diff --git a/W08_Generative_Vision/students/CIS_522_W8D1_Tutorial.ipynb b/W08_Generative_Vision/students/CIS_522_W8D1_Tutorial.ipynb index dfbb5c5..50c01e3 100644 --- a/W08_Generative_Vision/students/CIS_522_W8D1_Tutorial.ipynb +++ b/W08_Generative_Vision/students/CIS_522_W8D1_Tutorial.ipynb @@ -1,9900 +1,9898 @@ { - "cells": [ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "ML2DwqwkVwfo" + }, + "source": [ + "# CIS-522 Week 8 Part 1\n", + "# AutoEncoders (AEs) and Variational AutoEncoders (VAEs)\n", + "\n", + "__Instructor:__ Konrad Kording\n", + "\n", + "__Content creators:__ Richard Lange, Arash Ash, Jordan Matelsky\n", + "\n", + "__Content reviewers:__ Ann-Katrin Reuel" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "exeRQO8LnRZB" + }, + "source": [ + "## Today's agenda\n", + "In the first tutorial of Week 8, we are going to\n", + "\n", + "1. Think about unsupervised learning and get a bird's eye view of why it is useful\n", + "2. See the connection between AutoEncoding and dimensionality reduction\n", + "3. Start thinking about neural networks as generative models\n", + "4. Put on our Bayesian hats and turn AEs into VAEs" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "cellView": "form", + "id": "NBdRadpsIQME" + }, + "outputs": [], + "source": [ + "#@markdown What is your Pennkey and pod? (text, not numbers, e.g. bfranklin)\n", + "my_pennkey = '' #@param {type:\"string\"}\n", + "my_pod = \"Select\" # @param [\"Factorial Ferrets\", \"Causal Crows\", \"Recursive Roosters\", \"Bayesian Bighorns\", \"Probabilistic Pronghorns\", \"Hashing Hares\", \"Multiplicative Mustangs\", \"Curiosity Capybaras\", \"Subspace Salamanders\"]\n", + "my_email = '' #@param {type:\"string\"}\n", + "tutorial = 'W8D1'\n", + "\n", + "# start timing\n", + "import time\n", + "try:t0;\n", + "except NameError: t0 = time.time()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 320 + }, + "id": "vtPEm8gbshnH", + "outputId": "c9950faf-06cf-4bbc-93d7-9f4b10491058" + }, + "outputs": [ { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "id": "ML2DwqwkVwfo" - }, - "source": [ - "# CIS-522 Week 8 Part 1\n", - "# AutoEncoders (AEs) and Variational AutoEncoders (VAEs)\n", - "\n", - "__Instructor:__ Konrad Kording\n", - "\n", - "__Content creators:__ Richard Lange, Arash Ash, Jordan Matelsky\n", - "\n", - "__Content reviewers:__ Ann-Katrin Reuel" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/jordan/projects/.venv/lib/python3.10/site-packages/IPython/core/display.py:431: UserWarning: Consider using IPython.display.IFrame instead\n", + " warnings.warn(\"Consider using IPython.display.IFrame instead\")\n" + ] }, { - "cell_type": "markdown", - "metadata": { - "id": "exeRQO8LnRZB" - }, - "source": [ - "## Today's agenda\n", - "In the first tutorial of Week 8, we are going to\n", - "\n", - "1. Think about unsupervised learning and get a bird's eye view of why it is useful\n", - "2. See the connection between AutoEncoding and dimensionality reduction\n", - "3. Start thinking about neural networks as generative models\n", - "4. Put on our Bayesian hats and turn AEs into VAEs" + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# @title Slides\n", + "from IPython.display import HTML\n", + "HTML('')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Y_mmmZQ0TIBi" + }, + "source": [ + "\n", + "## Recap the experience from last week" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "xRPk6HG-Rj5N", + "outputId": "c91e5760-6742-4f43-b302-0b28bcf1364c" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 1, - "metadata": { - "cellView": "form", - "id": "NBdRadpsIQME" - }, - "outputs": [], - "source": [ - "#@markdown What is your Pennkey and pod? (text, not numbers, e.g. bfranklin)\n", - "my_pennkey = '' #@param {type:\"string\"}\n", - "my_pod = \"Select\" # @param [\"Factorial Ferrets\", \"Causal Crows\", \"Recursive Roosters\", \"Bayesian Bighorns\", \"Probabilistic Pronghorns\", \"Hashing Hares\", \"Multiplicative Mustangs\", \"Curiosity Capybaras\", \"Subspace Salamanders\"]\n", - "my_email = '' #@param {type:\"string\"}\n", - "tutorial = 'W8D1'\n", - "\n", - "# start timing\n", - "import time\n", - "try:t0;\n", - "except NameError: t0 = time.time()" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=VHhtye5SwY0\n" + ] }, { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 