{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3a79a27e",
   "metadata": {},
   "source": [
    "# CNNs for Image Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a58f322",
   "metadata": {},
   "source": [
    "Note: if you have a GPU, you can run this locally. In that case, be sure to check that you installed a GPU-enabled pytorch version:\n",
    "```\n",
    "torch.cuda.is_available()  # should be True\n",
    "torch.tensor([1]).cuda()  # should create a tensor and move it to the GPU\n",
    "```\n",
    "\n",
    "If you don't have a GPU, you can run it on [google colab](https://colab.research.google.com/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9ad2b7f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torchvision\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9de9648a",
   "metadata": {},
   "source": [
    "# Dataset\n",
    "torchvision provides the standard vision datasets and image augmentations.\n",
    "[CIFAR10-100 webpage](https://cave.cs.toronto.edu/kriz/cifar.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8b171887",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\w-32\\miniconda3\\envs\\cv\\Lib\\site-packages\\torchvision\\datasets\\cifar.py:83: VisibleDeprecationWarning: dtype(): align should be passed as Python or NumPy boolean but got `align=0`. Did you mean to pass a tuple to create a subarray type? (Deprecated NumPy 2.4)\n",
      "  entry = pickle.load(f, encoding=\"latin1\")\n"
     ]
    }
   ],
   "source": [
    "from torchvision.datasets import CIFAR10\n",
    "from torchvision import transforms\n",
    "\n",
    "# preprocessing + augmentations for training\n",
    "train_transform = transforms.Compose([\n",
    "    transforms.RandomCrop(32, padding=4),\n",
    "    transforms.RandomHorizontalFlip(),\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),\n",
    "])\n",
    "\n",
    "# preprocessing only for inference\n",
    "eval_transform = transforms.Compose([\n",
    "    transforms.ToTensor(),\n",
    "    transforms.Normalize((0.4914, 0.4822, 0.4465), (0.2023, 0.1994, 0.2010)),\n",
    "])\n",
    "\n",
    "data_dir = \"./data\"\n",
    "train_data = CIFAR10(root=data_dir, train=True, transform=train_transform, download=True)\n",
    "test_data = CIFAR10(root=data_dir, train=False, transform=eval_transform, download=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "65b6afc1-396c-4819-922c-4c93ed25e77a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(torch.Size([3, 32, 32]), 6)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x, y = train_data[0]\n",
    "x.shape, y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a7fbe4bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [-2.4290657..2.5574567].\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'label=6')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(train_data[0][0].transpose(0,2).numpy())\n",
    "plt.title(f\"label={train_data[0][1]}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9d077289-21ca-4d68-8282-a76b69f7fe73",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x12e06084b10>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 100x100 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(1,1))\n",
    "plt.imshow(train_data.data[200])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0b374b17",
   "metadata": {},
   "source": [
    "# Dataloading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8e71f88d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x.shape: torch.Size([100, 3, 32, 32])\n",
      "y: tensor([1, 6, 5, 1, 6, 4, 6, 3, 2, 6, 7, 7, 1, 6, 8, 3, 2, 2, 5, 8, 7, 7, 3, 1,\n",
      "        8, 4, 8, 1, 2, 6, 2, 3, 6, 4, 6, 4, 3, 7, 6, 5, 0, 1, 7, 8, 5, 2, 1, 1,\n",
      "        9, 8, 4, 1, 2, 9, 4, 5, 4, 8, 8, 6, 6, 0, 2, 4, 6, 6, 3, 6, 6, 3, 7, 7,\n",
      "        0, 1, 3, 7, 9, 6, 1, 5, 0, 3, 5, 8, 8, 1, 5, 8, 8, 8, 9, 0, 9, 4, 1, 2,\n",
      "        5, 9, 4, 2])\n"
     ]
    }
   ],
   "source": [
    "from torch.utils.data import DataLoader\n",
    "\n",
    "dataloader = DataLoader(train_data, batch_size=100, shuffle=True)\n",
    "for i, (x, y) in enumerate(dataloader):\n",
    "    # x is the input\n",
    "    # y is the target class\n",
    "    if i == 0:\n",
    "        print(f\"x.shape: {x.shape}\")\n",
    "        print(f\"y: {y}\")\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "218664fc",
   "metadata": {},
   "source": [
    "# Model\n",
    "We use a slim ResNet18. Then standard ResNet18 is designed for 224x224 images, while CIFAR10 has 32x32 images."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "60eeb7ea",
   "metadata": {},
   "outputs": [],
   "source": [
    "# from https://github.com/weiaicunzai/pytorch-cifar100/blob/master/models/resnet.py\n",
    "\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "\n",
    "class BasicBlock(nn.Module):\n",
    "    \"\"\"Basic Block for resnet 18 and resnet 34\"\"\"\n",
    "    #BasicBlock and BottleNeck block\n",
    "    #have different output size\n",
    "    #we use class attribute expansion\n",
    "    #to distinct\n",
    "    expansion = 1\n",
    "\n",
    "    def __init__(self, in_channels, out_channels, stride=1):\n",
    "        super().__init__()\n",
    "        #residual function\n",
    "        self.residual_function = nn.Sequential(\n",
    "            nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=stride, padding=1, bias=False),\n",
    "            nn.BatchNorm2d(out_channels),\n",
    "            nn.ReLU(inplace=True),\n",
    "            nn.Conv2d(out_channels, out_channels * BasicBlock.expansion, kernel_size=3, padding=1, bias=False),\n",
    "            nn.BatchNorm2d(out_channels * BasicBlock.expansion)\n",
    "        )\n",
    "\n",
    "        #shortcut\n",
    "        self.shortcut = nn.Sequential()\n",
    "\n",
    "        #the shortcut output dimension is not the same with residual function\n",
    "        #use 1*1 convolution to match the dimension\n",
    "        if stride != 1 or in_channels != BasicBlock.expansion * out_channels:\n",
    "            self.shortcut = nn.Sequential(\n",
    "                nn.Conv2d(in_channels, out_channels * BasicBlock.expansion, kernel_size=1, stride=stride, bias=False),\n",
    "                nn.BatchNorm2d(out_channels * BasicBlock.expansion)\n",
    "            )\n",
    "\n",
    "    def forward(self, x):\n",
    "        return nn.ReLU(inplace=True)(self.residual_function(x) + self.shortcut(x))\n",
    "\n",
    "class BottleNeck(nn.Module):\n",
    "    \"\"\"Residual block for resnet over 50 layers\"\"\"\n",
    "    expansion = 4\n",
    "    def __init__(self, in_channels, out_channels, stride=1):\n",
    "        super().__init__()\n",
    "        self.residual_function = nn.Sequential(\n",
    "            nn.Conv2d(in_channels, out_channels, kernel_size=1, bias=False),\n",
    "            nn.BatchNorm2d(out_channels),\n",
    "            nn.ReLU(inplace=True),\n",
    "            nn.Conv2d(out_channels, out_channels, stride=stride, kernel_size=3, padding=1, bias=False),\n",
    "            nn.BatchNorm2d(out_channels),\n",
    "            nn.ReLU(inplace=True),\n",
    "            nn.Conv2d(out_channels, out_channels * BottleNeck.expansion, kernel_size=1, bias=False),\n",
    "            nn.BatchNorm2d(out_channels * BottleNeck.expansion),\n",
    "        )\n",
    "\n",
    "        self.shortcut = nn.Sequential()\n",
    "        if stride != 1 or in_channels != out_channels * BottleNeck.expansion:\n",
    "            self.shortcut = nn.Sequential(\n",
    "                nn.Conv2d(in_channels, out_channels * BottleNeck.expansion, stride=stride, kernel_size=1, bias=False),\n",
    "                nn.BatchNorm2d(out_channels * BottleNeck.expansion)\n",
    "            )\n",
    "\n",
    "    def forward(self, x):\n",
    "        return nn.ReLU(inplace=True)(self.residual_function(x) + self.shortcut(x))\n",
    "\n",
    "class ResNet(nn.Module):\n",
    "    def __init__(self, block, num_block, num_classes=100):\n",
    "        super().__init__()\n",
    "        self.in_channels = 64\n",
    "        self.conv1 = nn.Sequential(\n",
    "            nn.Conv2d(3, 64, kernel_size=3, padding=1, bias=False),\n",
    "            nn.BatchNorm2d(64),\n",
    "            nn.ReLU(inplace=True))\n",
    "        #we use a different inputsize than the original paper\n",
    "        #so conv2_x's stride is 1\n",
    "        self.conv2_x = self._make_layer(block, 64, num_block[0], 1)\n",
    "        self.conv3_x = self._make_layer(block, 128, num_block[1], 2)\n",
    "        self.conv4_x = self._make_layer(block, 256, num_block[2], 2)\n",
    "        self.conv5_x = self._make_layer(block, 512, num_block[3], 2)\n",
    "        self.avg_pool = nn.AdaptiveAvgPool2d((1, 1))\n",
    "        self.fc = nn.Linear(512 * block.expansion, num_classes)\n",
