notebooks/[demo] pretrained AlexNet feature maps.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "device(type='cuda', index=0)"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "from torch import nn\n",
    "from torchvision import datasets, transforms\n",
    "from torch.utils.data import DataLoader\n",
    "import torch.optim as optim\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "plt.rc('font', size=16)\n",
    "import time\n",
    "\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "device"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### load AlexNet with pretrained weights from ImageNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torchvision.models as models\n",
    "\n",
    "alexnet = models.alexnet(pretrained=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AlexNet(\n",
       "  (features): Sequential(\n",
       "    (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n",
       "    (1): ReLU(inplace=True)\n",
       "    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
       "    (4): ReLU(inplace=True)\n",
       "    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (7): ReLU(inplace=True)\n",
       "    (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (9): ReLU(inplace=True)\n",
       "    (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (11): ReLU(inplace=True)\n",
       "    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  )\n",
       "  (avgpool): AdaptiveAvgPool2d(output_size=(6, 6))\n",
       "  (classifier): Sequential(\n",
       "    (0): Dropout(p=0.5, inplace=False)\n",
       "    (1): Linear(in_features=9216, out_features=4096, bias=True)\n",
       "    (2): ReLU(inplace=True)\n",
       "    (3): Dropout(p=0.5, inplace=False)\n",
       "    (4): Linear(in_features=4096, out_features=4096, bias=True)\n",
       "    (5): ReLU(inplace=True)\n",
       "    (6): Linear(in_features=4096, out_features=1000, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alexnet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Input shape:\t torch.Size([1, 3, 224, 224])\n",
      "Conv2d output shape:\t torch.Size([1, 64, 55, 55])\n",
      "ReLU output shape:\t torch.Size([1, 64, 55, 55])\n",
      "MaxPool2d output shape:\t torch.Size([1, 64, 27, 27])\n",
      "Conv2d output shape:\t torch.Size([1, 192, 27, 27])\n",
      "ReLU output shape:\t torch.Size([1, 192, 27, 27])\n",
      "MaxPool2d output shape:\t torch.Size([1, 192, 13, 13])\n",
      "Conv2d output shape:\t torch.Size([1, 384, 13, 13])\n",
      "ReLU output shape:\t torch.Size([1, 384, 13, 13])\n",
      "Conv2d output shape:\t torch.Size([1, 256, 13, 13])\n",
      "ReLU output shape:\t torch.Size([1, 256, 13, 13])\n",
      "Conv2d output shape:\t torch.Size([1, 256, 13, 13])\n",
      "ReLU output shape:\t torch.Size([1, 256, 13, 13])\n",
      "MaxPool2d output shape:\t torch.Size([1, 256, 6, 6])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at  /pytorch/c10/core/TensorImpl.h:1156.)\n",
      "  return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)\n"
     ]
    }
   ],
   "source": [
    "X = torch.randn(1, 3, 224, 224)#.to(device)\n",
    "\n",
    "print('Input shape:\\t', X.shape)\n",
    "\n",
    "for layer in alexnet.features:\n",
    "    X=layer(X)\n",
    "    print(layer.__class__.__name__, 'output shape:\\t', X.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([64, 3, 11, 11])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alexnet.features[0].weight.data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_weights(model, layerID, in_channelID=None, out_channelID=None):\n",
    "    '''plot filters of channels \n",
    "        If in_channelID  is given, plot filters of all out_channels (at fixed in_channelID ).\n",
    "        If out_channelID is given, plot filters of all in_channels  (at fixed out_channelID).\n",
    "    '''\n",
    "    \n",
    "    if in_channelID is not None:\n",
    "        layerW = model[layerID].weight.data[:,in_channelID,:,:].cpu().numpy()\n",
    "    if out_channelID is not None:\n",
    "        layerW = model[layerID].weight.data[out_channelID,:,:,:].cpu().numpy()\n",
    "    \n",
    "    return layerW\n",
    "\n",
    "def view_3D_cubes(cube3D, Ncols, Nrows, figsize, cmap='Greys'):\n",
    "    \n",
    "    fig, axs = plt.subplots(Nrows, Ncols, figsize=figsize)\n",
    "    plt.subplots_adjust(hspace=0.1, wspace=0.1)\n",
    "    \n",
    "    for i in range(Nrows):    \n",
    "        for j in range(Ncols):\n",
    "    \n",
    "            axs[i,j].imshow(cube3D[i*Ncols+j], cmap=cmap)\n",
    "            axs[i,j].axis('off')\n",
    "    return fig, axs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1440x1440 with 64 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1101,
       "width": 1127
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "layerW = get_weights(alexnet.features, 0, in_channelID=0)\n",
    "_,__ = view_3D_cubes(layerW, Ncols=8, Nrows=8, figsize=(20,20), cmap='Greys')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x1440 with 64 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1101,
       "width": 1127
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "layerW = get_weights(alexnet.features, 0, in_channelID=2)\n",
    "_,__ = view_3D_cubes(layerW, Ncols=8, Nrows=8, figsize=(20,20), cmap='Greys')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1440x1440 with 64 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 1101,
       "width": 1127
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "layerW = get_weights(alexnet.features, 3, out_channelID=2)\n",
    "_,__ = view_3D_cubes(layerW, Ncols=8, Nrows=8, figsize=(20,20), cmap='Greys')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Take the pretrained AlexNet kernel and applied on fashion-MNIST dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.8/dist-packages/torchvision/datasets/mnist.py:498: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  /pytorch/torch/csrc/utils/tensor_numpy.cpp:180.)\n",
      "  return torch.from_numpy(parsed.astype(m[2], copy=False)).view(*s)\n"
     ]
    }
   ],
   "source": [
    "### load Fashion-MNIST data\n",
