Experiments with autoencoders of MNIST Data in pytorch, with a visualization of projection to 2D latent space

AutoencoderTest.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "035bdd71",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim as optim\n",
    "import matplotlib.pyplot as plt\n",
    "from torch.utils.data.sampler import SubsetRandomSampler\n",
    "from torch.utils.data import DataLoader\n",
    "from torchvision import datasets, transforms\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c564da3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Converting data to torch.FloatTensor\n",
    "torch.manual_seed(1)\n",
    "transform = transforms.ToTensor()\n",
    "train_data = datasets.MNIST(root='data', train=True, download=True, transform=transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e47dfff5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset MNIST\n",
       "    Number of datapoints: 60000\n",
       "    Root location: data\n",
       "    Split: Train\n",
       "    StandardTransform\n",
       "Transform: ToTensor()"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "aa1edf56",
   "metadata": {},
   "outputs": [],
   "source": [
    "test_data = datasets.MNIST(root='data', train=False, download=True, transform=transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "16853a35",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Dataset MNIST\n",
       "    Number of datapoints: 10000\n",
       "    Root location: data\n",
       "    Split: Test\n",
       "    StandardTransform\n",
       "Transform: ToTensor()"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b93f77be",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Prepare data loaders\n",
    "train_loader = torch.utils.data.DataLoader(train_data, batch_size=32, num_workers=0)\n",
    "test_loader = torch.utils.data.DataLoader(test_data, batch_size=50, num_workers=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "874d6eb0",
   "metadata": {},
   "outputs": [],
   "source": [
    "dataiter = iter(train_loader)\n",
    "images, labels = dataiter.next()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "023c9870",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f268f2beeb0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(images[1][0, :, :], cmap='gray')\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "63c467fb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([1, 28, 28])\n"
     ]
    }
   ],
   "source": [
    "class AutoencoderCNN(nn.Module):\n",
    "    def __init__(self, dim=10):\n",
    "        super(AutoencoderCNN, self).__init__()\n",
    "        self.dim = dim\n",
    "        self.conv1 = nn.Conv2d(1, 8, 3, stride=2, padding=1)\n",
    "        self.conv1_relu = nn.ReLU()\n",
    "        self.conv2 = nn.Conv2d(8, 16, 3, stride=2, padding=1)\n",
    "        self.conv2_relu = nn.ReLU()\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.latentdown = nn.Linear(784, dim)\n",
    "        self.latentdown_relu = nn.ReLU()\n",
    "        self.latentup = nn.Linear(dim, 784)\n",
    "        self.latentup_relu = nn.ReLU()\n",
    "        self.reshape = nn.Unflatten(1, (16, 7, 7))\n",
    "        self.conv2up = nn.ConvTranspose2d(16, 8, 3, stride=2, padding=1)\n",
    "        self.conv2up_relu = nn.ReLU()\n",
    "        self.conv1up = nn.ConvTranspose2d(8, 1, 3, stride=2, output_padding=1)\n",
    "        self.conv1up_relu = nn.ReLU()\n",
    "    \n",
    "    def forward(self, x):\n",
    "        layers = [self.conv1, self.conv1_relu, self.conv2, self.conv2_relu]\n",
    "        layers += [self.flatten, self.latentdown, self.latentdown_relu]\n",
    "        layers += [self.latentup, self.latentup_relu, self.reshape]\n",
    "        layers += [self.conv2up, self.conv2up_relu, self.conv1up, self.conv1up_relu]\n",
    "        y = x\n",
    "        for layer in layers:\n",
    "            y = layer(y)\n",
    "        return y\n",
    "    \n",
    "    def project_latent(self, x):\n",
    "        layers = [self.conv1, self.conv1_relu, self.conv2, self.conv2_relu]\n",
    "        layers += [self.flatten, self.latentdown, self.latentdown_relu]\n",