    "\n",
    "    def _make_layer(self, block, out_channels, num_blocks, stride):\n",
    "        \"\"\"make resnet layers(by layer i didnt mean this 'layer' was the\n",
    "        same as a neuron netowork layer, ex. conv layer), one layer may\n",
    "        contain more than one residual block\n",
    "\n",
    "        Args:\n",
    "            block: block type, basic block or bottle neck block\n",
    "            out_channels: output depth channel number of this layer\n",
    "            num_blocks: how many blocks per layer\n",
    "            stride: the stride of the first block of this layer\n",
    "\n",
    "        Return:\n",
    "            return a resnet layer\n",
    "        \"\"\"\n",
    "        # we have num_block blocks per layer, the first block\n",
    "        # could be 1 or 2, other blocks would always be 1\n",
    "        strides = [stride] + [1] * (num_blocks - 1)\n",
    "        layers = []\n",
    "        for stride in strides:\n",
    "            layers.append(block(self.in_channels, out_channels, stride))\n",
    "            self.in_channels = out_channels * block.expansion\n",
    "        return nn.Sequential(*layers)\n",
    "\n",
    "    def forward(self, x):\n",
    "        output = self.conv1(x)\n",
    "        output = self.conv2_x(output)\n",
    "        output = self.conv3_x(output)\n",
    "        output = self.conv4_x(output)\n",
    "        output = self.conv5_x(output)\n",
    "        output = self.avg_pool(output)\n",
    "        output = output.view(output.size(0), -1)\n",
    "        output = self.fc(output)\n",
    "        return output\n",
    "\n",
    "\n",
    "def resnet18(num_classes=100):\n",
    "    \"\"\"return a ResNet 18 object\"\"\"\n",
    "    return ResNet(BasicBlock, [2, 2, 2, 2], num_classes=num_classes)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "2f67c27e",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ResNet(\n",
      "  (conv1): Sequential(\n",
      "    (0): Conv2d(3, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "    (2): ReLU(inplace=True)\n",
      "  )\n",
      "  (conv2_x): Sequential(\n",
      "    (0): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential()\n",
      "    )\n",
      "    (1): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential()\n",
      "    )\n",
      "  )\n",
      "  (conv3_x): Sequential(\n",
      "    (0): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential(\n",
      "        (0): Conv2d(64, 128, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
      "        (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "    )\n",
      "    (1): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential()\n",
      "    )\n",
      "  )\n",
      "  (conv4_x): Sequential(\n",
      "    (0): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential(\n",
      "        (0): Conv2d(128, 256, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
      "        (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "    )\n",
      "    (1): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential()\n",
      "    )\n",
      "  )\n",
      "  (conv5_x): Sequential(\n",
      "    (0): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential(\n",
      "        (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False)\n",
      "        (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "    )\n",
      "    (1): BasicBlock(\n",
      "      (residual_function): Sequential(\n",
      "        (0): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "        (2): ReLU(inplace=True)\n",
      "        (3): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
      "        (4): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, bias=True, track_running_stats=True)\n",
      "      )\n",
      "      (shortcut): Sequential()\n",
      "    )\n",
      "  )\n",
      "  (avg_pool): AdaptiveAvgPool2d(output_size=(1, 1))\n",
      "  (fc): Linear(in_features=512, out_features=10, bias=True)\n",
      ")\n"
     ]
    }
   ],
   "source": [
    "model = resnet18(num_classes=10)\n",
    "print(model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b07d5923",
   "metadata": {},
   "source": [
    "# Training"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b21d3fea",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Loss: 1.1877: 100%|██████████| 1563/1563 [36:23<00:00,  1.40s/it] \n",
      "Loss: 1.1878:  17%|█▋        | 261/1563 [10:03<50:08,  2.31s/it]   \n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mKeyboardInterrupt\u001b[39m                         Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[23]\u001b[39m\u001b[32m, line 26\u001b[39m\n\u001b[32m     22\u001b[39m         x, y = x.to(device), y.to(device)\n\u001b[32m     23\u001b[39m         \u001b[38;5;66;03m# - reset the gradients\u001b[39;00m\n\u001b[32m     24\u001b[39m         optimizer.zero_grad()\n\u001b[32m     25\u001b[39m         \u001b[38;5;66;03m# - forward pass\u001b[39;00m\n\u001b[32m---> \u001b[39m\u001b[32m26\u001b[39m         pred = model(x)\n\u001b[32m     27\u001b[39m         loss = criterion(pred, y)\n\u001b[32m     28\u001b[39m         \u001b[38;5;66;03m# - backward pass\u001b[39;00m\n\u001b[32m     29\u001b[39m         loss.backward()\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1783\u001b[39m, in \u001b[36mModule._wrapped_call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1781\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._compiled_call_impl(*args, **kwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[32m   1782\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1783\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_call_impl\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1794\u001b[39m, in \u001b[36mModule._call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1789\u001b[39m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[32m   1790\u001b[39m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[32m   1791\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m._backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_pre_hooks\n\u001b[32m   1792\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[32m   1793\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[32m-> \u001b[39m\u001b[32m1794\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mforward_call\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m   1796\u001b[39m result = \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m   1797\u001b[39m called_always_called_hooks = \u001b[38;5;28mset\u001b[39m()\n",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[16]\u001b[39m\u001b[32m, line 115\u001b[39m, in \u001b[36mResNet.forward\u001b[39m\u001b[34m(self, x)\u001b[39m\n\u001b[32m    112\u001b[39m     \u001b[38;5;28;01mdef\u001b[39;00m forward(self, x):\n\u001b[32m    113\u001b[39m         output = self.conv1(x)\n\u001b[32m    114\u001b[39m         output = self.conv2_x(output)\n\u001b[32m--> \u001b[39m\u001b[32m115\u001b[39m         output = self.conv3_x(output)\n\u001b[32m    116\u001b[39m         output = self.conv4_x(output)\n\u001b[32m    117\u001b[39m         output = self.conv5_x(output)\n\u001b[32m    118\u001b[39m         output = self.avg_pool(output)\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1783\u001b[39m, in \u001b[36mModule._wrapped_call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1781\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._compiled_call_impl(*args, **kwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[32m   1782\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1783\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_call_impl\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1794\u001b[39m, in \u001b[36mModule._call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1789\u001b[39m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[32m   1790\u001b[39m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[32m   1791\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m._backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_pre_hooks\n\u001b[32m   1792\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[32m   1793\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[32m-> \u001b[39m\u001b[32m1794\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mforward_call\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m   1796\u001b[39m result = \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m   1797\u001b[39m called_always_called_hooks = \u001b[38;5;28mset\u001b[39m()\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\container.py:259\u001b[39m, in \u001b[36mSequential.forward\u001b[39m\u001b[34m(self, input)\u001b[39m\n\u001b[32m    255\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m    256\u001b[39m \u001b[33;03mRuns the forward pass.