    "\n",
    "transform = transforms.Compose([transforms.Resize([224, 224]),\n",
    "                                transforms.RandomHorizontalFlip(),\n",
    "                                transforms.ToTensor()])\n",
    "\n",
    "fmnist_train = datasets.FashionMNIST(\n",
    "    root=\"../../../data\", train=True, transform=transform, download=True)\n",
    "fmnist_test = datasets.FashionMNIST(\n",
    "    root=\"../../../data\", train=False, transform=transform, download=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "layerW = get_weights(alexnet.features, 0, in_channelID=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 3 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 251,
       "width": 678
      },
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "channelID = 51\n",
    "\n",
    "conv2d = nn.Conv2d(1, 1, kernel_size=(3, 3), bias=False)\n",
    "conv2d.weight.data = torch.tensor(layerW[channelID]).view(1, 1, 11, 11)\n",
    "\n",
    "\n",
    "imageID = 22\n",
    "X, _ = fmnist_train.__getitem__(imageID)\n",
    "outX = conv2d(X.unsqueeze(dim=0))  # Convolution\n",
    "outX = nn.ReLU()(outX)             # Apply ReLU\n",
    "\n",
    "###############\n",
    "\n",
    "fig, axes = plt.subplots(1, 3, figsize=(12, 4))\n",
    "plt.subplots_adjust(hspace=0.001, wspace=0.001)\n",
    "plt.rc('font', size=16)\n",
    "axes[0].imshow(X.squeeze().numpy(), cmap='Blues')\n",
    "axes[1].imshow(layerW[channelID], cmap='Greys')\n",
    "axes[2].imshow(outX.squeeze().detach().numpy(), cmap='Blues')\n",
    "\n",
    "axes[0].text(0.96, 0.01, f'ImageID:{imageID}',\n",
    "                           verticalalignment='bottom', horizontalalignment='right',\n",
    "                           transform=axes[0].transAxes,\n",
    "                           color='k', fontsize=18)\n",
    "\n",
    "axes[1].text(0.96, 0.01, f'{channelID}',\n",
    "                           verticalalignment='bottom', horizontalalignment='right',\n",
    "                           transform=axes[1].transAxes,\n",
    "                           color='b', fontsize=18)\n",
    "\n",
    "axes[0].set_title('original')\n",
    "axes[1].set_title('3x3 ConV')\n",
    "axes[2].set_title('feature map')\n",
    "\n",
    "for i in range(3):\n",
    "    axes[i].axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Transfer Learning : change the final layer of AlexNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AlexNet(\n",
       "  (features): Sequential(\n",
       "    (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n",
       "    (1): ReLU(inplace=True)\n",
       "    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
       "    (4): ReLU(inplace=True)\n",
       "    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (7): ReLU(inplace=True)\n",
       "    (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (9): ReLU(inplace=True)\n",
       "    (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (11): ReLU(inplace=True)\n",
       "    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  )\n",
       "  (avgpool): AdaptiveAvgPool2d(output_size=(6, 6))\n",
       "  (classifier): Sequential(\n",
       "    (0): Dropout(p=0.5, inplace=False)\n",
       "    (1): Linear(in_features=9216, out_features=4096, bias=True)\n",
       "    (2): ReLU(inplace=True)\n",
       "    (3): Dropout(p=0.5, inplace=False)\n",
       "    (4): Linear(in_features=4096, out_features=4096, bias=True)\n",
       "    (5): ReLU(inplace=True)\n",
       "    (6): Linear(in_features=4096, out_features=1000, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alexnet_TL = models.alexnet(pretrained=True)\n",
    "\n",
    "alexnet_TL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "alexnet_TL.classifier[6] = nn.Linear(4096, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AlexNet(\n",
       "  (features): Sequential(\n",
       "    (0): Conv2d(3, 64, kernel_size=(11, 11), stride=(4, 4), padding=(2, 2))\n",
       "    (1): ReLU(inplace=True)\n",
       "    (2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (3): Conv2d(64, 192, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2))\n",
       "    (4): ReLU(inplace=True)\n",
       "    (5): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "    (6): Conv2d(192, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (7): ReLU(inplace=True)\n",
       "    (8): Conv2d(384, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (9): ReLU(inplace=True)\n",
       "    (10): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "    (11): ReLU(inplace=True)\n",
       "    (12): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  )\n",
       "  (avgpool): AdaptiveAvgPool2d(output_size=(6, 6))\n",
       "  (classifier): Sequential(\n",
       "    (0): Dropout(p=0.5, inplace=False)\n",
       "    (1): Linear(in_features=9216, out_features=4096, bias=True)\n",
       "    (2): ReLU(inplace=True)\n",
       "    (3): Dropout(p=0.5, inplace=False)\n",
       "    (4): Linear(in_features=4096, out_features=4096, bias=True)\n",
       "    (5): ReLU(inplace=True)\n",
       "    (6): Linear(in_features=4096, out_features=10, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alexnet_TL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total network parameters : 57044810\n"
     ]
    }
   ],
   "source": [
    "# count total network parameters (before freeze the parameters)\n",
    "print('Total network parameters :', sum(param.numel() for param in alexnet_TL.parameters() if param.requires_grad))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Freeze the parameters in the CNN part\n",
    "for param in alexnet_TL.features.parameters():\n",
    "    param.requires_grad = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total network parameters : 54575114\n"
     ]
    }
   ],
   "source": [
    "# count total network parameters (before freeze the parameters)\n",
    "print('Total network parameters :', sum(param.numel() for param in alexnet_TL.parameters() if param.requires_grad))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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