 32]) tensor([89, 78, 17,  3, 52, 99, 54, 59, 88, 26, 21, 35, 49, 71, 28,  5, 49, 49,\n",
      "         6,  4, 37, 87, 36, 31, 79, 94, 22, 31,  2, 59, 19, 35])\n",
      "1106 torch.Size([32, 3, 32, 32]) tensor([ 4, 84, 28, 67, 14,  4, 35, 19, 10, 82, 49, 17, 45, 26, 28, 44, 58, 78,\n",
      "         5, 79, 88, 47,  5, 26, 79, 21,  9,  4, 83, 84, 16,  9])\n",
      "1107 torch.Size([32, 3, 32, 32]) tensor([89,  2, 62, 46, 77, 17, 81, 22,  3, 86, 62, 50,  8, 44, 29,  9,  5, 27,\n",
      "        80,  9, 64, 95, 83, 75, 52, 68, 34, 37, 43, 72, 93, 99])\n",
      "1108 torch.Size([32, 3, 32, 32]) tensor([40, 93, 84, 97, 33, 20, 86, 77, 86, 42, 40, 25, 36, 17, 36, 88, 10, 40,\n",
      "        18, 43, 96, 10,  3, 17, 36, 74, 30, 30, 97, 27, 20, 85])\n",
      "1109 torch.Size([32, 3, 32, 32]) tensor([29, 80, 86, 64, 65, 51, 86,  9, 64, 47, 46, 15, 38, 93, 19,  9, 98, 95,\n",
      "        24, 46, 91, 47, 60, 18, 10, 64, 50, 77, 89, 65, 35, 45])\n",
      "1110 torch.Size([32, 3, 32, 32]) tensor([30, 43, 84, 43, 97, 97, 12, 76, 48, 62, 49, 87, 27, 68, 33, 65, 43, 21,\n",
      "        77, 35, 93, 15, 91, 75, 27, 50, 41, 51, 11, 37, 54,  8])\n",
      "1111 torch.Size([32, 3, 32, 32]) tensor([ 1, 73, 56, 18, 81,  3, 45,  7, 56, 25,  8,  7, 52, 49,  5, 60, 48,  7,\n",
      "        34, 25, 59, 27, 65, 52, 57, 93, 72, 45, 82, 13, 61,  9])\n",
      "1112 torch.Size([32, 3, 32, 32]) tensor([26, 92, 81, 82, 57, 56, 82, 61, 90, 12, 24, 33, 66, 37, 32, 48, 12, 64,\n",
      "        58, 88, 60, 14, 42,  2, 49, 64, 48, 98,  7, 43, 54,  6])\n",
      "1113 torch.Size([32, 3, 32, 32]) tensor([58, 61, 70, 95, 97, 56, 94, 81, 78, 83, 70, 61, 35, 70, 70, 15, 53, 15,\n",
      "        26, 29, 44, 72, 30,  2, 28, 57,  3,  9, 52, 94, 72, 78])\n",
      "1114 torch.Size([32, 3, 32, 32]) tensor([58, 67, 12, 18, 13, 40, 33, 77, 95,  9, 35, 40, 14, 63, 69, 27, 75, 27,\n",
      "        73,  9, 73, 15, 31, 86, 86, 24, 16,  1, 44, 18, 53, 84])\n",
      "1115 torch.Size([32, 3, 32, 32]) tensor([42,  4, 35, 97, 74, 86,  5, 37, 29, 80,  1, 79, 75, 91, 39,  2, 47, 10,\n",
      "        74, 47, 84, 45, 75, 36, 30, 89, 22, 91, 32, 31, 23, 34])\n",
      "1116 torch.Size([32, 3, 32, 32]) tensor([85, 34,  0, 67, 26, 26, 97, 81, 80, 30, 23, 95, 45,  7, 59, 85, 10, 20,\n",
      "        89, 91, 20,  2, 21, 22, 94, 92,  3,  9, 97, 45, 50, 56])\n",
      "1117 torch.Size([32, 3, 32, 32]) tensor([97,  1, 86, 88, 37, 46, 26, 26, 54, 28, 16, 95, 45, 75, 46, 53, 82, 12,\n",
      "        66, 27, 59, 72, 90, 95, 46, 71, 54, 23, 70, 51, 35, 79])\n",
      "1118 torch.Size([32, 3, 32, 32]) tensor([45, 43, 32, 12, 74, 18, 10, 30, 62, 85, 93, 36, 41, 70, 86, 63, 55, 55,\n",
      "        12, 91, 47, 52, 33, 88, 24, 27, 37, 49, 14,  4, 12, 31])\n",
      "1119 torch.Size([32, 3, 32, 32]) tensor([80, 35,  6, 31, 78, 54,  4, 82, 36, 99, 59, 78, 20, 86, 50, 60, 42, 40,\n",
      "         7,  0, 41, 12, 95, 95, 83, 46, 74, 73, 87, 38, 31, 74])\n",
      "1120 torch.Size([32, 3, 32, 32]) tensor([75, 84, 11, 73, 22, 25, 47, 49, 56, 72, 77, 60, 26, 52, 46, 32, 20, 72,\n",
      "        26, 61, 81, 15, 62, 59, 83, 10, 16, 26, 92, 92, 67, 75])\n",
      "1121 torch.Size([32, 3, 32, 32]) tensor([ 5, 90, 67, 19, 69,  9, 65, 47, 41, 54, 74, 73,  0, 45,  5,  6, 83, 11,\n",
      "        52, 71, 54, 46, 86, 52, 58, 49, 82, 94, 21, 60, 13, 48])\n",
      "1122 torch.Size([32, 3, 32, 32]) tensor([53, 60, 25, 38, 30, 17, 31, 24, 20, 12, 29, 42, 46, 78, 50, 18, 23, 74,\n",
      "        75, 25, 80,  8, 33, 10, 42, 65, 24, 34,  5, 95, 74, 70])\n",
      "1123 torch.Size([32, 3, 32, 32]) tensor([ 6, 49, 90, 87,  0, 26,  1, 36,  4, 45, 95, 14, 93, 26, 18,  5,  9, 41,\n",
      "        73, 56, 79, 86,  4,  9, 99, 38, 47, 60, 41, 66, 66, 34])\n",
      "1124 torch.Size([32, 3, 32, 32]) tensor([77, 40, 88, 79,  5, 61, 26, 72, 77, 71, 94, 63, 36,  1, 66,  3, 46, 17,\n",
      "        33, 61, 43, 55, 52,  5, 36,  0, 19, 46, 38, 99, 66, 96])\n",
      "1125 torch.Size([32, 3, 32, 32]) tensor([ 5, 78, 65, 10, 86, 84, 16, 12, 66, 38, 79, 37, 92, 30, 21, 58,  9, 43,\n",
      "        43, 94, 32, 88, 68, 65, 36, 73, 82, 19, 83, 38, 97, 68])\n",
      "1126 torch.Size([32, 3, 32, 32]) tensor([59, 39, 82, 80,  2, 57, 41, 39, 48, 77, 15, 39, 57, 73, 15, 85, 29, 70,\n",
      "        18, 19, 26, 98, 13, 99, 71, 81, 23, 12, 72, 12, 36, 23])\n",
      "1127 torch.Size([32, 3, 32, 32]) tensor([ 7, 44,  1, 71, 50, 21, 81, 94, 91,  3, 48, 95, 30,  3, 65, 31, 72, 75,\n",
      "        71, 17, 53, 65, 79, 57, 79, 71, 90, 70, 26, 76, 94,  6])\n",
      "1128 torch.Size([32, 3, 32, 32]) tensor([ 4, 78, 59, 20,  8, 96, 73, 68,  1,  9, 86, 16, 59, 30, 50, 45, 71, 43,\n",
      "        32, 17,  2, 54, 67, 73, 63, 71, 70, 27, 48, 30, 56, 15])\n",
      "1129 torch.Size([32, 3, 32, 32]) tensor([35, 20, 45, 93, 66, 78, 68, 55, 36,  6, 23, 81, 94, 54,  8, 50, 95, 33,\n",
      "        86, 35, 16,  3, 89, 77, 48, 37, 37, 81, 64, 18, 30, 90])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1130 torch.Size([32, 3, 32, 32]) tensor([ 0, 76, 40, 62, 81, 14, 96, 12,  0, 38, 95, 30, 50, 64, 14, 99, 42,  8,\n",
      "         0, 56, 19, 15, 13, 55, 75, 36, 81, 36, 43, 59, 52, 20])\n",
      "1131 torch.Size([32, 3, 32, 32]) tensor([ 1, 64, 65, 87, 17, 72, 82, 84, 29, 85, 10, 59, 73,  6, 89, 26, 96, 62,\n",
      "        67, 92, 28, 36,  2, 54, 51, 45, 93, 41, 68, 98, 86, 31])\n",
      "1132 torch.Size([32, 3, 32, 32]) tensor([37, 99, 80, 78,  7, 26, 44, 69, 56, 51, 71, 34, 94, 63, 21, 31, 71, 90,\n",
      "        20, 51,  3, 14, 43,  1, 42, 43, 31, 82,  4, 80, 90, 55])\n",
      "1133 torch.Size([32, 3, 32, 32]) tensor([35, 48, 69, 47, 63, 43, 35, 87, 84, 61, 69, 95, 72, 35, 40, 49, 89, 82,\n",
      "        79, 63, 47, 22, 94,  2, 80,  4, 14, 70, 24, 68, 37, 70])\n",
      "1134 torch.Size([32, 3, 32, 32]) tensor([97, 66, 49,  9, 99, 22, 72, 90, 85, 66, 51, 34, 96, 87, 87, 34, 15, 15,\n",
      "        66, 79, 50, 76, 84, 35,  8, 23, 73, 30, 32, 10, 21, 45])\n",
      "1135 torch.Size([32, 3, 32, 32]) tensor([13, 95,  6, 70, 16, 17, 50, 65, 63, 85, 40, 45, 39, 13, 70, 35, 34,  2,\n",
      "        51, 52, 60, 83, 66,  0, 88, 78, 71, 30, 87, 60, 48, 74])\n",
      "1136 torch.Size([32, 3, 32, 32]) tensor([73, 12, 30, 32, 51, 85, 10, 43,  9, 89, 97, 32, 23, 80, 63, 57, 39, 33,\n",
      "        25, 19, 30,  4,  4, 20, 19, 99, 27, 16, 91,  8, 22, 41])\n",
      "1137 torch.Size([32, 3, 32, 32]) tensor([15, 81, 16, 63, 76, 71,  2, 39, 47, 38, 72, 22, 35, 44, 92, 28, 76, 26,\n",
      "        21, 44, 22, 63, 20, 51, 39, 37, 96, 15, 89, 38,  8, 28])\n",
      "1138 torch.Size([32, 3, 32, 32]) tensor([35, 97, 52, 72, 99, 87,  5, 14, 17, 10, 74, 87, 50, 34, 29, 89, 28, 65,\n",
      "        17,  7, 34, 56,  6, 48, 65, 56, 29, 59,  9, 42, 16, 88])\n",
      "1139 torch.Size([32, 3, 32, 32]) tensor([13, 88, 21, 17, 24, 96, 57, 46, 96, 85, 86, 60, 31, 46, 77, 73, 38, 80,\n",
      "        69, 45, 13, 78, 27, 26, 77, 46, 96, 47, 59, 55, 16, 13])\n",
      "1140 torch.Size([32, 3, 32, 32]) tensor([18, 80, 18, 23, 29, 66, 79, 65, 18, 89, 82, 85, 78, 30, 16, 84, 20, 83,\n",
      "        87,  1, 91, 15, 54, 39, 96, 14, 27, 66, 28, 10, 42, 55])\n",
      "1141 torch.Size([32, 3, 32, 32]) tensor([ 0, 84, 52, 74, 79,  3, 97, 73, 99, 89, 17, 59, 23, 36,  1, 50, 48, 25,\n",
      "        57, 11, 42, 57,  9, 91,  7, 84, 36, 62, 85, 21, 17, 64])\n",
      "1142 torch.Size([32, 3, 32, 32]) tensor([14, 16, 71, 73, 55, 34, 75,  4, 81, 23, 48, 98, 64, 53, 23, 99, 14, 32,\n",
      "        49, 59, 25, 98, 53, 12, 14, 16, 30, 65, 57, 16, 44, 86])\n",
      "1143 torch.Size([32, 3, 32, 32]) tensor([22, 83,  0, 26, 43, 34, 56, 98, 32, 45, 82, 25, 20, 74, 40, 95, 91, 95,\n",
      "        99, 80, 13, 64, 91, 84, 36, 32, 79, 46, 18, 22, 74,  3])\n",
      "1144 torch.Size([32, 3, 32, 32]) tensor([58, 63, 63, 31, 37, 62, 32,  8, 82,  0, 97, 88, 45, 80, 79, 98, 68, 78,\n",
      "        46, 18, 12, 74, 36, 67, 98, 41, 71,  5, 72, 47, 95, 25])\n",
      "1145 torch.Size([32, 3, 32, 32]) tensor([13, 43, 40, 80, 97, 31, 71,  4, 49, 98, 80, 20, 88, 36, 48, 36, 50, 42,\n",
      "        44,  1,  5, 53, 18, 74, 32, 38,  0,  9, 55,  7, 70, 24])\n",
      "1146 torch.Size([32, 3, 32, 32]) tensor([ 7, 68, 35, 24, 55, 97, 55, 27, 63, 90, 82, 54, 59, 86, 24, 34, 54, 67,\n",
      "        56, 65, 62, 19, 63, 65, 87, 32, 18, 95, 41, 16, 37, 42])\n",
      "1147 torch.Size([32, 3, 32, 32]) tensor([73,  1, 38, 79, 92, 10, 92, 61,  3, 89, 16, 52, 45, 20, 66, 53, 20, 80,\n",
      "        31, 41, 87,  7, 59, 45, 71, 61, 83, 70, 28, 34, 15, 91])\n",
      "1148 torch.Size([32, 3, 32, 32]) tensor([53,  5, 54, 21, 76, 89, 34, 66, 75, 33, 14, 66, 12, 38, 26, 85,  0, 18,\n",
      "        78, 59, 93,  1, 59, 84, 48, 16, 69, 13, 89, 47, 37, 60])\n",
      "1149 torch.Size([32, 3, 32, 32]) tensor([32, 69, 68, 16, 52, 55, 29, 99, 25, 28, 21, 33, 68, 47,  2, 74, 20,  0,\n",
      "        29, 42, 66,  2, 29, 98, 83, 45, 89, 60, 42, 28, 60, 75])\n",
      "1150 torch.Size([32, 3, 32, 32]) tensor([22, 18, 49, 78, 69, 72, 23, 54, 40, 18,  2, 13, 17, 19, 87,  2, 27,  8,\n",
      "        53, 33, 77, 44, 77, 36, 84, 53, 10, 45,  2, 18, 71, 69])\n",
      "1151 torch.Size([32, 3, 32, 32]) tensor([88, 87, 35, 83, 23, 63, 96, 53, 60, 10, 82, 92, 16, 10, 56, 40, 82, 76,\n",
      "        45, 87, 64,  3, 64, 30, 90, 31, 47, 74, 13, 43,  3, 41])\n",
      "1152 torch.Size([32, 3, 32, 32]) tensor([45,  8,  4, 70, 21, 73, 31, 86, 48, 61, 14, 53, 94, 93, 79, 95, 12, 95,\n",
      "        84, 65, 83, 48,  1, 50, 56, 42, 24, 73,  1, 52, 48, 36])\n",
      "1153 torch.Size([32, 3, 32, 32]) tensor([92, 21, 87, 26, 71, 21, 46, 86, 15, 75, 45, 60,  4, 68, 90, 11, 61, 17,\n",
      "        88, 41, 39, 59, 94,  9, 85, 86, 12, 24, 32, 81, 90, 99])\n",
      "1154 torch.Size([32, 3, 32, 32]) tensor([22, 40, 73, 78, 42, 13, 90, 18, 69, 36, 57, 14, 98, 82, 28, 17, 47, 39,\n",
      "        44, 73, 93, 27,  3,  7, 82, 66, 18, 67, 58, 54, 83, 59])\n",
      "1155 torch.Size([32, 3, 32, 32]) tensor([91, 36, 18, 93,  7, 35, 90, 53, 77, 67, 54,  4, 26, 21, 89, 80, 59, 72,\n",
      "        26, 61, 42, 17,  0, 17,  5, 48, 66,  9, 36, 83, 27, 43])\n",
      "1156 torch.Size([32, 3, 32, 32]) tensor([47, 28, 23, 36, 18, 69, 70, 49, 74, 17, 42,  3, 10, 61, 76, 43, 50, 90,\n",
      "        97, 36, 64, 61, 15, 38, 61, 62, 83, 12, 56, 31, 10, 99])\n",
      "1157 torch.Size([32, 3, 32, 32]) tensor([45, 37, 41, 30, 31, 52, 96,  3, 53, 76, 22, 70,  2, 91, 35, 68, 41, 65,\n",
      "        61, 24, 12, 39, 16, 52, 82, 95, 17, 50, 46, 76, 39,  1])\n",
      "1158 torch.Size([32, 3, 32, 32]) tensor([51, 61, 29, 80, 79, 29,  2, 55, 15, 58,  9, 84, 76, 42, 39, 15, 24, 97,\n",
      "        91, 40, 74, 67, 10, 29, 33, 37,  1, 91, 15, 47, 48, 19])\n",
      "1159 torch.Size([32, 3, 32, 32]) tensor([33, 37, 86, 81, 73, 94, 64,  8, 57,  3, 78, 34, 62, 59, 43, 54, 30, 82,\n",
      "        44, 60, 48, 52, 61, 91, 87, 13, 53, 47, 85, 38, 37, 63])\n",
      "1160 torch.Size([32, 3, 32, 32]) tensor([35, 74, 23, 30, 92, 84, 64, 80, 95, 45, 42, 48, 94, 17,  1, 38, 93, 22,\n",
      "        29, 31,  1, 44, 32, 59, 60, 99, 70,  2, 21, 49, 66, 77])\n",
      "1161 torch.Size([32, 3, 32, 32]) tensor([38, 42, 45, 15,  8, 80, 74, 74, 38, 96, 36, 40,  2, 78, 44, 84, 84,  4,\n",
      "        99, 99, 39, 48,  2, 13, 48, 71,  0, 83, 99, 14, 98, 32])\n",
      "1162 torch.Size([32, 3, 32, 32]) tensor([29, 25, 47, 75, 11, 32, 41, 57, 81, 10,  3,  9, 26, 87, 84, 49, 66, 66,\n",
      "        50,  4, 67, 46, 96, 93, 69, 34, 79, 96, 88, 36,  8, 89])\n",
      "1163 torch.Size([32, 3, 32, 32]) tensor([ 2, 80, 78, 91, 84, 14, 57, 22, 56, 58, 71, 14, 72, 98, 48, 74, 18, 36,\n",
      "         9, 13,  0, 49, 72, 38, 75, 89, 68, 89, 90,  6, 53,  9])\n",
      "1164 torch.Size([32, 3, 32, 32]) tensor([75, 58, 22, 64, 81, 36, 61, 70, 40, 11, 43, 36,  9, 71, 82, 35, 45, 19,\n",
      "        58, 73, 37, 21, 89, 84, 72, 25, 17,  8, 12, 64, 22, 16])\n",
      "1165 torch.Size([32, 3, 32, 32]) tensor([91, 84, 84, 32, 58, 76,  1, 79, 44, 16, 27, 74, 69,  2, 69, 60, 36, 12,\n",
      "        94, 57, 77, 93,  2, 35, 96, 40, 45, 57, 31,  5, 56, 64])\n",
      "1166 torch.Size([32, 3, 32, 32]) tensor([61, 59, 97, 59, 50, 57, 91, 25, 50, 11, 42, 86, 80, 21, 72, 39, 46, 95,\n",
      "        27, 99, 50,  5, 73, 57, 73, 28, 42, 76, 42, 12, 23, 66])\n",
      "1167 torch.Size([32, 3, 32, 32]) tensor([59,  4, 29, 97, 63, 86, 23,  3, 25, 80, 25, 41, 94, 82, 28, 18, 86, 48,\n",
      "        87, 98, 38, 88,  0, 95,  1, 66,  6, 31,  3, 99, 35, 65])\n",
      "1168 torch.Size([32, 3, 32, 32]) tensor([23, 59, 26, 87, 95, 63,  3, 93, 25, 17, 90, 33, 95, 82, 46, 19, 23, 36,\n",
      "         6, 64,  3, 36,  7, 49, 28, 54, 17, 96, 76, 18, 58, 21])\n",
      "1169 torch.Size([32, 3, 32, 32]) tensor([19, 35, 68, 52, 42, 76, 39, 75, 39, 99, 25, 76,  4, 73, 74, 56, 23, 66,\n",
      "        65, 17, 76, 88, 39, 76, 21, 75, 32, 46, 84, 23, 77, 18])\n",
      "1170 torch.Size([32, 3, 32, 32]) tensor([35, 24, 98, 86, 90, 21, 34,  8, 70, 46, 24, 61, 61, 42, 70, 72, 40, 99,\n",
      "        80, 74, 18, 10, 20, 51, 10,  6, 61, 22, 37,  2, 56, 91])\n",
      "1171 torch.Size([32, 3, 32, 32]) tensor([61, 75, 59,  8, 28,  1, 42, 89, 28, 80, 16, 39, 43, 68, 72, 55, 45, 79,\n",
      "        55, 35, 76, 15, 28, 66, 46, 13, 47, 78, 65, 99, 31, 47])\n",
      "1172 torch.Size([32, 3, 32, 32]) tensor([66, 91, 57, 29,  2, 96, 37, 66, 52, 47, 86, 44,  5, 96,  3, 70, 60, 60,\n",
      "        78, 88, 73, 78, 47, 11, 18, 98, 57, 41, 62, 52, 99, 28])\n",
      "1173 torch.Size([32, 3, 32, 32]) tensor([93,  8, 32, 10, 78,  9, 11, 69, 77,  0, 24, 65, 68, 14, 57, 71, 14, 77,\n",
      "         8, 93, 17, 61, 81, 98, 55, 39, 72, 18, 39,  3, 96, 53])\n",
      "1174 torch.Size([32, 3, 32, 32]) tensor([12, 65, 37, 17, 49, 67, 80, 33, 97, 39, 73, 89, 40, 89, 61, 16, 44, 88,\n",
      "        66, 47, 91, 75, 93, 60, 30, 28, 81, 78, 42, 75, 57, 45])\n",
      "1175 torch.Size([32, 3, 32, 32]) tensor([83, 13, 12, 51, 60, 30, 65, 53,  7, 19,  9, 17, 85, 15, 66, 29, 97, 26,\n",
      "        25, 48, 81, 24, 51,  0, 55, 92, 42, 72, 45, 46, 10, 54])\n",
      "1176 torch.Size([32, 3, 32, 32]) tensor([29, 95, 12, 58, 40, 44,  0, 11, 91, 24, 22, 41, 73, 87, 90, 64, 34, 41,\n",
      "        44, 59, 38,  7, 54, 98, 72, 25, 46, 25, 93, 96,  8, 50])\n",
      "1177 torch.Size([32, 3, 32, 32]) tensor([27, 15, 52, 28, 91, 30, 34, 53,  0, 67, 19, 23, 64, 27, 98, 14, 68,  5,\n",
      "        94, 90, 57,  0, 81, 50,  0, 60, 13, 53, 14, 35, 77, 90])\n",
      "1178 torch.Size([32, 3, 32, 32]) tensor([43, 99, 91, 97, 26, 20, 71, 13, 38, 76, 45,  7, 81, 34, 34, 48, 25, 91,\n",
      "        65, 60, 22, 80, 79, 74, 77, 49, 44, 99, 57, 36, 37, 47])\n",
      "1179 torch.Size([32, 3, 32, 32]) tensor([86, 60,  1, 49, 73, 61, 94, 60,  1,  5, 36, 60, 75, 66,  4, 60, 84, 59,\n",
      "        34,  0, 94,  8, 63, 83, 65, 82, 82, 14, 91, 65, 18, 56])\n",
      "1180 torch.Size([32, 3, 32, 32]) tensor([82, 27, 60, 99, 89, 68, 79, 66, 20, 41, 59, 85, 70, 49,  2, 96, 84, 80,\n",
      "        10, 45, 50, 82,  7, 14, 22, 24, 51, 60, 46, 68, 50, 35])\n",
      "1181 torch.Size([32, 3, 32, 32]) tensor([94, 45, 74, 17, 20, 65, 75, 97, 82, 10, 26, 53,  8, 20, 97,  2, 16, 62,\n",
      "        10, 34, 61, 42, 27, 52,  2, 38, 25, 41, 77, 65, 29,  5])\n",
      "1182 torch.Size([32, 3, 32, 32]) tensor([86, 27, 24, 74, 39, 76, 78, 94, 95, 13, 32,  0, 77, 82, 47, 12, 47, 34,\n",
      "         4, 26, 33, 58,  1, 81,  8, 85, 21, 76, 24, 21, 93, 76])\n",
      "1183 torch.Size([32, 3, 32, 32]) tensor([27, 70, 18, 42, 61, 93, 53, 52, 85, 62, 69,  6, 26, 15, 78, 86, 61, 96,\n",
      "         6, 38, 67, 53,  5, 28,  4,  8, 33, 55,  0, 57, 72, 17])\n",
      "1184 torch.Size([32, 3, 32, 32]) tensor([ 1, 55, 94, 42, 22, 89, 64, 59, 68, 24, 83,  1, 88, 33, 75,  7, 86, 37,\n",
      "        84, 16,  6, 83,  5, 81, 96, 77, 12, 70,  5,  6,  5, 54])\n",
      "1185 torch.Size([32, 3, 32, 32]) tensor([46, 34, 84, 24,  7,  8, 97, 13, 65, 86, 91, 76,  4, 84, 90, 35, 24, 51,\n",
      "        51,  8, 66, 68, 58, 71, 61, 88, 62, 68, 90, 18, 31, 77])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1186 torch.Size([32, 3, 32, 32]) tensor([76,  8, 51, 55, 31, 46, 70,  6, 85,  5, 80, 39, 90,  3, 55, 61, 32,  3,\n",
      "         1, 69, 62, 85, 58, 28, 37, 43, 55, 89,  5,  9, 13, 74])\n",
      "1187 torch.Size([32, 3, 32, 32]) tensor([58, 47, 98, 44, 12, 34, 36, 42, 98, 73, 22, 19, 13, 19, 20, 11, 12,  2,\n",
      "        72,  1, 53, 68, 24, 64, 13, 51, 35, 96, 49, 73, 10, 62])\n",
      "1188 torch.Size([32, 3, 32, 32]) tensor([88,  2, 92, 64,  3,  1, 73, 92, 38,  5, 41, 17, 72, 36, 54, 26, 38, 40,\n",
      "        30, 10, 84, 50, 43, 49, 36,  2, 81, 16, 96, 95,  7, 55])\n",
      "1189 torch.Size([32, 3, 32, 32]) tensor([ 4, 32, 52, 97, 75,  9, 66, 44, 19, 89,  7, 27,  5, 13, 30, 97, 65, 27,\n",
      "        28, 50, 58, 30, 45,  0, 11, 97, 84, 23,  4, 37, 34, 83])\n",
      "1190 torch.Size([32, 3, 32, 32]) tensor([64,  5, 80, 20, 81,  9, 30, 11, 26, 74, 16, 98, 33, 48, 68, 65, 33, 19,\n",
      "        86, 78, 43,  4, 49, 19, 12, 10, 54, 50, 98, 62, 42, 42])\n",
      "1191 torch.Size([32, 3, 32, 32]) tensor([57,  0, 22, 52,  8, 41, 16, 10, 29, 66, 58, 85, 75, 14, 21, 93, 69, 31,\n",
      "        74, 96, 33, 44, 76, 85, 47, 45, 27, 72, 19, 46, 75, 47])\n",
      "1192 torch.Size([32, 3, 32, 32]) tensor([41, 88, 56, 61, 22, 70, 50, 45, 97, 29, 66, 44, 69, 19, 96, 39,  4,  2,\n",
      "        97, 53, 82, 41, 72, 74, 45, 47, 22, 98, 93, 49, 57, 84])\n",
      "1193 torch.Size([32, 3, 32, 32]) tensor([69, 18, 71, 93, 37, 56, 59, 65, 71, 58, 43, 18, 22, 67, 43, 20, 39, 16,\n",
      "        45, 53, 73, 84, 25, 84, 64, 16,  1, 54, 81, 37, 39, 14])\n",
      "1194 torch.Size([32, 3, 32, 32]) tensor([66, 79, 66,  6, 76, 85, 25, 85, 82, 44, 77, 43, 27, 87, 85, 61, 53, 15,\n",
      "        20, 73, 61, 82, 11, 89, 13, 79,  0, 29, 51, 52, 79, 26])\n",
      "1195 torch.Size([32, 3, 32, 32]) tensor([27, 85,  0, 46, 25, 18, 66, 55, 26, 63, 76, 96, 72, 93, 60, 91, 86, 65,\n",
      "         1,  6, 72, 54, 35, 88, 64,  0, 33,  6, 76, 23, 95, 48])\n",
      "1196 torch.Size([32, 3, 32, 32]) tensor([30, 26, 82, 55, 37, 39, 61, 92, 79, 23, 43, 65, 43, 24, 77, 92, 95, 78,\n",
      "         2, 74, 80, 72, 76, 28,  1, 48, 16, 68, 24, 17, 86, 16])\n",
      "1197 torch.Size([32, 3, 32, 32]) tensor([17, 39,  2, 94, 52, 13,  9, 37, 38, 63, 15, 52, 92,  1, 48, 35, 15, 43,\n",
      "        21, 26, 19, 97, 96, 61, 32, 46, 54, 77, 46, 27, 79, 50])\n",
      "1198 torch.Size([32, 3, 32, 32]) tensor([77, 83, 89, 94, 60,  9, 10, 95, 77, 28, 57, 15, 61, 79, 84,  2, 67, 93,\n",
      "        81, 52, 66, 96, 64, 10, 54, 20, 95, 55,  9, 51, 56, 54])\n",
      "1199 torch.Size([32, 3, 32, 32]) tensor([90, 30, 82, 61, 56, 57, 23, 72, 56, 70, 67, 68, 46, 37, 44, 30,  3, 61,\n",
      "        65,  7, 95,  2,  8, 83,  4,  7, 41, 85, 64, 88, 15, 63])\n",
      "1200 torch.Size([32, 3, 32, 32]) tensor([62, 91, 99, 80, 37, 84, 99, 61, 95, 74,  8, 76, 68,  1, 43, 91, 98, 54,\n",
      "        77, 86, 15, 64, 72, 85, 95, 62, 86, 84, 59, 65, 81, 86])\n",
      "1201 torch.Size([32, 3, 32, 32]) tensor([64, 18, 41, 23, 13, 37, 96, 18, 46, 58, 78, 54, 35, 12, 24, 94, 63, 49,\n",
      "        78, 99, 90, 57,  9, 51, 97, 24, 45, 37, 16, 44,  4, 74])\n",
      "1202 torch.Size([32, 3, 32, 32]) tensor([17, 63, 40, 74, 58, 91, 34, 25, 59, 72, 89, 35, 89, 22, 65, 90,  9, 36,\n",
      "        82, 38, 51, 38, 81, 51, 37, 44, 44,  8, 76, 21, 12, 44])\n",
      "1203 torch.Size([32, 3, 32, 32]) tensor([45, 92,  6, 74,  3, 47, 49, 73, 12, 64, 21, 77, 48,  9, 41, 86, 78, 51,\n",
      "        44, 42, 44, 58,  1, 90, 48, 78, 68, 69, 34,  0, 89, 71])\n",
      "1204 torch.Size([32, 3, 32, 32]) tensor([25, 25, 11, 75, 94, 74, 94, 21, 63, 52, 63, 11, 34, 54, 81, 78, 42,  5,\n",
      "        44, 91, 87, 63, 82, 16, 58, 91, 76, 82, 80, 94, 31, 76])\n",
      "1205 torch.Size([32, 3, 32, 32]) tensor([54, 67, 88, 26, 10, 26, 10, 22, 15, 11, 74, 25, 18, 59, 34,  9, 18, 80,\n",
      "        41, 85, 32, 10, 67, 16, 24, 12, 92, 66,  0, 28,  9, 57])\n",
