{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Variational Autoencoders\n", "\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/borchero/pyblaze/blob/master/docs/examples/vae.ipynb)\n", "[![Download Jupyter Notebbok](https://img.shields.io/badge/Github-Download-brightgreen)](https://github.com/borchero/pyblaze/blob/master/docs/examples/vae.ipynb)\n", "\n", "In this tutorial, we want to use PyBlaze to train a variational autoencoder (VAE). More precisely, we want to generate handwritten digits as obtained from the MNIST dataset.\n", "\n", "Later on, we will repeat the same tutorial and train a Wasserstein GAN instead of a VAE.\n", "\n", "**_Note: This tutorial currently lacks both explanation and any theory. It will be added in the future._**" ] }, { "cell_type": "code", "execution_count": 1, "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 torch.distributions as D\n", "import torchvision\n", "import torchvision.transforms as transforms\n", "import pyblaze.nn as xnn\n", "import pyblaze.nn.functional as X\n", "import matplotlib.pyplot as plt\n", "\n", "%reload_ext autoreload\n", "%autoreload 2\n", "\n", "plt.style.use('seaborn-notebook')\n", "plt.rcParams['figure.dpi'] = 150" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Loading the Data\n", "\n", "At first, we want to load the data. Again, `torchvision` can make our life easier:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "train_val_dataset = torchvision.datasets.MNIST(\n", " root=\"~/Downloads/\", train=True, download=True, transform=transforms.ToTensor()\n", ")\n", "test_dataset = torchvision.datasets.MNIST(\n", " root=\"~/Downloads/\", train=False, download=True, transform=transforms.ToTensor()\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As we did before, we can also easily initialize the data loaders:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "train_dataset, val_dataset = train_val_dataset.random_split(0.8, 0.2)\n", "train_loader = train_dataset.loader(batch_size=256, num_workers=4, shuffle=True)\n", "val_loader = val_dataset.loader(batch_size=2048)\n", "test_loader = test_dataset.loader(batch_size=2048)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Before we continue to set up our model, we first have a look at a few randomly sampled images from our training data:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "scrolled": false }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "\n", "images = [train_dataset[i] for i in np.random.choice(len(train_dataset), 10)]\n", "for i, (image, _) in enumerate(images):\n", " plt.subplot(1, 10, i+1)\n", " plt.imshow(image[0], cmap='binary')\n", " plt.axis('off')\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Defining the Model\n", "\n", "After we had a look at the data, we can define our model. We use convolutional layers in the encoder and scale the hidden representation up in the end." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "class Encoder(nn.Module):\n", " \n", " def __init__(self):\n", " super().__init__()\n", " self.conv = nn.Sequential(\n", " nn.Conv2d(1, 32, 3),\n", " nn.ReLU(),\n", " nn.Conv2d(32, 64, 5),\n", " nn.ReLU(),\n", " nn.MaxPool2d(2),\n", " nn.Conv2d(64, 64, 5),\n", " nn.ReLU(),\n", " nn.MaxPool2d(2)\n", " )\n", " self.fc_mu = nn.Linear(576, 16)\n", " self.fc_logvar = nn.Linear(576, 16)\n", " \n", " def forward(self, x):\n", " z = self.conv(x)\n", " z = z.view(z.size(0), -1)\n", " return self.fc_mu(z), self.fc_logvar(z)\n", " \n", "\n", "class Decoder(nn.Module):\n", " \n", " def __init__(self):\n", " super().__init__()\n", " self.fc = nn.Linear(16, 2048)\n", " self.conv = nn.Sequential(\n", " nn.ReLU(),\n", " nn.ConvTranspose2d(128, 64, 5, stride=2),\n", " nn.ReLU(),\n", " nn.ConvTranspose2d(64, 32, 5, stride=2, padding=1),\n", " nn.ReLU(),\n", " nn.ConvTranspose2d(32, 1, 6)\n", " )\n", " \n", " def forward(self, x):\n", " z = self.fc(x)\n", " z = z.view(-1, 128, 4, 4)\n", " return self.conv(z)\n", "\n", "\n", "class VAE(nn.Module):\n", "\n", " def __init__(self):\n", " super().