320 - }, - "id": "vtPEm8gbshnH", - "outputId": "c9950faf-06cf-4bbc-93d7-9f4b10491058" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/jordan/projects/.venv/lib/python3.10/site-packages/IPython/core/display.py:431: UserWarning: Consider using IPython.display.IFrame instead\n", - " warnings.warn(\"Consider using IPython.display.IFrame instead\")\n" - ] - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "# @title Slides\n", - "from IPython.display import HTML\n", - "HTML('')" + "text/plain": [ + "" ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Week 7 Recap\n", + "import time\n", + "try: t0;\n", + "except NameError: t0=time.time()\n", + "\n", + "from IPython.display import YouTubeVideo\n", + "video = YouTubeVideo(id=\"VHhtye5SwY0\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "5x61BA1qPubi" + }, + "source": [ + "---\n", + "# Setup" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "EuOTxAJdmhsl", + "outputId": "37725a62-5283-46a3-c89d-b607c09a1656" + }, + "outputs": [], + "source": [ + "# we need to first upgrade the Colab's TorchVision, mute output\n", + "!pip install --upgrade torchvision &> /dev/null" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "id": "uw7q7Z_ZPt66" + }, + "outputs": [], + "source": [ + "# imports\n", + "import matplotlib.pylab as plt\n", + "from tqdm.notebook import tqdm, trange\n", + "from math import sqrt\n", + "\n", + "import torch\n", + "import torch.nn as nn\n", + "import torch.nn.functional as F\n", + "import torch.optim as optim\n", + "import torchvision as tv\n", + "from torch.utils.data import DataLoader\n", + "\n", + "DEVICE = 'cuda' if torch.cuda.is_available() else 'cpu'" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "cellView": "form", + "id": "LID483Ou-z53" + }, + "outputs": [], + "source": [ + "# @title Figure Settings\n", + "%config InlineBackend.figure_format = 'retina'\n", + "%matplotlib inline \n", + "\n", + "fig_w, fig_h = (8, 6)\n", + "plt.rcParams.update({'figure.figsize': (fig_w, fig_h)})\n", + "\n", + "plt.style.use(\"https://raw.githubusercontent.com/NeuromatchAcademy/course-content/master/nma.mplstyle\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "cellView": "form", + "id": "rNg1RPFSH1Xc" + }, + "outputs": [], + "source": [ + "# @title Helper functions\n", + "\n", + "\n", + "def image_moments(image_batches, n_batches=None):\n", + " \"\"\"\n", + " Compute mean an covariance of all pixels from batches of images\n", + " \"\"\"\n", + " m1, m2 = torch.zeros((), device=DEVICE), torch.zeros((), device=DEVICE)\n", + " n = 0\n", + " for im in tqdm(\n", + " image_batches,\n", + " total=n_batches,\n", + " leave=False,\n", + " desc=\"Computing pixel mean and covariance...\",\n", + " ):\n", + " im = im.to(DEVICE)\n", + " b = im.size()[0]\n", + " im = im.view(b, -1)\n", + " m1 = m1 + im.sum(dim=0)\n", + " m2 = m2 + (im.view(b, -1, 1) * im.view(b, 1, -1)).sum(dim=0)\n", + " n += b\n", + " m1, m2 = m1 / n, m2 / n\n", + " cov = m2 - m1.view(-1, 1) * m1.view(1, -1)\n", + " return m1.cpu(), cov.cpu()\n", + "\n", + "\n", + "def pca_encoder_decoder(mu, cov, k):\n", + " \"\"\"\n", + " Compute encoder and decoder matrices for PCA dimensionality reduction\n", + " \"\"\"\n", + " mu = mu.view(1, -1)\n", + " u, s, v = torch.svd_lowrank(cov, q=k)\n", + " W_encode = v / torch.sqrt(s)\n", + " W_decode = u * torch.sqrt(s)\n", + "\n", + " def pca_encode(x):\n", + " # Encoder: subtract mean image and project onto top K eigenvectors of\n", + " # the data covariance\n", + " return (x.view(-1, mu.numel()) - mu) @ W_encode\n", + "\n", + " def pca_decode(h):\n", + " # Decoder: un-project then add back in the mean\n", + " return (h @ W_decode.T) + mu\n", + "\n", + " return pca_encode, pca_decode\n", + "\n", + "\n", + "# Helper for plotting images\n", + "def plot_torch_image(image, ax=None):\n", + " ax = ax if ax is not None else plt.gca()\n", + " c, h, w = image.size()\n", + " cm = \"gray\" if c == 1 else None\n", + " # Torch images have shape (channels, height, width) but matplotlib expects\n", + " # (height, width, channels) or just (height,width) when grayscale\n", + " ax.imshow(image.detach().cpu().permute(1, 2, 0).squeeze(), cmap=cm)\n", + " ax.set_xticks([])\n", + " ax.set_yticks([])\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "AeuJ4budZOas" + }, + "source": [ + "---\n", + "# Section 1: Supervised and unsupervised learning" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "NMCMAipWKMeZ", + "outputId": "895ff690-ce79-48ea-9595-38b15b8b1035" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "Y_mmmZQ0TIBi" - }, - "source": [ - "\n", - "## Recap the experience from last week" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=Vw9MLfb4bi4\n" + ] }, { - "cell_type": "code", - "execution_count": 3, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "xRPk6HG-Rj5N", - "outputId": "c91e5760-6742-4f43-b302-0b28bcf1364c" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=VHhtye5SwY0\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "#@title Video: Week 7 Recap\n", - "import time\n", - "try: t0;\n", - "except NameError: t0=time.time()\n", - "\n", - "from IPython.display import YouTubeVideo\n", - "video = YouTubeVideo(id=\"VHhtye5SwY0\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" + "text/plain": [ + "" ] - }, + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Datasets\n", + "\n", + "try: t1;\n", + "except NameError: t1=time.time()\n", + "\n", + "video = YouTubeVideo(id=\"Vw9MLfb4bi4\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "cellView": "form", + "id": "Ev8xgKVBiwCB" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "5x61BA1qPubi" - }, - "source": [ - "---\n", - "# Setup" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n", + "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./mnist/MNIST/raw/train-images-idx3-ubyte.gz\n" + ] }, { - "cell_type": "code", - "execution_count": 4, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "EuOTxAJdmhsl", - "outputId": "37725a62-5283-46a3-c89d-b607c09a1656" + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "782c4c71bc124eccaf8abacd8f1bd2ff", + "version_major": 2, + "version_minor": 0 }, - "outputs": [], - "source": [ - "# we need to first upgrade the Colab's TorchVision, mute output\n", - "!pip install --upgrade torchvision &> /dev/null" + "text/plain": [ + " 0%| | 0/9912422 [00:00\n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#@title Video: Datasets\n", - "\n", - "try: t1;\n", - "except NameError: t1=time.time()\n", - "\n", - "video = YouTubeVideo(id=\"Vw9MLfb4bi4\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Extracting ./mnist/MNIST/raw/t10k-images-idx3-ubyte.gz to ./mnist/MNIST/raw\n", + "\n", + "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n", + "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to ./mnist/MNIST/raw/t10k-labels-idx1-ubyte.gz\n" + ] }, { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "cellView": "form", - "id": "Ev8xgKVBiwCB" + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "3860caa90dc84603b6ed4dc2851c78dc", + "version_major": 2, + "version_minor": 0 }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n", - "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to ./mnist/MNIST/raw/train-images-idx3-ubyte.gz\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "782c4c71bc124eccaf8abacd8f1bd2ff", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/9912422 [00:00" - ] - }, - "metadata": { - "image/png": { - "height": 378, - "width": 945 - } - }, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "MNIST contains 60000 examples each of size torch.Size([1, 28, 28]) with values ranging in [0.0,1.0]\n" - ] - } - ], - "source": [ - "minval, maxval = float(\"inf\"), float(\"-inf\")\n", - "plt.figure(figsize=(10, 4))\n", - "for i in range(10):\n", - " idx = torch.randint(len(mnist), size=())\n", - " image, label_idx = mnist[idx]\n", - " plt.subplot(2, 5, i + 1)\n", - " plot_torch_image(image)\n", - " plt.title(f\"'{label_idx}'\")\n", - " minval, maxval = min(minval, image.min()), max(maxval, image.max())\n", - "plt.show()\n", - "\n", - "print(\n", - " f\"MNIST contains {len(mnist)} examples each of size {image.size()} with values ranging in [{minval},{maxval}]\"\n", - ")\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Extracting ./cifar10/cifar-10-python.tar.gz to ./cifar10/\n", + "Files already downloaded and verified\n" + ] + } + ], + "source": [ + "#@title Download a few standard image datasets while the above video plays\n", + "# See https://pytorch.org/docs/stable/torchvision/datasets.html\n", + "\n", + "# MNIST contains handwritten