      "1206 torch.Size([32, 3, 32, 32]) tensor([99, 22, 51, 53, 56, 91, 17, 75, 27, 30, 16, 68, 54,  4, 60, 16,  3, 37,\n",
      "        43, 86,  6,  8, 13, 25, 29, 61, 50, 37, 79, 26, 92,  6])\n",
      "1207 torch.Size([32, 3, 32, 32]) tensor([82, 65, 99, 21, 80,  5, 53, 34,  3,  2, 58, 67, 47, 15, 26, 10, 15, 77,\n",
      "        54, 92, 10, 63, 66, 91, 17, 52, 33, 37, 83, 56, 79, 52])\n",
      "1208 torch.Size([32, 3, 32, 32]) tensor([76, 92, 95, 51, 65, 72,  6, 83, 64, 61,  7, 89, 76, 57,  3, 12, 50, 20,\n",
      "         6, 35,  0, 62, 12, 32, 35,  9, 95, 39, 67, 77, 44, 87])\n",
      "1209 torch.Size([32, 3, 32, 32]) tensor([42, 19, 19, 80, 60, 28, 23, 13,  2, 59, 86, 74, 56, 29, 29, 11, 72, 53,\n",
      "        67, 84, 64, 11, 26, 79, 70, 26, 78, 74, 60,  7, 14, 40])\n",
      "1210 torch.Size([32, 3, 32, 32]) tensor([75, 51, 73, 52, 75, 94, 11, 67, 22, 95, 38, 88, 27, 94, 11, 49, 15, 33,\n",
      "        33, 74, 21, 48,  5,  6, 65, 25, 58, 67, 59, 90, 91, 42])\n",
      "1211 torch.Size([32, 3, 32, 32]) tensor([77, 69, 83, 68, 62,  1, 54, 92, 19, 85, 70, 14, 49, 30, 20, 85, 77, 63,\n",
      "         8, 25,  7, 86, 84, 74, 50, 41, 96, 67, 75, 82, 65, 43])\n",
      "1212 torch.Size([32, 3, 32, 32]) tensor([79, 66, 41,  5, 15, 18,  0, 54, 26, 94, 90, 97, 92, 80, 11,  1, 13, 69,\n",
      "        18, 71, 69, 98, 45, 22,  4, 30, 97, 62, 31, 56, 81, 79])\n",
      "1213 torch.Size([32, 3, 32, 32]) tensor([46, 74, 87, 96, 98, 70, 48, 31,  8, 19, 20, 18,  8, 44, 40, 56, 71, 92,\n",
      "         5, 78, 96,  1, 30, 85, 31, 35,  2, 95, 10, 15, 47, 66])\n",
      "1214 torch.Size([32, 3, 32, 32]) tensor([76, 62, 19, 81, 51, 84, 88, 52, 16, 33, 37, 87, 98, 35,  4,  6, 22, 66,\n",
      "         0, 73, 83, 48, 14, 69, 43,  9, 79, 34, 50, 58, 56, 28])\n",
      "1215 torch.Size([32, 3, 32, 32]) tensor([86, 21, 13, 40, 65, 56, 34, 27, 92, 40, 95, 31, 83, 48, 65, 86, 87,  1,\n",
      "        47, 86, 49, 90, 19, 75,  4, 34,  2, 62, 92, 11, 67, 10])\n",
      "1216 torch.Size([32, 3, 32, 32]) tensor([ 6, 28, 97, 63, 15, 38, 78, 38, 73, 79, 82, 60, 58, 94,  7, 68, 38, 83,\n",
      "        59,  1, 63, 60,  2, 68, 68, 68, 88, 28, 67,  7, 56, 89])\n",
      "1217 torch.Size([32, 3, 32, 32]) tensor([93, 41, 13, 42, 66, 78, 44, 70, 35, 80, 38, 94, 77, 66,  6, 59, 20, 61,\n",
      "        56, 19, 98, 27, 43, 79, 44, 52, 30, 57,  8, 30, 33, 66])\n",
      "1218 torch.Size([32, 3, 32, 32]) tensor([42, 43, 44, 99, 23, 38, 33, 95, 73,  4, 61, 60, 62, 88, 71, 21, 41, 34,\n",
      "        67, 19, 79, 39, 66, 25, 70, 28, 82, 84, 41, 49, 76, 57])\n",
      "1219 torch.Size([32, 3, 32, 32]) tensor([95, 52, 12, 99, 53, 62, 35, 12,  4, 27, 69, 27, 58, 98,  2, 93, 67, 17,\n",
      "         9, 19,  4, 44, 65, 56, 86, 92, 61, 46, 58, 57, 66, 31])\n",
      "1220 torch.Size([32, 3, 32, 32]) tensor([20, 46, 48, 33, 21, 55, 36, 58, 80, 93, 18, 42,  5, 77, 41, 43, 12, 26,\n",
      "        54, 90, 36, 63,  0,  2, 73, 39,  3, 66, 59,  8, 34, 48])\n",
      "1221 torch.Size([32, 3, 32, 32]) tensor([56, 22, 94, 26, 77, 96, 67, 26, 86, 59, 38, 10, 46, 92, 11, 11, 32, 24,\n",
      "        31, 63,  0,  8, 40,  4,  3,  8, 34, 48, 45, 39,  7, 24])\n",
      "1222 torch.Size([32, 3, 32, 32]) tensor([69, 94, 14, 22, 95, 76, 60, 44, 40, 90, 95, 44, 55, 86, 55, 22, 88, 60,\n",
      "        62, 23, 15, 79, 92, 21, 85, 92, 85, 15,  0, 74, 40, 21])\n",
      "1223 torch.Size([32, 3, 32, 32]) tensor([17, 53, 58, 31, 16, 68, 70,  7, 84, 61, 41, 52, 74, 34, 89, 74, 15, 86,\n",
      "        61, 47, 74, 58, 26, 99, 88, 20, 97, 31, 24, 66, 61, 52])\n",
      "1224 torch.Size([32, 3, 32, 32]) tensor([18, 48, 73, 51, 85, 39, 66, 59, 25, 16, 56, 99, 98, 72, 54, 58, 55, 65,\n",
      "        38, 49, 43, 26, 82,  0, 36, 62, 27, 59, 58, 53, 68, 44])\n",
      "1225 torch.Size([32, 3, 32, 32]) tensor([44, 85, 89, 18,  9, 35, 70, 96, 92, 69, 22, 17, 71, 85, 30, 40,  7,  8,\n",
      "        20, 74, 83, 26, 15, 89, 74, 30, 21, 33, 33, 60, 34,  0])\n",
      "1226 torch.Size([32, 3, 32, 32]) tensor([18, 12, 18, 18, 75, 78, 10, 15, 38, 51, 10,  7, 24, 69, 58, 65, 27, 77,\n",
      "        76, 87,  9, 96, 71, 66, 21, 34, 23, 76, 98,  9,  2, 27])\n",
      "1227 torch.Size([32, 3, 32, 32]) tensor([36, 95,  2, 58, 68, 11, 35,  6, 45, 70, 97, 75, 78,  6, 40, 17, 32, 45,\n",
      "        13,  1, 27, 26, 51, 31, 25, 47, 65, 59, 61, 20, 12, 92])\n",
      "1228 torch.Size([32, 3, 32, 32]) tensor([59, 58, 70, 80, 66, 94, 42, 25, 40, 14,  9, 67, 41, 42, 15, 99, 91, 17,\n",
      "        67,  8,  7, 68, 34, 78, 26,  4, 54, 76, 57, 17, 24, 27])\n",
      "1229 torch.Size([32, 3, 32, 32]) tensor([54, 86, 25, 50, 89, 63, 78, 46, 51, 62,  7, 40, 65, 80,  1, 89, 38, 80,\n",
      "        67, 89, 24, 63, 54, 73, 37, 48, 64, 10, 16, 31, 45, 24])\n",
      "1230 torch.Size([32, 3, 32, 32]) tensor([ 4, 61, 33, 51, 58, 28, 53, 78, 68, 23,  8, 91, 15, 14, 49, 11, 26, 39,\n",
      "         3, 36, 89, 36, 73, 14, 65, 69, 93, 35, 14, 51, 67, 54])\n",
      "1231 torch.Size([32, 3, 32, 32]) tensor([56, 90, 85, 99,  8, 50, 73, 53, 42, 63, 16, 73, 97, 24, 73, 21, 73, 48,\n",
      "        51, 67, 46, 30, 86, 57, 66, 10, 56, 24, 11, 52, 65, 33])\n",
      "1232 torch.Size([32, 3, 32, 32]) tensor([95, 92, 65, 26, 68, 44, 27, 24,  1, 35, 70, 71, 95, 98, 12, 49, 78, 51,\n",
      "        52,  5, 98, 44, 45, 88, 44, 30, 31, 53, 30,  7, 97, 72])\n",
      "1233 torch.Size([32, 3, 32, 32]) tensor([44, 84, 57, 12, 35, 29, 34, 16, 80, 75, 10, 91, 30, 82, 65, 96, 99, 77,\n",
      "         7, 20, 64, 26, 95, 73, 39, 43,  3, 26, 44, 49, 33, 78])\n",
      "1234 torch.Size([32, 3, 32, 32]) tensor([11, 55, 27, 96,  8, 30, 39, 49, 69, 10, 13,  2, 59, 82, 48, 76, 77, 87,\n",
      "        99, 10, 95, 77, 40, 86, 60, 12, 40, 36, 17, 31, 48, 60])\n",
      "1235 torch.Size([32, 3, 32, 32]) tensor([61, 62, 23, 48, 21, 16, 71, 79, 56, 56, 91, 89, 17,  3, 76, 85, 20, 93,\n",
      "        46, 48, 96, 29, 24, 45, 52, 59, 35, 65, 46, 81, 24, 76])\n",
      "1236 torch.Size([32, 3, 32, 32]) tensor([45, 19, 89, 46, 29, 72, 73, 82, 85, 75, 73, 47, 34, 22,  9, 17, 71, 72,\n",
      "        41, 89, 76, 65, 74, 72, 89, 20, 17, 38, 27, 14, 45, 65])\n",
      "1237 torch.Size([32, 3, 32, 32]) tensor([61, 59, 53, 65, 56, 14, 55, 78, 52, 49, 86, 12, 83, 70, 76, 74, 17, 81,\n",
      "        91, 25, 89, 99, 71, 83, 60, 41, 31, 72, 26, 48, 91, 74])\n",
      "1238 torch.Size([32, 3, 32, 32]) tensor([ 0, 75, 26, 55, 80, 77, 74, 97, 75, 45,  0, 41,  5, 96, 14,  5, 29, 16,\n",
      "        53, 15, 77, 95, 46,  4, 81, 16, 70, 48, 22, 26, 68, 78])\n",
      "1239 torch.Size([32, 3, 32, 32]) tensor([69, 87, 85, 79, 18, 41, 89, 51, 23, 94, 16, 50, 70, 68, 95, 89, 27,  4,\n",
      "        23, 93, 88, 62, 28, 64, 91, 97, 31, 29, 58, 80, 43, 10])\n",
      "1240 torch.Size([32, 3, 32, 32]) tensor([81, 12, 26, 97, 75, 81, 95, 75, 26, 52, 75, 27, 61, 62, 58,  1, 21, 57,\n",
      "        17, 70, 37, 18, 45, 78, 89, 71, 74, 40, 68, 13, 33, 60])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1241 torch.Size([32, 3, 32, 32]) tensor([ 7, 60, 85, 73, 24, 73, 97, 32, 99,  0, 35, 99, 60, 62, 12, 68, 12, 48,\n",
      "        17,  6, 84, 71, 89, 26, 75, 42,  0, 54, 46, 33, 39, 62])\n",
      "1242 torch.Size([32, 3, 32, 32]) tensor([53, 81, 92, 94, 15, 11,  9,  2, 38, 81,  2, 81, 35, 53, 19, 73, 75, 82,\n",
      "        74, 92, 69, 27, 89, 24, 63, 92, 33, 46, 22, 44, 12, 20])\n",
      "1243 torch.Size([32, 3, 32, 32]) tensor([40, 90, 89, 90, 48, 74, 51, 66, 64, 61, 75, 28, 32, 29, 19, 16, 33, 13,\n",
      "        45, 43, 88, 47, 77, 39,  8, 78, 92, 62, 44, 15, 96, 41])\n",
      "1244 torch.Size([32, 3, 32, 32]) tensor([26, 91,  4, 83, 66, 67, 26, 70, 96, 76, 74, 71, 26, 91, 88, 16,  4, 31,\n",
      "        68, 14, 17, 85, 82, 68, 70, 39, 60, 16, 39,  2,  4, 83])\n",
      "1245 torch.Size([32, 3, 32, 32]) tensor([20,  6,  1, 63, 71, 43, 94, 69, 65, 26, 83, 26, 99, 85, 88, 38, 74, 21,\n",
      "        98, 19, 99,  8, 18,  0,  6, 83, 57, 63, 34, 60, 47, 64])\n",
      "1246 torch.Size([32, 3, 32, 32]) tensor([22, 89, 98, 72, 50,  9, 96, 72, 71, 37, 96, 78, 78, 70, 37, 69, 84, 81,\n",
      "        21, 88, 28,  2, 36, 35, 80,  5, 74,  9,  3, 85, 94,  2])\n",
      "1247 torch.Size([32, 3, 32, 32]) tensor([ 6, 26, 93, 28, 83, 80, 78, 91, 55, 73, 28, 44, 96, 63,  0, 16,  1,  8,\n",
      "        87, 57, 10, 48, 11,  1, 97, 51, 66,  5, 80, 39, 41, 67])\n",
      "1248 torch.Size([32, 3, 32, 32]) tensor([59, 62, 85, 41, 99, 63, 49,  8, 48, 43, 40, 14, 59, 32, 10, 17, 40, 18,\n",
      "        19, 54, 81, 61, 41, 15,  9, 25, 86,  1, 52, 58, 18, 43])\n",
      "1249 torch.Size([32, 3, 32, 32]) tensor([16, 68, 44, 66, 91, 98, 15, 20, 59,  9, 27, 91, 22, 70, 54, 36,  0, 80,\n",
      "        55, 66, 25,  3, 92,  7, 67, 53, 40, 88, 46, 47, 68,  6])\n",
      "1250 torch.Size([32, 3, 32, 32]) tensor([57, 96, 69,  7, 71, 34, 69, 18, 44,  2, 75, 95, 82, 27, 10, 39,  1, 97,\n",
      "        32, 57, 63, 62, 40, 88, 26, 32, 56,  0, 93, 47, 85, 52])\n",
      "1251 torch.Size([32, 3, 32, 32]) tensor([19, 45, 41, 98,  8,  9, 48, 78, 73, 21, 92, 95,  5, 69, 70, 55, 94, 36,\n",
      "        81, 66, 19,  2, 57, 74, 88,  5, 46, 93,  5,  3, 47,  9])\n",
      "1252 torch.Size([32, 3, 32, 32]) tensor([98, 10, 35, 39, 29, 30, 58, 89, 28, 57, 11, 46, 64, 44, 93, 48, 39, 81,\n",
      "        55,  4, 15, 55, 64,  8, 23, 51, 31, 65, 12, 15, 78,  7])\n",
      "1253 torch.Size([32, 3, 32, 32]) tensor([98, 97, 63, 85, 80, 86, 97, 68, 25, 12, 68, 49,  3, 22, 58, 39,  6, 60,\n",
      "        16, 19, 32, 16, 44, 46, 40, 74, 51, 92, 64, 39, 33, 41])\n",
      "1254 torch.Size([32, 3, 32, 32]) tensor([76, 99, 87, 97, 32, 69, 61, 28,  3, 70, 57, 27,  9, 85, 44, 28, 48, 16,\n",
      "        38, 86, 88, 68, 49, 52, 71, 61, 54, 57, 13, 18, 22, 57])\n",
      "1255 torch.Size([32, 3, 32, 32]) tensor([56, 88, 28, 12, 83, 48, 17, 97, 10, 25, 24,  4, 68, 73, 44, 93, 97, 99,\n",
      "        49, 26, 88, 57, 95,  0, 48, 41, 14, 66, 80, 11, 46, 11])\n",
      "1256 torch.Size([32, 3, 32, 32]) tensor([ 0, 51, 99, 99, 71, 35, 83, 63,  9, 40, 11, 57, 52, 80, 54, 71,  8, 20,\n",
      "        18, 39, 87, 45, 76, 74, 24, 75, 70, 10, 58, 32, 78, 70])\n",
      "1257 torch.Size([32, 3, 32, 32]) tensor([60, 35, 33, 14, 98, 77, 24, 44, 38, 72,  7, 43,  2, 83, 16, 33, 62, 44,\n",
      "         3, 87, 46, 84, 30, 51, 91, 28, 99, 31, 90, 11, 82, 62])\n",
      "1258 torch.Size([32, 3, 32, 32]) tensor([98, 66, 21, 42, 60, 12, 85, 32,  3, 26,  9,  8, 74, 11, 97, 27,  3, 41,\n",
      "        86, 31, 44, 16, 32, 74, 95, 42, 37, 79, 58, 25, 18, 76])\n",
      "1259 torch.Size([32, 3, 32, 32]) tensor([59, 99,  1, 86, 41, 13, 78, 96, 10, 98, 98, 93,  5, 77, 72, 79, 29, 93,\n",
      "        62, 61, 40, 29, 46, 36,  2,  0, 45, 31, 82, 37, 46, 34])\n",
      "1260 torch.Size([32, 3, 32, 32]) tensor([93, 15, 71, 37, 49,  3, 31, 67,  6, 47, 97,  5, 87, 91, 18, 11, 10, 92,\n",
      "        88,  5, 80,  5, 98, 86, 68, 37,  5, 86, 48, 77, 24, 73])\n",
      "1261 torch.Size([32, 3, 32, 32]) tensor([85, 65, 82, 52, 70,  1, 17, 64, 32,  3, 28, 41, 74, 56, 99,  8, 38, 81,\n",
      "        80,  0, 57, 78, 62,  5, 41, 39, 49, 19, 11, 73, 89, 27])\n",
      "1262 torch.Size([32, 3, 32, 32]) tensor([86, 76, 66, 40, 69, 74, 81, 14, 15, 12, 91, 36, 38, 81, 61, 81, 99, 70,\n",
      "        38, 44, 82, 18, 73,  0, 59,  5, 75, 28, 53, 43, 30, 91])\n",
      "1263 torch.Size([32, 3, 32, 32]) tensor([ 7, 94, 56,  8, 23, 71,  8, 71, 33, 34, 64, 88, 56, 21, 32, 68, 73, 12,\n",
      "        48, 21, 87, 20, 66, 33,  6, 86,  7,  7, 37, 61, 85, 39])\n",
      "1264 torch.Size([32, 3, 32, 32]) tensor([86, 70,  9, 85, 72, 90, 99, 70, 97, 35, 44, 87,  7, 90, 88, 51, 63, 53,\n",
      "        88, 71, 93, 23, 60, 33, 22, 63, 51, 13, 85, 24, 77, 27])\n",
      "1265 torch.Size([32, 3, 32, 32]) tensor([14, 29, 46, 92, 65, 38, 79,  3, 47, 59, 80, 50, 60, 85, 17, 16, 51, 15,\n",
      "        26, 27, 59, 61,  4, 15, 51, 20, 20, 73, 42,  5, 16, 33])\n",
      "1266 torch.Size([32, 3, 32, 32]) tensor([93, 90,  4, 52, 20, 69, 88, 59, 63, 64, 50, 36, 29, 46, 45, 58, 46, 91,\n",
      "        35, 56, 92, 40, 61, 98, 94, 15, 59, 70, 97,  2, 84, 58])\n",
      "1267 torch.Size([32, 3, 32, 32]) tensor([53, 72, 44, 82,  0, 14, 29, 55, 88, 37, 47, 80, 76, 92, 39, 69, 71, 49,\n",
      "        11,  3,  9,  8, 14, 51, 91, 69, 41, 30,  9, 21, 62, 33])\n",
      "1268 torch.Size([32, 3, 32, 32]) tensor([68,  2, 41, 64, 35, 65, 19, 84, 59, 14, 59, 91, 76, 36, 68, 22, 47, 39,\n",
      "        71, 59, 39, 22,  8, 72, 67, 75, 21, 70, 77, 84, 16, 38])\n",
      "1269 torch.Size([32, 3, 32, 32]) tensor([35, 67, 24, 49, 22,  8, 60, 71, 93, 75, 56, 10, 99, 32, 80, 71, 90, 56,\n",
      "        58, 69, 22, 40, 88, 47, 88,  7, 33, 35, 37, 68, 59, 48])\n",
      "1270 torch.Size([32, 3, 32, 32]) tensor([87, 19, 97, 45, 84, 58,  0, 96, 56, 58, 89, 61, 91, 81, 79, 88, 65, 45,\n",
      "         5,  1, 35, 33, 59, 74, 55,  8, 19, 95, 24, 65, 42, 16])\n",
      "1271 torch.Size([32, 3, 32, 32]) tensor([56, 94, 43,  9, 19, 98, 36, 23, 14, 81,  4, 76, 35, 73, 19, 53, 67, 62,\n",
      "        89, 26, 29, 24, 12, 91, 23,  8, 87, 18, 56, 52, 45, 40])\n",
      "1272 torch.Size([32, 3, 32, 32]) tensor([31, 59, 13, 64, 15, 70, 91, 53, 66, 16, 65, 35,  6, 99, 52, 61, 66, 86,\n",
      "        96, 53, 64, 83, 90, 76, 87, 34, 59, 37, 25, 89, 77,  3])\n",
      "1273 torch.Size([32, 3, 32, 32]) tensor([65, 72, 86, 20, 92, 31, 32,  4, 93, 95,  9, 22, 19, 21, 16, 38, 53, 73,\n",
      "        37, 42, 62, 83, 57, 76, 15, 58, 28, 55, 26, 78, 27, 67])\n",
      "1274 torch.Size([32, 3, 32, 32]) tensor([33, 90, 12, 19, 26,  8, 93, 78, 51, 53, 19, 88, 99, 88, 78, 99, 15, 22,\n",
      "        25,  5, 41, 94,  1, 59, 11, 90, 49, 75,  7, 94,  6, 72])\n",
      "1275 torch.Size([32, 3, 32, 32]) tensor([92, 53,  0, 92, 20, 66, 59, 82, 39, 28, 82,  0, 38, 53, 32, 86, 97, 28,\n",
      "        16, 38, 26, 35, 36, 83, 55, 63, 73, 82, 62, 13, 51, 87])\n",
      "1276 torch.Size([32, 3, 32, 32]) tensor([22, 38, 19, 11, 10, 36,  5,  2, 34, 80, 92, 86, 91,  8, 62, 65, 25, 60,\n",
      "        67, 41, 45,  4, 98, 23, 17, 36,  0, 33, 98, 27, 83, 25])\n",
      "1277 torch.Size([32, 3, 32, 32]) tensor([19, 67, 29,  8, 25, 91, 59, 32, 90, 20, 86,  1, 18, 33, 40, 70, 43, 18,\n",
      "         8, 87, 94, 94, 76,  0, 33, 15, 48, 87,  7, 49,  4, 15])\n",
      "1278 torch.Size([32, 3, 32, 32]) tensor([30, 50,  5, 15, 55,  1, 24, 69, 91, 82, 84,  9, 68,  2, 64, 24, 45, 89,\n",
      "        75, 72, 16, 73,  5,  0, 28, 61, 27, 34,  4, 86,  1, 66])\n",
      "1279 torch.Size([32, 3, 32, 32]) tensor([89, 86, 22, 28, 50,  2, 62, 32, 30, 32, 30, 73, 92, 32, 61, 13, 53, 82,\n",
      "        78,  0, 73, 57, 46, 54, 34,  2, 79, 13, 71, 85, 34, 12])\n",
      "1280 torch.Size([32, 3, 32, 32]) tensor([19, 32, 60, 50, 70, 54, 47, 37, 59, 77, 32, 71, 36, 27, 93, 31, 88, 20,\n",
      "        81, 51, 52, 23, 60, 80,  4, 71, 41, 58,  5, 91,  7, 66])\n",
      "1281 torch.Size([32, 3, 32, 32]) tensor([85, 79,  3, 93, 21, 27, 53, 15, 94, 76, 45, 34, 24, 98, 88, 16, 73, 86,\n",
      "        88, 88, 52, 77, 15, 63, 97, 39, 16, 91,  8, 60, 67, 79])\n",
      "1282 torch.Size([32, 3, 32, 32]) tensor([91, 46, 23, 67, 50, 87, 28, 79, 56, 96, 22, 77, 65, 60, 43, 64, 42, 66,\n",
      "        65, 99, 59, 59, 98, 15, 56, 41, 94, 66, 84, 53, 66, 28])\n",
      "1283 torch.Size([32, 3, 32, 32]) tensor([90, 41, 64, 84, 94,  7, 75, 70, 49, 55, 88, 18, 80, 45, 20, 42, 74, 55,\n",
      "        77,  9, 41, 18, 50, 13, 43, 66, 33, 73, 84, 29, 77, 16])\n",
      "1284 torch.Size([32, 3, 32, 32]) tensor([97, 58,  6, 67, 63, 93, 20, 76, 52, 86, 88, 88, 70,  4, 88,  5, 71, 86,\n",
      "        42, 28, 33, 57, 36, 50, 95, 78, 17, 34, 15, 86, 61, 50])\n",
      "1285 torch.Size([32, 3, 32, 32]) tensor([23, 96, 68,  3, 40, 67, 12, 49, 15, 69, 66, 59,  3,  0, 14, 10, 54, 28,\n",
      "        42, 82, 78, 92, 81,  1, 80, 50, 43, 40,  7, 57, 89, 71])\n",
      "1286 torch.Size([32, 3, 32, 32]) tensor([44, 60, 51, 41, 18, 51, 89, 55, 30, 42,  2, 25, 62, 50, 82, 21, 26, 85,\n",
      "        38, 33, 89, 30,  1, 92, 55, 14, 37, 65, 25, 31, 96, 63])\n",
      "1287 torch.Size([32, 3, 32, 32]) tensor([ 0, 84, 21, 76, 94, 46, 88, 47, 47, 51, 48, 75, 20,  7, 39, 31, 68, 65,\n",
      "        16, 70, 57, 83, 30,  3, 10, 61, 15, 49, 94,  2, 74, 89])\n",
      "1288 torch.Size([32, 3, 32, 32]) tensor([27, 78, 57,  3, 29, 93, 58, 81, 74, 37, 26, 12, 69, 95, 63, 40, 68, 88,\n",
      "        97,  9,  6, 52, 34, 38, 52, 56,  5, 84, 81, 92, 92, 93])\n",
      "1289 torch.Size([32, 3, 32, 32]) tensor([89, 96, 12,  5, 38,  5, 91, 91, 72,  8, 89, 33, 40, 80, 95,  6, 11, 77,\n",
      "        81,  8, 97, 30, 80, 62, 75,  6, 77, 28,  8, 83, 48, 31])\n",
      "1290 torch.Size([32, 3, 32, 32]) tensor([84, 81, 20, 64,  1, 90, 47, 69,  2, 65, 95, 39, 51, 80, 28, 15, 15, 83,\n",
      "         4, 17, 71, 70, 17, 31, 49, 36, 52, 43, 52, 94, 79, 14])\n",
      "1291 torch.Size([32, 3, 32, 32]) tensor([40, 36, 76, 84, 58, 97, 25,  5, 63, 26,  2, 36, 15, 55, 12, 26, 88,  3,\n",
      "        80, 81, 66, 37, 54,  0, 81, 58, 78, 65, 56,  1, 26, 57])\n",
      "1292 torch.Size([32, 3, 32, 32]) tensor([ 7, 19, 94, 75, 11, 78, 76, 67, 65, 67,  8, 46, 10,  8,  0, 81, 48, 92,\n",
      "        54, 35,  2, 77, 92, 11, 33, 11,  2, 83, 75, 73, 33, 28])\n",
      "1293 torch.Size([32, 3, 32, 32]) tensor([ 6,  6, 28, 29, 61, 20, 25, 56, 67, 49, 39, 52, 49, 75, 25,  9, 79, 72,\n",
      "        27, 52, 56, 54, 26, 87, 83, 36, 15, 49, 60, 80,  1,  0])\n",
      "1294 torch.Size([32, 3, 32, 32]) tensor([52, 38, 32, 88, 64,  9, 59, 51, 79, 39, 39, 49, 19, 91, 38, 95, 27, 42,\n",
      "        80, 17, 89, 40, 55, 75, 87, 54, 91, 89, 37, 14, 65,  9])\n",
      "1295 torch.Size([32, 3, 32, 32]) tensor([11, 94, 25, 42, 76, 54, 89, 64, 96, 54, 24, 88, 78, 49, 89, 21, 54, 34,\n",
      "        31, 83, 74, 18, 14, 37, 89, 82, 98, 66, 85, 91, 81,  8])\n",
      "1296 torch.Size([32, 3, 32, 32]) tensor([53, 84, 43, 55, 27, 98, 67, 63, 20, 21, 91, 52,  7, 26, 99, 98, 69, 57,\n",
      "        67, 37, 35,  2, 64, 23,  7, 12, 28, 57, 71, 96, 65, 79])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1297 torch.Size([32, 3, 32, 32]) tensor([27, 18, 46, 47, 68, 87, 75,  5,  0, 81, 81, 10, 71, 78, 99, 32, 28, 76,\n",
      "        73, 12,  0, 81, 17, 27, 80, 23, 17, 81, 39, 22, 84, 89])\n",
      "1298 torch.Size([32, 3, 32, 32]) tensor([91, 83, 21, 11, 39, 61, 41, 34, 12, 93, 56, 60, 65, 58, 80, 43,  2, 87,\n",
      "        72, 36, 67, 89, 69, 34, 57, 54, 77, 49, 49, 41, 39, 33])\n",
      "1299 torch.Size([32, 3, 32, 32]) tensor([62, 70, 67, 20,  1, 41, 84, 65, 79, 43, 12,  8, 26, 75, 75,  2, 32, 91,\n",
      "        43,  6, 18, 72,  0,  4, 88, 53, 65, 38,  5, 49, 13, 17])\n",
      "1300 torch.Size([32, 3, 32, 32]) tensor([31, 75, 70, 65, 57, 32, 79, 23, 83,  3, 49, 40, 66, 55, 29, 45,  5, 46,\n",
      "        31, 19, 82, 13, 56, 22, 19, 58, 27, 11, 58, 80, 21, 75])\n",
      "1301 torch.Size([32, 3, 32, 32]) tensor([72, 26, 89, 28, 87, 53, 28, 38, 72, 63,  8, 83, 55, 51,  1, 65, 68,  6,\n",
      "        45, 62, 39, 92, 97, 31, 42, 66,  3, 16, 98, 79, 10, 25])\n",
      "1302 torch.Size([32, 3, 32, 32]) tensor([33,  1, 33, 18, 15, 60, 47, 40, 66, 14, 10, 26, 37,  2, 19, 23, 14, 85,\n",
      "        29, 68, 54, 19, 52, 43, 89,  9, 11, 20, 85, 62, 11, 71])\n",
      "1303 torch.Size([32, 3, 32, 32]) tensor([71,  4, 59, 61, 79, 30, 33, 20, 47, 61, 94, 77, 19, 68, 56, 49, 94, 18,\n",
      "        73, 91, 41, 34, 82,  9, 83,  8, 37, 15, 50, 42, 44, 48])\n",
      "1304 torch.Size([32, 3, 32, 32]) tensor([64,  0, 53, 62, 31, 61, 96, 49, 80, 15, 76, 15, 47, 76, 70, 41, 37, 30,\n",
      "        83,  5, 48, 70, 74, 88, 65, 49, 81, 90, 97, 15, 43, 89])\n",
      "1305 torch.Size([32, 3, 32, 32]) tensor([48, 18, 97, 46, 64, 24, 81, 64, 49, 81, 72,  0, 85, 52, 89, 25, 72, 10,\n",
      "        44, 37, 77, 19, 67, 18, 40, 19, 48, 13, 42, 72, 73, 17])\n",
      "1306 torch.Size([32, 3, 32, 32]) tensor([84, 59,  5, 38, 35, 45, 65, 74, 56, 13, 89, 99, 66, 79, 68, 87, 75, 91,\n",