\u001b[39;00m\n\u001b[32m    257\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m    258\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m:\n\u001b[32m--> \u001b[39m\u001b[32m259\u001b[39m     \u001b[38;5;28minput\u001b[39m = \u001b[30;43mmodule\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43minput\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m    260\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28minput\u001b[39m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1783\u001b[39m, in \u001b[36mModule._wrapped_call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1781\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._compiled_call_impl(*args, **kwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[32m   1782\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1783\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_call_impl\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1794\u001b[39m, in \u001b[36mModule._call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1789\u001b[39m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[32m   1790\u001b[39m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[32m   1791\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m._backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_pre_hooks\n\u001b[32m   1792\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[32m   1793\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[32m-> \u001b[39m\u001b[32m1794\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mforward_call\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m   1796\u001b[39m result = \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m   1797\u001b[39m called_always_called_hooks = \u001b[38;5;28mset\u001b[39m()\n",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[16]\u001b[39m\u001b[32m, line 38\u001b[39m, in \u001b[36mBasicBlock.forward\u001b[39m\u001b[34m(self, x)\u001b[39m\n\u001b[32m     37\u001b[39m     \u001b[38;5;28;01mdef\u001b[39;00m forward(self, x):\n\u001b[32m---> \u001b[39m\u001b[32m38\u001b[39m         \u001b[38;5;28;01mreturn\u001b[39;00m nn.ReLU(inplace=\u001b[38;5;28;01mTrue\u001b[39;00m)(self.residual_function(x) + self.shortcut(x))\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1783\u001b[39m, in \u001b[36mModule._wrapped_call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1781\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._compiled_call_impl(*args, **kwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[32m   1782\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1783\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_call_impl\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1794\u001b[39m, in \u001b[36mModule._call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1789\u001b[39m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[32m   1790\u001b[39m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[32m   1791\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m._backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_pre_hooks\n\u001b[32m   1792\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[32m   1793\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[32m-> \u001b[39m\u001b[32m1794\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mforward_call\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m   1796\u001b[39m result = \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m   1797\u001b[39m called_always_called_hooks = \u001b[38;5;28mset\u001b[39m()\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\container.py:259\u001b[39m, in \u001b[36mSequential.forward\u001b[39m\u001b[34m(self, input)\u001b[39m\n\u001b[32m    255\u001b[39m \u001b[38;5;250m\u001b[39m\u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m    256\u001b[39m \u001b[33;03mRuns the forward pass.\u001b[39;00m\n\u001b[32m    257\u001b[39m \u001b[33;03m\"\"\"\u001b[39;00m\n\u001b[32m    258\u001b[39m \u001b[38;5;28;01mfor\u001b[39;00m module \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m:\n\u001b[32m--> \u001b[39m\u001b[32m259\u001b[39m     \u001b[38;5;28minput\u001b[39m = \u001b[30;43mmodule\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43minput\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m    260\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28minput\u001b[39m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1783\u001b[39m, in \u001b[36mModule._wrapped_call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1781\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m._compiled_call_impl(*args, **kwargs)  \u001b[38;5;66;03m# type: ignore[misc]\u001b[39;00m\n\u001b[32m   1782\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m-> \u001b[39m\u001b[32m1783\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_call_impl\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\module.py:1794\u001b[39m, in \u001b[36mModule._call_impl\u001b[39m\u001b[34m(self, *args, **kwargs)\u001b[39m\n\u001b[32m   1789\u001b[39m \u001b[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[32m   1790\u001b[39m \u001b[38;5;66;03m# this function, and just call forward.\u001b[39;00m\n\u001b[32m   1791\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m (\u001b[38;5;28mself\u001b[39m._backward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_hooks \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m._forward_pre_hooks\n\u001b[32m   1792\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_backward_pre_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_backward_hooks\n\u001b[32m   1793\u001b[39m         \u001b[38;5;129;01mor\u001b[39;00m _global_forward_hooks \u001b[38;5;129;01mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[32m-> \u001b[39m\u001b[32m1794\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mforward_call\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43margs\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43m*\u001b[39;49m\u001b[30;43mkwargs\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m   1796\u001b[39m result = \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[32m   1797\u001b[39m called_always_called_hooks = \u001b[38;5;28mset\u001b[39m()\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\conv.py:565\u001b[39m, in \u001b[36mConv2d.forward\u001b[39m\u001b[34m(self, input)\u001b[39m\n\u001b[32m    564\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mforward\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;28minput\u001b[39m: Tensor) -> Tensor:\n\u001b[32m--> \u001b[39m\u001b[32m565\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43m_conv_forward\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43minput\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mweight\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mbias\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~\\miniconda3\\envs\\cv\\Lib\\site-packages\\torch\\nn\\modules\\conv.py:560\u001b[39m, in \u001b[36mConv2d._conv_forward\u001b[39m\u001b[34m(self, input, weight, bias)\u001b[39m\n\u001b[32m    547\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m.padding_mode != \u001b[33m\"\u001b[39m\u001b[33mzeros\u001b[39m\u001b[33m\"\u001b[39m:\n\u001b[32m    548\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m F.conv2d(\n\u001b[32m    549\u001b[39m         F.pad(\n\u001b[32m    550\u001b[39m             \u001b[38;5;28minput\u001b[39m, \u001b[38;5;28mself\u001b[39m._reversed_padding_repeated_twice, mode=\u001b[38;5;28mself\u001b[39m.padding_mode\n\u001b[32m   (...)\u001b[39m\u001b[32m    557\u001b[39m         \u001b[38;5;28mself\u001b[39m.groups,\n\u001b[32m    558\u001b[39m     )\n\u001b[32m--> \u001b[39m\u001b[32m560\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mF\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mconv2d\u001b[39;49m\u001b[30;43m(\u001b[39;49m\n\u001b[32m    561\u001b[39m \u001b[30;43m    \u001b[39;49m\u001b[30;43minput\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mweight\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mbias\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mstride\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mpadding\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mdilation\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mself\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mgroups\u001b[39;49m\n\u001b[32m    562\u001b[39m \u001b[30;43m\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n",
      "\u001b[31mKeyboardInterrupt\u001b[39m: "
     ]
    }
   ],
   "source": [
    "from tqdm import tqdm\n",
    "from torch.utils.data import DataLoader\n",
    "\n",
    "device = 'cpu'  # set device='cuda' if you have a GPU\n",
    "model = resnet18(num_classes=100)\n",
    "model = model.to(device)\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.04)\n",