digets 0-9, in grayscale images of size (1,28,28)\n", + "mnist = tv.datasets.MNIST('./mnist/', train=True, transform=tv.transforms.ToTensor(), download=True)\n", + "mnist_val = tv.datasets.MNIST('./mnist/', train=False, transform=tv.transforms.ToTensor(), download=True)\n", + "# CIFAR10 contains 10 object classes in color images of size (3,32,32)\n", + "cifar10 = tv.datasets.CIFAR10('./cifar10/', train=True, transform=tv.transforms.ToTensor(), download=True)\n", + "cifar10_val = tv.datasets.CIFAR10('./cifar10/', train=False, transform=tv.transforms.ToTensor(), download=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DsczwVZsKzEE" + }, + "source": [ + "Unsupervised and semi-supervised learning are broad concepts that can be applied in many different domains. In machine learning research, however, computer vision is by far the most common domain for studying these things. Using image datasets will also let us build on what you learned last week. But keep in mind that the techniques you learn this week are quite general!\n", + "\n", + "It's always a good idea to visualize your data. Let's look at some samples of images in each of the example datasets we've downloaded:" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DICj-nphMuQo" + }, + "source": [ + "### Visualize MNIST examples" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 306 }, + "id": "kQTwy7Y1MxqW", + "outputId": "21bf0a2b-275c-4954-a222-884efc339ecf" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "DMSlLFGWN2Ha" - }, - "source": [ - "### Visualize CIFAR10 examples" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 378, + "width": 945 + } + }, + "output_type": "display_data" }, { - "cell_type": "code", - "execution_count": 12, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 289 - }, - "id": "sKW3GfHQPeFf", - "outputId": "44960717-2e5c-49c9-8f90-fd3090590d77" - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 378, - "width": 945 - } - }, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CIFAR10 contains 50000 examples each of size torch.Size([3, 32, 32]) with values ranging in [0.0,1.0]\n" - ] - } - ], - "source": [ - "minval, maxval = float(\"inf\"), float(\"-inf\")\n", - "plt.figure(figsize=(10, 4))\n", - "for i in range(10):\n", - " idx = torch.randint(len(cifar10), size=())\n", - " image, label_idx = cifar10[idx]\n", - " plt.subplot(2, 5, i + 1)\n", - " plot_torch_image(image)\n", - " plt.title(f\"'{cifar10.classes[label_idx]}'\")\n", - " minval, maxval = min(minval, image.min()), max(maxval, image.max())\n", - "plt.show()\n", - "\n", - "print(\n", - " f\"CIFAR10 contains {len(cifar10)} examples each of size {image.size()} with values ranging in [{minval},{maxval}]\"\n", - ")\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "MNIST contains 60000 examples each of size torch.Size([1, 28, 28]) with values ranging in [0.0,1.0]\n" + ] + } + ], + "source": [ + "minval, maxval = float(\"inf\"), float(\"-inf\")\n", + "plt.figure(figsize=(10, 4))\n", + "for i in range(10):\n", + " idx = torch.randint(len(mnist), size=())\n", + " image, label_idx = mnist[idx]\n", + " plt.subplot(2, 5, i + 1)\n", + " plot_torch_image(image)\n", + " plt.title(f\"'{label_idx}'\")\n", + " minval, maxval = min(minval, image.min()), max(maxval, image.max())\n", + "plt.show()\n", + "\n", + "print(\n", + " f\"MNIST contains {len(mnist)} examples each of size {image.size()} with values ranging in [{minval},{maxval}]\"\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "DMSlLFGWN2Ha" + }, + "source": [ + "### Visualize CIFAR10 examples" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 289 }, + "id": "sKW3GfHQPeFf", + "outputId": "44960717-2e5c-49c9-8f90-fd3090590d77" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "Pa0bqPRVR2vN" - }, - "source": [ - "The goal of today is to make sense of these images in an _unsupervised_ way, that is without the labels." + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 378, + "width": 945 + } + }, + "output_type": "display_data" }, { - "cell_type": "markdown", - "metadata": { - "id": "sTr705q3aZRG" - }, - "source": [ - "### Select a dataset\n", - "\n", - "We've built today's tutorial to be flexible. It should work more-or-less out of the box with both MNIST and CIFAR (and other image datasets). MNIST is in many ways simpler, and the results will likely look better and run a bit faster if using MNIST. But we are leaving it up to you to pick which one you want to experiment with!