      "        35, 40, 36, 22, 30, 67,  9, 72, 93, 81, 72, 47, 90,  6])\n",
      "1307 torch.Size([32, 3, 32, 32]) tensor([ 9,  3, 34, 82, 72, 68, 83, 11,  4, 32, 69, 30, 26, 42,  4, 30, 75, 78,\n",
      "        44, 37, 26, 30, 66, 47, 98, 36, 87, 93, 89, 37, 36, 51])\n",
      "1308 torch.Size([32, 3, 32, 32]) tensor([39,  5, 93,  2, 92, 69, 86,  9, 21, 67, 59, 73, 75, 98, 19,  4, 33, 14,\n",
      "        96, 94, 10, 45, 67, 33, 75, 89, 74,  9,  4, 45, 38, 41])\n",
      "1309 torch.Size([32, 3, 32, 32]) tensor([77, 51, 79, 51, 57, 96, 36, 82, 96, 93, 22, 44, 97, 34, 10, 39, 58, 44,\n",
      "        48, 34, 21, 72, 14, 19, 60, 10, 57, 92, 32, 47, 83, 10])\n",
      "1310 torch.Size([32, 3, 32, 32]) tensor([82, 56, 72, 36, 90, 29, 17, 37, 98,  3, 80, 14, 49,  2, 38, 55, 20, 74,\n",
      "        16, 29, 58, 25, 27, 63, 22, 11,  8, 11, 23,  8, 25,  5])\n",
      "1311 torch.Size([32, 3, 32, 32]) tensor([95, 63, 83, 76, 98, 75, 31, 77,  1, 51, 60, 37, 21, 27, 54, 79, 14, 32,\n",
      "        32, 25, 17, 23,  6, 82, 75, 46, 77, 18,  9, 80, 35, 17])\n",
      "1312 torch.Size([32, 3, 32, 32]) tensor([93,  5, 60, 97, 12, 40, 45, 46, 51,  6, 93,  7, 23, 76, 21, 77, 96, 95,\n",
      "        12, 51,  9, 37, 47, 67, 39, 86, 35, 33, 18, 47, 49,  2])\n",
      "1313 torch.Size([32, 3, 32, 32]) tensor([13,  2, 56, 28, 42, 59,  2, 34, 32, 50,  8, 46, 57, 76, 85, 81, 49, 48,\n",
      "        88, 75, 60, 72, 10, 32, 38, 75,  2, 81, 68, 15, 56, 91])\n",
      "1314 torch.Size([32, 3, 32, 32]) tensor([25, 40,  7,  6, 73,  5, 41, 28, 20, 96, 13, 16, 31,  7, 67, 77, 17, 91,\n",
      "        63, 81, 88, 77, 83, 57, 59, 93, 99, 14, 45, 37, 11, 70])\n",
      "1315 torch.Size([32, 3, 32, 32]) tensor([53, 24, 31, 82, 23, 85, 70,  2, 27, 26, 65, 72, 63, 24, 58, 35, 17, 54,\n",
      "        63,  7, 48, 21,  7,  8, 86,  4, 11, 78,  6, 25, 83, 10])\n",
      "1316 torch.Size([32, 3, 32, 32]) tensor([35,  3, 75, 69,  1, 60, 44,  4, 22, 89, 77, 63, 35, 97, 65, 89, 39, 97,\n",
      "        99, 39, 43, 11, 75, 33,  8, 68, 73, 42, 97, 20, 93, 40])\n",
      "1317 torch.Size([32, 3, 32, 32]) tensor([39, 22, 64, 17, 61, 33, 39, 45, 58,  2, 66, 98, 65, 53, 97, 23, 14, 18,\n",
      "        23, 73, 19, 27, 77, 60, 39, 37, 36, 54, 33, 39, 63, 66])\n",
      "1318 torch.Size([32, 3, 32, 32]) tensor([37, 23, 16, 30, 79, 51, 97, 89, 52, 30, 37, 54, 20, 50,  7, 62, 29, 58,\n",
      "        24, 65, 33, 42, 23, 13, 82, 22, 88,  0, 93,  3,  7, 29])\n",
      "1319 torch.Size([32, 3, 32, 32]) tensor([70, 83,  5, 37, 33, 66, 70, 82, 88, 90,  9, 90, 44, 83, 22, 84, 23, 19,\n",
      "        38, 84,  2, 16, 87, 49, 52, 80, 66,  3, 91, 84, 23, 94])\n",
      "1320 torch.Size([32, 3, 32, 32]) tensor([77, 82, 29, 60, 62, 42, 59, 95, 96, 82, 87, 81, 59, 20, 95, 25, 16, 49,\n",
      "         4, 77, 25,  2, 83, 34, 57, 74, 42, 39,  5, 93, 14, 53])\n",
      "1321 torch.Size([32, 3, 32, 32]) tensor([ 3, 29, 16, 33, 32, 15, 73, 22, 73, 68, 39, 40, 49, 61, 63, 75, 84, 41,\n",
      "        36, 77, 56, 69, 32,  8, 21, 34, 71, 82, 47, 99, 24, 46])\n",
      "1322 torch.Size([32, 3, 32, 32]) tensor([98, 53, 84,  8, 92, 79, 24,  7,  8,  9, 67, 63, 81, 87, 79,  9, 46, 26,\n",
      "        65,  9, 33,  7, 82, 98,  3, 96, 84, 84, 60, 63, 19, 55])\n",
      "1323 torch.Size([32, 3, 32, 32]) tensor([49, 99, 99, 85, 55,  1, 48,  7, 56, 83, 31,  5, 36, 46, 20, 85, 52, 22,\n",
      "        45, 36, 67,  2, 62, 10, 99, 18, 95, 62, 25,  5, 70, 10])\n",
      "1324 torch.Size([32, 3, 32, 32]) tensor([29, 25, 52, 81, 34, 50,  5, 97, 71, 50, 13, 69, 47,  9, 52, 27, 56, 99,\n",
      "        69, 16, 63, 23, 16, 51, 15, 39, 52, 69, 79, 75, 60,  2])\n",
      "1325 torch.Size([32, 3, 32, 32]) tensor([97, 99, 41, 22, 71, 55, 61, 48, 48, 66, 66, 97, 50, 33, 73, 91, 59, 38,\n",
      "        16, 86, 90, 27, 34, 98, 73, 78, 90, 82, 62, 26, 85,  0])\n",
      "1326 torch.Size([32, 3, 32, 32]) tensor([25, 89, 21, 56, 59, 88,  6, 46,  7, 19, 81, 46, 22, 82, 14, 54, 53, 36,\n",
      "         2, 83,  8,  8, 58, 73, 61, 73, 95, 28, 70, 15, 29, 19])\n",
      "1327 torch.Size([32, 3, 32, 32]) tensor([52, 50, 20, 29, 98, 87, 52, 53, 18, 97, 61, 30, 56, 72, 93, 55, 64, 17,\n",
      "         0, 71, 96, 99, 83, 69, 34, 25, 19, 92, 17, 36, 37, 85])\n",
      "1328 torch.Size([32, 3, 32, 32]) tensor([26, 44, 34, 94, 38, 28, 20, 85, 11, 96, 79, 48, 19, 20,  3, 95, 42, 85,\n",
      "         7, 21, 67, 16, 70, 60, 66, 72, 29, 39, 64, 91, 47, 74])\n",
      "1329 torch.Size([32, 3, 32, 32]) tensor([63, 55, 72,  8, 48, 17, 18, 37, 67, 60, 22,  7, 96, 86, 72, 87, 21, 13,\n",
      "        53, 36, 68, 23, 63, 80, 85, 51, 14, 88,  0, 13, 78, 92])\n",
      "1330 torch.Size([32, 3, 32, 32]) tensor([85, 43, 48, 24, 41, 76, 32, 31, 41, 30, 79, 19, 73,  4, 85,  2, 42, 20,\n",
      "        75,  1, 62, 25, 43, 19, 39, 93, 81, 37, 28, 81, 20, 94])\n",
      "1331 torch.Size([32, 3, 32, 32]) tensor([42,  7, 10, 78, 59, 12, 62,  9, 22, 11, 23,  9,  6,  7, 24, 60, 68,  7,\n",
      "        77, 72, 47, 40, 35, 86, 92, 33, 12, 76, 54, 44, 34, 70])\n",
      "1332 torch.Size([32, 3, 32, 32]) tensor([43, 33, 87, 47, 93, 89,  9, 73,  8, 30,  0, 50, 98, 31, 95, 35, 37, 17,\n",
      "        39,  0, 26, 13, 17, 11, 81,  9, 44, 19, 23, 78, 84, 27])\n",
      "1333 torch.Size([32, 3, 32, 32]) tensor([ 6, 48, 33, 87, 95, 47, 22, 73, 82, 12, 81, 75, 44, 40, 55, 76, 64, 75,\n",
      "        26, 89, 54, 39, 81, 60, 95, 53, 47, 95, 62, 38,  6, 53])\n",
      "1334 torch.Size([32, 3, 32, 32]) tensor([12, 66, 17, 57, 48,  4, 47, 45, 82,  1, 81, 67, 46, 23, 71,  2, 34, 91,\n",
      "        64, 94, 16, 36, 15, 81, 90, 77, 50, 27, 85, 54, 91, 92])\n",
      "1335 torch.Size([32, 3, 32, 32]) tensor([20, 89, 97, 18, 23,  7, 61, 56, 26, 78,  4, 56, 21, 33, 35, 80,  0, 56,\n",
      "        95, 49, 18, 10, 81, 18, 19, 50, 49, 45, 11, 55, 53, 33])\n",
      "1336 torch.Size([32, 3, 32, 32]) tensor([87, 40, 99, 28, 46, 60, 50, 65, 42, 39, 21, 33, 93, 82, 86, 93, 23, 22,\n",
      "        38, 82, 72, 81, 65, 53,  9, 34, 95, 23, 91, 72, 97, 59])\n",
      "1337 torch.Size([32, 3, 32, 32]) tensor([ 5, 51, 37, 34, 98, 41,  2, 69, 93, 37, 84, 47, 84, 88, 64, 66, 54, 70,\n",
      "         9, 42, 75, 83, 19, 55, 37, 76, 27,  9, 44, 41, 83,  2])\n",
      "1338 torch.Size([32, 3, 32, 32]) tensor([19, 61, 98, 63, 17, 37, 17, 81, 76, 71, 47,  7, 59, 85, 48, 89, 67, 70,\n",
      "         6, 56,  6, 82,  7, 85, 70, 92, 21, 41, 82, 85, 94, 45])\n",
      "1339 torch.Size([32, 3, 32, 32]) tensor([ 0, 19, 60,  3, 21, 91, 68, 60, 11, 58, 17, 40, 31, 64, 90, 46, 13, 57,\n",
      "        45, 46, 71, 11, 99, 30, 30, 55, 54, 94, 45, 79, 27, 47])\n",
      "1340 torch.Size([32, 3, 32, 32]) tensor([11, 80, 49, 57,  2,  1, 89, 15, 80, 78, 89, 55, 85, 24, 25, 58, 55, 16,\n",
      "        33, 55, 18, 58, 91, 54, 62, 57, 41, 30, 76, 38, 13, 51])\n",
      "1341 torch.Size([32, 3, 32, 32]) tensor([ 8, 62, 24, 82, 73, 33, 19,  8,  5, 10, 17, 79, 41, 76, 25, 80,  0, 99,\n",
      "        93, 28, 18, 15, 48, 13, 71, 10,  6,  6, 10, 42, 46, 27])\n",
      "1342 torch.Size([32, 3, 32, 32]) tensor([53,  6, 54, 86, 80, 12, 57, 16, 58, 94, 22, 27, 85, 11, 47, 24, 82, 51,\n",
      "        60, 37, 30, 33, 21,  4, 72, 62, 79, 28, 95, 92, 85, 48])\n",
      "1343 torch.Size([32, 3, 32, 32]) tensor([93, 86, 89, 71, 14, 68, 11, 90, 17, 82, 75, 43, 24, 49, 46, 29, 15, 43,\n",
      "        11, 29,  3, 18, 10, 38, 31, 51, 48,  1, 36, 24, 51, 10])\n",
      "1344 torch.Size([32, 3, 32, 32]) tensor([15, 51, 69, 66,  4, 11, 88, 72,  2, 75, 91, 21, 44, 72, 13, 43, 58, 90,\n",
      "        82, 93, 44, 48,  6, 91, 94, 87, 93, 94, 35, 20, 86, 85])\n",
      "1345 torch.Size([32, 3, 32, 32]) tensor([94, 97, 19,  5, 25, 25, 27, 60, 97, 93, 58,  3, 47, 28, 14,  0, 87,  7,\n",
      "        47, 18, 79, 25, 11, 97, 58, 64, 10, 12, 47, 26,  5,  5])\n",
      "1346 torch.Size([32, 3, 32, 32]) tensor([83, 96, 21, 39, 83, 93, 28, 67, 35,  7, 56, 35, 12, 17, 42, 91, 42, 30,\n",
      "        98, 61, 77, 35,  2, 81, 84, 37, 95, 41, 18, 89, 32, 44])\n",
      "1347 torch.Size([32, 3, 32, 32]) tensor([21, 66, 62,  2, 72, 77, 43, 42, 10, 37, 40, 57, 22, 66, 16,  8, 52, 33,\n",
      "        21,  5, 99, 37, 93, 18, 36, 83, 60, 93, 66, 46, 79, 21])\n",
      "1348 torch.Size([32, 3, 32, 32]) tensor([12, 41, 92, 64, 84, 54, 48, 45, 72, 95, 88, 17, 31, 13, 68, 36, 80, 96,\n",
      "        25, 94, 85, 33, 41, 73, 82, 61, 35, 59, 31, 96, 81, 59])\n",
      "1349 torch.Size([32, 3, 32, 32]) tensor([20, 65, 21, 47, 71, 12, 76,  5, 68, 45, 57,  6, 21, 94, 39,  7, 32, 89,\n",
      "        83, 10, 68, 80, 67, 41, 70, 21, 54, 79, 34, 33, 62, 72])\n",
      "1350 torch.Size([32, 3, 32, 32]) tensor([15, 31, 13, 91, 97, 73, 48, 15, 34, 27, 71, 40, 13, 75, 16, 64, 45, 39,\n",
      "        23, 73, 39, 21, 31, 70, 40, 89, 54, 65, 34, 21,  5, 53])\n",
      "1351 torch.Size([32, 3, 32, 32]) tensor([51, 37, 94, 40, 34, 91, 40, 11, 26, 75, 16, 95, 52, 58, 84, 64, 77, 81,\n",
      "        56, 87, 43, 68, 53, 59, 21, 42, 27, 83, 26, 48, 61, 91])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1352 torch.Size([32, 3, 32, 32]) tensor([ 7, 66, 47, 37, 30, 80, 51, 35, 65, 83, 71, 80, 53, 47, 98, 67,  7, 10,\n",
      "        78, 58, 35, 71, 45, 20,  8, 35, 54, 19, 88, 59, 31, 51])\n",
      "1353 torch.Size([32, 3, 32, 32]) tensor([96, 85, 67, 37, 98, 81,  4, 58, 54, 98, 88, 66, 33, 94, 45, 99, 35, 95,\n",
      "        74, 17, 42, 39, 22, 95,  2, 37, 95, 20, 97, 56, 24,  9])\n",
      "1354 torch.Size([32, 3, 32, 32]) tensor([16, 97, 55, 18, 98, 23,  8, 88, 62, 40, 60, 37, 63, 44, 89, 11, 53, 98,\n",
      "        22, 39, 58, 65, 29, 55, 72, 92,  8, 72, 68, 70, 60, 50])\n",
      "1355 torch.Size([32, 3, 32, 32]) tensor([73, 90, 11, 14, 32, 21, 22, 39, 85,  7, 37, 98, 46, 27, 16, 59, 50, 58,\n",
      "        70, 77, 68, 99, 52, 87, 61, 26,  0, 24, 56, 13, 64, 64])\n",
      "1356 torch.Size([32, 3, 32, 32]) tensor([97,  0, 60, 23, 32, 25,  4, 71,  2, 85, 17, 12, 94, 61, 38, 95, 41, 37,\n",
      "        82, 95, 58, 36, 42,  8, 63, 30, 66, 24, 66, 58, 87,  0])\n",
      "1357 torch.Size([32, 3, 32, 32]) tensor([73, 66, 44, 12, 12, 32, 97,  9, 11, 34, 97, 53, 35,  4, 17, 24, 83, 11,\n",
      "        69, 22, 85, 57, 30, 52, 99, 86, 87, 55,  7, 48, 43, 42])\n",
      "1358 torch.Size([32, 3, 32, 32]) tensor([63, 72, 59, 46, 88, 19, 69, 99, 69, 80, 85, 94,  5, 80, 12, 34, 60, 53,\n",
      "        96, 72, 67, 11, 80, 59, 86, 10, 39, 56, 16, 59, 20, 93])\n",
      "1359 torch.Size([32, 3, 32, 32]) tensor([22, 95, 67, 44, 32, 88,  7, 64,  9, 85, 65, 27, 66, 36, 40, 24, 29, 94,\n",
      "        18, 15, 80, 74, 75, 59, 57, 14, 35, 58, 59, 68, 62, 31])\n",
      "1360 torch.Size([32, 3, 32, 32]) tensor([73, 63, 15, 10, 80,  6, 71, 35, 80, 40, 73, 84, 99, 41,  5, 49, 41, 88,\n",
      "         9, 55,  4, 56, 21, 67, 48, 71, 70, 40, 45,  3, 41,  4])\n",
      "1361 torch.Size([32, 3, 32, 32]) tensor([79, 72, 75, 80, 96, 90, 93,  7, 53,  2, 57, 16, 75, 14, 52, 23, 52, 37,\n",
      "        36, 16, 60, 26, 63, 28, 35, 21, 43, 35, 93, 60, 27,  9])\n",
      "1362 torch.Size([32, 3, 32, 32]) tensor([10, 21, 65, 57, 88,  5,  2, 59, 38, 35, 91, 20, 86, 13, 27, 39, 58, 91,\n",
      "        26, 28, 74, 47, 13, 18, 99, 13, 74, 35, 66,  7, 28, 39])\n",
      "1363 torch.Size([32, 3, 32, 32]) tensor([17, 84, 40, 48, 81, 39, 57,  7, 22, 48, 20, 31, 20, 11, 70, 31, 62, 67,\n",
      "        90,  0, 83, 81, 81, 24, 18, 11, 45, 43, 49, 99, 80, 88])\n",
      "1364 torch.Size([32, 3, 32, 32]) tensor([ 6, 59, 23, 74, 70, 34, 64,  5, 23, 67, 12, 54, 86, 84, 19, 73, 35, 51,\n",
      "         0, 75,  7, 16, 99, 19, 21, 26, 58, 58, 17,  3, 91, 33])\n",
      "1365 torch.Size([32, 3, 32, 32]) tensor([71, 74, 78, 13, 24,  8, 71, 14, 40, 34, 57,  7, 73,  8, 42, 32, 68, 52,\n",
      "        10, 42, 32, 45, 72,  6, 77, 83,  1,  1, 24,  5, 87, 70])\n",
      "1366 torch.Size([32, 3, 32, 32]) tensor([23, 87, 57, 40,  2, 71, 81,  5, 41, 19, 49,  1, 65,  2, 36, 30, 18, 19,\n",
      "        74, 97, 40, 43, 67, 28, 69, 46, 98, 36, 60, 10, 55, 64])\n",
      "1367 torch.Size([32, 3, 32, 32]) tensor([48, 97, 77,  8, 84, 27, 12, 28, 84, 18, 43, 22, 59,  3, 56, 73, 36,  6,\n",
      "        33, 60, 80, 75, 42, 10, 71, 51, 71, 92, 37, 72, 68, 97])\n",
      "1368 torch.Size([32, 3, 32, 32]) tensor([69,  1, 78, 47, 44, 45, 42, 84, 31, 58, 77, 53, 71, 51, 53, 23, 64, 20,\n",
      "        86, 29, 71, 87, 48, 94, 51, 54, 60, 25, 70, 69, 90, 25])\n",
      "1369 torch.Size([32, 3, 32, 32]) tensor([57, 83, 63, 76, 53, 15, 62,  3, 89, 86, 54, 97, 87, 84,  6, 67, 89, 47,\n",
      "        56, 26, 56, 14, 40, 30, 68, 72, 72, 21, 33, 75, 73, 50])\n",
      "1370 torch.Size([32, 3, 32, 32]) tensor([93, 96, 98,  4, 60, 77, 27, 30, 22, 97, 49, 73, 14, 34, 71,  3, 92, 37,\n",
      "        95, 26, 14, 40, 95, 21, 36, 20,  9, 59, 57, 72, 71, 77])\n",
      "1371 torch.Size([32, 3, 32, 32]) tensor([37, 30, 39, 38, 50, 80, 63, 56, 19, 25, 57, 25, 98, 90, 12, 82, 36, 51,\n",
      "        28, 32,  7, 44, 68, 47, 25, 86, 23, 46, 19, 80,  0, 66])\n",
      "1372 torch.Size([32, 3, 32, 32]) tensor([27, 42, 74, 76, 53, 23, 97, 71,  0, 41, 51, 71, 69, 81,  0, 78, 30, 59,\n",
      "        33, 85,  6, 67, 80, 93, 59, 96, 60,  2, 43, 86, 34,  9])\n",
      "1373 torch.Size([32, 3, 32, 32]) tensor([89, 21, 27, 91, 93, 97, 32, 91, 48, 19, 19, 75, 59, 54, 18, 43, 29, 79,\n",
      "        55, 33, 49, 45,  0, 88, 65, 91, 12, 47,  6, 54, 17, 67])\n",
      "1374 torch.Size([32, 3, 32, 32]) tensor([74, 30, 30, 88, 94, 69, 89, 13, 58,  3,  4, 31,  6, 93, 73, 35,  4, 37,\n",
      "        85, 75, 43, 44, 65, 87,  3, 47, 25, 45, 54, 79, 29, 28])\n",
      "1375 torch.Size([32, 3, 32, 32]) tensor([17, 15,  1, 45, 84, 60, 56, 11, 51, 57, 97, 75, 83, 68, 29, 55, 43,  7,\n",
      "        54, 94, 27, 42, 50, 45, 81, 63, 85, 70, 53, 14, 89, 43])\n",
      "1376 torch.Size([32, 3, 32, 32]) tensor([44, 99, 47, 91,  3, 14,  7, 14, 44, 30, 66,  3, 70, 80, 74, 68, 30, 63,\n",
      "        46,  1, 34, 93, 92,  0, 64, 84,  9, 17, 77, 43, 78, 39])\n",
      "1377 torch.Size([32, 3, 32, 32]) tensor([36, 83, 25, 80, 13, 32, 71, 59, 99,  7, 41, 56, 27,  4, 25, 56, 61, 55,\n",
      "        90, 19, 12, 53, 11, 90, 43, 83, 41, 77,  3, 45, 45, 70])\n",
      "1378 torch.Size([32, 3, 32, 32]) tensor([52, 33, 83, 79, 41, 59, 62, 50, 32, 86, 21, 76,  4, 69, 77,  8, 38, 60,\n",
      "        62, 48,  8, 94, 95,  0, 75, 25, 40, 26, 63, 78, 36, 66])\n",
      "1379 torch.Size([32, 3, 32, 32]) tensor([92, 75, 73, 19, 31,  0, 38, 43, 45, 44, 22,  3, 85, 75, 23, 45, 36, 16,\n",
      "        79, 59, 26, 72, 41,  9, 32, 24,  8, 82, 79, 95, 98,  8])\n",
      "1380 torch.Size([32, 3, 32, 32]) tensor([87, 31, 96, 10, 10, 74,  3, 36, 96, 58, 49, 13,  0, 11, 64, 61, 38, 15,\n",
      "        85,  6, 62, 58, 82, 56, 14, 76, 63, 82, 21, 37, 76, 29])\n",
      "1381 torch.Size([32, 3, 32, 32]) tensor([41, 99, 50, 71, 60, 19, 35, 28, 57, 66, 58, 61, 96, 75, 72, 21,  0, 81,\n",
      "         0, 53, 14, 88, 60, 29, 37, 14, 51, 84, 36, 31, 37, 87])\n",
      "1382 torch.Size([32, 3, 32, 32]) tensor([35, 11, 31, 69, 17, 54, 10, 32,  2, 29, 86, 70,  4, 71, 39, 33, 97, 23,\n",
      "        36,  6, 46, 79, 10, 16, 84, 57, 45, 57, 88, 73,  7, 28])\n",
      "1383 torch.Size([32, 3, 32, 32]) tensor([ 5, 65, 87,  6, 96, 97, 97, 82, 30, 48, 56, 64, 64, 30, 30, 13, 57, 55,\n",
      "        52,  0, 47,  8, 67, 11, 17, 48, 76, 17, 99,  2, 29, 24])\n",
      "1384 torch.Size([32, 3, 32, 32]) tensor([94, 96, 26, 18, 18,  9, 74, 47, 96, 20, 27,  0, 52, 19, 33, 68, 46, 42,\n",
      "        80, 77, 86, 78,  5, 65, 93, 46, 44, 51, 90, 97, 11, 31])\n",
      "1385 torch.Size([32, 3, 32, 32]) tensor([27, 67, 19,  1, 51,  6, 17, 25,  0, 89, 11, 53, 84, 66, 96, 84, 92, 30,\n",
      "        39, 47,  8, 51, 78, 12,  0, 72, 95, 36, 14, 93, 63, 32])\n",
      "1386 torch.Size([32, 3, 32, 32]) tensor([50, 74, 40, 28, 68, 47, 27, 30, 28, 84, 77, 38, 13, 12, 72, 20,  0, 67,\n",
      "        76, 73, 98, 40, 49, 18, 10, 10, 93, 98, 68,  4, 29, 20])\n",
      "1387 torch.Size([32, 3, 32, 32]) tensor([74,  0, 17, 49, 77, 94, 35, 97, 67, 84, 22, 99, 52, 28, 76, 10, 59, 67,\n",
      "        13, 10, 67, 49, 22, 18,  4, 16, 55, 49, 90, 89, 17, 92])\n",
      "1388 torch.Size([32, 3, 32, 32]) tensor([23, 15, 35, 85, 96, 22, 83, 68, 50, 69, 77, 17, 78, 62, 10, 78, 39, 21,\n",
      "        93, 81, 54, 43, 85, 92,  4, 99, 48, 25, 11, 20, 57, 36])\n",
      "1389 torch.Size([32, 3, 32, 32]) tensor([19, 22, 84, 74, 58, 92, 46, 44, 75, 40, 53, 86, 35, 85, 43, 46, 34,  2,\n",
      "        44, 62, 42, 56, 18, 73, 58, 49, 71,  9, 50, 11, 73, 21])\n",
      "1390 torch.Size([32, 3, 32, 32]) tensor([65, 43, 79, 44, 26, 63, 68, 59, 36, 94, 52, 89, 81, 51, 51, 42, 79, 44,\n",
      "        22, 55, 74, 78, 51,  8,  7, 46, 64, 96, 91, 25, 45, 10])\n",
      "1391 torch.Size([32, 3, 32, 32]) tensor([29, 77, 50, 45, 40, 75, 50, 55, 59, 76, 47, 16, 75, 28, 74, 18, 54, 47,\n",
      "        53, 35,  0, 59, 75, 76, 54,  3, 47,  9, 47, 12, 99,  4])\n",
      "1392 torch.Size([32, 3, 32, 32]) tensor([46, 90, 36, 30, 85, 78, 40, 62, 28, 25, 88, 35, 27, 39, 36, 10, 48, 44,\n",
      "        99, 98, 63,  0, 19,  4, 31, 84, 17, 77, 87, 98, 58, 47])\n",
      "1393 torch.Size([32, 3, 32, 32]) tensor([96, 40, 12, 48, 31, 40, 93, 23, 59, 40, 47, 19, 22, 31, 48, 93, 62, 82,\n",
      "        25, 48, 96, 36, 27, 21, 11, 53, 32, 86, 69,  1, 76, 90])\n",
      "1394 torch.Size([32, 3, 32, 32]) tensor([12, 40, 93, 63, 82, 47, 65, 35, 11,  2, 54, 55, 12,  5, 45, 13, 76, 53,\n",
      "        48, 38, 89, 77, 30, 45, 70, 94, 90, 82, 65,  5, 66,  6])\n",
      "1395 torch.Size([32, 3, 32, 32]) tensor([57, 70, 72, 15, 82, 73, 30, 94, 59,  3, 43, 29, 55, 73,  3,  1, 61,  6,\n",
      "         4, 93, 36, 20, 85, 82, 55, 80, 35,  9, 86, 62,  3, 50])\n",
      "1396 torch.Size([32, 3, 32, 32]) tensor([82, 19, 96, 18, 76, 51, 20, 51, 22,  0, 27, 26, 83, 43, 50, 40,  0, 54,\n",
      "        95, 55, 87, 54, 24,  8, 34, 34, 23, 49, 33, 99, 94, 69])\n",
      "1397 torch.Size([32, 3, 32, 32]) tensor([49, 95, 89, 68, 82, 81, 57, 74, 88, 80, 62, 86, 18,  7, 88, 73, 94,  9,\n",
      "        32, 38, 22, 79, 31, 23, 33, 74, 45, 25, 17, 53, 93, 42])\n",
      "1398 torch.Size([32, 3, 32, 32]) tensor([72, 97, 32, 45, 90, 74, 42,  4, 57, 83, 51, 73, 55, 88, 31, 54, 81, 90,\n",
      "        45, 71, 30,  6, 69, 83, 67,  5, 83, 75, 11, 86, 69, 85])\n",
      "1399 torch.Size([32, 3, 32, 32]) tensor([94, 28, 37, 43, 27, 75, 86, 67,  8, 47, 49, 89, 70, 62,  0, 30, 65, 34,\n",
      "        98, 85, 69, 73, 85, 68,  9, 85, 12,  0, 45, 71, 84,  7])\n",
      "1400 torch.Size([32, 3, 32, 32]) tensor([13, 77, 98, 10, 16, 83, 42,  4, 22, 85, 53, 48, 35, 77, 79,  8, 13, 35,\n",
      "        91, 38, 66, 92, 13,  0, 65,  8, 45, 77, 21, 91, 67, 29])\n",
      "1401 torch.Size([32, 3, 32, 32]) tensor([92, 50, 48, 22, 35,  7, 93, 71, 43, 24, 80, 88, 43, 61, 32, 86, 28, 14,\n",
      "         1, 29, 54,  0, 33, 78,  8, 20, 11,  8, 11, 24,  0, 15])\n",
      "1402 torch.Size([32, 3, 32, 32]) tensor([45, 29, 71, 98, 39, 54, 54, 72, 89, 18, 55, 93,  6, 10, 45, 29, 51, 38,\n",
      "        94, 26, 78, 36, 16, 22, 78, 34, 40, 17,  8, 80, 94, 10])\n",
      "1403 torch.Size([32, 3, 32, 32]) tensor([98, 11, 39, 96, 11, 34, 20, 10, 47, 12, 70, 96, 79, 50, 70, 57,  6, 81,\n",
      "        60, 22, 58, 40, 33, 59, 62, 96, 81, 17, 78, 31, 95,  9])\n",
      "1404 torch.Size([32, 3, 32, 32]) tensor([70, 43, 21, 92, 78, 54, 93, 91, 37,  1, 19, 72, 16, 40, 46, 98, 29, 61,\n",
      "        19,  8, 63, 35, 13, 89, 44, 48, 89, 81, 24, 64, 91, 24])\n",
      "1405 torch.Size([32, 3, 32, 32]) tensor([68, 95, 43, 23, 39,  7, 12, 91, 76,  5, 62, 97, 99, 67, 32,  6, 83, 47,\n",
      "        91, 26, 23, 91,  5, 62, 88, 79, 79, 10, 56, 40, 23, 87])\n",
      "1406 torch.Size([32, 3, 32, 32]) tensor([31, 74, 76, 70, 58, 87,  6,  6, 95, 37, 26, 34, 54, 96, 23, 76, 17, 74,\n",
      "        27, 25, 48, 53, 46, 87, 68, 18, 59, 81, 87, 41, 41,  1])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1407 torch.Size([32, 3, 32, 32]) tensor([83, 26, 60,  3,  2, 68,  0, 43, 78, 92, 52, 72, 48, 53, 59, 96, 38, 97,\n",