    "        y = x\n",
    "        for layer in layers:\n",
    "            y = layer(y)\n",
    "        return y\n",
    "\n",
    "class AutoencoderCNNDeeper(nn.Module):\n",
    "    def __init__(self, dim=10):\n",
    "        super(AutoencoderCNNDeeper, self).__init__()\n",
    "        self.dim = dim\n",
    "        self.conv1 = nn.Conv2d(1, 32, 3, stride=2, padding=1) # 32 x 14 x 14\n",
    "        self.conv1_relu = nn.ReLU()\n",
    "        self.conv2 = nn.Conv2d(32, 64, 3, stride=2, padding=1) # 64 x 7 x 7\n",
    "        self.conv2_relu = nn.ReLU()\n",
    "        self.conv3 = nn.Conv2d(64, 128, 3, stride=2) # 128 x 3 x 3\n",
    "        self.conv3_relu = nn.ReLU()\n",
    "        self.flatten = nn.Flatten()\n",
    "        self.latentdown = nn.Linear(1152, dim)\n",
    "        self.latentdown_relu = nn.ReLU()\n",
    "        self.latentup = nn.Linear(dim, 1152)\n",
    "        self.latentup_relu = nn.ReLU()\n",
    "        self.reshape = nn.Unflatten(1, (128, 3, 3))\n",
    "        self.conv3up = nn.ConvTranspose2d(128, 64, 3, stride=2)\n",
    "        self.conv3up_relu = nn.ReLU()\n",
    "        self.conv2up = nn.ConvTranspose2d(64, 32, 3, stride=2, padding=1, output_padding=1)\n",
    "        self.conv2up_relu = nn.ReLU()\n",
    "        self.conv1up = nn.ConvTranspose2d(32, 1, 3, stride=2, padding=1, output_padding=1)\n",
    "        self.conv1up_relu = nn.ReLU()\n",
    "    \n",
    "    def forward(self, x):\n",
    "        layers = [self.conv1, self.conv1_relu, self.conv2, self.conv2_relu, self.conv3, self.conv3_relu]\n",
    "        layers += [self.flatten, self.latentdown, self.latentdown_relu]\n",
    "        layers += [self.latentup, self.latentup_relu, self.reshape]\n",
    "        layers += [self.conv3up, self.conv3up_relu, self.conv2up, self.conv2up_relu, self.conv1up, self.conv1up_relu]\n",
    "        y = x\n",
    "        for layer in layers:\n",
    "            y = layer(y)\n",
    "        return y\n",
    "    \n",
    "    def project_latent(self, x):\n",
    "        layers = [self.conv1, self.conv1_relu, self.conv2, self.conv2_relu, self.conv3, self.conv3_relu]\n",
    "        layers += [self.flatten, self.latentdown, self.latentdown_relu]\n",
    "        y = x\n",
    "        for layer in layers:\n",
    "            y = layer(y)\n",
    "        return y\n",
    "    \n",
    "model = AutoencoderCNNDeeper(2)\n",
    "res = model(images)\n",
    "print(res[0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f653f024",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda:0\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "AutoencoderCNNDeeper(\n",
       "  (conv1): Conv2d(1, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "  (conv1_relu): ReLU()\n",
       "  (conv2): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "  (conv2_relu): ReLU()\n",
       "  (conv3): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2))\n",
       "  (conv3_relu): ReLU()\n",
       "  (flatten): Flatten(start_dim=1, end_dim=-1)\n",
       "  (latentdown): Linear(in_features=1152, out_features=2, bias=True)\n",
       "  (latentdown_relu): ReLU()\n",
       "  (latentup): Linear(in_features=2, out_features=1152, bias=True)\n",
       "  (latentup_relu): ReLU()\n",
       "  (reshape): Unflatten(dim=1, unflattened_size=(128, 3, 3))\n",
       "  (conv3up): ConvTranspose2d(128, 64, kernel_size=(3, 3), stride=(2, 2))\n",
       "  (conv3up_relu): ReLU()\n",
       "  (conv2up): ConvTranspose2d(64, 32, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), output_padding=(1, 1))\n",
       "  (conv2up_relu): ReLU()\n",
       "  (conv1up): ConvTranspose2d(32, 1, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), output_padding=(1, 1))\n",
       "  (conv1up_relu): ReLU()\n",
       ")"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_device():\n",
    "    if torch.cuda.is_available():\n",
    "        device = 'cuda:0'\n",
    "    else:\n",
    "        device = 'cpu'\n",
    "    return device\n",
    "\n",
    "device = get_device()\n",
    "print(device)\n",