    "criterion = torch.nn.CrossEntropyLoss()\n",
    "\n",
    "# don't forget to set the training mode!\n",
    "# it controls the behavior of modules that differ at training and inference time (e.g. BatchNorm)\n",
    "model.train()\n",
    "\n",
    "# Iterate over the dataset and train the model\n",
    "for ep in range(10):  # 10 epoch is a bit on the low end. With a GPU you can run a larger experiment\n",
    "    # increase num_workers if you have more CPUs\n",
    "    # setting num_workers > 0 allows to do the pre-processing in parallel.\n",
    "    # with num_workers=0, the GPU is stuck waiting on the data that is preprocessed and augmented on the CPU\n",
    "    dataloader = DataLoader(train_data, batch_size=32, shuffle=True, num_workers=0)\n",
    "    pbar = tqdm(dataloader)\n",
    "    for x, y in pbar:\n",
    "        x, y = x.to(device), y.to(device)\n",
    "        # - reset the gradients\n",
    "        optimizer.zero_grad()   \n",
    "        # - forward pass\n",
    "        pred = model(x)\n",
    "        loss = criterion(pred, y)\n",
    "        # - backward pass\n",
    "        loss.backward()\n",
    "        # - descent step\n",
    "        optimizer.step()\n",
    "        pbar.set_description(f\"Loss: {loss.item():0.4f}\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a017e21f",
   "metadata": {},
   "source": [
    "# Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f079156f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ACC: 0.6323: 100%|██████████| 313/313 [02:29<00:00,  2.10it/s]\n"
     ]
    }
   ],
   "source": [
    "with torch.no_grad():\n",
    "    model = model.eval()\n",
    "    dataloader = DataLoader(test_data, batch_size=32, num_workers=0)  # increase num_workers if you have more CPUs\n",
    "    pbar = tqdm(dataloader)\n",
    "    correct, tot = 0, 0\n",
    "    for x, y in pbar:\n",
    "        x, y = x.to(device), y.to(device)\n",
    "        pred = model(x)\n",
    "        _, pred = torch.max(pred.data, 1)\n",
    "        correct += (pred == y).sum().item()\n",
    "        tot += x.shape[0]\n",
    "        pbar.set_description(f\"ACC: {correct / tot:.4f}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6d849d8-41c4-4713-a0c1-4a22d66b92e6",
   "metadata": {},
   "source": [
    "# Feature Maps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5b0bd4fc-2b64-4439-af66-87490d1dd176",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([16, 3, 32, 32])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "6826e315-5279-4bfd-9e91-73e5490140dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [-2.0025976..2.3590088].\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x292731129d0>"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 200x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(2,2))\n",
    "plt.imshow(x[0].detach().cpu().numpy().transpose(1,2,0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5ad4e305-2d30-4b4f-b258-20703cd5e269",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.decomposition import PCA\n",
    "\n",
    "def visualize_pca(feature_map):\n",
    "    \"\"\"feature_map: torch.Tensor of shape (C, H, W) or (1, C, H, W)\"\"\"\n",
    "    x = feature_map.detach().float().cpu().squeeze()\n",
    "    C, H, W = x.shape\n",
    "    x = x.reshape(C, -1).T.numpy()  # Reshape: (C, H, W) -> (H*W, C)\n",
    "    x = PCA(n_components=3).fit_transform(x)  # PCA: C channels -> 3 components\n",
    "    x = (x - x.min(axis=0)) / (np.ptp(x, axis=0) + 1e-8)  # Normalize in [0, 1]\n",
    "    rgb = x.reshape(H, W, 3)  # Reshape to RGB image\n",
    "\n",
    "    plt.figure(figsize=(3, 3))\n",
    "    plt.imshow(rgb)\n",
    "    return rgb\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "5ac66d8d-df43-435a-97ae-8826a43c3061",
   "metadata": {},
   "outputs": [],
   "source": [
    "activations = []\n",
    "def hook(model, input, output):\n",
    "    activations.append(output.detach())\n",
    "\n",
    "h = model.conv4_x.register_forward_hook(hook)\n",
    "model(x)\n",
    "h.remove()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "a548d64b-a273-4277-9298-57d0df02e3b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([16, 256, 8, 8])"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "activations[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "6e6aee12-cbe6-4354-91b8-5ced1b8d5d59",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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//35pbW21b+Dc3NwsTlVaWirr1q2TtLQ0cZrr169LTk6OhISEyJ49e+TkyZPy8ccfS2xsrDiC5QPGjBljFRQUtK27XC4rPj7eWrFiheVE9fX16toZq7i42HKixsZGa8iQIdb+/futcePGWQsWLLCcZPHixdbYsWMtp/L6PQ3Vnb68vFwmTpzYbtKbWj969Kg40c2bN+1/e/fuLU6k9qpUd74/f0+dZNeuXTJ69GiZPn26fbg5atQo2bBhgziF14fG1atXxeVySf/+/ds9rtbr6urEadStA9Qxvtq9TU1NFacpLCy0DzHVeRynOnv2rKxZs0aGDBki+/btk/z8fJk/f75s2bJFnIC+il74V7iyslKOHDkiTqPuK7FgwQL7vI06oe1Ubrfb3tNYvny5va72NNT3dO3atXY7U1/n9Xsaffv2laCgILly5Uq7x9X6gAEDxEnmzZsnu3fvlp9//vmR7jnirdRhpjp5nZ6ebvcBVos6CfzZZ5/ZX6s9SieIi4uTlJSUdo8NGzbMbmfqBF4fGqGhoZKRkSEHDx5sl+RqPTs7W5xAzRlUgbFjxw756aefJDk5WZxowoQJUlFRISdOnGhb1F/kGTNm2F+rPw5OkJOT85ePzE+dOiUDBw4UR7B8QGFhoRUWFmZt3rzZOnnypDV37lyrV69eVl1dneUE+fn5VkxMjHXo0CHr8uXLbcutW7csp3PipyfHjh2zgoODrWXLllmnT5+2tm3bZkVGRlpbt261nMAnQkP5/PPPraSkJCs0NNT+CLakpMRyCpXdD1o2bdpkOZ0TQ0P5/vvvrdTUVPuP3dChQ63169dbTsH9NAA465wGAO9CaADQQmgA0EJoANBCaADQQmgA0EJoANBCaADQQmgA0EJoANBCaAAQHf8LyoTiGYGF6K4AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQ0AAAESCAYAAADnkoBGAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjksIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvJkbTWQAAAAlwSFlzAAAPYQAAD2EBqD+naQAAEMhJREFUeJzt3XtMVVebx/HncBNQQMQi8IJKW6oiYkXUGGytFTXEmtpJTNPo1NqMpgar1nTi+E9t03jpH+3Yi/EWq07UYtNUa03VQas4phIEXzJSZ1SqFrwg2qpcVMBz9mTtN2IZBVnoWXL2+X6SHdkn+/AsBH7svc9Z63FZlmUJALRTQHsPBABCA4A2zjQAaCE0AGghNABoITQAaCE0AGgJEsM8Ho9cvHhRIiIixOVymS4PoBXqLVu1tbWSkJAgAQEBnSc0VGAkJSWZLgugnSorKyUxMbHzhIY6w7AL//sicYWFGqvb1PeKGBd+y3zNxkqj5SISqsS09L/1M14z5lK68Zp/3/eP3xVTPLduy4V//bfm39FOExp3L0lUYJgMDVfXLmJcV7fxklZDsNF6rohAMS0o0uzXqATXmftZvSsgLEyehIfdNuBGKAAthAYALYQGAC2EBgAthAYALYQGAC2EBgAthAYA74fGypUrpW/fvhIaGiojRoyQoqKijnwaAP4QGtu2bZMFCxbI4sWL5dixYzJ48GCZMGGCVFdXe2eEAHw7ND777DOZOXOmzJgxQ1JTU2X16tUSHh4uX3/9tXdGCMB3Q6OxsVFKSkokOzv73icICLD3jxw58sDnNDQ0SE1NTYsNgJ+ExtWrV8XtdkuvXr1aPK72q6oePNtx2bJlEhUV1bwxLR7wbV5/9WTRokVy48aN5k3N1Qfgu7Smxvfs2VMCAwPl8uXLLR5X+3FxcQ98TpcuXewNgB+eaYSEhMjQoUNl//79LZbvU/sjR470xvgAdDLai/Col1unT58umZmZMnz4cFmxYoXU19fbr6YAcD7t0Hj99dflypUr8sEHH9g3P59//nnZs2fPfTdHAThTh5b7mzNnjr0B8D/MPQGghdAAoIXQAKCF0ACghdAAoIXQAKCF0ACgxXhbxrv6HYmUwBBzbecSK8y3uGvq8YfxmsFJp4zWez0pVkz7pwuLjNfc/Uua8ZpXysuM1rvTUCftmU7KmQYALYQGAC2EBgAthAYALYQGAC2EBgAthAYALYQGAC2EBgAthAYA74bGoUOHZNKkSZKQkCAul0t27Nih+ykA+FNoqJXHVdNn1TkegP/RnrCWk5NjbwD8k9dnuaoG0Gq7iwbQgG/z+o1QGkADzkIDaACd6/KEBtCAs/A+DQDePdOoq6uT8vLy5v2zZ89KaWmp9OjRQ3r37q376QA4PTSKi4tlzJgxLbrIK6qT/MaNGx/v6AD4fmi89NJLYlmWd0YDoNPjngYALYQGAC2EBgAthAYALYQGAC2EBgAthAYA32gA7TnbR1xBXc0VPJgvpsVn/rfxmpmu80br/fOBfmLaqfJG4zXPxd9b3sGUhiiPmHTnTvvqcaYBQAuhAUALoQFAC6EBQAuhAUALoQFAC6EBQAuhAUALoQFAC6EBwHuhoRofDRs2TCIiIiQ2NlYmT54sJ0+e1KsIwH9Co6CgQHJzc6WwsFDy8/OlqalJxo8fbzeFBuAftCas7dmzp8W+Wn1cnXGUlJTIiy+++MDn0MsVcJZHuqdx48YN+1/V86Q19HIFnKXDoeHxeGT+/PmSlZUlaWlprR63aNEiO1zubpWVlR0tCcCX19NQ9zbKysrk8OHDbR5HL1fAWToUGnPmzJFdu3bJoUOHJDEx8fGPCoAzQkN1Vnv33Xdl+/btcvDgQUlOTvbeyAD4fmioS5KtW7fKDz/8YL9Xo6qqyn48KipKwsLCvDVGAL56I3TVqlX2zUzVzzU+Pr5527Ztm/dGCMC3L08A+DfmngDQQmgA0EJoANBCaADQQmgA0EJoANBCaADwjQbQt7t5JDDYbazejT8HimkNB/5uvGZ0oNl6396MNFtQRJ6Ka3uSpDecK37eeM3gjD+N1nM1tW8xLc40AGghNABoITQAaCE0AGghNABoITQAaCE0AGghNABoITQAaCE0AHh3jdD09HSJjIy0t5EjR8ru3bv1KgLwn9BQPU6WL19u924tLi6Wl19+WV599VX59ddfvTdCAL47YW3SpEkt9pcsWWKffagu8gMHPnhCGA2gAWfp8D0Nt9steXl5Ul9fb1+mtIYG0ICfh8bx48elW7dudo/Wd955x+62lpqa2urxNIAG/Hw9jX79+klpaandNOm7776T6dOnS0FBQavBQQNowM9DIyQkRJ599ln746FDh8rRo0fl888/lzVr1nhjfACc9j4Nj8dj3+wE4B+0zjTU/YmcnBzp3bu31NbW2s2gVff4vXv3em+EAHw3NKqrq+XNN9+US5cu2Z3i1Ru9VGCMGzfOeyME4LuhsX79eu+NBIBPYO4JAC2EBgAthAYALYQGAC2EBgAthAYA3+jl2hDWIAHB5hqP3o5KE9OC/uxqvGZ511Cj9a40ma2nBPyP8ZJyPXGT8Zq3rjQared232rXcZxpANBCaADQQmgA0EJoANBCaADQQmgA0EJoANBCaADQQmgA0EJoADAXGqpFo8vlkvnz5z/KpwHgD6GhWheotgVqnVAA/qNDoVFXVydTp06VdevWSXR09OMfFQBnhUZubq5MnDhRsrOzH3qs6olSU1PTYgPgR1PjVdPnY8eO2Zcn7aEaQH/00UcdGRsAXz/TqKyslHnz5smWLVskNLR96yjQABrw4zONkpISu2FSRkZG82Nut1sOHTokX331lX0pEhjYcmEdGkADfhwaY8eOlePHj7d4bMaMGdK/f39ZuHDhfYEBwM9DIyIiQtLSWi6b17VrV4mJibnvcQDOxDtCAZhdWFh1jQfgPzjTAKCF0ACghdAAoIXQAKCF0ACghdAAQGgAcGAD6OvB9eIK8RirF5FSIqalnso0XrO+JthovfPd6sS0kPD/Ml4zbHiT8ZppKclG6zU2NEhpO35NuDwBoIXQAKCF0ACghdAAoIXQAKCF0ACghdAAoIXQAKCF0ACghdAA4L3Q+PDDD+2Gz3/d1ErkAPyH9tyTgQMHyr59++59gqAnNn0FwBOg/RuvQiIuLs47owHgvHsap0+floSEBHn66aftzvEVFRVtHk8DaMCPQ2PEiBGyceNG2bNnj6xatUrOnj0rL7zwgtTW1rbZADoqKqp5S0pKehzjBuALoZGTkyNTpkyR9PR0mTBhgvz0009y/fp1+fbbb1t9Dg2gAWd5pLuY3bt3l+eee07Ky8tbPYYG0ICzPNL7NOrq6uS3336T+Pj4xzciAM4Jjffff18KCgrk3Llz8ssvv8hrr71md4p/4403vDdCAL57eXL+/Hk7IP744w956qmnZNSoUVJYWGh/DMA/aIVGXl6e90YCwCcw9wSAFkIDgBZCA4AWQgOAFkIDgBZCA4AWQgOAlie2go4rokJcIaHG6kW7zTeAHv6/fzNes6i+n9F6Fcn/KaYFR58wXvPlxJvGa46Z8C9G69XVN8o3Kx5+HGcaALQQGgC0EBoAtBAaALQQGgC0EBoAtBAaALQQGgC0EBoAtBAaALwbGhcuXJBp06ZJTEyMhIWFyaBBg6S4uFj30wDwh7kn165dk6ysLBkzZozs3r3bXlBYtWmMjo723ggB+G5ofPLJJ3ZbxQ0bNjQ/lpyc7I1xAXDC5cnOnTslMzPTbs0YGxsrQ4YMkXXr1rX5HBpAA34cGmfOnLEbP6ekpMjevXtl9uzZMnfuXNm0aVOrz6EBNODHoeHxeCQjI0OWLl1qn2XMmjVLZs6cKatXr271OTSABvw4NFTP1tTU1BaPDRgwQCoqKtpsAB0ZGdliA+AnoaFeOTl58mSLx06dOiV9+vR53OMC4ITQeO+99+zererypLy8XLZu3Spr166V3Nxc740QgO+GxrBhw2T79u3yzTffSFpamnz88ceyYsUKmTp1qvdGCMC3FxZ+5ZVX7A2Af2LuCQAthAYALYQGAC2EBgAthAYALYQGAC2EBgDfaAAdbgVKgBVorN6z4V3EtPMNfY3XvPz0LaP1QmOTxLT0nma/RiU7+brxmr9/Pd5ovZuNqsn1fzz0OM40AGghNABoITQAaCE0AGghNABoITQAaCE0AGghNABoITQAaCE0AHgvNPr27Ssul+u+jYWFAf+hNffk6NGj4na7m/fLyspk3LhxdptGAP5BKzRUl/i/Wr58uTzzzDMyevToxz0uAE6b5drY2CibN2+WBQsW2JcobTWAVttdNTU1HS0JwJdvhO7YsUOuX78ub731VpvH0QAacJYOh8b69eslJydHEhIS2jyOBtCAs3To8uT333+Xffv2yffff//QY1UDaLUB8OMzjQ0bNkhsbKxMnDjx8Y8IgLNCw+Px2KExffp0CQp6YqsFAvCV0FCXJRUVFfL22297Z0QAOjXtU4Xx48eLZVneGQ2ATo+5JwC0EBoAtBAaALQQGgC0EBoAtBAaALQYf3fW3ZdrPY33Zr6a0NjUJKY1eG4br3nHbbbmnTtP4P+16d6aLqbU3fYYr3nT7q1qsF7TP3rkPuwtFS7L8Jsuzp8/L0lJ5psGA2ifyspKSUxM7Dyhod6GfvHiRYmIiGhzHY7/T63DocJGfUGRkZHiVHydzlHjYz+zKgpqa2vtmesBAQGd5/JEDaatFHsY9Z/vC9+AR8XX6RyRPvQzGxUV9dBjuBEKQAuhAcCZoaEW8lm8eLHjF/Th63SOLg79mTV+IxSAb/OZMw0AnQOhAUALoQFAC6EBQAuhAcCZobFy5Uq7a31oaKiMGDFCioqKxClUF7phw4bZb61XrSEmT54sJ0+eFKdTvYDVVIL58+eL01y4cEGmTZsmMTExEhYWJoMGDZLi4mJxAp8IjW3bttk9Y9Vr3seOHZPBgwfLhAkTpLq6WpygoKBAcnNzpbCwUPLz86WpqclewLm+vl6c6ujRo7JmzRpJT08Xp7l27ZpkZWVJcHCw7N69W06cOCGffvqpREdHiyNYPmD48OFWbm5u877b7bYSEhKsZcuWWU5UXV2t3jtjFRQUWE5UW1trpaSkWPn5+dbo0aOtefPmWU6ycOFCa9SoUZZTdfozDdWdvqSkRLKzs1tMelP7R44cESe6ceOG/W+PHj3EidRZlerO99fvqZPs3LlTMjMzZcqUKfbl5pAhQ2TdunXiFJ0+NK5evSput1t69erV4nG1X1VVJU6jlg5Q1/jq9DYtLU2cJi8vz77EVPdxnOrMmTOyatUqSUlJkb1798rs2bNl7ty5smnTJnEC+ip2wr/CZWVlcvjwYXEata7EvHnz7Ps26oa2U3k8HvtMY+nSpfa+OtNQ39PVq1fb7Ux9Xac/0+jZs6cEBgbK5cuXWzyu9uPi4sRJ5syZI7t27ZIDBw480pojnZW6zFQ3rzMyMuw+wGpTN4G/+OIL+2N1RukE8fHxkpqa2uKxAQMG2O1MnaDTh0ZISIgMHTpU9u/f3yLJ1f7IkSPFCdScQRUY27dvl59//lmSk5PFicaOHSvHjx+X0tLS5k39RZ46dar9sfrj4ARZWVn3vWR+6tQp6dOnjziC5QPy8vKsLl26WBs3brROnDhhzZo1y+revbtVVVVlOcHs2bOtqKgo6+DBg9alS5eat5s3b1pO58RXT4qKiqygoCBryZIl1unTp60tW7ZY4eHh1ubNmy0n8InQUL788kurd+/eVkhIiP0SbGFhoeUUKrsftG3YsMFyOieGhvLjjz9aaWlp9h+7/v37W2vXrrWcgvU0ADjrngaAzoXQAKCF0ACghdAAoIXQAKCF0ACghdAAoIXQAKCF0ACghdAAoIXQACA6/g9Creintli6+AAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAQ0AAAESCAYAAADnkoBGAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjksIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvJkbTWQAAAAlwSFlzAAAPYQAAD2EBqD+naQAAEMNJREFUeJzt3XtMFHe/x/HvAuVWAa/cjqK0xSqiVkWNB1vrPcSa2j+MaTS1NkdTg1Vrmhj/qW0aLz1JG3sxXogF86jFpq3WmqJRWzE+lcgl5pF6ilIv4AUoVgFREXfnyW+eSMtRkB+6v7Kz71cygdnM7veHix9+MzszX5dlWZYAQDsFtHdDACA0AGhjpgFAC6EBQAuhAUALoQFAC6EBQEuQGObxeOTy5csSEREhLpfLdHkArVCnbNXX10t8fLwEBAR0ntBQgdGnTx/TZQG0U0VFhfTu3bvzhIaaYSjRsy5IQHCksbqhXWvEtLq4UuM1XSWtv9neEHG3l5gW3dTFeM3w0EbjNWus80bruZtuyP99M6H5/2inCY17uyQqMEyGRkCI+Tc9IPRJ4zVdwW2/4Y9bQIC59/CeIDEfGkHB5n9/Ai3zP6fysMMGHAgFoIXQAKCF0ACghdAAoIXQAKCF0ACghdAAoIXQAOD90Fi/fr3069dPQkNDZfTo0XL8+PGOvAwAfwiNnTt3yrJly2TlypVSXFwsQ4cOlalTp0p1dbV3RgjAt0Pj448/lvnz58u8efMkOTlZNm7cKOHh4fLFF194Z4QAfDc07ty5I0VFRTJp0qQ/XyAgwF4/duzYA5/T2NgodXV1LRYAfhIaNTU14na7JSYmpsXjar2ysvKBz1mzZo1ERUU1L1wWD/g2r396smLFCqmtrW1e1LX6AHyX1qXxPXv2lMDAQKmqqmrxuFqPjY194HNCQkLsBYAfzjSCg4NlxIgRcujQoRa371PrY8aM8cb4AHQy2jfhUR+3zp07V1JTU2XUqFGybt06aWhosD9NAeB82qExa9Ys+f333+Xdd9+1D34+99xzsm/fvvsOjgJwpg7d7m/RokX2AsD/cO0JAC2EBgAthAYALYQGAC2EBgAthAYALYQGAC3G2zLeE9j4TwnwmGtbGNdwR0zrFfGr8ZpVE/YYrReRFSym9bwSaLymK9x8+8molHCj9ZrklpS0YztmGgC0EBoAtBAaALQQGgC0EBoAtBAaALQQGgC0EBoAtBAaALQQGgC8GxpHjhyR6dOnS3x8vLhcLtm9e7fuSwDwp9BQdx5XTZ9V53gA/kf7grX09HR7AeCfvH6Vq2oArZZ7aAAN+DavHwilATTgLDSABtC5dk9oAA04C+dpAPDuTOPGjRtSVlbWvH7u3Dk5ceKEdO/eXRISEnRfDoDTQ6OwsFDGjx/foou8ojrJZ2dnP97RAfD90HjxxRfFsizvjAZAp8cxDQBaCA0AWggNAFoIDQBaCA0AWggNAFoIDQC+0QD6dtdbEhDsMlav6ulLYlq8x2wDX6WXRBmtVzP9gtF6ds28W8ZrNkaEGa8Z/a9njdZrct9u13bMNABoITQAaCE0AGghNABoITQAaCE0AGghNABoITQAaCE0AGghNAB4LzRU46ORI0dKRESEREdHy4wZM6S0tFSvIgD/CY28vDzJyMiQ/Px8OXDggDQ1NcmUKVPsptAA/IPWBWv79u1rsa7uPq5mHEVFRfLCCy888Dn0cgWc5ZGOadTW1tpfVc+T1tDLFXCWDoeGx+ORpUuXSlpamqSkpLS63YoVK+xwubdUVFR0tCQAX76fhjq2UVJSIkePHm1zO3q5As7SodBYtGiR7N27V44cOSK9e/d+/KMC4IzQUJ3V3nrrLdm1a5ccPnxYEhMTvTcyAL4fGmqXZMeOHfLdd9/Z52pUVlbaj0dFRUlYmPnboQHo5AdCN2zYYB/MVP1c4+LimpedO3d6b4QAfHv3BIB/49oTAFoIDQBaCA0AWggNAFoIDQBaCA0AWggNAL7RALpPTKwEhnYxVm9yaoyY1njtvPGal//5q9F6/ULqxTQrzfzZx0H/fd14TSn/zxnXpjTdbBT5n4dvx0wDgBZCA4AWQgOAFkIDgBZCA4AWQgOAFkIDgBZCA4AWQgOAFkIDgHfvETpkyBCJjIy0lzFjxkhubq5eRQD+Exqqx8natWvt3q2FhYUyYcIEefnll+WXX37x3ggB+O4Fa9OnT2+xvmrVKnv2obrIDxo06IHPoQE04CwdPqbhdrslJydHGhoa7N2U1tAAGvDz0Dh58qR06dLF7tH65ptv2t3WkpOTW92eBtCAn99P49lnn5UTJ07YTZO+/vprmTt3ruTl5bUaHDSABvw8NIKDg+WZZ56xvx8xYoQUFBTIJ598Ips2bfLG+AA47TwNj8djH+wE4B+0Zhrq+ER6erokJCRIfX293QxadY/fv3+/90YIwHdDo7q6Wl577TW5cuWK3SleneilAmPy5MneGyEA3w2NLVu2eG8kAHwC154A0EJoANBCaADQQmgA0EJoANBCaADwjV6u/Y6KPGGwelLmbTEtSC4brzn4f6uM1us/s4+YFlM7ynjN4oKrxmtW7b5mtN6tptvyTTu2Y6YBQAuhAUALoQFAC6EBQAuhAUALoQFAC6EBQAuhAUALoQFAC6EBwFxoqBaNLpdLli5d+igvA8AfQkO1LlBtC9R9QgH4jw6Fxo0bN2T27NmSmZkp3bp1e/yjAuCs0MjIyJBp06bJpEmTHrqt6olSV1fXYgHgu7QvTldNn4uLi+3dk/ZQDaDff//9jowNgK/PNCoqKmTJkiWyfft2CQ0NbddzaAAN+PFMo6ioyG6YNHz48ObH3G63HDlyRD7//HN7VyQwMLDFc2gADfhxaEycOFFOnjzZ4rF58+bJgAEDZPny5fcFBgA/D42IiAhJSUlp8diTTz4pPXr0uO9xAM7EGaEAtDzyrX1V13gA/oOZBgAthAYALYQGAC2EBgAthAYALYQGAEIDgAMbQP/q+pcEusKM1buadFRMS4zobrzmlPIBRuulrTLfALos23xj7SLXXuM1vxnWZLSeR+62azt2TwBoITQAaCE0AGghNABoITQAaCE0AGghNABoITQAaCE0AGghNAB4LzTee+89u+HzXxd1J3IA/kP72pNBgwbJwYMH/3yBoL/t8hUAfwPt//EqJGJjY70zGgDOO6Zx5swZiY+Pl6eeesruHF9eXt7m9jSABvw4NEaPHi3Z2dmyb98+2bBhg5w7d06ef/55qa+vb7MBdFRUVPPSp4/5S6kB/E2hkZ6eLjNnzpQhQ4bI1KlT5YcffpDr16/LV1991epzaAANOMsjHcXs2rWr9O/fX8rKylrdhgbQgLM80nkaN27ckN9++03i4uIe34gAOCc03nnnHcnLy5Pz58/Lzz//LK+88ordKf7VV1/13ggB+O7uycWLF+2AuHr1qvTq1UvGjh0r+fn59vcA/INWaOTk5HhvJAB8AteeANBCaADQQmgA0EJoANBCaADQQmgA0EJoANDyt91Bp7T/H+IKCTVXL6baWK17ztbfNl4z4eubRuvl5p8T0/Y8c954zX/M+sl4zVuuMUbrWY3udm3HTAOAFkIDgBZCA4AWQgOAFkIDgBZCA4AWQgOAFkIDgBZCA4AWQgOAd0Pj0qVLMmfOHOnRo4eEhYXJ4MGDpbCwUPdlAPjDtSfXrl2TtLQ0GT9+vOTm5to3FFZtGrt16+a9EQLw3dD48MMP7baKWVlZzY8lJiZ6Y1wAnLB7smfPHklNTbVbM0ZHR8uwYcMkMzOzzefQABrw49A4e/as3fg5KSlJ9u/fLwsXLpTFixfL1q1bW30ODaABPw4Nj8cjw4cPl9WrV9uzjAULFsj8+fNl48aNrT6HBtCAH4eG6tmanJzc4rGBAwdKeXl5mw2gIyMjWywA/CQ01CcnpaWlLR47ffq09O3b93GPC4ATQuPtt9+2e7eq3ZOysjLZsWOHbN68WTIyMrw3QgC+GxojR46UXbt2yZdffikpKSnywQcfyLp162T27NneGyEA376x8EsvvWQvAPwT154A0EJoANBCaADQQmgA0EJoANBCaADQQmgA8I0G0FZ4jFghYeYKRgwV02o8V43X/LHvH0br/eG6I6YVDOtjvObd/0o3XjPsznNG61m3G+WmFDx0O2YaALQQGgC0EBoAtBAaALQQGgC0EBoAtBAaALQQGgC0EBoAtBAaALwXGv369ROXy3Xfwo2FAf+hde1JQUGBuN3u5vWSkhKZPHmy3aYRgH/QCg3VJf6v1q5dK08//bSMGzfucY8LgNOucr1z545s27ZNli1bZu+itNUAWi331NXVdbQkAF8+ELp79265fv26vP76621uRwNowFk6HBpbtmyR9PR0iY+Pb3M7GkADztKh3ZMLFy7IwYMH5dtvv33otqoBtFoA+PFMIysrS6Kjo2XatGmPf0QAnBUaHo/HDo25c+dKUNDfdrdAAL4SGmq3pLy8XN544w3vjAhAp6Y9VZgyZYpYluWd0QDo9Lj2BIAWQgOAFkIDgBZCA4AWQgOAFkIDgBbjZ2c1f1zbeMts3Vt/XmlrrOZt831O7zY1Ga3XeNdsPcV9x/y/q3XL/M9pNTUa7+Vqf33IKRUuy/BJFxcvXpQ+fcw38AXQPhUVFdK7d+/OExrqNPTLly9LREREm/fh+P/UfThU2KgfKDIyUpyKn9M56nzsd1ZFQX19vX3lekBAQOfZPVGDaSvFHkb94/vCG/Co+DmdI9KHfmejoqIeug0HQgFoITQAODM01I18Vq5c6fgb+vBzOkeIQ39njR8IBeDbfGamAaBzIDQAaCE0AGghNABoITQAODM01q9fb3etDw0NldGjR8vx48fFKVQXupEjR9qn1qvWEDNmzJDS0lJxOtULWF1KsHTpUnGaS5cuyZw5c6RHjx4SFhYmgwcPlsLCQnECnwiNnTt32j1j1WfexcXFMnToUJk6dapUV1eLE+Tl5UlGRobk5+fLgQMHpKmpyb6Bc0NDgzhVQUGBbNq0SYYMGSJOc+3aNUlLS5MnnnhCcnNz5dSpU/LRRx9Jt27dxBEsHzBq1CgrIyOjed3tdlvx8fHWmjVrLCeqrq5W585YeXl5lhPV19dbSUlJ1oEDB6xx48ZZS5YssZxk+fLl1tixYy2n6vQzDdWdvqioSCZNmtTioje1fuzYMXGi2tpa+2v37t3FidSsSnXn++t76iR79uyR1NRUmTlzpr27OWzYMMnMzBSn6PShUVNTI263W2JiYlo8rtYrKyvFadStA9Q+vprepqSkiNPk5OTYu5jqOI5TnT17VjZs2CBJSUmyf/9+WbhwoSxevFi2bt0qTkBfxU74V7ikpESOHj0qTqPuK7FkyRL7uI06oO1UHo/HnmmsXr3aXlczDfWebty40W5n6us6/UyjZ8+eEhgYKFVVVS0eV+uxsbHiJIsWLZK9e/fKTz/99Ej3HOms1G6mOng9fPhwuw+wWtRB4E8//dT+Xs0onSAuLk6Sk5NbPDZw4EC7nakTdPrQCA4OlhEjRsihQ4daJLlaHzNmjDiBumZQBcauXbvkxx9/lMTERHGiiRMnysmTJ+XEiRPNi/qLPHv2bPt79cfBCdLS0u77yPz06dPSt29fcQTLB+Tk5FghISFWdna2derUKWvBggVW165drcrKSssJFi5caEVFRVmHDx+2rly50rzcvHnTcjonfnpy/PhxKygoyFq1apV15swZa/v27VZ4eLi1bds2ywl8IjSUzz77zEpISLCCg4Ptj2Dz8/Mtp1DZ/aAlKyvLcjonhoby/fffWykpKfYfuwEDBlibN2+2nIL7aQBw1jENAJ0LoQFAC6EBQAuhAUALoQFAC6EBQAuhAUALoQFAC6EBQAuhAUALoQFAdPwbZ9jnZFTzZCkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "for iii in range(16):\n",
    "    visualize_pca(activations[0][iii])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d8768017-a1f0-443a-aea7-c0ca7f1e8660",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 64 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hx = activations[0][0]\n",
    "\n",
    "for iii in range(64):\n",