      "        32, 58, 56, 42, 69, 39, 34, 74, 78, 11,  7, 98, 67, 44])\n",
      "1408 torch.Size([32, 3, 32, 32]) tensor([77, 85, 54, 74,  2, 69, 42,  5, 61,  3, 99, 27, 61, 11, 48, 97,  0, 56,\n",
      "        19, 65, 47, 93, 54, 27, 99, 73, 66,  3, 34, 18, 72, 62])\n",
      "1409 torch.Size([32, 3, 32, 32]) tensor([46, 28, 68, 86,  8, 74, 21, 25, 52, 55, 84, 36, 67, 61, 94, 77, 70, 73,\n",
      "        74, 31, 81, 21, 55, 28, 18, 78, 51, 66, 26, 24, 67, 66])\n",
      "1410 torch.Size([32, 3, 32, 32]) tensor([40, 61, 45, 77, 63, 43, 56, 21, 34, 79,  0, 56,  5, 32, 54, 84, 90, 45,\n",
      "        91, 26, 11, 34, 91,  0, 52, 33, 55, 85, 76, 89, 29, 73])\n",
      "1411 torch.Size([32, 3, 32, 32]) tensor([36, 30, 75, 66, 22, 43, 17, 81, 17, 82, 69,  3, 56,  0, 85, 56, 39, 41,\n",
      "        91, 58, 83, 18, 21, 21, 41, 52, 67, 63, 52, 62, 84, 90])\n",
      "1412 torch.Size([32, 3, 32, 32]) tensor([90, 57, 45, 99, 32, 35, 13, 84, 54, 11, 84, 72,  6, 76, 60, 43,  8, 98,\n",
      "        65, 38, 77, 21, 73, 36, 96, 20, 19, 56, 48, 42, 12, 68])\n",
      "1413 torch.Size([32, 3, 32, 32]) tensor([78, 89, 38, 84, 29, 48,  5, 27, 71, 61, 28, 58, 52, 65, 83, 30, 37, 62,\n",
      "        26, 49, 60,  3, 64, 27, 87, 41, 73, 86, 21,  9, 84, 40])\n",
      "1414 torch.Size([32, 3, 32, 32]) tensor([91, 68, 46, 58, 32, 82, 17, 66, 83, 47, 82, 34, 55, 45,  0, 19, 44, 26,\n",
      "        65, 41, 53, 57, 33, 28, 24, 35,  5, 84, 14, 32, 28, 58])\n",
      "1415 torch.Size([32, 3, 32, 32]) tensor([89, 41, 28, 56, 36,  1, 58, 81, 30, 46, 45, 70,  6, 32, 34, 52, 24, 68,\n",
      "        54, 30, 41, 40, 57,  1, 58, 95, 29, 95, 58, 89, 18, 97])\n",
      "1416 torch.Size([32, 3, 32, 32]) tensor([18, 34, 60,  7, 73, 27, 19, 58,  9, 18, 88, 49, 28, 36, 46, 23, 78,  3,\n",
      "        37, 13, 45, 98, 18, 99, 80,  3, 37, 55, 57, 28, 15, 80])\n",
      "1417 torch.Size([32, 3, 32, 32]) tensor([25, 22, 37, 66,  8,  1, 53, 78, 40, 57, 31, 60, 63, 69, 96, 11, 35, 74,\n",
      "        65, 89, 14, 10, 42, 97, 62, 14, 81, 84, 50, 52, 29,  0])\n",
      "1418 torch.Size([32, 3, 32, 32]) tensor([95, 79,  6, 76, 54, 67, 53, 46, 69, 52, 93, 85, 36, 93, 72, 34, 84, 45,\n",
      "        64, 61, 88, 93, 14, 21, 64, 40, 10, 25, 91, 12,  1, 77])\n",
      "1419 torch.Size([32, 3, 32, 32]) tensor([78, 54,  2, 19, 62, 33, 46, 39, 39, 49, 79, 88, 80, 26,  8, 65, 79, 61,\n",
      "         8,  4,  8, 64,  6, 63, 73, 95, 18,  4, 82,  3, 83, 72])\n",
      "1420 torch.Size([32, 3, 32, 32]) tensor([45, 15, 32, 75, 21, 95, 62, 42, 75, 30, 16, 99, 27, 34, 68, 92, 26, 93,\n",
      "         1,  4, 32, 44, 96, 55, 52, 29, 19, 87, 61, 83, 86, 86])\n",
      "1421 torch.Size([32, 3, 32, 32]) tensor([71,  3, 68, 79, 44, 15, 98, 98, 77, 26, 23, 77, 55, 59, 45, 85, 67, 23,\n",
      "        80, 60, 20, 74, 42, 20, 20, 60, 64, 59, 65, 59, 41, 21])\n",
      "1422 torch.Size([32, 3, 32, 32]) tensor([77, 85,  9,  9, 12,  4,  5, 78, 58, 10, 43, 92, 88, 14, 43, 73, 72, 29,\n",
      "        99, 94, 73, 86, 89, 17, 17, 13, 44, 91, 92, 59, 98, 52])\n",
      "1423 torch.Size([32, 3, 32, 32]) tensor([40, 36, 73, 98, 20,  2, 13, 34, 45, 42, 50,  8, 92, 22, 72, 84, 29, 56,\n",
      "        94, 36, 20, 74, 80, 47, 18, 61, 22, 60, 82, 98, 81, 12])\n",
      "1424 torch.Size([32, 3, 32, 32]) tensor([18, 63, 13, 58, 33,  0,  4, 19, 32,  6, 44, 26, 24, 94, 38, 30, 45, 38,\n",
      "         5, 42,  7, 99, 70, 45, 69, 31, 53, 85, 56, 80, 20, 45])\n",
      "1425 torch.Size([32, 3, 32, 32]) tensor([99, 77, 77, 56, 69, 73, 69, 93, 91,  4, 30, 68, 67, 92, 36, 97, 61, 13,\n",
      "        97, 23, 51, 33, 64, 50, 33, 25, 86, 90, 44, 90, 65, 72])\n",
      "1426 torch.Size([32, 3, 32, 32]) tensor([87, 14, 59, 83, 46, 20, 73, 28, 44, 93, 70, 17, 86, 22,  5,  3, 23, 18,\n",
      "        23, 73, 30, 28, 34, 33,  9, 50, 40, 11, 49, 18,  0, 88])\n",
      "1427 torch.Size([32, 3, 32, 32]) tensor([69, 54, 16, 44, 29, 77, 39, 10, 17, 92, 69, 36, 34, 69, 79, 12, 72,  8,\n",
      "        65, 15, 60, 75,  9,  3, 59, 29, 49, 32, 54, 63, 69, 42])\n",
      "1428 torch.Size([32, 3, 32, 32]) tensor([57, 57, 32, 30, 43,  5, 60, 74, 65, 63, 91,  8, 89, 36, 13, 63, 35, 87,\n",
      "         9, 35, 67, 47, 38, 42, 46,  5, 11, 72, 83, 78, 32, 48])\n",
      "1429 torch.Size([32, 3, 32, 32]) tensor([60, 24, 71, 56, 23, 60, 18, 31, 31, 66,  8, 66, 30, 12,  0,  8, 98, 10,\n",
      "         4, 17,  6, 69, 55, 57, 19, 38, 24,  2, 78, 92, 62, 58])\n",
      "1430 torch.Size([32, 3, 32, 32]) tensor([28, 91, 40, 95, 99, 46, 23, 29, 59, 85, 43, 49, 81, 70,  4, 18, 88, 19,\n",
      "        99, 64, 57, 48, 76, 57, 14, 94, 68, 30, 77, 65, 30, 54])\n",
      "1431 torch.Size([32, 3, 32, 32]) tensor([48, 33, 94, 69, 17, 25,  6,  1, 51, 42, 63, 34, 16, 68, 93, 18, 31, 41,\n",
      "        29, 84, 44, 63, 51, 40, 24, 61, 17, 14, 27, 41, 37, 94])\n",
      "1432 torch.Size([32, 3, 32, 32]) tensor([61, 58, 56, 41, 77, 48, 95, 11, 78,  9, 50, 44, 72, 74,  6, 72, 59, 82,\n",
      "        50, 51, 88, 82, 22, 89, 91, 14, 10, 62, 15, 19, 65, 80])\n",
      "1433 torch.Size([32, 3, 32, 32]) tensor([91, 64, 47, 49, 69, 39,  4, 66, 65, 92, 43, 63, 99, 17, 88,  4, 56, 30,\n",
      "        77, 90, 25, 90, 51, 65, 55, 39, 59, 44, 19, 71, 96, 90])\n",
      "1434 torch.Size([32, 3, 32, 32]) tensor([85, 25, 42,  1, 57,  5, 97, 71, 67, 21, 68, 49, 43, 40, 53, 68, 11,  5,\n",
      "        56, 28,  9, 99, 38, 58, 19, 10, 71,  3, 65, 10, 74, 48])\n",
      "1435 torch.Size([32, 3, 32, 32]) tensor([71, 49, 17, 49, 65,  9, 14, 78, 53, 77, 99, 48,  3, 78, 73, 36, 46, 94,\n",
      "        40,  8, 82, 99, 36, 83, 71, 42, 58,  1,  7, 43, 40, 78])\n",
      "1436 torch.Size([32, 3, 32, 32]) tensor([63, 25, 44, 35, 52,  2,  6, 12, 58, 66, 33, 48, 49, 14, 49, 88, 72, 96,\n",
      "        29, 65, 18, 24,  7, 65,  6, 38, 59, 16, 78, 50, 78, 16])\n",
      "1437 torch.Size([32, 3, 32, 32]) tensor([47, 41, 66, 46, 51, 83, 46, 10, 79, 83,  3, 42,  8, 58, 63, 87, 92,  7,\n",
      "        90, 97, 94, 15, 36, 44, 37,  2, 37, 37, 57, 23, 89, 47])\n",
      "1438 torch.Size([32, 3, 32, 32]) tensor([20, 72, 87, 38, 62, 48,  1, 19, 67, 75, 60, 83, 11, 86, 19, 47, 18, 51,\n",
      "        19, 41,  5, 21,  5, 96, 31,  5, 60, 57, 17, 53, 59, 51])\n",
      "1439 torch.Size([32, 3, 32, 32]) tensor([56, 50, 37, 73, 65, 82, 83, 28, 97, 40, 66, 70, 21, 31, 46, 44, 17, 85,\n",
      "        60, 66, 17, 18, 60, 47, 43, 17, 51, 54, 44, 28, 66, 61])\n",
      "1440 torch.Size([32, 3, 32, 32]) tensor([ 0, 91, 29, 79, 52, 47, 26, 75, 94, 31, 94, 62, 85, 94, 78, 72,  4, 54,\n",
      "        41, 91, 80, 40, 70, 57, 81, 29, 88, 81, 79, 66, 52, 56])\n",
      "1441 torch.Size([32, 3, 32, 32]) tensor([98, 75, 86, 13, 56, 66, 77, 20, 85, 22, 53, 61, 13, 17, 85, 70, 44, 46,\n",
      "        73, 73, 94, 24, 22, 48, 82, 10, 88, 29, 74,  9, 28, 37])\n",
      "1442 torch.Size([32, 3, 32, 32]) tensor([89, 62, 71,  3, 54, 62, 54, 86, 63, 34, 33, 52, 69, 13, 17, 98, 68, 28,\n",
      "        45, 20,  7, 84, 14, 34, 71, 89, 82, 25, 68,  4, 55,  1])\n",
      "1443 torch.Size([32, 3, 32, 32]) tensor([30,  4,  6, 72, 12,  9, 79, 13,  8, 35, 16, 26, 99, 96, 26, 49, 32, 52,\n",
      "        24, 84,  7, 25, 29, 46, 54, 25, 32, 76, 59, 81, 89, 26])\n",
      "1444 torch.Size([32, 3, 32, 32]) tensor([ 0, 84,  2,  3, 88, 39, 10, 70,  3, 55, 42, 48, 95,  8, 77, 16, 75, 29,\n",
      "        95, 19, 98, 51, 95, 49, 67, 50,  9, 91, 52,  7, 58, 92])\n",
      "1445 torch.Size([32, 3, 32, 32]) tensor([74, 76, 87, 73, 69, 59, 69, 24, 16, 86, 96, 15, 25, 89, 12, 70, 96, 59,\n",
      "         9, 43, 74, 90, 57, 25, 39, 66, 14, 77, 93, 85, 89, 75])\n",
      "1446 torch.Size([32, 3, 32, 32]) tensor([63, 49, 69, 70, 11, 85, 25, 33, 43, 20, 24, 54, 90, 78, 78,  1, 36, 84,\n",
      "         5, 80, 78, 71, 92, 74, 32, 90, 82, 37, 98, 40, 58, 82])\n",
      "1447 torch.Size([32, 3, 32, 32]) tensor([41, 17, 85, 33, 45, 11, 58, 96, 24, 44, 25, 91, 38, 18, 46, 60, 38, 90,\n",
      "        97, 71, 94, 22, 60, 26, 30, 50, 49, 71, 54, 22, 92, 73])\n",
      "1448 torch.Size([32, 3, 32, 32]) tensor([35, 69, 75,  4, 55, 37, 30, 77, 65, 12, 83, 35, 69,  5, 88, 28, 74, 99,\n",
      "        36, 11, 92, 32, 73, 98, 87, 22, 73, 96, 36, 24, 92, 52])\n",
      "1449 torch.Size([32, 3, 32, 32]) tensor([23, 63, 30, 97, 64, 62, 58, 72, 99, 16, 53, 61, 32, 99, 35, 92,  0, 80,\n",
      "        35, 66, 32, 66, 84, 89, 51, 32, 61, 81,  3, 21,  5, 79])\n",
      "1450 torch.Size([32, 3, 32, 32]) tensor([89, 90, 83, 51, 23, 41, 87, 74, 46, 23, 17,  7, 92, 85, 38,  3, 26, 45,\n",
      "        14, 52, 67, 29, 98, 33, 63, 76,  5, 32, 23,  1, 19, 32])\n",
      "1451 torch.Size([32, 3, 32, 32]) tensor([13, 98, 46, 30,  5, 29,  7, 23, 18, 18, 94, 51, 78, 97, 83, 45, 58, 31,\n",
      "        75, 48,  5, 92, 21, 84, 46, 33, 13, 93, 78, 81, 22, 13])\n",
      "1452 torch.Size([32, 3, 32, 32]) tensor([35, 32, 80, 79, 39, 80, 82, 80, 77, 49, 97, 58, 57, 12, 23, 66, 23, 11,\n",
      "        78, 91, 54,  0,  9, 56, 79, 35, 44, 69, 69, 88,  5, 50])\n",
      "1453 torch.Size([32, 3, 32, 32]) tensor([41, 86, 44, 37, 77, 71, 89, 22, 49, 21, 26, 87, 81,  6,  2, 18, 40, 66,\n",
      "        56, 45, 32, 46, 32, 53, 67, 21,  1, 67, 69, 46,  1, 17])\n",
      "1454 torch.Size([32, 3, 32, 32]) tensor([64, 60, 56, 55, 30, 85, 24, 76, 77, 85, 94, 50, 71, 33, 34, 77, 68, 88,\n",
      "         7,  6, 98, 73,  7, 96, 78,  8, 95, 80, 20, 58, 47, 50])\n",
      "1455 torch.Size([32, 3, 32, 32]) tensor([65, 67,  5, 69,  7, 21, 59, 58, 37, 77, 36, 33,  2, 31, 95, 48, 58, 58,\n",
      "         0, 85,  9, 27, 23, 54, 55, 18, 54, 76, 74, 29, 61, 42])\n",
      "1456 torch.Size([32, 3, 32, 32]) tensor([96, 37, 24, 98, 36, 39, 35, 68, 36, 27, 49, 25, 46, 68, 30, 70, 52, 11,\n",
      "        13, 44, 28, 40, 74, 49, 13, 86, 17, 33, 17, 78, 52, 88])\n",
      "1457 torch.Size([32, 3, 32, 32]) tensor([35, 64, 20, 80, 34, 33,  7, 64,  2, 66, 47, 69, 25, 87, 89, 18, 88, 83,\n",
      "        94, 72, 90, 52, 57, 67, 71, 95,  4, 66, 91,  7, 39, 67])\n",
      "1458 torch.Size([32, 3, 32, 32]) tensor([95, 36, 48, 94, 73, 50, 91, 48, 88, 93, 25, 39, 14, 67, 12, 36, 91, 32,\n",
      "        33,  1, 21, 83, 14, 78, 46, 43, 58, 78, 99, 85, 25, 37])\n",
      "1459 torch.Size([32, 3, 32, 32]) tensor([32, 17, 20, 31, 71, 64, 34, 21, 91, 83, 67, 94, 86, 22, 71, 98, 23, 88,\n",
      "        52, 74, 88, 88, 64, 46, 31, 15, 65, 15, 81, 77, 76, 55])\n",
      "1460 torch.Size([32, 3, 32, 32]) tensor([43, 39, 45, 58, 88, 62, 19, 56,  2, 76,  3, 99, 70, 42, 57, 82,  3,  2,\n",
      "        23, 91, 58, 44, 38, 42, 74, 97, 25, 13, 76, 84, 83, 73])\n",
      "1461 torch.Size([32, 3, 32, 32]) tensor([67, 13, 89, 91,  8, 73, 90, 39, 54, 41, 12, 92, 85,  4, 41, 35, 65, 46,\n",
      "        46, 59, 21, 33, 92,  7,  0, 65, 59, 57,  3, 24, 61, 31])\n",
      "1462 torch.Size([32, 3, 32, 32]) tensor([70, 50, 48, 71, 17, 81, 27, 45, 13, 85, 45, 71, 96, 22, 98,  1, 29, 84,\n",
      "        44, 81,  3, 79, 16, 47, 60, 39, 54, 56, 72,  8, 45, 54])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1463 torch.Size([32, 3, 32, 32]) tensor([59, 30, 77, 41, 17, 37, 64, 95,  4,  8, 40, 20, 58, 38, 16, 22, 53, 20,\n",
      "        36, 28, 65, 75, 92, 76, 73, 45, 48, 84, 73, 58, 91, 24])\n",
      "1464 torch.Size([32, 3, 32, 32]) tensor([47, 46, 20, 50, 78, 89, 94, 20,  0, 91, 39, 86, 75,  7, 17, 59, 16, 40,\n",
      "         8, 27,  5, 21, 53, 49, 71, 65,  2, 50, 35, 90, 59, 87])\n",
      "1465 torch.Size([32, 3, 32, 32]) tensor([66, 32, 94, 47, 80,  2, 79, 92, 80, 92, 35, 37, 17, 81, 76, 49, 89, 17,\n",
      "        54, 11, 81, 85, 29,  8,  5, 67, 79,  1,  5, 99, 43, 20])\n",
      "1466 torch.Size([32, 3, 32, 32]) tensor([43, 97, 86, 73, 20, 10, 48, 67, 37, 17, 42, 71, 39, 25, 66, 77, 95, 46,\n",
      "        98, 34, 49, 25, 33, 38, 43, 96, 16, 22, 64, 95, 18, 85])\n",
      "1467 torch.Size([32, 3, 32, 32]) tensor([75, 24, 81, 28, 71, 53, 84, 88, 88, 67, 69, 57, 95, 46, 16, 90, 20, 70,\n",
      "        36, 76, 30, 87, 69, 77, 18, 68, 63, 86, 88, 67, 45,  3])\n",
      "1468 torch.Size([32, 3, 32, 32]) tensor([11,  6, 51, 33, 76, 85, 31, 69, 73, 14, 11, 26, 55, 41,  0, 65, 47, 79,\n",
      "         5, 27, 77, 25, 95, 36, 13, 94, 20, 93, 56, 40,  8, 28])\n",
      "1469 torch.Size([32, 3, 32, 32]) tensor([ 7, 10,  2, 94, 45, 72, 49, 76, 61, 70, 42,  0,  1, 31, 66, 31, 47, 35,\n",
      "        88, 74, 42, 97, 60, 22, 90, 42, 14, 24, 48, 55,  1, 97])\n",
      "1470 torch.Size([32, 3, 32, 32]) tensor([53, 30, 45, 68, 38, 45, 50, 95, 85, 14, 78, 62, 78, 32, 87, 63, 69, 79,\n",
      "        45, 32, 97, 72, 49, 75, 37, 75, 68, 69, 75,  2, 64, 18])\n",
      "1471 torch.Size([32, 3, 32, 32]) tensor([66, 40, 87, 41, 59, 92, 45, 48, 53, 44, 88, 73, 71,  5, 31, 80, 57, 43,\n",
      "        58, 41, 99, 56, 78, 89, 86,  6, 44, 74, 13, 36, 13,  6])\n",
      "1472 torch.Size([32, 3, 32, 32]) tensor([ 8, 64, 85, 77, 31,  1, 53, 96,  7, 39, 76, 41, 97, 55, 91, 14, 90, 91,\n",
      "        80, 41, 23, 86, 12, 26, 70, 17, 21, 51, 67, 96, 47,  9])\n",
      "1473 torch.Size([32, 3, 32, 32]) tensor([80, 25,  9, 39, 19,  7, 89, 21, 81, 36,  4, 75, 44, 43, 30,  3, 56, 98,\n",
      "        54, 43, 55, 31, 69, 11, 36,  4, 93, 61, 32, 19, 88, 21])\n",
      "1474 torch.Size([32, 3, 32, 32]) tensor([76, 84, 42, 23, 47, 65, 69,  3, 86, 10, 54,  7, 94, 72, 44, 91, 85,  9,\n",
      "        81, 66, 50,  6, 51, 45,  0, 20, 75, 27, 49, 84, 42, 99])\n",
      "1475 torch.Size([32, 3, 32, 32]) tensor([ 7, 99,  5, 71, 13, 59, 94, 25, 39, 22, 52, 88, 39, 65, 41, 20, 15, 47,\n",
      "        81, 98,  7, 44, 65, 28,  0, 48, 38,  8, 28, 36, 56, 77])\n",
      "1476 torch.Size([32, 3, 32, 32]) tensor([94, 90, 30, 89, 93, 56, 84, 57, 19, 14, 60, 47, 10, 33, 62,  8, 53, 60,\n",
      "        62, 81, 83, 61, 37, 91, 76,  7, 49, 77, 41, 25, 49, 77])\n",
      "1477 torch.Size([32, 3, 32, 32]) tensor([ 3, 79, 26, 46, 37, 79,  7, 46, 73, 69, 56, 42, 13,  9, 95, 92, 92, 99,\n",
      "        76, 73, 58,  5, 42, 42,  4, 13, 96, 98, 53, 65, 24, 69])\n",
      "1478 torch.Size([32, 3, 32, 32]) tensor([95, 47, 54, 80,  9,  2,  8,  3, 17, 69, 65,  2, 38, 38, 42, 64, 83,  9,\n",
      "        92, 61, 12, 70,  1, 44, 50, 58, 23, 81, 45, 75, 40, 23])\n",
      "1479 torch.Size([32, 3, 32, 32]) tensor([92, 32, 87, 28, 53, 76, 23, 49, 59, 55, 33, 28, 25, 44, 78,  2, 20, 69,\n",
      "        14, 26, 85, 16, 46, 51, 62, 70, 31, 88, 28, 13,  2, 55])\n",
      "1480 torch.Size([32, 3, 32, 32]) tensor([41, 98, 23,  2, 93, 50, 12, 45, 64, 89, 98, 30, 46, 44, 74, 41, 78, 80,\n",
      "        69, 63,  8,  6, 42, 35, 48, 28,  0, 77, 55, 86, 50, 22])\n",
      "1481 torch.Size([32, 3, 32, 32]) tensor([55, 27, 53, 41, 46,  2, 80, 40, 47, 44, 34, 32,  6, 56, 79,  0, 24, 91,\n",
      "        80,  6, 86, 25, 98, 41, 97, 30, 30, 77, 69, 66, 39, 41])\n",
      "1482 torch.Size([32, 3, 32, 32]) tensor([64, 61, 63, 78, 64, 95, 23, 84,  6, 43, 37, 50, 32, 82, 83, 89, 80, 62,\n",
      "        26, 71, 67, 28, 95, 99, 31, 44, 41, 88, 78, 64, 25, 10])\n",
      "1483 torch.Size([32, 3, 32, 32]) tensor([22, 90, 50, 33, 69, 35,  0, 26, 37,  0,  3,  8, 77, 67, 18, 52, 71, 68,\n",
      "        63, 18, 34,  9, 57, 87, 88, 69, 31, 18, 92, 18, 43, 90])\n",
      "1484 torch.Size([32, 3, 32, 32]) tensor([16, 98, 98, 65, 41, 34,  9, 52, 55, 26, 34, 28, 10, 18, 12, 74,  0, 19,\n",
      "        44,  8, 37, 55, 53, 73,  4, 53, 21,  0, 84, 42, 48,  2])\n",
      "1485 torch.Size([32, 3, 32, 32]) tensor([ 1, 71, 96, 72, 38, 62, 75, 28, 46, 10, 88, 75, 25,  8,  9, 30, 64, 95,\n",
      "        49, 68, 24, 12, 71,  7, 73, 37, 77, 16, 93, 35, 53, 36])\n",
      "1486 torch.Size([32, 3, 32, 32]) tensor([43, 20, 37, 40, 15, 31, 57, 17, 90, 69, 37, 26, 15, 45, 88, 72, 77, 11,\n",
      "        79, 89, 24, 73,  3, 12, 69,  6, 55,  5, 10,  8, 44, 74])\n",
      "1487 torch.Size([32, 3, 32, 32]) tensor([88, 83, 56, 37, 45, 99, 21, 25,  9,  1, 53, 32, 57, 16,  9, 28, 43, 23,\n",
      "        66, 65, 20,  3, 37,  4, 33, 45, 98,  6, 97, 95, 84, 78])\n",
      "1488 torch.Size([32, 3, 32, 32]) tensor([16, 18, 47,  4, 81, 70, 96, 32, 86, 68, 97, 58, 72, 14, 16, 36, 67, 67,\n",
      "        13, 59, 17, 97, 37,  4,  6,  7, 63, 92, 45,  0, 22, 49])\n",
      "1489 torch.Size([32, 3, 32, 32]) tensor([24, 20, 21, 33, 99, 65, 85, 98, 91, 18, 59, 58, 93,  6, 90, 17, 68, 22,\n",
      "        67, 40, 88, 94, 11, 10, 93, 29, 63, 66, 60,  8, 33, 70])\n",
      "1490 torch.Size([32, 3, 32, 32]) tensor([48, 57, 26, 69,  1, 82, 61, 33, 49, 29, 52, 26, 78, 81, 42, 21, 27, 45,\n",
      "        34, 62, 47, 18, 21, 43, 39, 89, 83, 94, 85, 72, 66, 81])\n",
      "1491 torch.Size([32, 3, 32, 32]) tensor([47, 87, 27, 45, 18, 13, 48, 43, 26, 28, 90,  6, 47, 28, 18, 17, 12, 13,\n",
      "        28, 15, 98, 66, 90, 77,  7, 45, 96, 79, 56, 31, 76, 18])\n",
      "1492 torch.Size([32, 3, 32, 32]) tensor([43, 53, 67, 23, 35,  1, 52, 60, 35, 22, 93, 83, 13, 92, 18, 77, 52, 43,\n",
      "        62, 21, 81,  3, 89, 51, 50, 16, 27, 33, 31,  5, 43, 85])\n",
      "1493 torch.Size([32, 3, 32, 32]) tensor([22, 45, 97, 88, 93, 22, 57,  2, 84, 41, 14, 41, 72, 57, 35, 99, 39, 60,\n",
      "        32,  3, 86, 18, 61, 39, 89, 30,  9, 64, 79, 83, 85, 57])\n",
      "1494 torch.Size([32, 3, 32, 32]) tensor([73, 60, 51, 25, 37, 47, 28, 40, 78, 16, 17, 31, 34, 55, 92, 25, 17, 43,\n",
      "        10,  5, 95, 28, 31, 94, 45, 41, 27, 20, 54, 81, 15, 37])\n",
      "1495 torch.Size([32, 3, 32, 32]) tensor([ 7, 86, 42, 73, 89, 45, 97, 73, 94, 44, 27, 92, 66, 36, 44, 37, 44, 97,\n",
      "        22, 11,  0, 80, 23, 38, 98, 61, 69, 91, 17, 83, 92,  3])\n",
      "1496 torch.Size([32, 3, 32, 32]) tensor([29, 49, 32, 81, 61, 35, 49, 95, 21, 59, 84, 79, 46, 60, 30, 84,  2, 44,\n",
      "        55, 81, 86, 81, 35, 87, 39, 93, 92, 93, 91, 12, 60, 46])\n",
      "1497 torch.Size([32, 3, 32, 32]) tensor([51, 47, 89, 64,  7, 23, 25, 87, 68, 16, 47, 17, 57, 52, 59, 90, 17, 93,\n",
      "        30, 79, 75, 73, 96, 10,  1, 60, 43, 89, 91, 44, 43, 94])\n",
      "1498 torch.Size([32, 3, 32, 32]) tensor([37, 64, 62, 29, 75, 55, 31, 93, 95, 85,  3, 59, 37, 10, 63, 99, 33, 48,\n",
      "         2, 76, 21, 96, 85, 38, 29, 40, 86, 80, 95, 86, 70, 28])\n",
      "1499 torch.Size([32, 3, 32, 32]) tensor([32, 94, 50, 84, 32, 37, 11, 69, 62,  8, 40, 97, 37, 88, 98,  4, 65, 35,\n",
      "        93, 54, 60, 43, 71, 84, 38, 85, 64, 59, 73,  6, 96,  1])\n",
      "1500 torch.Size([32, 3, 32, 32]) tensor([14, 37, 55,  2, 11,  3, 44, 32, 19, 25, 74, 33, 76,  7, 46, 69, 62, 65,\n",
      "        34, 92, 95, 99, 38, 61,  1, 57, 89, 28, 10, 99, 91, 75])\n",
      "1501 torch.Size([32, 3, 32, 32]) tensor([ 3, 41, 82, 76, 46, 99, 68, 33, 87, 33, 23, 34,  0, 34, 21,  2, 97, 18,\n",
      "        29, 92, 62, 90, 63, 13, 57, 86, 33, 46, 61, 25, 47, 42])\n",
      "1502 torch.Size([32, 3, 32, 32]) tensor([68, 29, 87, 15, 57, 93, 17, 33, 23, 69, 12, 53, 20,  6, 99, 67, 57, 77,\n",
      "        86,  3, 72, 19, 89, 48, 11,  1, 37, 26, 89, 78, 81, 28])\n",
      "1503 torch.Size([32, 3, 32, 32]) tensor([78, 45, 79, 33, 82,  8, 11, 77, 41,  0, 66,  8, 64, 53,  5, 96, 68, 90,\n",
      "        98, 24, 90, 93, 16,  2, 68, 64, 13, 20, 96, 68, 10, 56])\n",
      "1504 torch.Size([32, 3, 32, 32]) tensor([51, 76, 48,  9, 64, 53,  0, 50, 92, 45, 54, 55, 54, 34,  3, 25,  0, 23,\n",
      "        23, 81, 70,  9, 14,  6, 34, 88, 50, 29, 21, 37, 23, 60])\n",
      "1505 torch.Size([32, 3, 32, 32]) tensor([73, 94, 20,  7, 72, 70, 73, 48, 32, 86, 14, 54, 26, 31, 50, 58, 21, 82,\n",
      "        60, 76, 24, 63, 62, 69, 57, 31, 49, 82, 66, 27, 34, 86])\n",
      "1506 torch.Size([32, 3, 32, 32]) tensor([26, 90, 10, 59, 50, 98, 28, 21, 32, 87,  6, 40, 63, 11, 11, 57, 40, 71,\n",
      "        11, 99, 28, 21, 92, 38, 27, 83, 46, 90, 79, 28, 66, 91])\n",
      "1507 torch.Size([32, 3, 32, 32]) tensor([33, 71, 82, 97, 75, 46, 67, 57, 51, 68, 15, 89, 81, 25, 24, 66, 48, 10,\n",
      "         6, 52,  7, 66, 92, 16, 59, 18, 78, 48, 33, 12, 43, 37])\n",