    "model.to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "50016678",
   "metadata": {},
   "outputs": [],
   "source": [
    "for data in test_loader:\n",
    "    break\n",
    "test_data = data[0]\n",
    "test_data = test_data.to(device)\n",
    "K=10\n",
    "def test_model(model):\n",
    "    res = model(test_data)\n",
    "    orig = test_data\n",
    "    if not device == \"cpu\":\n",
    "        orig = orig.cpu()\n",
    "        res = res.cpu()\n",
    "    orig = orig.detach().numpy()\n",
    "    res = res.detach().numpy()\n",
    "    for k in range(K*int(K/2)):\n",
    "        plt.subplot(K, 2*int(K/2), 2*k+1)\n",
    "        plt.imshow(orig[k, 0, :, :], cmap='gray')\n",
    "        plt.axis(\"off\")\n",
    "        if k < int(K/2):\n",
    "            plt.title(\"Original\")\n",
    "        plt.subplot(K, 2*int(K/2), 2*k+2)\n",
    "        plt.imshow(res[k, 0, :, :], cmap='gray')\n",
    "        plt.axis(\"off\")\n",
    "        if k < int(K/2):\n",
    "            plt.title(\"Reconstructed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3f3c691b",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.621,1.424,1.349,1.312,1.288,1.271,1.257,1.247,1.237,1.232,1.223,1.218,1.213,1.207,1.205,1.200,1.196,1.192,1.190,1.186,1.183,1.182,1.178,1.176,1.175,1.173,1.170,1.169,1.167,1.165,1.163,1.164,1.161,1.160,1.158,1.157,1.155,1.154,1.154,1.152,"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 100 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "criterion = nn.MSELoss()\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=0.001)\n",
    "plt.figure(figsize=(K*2, K*2))\n",
    "\n",
    "n_epochs = 40\n",
    "losses = []\n",
    "for epoch in range(n_epochs):\n",
    "    tic = time.time()\n",
    "    train_loss = 0.0\n",
    "    for data in train_loader:\n",
    "        images, _ = data\n",
    "        images = images.to(device)\n",
    "        optimizer.zero_grad()\n",
    "        outputs = model(images)\n",
    "        loss = criterion(outputs, images)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        train_loss += loss.item()*images.size(0)\n",
    "    train_loss /= len(train_loader)\n",
    "    losses.append(train_loss)\n",
    "    plt.clf()\n",
    "    test_model(model)\n",
    "    s = '{:.3f}'.format(train_loss)\n",
    "    print(s, end=',')#, \"\\nElapsed Time={:.3f}\".format(time.time()-tic))\n",
    "    plt.title(s)\n",
    "    plt.savefig(\"{}.png\".format(epoch), bbox_inches='tight', facecolor='white')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "977dae49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'Iteration')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(losses)\n",
    "plt.ylabel(\"Loss\")\n",
    "plt.xlabel(\"Iteration\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1dc6cd71",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.offsetbox import OffsetImage, AnnotationBbox\n",
    "# Plot the first two coordinates of 1000 random encodings\n",
    "n_digits = 1000 # Number of digits to shoot for\n",
    "plt.figure(figsize=(20, 20))\n",
    "ax = plt.gca()\n",
    "encoded_imgs = np.array([])\n",
    "for data in test_loader:\n",
    "    data = data[0]\n",
    "    data = data.to(device)\n",
    "    \n",
    "    res = model.project_latent(data)\n",
    "    orig = data\n",
    "    if not device == \"cpu\":\n",
    "        orig = orig.cpu()\n",
    "        res = res.cpu()\n",
    "    orig = orig.detach().numpy()\n",
    "    res = res.detach().numpy()\n",
    "    for k in range(orig.shape[0]):\n",
    "        x, y = res[k, :]\n",
    "        img = orig[k, 0, :, :]\n",
    "        img = OffsetImage(img, zoom=0.75, cmap='gray_r')\n",
    "        ab = AnnotationBbox(img, (x, y), xycoords='data', frameon=False)\n",
    "        ax.add_artist(ab)\n",
    "    if encoded_imgs.size == 0:\n",
    "        encoded_imgs = res\n",
    "    else:\n",
    "        encoded_imgs = np.concatenate((encoded_imgs, res), axis=0)\n",
    "    if encoded_imgs.shape[0] > n_digits:\n",
    "        break\n",
    "ax.update_datalim(encoded_imgs)\n",
    "ax.autoscale()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}