\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "CIFAR10 contains 50000 examples each of size torch.Size([3, 32, 32]) with values ranging in [0.0,1.0]\n" + ] + } + ], + "source": [ + "minval, maxval = float(\"inf\"), float(\"-inf\")\n", + "plt.figure(figsize=(10, 4))\n", + "for i in range(10):\n", + " idx = torch.randint(len(cifar10), size=())\n", + " image, label_idx = cifar10[idx]\n", + " plt.subplot(2, 5, i + 1)\n", + " plot_torch_image(image)\n", + " plt.title(f\"'{cifar10.classes[label_idx]}'\")\n", + " minval, maxval = min(minval, image.min()), max(maxval, image.max())\n", + "plt.show()\n", + "\n", + "print(\n", + " f\"CIFAR10 contains {len(cifar10)} examples each of size {image.size()} with values ranging in [{minval},{maxval}]\"\n", + ")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Pa0bqPRVR2vN" + }, + "source": [ + "The goal of today is to make sense of these images in an _unsupervised_ way, that is without the labels." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "sTr705q3aZRG" + }, + "source": [ + "### Select a dataset\n", + "\n", + "We've built today's tutorial to be flexible. It should work more-or-less out of the box with both MNIST and CIFAR (and other image datasets). MNIST is in many ways simpler, and the results will likely look better and run a bit faster if using MNIST. But we are leaving it up to you to pick which one you want to experiment with!\n" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "4aiHOutIa7E_", - "outputId": "3ba50e62-962f-4bc4-98ee-9e0f5f94cd64" - }, - "outputs": [], - "source": [ - "# Uncomment this to select MNIST\n", - "my_dataset = mnist\n", - "my_dataset_name = \"MNIST\"\n", - "my_dataset_size = (1, 28, 28)\n", - "my_dataset_dim = 28*28\n", - "my_valset = mnist_val\n", - "\n", - "# Uncomment this to select CIFAR\n", - "# my_dataset = cifar10\n", - "# my_dataset_name = \"CIFAR\"\n", - "# my_dataset_size = (3, 32, 32)\n", - "# my_dataset_dim = 3*32*32\n", - "# my_valset = cifar10_val" - ] + "id": "4aiHOutIa7E_", + "outputId": "3ba50e62-962f-4bc4-98ee-9e0f5f94cd64" + }, + "outputs": [], + "source": [ + "# Uncomment this to select MNIST\n", + "my_dataset = mnist\n", + "my_dataset_name = \"MNIST\"\n", + "my_dataset_size = (1, 28, 28)\n", + "my_dataset_dim = 28*28\n", + "my_valset = mnist_val\n", + "\n", + "# Uncomment this to select CIFAR\n", + "# my_dataset = cifar10\n", + "# my_dataset_name = \"CIFAR\"\n", + "# my_dataset_size = (3, 32, 32)\n", + "# my_dataset_dim = 3*32*32\n", + "# my_valset = cifar10_val" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Z4Gl5z8zlRWH" + }, + "source": [ + "---\n", + "# Section 2: AutoEncoders\n", + "## Conceptual introduction to AutoEncoders\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "DQouSlpSaooX", + "outputId": "14bc155a-c6c5-46b5-9fe0-1fd8ed90a3ca" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "Z4Gl5z8zlRWH" - }, - "source": [ - "---\n", - "# Section 2: AutoEncoders\n", - "## Conceptual introduction to AutoEncoders\n", - "\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=QwsHAKDN_vw\n" + ] }, { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "DQouSlpSaooX", - "outputId": "14bc155a-c6c5-46b5-9fe0-1fd8ed90a3ca" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=QwsHAKDN_vw\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "#@title Video: Linear Autoencoders\n", - "\n", - "try: t2;\n", - "except NameError: t2=time.time()\n", - "\n", - "video = YouTubeVideo(id=\"QwsHAKDN_vw\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" + "text/plain": [ + "" ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Linear Autoencoders\n", + "\n", + "try: t2;\n", + "except NameError: t2=time.time()\n", + "\n", + "video = YouTubeVideo(id=\"QwsHAKDN_vw\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "QkephF68qxjP" + }, + "source": [ + "## Build a linear AutoEncoder" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "GWBr4YYTbgGE" + }, + "source": [ + "Now we'll create our first autoencoder. It will reduce images down to $K$ dimensions. The architecture will be quite simple: the input will be linearly mapped to a single hidden layer with $K$ units, which will