      "1508 torch.Size([32, 3, 32, 32]) tensor([75, 50, 34,  9, 27, 88, 84, 30, 83, 89, 21, 91, 11, 29, 27, 49, 11, 65,\n",
      "        98, 77, 24, 58, 17, 63, 52, 33, 45, 44,  7, 24, 10, 55])\n",
      "1509 torch.Size([32, 3, 32, 32]) tensor([19, 20, 77,  3,  3, 49,  4, 58, 30, 89, 33, 52,  2, 38, 41, 83, 13, 91,\n",
      "        33, 19, 37, 65,  1, 70, 55, 55, 31, 34, 49,  4, 95, 26])\n",
      "1510 torch.Size([32, 3, 32, 32]) tensor([24, 13, 25, 20,  7, 39, 23,  1, 80, 78, 36, 37, 64, 17, 12, 77,  9, 29,\n",
      "        51, 37, 57, 54, 41, 67, 55, 36, 84, 71, 24,  9, 73, 42])\n",
      "1511 torch.Size([32, 3, 32, 32]) tensor([69,  8, 49, 46, 44, 91, 28, 80, 86, 84, 36, 48, 60, 86,  4, 27,  1, 92,\n",
      "        77, 35, 53, 84, 57,  9, 99,  5, 16, 40, 93, 35, 73, 40])\n",
      "1512 torch.Size([32, 3, 32, 32]) tensor([ 5, 74, 23, 20,  6, 66, 81, 73, 31, 36,  1, 46, 17, 36, 34,  2, 62, 94,\n",
      "        93, 77, 53, 58, 22, 15, 70, 40, 58, 68, 82, 78, 98, 44])\n",
      "1513 torch.Size([32, 3, 32, 32]) tensor([98, 31, 33, 98, 43, 61, 13, 71, 33, 30, 48, 45, 57, 17, 45, 75, 30, 29,\n",
      "        17, 79,  2, 61, 51, 41,  6, 64, 84, 82, 20,  6, 33, 39])\n",
      "1514 torch.Size([32, 3, 32, 32]) tensor([76,  5, 35, 35, 92,  2, 76, 18, 97, 18, 36, 50, 45, 67, 69, 87, 48, 44,\n",
      "        82, 48, 32, 82, 51, 72, 27, 37, 84,  9, 59, 48, 99, 92])\n",
      "1515 torch.Size([32, 3, 32, 32]) tensor([57, 40, 71, 45, 17, 43, 67, 21, 97, 21, 57, 69, 79,  7, 50,  9,  6, 77,\n",
      "        89, 13, 69, 22, 24, 24, 51, 85, 11, 32, 99, 94, 96, 75])\n",
      "1516 torch.Size([32, 3, 32, 32]) tensor([96, 67, 95, 83, 54,  9, 93, 81, 81, 40, 52, 70, 56, 14, 70, 81, 56, 63,\n",
      "        81, 37, 10, 72, 21, 25, 52, 87, 88, 41, 76, 16, 22, 78])\n",
      "1517 torch.Size([32, 3, 32, 32]) tensor([56, 62, 44, 15, 23,  3, 76,  8, 55, 86, 55, 46, 56,  7, 57, 24, 43, 31,\n",
      "        86, 38, 12, 31, 70, 56, 91, 64,  0, 35, 28, 68, 85, 11])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1518 torch.Size([32, 3, 32, 32]) tensor([31, 88,  0, 71, 83, 42,  7, 10, 38, 60, 83, 21, 55, 22, 24, 19,  1, 74,\n",
      "        32, 64, 41, 35, 72, 27, 59, 18, 27, 18, 21, 84, 52, 52])\n",
      "1519 torch.Size([32, 3, 32, 32]) tensor([56, 60, 57, 40, 95,  4, 36, 85, 62, 48,  2, 51, 53, 16, 13, 64, 12, 93,\n",
      "        88, 36, 36, 98, 13, 74, 68, 76, 92,  0, 98, 48, 64, 52])\n",
      "1520 torch.Size([32, 3, 32, 32]) tensor([19, 16, 86,  3, 56, 48, 43, 23, 26, 87, 85, 71, 85, 27, 98, 92, 39, 21,\n",
      "        31, 16, 50, 60, 59, 43, 33, 40, 79, 94, 29, 52, 90, 50])\n",
      "1521 torch.Size([32, 3, 32, 32]) tensor([81, 75, 35, 32, 83, 81,  4, 34, 29, 56, 77, 59, 56, 59, 12, 56, 24, 93,\n",
      "        10,  5, 56, 67, 16, 14, 57, 55, 91, 46, 44, 12, 23, 58])\n",
      "1522 torch.Size([32, 3, 32, 32]) tensor([80, 23, 49, 51, 95, 79, 87, 16, 41, 61, 69, 99,  6, 95, 87, 17, 95, 25,\n",
      "        31, 29, 64, 16, 93, 47, 23,  3, 51, 89, 25, 45, 11, 24])\n",
      "1523 torch.Size([32, 3, 32, 32]) tensor([78, 36, 17, 78, 70, 22, 52, 13, 10, 79,  1, 89, 39, 37, 73, 33, 35, 83,\n",
      "        30, 14,  0,  1, 51, 41, 46, 76, 27, 66, 71, 40, 70, 32])\n",
      "1524 torch.Size([32, 3, 32, 32]) tensor([35,  1, 64, 33, 69, 16, 36, 34, 62, 45, 97, 84, 97, 38, 14, 86, 71, 15,\n",
      "         0, 11, 41,  6, 12,  3, 44, 87, 26,  0, 13, 30, 23, 63])\n",
      "1525 torch.Size([32, 3, 32, 32]) tensor([25, 12, 59, 64, 28, 20, 15, 29, 33, 22, 69, 40, 70, 46, 76, 17, 74, 95,\n",
      "        75, 13, 82, 13, 48, 95, 61, 70,  9, 92, 86, 80, 74, 13])\n",
      "1526 torch.Size([32, 3, 32, 32]) tensor([23,  0, 45, 80, 20, 83, 40, 64, 73, 38, 35, 27, 39, 79, 88, 97, 32,  7,\n",
      "        24,  7, 42, 56, 72, 53, 28,  3, 48, 21, 38, 83, 19, 48])\n",
      "1527 torch.Size([32, 3, 32, 32]) tensor([43, 68, 27, 78, 69, 39,  6, 18, 19, 12, 39, 46, 32,  6, 87, 95, 89, 42,\n",
      "        75, 57, 10, 87, 75,  8, 32, 72, 30, 13, 90, 69, 84, 36])\n",
      "1528 torch.Size([32, 3, 32, 32]) tensor([17, 16, 87, 60, 90, 45, 39, 38, 70, 21, 67, 61, 42, 52, 52, 76, 16, 87,\n",
      "        76, 52, 54, 42, 92, 95, 23, 18, 41, 17, 48, 94,  6,  1])\n",
      "1529 torch.Size([32, 3, 32, 32]) tensor([65, 70, 25, 20, 99, 34, 61,  4, 17, 61,  7,  2, 72, 58, 99, 81, 38, 11,\n",
      "        75, 19, 39, 98, 23, 68, 35, 19,  4,  2, 12,  7, 64, 53])\n",
      "1530 torch.Size([32, 3, 32, 32]) tensor([35, 45, 63, 24, 31, 44, 56, 54, 98, 43, 26,  4, 71, 76, 94, 95, 23, 66,\n",
      "        10, 93,  2, 44, 65, 41, 57, 98, 67, 45, 15, 32, 27,  4])\n",
      "1531 torch.Size([32, 3, 32, 32]) tensor([ 0, 11, 32,  0, 15, 32, 12, 92,  6, 84, 38, 49, 36, 93, 58, 11, 25, 91,\n",
      "        15, 92, 28,  6,  8,  3, 52, 61,  3, 28, 64, 97, 62, 73])\n",
      "1532 torch.Size([32, 3, 32, 32]) tensor([62, 37, 14, 57, 30, 44, 81, 43, 30, 53, 21, 34, 82, 28, 50, 45, 81,  0,\n",
      "         7, 14, 16, 53,  9, 23, 51, 96, 22,  0, 29, 20, 10,  9])\n",
      "1533 torch.Size([32, 3, 32, 32]) tensor([97, 63, 26, 27, 38, 53, 56, 72, 34, 56,  7, 61, 21, 72, 90, 60, 49, 50,\n",
      "        66, 76, 23, 27, 83, 19, 15, 38,  5, 19, 52, 99, 68,  9])\n",
      "1534 torch.Size([32, 3, 32, 32]) tensor([ 1, 48, 20,  3,  8, 24, 70, 37, 80, 88, 61, 92, 54, 63, 52, 36, 66,  6,\n",
      "        74, 38, 73, 44, 64, 89, 68, 58, 89, 26, 58, 67, 49, 60])\n",
      "1535 torch.Size([32, 3, 32, 32]) tensor([16, 38, 66, 87, 41, 17, 35, 42, 24, 77, 41, 71, 78, 55, 67,  6, 76, 41,\n",
      "        54, 31, 14, 13,  1, 72, 21, 92, 98, 85, 85, 24, 92, 84])\n",
      "1536 torch.Size([32, 3, 32, 32]) tensor([66, 10, 74, 78, 10, 90, 21, 31,  8, 28, 81, 25, 18, 31, 92, 94, 96, 57,\n",
      "        10, 77, 33, 80, 95, 21, 54, 95, 40, 41, 62, 59, 39, 47])\n",
      "1537 torch.Size([32, 3, 32, 32]) tensor([60, 49, 56, 40, 62, 39,  1, 14, 74, 58, 60, 58, 14, 51, 86,  2, 87, 90,\n",
      "         3, 54, 72, 22, 22, 76, 78, 98, 43, 81, 79, 18, 26, 17])\n",
      "1538 torch.Size([32, 3, 32, 32]) tensor([12, 55, 89, 53, 19, 28, 48, 94, 74, 10, 57, 66, 25, 86, 22, 27, 53, 88,\n",
      "        63,  1, 36, 76, 27,  0, 45, 70, 48, 83, 85, 41,  6, 88])\n",
      "1539 torch.Size([32, 3, 32, 32]) tensor([33, 95, 99, 44, 94,  0, 15, 38, 34, 43, 77, 14, 70, 90, 98, 17, 95, 93,\n",
      "        37, 75, 56, 98, 27, 25, 32, 88, 97,  6, 16, 61, 65, 75])\n",
      "1540 torch.Size([32, 3, 32, 32]) tensor([36, 85,  9, 10, 19, 38, 49,  9, 11, 67, 16, 62, 32, 59, 87, 46, 27, 86,\n",
      "        13, 60, 82, 69, 75, 46, 51, 30, 54, 38, 95, 51, 69,  3])\n",
      "1541 torch.Size([32, 3, 32, 32]) tensor([50, 18, 88, 11, 19,  9, 21, 67, 80, 73, 36, 22, 64, 94, 90, 92, 26, 73,\n",
      "        11,  4, 54, 31, 88,  6, 25, 66, 10, 90, 73,  7,  0, 91])\n",
      "1542 torch.Size([32, 3, 32, 32]) tensor([77, 75, 58,  1, 78, 90,  8,  2, 52, 13, 63, 28, 73, 32, 65,  1, 53, 33,\n",
      "         9,  8, 99, 29, 62, 75,  7, 96, 53, 46, 88, 74, 72, 65])\n",
      "1543 torch.Size([32, 3, 32, 32]) tensor([26, 44, 47, 30, 25, 93, 11, 77, 43, 62, 25, 81, 35, 88, 39, 61, 40, 29,\n",
      "        15, 31,  1, 92, 45, 45, 70, 41, 21, 75, 47, 25, 97, 63])\n",
      "1544 torch.Size([32, 3, 32, 32]) tensor([23, 78, 11, 34,  1, 71,  8, 20, 75, 86, 78, 66, 27, 42, 17, 96, 81, 65,\n",
      "        54, 25, 50, 44, 90, 79, 81,  4, 72, 32,  0, 94, 98, 95])\n",
      "1545 torch.Size([32, 3, 32, 32]) tensor([27, 95, 11,  9, 54,  9, 30, 72, 71,  4, 83, 55, 84, 98,  2, 10, 67, 30,\n",
      "        77, 19, 43, 86, 19, 36, 88, 31, 60, 20, 93, 22, 43, 42])\n",
      "1546 torch.Size([32, 3, 32, 32]) tensor([37, 23, 62, 86, 98, 53, 57, 93, 25, 70,  6, 29, 42, 85, 34, 24, 90, 90,\n",
      "        49, 65, 58, 85, 81, 24, 79, 38, 78, 62, 47, 58, 70, 39])\n",
      "1547 torch.Size([32, 3, 32, 32]) tensor([74, 73,  1, 90, 77, 60, 47, 15, 98, 37, 86, 49, 34,  0, 65, 57, 57, 86,\n",
      "        40, 76, 49, 44, 50, 32, 40, 13, 58, 32, 65, 94, 50,  5])\n",
      "1548 torch.Size([32, 3, 32, 32]) tensor([ 6, 71, 13, 91, 19, 57, 63, 64, 17, 51, 53, 99, 63, 63, 86, 30, 99, 34,\n",
      "        75, 73, 13, 84,  5, 15, 43, 12, 38, 89, 64, 53, 66, 99])\n",
      "1549 torch.Size([32, 3, 32, 32]) tensor([58, 39, 16, 24, 96, 65, 55, 80, 75, 70, 49, 58, 20, 55, 95, 45, 36, 13,\n",
      "         2, 77, 27, 91, 39, 93, 82, 39, 68, 23, 52, 61, 71, 84])\n",
      "1550 torch.Size([32, 3, 32, 32]) tensor([34, 32, 70, 14, 27, 24, 69, 57, 27, 90, 91, 47, 98, 69, 28, 53, 13, 18,\n",
      "        10,  8, 80, 86, 91, 83, 39,  4, 77,  2, 12, 84, 37, 96])\n",
      "1551 torch.Size([32, 3, 32, 32]) tensor([ 8, 21, 76, 36, 62, 60, 38, 61, 59, 29, 80, 47, 87, 40, 76, 23, 79, 91,\n",
      "         6, 66, 52, 41, 41, 28, 40, 40, 43, 27, 59, 48, 46,  9])\n",
      "1552 torch.Size([32, 3, 32, 32]) tensor([29, 83, 19, 96,  4, 18, 74, 94, 64, 69, 25, 98, 32, 86,  3, 82, 91, 87,\n",
      "        62, 31, 66, 71, 48, 14, 12, 41,  1, 58, 27, 62, 17, 89])\n",
      "1553 torch.Size([32, 3, 32, 32]) tensor([ 1, 83, 29, 26, 57, 15, 16, 15, 78, 33,  0,  3, 74, 41, 79,  7, 98,  3,\n",
      "        88, 41,  2, 84, 83, 60, 89, 79,  3, 82, 17, 74, 30, 31])\n",
      "1554 torch.Size([32, 3, 32, 32]) tensor([73, 60, 11, 59, 93, 14, 22, 64, 67, 81, 24,  4, 79, 83, 17, 73, 65, 48,\n",
      "        67, 43, 98,  8, 10, 27, 75, 67, 16, 66, 53, 21, 33, 92])\n",
      "1555 torch.Size([32, 3, 32, 32]) tensor([79, 63, 59, 61, 89, 39, 25, 84, 40, 28, 69, 17, 74, 20, 90, 11, 29, 53,\n",
      "         2, 50, 10, 60, 38, 51, 21,  8, 60, 92,  4, 34,  7, 56])\n",
      "1556 torch.Size([32, 3, 32, 32]) tensor([13, 45, 86, 12, 33, 95, 30, 26, 62, 62, 57, 99, 40, 80, 41,  5,  4, 57,\n",
      "        31, 93, 40, 47, 57, 54, 77, 73, 67, 63, 88, 63, 54, 33])\n",
      "1557 torch.Size([32, 3, 32, 32]) tensor([14, 81, 20,  9, 79,  1, 84,  9, 45,  6, 34,  9, 27, 82, 35, 85, 27, 41,\n",
      "        78, 78, 99, 99, 12, 18, 50, 96, 71, 21,  5, 79, 27, 21])\n",
      "1558 torch.Size([32, 3, 32, 32]) tensor([94, 54, 38, 82, 31, 31, 48, 40, 67, 83, 64, 13, 34, 44, 47, 79, 52, 40,\n",
      "        99, 88, 39, 51, 10, 89,  0, 14, 51,  1,  4,  9, 54, 72])\n",
      "1559 torch.Size([32, 3, 32, 32]) tensor([17, 20, 18, 90, 43, 74, 61,  5, 74, 90, 16, 90, 12, 14, 24, 69, 66, 36,\n",
      "         3, 25, 62,  2, 84, 60, 96, 44, 29,  3, 36, 11, 13, 45])\n",
      "1560 torch.Size([32, 3, 32, 32]) tensor([27,  6, 11, 78, 17, 52, 53, 88, 97, 48, 52, 34, 66, 50, 81, 90, 46, 81,\n",
      "        49, 79, 11,  3,  5, 67, 26, 87, 65, 59, 29, 20, 55, 90])\n",
      "1561 torch.Size([32, 3, 32, 32]) tensor([ 1, 38, 92, 76, 13, 52, 62, 38,  8, 95, 43, 43,  2, 32, 28, 69, 62, 72,\n",
      "        22, 61, 89,  9, 90, 36, 97,  7, 48, 22, 49, 74, 21, 30])\n",
      "1562 torch.Size([16, 3, 32, 32]) tensor([53, 61, 81, 41, 21, 19, 97, 47, 72, 51, 67, 42, 14, 86, 37, 36])\n"
     ]
    }
   ],
   "source": [
    "for k, (data, target) in enumerate(test_loader):\n",
    "    print(k, data.shape, target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 2, 2, 0, 1, 7, 6, 1, 4, 7, 5, 8, 1, 3, 1, 4])\n",
      "1 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 8, 0, 8, 2, 3, 1, 1, 8, 5, 5, 6, 4, 8, 2])\n",
      "2 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 7, 0, 3, 9, 4, 2, 6, 7, 4, 2, 5, 2, 7, 5])\n",
      "3 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 6, 7, 8, 0, 6, 1, 8, 7, 2, 7, 6, 2, 0, 7, 6])\n",
      "4 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 7, 7, 0, 3, 2, 8, 6, 2, 2, 0, 3, 5, 3, 5, 2])\n",
      "5 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 7, 8, 3, 1, 4, 7, 4, 4, 7, 9, 7, 3, 3, 0, 9])\n",
      "6 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 7, 9, 3, 2, 3, 7, 2, 4, 2, 3, 8, 0, 1, 9, 8])\n",
      "7 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 4, 1, 0, 9, 3, 8, 1, 2, 7, 6, 8, 9, 8, 6, 5])\n",
      "8 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 6, 1, 9, 7, 2, 1, 1, 6, 4, 9, 7, 2, 8, 3])\n",
      "9 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 3, 6, 1, 3, 8, 0, 0, 5, 9, 3, 7, 3, 5, 6])\n",
      "10 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 7, 8, 5, 6, 0, 4, 2, 9, 4, 3, 9, 9, 1, 9])\n",
      "11 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 1, 0, 0, 4, 4, 5, 8, 1, 9, 2, 6, 5, 6, 6])\n",
      "12 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 4, 8, 3, 9, 0, 8, 7, 6, 3, 5, 3, 2, 3, 3, 6])\n",
      "13 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 6, 3, 1, 8, 5, 5, 6, 4, 1, 0, 0, 9, 8, 0])\n",
      "14 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 9, 6, 9, 0, 9, 6, 5, 1, 4, 6, 0, 0, 5, 8])\n",
      "15 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 1, 3, 9, 6, 7, 1, 3, 7, 4, 2, 4, 3, 7, 6, 6])\n",
      "16 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 2, 5, 8, 9, 7, 4, 2, 1, 9, 6, 5, 5, 0, 0, 0])\n",
      "17 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 5, 0, 1, 0, 5, 5, 0, 3, 0, 4, 1, 1, 7, 0])\n",
      "18 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 1, 3, 1, 2, 2, 1, 6, 8, 3, 3, 1, 4, 8, 8])\n",
      "19 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 8, 6, 7, 2, 2, 0, 1, 2, 6, 7, 4, 3, 9, 3, 9])\n",
      "20 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 8, 1, 7, 7, 8, 8, 1, 2, 5, 8, 7, 0, 4, 4])\n",
      "21 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 8, 8, 9, 5, 4, 8, 9, 6, 3, 3, 7, 7, 8, 4])\n",
      "22 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 0, 2, 4, 3, 3, 9, 4, 9, 4, 3, 6, 9, 2, 7])\n",
      "23 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 4, 8, 1, 7, 5, 6, 8, 2, 2, 2, 5, 2, 1, 6])\n",
      "24 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 1, 1, 5, 6, 2, 3, 4, 2, 8, 9, 2, 1, 9, 7])\n",
      "25 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 4, 2, 7, 8, 3, 8, 8, 8, 3, 6, 5, 0, 9, 1])\n",
      "26 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 4, 8, 5, 4, 5, 0, 6, 4, 4, 0, 8, 2, 1, 9, 8])\n",
      "27 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 3, 6, 7, 4, 9, 8, 0, 4, 0, 1, 1, 4, 5, 5])\n",
      "28 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 0, 9, 7, 1, 6, 5, 0, 8, 2, 2, 5, 8, 4, 7])\n",
      "29 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 7, 7, 8, 7, 9, 7, 3, 6, 1, 5, 3, 5, 5, 1])\n",
      "30 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 0, 6, 4, 5, 9, 3, 1, 0, 2, 9, 1, 5, 2, 7])\n",
      "31 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 9, 1, 5, 3, 0, 2, 3, 6, 4, 0, 9, 8, 0, 0])\n",
      "32 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 7, 3, 9, 1, 6, 3, 9, 1, 9, 3, 7, 0, 7, 9])\n",
      "33 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 1, 3, 8, 9, 4, 1, 9, 2, 5, 4, 9, 2, 8, 9])\n",
      "34 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 2, 1, 6, 3, 5, 8, 1, 9, 4, 0, 8, 1, 8, 4])\n",
      "35 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 2, 8, 1, 3, 4, 8, 2, 2, 3, 3, 6, 6, 2, 2])\n",
      "36 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 9, 7, 4, 6, 6, 5, 5, 8, 8, 1, 9, 3, 2, 2])\n",
      "37 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 8, 8, 6, 2, 0, 9, 6, 7, 0, 9, 2, 2, 5, 9, 4])\n",
      "38 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 4, 4, 4, 7, 9, 0, 5, 2, 4, 3, 2, 2, 0, 9])\n",
      "39 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 7, 9, 6, 7, 7, 6, 9, 0, 3, 1, 3, 8, 0, 4])\n",
      "40 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 0, 8, 4, 3, 6, 6, 9, 6, 3, 8, 0, 7, 2, 4])\n",
      "41 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 3, 8, 7, 5, 0, 1, 8, 8, 2, 0, 7, 6, 6, 4, 0])\n",
      "42 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 3, 5, 2, 7, 1, 3, 0, 1, 5, 5, 0, 1, 9, 8, 6])\n",
      "43 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 4, 5, 3, 8, 1, 8, 4, 7, 0, 6, 4, 6, 6, 4])\n",
      "44 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 2, 3, 3, 3, 5, 4, 0, 4, 3, 2, 6, 5, 4, 0])\n",
      "45 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 1, 4, 5, 5, 8, 2, 9, 5, 1, 3, 5, 2, 6, 2])\n",
      "46 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 6, 7, 1, 2, 6, 5, 2, 7, 5, 1, 5, 6, 1, 3, 4])\n",
      "47 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 9, 0, 8, 0, 3, 7, 6, 3, 5, 3, 4, 9, 3, 1, 9])\n",
      "48 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 7, 3, 1, 8, 7, 2, 7, 3, 4, 0, 1, 0, 0, 9, 8])\n",
      "49 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 4, 1, 8, 6, 9, 9, 2, 7, 1, 9, 5, 2, 7, 6, 8])\n",
      "50 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 8, 3, 5, 3, 6, 7, 4, 5, 3, 6, 0, 1, 1, 2, 6])\n",
      "51 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 4, 4, 0, 3, 3, 6, 1, 2, 3, 0, 8, 4, 9, 2, 3])\n",
      "52 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 0, 4, 3, 5, 6, 3, 7, 3, 7, 7, 3, 0, 0, 6, 5])\n",
      "53 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 7, 5, 0, 9, 4, 4, 1, 3, 8, 5, 1, 2, 6, 8])\n",
      "54 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 0, 2, 7, 4, 6, 5, 6, 3, 6, 2, 5, 0, 4, 2])\n",
      "55 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 0, 8, 0, 9, 0, 3, 1, 1, 6, 1, 2, 7, 3, 4])\n",
      "56 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 1, 1, 4, 4, 2, 4, 9, 8, 9, 0, 3, 9, 3, 4, 7])\n",
      "57 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 2, 1, 9, 1, 6, 1, 3, 1, 8, 0, 1, 7, 0, 1])\n",
      "58 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 6, 8, 9, 0, 3, 6, 0, 9, 9, 0, 4, 7, 0, 8])\n",
      "59 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 0, 7, 8, 2, 3, 3, 4, 7, 1, 5, 5, 5, 0, 2])\n",
      "60 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 7, 2, 2, 3, 3, 2, 1, 1, 8, 8, 8, 0, 6, 5])\n",
      "61 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 4, 5, 6, 1, 9, 1, 2, 0, 8, 0, 5, 4, 2, 5, 7])\n",
      "62 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 7, 3, 3, 0, 9, 4, 5, 6, 1, 9, 7, 2, 9, 1, 9])\n",
      "63 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 8, 7, 5, 6, 7, 8, 5, 5, 6, 8, 4, 2, 1, 1, 1])\n",
      "64 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 8, 8, 0, 9, 2, 4, 2, 2, 5, 2, 9, 9, 7, 3])\n",
      "65 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 3, 9, 6, 9, 7, 9, 9, 2, 5, 9, 4, 3, 1, 2, 3])\n",
      "66 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 8, 8, 6, 8, 9, 7, 7, 2, 4, 4, 9, 7, 0, 3, 9])\n",
      "67 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 0, 1, 1, 1, 6, 1, 6, 6, 5, 1, 2, 5, 7, 0, 5])\n",
      "68 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 3, 6, 1, 2, 7, 5, 5, 8, 9, 8, 2, 5, 2, 1, 1])\n",
      "69 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 6, 4, 7, 3, 4, 2, 6, 9, 4, 2, 6, 0, 0, 6])\n",
      "70 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 0, 9, 2, 2, 3, 6, 4, 0, 1, 9, 0, 9, 2, 4])\n",
      "71 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 9, 3, 7, 1, 7, 0, 0, 1, 5, 4, 4, 8, 5, 9])\n",
      "72 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 5, 0, 7, 8, 2, 2, 1, 7, 4, 0, 0, 3, 0, 0, 9])\n",
      "73 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 8, 1, 2, 4, 2, 2, 9, 4, 0, 9, 5, 8, 9, 5])\n",
      "74 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 9, 7, 6, 1, 5, 3, 8, 3, 1, 2, 7, 9, 1, 6])\n",
      "75 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 5, 9, 6, 8, 9, 2, 7, 1, 1, 0, 5, 1, 6, 3])\n",
      "76 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 2, 2, 7, 5, 5, 7, 4, 9, 6, 0, 9, 2, 4, 1, 9])\n",
      "77 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 2, 2, 0, 3, 5, 3, 0, 0, 2, 1, 4, 0, 6, 5, 4])\n",
      "78 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 0, 5, 7, 9, 8, 9, 3, 1, 9, 4, 8, 0, 5, 2])\n",
      "79 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 4, 0, 0, 2, 4, 2, 4, 0, 4, 9, 4, 4, 6, 2, 7])\n",
      "80 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 2, 9, 9, 8, 5, 8, 1, 8, 8, 3, 0, 4, 0, 9])\n",
      "81 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 1, 2, 5, 2, 2, 2, 9, 0, 5, 1, 3, 4, 5, 4, 1])\n",