__init__()\n", " self.encoder = Encoder()\n", " self.decoder = Decoder()\n", "\n", " def forward(self, x):\n", " mu, logvar = self.encoder(x)\n", " std = (0.5 * logvar).exp()\n", " eps = torch.randn_like(std)\n", " z = mu + eps * std\n", " return self.decoder(z), mu, logvar" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Having defined the model, we can initialize it. Let's also see how big it is:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Total parameters: 464,577\n", "Encoder parameters: 172,512\n", "Decoder parameters: 292,065\n" ] } ], "source": [ "model = VAE()\n", "\n", "print(f'Total parameters: {sum(p.numel() for p in model.parameters()):6,}')\n", "print(f'Encoder parameters: {sum(p.numel() for p in model.encoder.parameters()):6,}')\n", "print(f'Decoder parameters: {sum(p.numel() for p in model.decoder.parameters()):6,}')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Training the Model" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "optimizer = optim.Adam(model.parameters())\n", "loss = xnn.VAELoss(nn.BCEWithLogitsLoss(reduction='none'))\n", "engine = xnn.AutoencoderEngine(model, expects_data_target=True)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "scrolled": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/50:\n", "\u001b[2K [Elapsed 0:00:05 | 33.81 it/s] loss: 224.27307, val_loss: 159.77618 \n", "Epoch 2/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.45 it/s] loss: 136.16475 \n", "Epoch 3/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.73 it/s] loss: 118.60185 \n", "Epoch 4/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.37 it/s] loss: 113.22937 \n", "Epoch 5/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.84 it/s] loss: 110.84675 \n", "Epoch 6/50:\n", "\u001b[2K [Elapsed 0:00:05 | 33.62 it/s] loss: 109.05308, val_loss: 108.66338 \n", "Epoch 7/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.16 it/s] loss: 107.91442 \n", "Epoch 8/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.23 it/s] loss: 106.88257 \n", "Epoch 9/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.17 it/s] loss: 106.14308 \n", "Epoch 10/50:\n", "\u001b[2K [Elapsed 0:00:04 | 46.60 it/s] loss: 105.65662 \n", "Epoch 11/50:\n", "\u001b[2K [Elapsed 0:00:05 | 32.55 it/s] loss: 104.96011, val_loss: 105.40081 \n", "Epoch 12/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.57 it/s] loss: 104.49724 \n", "Epoch 13/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.58 it/s] loss: 104.16228 \n", "Epoch 14/50:\n", "\u001b[2K [Elapsed 0:00:04 | 46.98 it/s] loss: 103.70670 \n", "Epoch 15/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.52 it/s] loss: 103.35032 \n", "Epoch 16/50:\n", "\u001b[2K [Elapsed 0:00:05 | 32.94 it/s] loss: 102.94538, val_loss: 104.24427 \n", "Epoch 17/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.96 it/s] loss: 102.75075 \n", "Epoch 18/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.43 it/s] loss: 102.43628 \n", "Epoch 19/50:\n", "\u001b[2K [Elapsed 0:00:04 | 46.99 it/s] loss: 102.14312 \n", "Epoch 20/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.86 it/s] loss: 102.00880 \n", "Epoch 21/50:\n", "\u001b[2K [Elapsed 0:00:05 | 34.45 it/s] loss: 101.70227, val_loss: 102.42951 \n", "Epoch 22/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.53 it/s] loss: 101.51430 \n", "Epoch 23/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.14 it/s] loss: 101.41744 \n", "Epoch 24/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.21 it/s] loss: 101.11735 \n", "Epoch 25/50:\n", "\u001b[2K [Elapsed 0:00:04 | 46.84 it/s] loss: 100.98458 \n", "Epoch 26/50:\n", "\u001b[2K [Elapsed 0:00:05 | 34.03 it/s] loss: 100.77367, val_loss: 101.82356 \n", "Epoch 