    "    plt.subplot(8,8,iii+1)\n",
    "    plt.imshow(hx[iii])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "cb31105c-01ea-48bf-bc25-fd016f59ff31",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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4BCMWAEDowLEAAEIHjgUAEDpwLACA0IFjAQCEDhwLAKBw5GbVlyaVHBpNme5uZI/p82LiOY1iPst6kcEXd7dt/pqUR4LzU1L088CIfL4SImlJkGEDc4UQhWvzsrER4fsuqYS2CtK4xha6L+LzUb+OICnbQrF0jSVEXPtpXv5OWEJUtCD9KqEygiY+wEvKCeGzdoiPDPcs+TmQ0svyReEhNwMATiD4KQQACB04FgBA6MCxAABCB44FABA6cCwAgBMvN2/atIkee+wx2rZtG7W3t9OaNWuy6jLfdNNN9Jvf/CbrmLlz5wZlVoeDMpxg+yyGUAjbkoObyRAKd6dsXvq1DV5KtH1Z1ksrXgI3nS7W5kT5CFzzo2rhgnykbEDFh6yp1OHlVM+sZG29YkJsWWq1haTOEZuPNLaJl5SdPLKo5fFJsZPEX1MxxdI1RiLB2lIp/nrBeXv4axoWnxTbjvC2aFROqq58/thIJPdnkhaSuB/3iEXXZZ4xYwYtWbKEfc+XvvSlwOkMbs8999xwLwMAKKQRy7x584JNwnVdqq+X85QAAMYvozLHsmHDBqqtraVp06bR7bffTocPH2bfm0gkqLu7O2sDAIxtQncs+mfQs88+S+vWraNHHnmENm7cGIxwPC/37/CWlhaKxWKZrampKewmAQDGeqzQjTfemPn/+eefT9OnT6epU6cGo5irrrpqyPubm5tp8eLFmdd6xALnAsDYZtTl5tNOO42qq6tp9+7d7HxMeXl51gYAGNuMenTzvn37gjmWhoaGYR3nlKXJylEz2S3ho2xJ8bJwYO6qZW0D5bzUGik+yNqcKH/OwK54qdEt5q9Zagi1ifuEiXFB+tUYiXb+0MNnsraUy0uiVhkv/ZYKda81EeKTbbs2L5k6Pi9j23lkUSUFlffzknIyzZ83JXyVVDqP9CtEhxs2n4jbdfk+sBT/bGl8W4puzt0HKl9d8ONxLL29vVmjj9bWVtq+fTtVVlYG20MPPUTz588PVKE9e/bQPffcQ6effnqwlgUAUBgM27Fs3bqVrrjiiszrwfmRBQsW0NKlS2nHjh3BArnOzk5qbGykq6++mn784x8HP3kAAIXBsB3L5ZdfLiaJefXVV4+3TQCAMQ5ihQAAoQPHAgAIHTgWAEDowLEAAAonS79ldpNtDg3tLhLCwa0uOW9Cr1nBH2vxKQysFF/Y3UzwGdaDYwWbmRLW5KT586b6eVvS3S+2pzzOtyid5NdwpIv4/nGFwvfFCbkofMTn1+vYQhb6iC+scRHWm2iSUpqCOL9AUwnZ/30hxYPKUzXALOXtkQi/VsU3+VQNZkJO1ZAWjjUo93NgDGMcghELACB04FgAAKEDxwIACB04FgBA6MCxAABCB44FAFA4cjO936HTkA/Z7dk97CFur5x9zqznj62o4W3RAT4rfuKQUDBeR+H38Nn2DUuQPaXk/wYv4VrVfPZ1TaqLl6r9FH/ehP8Ba3N7hGLyA7zEr1Fp/hH0BZlWKjavhELqwXkN3m66fE4F1+Xb49l8v/tKTmURMfllB5bFPz8U4ccFqkS+plPLpxipPVyTc39qgJeoPwtGLACA0IFjAQCEDhwLACB04FgAAKEDxwIACB04FgBA4cjN8QNRsqyheXLNug72mO7ENPGcbvR/WVt5Fd8VFQfPY21HKmTfnBKSpXs+nwe4XygGbtXzfdB4SpvYntLD57C2Ti+3zKgZoK2srWRAkKkTcjmXtCC1FkcEqdVzeJuQ9V5jCWn6bUGqtgU53onyUrQpVZbQknwFf6w9gV8GUVbJn3dCpSwNN5YeYG3mn3M/B3EzTqvFsx51jmN8HwAAHDNwLACA0IFjAQCEDhwLACB04FgAAKEDxwIAOLFyc0tLC73wwgu0c+dOKioqoksuuYQeeeQRmjbtU5k3Ho/T3XffTatWraJEIhHUbH766aeprq5uWA1LFJeTZQ0N8XUSncJRciLp0q73eVsfH4Vb4fGasVsiF7v3y/nI30TvIdaWVLxc6FS/x9rKE/z1NGb7DNbW1cc/DvF6Xp5MmXwotuFLFdiJog5v99J8QXR/gJexU3yhzk+OdYVE0uW8pFxyCi9/1zXwbY1N4BOGa8pL+faURj5ibRN8PsF5Vfxj8ZpV7Xx08/tvf1pC+Wj6k/KzNeIRy8aNG+mOO+6gLVu20GuvvUapVCqozdzX92kj77rrLnr55Zdp9erVwfv3799P119//XAuAwAopBHL2rVrs16vWLGCamtradu2bXTZZZdRV1cXPfPMM7Ry5Uq68sorg/csX76czj777MAZXXTRReG2HgAw/uZYtCPRVFZWBv9qB6NHMXPmzMm856yzzqJJkybR5s2bc55D/1zq7u7O2gAABepYfN+nRYsW0ezZs+m88z5Z8t7R0UGRSIQqKrLnK/T8irZx8zaxWCyzNTXJWeAAAOPYsei5lnfffTeYpD0empubg5HP4NbWJse6AADGaRDiwoUL6ZVXXqFNmzbRxIkTM/vr6+spmUxSZ2dn1qjlwIEDgS0XrusGGwCgQEcsSqnAqaxZs4bWr19PU6ZMybLPnDmTHMehdevWZfbt2rWL9u7dSxdffHF4rQYAjJ8Ri/75oxWfl156icrKyjLzJnpuRK9r0f/efPPNtHjx4mBCt7y8nO68887AqQxXERpQtWSqoVnsPcVnmXddPpO8pqiTX2tQvpP3sYm6dtZWEZOLnpcU85n4O6wy1tad4tsTM//G2txW/nqariOfZ229/btYW38XH77fOcBf082ToT4t/G0z4vz6mJTNPwdOXVxewzGRb1OtUOWgtpJ/fqqdg6wtJmdNoPID/BtKD/HXLNrPP3uR/VXiNc3DuX9BaP73vQty7k+n+WfguBzL0qVLg38vv/zyrP1aUr7pppuC/z/xxBNkmibNnz8/a4EcAKBwsIf7Uygf0WiUlixZEmwAgMIEsUIAgNCBYwEAhA4cCwAgdOBYAACFk6W/R9WToYqH7C/mE5qT4/Kh/Zp4VFiI18lLv1HvH6zN6LbEa1aW80XjjYYS1lbFN4cmR/gM9b1pXkbUdFt8e5tifHqIwxOF/jH4+ygRrqeZYPLXLDb4Y2MlfKqBWiEDvWaSkKqhIcGnOKjby18z1so/W0a7LP16vbxs7Cc/icPLSZofF/iCLZ8Q4/m5lw94fh7d/CgwYgEAhA4cCwAgdOBYAAChA8cCAAgdOBYAQOjAsQAACkdu9sglg4ZGt8YTvOTnkZxFPF7N2zrP5OXCz33MS6Kq5z/iNfsdPkK3IcVn6S+O8lnUJwkfW3etHNlbeuom1lZyNl/lIHYq3wdGgo96tQf4+9BEE/x5rSR/n5X9h1lbQ3vubIWDVP2Dl3DtNr5ag3GIt/l9vOSeUvwzEBxrCRHgFr++wuK7jhS/IuGTYwW52TbMYe3PBUYsAIDQgWMBAIQOHAsAIHTgWAAAoQPHAgAIHTgWAEDhyM3KLiayhkY3J4UEy3ElR9ImhKLx6TJenzOsmaytQVabKX54N2vzhSLsVR/y54wRL3tWk9wHNWU7WJvzH17arCzjI1tLfF5SNtJyaRcrzX+eRXG+PbEj/HGRA6eJ10weEQrK+3yksTJG9lVSllwU3jYFSZmEi/rCuCBPFllDOK/h5Y5uNjxENwMATiD4KQQACB04FgBA6MCxAABCB44FABA6cCwAgBMrN7e0tNALL7xAO3fuDGo1X3LJJfTII4/QtGnTMu/R5Vc3btyYddx3v/tdWrZs2bAaFil3yLSHSn99/insMQPUJZ7T7znC2ko7eB/b2zOLtXUn+WTZmkqLj2C29/OR2tE0L3sOuHxbSwy5lvTUeDdrsxL84+D5fJJuIR822Y6sezrCnzZbkM77hSTdfVLYr75Pi7+oKbTHEJJ7K/E+fLE9hiAbG+JXVLpPuQ9kuKUXeUKmRzpi0Q5DF4bfsmULvfbaa5RKpejqq6+mvr7sdQy33HILtbe3Z7ZHH310OJcBABTSiGXt2rVZr1esWEG1tbW0bds2uuyyyzL7i4uLqb5eLkMBABi/HNccS1fXJz89KiuzE+f89re/perqajrvvPOoubmZ+vv5BEyJRIK6u7uzNgBAgS7p932fFi1aRLNnzw4cyCBf//rXafLkydTY2Eg7duygH/zgB7Rr165gboabt3nooYdG2gwAwHhyLHqu5d1336U333wza/+tt96a+f/5559PDQ0NdNVVV9GePXto6tSpQ86jRzSLFy/OvNYjlqamppE2CwAwVh3LwoUL6ZVXXqFNmzbRxIkTxffOmvWJorJ79+6cjsV13WADABSoY9H1Xu+8805as2YNbdiwgaZMmZL3mO3btwf/6pELAKAwsIf782flypX00ksvUVlZGXV0fJINPRaLBeta9M8dbf/yl79MVVVVwRzLXXfdFShG06dPH17DvDiZOdYNKJdPGZBWpeI540IB97jH23p6O1mbP+Ej8ZokZOlvcviRmoryhcuTgs1OyaHtvsVnkzeE9TGOx6/FUHzUP5Evr2PxPCktAP+ZmEJie8OSr2kK61ykzBuGkKXeNIQ0BIaskQiH6sYKB6qRp02Q2susgZFSLRyXY1m6dGlmEdzRLF++nG666SaKRCL0+uuv05NPPhmsbdFzJfPnz6f77rtvOJcBABTaTyEJ7Ug+u+oWAFB4IFYIABA6cCwAgNCBYwEAhA4cCwCgcLL0Dwy4ZNg5pFqb1xnTdu7s4oPE+2pZ2wHipV/T52OdJh5pFa/ZneCDMdvKzmBtJTVtrG1qmk+3EOmT+0BShi2X71tbSBlgCFK0mRZ04UCqls5LI7ompWVZ1EvzIoTUWssQJHdrZGka8tklpVqUqfNJw4LZYLRqbn8uMGIBAIQOHAsAIHTgWAAAoQPHAgAIHTgWAEDowLEAAApHbrZjREaupOAxXhB0/Jh4zvjHp7K2j4WUmKqMj252vaGF64/G6OElykSSr/w+YLaztsYkf59uQpabLTvJ2kybfxxsW4h8FuTSPAnziWy+f3yLF8dNKW5NVrjFyF/f5xssqNSkfOE+PLkT0kKKf0sogWBINlmLJlM6VnnD2p/z/Mf8TgAAOEbgWAAAoQPHAgAIHTgWAEDowLEAAEIHjgUAUDhy84Sqg2RFeofsT9bwkb2OL0u/pnUma+t7/2PW5vfs589Zw8u3mt4KvosnHephbZEkb9s9UMfaSiLy34qaKJ9su0qI3k0JcnNRhC9EX+TKhcQjJn9NW5B+fUGiVcJ9aAxLkE0FfdwUzmt4/DlVSv5MfMHupYX7lNTfPBK3pXi758WHtT8XGLEAAEIHjgUAEDpwLACA0IFjAQCEDhwLACB04FgAAKEDxwIACJ1h127W2wcffBC8Pvfcc+mBBx6gefPmBa/j8TjdfffdtGrVKkokEjR37lx6+umnqa6OX3fBUawOkuUPTQFgDfD6uyUV0NZrDYqqWVu8tIa1dX7Inzc18G/xmslJ+3hbzQT+QMWvDUkISxRK43xFAU1fL78WoyfBPw4lvX2szUl1sTa7Vn7EJtTwa4+qovwamCKLP6+R7++lUKjeUCNLU6BM4T6jeVIYRIXs/8L6GF8oueDzy70CUsLamaSd+7NOkvxsjXjEMnHiRHr44Ydp27ZttHXrVrryyivpmmuuoX/+85+B/a677qKXX36ZVq9eHdRw3r9/P11//fXDuQQAoNBGLF/5yleyXv/0pz8NRjBbtmwJnM4zzzxDK1euDByOZvny5XT22WcH9osuuijnOfXIRm+DdAsJlwAA43yOxfO84CdPX18fXXzxxcEoJpVK0Zw5czLvOeuss2jSpEm0efNm9jwtLS0Ui8UyW1NT00ibBAAYq47lnXfeodLSUnJdl2677TZas2YNnXPOOdTR0UGRSIQqKiqy3q/nV7SNo7m5mbq6ujJbWxtfARAAME6DEKdNm0bbt28PnMDvf/97WrBgQTCfMlK0g9IbAKCAHYselZx++unB/2fOnElvv/02/exnP6MbbriBkskkdXZ2Zo1aDhw4QPX1fP1iAMD447jTJvi+H0y+aifjOA6tW7eO5s+fH9h27dpFe/fuDeZghku0msjOMZCJFTWMSCrUpMqyf6YdTVFtGWtTs3i5uaxHzlweifMyrZfk5ebDfZWs7YhQ0bs8T1b8on5eat2f5O8zEi/lbUIlgsihg2J7onSEtZWl+WsWpaOszczzHIhp+qXs/2KhdUmKVnJrhFUSvqVGNJEhZJz45JrEf2b/OuW9nPvjHv8sH5dj0fMhes2KnpDt6ekJFKANGzbQq6++Gky83nzzzbR48WKqrKyk8vJyuvPOOwOnwilCAIDxybAcy8GDB+lb3/oWtbe3B45k+vTpgVP54he/GNifeOIJMk0zGLEcvUAOAFBYDMux6HUqEtFolJYsWRJsAIDCBbFCAIDQgWMBAIz/ZNrqv7PyXnIgp900EyNWhdKKTwbsER/wpoRrppN8cmqNmRTqDyf5RNzJlJDUOcW3J5HOE/Dm8e31PF6e8H3+UfEFJcVTcrJxRbzdEo5Vwmd9XKoQjYIqpPKoQlItackoHUcjV4U49Sfh9x3T/WgMdSzv+n9k3759WNYPwEmMXh2vYwPHlGPR62J0VHRZWRkZhhEEJer4IX0zWsIG2aB/ZNA/4fWRdhV6mUljY2Og/o6pn0K6wbm8ob5hOBYe9I8M+iecPtLLTI4FTN4CAEIHjgUAUHiORUc+P/jgg4iARv/g+RlD37GTbvIWADD2OelHLACAsQccCwAgdOBYAAChA8cCAAgdOBYAQGE5Fp3X5dRTTw3yvMyaNYv++te/UqGyadOmoK6TXk6tQx1efPHFLLsW93RVyoaGBioqKgrKsLz3Xu4Ug+MRXUbm85//fBAKUltbS9dee22QGvVodKXOO+64g6qqqoJKEzohmc7JXAgsXbo0SMw2uLpWZ3b805/+NGp9c9I6lueffz5Ic6n19b/97W80Y8aMICOdzmJXiOj6TboPuCRajz76KD311FO0bNkyeuutt6ikpCToL/3AFAK6UoT+YujieK+99lpQ4+rqq68O+m2QQq7UOfH/u4qpOkm58MIL1R133JF57XmeamxsVC0tLarQ0R/bmjVrMq9931f19fXqsccey+zr7OxUruuq5557ThUiBw8eDPpp48aNmf5wHEetXr06855///vfwXs2b96sCpEJEyaoX/3qV6PSNyfliEWXEdGe9eiqijo4Ub+WqioWKq2trUFRuKP7SweL6Z+Phdpfuu6VRid214y0Uud4xAupiumYim7WHDp0KLh5XUXxaPTrnTt3nrB2nawMVprM1V9SFcrxik69sWjRIpo9ezadd955wb6RVuocT7zzzjuBI9E/j/U8ymAVU12AMOy+OSkdCwDHg55reffdd+nNN99ER45iFVOJk/KnUHV1NVmWNWRWGlUVczNYaRL9RbRw4UJ65ZVX6I033sjK66P7aLBSZ6E+U5H/VjHVxQW1iqbFAF3FdDT6xjxZO0DfvK6qePTwVr8eSVXF8c6UKVOCB+Do/tJZwbQ6VCj9pee0tVPRw/v169cHfXI0R1fqHOR4KnWOB/wcVUxD6xt1krJq1apA1VixYoX617/+pW699VZVUVGhOjo6VCHS09Oj/v73vweb/tgef/zx4P8ffvhhYH/44YeD/nnppZfUjh071DXXXKOmTJmiBgYGVCFw++23q1gspjZs2KDa29szW39/f+Y9t912m5o0aZJav3692rp1q7r44ouDrRC49957A4WstbU1eD70a8Mw1J///OdR6ZuT1rFofv7znwc3G4lEAvl5y5YtqlB54403Aofy2W3BggUZyfn+++9XdXV1gUO+6qqr1K5du1ShkKtv9LZ8+fLMe7ST/d73vhfIrMXFxeq6664LnE8h8J3vfEdNnjw5+C7V1NQEz8egUxmNvkE+FgBA6JyUcywAgLENHAsAIHTgWAAAoQPHAgAIHTgWAEDowLEAAEIHjgUAEDpwLACA0IFjAQCEDhwLACB04FgAABQ2/wfmahlbt6pUOwAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Kg9w8Po+Qu0POmG/wWRPIaOClcVeVh7UFArxN4RdSiOhmepuLeT/tMc75kwAAcI7AsQAAHAeOBQDgOHAsAADHgWMBADgOHAsAIHvkZpXiUm19MIRIYyPDMYVC2B5NyNLPJ0MnIyFL3IYg67mETOmJBB/xGhY6FNblcOuigsOs7bTWwNre2/M+a9t9qI21JSfLt1j5xAmsreq/+MLv4718f4raImKb8Vb+uF2n+QjmgHC9/MF21uZJyiVtLJeXtekmb/MIp+nLkFHfm+Ql+a5E+vvLTGT4gvUATywAAMeBYwEAOA4cCwDAceBYAACOA8cCAHAcOBYAwMWXm7dt20ZPPvkk7d69mxobG2nDhg296jLfdttt9Pvf/77XPvPnz7fLrPbX4+n9yzFNZoZkv24pmbbFH9gQdOxkXG6zS5CxXTp/3GiU3y8a5U8kGpejm4+38UmxIy28BPme96v8fpNms7bqqbwUrQiV8fJ4RQ4/tt7TvBwfDcsJxamD//80R+cTcWvEtxkRbAGfPAZRD5+IO5DDF5sfGeMjx42