      "82 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 9, 5, 2, 6, 5, 2, 8, 8, 7, 7, 8, 7, 7, 8])\n",
      "83 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 9, 0, 3, 7, 4, 4, 7, 3, 6, 6, 8, 7, 7, 2])\n",
      "84 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 9, 5, 2, 7, 1, 4, 0, 9, 3, 3, 5, 3, 9, 7, 3])\n",
      "85 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 8, 4, 8, 3, 3, 9, 3, 3, 4, 9, 2, 5, 3, 0])\n",
      "86 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 8, 2, 5, 0, 5, 7, 3, 6, 2, 3, 6, 9, 8, 2])\n",
      "87 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 0, 1, 0, 7, 9, 1, 2, 3, 6, 5, 5, 6, 7, 3])\n",
      "88 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 0, 2, 0, 2, 6, 7, 8, 2, 8, 5, 4, 5, 8, 1, 4])\n",
      "89 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 0, 7, 2, 9, 8, 3, 7, 6, 0, 6, 1, 5, 0, 0])\n",
      "90 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 2, 2, 9, 2, 6, 7, 4, 5, 5, 0, 5, 5, 1, 1])\n",
      "91 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 6, 2, 7, 1, 3, 5, 4, 9, 3, 7, 8, 9, 2, 0])\n",
      "92 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 9, 2, 0, 2, 7, 9, 4, 7, 9, 7, 2, 2, 3, 5])\n",
      "93 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 3, 1, 7, 2, 4, 3, 1, 4, 9, 0, 3, 1, 2, 6, 7])\n",
      "94 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 6, 3, 4, 5, 4, 6, 9, 8, 1, 2, 5, 9, 9, 1])\n",
      "95 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 0, 8, 5, 2, 4, 6, 3, 5, 1, 6, 2, 3, 9, 7])\n",
      "96 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 9, 8, 6, 0, 7, 9, 2, 4, 3, 0, 2, 1, 4, 0])\n",
      "97 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 9, 8, 1, 9, 6, 2, 1, 6, 6, 7, 3, 5, 9, 2])\n",
      "98 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 9, 9, 9, 8, 3, 7, 6, 5, 3, 3, 9, 2, 0, 9, 1])\n",
      "99 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 5, 6, 3, 4, 8, 8, 9, 1, 5, 5, 5, 6, 0, 8])\n",
      "100 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 0, 2, 9, 4, 4, 8, 9, 3, 3, 6, 5, 0, 8, 4])\n",
      "101 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 9, 3, 6, 1, 2, 7, 1, 5, 0, 4, 1, 6, 4, 7])\n",
      "102 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 8, 5, 2, 5, 0, 3, 5, 5, 6, 7, 3, 7, 0, 3, 4])\n",
      "103 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 2, 6, 9, 0, 3, 2, 3, 5, 9, 8, 9, 5, 0, 6, 0])\n",
      "104 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 7, 6, 2, 6, 4, 3, 0, 2, 2, 1, 8, 2, 9, 0])\n",
      "105 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 9, 7, 2, 8, 2, 6, 4, 6, 3, 6, 4, 3, 1, 0, 7])\n",
      "106 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 6, 3, 1, 5, 2, 9, 4, 8, 0, 5, 0, 5, 6, 7])\n",
      "107 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 2, 0, 3, 3, 1, 9, 4, 1, 6, 3, 5, 2, 6, 1, 7])\n",
      "108 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 2, 2, 9, 6, 8, 8, 6, 4, 8, 1, 6, 2, 3, 6])\n",
      "109 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 3, 0, 1, 9, 0, 7, 9, 1, 1, 7, 2, 7, 3, 8, 8])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "110 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 1, 3, 3, 9, 5, 1, 9, 1, 2, 6, 8, 3, 9, 6])\n",
      "111 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 3, 8, 4, 3, 2, 1, 2, 2, 2, 8, 1, 5, 3, 3, 9])\n",
      "112 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 4, 3, 6, 6, 3, 7, 8, 6, 6, 2, 8, 8, 5, 9])\n",
      "113 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 0, 4, 0, 6, 9, 6, 9, 2, 9, 0, 2, 7, 0, 2])\n",
      "114 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 4, 2, 8, 7, 9, 7, 5, 9, 6, 9, 9, 5, 0, 2])\n",
      "115 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 3, 1, 9, 5, 4, 1, 9, 4, 5, 7, 9, 6, 7, 1, 1])\n",
      "116 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 9, 9, 2, 4, 9, 2, 4, 8, 8, 8, 3, 8, 5, 2])\n",
      "117 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 7, 1, 0, 1, 3, 2, 5, 9, 7, 4, 2, 2, 2, 4, 9])\n",
      "118 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 1, 9, 0, 8, 8, 4, 0, 0, 7, 1, 2, 4, 3, 3])\n",
      "119 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 0, 3, 1, 3, 8, 0, 8, 5, 2, 1, 2, 0, 7, 9, 8])\n",
      "120 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 6, 9, 8, 8, 2, 5, 7, 7, 7, 3, 5, 2, 2, 3, 2])\n",
      "121 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 2, 3, 3, 3, 9, 1, 2, 1, 4, 9, 8, 8, 6, 1])\n",
      "122 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 0, 7, 2, 5, 6, 2, 5, 0, 8, 6, 2, 9, 0, 5])\n",
      "123 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 0, 0, 0, 8, 1, 4, 4, 1, 9, 4, 7, 3, 5, 1])\n",
      "124 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 5, 3, 0, 0, 4, 3, 6, 4, 3, 9, 7, 4, 2, 8, 2])\n",
      "125 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 1, 7, 2, 1, 9, 8, 7, 8, 5, 1, 8, 0, 9, 6, 0])\n",
      "126 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 0, 9, 3, 3, 9, 8, 3, 5, 7, 8, 3, 1, 0, 2])\n",
      "127 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 5, 3, 9, 8, 2, 7, 0, 8, 4, 2, 6, 4, 5, 9, 1])\n",
      "128 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 3, 0, 9, 4, 0, 5, 2, 3, 4, 6, 3, 6, 1, 3, 5])\n",
      "129 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 9, 2, 4, 9, 2, 4, 0, 9, 1, 4, 8, 6, 7, 4, 0])\n",
      "130 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 7, 7, 4, 5, 1, 3, 2, 0, 1, 0, 2, 6, 6, 8, 9])\n",
      "131 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 5, 7, 6, 6, 8, 0, 2, 5, 4, 3, 1, 0, 9, 4])\n",
      "132 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 0, 7, 9, 1, 4, 2, 3, 0, 1, 6, 4, 0, 7, 1, 1])\n",
      "133 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 6, 5, 7, 6, 6, 8, 2, 6, 8, 4, 5, 3, 5, 1])\n",
      "134 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 0, 0, 0, 2, 6, 8, 6, 8, 1, 9, 7, 5, 4, 7, 8])\n",
      "135 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 4, 2, 1, 9, 5, 3, 3, 2, 4, 4, 5, 6, 1, 0])\n",
      "136 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 8, 2, 4, 5, 4, 9, 1, 5, 4, 8, 3, 4, 0, 1])\n",
      "137 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 4, 8, 3, 0, 6, 7, 0, 4, 0, 7, 6, 4, 7, 0])\n",
      "138 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 5, 8, 1, 1, 5, 1, 0, 5, 7, 3, 3, 8, 0, 8, 6])\n",
      "139 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 7, 3, 3, 9, 8, 4, 0, 6, 1, 0, 4, 7, 6, 4])\n",
      "140 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 5, 4, 2, 1, 5, 9, 9, 8, 2, 7, 0, 1, 0, 2])\n",
      "141 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 7, 0, 8, 2, 0, 8, 3, 4, 2, 2, 3, 6, 0, 6])\n",
      "142 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 5, 8, 2, 1, 1, 3, 0, 4, 1, 9, 0, 5, 7, 4])\n",
      "143 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 0, 7, 4, 7, 3, 2, 2, 8, 9, 1, 4, 8, 3, 0])\n",
      "144 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 5, 9, 6, 8, 7, 7, 2, 8, 6, 7, 2, 1, 8, 6])\n",
      "145 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 8, 9, 4, 4, 0, 7, 4, 5, 3, 2, 8, 1, 2, 9, 8])\n",
      "146 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 0, 7, 4, 5, 3, 3, 9, 5, 4, 5, 6, 8, 3, 2, 7])\n",
      "147 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 9, 0, 5, 1, 4, 3, 1, 6, 8, 2, 0, 2, 0, 0])\n",
      "148 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 4, 8, 1, 8, 0, 4, 5, 8, 5, 7, 8, 2, 6, 8])\n",
      "149 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 0, 7, 5, 9, 6, 1, 3, 8, 7, 9, 2, 6, 8, 2, 0])\n",
      "150 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 0, 7, 2, 3, 7, 0, 5, 1, 0, 7, 1, 3, 6, 7, 9])\n",
      "151 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 0, 7, 0, 1, 6, 2, 3, 8, 6, 3, 7, 5, 5, 9])\n",
      "152 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 1, 4, 7, 8, 9, 4, 0, 7, 7, 9, 9, 7, 1, 3])\n",
      "153 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 9, 6, 0, 6, 9, 1, 2, 8, 4, 5, 7, 5, 6, 5, 0])\n",
      "154 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 9, 8, 1, 4, 4, 2, 1, 1, 3, 6, 8, 9, 4, 4, 9])\n",
      "155 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 9, 4, 3, 9, 7, 1, 6, 8, 4, 4, 3, 1, 4, 5, 1])\n",
      "156 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 5, 2, 5, 9, 9, 8, 6, 6, 1, 4, 9, 2, 1, 3, 3])\n",
      "157 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 0, 0, 7, 1, 4, 2, 5, 8, 8, 2, 7, 1, 0, 8, 8])\n",
      "158 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 7, 4, 5, 5, 8, 1, 4, 8, 4, 7, 1, 7, 7, 5, 3])\n",
      "159 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 2, 0, 3, 2, 5, 5, 5, 1, 9, 3, 0, 8, 6, 9])\n",
      "160 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 3, 6, 2, 9, 0, 0, 9, 9, 1, 7, 7, 3, 1, 6, 0])\n",
      "161 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 6, 2, 9, 4, 1, 5, 4, 7, 9, 7, 8, 7, 2, 2, 1])\n",
      "162 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 2, 6, 4, 4, 3, 0, 4, 4, 9, 6, 7, 1, 1, 8, 1])\n",
      "163 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 7, 5, 9, 2, 5, 8, 2, 5, 5, 3, 7, 8, 0, 1])\n",
      "164 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 2, 4, 4, 2, 7, 4, 9, 9, 2, 9, 1, 0, 5, 6, 4])\n",
      "165 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 6, 8, 8, 7, 3, 9, 5, 4, 5, 2, 9, 8, 8, 3, 9])\n",
      "166 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 8, 3, 3, 0, 9, 2, 6, 9, 3, 1, 9, 7, 6, 8, 8])\n",
      "167 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 5, 7, 0, 8, 5, 4, 4, 8, 7, 6, 8, 9, 7, 7, 5])\n",
      "168 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 8, 6, 1, 6, 1, 5, 8, 6, 8, 0, 1, 7, 5, 0, 4])\n",
      "169 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 6, 0, 3, 9, 6, 7, 3, 2, 4, 8, 4, 8, 9, 9])\n",
      "170 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 4, 9, 7, 7, 5, 2, 2, 7, 4, 6, 2, 5, 0, 9])\n",
      "171 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 9, 9, 1, 3, 5, 0, 0, 9, 0, 0, 6, 1, 5, 7, 5])\n",
      "172 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 2, 0, 0, 4, 3, 3, 8, 0, 4, 9, 4, 8, 7, 7, 1])\n",
      "173 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 0, 0, 5, 9, 2, 7, 5, 0, 6, 2, 6, 7, 6, 3])\n",
      "174 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 2, 0, 1, 6, 9, 4, 5, 3, 4, 6, 1, 7, 4, 6, 5])\n",
      "175 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 8, 2, 4, 0, 6, 6, 5, 4, 0, 5, 3, 5, 7, 9, 6])\n",
      "176 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 4, 5, 6, 9, 9, 0, 2, 5, 1, 3, 3, 4, 7, 6])\n",
      "177 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 9, 3, 9, 8, 2, 7, 3, 6, 0, 9, 2, 2, 8, 5])\n",
      "178 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 1, 2, 3, 5, 7, 6, 7, 5, 9, 7, 8, 0, 6, 9, 6])\n",
      "179 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 5, 3, 9, 2, 7, 4, 5, 8, 9, 2, 3, 3, 9, 5, 5])\n",
      "180 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 8, 2, 8, 7, 3, 9, 3, 9, 7, 7, 8, 5, 8, 4])\n",
      "181 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 4, 0, 6, 8, 5, 9, 9, 2, 8, 3, 7, 4, 7, 9])\n",
      "182 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 3, 1, 2, 9, 4, 4, 4, 4, 2, 9, 0, 8, 1, 6])\n",
      "183 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 5, 0, 6, 1, 5, 8, 1, 6, 3, 0, 9, 6, 6, 2])\n",
      "184 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 4, 6, 2, 7, 9, 3, 4, 2, 7, 1, 9, 5, 3, 7, 8])\n",
      "185 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 3, 1, 0, 2, 1, 3, 7, 7, 8, 8, 4, 2, 6, 6, 3])\n",
      "186 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 5, 2, 6, 6, 0, 4, 0, 9, 3, 0, 9, 3, 6, 6])\n",
      "187 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 7, 1, 4, 6, 2, 8, 1, 3, 1, 4, 1, 3, 2, 4, 8])\n",
      "188 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 8, 9, 8, 1, 0, 2, 7, 0, 3, 9, 7, 6, 9, 8, 0])\n",
      "189 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 5, 6, 3, 5, 6, 3, 9, 1, 2, 9, 2, 9, 6, 6])\n",
      "190 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 3, 2, 1, 6, 6, 8, 0, 3, 6, 3, 9, 7, 0, 9, 8])\n",
      "191 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 0, 1, 6, 0, 0, 0, 5, 2, 4, 6, 5, 6, 3, 3])\n",
      "192 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 0, 2, 8, 8, 7, 5, 6, 2, 0, 2, 9, 8, 6, 7, 8])\n",
      "193 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 5, 8, 1, 6, 2, 7, 7, 5, 9, 7, 9, 8, 5, 7])\n",
      "194 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 1, 2, 3, 9, 9, 9, 4, 4, 6, 4, 5, 1, 7, 1])\n",
      "195 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 6, 8, 8, 0, 4, 0, 3, 6, 7, 1, 0, 9, 7, 6, 6])\n",
      "196 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 0, 9, 4, 2, 7, 6, 7, 5, 9, 5, 0, 6, 3, 2])\n",
      "197 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 3, 6, 3, 3, 8, 0, 6, 8, 9, 4, 8, 1, 1, 8, 1])\n",
      "198 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 1, 8, 8, 0, 1, 6, 8, 6, 0, 5, 0, 4, 2, 2])\n",
      "199 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 3, 5, 9, 8, 4, 4, 4, 0, 3, 3, 8, 8, 4, 7])\n",
      "200 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 6, 4, 3, 3, 9, 0, 6, 5, 6, 0, 3, 2, 1, 5])\n",
      "201 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 0, 5, 8, 2, 4, 3, 8, 3, 6, 4, 3, 9, 8, 1])\n",
      "202 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 2, 4, 2, 3, 4, 6, 7, 1, 5, 2, 3, 5, 4, 0])\n",
      "203 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 1, 8, 0, 3, 6, 7, 5, 0, 5, 8, 3, 6, 7, 5])\n",
      "204 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 9, 4, 4, 9, 7, 3, 8, 5, 1, 6, 0, 6, 0, 1, 8])\n",
      "205 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 3, 0, 3, 0, 4, 1, 2, 4, 0, 2, 8, 9, 3, 8, 0])\n",
      "206 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 1, 5, 7, 8, 6, 3, 3, 3, 6, 8, 9, 9, 2, 2])\n",
      "207 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 2, 1, 8, 1, 0, 0, 7, 1, 2, 5, 7, 3, 0, 2, 9])\n",
      "208 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 2, 8, 9, 3, 7, 1, 3, 2, 7, 9, 7, 9, 4, 5, 3])\n",
      "209 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 5, 1, 4, 4, 8, 3, 5, 5, 7, 3, 7, 6, 6, 3])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "210 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 0, 2, 2, 7, 5, 1, 0, 8, 8, 6, 9, 1, 7, 1, 6])\n",
      "211 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 8, 9, 9, 8, 6, 5, 4, 8, 9, 1, 7, 6, 1, 9])\n",
      "212 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 3, 8, 8, 3, 0, 6, 2, 0, 2, 2, 7, 8, 9, 8])\n",
      "213 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 1, 5, 2, 4, 7, 7, 3, 4, 2, 8, 5, 3, 1, 6])\n",
      "214 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 8, 6, 9, 8, 9, 2, 8, 4, 7, 5, 5, 0, 3, 9])\n",
      "215 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 5, 1, 5, 9, 5, 9, 0, 8, 2, 0, 1, 2, 8, 9, 9])\n",
      "216 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 7, 3, 5, 7, 3, 2, 0, 3, 4, 9, 6, 2, 1, 9, 0])\n",
      "217 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 6, 5, 7, 4, 7, 1, 0, 5, 5, 1, 0, 2, 3, 6])\n",
      "218 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 7, 5, 0, 2, 4, 8, 1, 6, 0, 7, 7, 4, 2, 5])\n",
      "219 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 5, 9, 2, 2, 9, 8, 4, 6, 6, 6, 6, 5, 0, 5, 8])\n",
      "220 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 6, 5, 6, 7, 3, 0, 3, 3, 1, 4, 6, 8, 2, 9, 9])\n",
      "221 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 0, 5, 9, 5, 9, 9, 5, 8, 3, 5, 2, 7, 0, 0, 3])\n",
      "222 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 9, 3, 4, 3, 4, 0, 5, 2, 0, 7, 7, 2, 2, 6, 2])\n",
      "223 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 8, 6, 7, 5, 8, 0, 3, 8, 2, 9, 5, 7, 3, 5])\n",
      "224 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 5, 5, 4, 8, 9, 0, 5, 0, 5, 8, 5, 3, 4, 5])\n",
      "225 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 4, 5, 6, 9, 9, 7, 8, 7, 0, 2, 4, 1, 1, 4, 2])\n",
      "226 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 1, 0, 9, 7, 5, 9, 2, 6, 7, 5, 3, 9, 1, 1])\n",
      "227 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 7, 4, 9, 7, 6, 5, 7, 1, 5, 0, 5, 0, 9, 0])\n",
      "228 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 7, 1, 7, 1, 8, 5, 1, 0, 7, 9, 3, 2, 9, 3, 5])\n",
      "229 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 5, 3, 0, 6, 2, 8, 8, 0, 5, 5, 6, 7, 9, 1, 3])\n",
      "230 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 8, 7, 9, 3, 8, 0, 9, 3, 8, 4, 6, 5, 5, 2])\n",
      "231 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 8, 9, 6, 7, 9, 8, 6, 0, 0, 2, 2, 1, 3, 8, 0])\n",
      "232 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 1, 3, 6, 8, 3, 4, 0, 9, 5, 6, 3, 6, 6, 5, 8])\n",
      "233 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 9, 6, 1, 2, 0, 8, 5, 3, 4, 8, 0, 6, 4, 5])\n",
      "234 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 8, 6, 8, 9, 8, 4, 2, 9, 8, 3, 5, 1, 2, 7])\n",
      "235 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 1, 3, 7, 4, 8, 3, 4, 0, 3, 7, 0, 9, 1, 3, 7])\n",
      "236 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 7, 9, 6, 6, 8, 7, 4, 4, 7, 4, 5, 8, 3, 1])\n",
      "237 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 1, 1, 6, 1, 7, 0, 3, 2, 4, 1, 7, 7, 8, 7])\n",
      "238 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 4, 4, 9, 8, 5, 6, 7, 0, 6, 8, 8, 6, 7, 2, 4])\n",
      "239 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 1, 5, 0, 0, 7, 4, 4, 4, 2, 3, 5, 8, 4, 9, 6])\n",
      "240 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 1, 0, 8, 4, 2, 2, 5, 1, 7, 0, 7, 3, 9, 0, 4])\n",
      "241 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 4, 9, 5, 9, 9, 9, 0, 3, 3, 5, 3, 7, 4, 5])\n",
      "242 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 4, 5, 6, 3, 6, 6, 8, 7, 2, 3, 3, 8, 3, 5])\n",
      "243 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 3, 4, 2, 5, 8, 6, 0, 1, 4, 0, 5, 0, 3, 7, 4])\n",
      "244 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 6, 8, 7, 7, 0, 4, 8, 7, 1, 5, 4, 3, 1, 5])\n",
      "245 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 7, 6, 3, 8, 2, 1, 6, 8, 2, 6, 5, 0, 1, 8])\n",
      "246 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 3, 4, 7, 1, 6, 4, 4, 7, 4, 9, 4, 9, 6, 1])\n",
      "247 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 6, 5, 1, 0, 9, 9, 9, 7, 0, 4, 8, 7, 1, 3])\n",
      "248 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 8, 0, 0, 0, 2, 9, 3, 6, 4, 3, 8, 9, 3, 7, 1])\n",
      "249 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 6, 6, 4, 9, 8, 0, 9, 0, 7, 7, 3, 0, 1, 6])\n",
      "250 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 0, 0, 3, 2, 6, 2, 7, 3, 4, 7, 1, 0, 8, 5, 7])\n",
      "251 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 1, 8, 8, 4, 6, 4, 8, 0, 9, 0, 1, 5, 4, 4])\n",
      "252 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 1, 6, 5, 0, 3, 9, 2, 4, 2, 0, 1, 7, 7, 1])\n",
      "253 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 7, 0, 6, 0, 5, 3, 0, 8, 0, 6, 1, 0, 0, 8])\n",
      "254 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 2, 2, 9, 5, 3, 4, 0, 9, 5, 0, 4, 7, 2, 9])\n",
      "255 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 4, 0, 5, 0, 6, 8, 4, 8, 0, 7, 7, 8, 5, 7])\n",
      "256 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 7, 5, 8, 0, 2, 1, 8, 7, 7, 0, 6, 3, 5, 5, 0])\n",
      "257 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 9, 9, 0, 7, 3, 5, 6, 7, 9, 2, 5, 7, 7, 9, 3])\n",
      "258 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 1, 5, 8, 1, 2, 7, 3, 1, 1, 3, 4, 9, 5, 3])\n",