27/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.59 it/s] loss: 100.74920 \n", "Epoch 28/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.90 it/s] loss: 100.51038 \n", "Epoch 29/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.73 it/s] loss: 100.34299 \n", "Epoch 30/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.22 it/s] loss: 100.36984 \n", "Epoch 31/50:\n", "\u001b[2K [Elapsed 0:00:05 | 34.22 it/s] loss: 100.08789, val_loss: 101.58796 \n", "Epoch 32/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.51 it/s] loss: 99.98875 \n", "Epoch 33/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.47 it/s] loss: 99.85116 \n", "Epoch 34/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.31 it/s] loss: 99.75701 \n", "Epoch 35/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.25 it/s] loss: 99.61550 \n", "Epoch 36/50:\n", "\u001b[2K [Elapsed 0:00:05 | 33.42 it/s] loss: 99.44988, val_loss: 100.72999 \n", "Epoch 37/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.57 it/s] loss: 99.42586 \n", "Epoch 38/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.50 it/s] loss: 99.36446 \n", "Epoch 39/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.76 it/s] loss: 99.26171 \n", "Epoch 40/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.82 it/s] loss: 99.17992 \n", "Epoch 41/50:\n", "\u001b[2K [Elapsed 0:00:05 | 33.88 it/s] loss: 99.09690, val_loss: 100.31133 \n", "Epoch 42/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.69 it/s] loss: 98.97497 \n", "Epoch 43/50:\n", "\u001b[2K [Elapsed 0:00:03 | 49.46 it/s] loss: 98.90181 \n", "Epoch 44/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.44 it/s] loss: 98.79760 \n", "Epoch 45/50:\n", "\u001b[2K [Elapsed 0:00:03 | 48.53 it/s] loss: 98.63344 \n", "Epoch 46/50:\n", "\u001b[2K [Elapsed 0:00:05 | 33.40 it/s] loss: 98.56735, val_loss: 100.23586 \n", "Epoch 47/50:\n", "\u001b[2K [Elapsed 0:00:04 | 46.33 it/s] loss: 98.47528 \n", "Epoch 48/50:\n", "\u001b[2K [Elapsed 0:00:04 | 45.59 it/s] loss: 98.47498 \n", "Epoch 49/50:\n", "\u001b[2K [Elapsed 0:00:03 | 47.31 it/s] loss: 98.40941 \n", "Epoch 50/50:\n", "\u001b[2K [Elapsed 0:00:05 | 33.68 it/s] loss: 98.32704, val_loss: 100.99587 \n" ] } ], "source": [ "history = engine.train(\n", " train_loader,\n", " val_data=val_loader,\n", " epochs=50,\n", " eval_every=5,\n", " optimizer=optimizer,\n", " loss=loss,\n", " callbacks=[\n", " xnn.BatchProgressLogger()\n", " ]\n", ")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspecting the Model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Reconstructing Images" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "reconstructed = engine.predict(\n", " test_loader,\n", " reconstruct=True\n", ")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(dpi=150)\n", "\n", "im = next(iter(test_loader))\n", "for i in range(10):\n", " plt.subplot(1, 10, i+1)\n", " plt.imshow(np.concatenate([\n", " im[0][i][0].numpy(),\n", " reconstructed[0][i].sigmoid().numpy().reshape(28, 28)\n", " ]), cmap='binary')\n", " plt.axis('off')\n", "\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Generating Images" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "dim = 16\n", "distribution = D.Normal(torch.zeros(dim), torch.ones(dim))\n", "dist_data = xnn.NoiseDataset(distribution)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "generated = engine.predict(\n", " dist_data.loader(batch_size=10),\n", " iterations=1,\n", " reconstruct=False\n", ")" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure()\n", "\n", "for i in range(10):\n", " plt.subplot(1, 10, i+1)\n", " plt.imshow(generated[i].sigmoid().numpy().reshape(28, 28), cmap='binary')\n", " plt.axis('off')\n", "\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "epn", "language": "python", "name": "epn" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.3" } }, "nbformat": 4, "nbformat_minor": 4 }