ovOxAj/PXOsFE8ycMYd3F2cenfqLqMk+fPp1WrlzJfuarX/2q7XS6txdeeKG/zQAAsumJZcGCBfYm4fP5qLy8/EL6BQAYwgzIHMuWLVuotLSUqqur6e6776aWlhb2s/F4nMLhcK8NADC0cdyxqJ9Bzz//PG3evJkef/xx2rp1q/2Ew81T1NbWUjAYTG2VlZVOdwkAMNRjhW699dbUvy+//HKaNm0aTZgwwX6KueGGG/p8vqamhpYvX556rZ5Y4FwAGNoMuNw8fvx4KikpoQMHDrDzMQUFBb02AMDQZsCjm48ePWrPsVRUVPRrPxXYnC64mS5AbtaFSGPNFJJpS0mEM9SLtjShTRffZtLio1oTBaNZW07uOLk/LR/zbZr8/JZrjI+1BfP5hM+FnrFif0JRPiq4TGtibT4h0lazCsU2A8I1y3Hzkqo7yX9dkkKUe4cuR8C7C/nlA6PH8WPbcYyXosMNfFJwhSfAy+NdzNhaSX3gHEtHR0evp4+6ujras2cPFRcX29ujjz5KixYtslWhgwcP0v33308TJ06017IAALKDfjuWXbt20XXXXZd63T0/snjxYlq1ahXt3bvXXiDX2tpKoVCI5s2bRz/72c/snzwAgOyg347l2muvJUt4lHzjjTcutE8AgCEOYoUAAI4DxwIAcBw4FgCA48CxAACyKUu/ZW99MK3z9pNuYd2IW1iqYggF2q0MpQEsoTKAVOHe0ngVrbS0hLWNSMprOML7+PVEBw7y51I4j1/fMfKSOtZWGpZTBuSf4m3edn5fS8gynytkvVcUePjr2dXJn2d7F7/Ox9L5VA0+uSY8afn8vu5x/P0zWvsCa+vqnCy3KaSdaDyRvlpDZ5xP03A2eGIBADgOHAsAwHHgWAAAjgPHAgBwHDgWAIDjwLEAALJHbia7qHVfOVaKUyI9Q5Z+oai3xhTC7k6fydGVIW1C0s2Hvee7i1hbnjvI2qryeUm5KCZnZ9/TzqdVOHCMl5s9lx5ibb5pfOpRV1Gz2B+9g68q4G738DaDr4ge00/JWfF1PqVAJMFLv3FLSNUgSMqBDPG3buFr6PPyBeyL8oR0FclJYptGMoe1mR+n709ESBtxNnhiAQA4DhwLAMBx4FgAAI4DxwIAcBw4FgCA48CxAACyR27WLM3e+iCou2mjoXvgFqKJSah3nUjyMrbh4SU/xYhgiLWNFUqdlAf545Z4+ejc3KRcSVJ38/3Zf3A8a9v3t2OszTv5MGszq4/J/Snm5fG4xtv+fZw/z86onKG+QxijuJvXjV3CEoBiH78EIE+X9eY8k5fcQ4V+vk3vEdYWOC0vO9CO830yG9Lf76YRo3MFTywAAMeBYwEAOA4cCwDAceBYAACOA8cCAHAcOBYAwMWVm2tra+nll1+mffv2USAQoKuuuooef/xxqq6uTn0mFovRfffdR+vXr7ejglXN5meffZbKysr61TGNLHvrg1T4PVN0s6BVG0JR76TFS3MF+flim0UlfALiUfm8JFgoRGLndPB99bbKBcirCnh7lefz0rlnc2wXX4C89ZX/Zm3RhbL8fbSAL1KvxXjZuLWdXx/QFeMlWoUe4O9Ff1EeaysI8LYSH99mkbBcQTHSzd9DBUW8xB0TEstHE41im+42/qsfpfTSeYz4KP8LemLZunUrLVmyhHbs2EGbNm2iRCJh12aORD4PYb/33nvptddeo5deesn+fENDA9188839aQYAkE1PLBs3buz1eu3atVRaWkq7d++ma665htra2ui5556jdevW0fXXX29/Zs2aNTR58mTbGV155ZXO9h4AMPzmWJQjURQXF9t/KwejnmLmzp2b+syll15KY8aMoe3bt6c9hvq5FA6He20AgCx1LKZp0rJly2jOnDk0depU+72mpibyer1UWNj7N5qaX1E2bt4mGAymtsrKyvPtEgBgqDsWNdfy0Ucf2ZO0F0JNTY395NO91dfXX9DxAABDNAhx6dKl9Prrr9O2bdto9OjRqffLy8upq6uLWltbez21NDc327Z0+Hw+ewMAZOkTi0pkrZzKhg0b6K233qKqqqpe9hkzZpDH46HNmzen3tu/fz8dOXKEZs+e7VyvAQDD54lF/fxRis+rr75K+fn5qXkTNTei1rWov2+//XZavny5PaFbUFBA99xzj+1U/hOKkCtD8W1LWMeStPhC4i4vP0yFPj5bvCIaO87a2mL8Ghfd4te4+BN8iL7X4LOvK4py+ULrc77Ir1U59u581la/ic/SfyJHLgp/6v/x6z86cviJ/Eg5f000jU9HoQjm8tc6zyVUctD4LP1unS9SbyblJ3KPPoFvM8D/3x9tPcnaThJfbUBRGODvLyM//fgYSf4cL8ixrFq1yv772muv7fW+kpRvu+02+99PP/006bpOixYt6rVADgCQPfTLsYg1fT7D7/fTypUr7Q0AkJ0gVggA4DhwLAAAx4FjAQA4DhwLACCLsvSzaROkNP3y5LImVO52u/mhCJi8NHcqLMupDRovmXpO8LaOUXxGdKuIX52czDDBHuvkQ/j1ie+ztumuT1jbznVnQjrScfSNsWJ/krN4eTxayUumupuXfl26nDoiKixLMIXC74bJH1cLpF8AqsjxXkESlTp/7xW17GNtkVb+/nEZcpZ+dy5/f3WO7Ej/fuLc5WY8sQAAHAeOBQDgOHAsAADHgWMBADgOHAsAwHHgWAAA2SM320pzOrVZ2kfLkKVfcKOazsuMXVFeums5LTZJTW4+ejfQIwn52XR28v057uOjWn1+uSB6wl3B2opdU1jbJZV8m5PLeOnygwNjxP4UfipIuKW8LhxzSXKzLLlbglRtmbykqrkCrK0sxEvuU3LOpG7lqP7kA9aWqOcjx7UI39ewR5aG24121na6LH10c7RLlrB7gicWAIDjwLEAABwHjgUA4DhwLAAAx4FjAQA4DhwLACB75Gbtsz99EJREPYPMqGnmeSnVZsLD2rq65OTVMYNPpGxE+f7EonzCZ6+7iLXl0mVif8pCvNw8LvB5KZezKW3j+7NgKn8b7ftgstifzka+QJ115F+s7WQeX/S8s0hOcJ508UnMTeLP05fLF5OvLOPHYGwLHzWuiB8+ytoSrUJSdSGKuy1syG0KjxSJ8vTGpLTTWeCJBQDgOHAsAADHgWMBADgOHAsAwHHgWAAAjgPHAgC4uHJzbW0tvfzyy7Rv3z67VvNVV11Fjz/+OFVXV6c+o8qvbt26tdd+P/jBD2j16tWOJNOWc0VnrtTI78nv6xZkbM2SfbOQh5sicV7a1LRc1pabU8XaQvkjxf6END5BdV6Ul2ndsTN1utMxwn2EtU0o/4LYnxP+y1mb5yQvVXvq+ejdBjmgmqKT+NrXnsB41jauiE+YPa7zGGvLOcpHfysSUf7+0t38cgajk79e7e3yV9sI8hHX2oj0SyS02AAl01YOQxWG37FjB23atIkSiQTNmzePImeF/99xxx3U2NiY2p544on+NAMAyKYnlo0bN/Z6vXbtWiotLaXdu3fTNddck3o/JyeHyst57w4AGN5c0BxLW9uZmjrFxb0fq/7whz9QSUkJTZ06lWpqaqizk3/8jsfjFA6He20AgCxd0m+aJi1btozmzJljO5BuvvWtb9HYsWMpFArR3r176cc//jHt37/fnpvh5m0effTR8+0GAGA4ORY11/LRRx/RO++80+v9O++8M/Xvyy+/nCoqKuiGG26ggwcP0oQJE/ocRz3RLF++PPVaPbFUVvLxIwCAYepYli5dSq+//jpt27aNRo/mA9cUs2bNsv8+cOBAWsfi8/nsDQCQpY7Fsiy65557aMOGDbRlyxaqquJlz2727Nlj/62eXAAA2YG7vz9/1q1bR6+++irl5+dTU9OZtQ3BYNBe16J+7ij71772NRoxYoQ9x3LvvffaitG0adP61TGVxSBtUXhpH02eixZrxgtpE3SpH4a8RqHD5O1dGp+OwecbwdrGFvFPeKM8csqA0jAfal8UTrK2jmP8pPqpZDNrKyxOX2C8m0ABn1LgeIJXFiONpfxBffz6IEXZlFGsbXTZRNY22+IrFUw6wo+7flS+L5MJfk2Jj/i1I8lYnLd1yYt5dFeQtRVbrWnfjxLf3gU5llWrVqUWwfVkzZo1dNttt5HX66U333yTVqxYYa9tUXMlixYtogcffLA/zQAAsu2nkIRyJGevugUAZB+IFQIAOA4cCwDAceBYAACOA8cCAMieLP3ngy7qyXLOBVPQm60En9U9GuGLditafLykbAZ5OfWSEn71ccjPS8bFXXxcliIvwcvGxkm+UHjjYV5qPdjGy9SxUXK2+HwXP35WPn8uR0p5OV4jXjJWTHfzEvgk839Y26hjfGqEZIuw7KCTT4GhKPTyywfcQuH3jiRfNaAwn5fUFSNy+etpHEk/Pp1x+Vr2BE8sAADHgWMBADgOHAsAwHHgWAAAjgPHAgBwHDgWAED2yM1KOc6kHvdF3sHkVVoyTV5KCwsy4wctvE1xaAofRTp+Ch+hWzGBlxkrW3lpU2vjC4wrWuO81OqL8CUFmlt5ybTdxVcGyC2VbzFXLn9RAh5+3ymVJ1hbnPxim5Un+GsW6OSLzbe383K83xSqPOQKofNqXy2Pt3XysnppEX9MLflPsc3T7ekjmBWHWtKfS7Tr3KOb8cQCAHAcOBYAgOPAsQAAHAeOBQDgOHAsAADHgWMBAGSP3HxGOk5TFP6CjsjLfprFD8WhQ3xy5l0HeTlZ0fnlAtZWXc3vl+vnJdFo+F+s7WiLnLx6RIA/z+I8PqlzIsAXUncX8FJ0QY58xZI6HxlNFn+9Qj5eFk4Qn9zbPuxJPuI8HuXlb7ebl7EjcT5amDRZpnXn8tK5V2tgbe0tfALvpuNykvc2k79mp8z0UdMxk1+OcDZ4YgEAOA4cCwDAceBYAACOA8cCAHAcOBYAgOPAsQAAHAeOBQDgOP2u3ay2Q4cO2a+nTJlCDz/8MC1YsMB+HYvF6L777qP169dTPB6n+fPn07PPPktlZXw2cbEofNolEPy6CF2q7G5n4hfQXaypOXENa4vF5HMbX8lr/+V+PnRdb3qXtb1//DBrM2L8eSjcFfxaFa/GZ8zvKuGP6SW+zYSQ+kChGWIuC9aUFJa/eNzy2hlN469JMsr/X2t4+f50JgKszbLkIvVu92nW1mrw63WiEWl85EoFpSP5LP75ZvrqCJ1x98A8sYwePZoee+wx2r17N+3atYuuv/56WrhwIX388ce2/d5776XXXnuNXnrpJbuGc0NDA9188839aQIAkG1PLF//+td7vf7FL35hP8Hs2LHDdjrPPfccrVu3znY4ijVr1tDkyZNt+5VXXpn2mOrJRm3dhMN83RsAwDCfYzEMw/7JE4lEaPbs2fZTTCKRoLlz56Y+c+mll9KYMWNo+/bt7HFqa2spGAymtspKvlAXAGCYOpYPP/yQ8vLyyOfz0V133UUbNmygyy67jJqamsjr9VJhYe+YEjW/omwcNTU11NbWltrq6+vP70wAAEM3CLG6upr27NljO4E//elPtHjxYns+5XxRDkptAIAsdizqqWTixDMzzjNmzKB3332XfvnLX9Itt9xCXV1d1Nra2uuppbm5mcrL+RrFAIDhxwWnTTBN0558VU7G4/HQ5s2badGiRbZt//79dOTIEXsOpr8cov+h/DTday7gpTnT5MPhbdy8XfPyQ5E7eyprm1ixRGxyso8Pib+kng/vbz/EZ24/dWIGa8svl+XmsMWPX0znQ/TDFXwYftLFh+B7cvh0CwrL4mVaLclfL39CkpTlMfAIqxI8Fp/iwGXwMrWV5FMqGJagjSvZWBgDPcaPnyufP2bhSLlSQWEOPz3RkIimfT8e4ytHXJBjUfMhas2KmpBVpRCUArRlyxZ644037InX22+/nZYvX07FxcVUUFBA99xzj+1UOEUIADA86ZdjOX78OH33u9+lxsZG25FMmzbNdipf+cpXbPvTTz9Nuq7bTyw9F8gBALKLfjkWtU5Fwu/308qVK+0NAJC9IFYIAOA4cCwAgOGfTNuyzsz2d0TSz6RHYnyNZdPM4CfdQjJtIRYu2sXPhieScvLqeJRPeByNpJ99V8SivDoRi/Eqg6dTHoNOP38uyU7+uNEYr8LEhfFJ9gjXSItw3ITBX2tdSquelFUhQdwhQ1KFhMTfltBXI4MqpCX5NvU4P7Yu4TxcljwGPpKudfo2o7FEr++ohGady6f+gxw9ehTL+gEYxKjV8So2cEg5FrUuRkVF5+fnk6ZpdlCiih9SJ6MkbNAbjI8Mxse5MVKuQi0zCYVCtvo7pH4KqQ6n84bqhOFYeDA+MhgfZ8ZILTM5FzB5CwBwHDgWAED2ORYV+fzII48gAhrjg/tnCH3HBt3kLQBg6DPon1gAAEMPOBYAgOPAsQAAHAeOBQDgOHAsAIDsciwqr8u4cePsPC+zZs2if/zjH5StbNu2za7rpJZTq1CHV155pZddiXuqKmVFRQUFAgG7DMunn35K2YIqI/OlL33JDgUpLS2lG2+80U6N2hNVqXPJkiU0YsQIu9KESkimcjJnA6tWrbITs3WvrlWZHf/6178O2NgMWsfy4osv2mkulb7+3nvv0fTp0+2MdCqLXTai6jepMeCSaD3xxBP0zDPP0OrVq2nnzp2Um5trj5e6YbIBVSlCfTFUcbxNmzbZNa7mzZtnj1s32Vypc/R/uoqpNUiZOXOmtWTJktRrwzCsUChk1dbWWtmOumwbNmxIvTZN0yovL7eefPLJ1Hutra2Wz+ezXnjhBSsbOX78uD1OW7duTY2Hx+OxXnrppdRnPvnkE/sz27dvt7KRoqIi67e//e2AjM2gfGJRZUSUZ+1ZVVEFJ6rXUlXFbKWurs4uCtdzvFSwmPr5mK3jpepeKVRid8X5VuocjhgOVTEdUtHNipMnT9onr6oo9kS93rdv30Xr12Clu9JkuvGSqlAOV1TqjWXLltGcOXNo6tQzpVvOt1LncOLDDz+0HYn6eazmUbqrmKoChE6PzaB0LABcCGqu5aOPPqJ33nkHAzmAVUwlBuVPoZKSEnK5XH1mpVFVMT3dlSYxXkRLly6l119/nd5+++1eeX3UGHVX6szWe8r7WRVTVVxQqWhKDFBVTAdibPTBOgDq5FVVxZ6Pt+r1+VRVHO5UVVXZN0DP8VJZwZQ6lC3jpea0lVNRj/dvvfWWPSY96Vmps5sLqdQ5HDDTVDF1bGysQcr69ettVWPt2rXWP//5T+vOO++0CgsLraamJisbaW9vt95//317U5ftqaeesv99+PBh2/7YY4/Z4/Pqq69ae/futRYuXGhVVVVZ0WjUygbuvvtuKxgMWlu2bLEaGxtTW2dnZ+ozd911lzVmzBjrrbfesnbt2mXNnj3b3rKBBx54wFbI6urq7PtDvdY0zfrb3/42IGMzaB2L4le/+pV9sl6v15afd+zYYWUrb7/9tu1Qzt4WL16ckpwfeughq6yszHbIN9xwg7V//34rW0g3Nmpbs2ZN6jPKyf7whz+0ZdacnBzrpptusp1PNvD973/fGjt2rP1dGjlypH1/dDuVgRgb5GMBADjOoJxjAQAMbeBYAACOA8cCAHAcOBYAgOPAsQAAHAeOBQDgOHAsAADHgWMBADgOHAsAwHHgWAAAjgPHAgAgp/lfW5e9JZxUv+AAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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VmKttT/vxydiWhVNHVOTg1Aiuq/E2FTMnYjftxC+OQZv/xGFoSwlgt3qk7YC2PXVnZkNbYeVIaJuehs/1ttQa7T4jBj6f3ljibPxmjEXhCSEXEN4KEUIch8JCCHEcCgshxHEoLIQQx6GwEEKSx90slvvL5etvW164ytE9OHJXUVxeDm1ZV0WhrfxdHKHs26vPCG9dht2FrXk4xWe8CZ8an6aYfKoHu34VrjRcVcBn4YjYeAwXNvfV4fbk+rHbXHHaPQHaUqL4fM4Yg8+XMSOi3efkCL4O3B/jKOVgXTu0tYZwhQhzhL4PCvPwOfPux1MoUivxdIXagH7aweEUPIUiNZq4PWaU7mZCyAWEt0KEEMehsBBCHIfCQghxHAoLIcRxKCyEkAvvbt66das8/fTTsnv3bqmpqZH169d3q8t85513yp///Odu68yfP98us9onlCc2gTfWSvTmv4i2Ypeo4siWALQVzsAJoQ9cOxPaUrZN0u7zagsnSr6k5GNocx3ELlNXB+4DI6aP8LYShYz/C48Xuz0DmkhjTxivl2fokzrXF+H+CbdjN39JDPdPdugz7T5PV7dAW+sxP14xhCPVO9Kw6zeQq3c3X5LdDG2fn8BfUfMojhyfOrZYu88zxdXQlhJM3J54dACTaau6zNOnT5eVK1fCz3zrW9+yRadzeeWVV/q6G0JIMo1YFixYYC86/H6/FBbiMh2EkKHNgDxj2bx5s+Tn58uECRPk3nvvlcbGRvjZcDgsLS0t3RZCyODGcWFRt0EvvfSSbNy4UZ588knZsmWLPcKJxxNnPSsrK5NAINC1FBfr7w0JIUkYK3THHXd0/T916lSZNm2aXHLJJfYo5uabb+7x+dLSUlmxYkXXazViobgQMrgZcHfzuHHjJDc3VyoqKuDzmKysrG4LIWRwM+DRzSdOnLCfsYwYMaLPybQTepYt7E61XHqdrNpbBG0N5fuhLeOmE9B26v/pk0X7G3AUacYRHC3b5k6c0FgRNnAf+EHd3U5cFt6uW7PdtFTc1mgEH2M8iGs+K/KKm6Ctowm7YX0ncf3l3H+mavfpLsDHEhZNJLuB3cYjc3C/BgI4Ylrh6cDPFS8dhd31Lcdwv4+rwlMrFBWj8HUS7EgcOR6L4ojy8xaWtra2bqOPyspK2bNnj+Tk5NjL448/LosXL7a9QocPH5YHH3xQxo8fb89lIYQkB30Wll27dsmNN97Y9brz+ciSJUtk1apVsnfvXnuCXFNTkxQVFcm8efPk17/+tX3LQwhJDvosLDfccINY9n1KYt59993zbRMhZJDDWCFCiONQWAghjkNhIYQ4DoWFEJI8WfotNd/CSqB7id47h5QKilj7MGg79G42tOX/H1zw+/QCnJ3d3u6fcTBmxgFchN3rx2kKol6cMsCK4SoGCp/mlBuavtUR12Rvbz+jn/sQHVmBtzsBF2/vOIqz0IePjtXus9B3BtpC6bjfgy48byQ9jm2uZv11GQzhuSq5ATy3aFgmno8TatBfB8UdeL7OyXDi8JtYLPH7ieCIhRDiOBQWQojjUFgIIY5DYSGEOA6FhRDiOBQWQkjyuJtxln4cnt6Lt1m77rFPcRj+uG2V0JY6C2faV+z94ipoC2zDqSQujeO8ND4fdjNGRO/etTQeQ58LXw7uOM7EHw3j9AY1Dfrw/SYvrqzgnYp/91wpON2pr0KfOsI6ji+U9Czs4o57cOcFW3H/GH7973dI8zX0uXFbs0bg7XacxFMZFNNDeJ9W+GjC9yOxAczSTwghvUFhIYQ4DoWFEOI4FBZCiONQWAghjkNhIYQkkbvZdg1rXMuJ0GSg79okIKYpKP/pmxOhLet/b9fu8tC1OMo0sxlHrno+xRUFxsawC9efiqNzFVEDu0U1td3FE8GdF2vDl1HUg6NoFXXhPGgr1EwfKByBM9+nNOqz4nc0YFe+UYej1VOLcd/WenBlAE9vEecZ+Pc9GsN9O2osXi8W1E878DTjNpltic91KH7u30eOWAghjkNhIYQ4DoWFEOI4FBZCiONQWAghjkNhIYRcWHdzWVmZvP7661JeXi6pqaly7bXXypNPPikTJkzo+kwoFJIHHnhA1q1bJ+Fw2K7Z/MILL0hBQUGfGuayDHtxVgt14c/YlXbqyDho+3Q9Tsys8P0XTsS9dxaOlnWbGnfhXhyJPbpdH03sS8OR0aYXJ4QOhbF7sskcCW0pvlxte8bl4vZYrbhvgzgIWYJu/WXtwznVJVyNbdYpfO15ivD109asv2ZHCe7baApOnJ4RxQnFY4U4SbnCOI1tOfWJi9QHLU2nf3375/xJEdmyZYvcd999smPHDnnvvfckGo3atZnb27+6OO6//35566235LXXXrM/X11dLbfddltfdkMISaYRy4YNG7q9Xrt2reTn58vu3bvl+uuvl+bmZnnxxRfl5Zdflptuusn+zJo1a2TSpEm2GF199dXOtp4QMvSesSghUeTkfDlrVQmMGsXMnTu36zMTJ06U0aNHy/btiWeoqtullpaWbgshJEmFxTRNWb58ucyZM0emTJliv1dbWys+n0+ys7sX/1LPV5QNPbcJBAJdS3FxcX+bRAgZ7MKinrXs37/ffkh7PpSWltojn86lqqrqvLZHCBmkQYhLly6Vt99+W7Zu3SqjRn3loSgsLJRIJCJNTU3dRi11dXW2LRF+v99eCCFJOmKxLMsWlfXr18umTZukpKSkm33GjBni9Xpl48aNXe8dPHhQjh8/Ltdcc41zrSaEDJ0Ri7r9UR6fN998UzIzM7uem6hnI2pei/p71113yYoVK+wHullZWbJs2TJbVPrsEepH1oTeP6/L8K+Z4xLFI6rKT6Zq9+hx44Lf5o3Hoc24HqdNSI3juSp5+/RpCjzt6Xifmvr2Pj+ew+DNw3Nuwk36366sED7OjHZ8eYbdeO5H3KO/rANuPDfE9OK5Ie1ncJoL96W4f4IevJ7CdRq3Ny1DUzUgjq/ZjPRD2n36arCTpKMtLeH7QQv323kJy6pVq+y/N9xwQ7f3lUv5zjvvtP9/5plnxDAMWbx4cbcJcoSQ5MHT11uh3khJSZGVK1faCyEkOWGsECHEcSgshBDHobAQQhyHwkIISaYs/cpFZzqW+qA3q/a5tGZFM5ip3WfFRzPxujlfhkIkIrAQVw1oadE09ih2byviLfhgrA7sinb78KUyfBhOfeD162dStzXn4/ZU4z7I8+PC7650fbyZR1MdIWzi42wJ4f7xhHB70obr2xM71Qpt7g5cOiEUa4K29vaPtfusiid2KSs+C3yVBuVsIqZLpFHOCY5YCCGOQ2EhhDgOhYUQ4jgUFkKI41BYCCGOQ2EhhCSRu1l5VHsPTepjdDPeoKvPOzs3YlHsMm2WydDmxzXGZcLIfdDmTsWuX0U0hN2X3gh2QcbDmqLnGhftsF5cv14/jvCOhzSp5HXF29P12eTjuiBdAxeM96Ti9P4ZEdyvPtcpbXtigqsRnJ2o/us0tn0GbUeP6q+DD7LnQdvxQOLo+Wg8THczIeTCwVshQojjUFgIIY5DYSGEOA6FhRDiOBQWQkgSuZttzTP65lN29eIyNvtpM87DxZ2Bo5/zx2Fbbhy7KAPlOHl1R1h/SlN8eF2PYBdl3I07yApjN7W3FbtvFRlZbdAW8uCoXzOKjzPWpv+9dFn4pKWm4vaYms26NN5d64Q+4rytBYcM1xu7oW1/LU78/UH6Uu0+T//HtdA26kziRNwRVYT+czknOGIhhDgOhYUQ4jgUFkKI41BYCCGOQ2EhhDgOhYUQcmHdzWVlZfL6669LeXm5Xav52muvlSeffFImTPgq+a4qv7ply5Zu6/30pz+V1atXOxTerHEp9xagbPVXY3X71O/UOxJHBeePwT7K3MZ6aIuV4322m6n6E25gd7NpxKHN5dW4ogWvF+/Qu5v9rdnQlhpohraoC4coh6M4sbXCZ2G7x4VduKkefE5OR3Et6dPVDdr2RNoOQ9vWVny+tqT9ANpa507T7nPmFPzVz/vvxEm6QzG927zfIxYlGKow/I4dO+S9996TaDQq8+bN6xHa/ZOf/ERqamq6lqeeeqovuyGEJNOIZcOGDd1er127VvLz82X37t1y/fXXd72flpYmhYWFzrWSEJI8z1iam78cqubkdE9m9Je//EVyc3NlypQpUlpaKh0dHXAb4XBYWlpaui2EkCSd0m+apixfvlzmzJljC0gn3/ve92TMmDFSVFQke/fulV/84hdy8OBB+9kMem7z+OOP97cZhJChJCzqWcv+/ftl27Zt3d6/++67u/6fOnWqjBgxQm6++WY5fPiwXHLJJT22o0Y0K1as6HqtRizFxcX9bRYhZLAKy9KlS+Xtt9+WrVu3yqhRo7SfnT17tv23oqIiobD4/X57IYQkqbBYliXLli2T9evXy+bNm6WkpKTXdfbs2WP/VSMXQkhy4Onr7c/LL78sb775pmRmZkptba39fiAQsOe1qNsdZf/2t78tw4cPt5+x3H///bbHaNo0vV/dEXpNtK9LudBriv9+dWFaIZ7fkJOJUyN49uKUAaF6fKBuP84Wb68b1MzhiOC2elLxfApXmmb+iwunIVCYIc28mxacjsGTivsnaujS8IsETdx/kXZcGSAYOQBtVZlffhcSsT+I58YoGmvw/JD/CeC5KpFbboG2/7pOP59pXjNOx/DZF4mrBnhNffWDfgvLqlWruibBnc2aNWvkzjvvFJ/PJ++//748++yz9twW9axk8eLF8vDDD/dlN4SQZLsV0qGE5OuzbgkhyQdjhQghjkNhIYQ4DoWFEOI4FBZCSBJl6VcZ9xNl3T+f2u0u51cz/SnadQO52O2XHcPh9L6TOL6qXeNN9afqO8jyYntUU9zdFcVF2P1p2BXtTtG7v10mTscQ1bi/JY4nVbpS9OH9YbMa2upbsUv5WO0RaPskhl3K+6zLte2p8H4L2prHTYe2qf8Lu8bzQvrUEZk7Exd+VwyPJr5mO6xzH4dwxEIIcRwKCyHEcSgshBDHobAQQhyHwkIIcRwKCyEkidzNMEv/efiTtWZNVXhNM1wBfS6ZzDy8ctop7FJ2V+NI0hYvjvpNd+vdjC4Pbo/Lp4lS1nSeFdP8Ppn69oimMoDhwZHRwQh2f4dP613c4dgxaDtYjff5XvM10LZ92CRoOz3lMm17CqdfCW2zhhdA2+2ZH0BbqBm71G17Hf7qp7Ymvi4t69yjmzliIYQ4DoWFEOI4FBZCiONQWAghjkNhIYQ4DoWFEJJE7mYVSdmHaMpzil7Wea8TRVJ3rYbb4cnVd2F6Bi5sLsexa7O9Dh+MNw1H/caMXtzNYexWd7nxPg1L4443sc2K60+KGcf9Z8Zxv7s0gc/BlnTtPmsOf1Vg7+scasPR6AdGzIA239Sp0HbDlSO17RldgN24GQfxdZn1Ts9yOp1cOh4n91ZYAVzg/hSI1LZEn6T8bDhiIYQ4DoWFEOI4FBZCiONQWAghjkNhIYQ4DoWFEOI4FBZCiOP0uXazWo4ePWq/njx5sjz66KOyYMEC+3UoFJIHHnhA1q1bJ+FwWObPny8vvPCCFBTg0O++o5sXcR4p/DWrWppUBP5s/T59Vgu0RavwvICmDpwWIG0YTjUQjeCM+bY9jueceDVzYKK6OSUmbo/Vy+SiuOYSNC1ss0TTB259KotGD05/IOmXQtPU0ZnQ1oyT6cvkLFyNQTErjNM4uFqaoM33BT7X8YZe5pyE8NyZDnfitBMdVkybXaTfI5ZRo0bJE088Ibt375Zdu3bJTTfdJAsXLpTPPvvMtt9///3y1ltvyWuvvWbXcK6urpbbbrutL7sghCTbiOWWW27p9vq3v/2tPYLZsWOHLTovvviivPzyy7bgKNasWSOTJk2y7VdffXXCbaqRjVo6aWnBv/CEkCH+jCUej9u3PO3t7XLNNdfYo5hoNCpz587t+szEiRNl9OjRsn37dridsrIyCQQCXUtxcXF/m0QIGazCsm/fPsnIyBC/3y/33HOPrF+/Xi6//HKpra0Vn88n2dnZ3T6vnq8oG6K0tFSam5u7lqqqqv4dCSFk8AYhTpgwQfbs2WOLwN/+9jdZsmSJ/TylvyiBUgshJImFRY1Kxo8fb/8/Y8YM+eijj+T3v/+93H777RKJRKSpqanbqKWurk4KCwudbTUhZGinTTBN0374qkTG6/XKxo0bZfHixbbt4MGDcvz4cfsZTF/J8E4Uw90zG32qxiXq6iVtgtVPd7Rh4A2PcutdiXmN5dDWfhK7GU+YOKVCTPCtZaulSdMgIkfiOIO9x4VduG5NWgkjpsn8b/RSpN5n9MvdbEbxdRD0Y7ewomZECbRVt4+BtriB0zEUWbhgfGtDnbY9n57E59rXgM9XLIj7wKrE51JheLE7ujpnWsL3w2ZMpFGcFxb1PETNWVEPZFtbW20P0ObNm+Xdd9+1H7zeddddsmLFCsnJyZGsrCxZtmyZLSrII0QIGZr0SVjq6+vlhz/8odTU1NhCMm3aNFtUvvnNb9r2Z555RgzDsEcsZ0+QI4QkF30SFjVPRUdKSoqsXLnSXgghyQtjhQghjkNhIYQM/WTalvWlF8GMB/vsDXCZ57btvjcKe4ViocTt7CTagZ++R8L4iX8kgm0hTULsYLiXY4xiuyeu8fzEB8grpPHUmZq2Wpp9BmP6CyGk8YxF4vh8xWM4g3c4hLcZ1wRp2u2J4PbGozqbpp52L9GChsZue38075/L98hl9fvbNjCcOHGC0/oJuYhRs+NVbOCgEhY1L0ZFRWdmZorL5bKDElX8kDoY5cIm3WH/6GH/ONdHSirUNJOioiLb+zuoboVUgxOpoTpgCguG/aOH/eNMH6lpJucCH94SQhyHwkIIST5hUZHPjz32GCOg2T+8fgbRd+yie3hLCBn8XPQjFkLI4IPCQghxHAoLIcRxKCyEEMehsBBCkktYVF6XsWPH2nleZs+eLf/85z8lWdm6datd10lNp1ahDm+88UY3u3LuqaqUI0aMkNTUVLsMy6FDhyRZUGVkZs6caYeC5Ofny6JFi+zUqGejKnXed999Mnz4cLvShEpIpnIyJwOrVq2yE7N1zq5VmR3//ve/D1jfXLTC8uqrr9ppLpV//eOPP5bp06fbGelUFrtkRNVvUn2Akmg99dRT8txzz8nq1atl586dkp6ebveXumCSAVUpQn0xVHG89957z65xNW/ePLvfOknmSp2j/t1VTK2LlFmzZln33Xdf1+t4PG4VFRVZZWVlVrKjTtv69eu7XpumaRUWFlpPP/1013tNTU2W3++3XnnlFSsZqa+vt/tpy5YtXf3h9Xqt1157reszBw4csD+zfft2KxkZNmyY9ac//WlA+uaiHLGoMiJKWc+uqqiCE9VrXVXFZKWystIuCnd2f6lgMXX7mKz9pepeKVRid0V/K3UOReIOVTEdVNHNioaGBvvgVRXFs1Gvy8txOY1kpbPSZKL+0lWhHKqo1BvLly+XOXPmyJQpU+z3+lupcyixb98+W0jU7bF6jtJZxVQVIHS6by5KYSHkfFDPWvbv3y/btm1jRw5gFVMdF+WtUG5urrjd7h5PpVlVMTGdlSbZXyJLly6Vt99+Wz744INueX1UH3VW6kzWa8r3ryqmqrig8qIpZ4CqYjoQfWNcrB2gDl5VVTx7eKte96eq4lCnpKTEvgDO7i+VFUx5h5Klv9QzbSUqani/adMmu0/O5uxKnZ2cT6XOoYCZoIqpY31jXaSsW7fO9mqsXbvW+vzzz627777bys7Otmpra61kpLW11frkk0/sRZ223/3ud/b/x44ds+1PPPGE3T9vvvmmtXfvXmvhwoVWSUmJFQwGrWTg3nvvtQKBgLV582arpqama+no6Oj6zD333GONHj3a2rRpk7Vr1y7rmmuusZdk4KGHHrI9ZJWVlfb1oV67XC7rH//4x4D0zUUrLIo//OEP9sH6fD7b/bxjxw4rWfnggw9sQfn6smTJki6X8yOPPGIVFBTYgnzzzTdbBw8etJKFRH2jljVr1nR9Ronsz372M9vNmpaWZt166622+CQDP/7xj60xY8bY36W8vDz7+ugUlYHoG+ZjIYQ4zkX5jIUQMrihsBBCHIfCQghxHAoLIcRxKCyEEMehsBBCHIfCQghxHAoLIcRxKCyEEMehsBBCHIfCQggRp/n/KkHZ2u8WBbsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 300x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "activations = []\n",
    "def hook(model, input, output):\n",
    "    activations.append(output.detach())\n",
    "\n",
    "h = model.conv1.register_forward_hook(hook)\n",
    "model(x)\n",
    "h.remove()\n",
    "\n",
    "for iii in range(16):\n",
    "    visualize_pca(activations[0][iii])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "363de1f2-c655-4ac8-bc12-35fc2afddb2f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 64 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hx = activations[0][0]\n",
    "\n",
    "for iii in range(64):\n",
    "    plt.subplot(8,8,iii+1)\n",
    "    plt.imshow(hx[iii])"
   ]
  },
  {
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    "# Exercises\n",
    "- **resnet**: check the ResNet code. Do you understand everything? If not, check the documentation or ask for help. Check that you understand the shapes of the feature maps and how the conv hyperparameters affect them.\n",
    "- simple sanity checks:\n",
    "    - **augmentations matter**: try to train a model with and without augmentations.\n",
    "    - **training stability and lr**: try to increase the learning rate (10x, 100x, ...). What happens to the learning curve? You can also try some learning rate scheduler.\n",
    "- **reproduce sota for CIFAR100**: use this notebook to reproduce a result from [this repo](https://github.com/weiaicunzai/pytorch-cifar100). NOTE: our resnet18 is slightly different from theirs (slim version, less units)\n",
    "    - [learning rate scheduler in pytorch](https://docs.pytorch.org/docs/2.14/generated/torch.optim.lr_scheduler.MultiStepLR.html)"
   ]
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