      "259 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 4, 3, 1, 8, 7, 2, 3, 4, 5, 9, 3, 2, 1, 7, 3])\n",
      "260 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 3, 1, 0, 6, 1, 2, 4, 9, 7, 7, 4, 0, 5, 4, 4])\n",
      "261 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 7, 2, 6, 4, 0, 0, 1, 0, 4, 0, 9, 4, 1, 2])\n",
      "262 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 9, 6, 8, 9, 2, 8, 7, 5, 6, 3, 3, 2, 0, 6])\n",
      "263 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 1, 8, 1, 2, 6, 2, 9, 3, 4, 6, 7, 6, 1, 4, 3])\n",
      "264 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 0, 7, 7, 2, 6, 2, 1, 7, 8, 7, 1, 8, 3, 4, 0])\n",
      "265 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 2, 8, 9, 1, 8, 5, 0, 8, 5, 5, 8, 7, 7, 9])\n",
      "266 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 3, 7, 6, 7, 3, 3, 1, 4, 0, 9, 4, 0, 4, 2, 3])\n",
      "267 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 0, 9, 6, 8, 6, 4, 3, 5, 7, 0, 0, 7, 7, 7, 9])\n",
      "268 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 7, 6, 0, 4, 7, 5, 9, 6, 9, 4, 9, 2, 7, 3])\n",
      "269 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 4, 7, 6, 4, 9, 0, 0, 4, 7, 4, 1, 5, 6, 2])\n",
      "270 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 0, 5, 9, 7, 5, 0, 0, 0, 9, 8, 9, 3, 7, 7, 9])\n",
      "271 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 1, 5, 9, 7, 1, 9, 7, 5, 8, 5, 4, 2, 3, 6])\n",
      "272 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 7, 0, 0, 5, 4, 2, 1, 6, 8, 3, 2, 6, 4, 7])\n",
      "273 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 1, 4, 0, 9, 2, 3, 3, 9, 5, 2, 3, 2, 4, 1, 9])\n",
      "274 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 5, 5, 0, 5, 1, 8, 2, 9, 2, 3, 4, 2, 1, 7])\n",
      "275 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 8, 0, 0, 9, 8, 4, 8, 6, 7, 7, 6, 6, 8, 5, 2])\n",
      "276 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 2, 6, 6, 4, 8, 3, 0, 1, 5, 5, 9, 7, 2, 8, 4])\n",
      "277 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 1, 7, 0, 9, 7, 5, 1, 1, 9, 7, 0, 1, 8, 0])\n",
      "278 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 1, 9, 0, 4, 0, 2, 7, 2, 0, 5, 1, 7, 1, 9, 1])\n",
      "279 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 2, 4, 1, 2, 2, 2, 2, 0, 7, 0, 2, 0, 4, 5, 6])\n",
      "280 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 8, 4, 9, 5, 0, 3, 0, 3, 9, 4, 4, 4, 5, 1])\n",
      "281 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 4, 1, 7, 4, 9, 5, 8, 6, 6, 8, 5, 7, 0, 5, 5])\n",
      "282 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 6, 1, 1, 8, 1, 4, 1, 4, 2, 1, 5, 5, 6, 5])\n",
      "283 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 6, 1, 2, 3, 3, 9, 9, 2, 9, 2, 8, 4, 1, 8])\n",
      "284 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 9, 0, 4, 8, 3, 5, 1, 6, 4, 6, 3, 4, 3, 1, 5])\n",
      "285 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 9, 0, 4, 3, 4, 2, 3, 7, 3, 6, 6, 3, 7, 5, 2])\n",
      "286 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 3, 3, 5, 2, 5, 6, 6, 9, 3, 0, 1, 6, 4, 8, 1])\n",
      "287 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 0, 1, 4, 3, 8, 7, 9, 3, 1, 0, 6, 6, 6, 1])\n",
      "288 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 4, 4, 3, 1, 8, 0, 2, 2, 5, 6, 5, 2, 8, 8, 5])\n",
      "289 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 1, 1, 1, 9, 2, 4, 6, 7, 0, 9, 6, 5, 1, 0])\n",
      "290 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 3, 1, 5, 7, 1, 2, 0, 0, 1, 1, 6, 6, 5, 3, 7])\n",
      "291 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 5, 4, 4, 5, 1, 0, 5, 2, 1, 3, 9, 7, 4, 7])\n",
      "292 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 0, 1, 7, 1, 2, 8, 5, 2, 7, 3, 6, 5, 5, 3, 4])\n",
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      "294 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 1, 2, 1, 4, 7, 4, 3, 7, 8, 3, 1, 1, 2, 3, 9])\n",
      "295 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 3, 8, 8, 6, 6, 0, 3, 2, 4, 4, 5, 8, 0, 6, 9])\n",
      "296 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 0, 3, 5, 0, 9, 8, 0, 8, 4, 2, 8, 3, 9, 2, 2])\n",
      "297 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 9, 0, 4, 3, 3, 4, 0, 9, 8, 8, 0, 0, 0, 2])\n",
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      "300 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 8, 6, 2, 7, 6, 6, 5, 6, 5, 7, 3, 1, 7, 3])\n",
      "301 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 5, 9, 9, 1, 0, 9, 1, 5, 2, 3, 8, 8, 2, 8])\n",
      "302 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 9, 0, 2, 4, 8, 6, 5, 3, 3, 2, 2, 8, 7, 8])\n",
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      "304 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 2, 1, 9, 8, 7, 1, 1, 4, 5, 6, 1, 0, 0, 2])\n",
      "305 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 7, 7, 1, 0, 1, 9, 9, 6, 0, 4, 8, 3, 0, 2])\n",
      "306 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 7, 0, 2, 5, 2, 6, 3, 6, 0, 0, 4, 9, 5, 8, 0])\n",
      "307 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 8, 4, 5, 9, 0, 5, 0, 6, 2, 2, 5, 9, 0, 4, 2])\n",
      "308 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 8, 1, 5, 3, 4, 5, 3, 3, 6, 7, 0, 1, 3, 9])\n",
      "309 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 1, 1, 7, 7, 8, 3, 7, 2, 6, 6, 4, 9, 3, 5, 4])\n",
      "310 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 0, 3, 0, 1, 1, 9, 7, 5, 8, 6, 8, 3, 4, 2])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "311 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 6, 1, 0, 5, 5, 8, 5, 4, 4, 5, 5, 3, 2, 4, 5])\n",
      "312 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 7, 7, 3, 3, 0, 2, 2, 7, 3, 2, 4, 4, 3, 0])\n",
      "313 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 3, 3, 4, 8, 8, 5, 7, 0, 7, 2, 9, 4, 1, 9, 8])\n",
      "314 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 2, 5, 3, 2, 6, 9, 3, 9, 2, 0, 3, 9, 1, 8, 1])\n",
      "315 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 6, 1, 7, 3, 7, 9, 3, 4, 6, 1, 3, 3, 0, 8, 1])\n",
      "316 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 4, 9, 1, 6, 1, 8, 1, 3, 8, 7, 1, 5, 2, 1])\n",
      "317 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 3, 3, 6, 4, 5, 3, 0, 0, 1, 1, 8, 1, 0, 2])\n",
      "318 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 6, 6, 5, 2, 9, 8, 2, 6, 5, 5, 6, 6, 7, 6])\n",
      "319 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 3, 3, 1, 7, 6, 3, 9, 8, 5, 1, 5, 6, 5, 6])\n",
      "320 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 0, 8, 5, 8, 1, 0, 3, 1, 1, 7, 4, 9, 1, 2])\n",
      "321 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 2, 6, 6, 9, 8, 2, 3, 2, 6, 7, 3, 2, 6, 5])\n",
      "322 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 8, 9, 6, 8, 4, 1, 6, 6, 0, 7, 7, 3, 7, 9])\n",
      "323 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 3, 2, 3, 7, 4, 8, 7, 8, 8, 2, 4, 4, 3, 5, 1])\n",
      "324 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 5, 2, 7, 8, 9, 6, 3, 7, 1, 8, 2, 8, 9, 3, 1])\n",
      "325 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 0, 0, 4, 4, 8, 6, 4, 8, 3, 2, 8, 6, 2, 9, 1])\n",
      "326 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 8, 3, 2, 1, 7, 0, 0, 7, 5, 6, 5, 5, 9, 4, 3])\n",
      "327 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 4, 2, 7, 0, 8, 2, 3, 6, 7, 1, 9, 2, 0, 3, 8])\n",
      "328 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 9, 8, 0, 2, 9, 0, 7, 2, 4, 7, 2, 9, 1, 7])\n",
      "329 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 5, 1, 2, 3, 1, 7, 9, 9, 4, 7, 7, 9, 9, 7])\n",
      "330 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 3, 1, 8, 6, 2, 5, 7, 2, 6, 6, 4, 2, 5, 5, 3])\n",
      "331 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 6, 4, 2, 0, 0, 2, 0, 6, 4, 2, 4, 7, 0, 7])\n",
      "332 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 0, 5, 7, 5, 0, 2, 7, 5, 6, 7, 4, 0, 7, 8])\n",
      "333 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 3, 5, 7, 0, 0, 3, 6, 8, 1, 9, 7, 6, 4, 0, 7])\n",
      "334 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 7, 0, 7, 7, 5, 8, 9, 9, 2, 6, 3, 4, 8, 2, 3])\n",
      "335 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 3, 2, 2, 6, 2, 3, 6, 8, 8, 5, 1, 5, 8, 5, 6])\n",
      "336 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 3, 8, 6, 6, 4, 2, 3, 0, 8, 4, 4, 5, 5, 3])\n",
      "337 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 2, 6, 4, 4, 1, 1, 4, 9, 0, 8, 3, 5, 3, 1])\n",
      "338 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 6, 8, 7, 5, 1, 1, 7, 9, 9, 2, 1, 9, 6, 0, 6])\n",
      "339 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 1, 9, 1, 7, 6, 1, 3, 0, 2, 4, 9, 1, 1, 2, 2])\n",
      "340 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 9, 5, 2, 5, 5, 9, 2, 3, 0, 9, 2, 0, 7, 6])\n",
      "341 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 7, 8, 2, 0, 9, 6, 2, 5, 3, 3, 2, 1, 1, 8])\n",
      "342 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 3, 7, 8, 6, 0, 9, 5, 8, 6, 1, 7, 4, 2, 2])\n",
      "343 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 4, 3, 4, 6, 3, 0, 2, 7, 3, 2, 1, 2, 0, 0])\n",
      "344 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 6, 3, 9, 1, 5, 1, 0, 0, 9, 0, 9, 7, 9, 1, 6])\n",
      "345 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 4, 4, 8, 9, 4, 6, 5, 9, 7, 1, 0, 6, 3, 2, 7])\n",
      "346 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 4, 7, 8, 0, 4, 2, 2, 6, 7, 3, 5, 3, 2, 1])\n",
      "347 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 1, 9, 2, 2, 0, 0, 2, 2, 2, 1, 7, 3, 6, 5])\n",
      "348 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 4, 8, 1, 1, 9, 4, 8, 2, 6, 2, 0, 2, 7, 6, 6])\n",
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      "353 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 4, 9, 7, 0, 4, 8, 6, 7, 5, 5, 5, 1, 9, 7, 3])\n",
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      "358 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 4, 4, 3, 3, 1, 7, 0, 9, 1, 7, 8, 9, 7, 9, 6])\n",
      "359 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 3, 7, 9, 9, 5, 2, 3, 6, 1, 1, 8, 9, 6, 2])\n",
      "360 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 3, 7, 9, 9, 7, 7, 4, 6, 0, 6, 1, 7, 0, 7, 7])\n",
      "361 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 2, 5, 3, 1, 1, 8, 3, 7, 0, 5, 5, 2, 2, 5])\n",
      "362 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 9, 7, 3, 2, 5, 6, 1, 0, 0, 6, 5, 2, 9, 4, 0])\n",
      "363 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 9, 4, 9, 8, 1, 1, 9, 1, 3, 2, 7, 0, 2, 2])\n",
      "364 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 3, 0, 0, 2, 2, 6, 6, 5, 6, 3, 3, 2, 5, 1, 9])\n",
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      "367 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 5, 8, 9, 9, 6, 3, 4, 9, 7, 3, 8, 1, 4, 7])\n",
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      "371 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 5, 7, 7, 0, 8, 9, 2, 8, 7, 6, 5, 0, 4, 9])\n",
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      "380 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 0, 5, 2, 7, 7, 1, 3, 8, 3, 3, 5, 4, 3, 1, 4])\n",
      "381 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 5, 1, 7, 0, 8, 1, 3, 8, 6, 5, 0, 0, 1, 0])\n",
      "382 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 6, 2, 0, 1, 5, 1, 2, 4, 7, 5, 4, 5, 6, 9, 0])\n",
      "383 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 1, 8, 0, 4, 6, 3, 2, 5, 7, 7, 2, 4, 4, 9, 8])\n",
      "384 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 1, 3, 4, 0, 1, 2, 5, 6, 3, 5, 6, 0, 9, 2])\n",
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      "387 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 1, 6, 7, 8, 3, 1, 5, 2, 4, 3, 1, 9, 2, 2, 3])\n",
      "388 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 1, 3, 2, 6, 8, 7, 0, 8, 3, 1, 0, 2, 4, 1])\n",
      "389 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 5, 8, 9, 6, 6, 6, 7, 0, 3, 9, 8, 5, 4, 6, 5])\n",
      "390 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 0, 9, 4, 0, 0, 7, 9, 1, 5, 6, 5, 2, 2, 9])\n",
      "391 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 8, 0, 9, 0, 9, 4, 3, 2, 6, 0, 4, 1, 9, 4, 0])\n",
      "392 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 7, 6, 2, 4, 9, 0, 8, 7, 0, 6, 7, 6, 5, 1])\n",
      "393 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 4, 6, 1, 9, 1, 8, 2, 4, 3, 7, 9, 3, 8, 2])\n",
      "394 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 2, 8, 2, 4, 9, 9, 5, 4, 0, 5, 2, 7, 7, 0, 4])\n",
      "395 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 1, 4, 0, 4, 5, 6, 7, 5, 4, 6, 1, 0, 5, 8])\n",
      "396 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 5, 6, 1, 4, 8, 1, 9, 3, 6, 1, 1, 7, 6, 2])\n",
      "397 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 4, 7, 8, 9, 5, 0, 3, 7, 2, 2, 7, 5, 5, 3])\n",
      "398 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 8, 3, 5, 2, 0, 1, 4, 0, 5, 0, 4, 5, 8, 6])\n",
      "399 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 9, 6, 0, 5, 6, 4, 1, 4, 8, 4, 9, 2, 6, 3])\n",
      "400 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 8, 1, 5, 4, 1, 9, 0, 6, 9, 8, 7, 0, 7, 4, 4])\n",
      "401 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 9, 9, 1, 7, 7, 9, 3, 7, 4, 1, 2, 9, 4, 3])\n",
      "402 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 0, 7, 1, 4, 8, 1, 0, 0, 6, 1, 3, 3, 8, 6, 7])\n",
      "403 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 0, 7, 4, 5, 4, 1, 0, 9, 5, 8, 1, 8, 1, 1])\n",
      "404 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 6, 4, 4, 5, 9, 5, 8, 6, 6, 6, 4, 1, 1, 9])\n",
      "405 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 0, 6, 6, 1, 8, 1, 0, 7, 4, 0, 0, 6, 2, 3, 3])\n",
      "406 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 1, 1, 6, 4, 2, 7, 1, 3, 0, 7, 7, 1, 9, 6, 3])\n",
      "407 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 3, 4, 7, 1, 8, 0, 2, 9, 2, 4, 9, 5, 1, 5, 4])\n",
      "408 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 3, 2, 7, 2, 5, 8, 7, 5, 2, 4, 9, 4, 6, 3, 0])\n",
      "409 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 2, 6, 1, 9, 5, 2, 2, 8, 9, 0, 6, 4, 0, 1])\n",
      "410 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 0, 1, 7, 2, 4, 5, 9, 3, 5, 6, 4, 8, 9, 8, 0])\n",
      "411 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 2, 0, 4, 1, 3, 8, 6, 4, 1, 4, 7, 4, 9, 0, 3])\n",
      "412 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 5, 6, 2, 3, 3, 4, 0, 2, 5, 9, 5, 6, 9, 8])\n",
      "413 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 0, 7, 9, 7, 0, 6, 0, 8, 8, 5, 7, 5, 4, 2])\n",
      "414 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 9, 9, 8, 5, 4, 0, 3, 9, 4, 0, 2, 9, 4, 6])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "415 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 0, 0, 2, 5, 6, 5, 9, 6, 4, 3, 4, 2, 6, 5, 2])\n",
      "416 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 5, 3, 6, 8, 9, 8, 7, 4, 7, 5, 2, 2, 7, 8])\n",
      "417 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 0, 1, 0, 3, 1, 9, 1, 6, 2, 6, 2, 8, 2, 7])\n",
      "418 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 1, 9, 7, 9, 0, 3, 7, 4, 2, 1, 4, 6, 6, 0])\n",
      "419 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 0, 9, 8, 4, 1, 5, 6, 6, 4, 5, 6, 6, 8, 4])\n",
      "420 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 3, 8, 5, 5, 9, 5, 0, 7, 4, 5, 1, 4, 6, 3])\n",
      "421 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 2, 2, 3, 2, 4, 1, 6, 2, 6, 8, 9, 2, 2, 2])\n",
      "422 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 1, 9, 3, 5, 7, 6, 7, 7, 5, 8, 2, 7, 2, 9])\n",
      "423 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 9, 8, 3, 1, 4, 8, 6, 1, 7, 1, 5, 3, 5, 8])\n",
      "424 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 3, 0, 7, 7, 2, 0, 3, 8, 9, 9, 0, 8, 5, 7, 4])\n",
      "425 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 9, 2, 2, 2, 0, 3, 4, 6, 1, 8, 6, 2, 7, 8, 2])\n",
      "426 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 1, 7, 4, 4, 8, 0, 2, 8, 8, 1, 3, 6, 2, 3, 3])\n",
      "427 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 8, 9, 5, 0, 2, 2, 0, 6, 6, 1, 7, 3, 5, 7, 0])\n",
      "428 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 8, 3, 0, 0, 6, 4, 6, 7, 2, 7, 4, 1, 6, 2, 7])\n",
      "429 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 2, 9, 2, 1, 1, 1, 4, 2, 0, 8, 3, 7, 8, 6, 5])\n",
      "430 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 1, 6, 9, 1, 9, 6, 4, 3, 9, 8, 2, 4, 0, 3])\n",
      "431 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 1, 2, 3, 5, 5, 1, 4, 0, 9, 7, 3, 2, 7, 4, 0])\n",
      "432 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 3, 1, 5, 2, 1, 9, 0, 6, 7, 1, 1, 1, 0, 7, 8])\n",
      "433 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 6, 8, 6, 9, 1, 0, 8, 0, 4, 5, 6, 8, 1, 9])\n",
      "434 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 1, 5, 8, 5, 5, 5, 3, 1, 3, 0, 1, 4, 4, 6])\n",
      "435 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 3, 0, 1, 2, 0, 0, 1, 6, 5, 8, 7, 5, 8, 6])\n",
      "436 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 0, 2, 3, 9, 3, 0, 6, 4, 1, 1, 1, 8, 2, 1, 6])\n",
      "437 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 4, 9, 1, 9, 9, 9, 1, 8, 9, 3, 5, 6, 2, 0])\n",
      "438 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 3, 5, 6, 1, 6, 8, 6, 4, 6, 6, 5, 8, 0, 0])\n",
      "439 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 1, 1, 6, 5, 5, 8, 3, 7, 3, 2, 7, 8, 4, 0, 3])\n",
      "440 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 8, 6, 6, 4, 9, 3, 8, 8, 7, 8, 1, 7, 6, 7, 8])\n",
      "441 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 7, 1, 9, 0, 3, 2, 9, 0, 3, 8, 8, 3, 7, 8, 0])\n",
      "442 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 7, 9, 3, 8, 2, 4, 3, 7, 9, 9, 9, 2, 4, 8, 8])\n",
      "443 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 8, 6, 9, 3, 0, 7, 1, 0, 3, 5, 9, 7, 2, 5])\n",
      "444 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 6, 7, 8, 9, 8, 5, 0, 5, 6, 3, 6, 9, 8, 5, 0])\n",
      "445 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 7, 3, 4, 8, 9, 7, 1, 9, 9, 7, 7, 0, 4, 5])\n",
      "446 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 2, 6, 6, 7, 1, 0, 7, 6, 1, 1, 3, 0, 4, 4])\n",
      "447 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 9, 8, 5, 2, 4, 4, 9, 9, 4, 6, 0, 3, 0, 0, 6])\n",
      "448 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 5, 7, 2, 6, 9, 5, 6, 8, 7, 7, 7, 4, 5, 1])\n",
      "449 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 5, 8, 1, 8, 9, 5, 6, 2, 6, 7, 6, 2, 1, 3])\n",
      "450 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 9, 2, 9, 2, 1, 6, 4, 9, 9, 3, 2, 6, 4, 1])\n",
      "451 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 4, 2, 2, 6, 0, 1, 4, 2, 4, 4, 3, 3, 0, 6])\n",
      "452 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 7, 8, 7, 7, 7, 3, 2, 5, 1, 8, 6, 3, 4, 5, 8])\n",
      "453 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 8, 7, 6, 7, 9, 3, 1, 4, 2, 8, 1, 4, 6, 6, 3])\n",
      "454 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 6, 9, 5, 0, 0, 2, 8, 3, 3, 8, 7, 3, 1, 3])\n",
      "455 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 2, 1, 5, 7, 9, 8, 8, 9, 1, 4, 4, 0, 0, 0])\n",
      "456 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 0, 0, 6, 0, 3, 1, 2, 5, 2, 7, 3, 7, 8, 0])\n",
      "457 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 8, 9, 7, 8, 3, 8, 1, 5, 5, 6, 1, 9, 5, 3])\n",
      "458 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 1, 9, 9, 8, 2, 4, 2, 1, 0, 7, 9, 3, 9, 5, 3])\n",
      "459 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 6, 3, 6, 4, 5, 4, 4, 7, 3, 1, 1, 6, 8, 6])\n",
      "460 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 4, 7, 9, 1, 9, 3, 9, 7, 9, 3, 2, 1, 0, 7])\n",
      "461 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 4, 2, 1, 5, 7, 9, 2, 3, 3, 8, 8, 0, 0, 6])\n",
      "462 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 7, 5, 5, 9, 4, 3, 5, 2, 6, 0, 4, 9, 4, 2, 3])\n",
      "463 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 4, 6, 5, 4, 2, 5, 1, 4, 3, 5, 0, 2, 6, 4])\n",
      "464 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 7, 6, 1, 6, 8, 2, 1, 3, 4, 2, 7, 8, 9, 6, 8])\n",
      "465 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 0, 3, 5, 7, 6, 4, 6, 3, 2, 7, 3, 9, 0, 1])\n",
      "466 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 7, 8, 3, 4, 9, 3, 0, 8, 6, 7, 4, 8, 2, 4, 8])\n",
      "467 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 0, 9, 9, 7, 5, 1, 4, 5, 9, 4, 2, 0, 5, 3, 0])\n",
      "468 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 7, 3, 0, 1, 5, 4, 2, 9, 6, 6, 9, 0, 5, 5])\n",
      "469 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 3, 8, 2, 4, 6, 4, 6, 6, 8, 3, 4, 1, 8, 5, 2])\n",
      "470 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 6, 1, 5, 4, 4, 4, 3, 1, 5, 9, 2, 6, 9, 7, 5])\n",
      "471 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 3, 0, 1, 7, 7, 6, 7, 5, 3, 1, 9, 2, 6, 5])\n",
      "472 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 1, 3, 6, 0, 7, 9, 8, 3, 4, 7, 3, 9, 5, 7, 8])\n",
      "473 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 4, 8, 5, 7, 3, 9, 2, 1, 0, 0, 4, 0, 3, 6, 7])\n",
      "474 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 7, 4, 7, 0, 3, 8, 1, 5, 4, 4, 4, 7, 1, 1, 4])\n",
      "475 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 4, 6, 8, 3, 8, 6, 6, 8, 9, 5, 3, 5, 3, 2])\n",
      "476 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 7, 9, 5, 7, 5, 6, 7, 0, 8, 3, 9, 6, 3, 4])\n",
      "477 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 7, 1, 0, 0, 0, 9, 4, 3, 9, 2, 1, 1, 2, 9])\n",
      "478 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 9, 5, 5, 8, 2, 9, 5, 1, 7, 7, 9, 3, 0, 5, 6])\n",
      "479 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 3, 6, 1, 3, 4, 5, 5, 3, 3, 4, 7, 8, 6, 3])\n",
      "480 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 8, 3, 0, 1, 3, 3, 4, 4, 7, 6, 8, 1, 5, 8])\n",
      "481 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 6, 4, 6, 0, 1, 2, 7, 0, 3, 8, 4, 1, 0, 4])\n",
      "482 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 1, 2, 4, 2, 6, 9, 1, 4, 4, 5, 9, 4, 0, 3, 0])\n",
      "483 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 3, 7, 8, 4, 2, 6, 5, 0, 0, 2, 7, 7, 5, 0, 4])\n",
      "484 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 9, 1, 0, 9, 0, 8, 9, 1, 4, 2, 6, 9, 1, 2, 5])\n",
      "485 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 1, 2, 7, 1, 9, 9, 2, 1, 3, 4, 9, 2, 0, 3])\n",
      "486 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 2, 8, 5, 7, 7, 1, 4, 6, 3, 2, 4, 4, 6, 8, 9])\n",
      "487 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 3, 6, 9, 4, 7, 9, 4, 8, 8, 2, 0, 2, 2, 8])\n",
      "488 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 4, 7, 9, 1, 0, 5, 1, 3, 5, 0, 3, 4, 9, 8])\n",
      "489 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 0, 8, 7, 1, 5, 3, 5, 7, 2, 4, 3, 5, 7, 6, 6])\n",
      "490 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 1, 9, 1, 7, 3, 9, 1, 9, 8, 2, 1, 7, 1, 7])\n",
      "491 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 4, 7, 6, 1, 3, 1, 3, 3, 6, 5, 4, 9, 3, 4, 9])\n",
      "492 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 7, 3, 6, 4, 5, 8, 8, 5, 4, 4, 1, 0, 3, 3])\n",
      "493 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 6, 6, 4, 1, 2, 4, 5, 4, 5, 7, 1, 5, 0, 3])\n",
      "494 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 5, 9, 9, 8, 5, 4, 2, 5, 4, 6, 7, 1, 0, 4])\n",
      "495 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 2, 1, 7, 2, 6, 9, 8, 4, 9, 8, 3, 1, 1, 1, 1])\n",
      "496 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 6, 9, 5, 1, 1, 7, 4, 9, 6, 4, 4, 9, 0, 3])\n",
      "497 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 9, 6, 2, 5, 9, 8, 0, 9, 5, 0, 5, 0, 5, 4])\n",
      "498 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 8, 0, 6, 7, 2, 4, 9, 6, 3, 5, 6, 1, 9, 8])\n",
      "499 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 2, 7, 2, 5, 5, 7, 7, 2, 8, 7, 3, 0, 2, 0])\n",
      "500 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 9, 4, 5, 3, 7, 9, 8, 2, 0, 5, 5, 7, 9, 3, 3])\n",
      "501 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 8, 5, 1, 2, 1, 6, 7, 8, 6, 6, 0, 5, 0, 4])\n",
      "502 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 2, 5, 7, 4, 4, 3, 1, 2, 1, 3, 6, 5, 0, 2, 2])\n",
      "503 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 3, 1, 3, 6, 3, 5, 5, 2, 5, 2, 2, 3, 6, 0])\n",
      "504 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 9, 9, 3, 3, 7, 7, 7, 8, 8, 6, 6, 2, 4, 1])\n",
      "505 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 5, 2, 1, 9, 8, 1, 6, 4, 3, 6, 5, 4, 5, 1, 2])\n",
      "506 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 6, 8, 9, 8, 6, 0, 7, 0, 2, 1, 4, 7, 9, 8, 6])\n",
      "507 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 2, 2, 5, 9, 3, 7, 0, 9, 3, 4, 1, 4, 0, 0, 3])\n",
      "508 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 0, 5, 1, 6, 5, 6, 4, 0, 2, 2, 7, 5, 3, 9])\n",
      "509 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 1, 8, 1, 2, 9, 5, 1, 6, 7, 2, 9, 5, 9, 0, 5])\n",
      "510 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 7, 4, 6, 5, 0, 4, 1, 5, 3, 7, 1, 7, 5, 4, 4])\n",
      "511 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 2, 8, 9, 2, 7, 0, 0, 0, 0, 7, 0, 9, 1, 2, 9])\n",
      "512 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 2, 7, 2, 1, 1, 4, 2, 7, 7, 4, 2, 3, 5, 2, 0])\n",
      "513 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 8, 8, 4, 4, 1, 5, 9, 6, 1, 5, 5, 6, 8, 5])\n",
      "514 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 6, 0, 8, 8, 2, 8, 7, 0, 9, 9, 8, 4, 0, 9, 8])\n",
      "515 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 0, 9, 6, 8, 5, 9, 5, 9, 6, 6, 0, 3, 1, 3, 0])\n",
      "516 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 8, 3, 4, 7, 6, 9, 1, 7, 5, 3, 2, 7, 9, 4, 7])\n",
      "517 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 1, 5, 6, 9, 0, 2, 3, 6, 8, 8, 4, 8, 6, 3, 7])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "518 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 8, 1, 4, 8, 5, 5, 1, 3, 4, 0, 5, 4, 8, 3])\n",
      "519 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 8, 7, 1, 7, 3, 9, 8, 7, 6, 8, 8, 6, 7, 1, 1])\n",
      "520 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 7, 7, 3, 0, 8, 8, 8, 6, 1, 5, 8, 8, 7, 3])\n",
      "521 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 2, 3, 7, 8, 8, 3, 9, 0, 6, 1, 1, 6, 0, 2])\n",
      "522 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 7, 7, 3, 8, 2, 2, 9, 1, 7, 3, 0, 8, 8, 4])\n",
      "523 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 1, 3, 0, 2, 9, 8, 3, 4, 0, 4, 8, 1, 1, 7])\n",
      "524 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 1, 6, 3, 1, 1, 5, 9, 8, 2, 5, 3, 3, 9, 3, 2])\n",
      "525 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 7, 4, 3, 3, 1, 1, 3, 7, 4, 5, 7, 6, 4, 7, 8])\n",
      "526 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 1, 0, 9, 6, 7, 6, 4, 8, 1, 8, 0, 9, 2, 2, 3])\n",
      "527 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 9, 7, 2, 5, 2, 4, 9, 6, 4, 7, 7, 0, 0, 0])\n",
      "528 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 1, 9, 5, 4, 2, 1, 6, 4, 9, 2, 9, 2, 6, 5])\n",
      "529 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 2, 1, 4, 6, 8, 7, 5, 3, 5, 2, 8, 3, 3, 5, 2])\n",
      "530 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 8, 3, 4, 1, 8, 8, 3, 5, 7, 2, 1, 4, 0, 6])\n",
      "531 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 8, 2, 0, 8, 9, 9, 0, 1, 7, 7, 4, 6, 2, 9, 4])\n",
      "532 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 0, 8, 9, 5, 5, 4, 6, 5, 8, 3, 2, 1, 6, 9, 2])\n",
      "533 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 7, 4, 4, 5, 2, 5, 9, 7, 9, 9, 2, 7, 8, 6])\n",
      "534 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 4, 3, 2, 1, 4, 1, 1, 9, 6, 7, 7, 5, 9, 7, 2])\n",
      "535 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 8, 8, 6, 0, 5, 4, 6, 9, 0, 7, 0, 3, 6, 7, 3])\n",
      "536 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 6, 4, 3, 1, 8, 0, 1, 9, 6, 4, 0, 3, 3, 9, 9])\n",
      "537 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 2, 5, 8, 8, 0, 2, 0, 1, 2, 8, 4, 4, 0, 1, 5])\n",
      "538 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 3, 1, 5, 4, 3, 4, 0, 4, 7, 4, 6, 7, 7, 4, 0])\n",
      "539 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 3, 0, 0, 8, 5, 4, 6, 4, 5, 0, 4, 1, 4, 3])\n",
      "540 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 7, 6, 5, 6, 1, 7, 9, 3, 4, 2, 5, 6, 9, 3, 5])\n",
      "541 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 1, 2, 8, 3, 2, 2, 2, 1, 1, 1, 9, 8, 0, 4, 2])\n",
      "542 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 4, 2, 5, 0, 9, 5, 1, 9, 8, 4, 9, 3, 8, 4])\n",
      "543 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 6, 4, 7, 6, 2, 5, 9, 2, 2, 8, 5, 4, 6, 7, 2])\n",
      "544 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 0, 5, 9, 5, 0, 2, 7, 4, 4, 2, 1, 6, 7, 9, 0])\n",
      "545 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 4, 0, 5, 6, 2, 6, 8, 0, 9, 9, 4, 6, 3, 3, 6])\n",
      "546 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 2, 1, 6, 3, 6, 7, 7, 7, 2, 5, 5, 0, 0, 4])\n",
      "547 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 6, 0, 6, 2, 3, 4, 3, 6, 8, 9, 2, 0, 9, 5, 8])\n",
      "548 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 8, 5, 6, 7, 7, 8, 8, 4, 2, 4, 3, 3, 8, 0])\n",
      "549 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 1, 3, 0, 7, 8, 2, 5, 4, 3, 1, 4, 0, 6, 2, 3])\n",
      "550 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 7, 4, 8, 2, 7, 7, 8, 4, 0, 4, 9, 0, 7, 7, 2])\n",
      "551 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 8, 9, 1, 7, 6, 6, 7, 4, 7, 1, 9, 9, 6, 8, 4])\n",
      "552 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 4, 7, 1, 2, 2, 1, 8, 4, 8, 4, 1, 7, 7, 7])\n",
      "553 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 6, 2, 1, 4, 7, 0, 4, 7, 0, 5, 8, 6, 2, 9])\n",
      "554 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 8, 9, 0, 4, 0, 3, 7, 6, 3, 4, 5, 3, 7, 6, 1])\n",
      "555 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 6, 1, 2, 6, 2, 8, 2, 7, 6, 9, 9, 5, 0, 9])\n",
      "556 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 8, 7, 7, 1, 3, 2, 5, 9, 3, 6, 0, 6, 0, 9, 6])\n",
      "557 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 4, 3, 7, 8, 4, 0, 9, 4, 9, 7, 3, 1, 6, 6, 2])\n",
      "558 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 0, 0, 7, 8, 5, 1, 9, 8, 1, 3, 7, 5, 4, 0])\n",
      "559 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 0, 9, 1, 1, 4, 0, 1, 4, 0, 4, 5, 8, 5, 9, 4])\n",
      "560 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 5, 6, 0, 1, 3, 5, 2, 3, 0, 0, 8, 3, 7, 6, 5])\n",
      "561 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 2, 2, 2, 1, 3, 8, 3, 8, 3, 2, 6, 9, 0, 8, 8])\n",
      "562 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 5, 8, 4, 7, 2, 1, 6, 9, 8, 0, 1, 6, 2, 9, 7])\n",
      "563 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 9, 5, 6, 5, 6, 7, 7, 6, 3, 6, 2, 9, 4, 1, 8])\n",
      "564 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 6, 2, 9, 7, 6, 9, 0, 4, 4, 6, 7, 7, 1, 8, 3])\n",
      "565 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 8, 9, 2, 4, 4, 2, 5, 9, 4, 6, 4, 6, 4, 9, 5])\n",
      "566 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 8, 2, 9, 8, 3, 6, 8, 8, 3, 5, 9, 2, 3, 8, 5])\n",
      "567 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 8, 6, 9, 4, 9, 4, 2, 3, 8, 9, 7, 7, 6, 6, 7])\n",
      "568 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 4, 8, 0, 5, 7, 6, 0, 3, 7, 0, 2, 7, 0, 8, 2])\n",
      "569 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 8, 1, 8, 8, 7, 4, 8, 8, 6, 9, 7, 0, 5, 6, 5])\n",
      "570 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 3, 3, 8, 7, 3, 7, 8, 7, 2, 9, 9, 6, 8, 6, 8])\n",
      "571 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 6, 3, 3, 3, 9, 0, 5, 4, 3, 7, 1, 5, 0, 7, 5])\n",
      "572 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 9, 9, 2, 4, 7, 7, 6, 2, 6, 1, 6, 9, 8, 7, 8])\n",
      "573 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 5, 4, 6, 8, 7, 5, 5, 2, 3, 7, 2, 9, 3, 8])\n",
      "574 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 4, 5, 6, 8, 5, 5, 8, 4, 5, 9, 1, 4, 9, 5, 3])\n",
      "575 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 3, 9, 3, 3, 8, 6, 3, 4, 2, 2, 1, 6, 5, 0, 1])\n",
      "576 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 0, 6, 9, 6, 9, 4, 6, 3, 0, 3, 0, 7, 4, 8, 3])\n",
      "577 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 9, 5, 1, 6, 1, 8, 5, 8, 3, 3, 2, 1, 7, 6, 5])\n",
      "578 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 4, 7, 5, 0, 7, 4, 4, 1, 7, 0, 9, 4, 8, 2, 9])\n",
      "579 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 5, 8, 0, 5, 3, 0, 4, 7, 7, 8, 7, 7, 1, 2])\n",
      "580 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 4, 7, 6, 8, 9, 0, 0, 7, 6, 8, 9, 7, 3, 5, 1])\n",
      "581 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 9, 3, 3, 6, 9, 3, 3, 1, 8, 4, 9, 4, 4, 6, 6])\n",
      "582 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 8, 1, 1, 3, 0, 4, 1, 6, 9, 2, 1, 6, 9, 7])\n",
      "583 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 2, 4, 8, 8, 5, 6, 3, 1, 4, 0, 1, 6, 2, 0, 0])\n",
      "584 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 5, 2, 7, 0, 0, 3, 8, 9, 0, 5, 4, 1, 6, 1, 4])\n",
      "585 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 5, 0, 1, 2, 4, 3, 9, 7, 1, 3, 7, 8, 9, 2, 3])\n",
      "586 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 1, 0, 6, 6, 4, 2, 9, 0, 8, 1, 6, 6, 4, 1, 0])\n",
      "587 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 0, 3, 4, 0, 9, 2, 6, 0, 1, 0, 1, 2, 2, 2, 7])\n",
      "588 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 4, 8, 5, 2, 3, 1, 6, 8, 6, 7, 2, 7, 4, 5, 9])\n",
      "589 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 8, 3, 8, 0, 3, 8, 4, 3, 3, 9, 6, 9, 5, 2, 6])\n",
      "590 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 4, 0, 1, 1, 6, 9, 4, 6, 8, 6, 4, 4, 4, 0, 9])\n",
      "591 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 6, 0, 9, 7, 3, 5, 3, 6, 8, 1, 3, 8, 6, 8, 4])\n",
      "592 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 1, 8, 5, 2, 6, 0, 8, 6, 8, 6, 5, 9, 6, 6])\n",
      "593 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 5, 7, 6, 3, 4, 2, 8, 3, 0, 5, 4, 4, 6, 3])\n",
      "594 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 8, 4, 3, 2, 8, 2, 7, 3, 9, 4, 4, 2, 5, 6])\n",
      "595 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 8, 2, 0, 0, 3, 5, 8, 4, 6, 6, 8, 7, 3, 8])\n",
      "596 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 4, 4, 4, 4, 2, 1, 6, 1, 4, 5, 4, 4, 6, 6, 9])\n",
      "597 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 7, 6, 5, 8, 2, 4, 4, 8, 2, 1, 6, 4, 8, 9, 8])\n",
      "598 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 0, 9, 3, 1, 8, 0, 9, 7, 6, 4, 8, 5, 5, 5, 4])\n",
      "599 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([2, 5, 4, 8, 3, 9, 6, 6, 8, 2, 0, 0, 3, 4, 9, 6])\n",
      "600 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 2, 8, 4, 4, 0, 6, 8, 5, 3, 7, 0, 6, 5, 5, 2])\n",
      "601 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 4, 3, 0, 2, 2, 6, 3, 7, 6, 8, 7, 4, 3, 0, 7])\n",
      "602 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 1, 0, 8, 0, 8, 9, 2, 2, 8, 9, 0, 7, 8, 2, 0])\n",
      "603 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 5, 6, 1, 4, 0, 6, 3, 6, 6, 2, 4, 7, 1, 8, 6])\n",
      "604 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 3, 5, 9, 2, 8, 2, 7, 0, 5, 0, 9, 9, 5, 3, 3])\n",
      "605 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([3, 1, 8, 5, 2, 8, 3, 8, 5, 9, 8, 7, 2, 7, 5, 0])\n",
      "606 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 5, 1, 7, 4, 2, 5, 1, 4, 3, 0, 0, 3, 0, 6, 8])\n",
      "607 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 9, 0, 2, 3, 4, 6, 0, 8, 1, 4, 3, 4, 0, 6, 8])\n",
      "608 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 3, 3, 6, 8, 8, 8, 7, 8, 4, 4, 8, 5, 4, 1, 2])\n",
      "609 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 5, 2, 2, 7, 1, 8, 0, 4, 7, 2, 2, 0, 7, 5])\n",
      "610 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 5, 0, 2, 1, 5, 9, 0, 0, 8, 8, 3, 2, 1, 5, 6])\n",
      "611 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 4, 8, 0, 1, 3, 8, 3, 7, 9, 9, 3, 7, 4, 3, 9])\n",
      "612 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([0, 4, 3, 4, 4, 5, 8, 1, 5, 1, 8, 0, 4, 5, 7, 8])\n",
      "613 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 7, 1, 8, 7, 5, 1, 2, 0, 5, 3, 6, 6, 5, 5, 7])\n",
      "614 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 6, 8, 5, 9, 1, 3, 7, 8, 9, 6, 1, 4, 4, 7, 2])\n",
      "615 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([6, 5, 6, 9, 5, 7, 4, 3, 4, 3, 7, 5, 2, 6, 9, 9])\n",
      "616 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 1, 4, 1, 1, 5, 4, 0, 1, 4, 7, 8, 8, 2, 6, 9])\n",
      "617 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([9, 6, 9, 1, 3, 1, 0, 4, 4, 5, 0, 6, 1, 0, 8, 5])\n",
      "618 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 3, 9, 5, 5, 5, 8, 0, 1, 8, 9, 6, 0, 3, 9, 6])\n",
      "619 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([7, 7, 9, 8, 6, 9, 7, 3, 9, 3, 3, 8, 3, 9, 1, 9])\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "620 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([8, 3, 0, 5, 8, 1, 8, 8, 1, 6, 0, 8, 1, 7, 5, 9])\n",
      "621 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 0, 0, 2, 5, 2, 0, 5, 1, 1, 8, 0, 2, 5, 0, 8])\n",
      "622 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([4, 9, 2, 9, 6, 4, 0, 4, 0, 3, 5, 0, 1, 8, 5, 8])\n",
      "623 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([5, 4, 2, 4, 1, 3, 3, 1, 6, 1, 5, 8, 4, 3, 2, 8])\n",
      "624 torch.Size([16, 3, 32, 32]) torch.Size([16]) tensor([1, 5, 3, 1, 2, 3, 1, 8, 3, 4, 3, 4, 0, 0, 6, 8])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(tensor([2985., 2769., 2730., 2883., 2748., 2889., 2751., 2788., 2787., 2828.,\n",
       "         2874., 2830., 2797., 2773., 2772., 2796.]),\n",
       " tensor([625., 625., 625., 625., 625., 625., 625., 625., 625., 625., 625., 625.,\n",
       "         625., 625., 625., 625.]))"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "record_data = torch.zeros(16)\n",
    "record = []\n",
    "record_ones = torch.zeros(16)\n",
    "for idx, (data, target) in enumerate(test_loader):\n",
    "    record.append(target)\n",
    "    record_data += target\n",
    "    record_ones += torch.ones_like(target)\n",
    "    print(idx, data.shape, target.shape, target)\n",
    "    \n",
    "record_data, record_ones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([4.4864, 4.4848, 4.5344, 4.4976, 4.4832, 4.1568, 4.4112, 4.5248, 4.7024,\n",
       "        4.5536, 4.5408, 4.3840, 4.6592, 4.5280, 4.3808, 4.6720])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "record_data /= idx + 1\n",
    "record_data"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python [conda env:python37] *",
   "language": "python",
   "name": "conda-env-python37-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}