then be linearly mapped back to an output that is the same size as the input:\n", + "$$\\mathbf{x} \\longrightarrow \\mathbf{h} \\longrightarrow \\mathbf{x'}$$\n", + "\n", + "The loss function we'll use will simply be mean squared error (MSE) quantifying how well the reconstruction ($\\mathbf{x'}$) matches the original image ($\\mathbf{x}$):\n", + "$$\\text{MSE Loss} = \\sum_{i=1}^{N} ||\\mathbf{x}_i - \\mathbf{x'}_i||^2_2$$\n", + "\n", + "If all goes well, then the AutoEncoder will learn, **end to end**, a good \"encoding\" or \"compression\" of inputs ($\\mathbf{x \\longrightarrow h}$) as well as a good \"decoding\" ($\\mathbf{h \\longrightarrow x'}$)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Rlb6MaPJk0kB" + }, + "source": [ + "The first choice to make is the dimensionality of $\\mathbf{h}$. We'll see more on this below, but For MNIST, 5 to 20 is plenty. For CIFAR, we need more like 50 to 100 dimensions.\n", + "\n", + "Try a variety of values for $K$ in each dataset to get a feeling of it's impact." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "id": "zYZNBb2olR4t" + }, + "outputs": [], + "source": [ + "# Pick your own K\n", + "K = ..." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Kl3x376LldRq" + }, + "source": [ + "### Exercise 1\n", + "### Fill in the missing parts of the `LinearAutoEncoder` class and training loop\n", + "\n", + "1. The `LinearAutoEncoder` as two stages: an `encoder` which linearly maps from inputs to a hidden layer of size `K` (with no nonlinearity), and a `decoder` which maps back from `K` up to the number of pixels in each image (`my_dataset_dim`).\n", + "2. The training loop will minimize MSE loss, as written above." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "id": "ejGv1nxRmHCp" + }, + "outputs": [], + "source": [ + "class LinearAutoEncoder(nn.Module):\n", + " def __init__(self, K):\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your class\n", + " raise NotImplementedError(\"Please complete the LinearAutoEncoder class!\")\n", + " #################################################################### \n", + " super(LinearAutoEncoder, self).__init__()\n", + " self.enc_lin = ... # your code here\n", + " self.dec_lin = ... # your code here\n", + " \n", + " def encode(self, x):\n", + " h = ... # your code here\n", + " return h\n", + " \n", + " def decode(self, h):\n", + " x_prime = ... # your code here\n", + " return x_prime\n", + "\n", + " def forward(self, x):\n", + " flat_x = x.view(x.size()[0], -1)\n", + " h = self.encode(flat_x)\n", + " return self.decode(h).view(x.size())\n", + "\n", + "def train_autoencoder(autoencoder, dataset, epochs=20, batch_size=250):\n", + " autoencoder.to(DEVICE)\n", + " optim = torch.optim.Adam(autoencoder.parameters(), lr=1e-3, weight_decay=1e-5)\n", + " loss_fn = nn.MSELoss()\n", + " loader = DataLoader(dataset, batch_size=batch_size, shuffle=True,\n", + " pin_memory=True, num_workers=2)\n", + " mse_loss = torch.zeros(epochs*len(dataset)//batch_size, device=DEVICE)\n", + " i = 0\n", + " for epoch in trange(epochs, desc='Epoch'):\n", + " for im_batch, _ in loader:\n", + " im_batch = im_batch.to(DEVICE)\n", + " optim.zero_grad()\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your function\n", + " raise NotImplementedError(\"Please complete the train_autoencoder function!\")\n", + " #################################################################### \n", + " loss = ... # your code here\n", + " loss.backward()\n", + " optim.step()\n", + "\n", + " mse_loss[i] = loss.detach()\n", + " i += 1\n", + " # After training completes, make sure the model is on CPU so we can easily\n", + " # do more visualizations and demos.\n", + " autoencoder.to('cpu')\n", + " return mse_loss.cpu()\n", + "\n", + "# Uncomment to test your code\n", + "# lin_ae = LinearAutoEncoder(K)\n", + "# lin_losses = train_autoencoder(lin_ae, my_dataset)\n", + "\n", + "# plt.figure()\n", + "# plt.plot(lin_losses)\n", + "# plt.ylim([0, 2*torch.as_tensor(lin_losses).median()])\n", + "# plt.xlabel('Training batch')\n", + "# plt.ylabel('MSE Loss')\n", + "# plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "UxSA-0UgPNc1" + }, + "source": [ + "One way to think about AutoEncoders is that they automatically discover good dimensionality-reduction of the data. Another easy and common technique for dimensionality reduction is to project data onto the top $K$ **principal components** (Principal Component Analysis or PCA). For comparison, let's also do PCA." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 17, + "referenced_widgets": [ + "80e074ada4d642d58c690fdd14020d13", + "69b3eb3b86c0451984fc07a02958dd45", + "d825e4a7719649f7b5a8f5bb2e8ccef4", + "a7501605ea394d47884111fdb2de00ea", + "22c8ca666f614b7dbb9ac0fa3f4e095a", + "76952d837cf7418795fb34158c80bd27", + "311f5429f3b146edbc9b8f6f528681d1", + "f8a4466e613344cd9a0f4f654726d3e7", + "441952e7c48e4366a3044537aadb330b", + "6067d9f4878e4a7597d7980fb4f57457", + "a30b5754bc1c49e7a0d6c0cda84a23e9" + ] }, + "id": "1At-bwcmPzwx", + "outputId": "a8cc9263-70e9-4d2a-ee25-40602b6418e9" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "QkephF68qxjP" + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "55cec385711c4b96a2fc1224e9326bb6", + "version_major": 2, + "version_minor": 0 }, - "source": [ - "## Build a linear AutoEncoder" + "text/plain": [ + "Computing pixel mean and covariance...: 0%| | 0/1875 [00:00" ] + }, + "metadata": { + "image/png": { + "height": 409, + "width": 974 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "n_plot = 7\n", + "plt.figure(figsize=(10,4.5))\n", + "for i in range(n_plot):\n", + " idx = torch.randint(len(my_dataset), size=())\n", + " image, _ = my_dataset[idx]\n", + " # Get reconstructed image from autoencoder\n", + " with torch.no_grad():\n", + " reconstruction = lin_ae(image.unsqueeze(0)).reshape(image.size())\n", + " \n", + " # Get reconstruction from PCA dimensionality reduction\n", + " h_pca = pca_encode(image)\n", + " recon_pca = pca_decode(h_pca).reshape(image.size())\n", + " \n", + " plt.subplot(3,n_plot,i+1)\n", + " plot_torch_image(image)\n", + " if i == 0:\n", + " plt.ylabel('Original\\nImage')\n", + " \n", + " plt.subplot(3,n_plot,i+1+n_plot)\n", + " plot_torch_image(reconstruction)\n", + " if i == 0:\n", + " plt.ylabel(f'Lin AE\\n(K={K})')\n", + " \n", + " plt.subplot(3,n_plot,i+1+2*n_plot)\n", + " plot_torch_image(recon_pca)\n", + " if i == 0:\n", + " plt.ylabel(f'PCA\\n(K={K})')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9m5arq_hqdLJ" + }, + "source": [ + "## Quiz Question 1\n", + "\n", + "Compare the PCA-based reconstructions to those from the linear autoencoder. Is one better than the other? Are they equally good? Equally bad?" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "cellView": "form", + "id": "9iqm4O6VnK6i" + }, + "outputs": [], + "source": [ + "linear_ae_vs_pca = \"\" #@param{type:'string'}" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Z80iE-ssiwsW" + }, + "source": [ + "If you're interested, Appendix C includes a plot of explained-variance as a function of $K$, as well as some discussion of why fraction of explained variance using PCA is a rough and not very good guide to choosing $K$ for a given dataset." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "yu1RomPmrAYm" + }, + "source": [ + "## Building a nonlinear convolutional autoencoder\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "SgKS9x0vS_oR", + "outputId": "7d272c24-6743-463f-d023-f25790aa7870" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "Rlb6MaPJk0kB" - }, - "source": [ - "The first choice to make is the dimensionality of $\\mathbf{h}$. We'll see more on this below, but For MNIST, 5 to 20 is plenty. For CIFAR, we need more like 50 to 100 dimensions.\n", - "\n", - "Try a variety of values for $K$ in each dataset to get a feeling of it's impact." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=mzHY6rW_4Eo\n" + ] }, { - "cell_type": "code", - "execution_count": 14, - "metadata": { - "id": "zYZNBb2olR4t" - }, - "outputs": [], - "source": [ - "# Pick your own K\n", - "K = ..." + "data": { + "image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEABALDBoYFhsaGRoeHRsfIiomIyIhIictJiIuMi01MC0tLjE2PVBCOjhLOi8tRGFFS1NWW1xbNUVlbWRYbVBZW1cBERISGRYZLxsbL1c9OT1XV1ddV1dXV1dXV1dXV1dXV1dXV1dXV1dXV1dXV11XV1dXV1dXV1dXV1dXXVdXV1dXV//AABEIAWgB4AMBIgACEQEDEQH/xAAbAAEAAgMBAQAAAAAAAAAAAAAAAQQDBQYCB//EAEQQAAIBAgMEBgcGBQMEAgMBAAABAgMRBBIhBTFBURMUIlNhkjJxgZGh0dIGFzNCUrEVFiPB8HJz4WKCsvE0Q2ODkwf/xAAYAQEBAQEBAAAAAAAAAAAAAAAAAQIDBP/EACMRAQEBAQACAgICAwEAAAAAAAABEQISIQMxIkFh8BNR0QT/2gAMAwEAAhEDEQA/APn4AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAOw+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ow+7jG97h/NU+gfdxje9w/mqfQBx4Ouqf/53jIxcnVw9km/Snw/7DWfyvX/XS98vpA0gN3/K1f8AXS98vpJ/lWv+ul75fSFxowbz+Va/66Xvl9JP8qYj9dL3y+kamNEDe/ypiP10vfL6Sf5TxH66Xvl9IMaEG+/lLEfrpeaX0k/yjiP10vNL6QNADoP5QxH66Pml9I/k/E/ro+aX0jRz4Oh/k7E/ro+aX0j+TsT+uj5pfSTRzwOh/k/E/ro+aX0kfyfif10fNL6Ro58G/f2RxH66Xml9J5f2UxC/PS98vpGj7GAQUSDFDEQlJwjOLlHfFSTa9a4B4iGfJnjn35brN7gYyggASCDzVqRhFylJRildtuyXrYHsHilVjOKlFpxkk01uae5noCQQAJBAAkEACQYaeJhKcoRnGUoWzRTTcb7r8tzMoEggx18RCmk6k4wTaSzNK7e5LxAyghuyu9LHijWjUhGcJKUZK6a3NcwMgIAEggASCABIMWIxMKUHOpOMIre5NJGQCQQY6deEpThGScoWzJPWN1dX9gGUEACQQY6eIhOUoxnGUoWUkmm434PkBlAAAAAAABhxf4VT/TL9ji0dpivwp/6X+xxyiStR51PSbPSielEivGpKTMiielEIxpMlJmVRPagBhSfI9JPkZ1A9KAGCz5HpRfIyylGO9pHqLT3NP1BNYlB8icj5FhIlRIK2R8iOjfIt2GUClKlLkUatSza5G5cTT7RhlqeDVwO3IJINo0e1MFOeJ6Wg8telTi4fpmnKWaEvB29hkwm06dacayustKpni/Sg4yjmi/FGwWHfTOpn0cVHLl5NvffxMa2ZTWInXStKpDJNcJeL8eBMdPKZlU/4pUVLD15KPRVnBOKTzQz+i73s96T0W8x4natanTxN1TdShNWjll24SSaaV733+VlqhsjLCnSlUcqNKSlCLWunopy4pergjPPZ8JYhV36Sg4W4Pk34pOS/7mPZvKcNiHUn2XF01CLuk7uUtd991rP2mXGfhVP9Ev2KH8OlQwypYecoyUrp2TvrpF33RtZepGwrU3OEo3tmTV7XtcM3N9NPs3Fyjh8HSgu1LDxm3lcrJKK3Jri+fA81cVipTwallpSlUnGccrallhJp+luaV7fIsy2K1Ch0daUKlCOSM1FO8dFaUXo9yM1bZjl0L6WXSUpueeybk3Fxem7c/YT23bzuve1sVKhh51YZW420knZ6pcH4mKtjqkcROmoqaVB1IpXUnJO2W/iWcdhFXozpSbSkrXW9cmVP4VN1HUliJZ3RdK6jFLV3zLlYrMzPb1sraHWLtVITikrpRcZwlrdSi22v/YxWKrLFQo0+jSnTnJSkm2nFxW5NXXa3fEy0MBlrOtKSlUcFC6jluk766u7JqYJyxEK2ezhCUFG2jUmm/wDxQPWtZDa2I6GFaSpZVW6KpFKV5f1OjzRd+zrrZ39Zn2htOpRlN2haNSnFR1cpRk4pybT7Ordrr8viev4N/QdHpdHV6W+VXvn6S2/df4EV9hufTLppRjVqRqNZVpKOXi+HZWhPbX46ryxXR7QxEYuPS1IUY083otrpG7+z2l2vi6iqdDBx6RU1OUskmtW1HsqXg+PAx4nYqqyrSlUd6kYK9rODhdxlF89We6+y5ynTqxryhWjHI5qKanHfaUd2/UvtLeas4GrUqUYyq0+iqNdqL1s/lxNBXqVZ7PqSqSU31lJdlrdiUub00Xq8TpKFLJFRu5c297fFs10ti3pTpKq8kqvSLsrsvP0lvHtfAU5sleqWMrdNXoz6NyhTjUg4qSVm5LLLV3tl36eorR2y40MLUnkpRrU7yqOLdOErRyx36J3erfDxL72e+mnW6TWdNU7ZdEk209/OTMdDZkqdKlTjVTjTpunaUE1NaWurrVW+LHs/Fbo1X0UZzy3yJyy+je13bwKeExdapGjWUYdDUjmktVKEWrxd768mrcS1g8HGjRhRjrGEcuvFFXAbJdG0FWnKjF9im0uzyTlvaXBBn17V5bXqLDwxdoujKSvGzzKEpZVK99+qdreBGK2liIrGOKpWw2uqk86yZmt6s/H4FinsZRp9Dnbw6nmUGtV2syjmv6N+FvC5NTZWZYpOppiVaXZ9Hs5dNeQ9tbyPHTWIoxllVGtBuLs8ymknlbvbVXe7geVtCo5UafYz1s8k7O0acdztfVu8eK3vlrmxWzI1aMKU5PsOLUlo+z81de094zAKpKlOMslSk24StdWas4tcU0E/FqNq4yVTCY6lUS6Sikm43tJSSlFpPdv3eBs44ufW5UOzlVGNSLs7puTjZ66rTwPFfZCqUq8HPtV2ukmlySSSXBWSMlTZ8nWjWjVcZZOjnaK7SvdWvud78949rvOZ/f01lPaFeutnTUoQ6Zyco5W1dQk1x3eBZq7WdJ4xzjG1F01HLdOTmla79bSPVHYmSlhoRrSvh23GWWOqacWrepmWpsiM3iOkk5RrqOZWtlyqyafx9ZPa287/AH/f/ETxlWnXpUqmSSrKWWUU1llFXs1d3TV9fAqYXa1eUMNVmqWSrU6OUYqWZNuSUk7+G63tNhTwEs0J1KmedOLUHlta6s5PXV29XEwU9jZaVGkqrtRqZ08qu3dtJ67tWX2kvLxX2lUhUimoWddU3FXbUX6MnJOyb32aMmA/+bjP/wBX/izw9hu2VV5KKrdNFZY6PNmab46t/wDJbw+CcK1Wrnv0uW6tuyqy1BbM9LgAK5gAAAADFifw5/6X+xyaidZifw5/6X+xzEYkqx4UT2oHtRPaiRWNQPagZFEyRiBiVM9qmZlE9KIGHIajF7UyNx9nqN9Y4/HQ6TEStorvdx8TXOftjqW+oqPGXe98feZsJjZc2rG0wmwackm9GZpbCjDxRufPEv8A5q8YDaiSSfvZvYK6ucdjcNKnU0eljo/s9jYVaTgtJU9JL17mO8s8ozxvN8a2GQZDNlGU4urA4Gt2zR7Cl+l/ubpxMGLoZ6c4807evgBtwAbQAAAAAQCQAAAAgkACCQAAAEAkACCQAAAAAAQCQAAAAAAAAAAAAAAAAAAAAAAYsR+HP/S/2ObijpcR+HP/AEv9jnYkqxMYntIhHtEVMUZEeUTcD2iTymLhFHbmM6DDymtbtR32dm9bPna5zFXailUdSFPKrJJNqy0Np9scTajCnb0nmvyt/wCzR4Kcei1hf3er+xb9Lz9r2D25JXT38Eru78C5Q+0FR3zUuxxau2jHsynRdF6x6bOppO3DdFP1ae0uUsPg6ss0IzTerjGMrvwvuRzuPR+WNZtHGwkuzJS/c6DY9ShHouhg100XrazfR6Nv13NDt7CU6NKlGKWd+k1z3v8AcvfYulmdSo7vKlGN3oru7S9yOku8vN1M611VibEomxBFjw0ZTyyIuAA2MOKxCpU5VGm1FXst7FCrKSblCVPXdJx19zZi2nRlUoVIRV3JWS9pUxuzl2MkHKCcnKF0220kn29NLP3gbUXNLPZVR5Yxk4wcE5XaclOCtC7W/er/AOhHips6o1CVSGdyUnUjHJpOVrNZtNEst94G9BrsHgLVJTqRu1kySk02moJN35+JW2lQ6TEziqXST6COV3SyPNO0rvVezXQDdXFzT9UqKvm6Nfmi5rL204qzbvd6rdwPNTZlsPTgqMXNwSm7RbUlCyerte+l9bAboXNJPZ85xnKVPttUcrbWZZbZtb6cSa+zpJzUYf0lWUlTjls10aWienpXdmBucyva6vvsTc09PAOM4Pom30bipPI5UnmbTfqT4GGjs6apuPRyjL+mpdqGWVpptq2rdr6vUDfXBq62By16UqVFWVr6RyJXu2uKlxut/E2gEgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADHiPw5/6X+xzqOixH4c/9L/Y51EV6TPSkeLi4GVSGYxpk3AyZjxKoQ2Y5MCltOgqs6V7PSoldXWsdH8DnKNN0oWkr9qSt6nZnR1qq6elFtJ2m0ub0X7XNVj8RRnGUYyWeNRvTinv1F+l59Vk2VUgpRnKhNpXu1G/tOip4ilJ54WafLx3Gn2Dh7tN1Fb9L+ZeqJutKMbacjlXq3IxbR2JPFVqLvloWldr0k/U+dkbvZOzY4WiqUXfVtye9tmeglljbdYzI6T1Hl6u3SwJBWUEMkhkFsAGh5nJRTbaSW9vcRTqRkrxakuad0U9t/wDxau7dx3b0a2OKdKVZwdNuTptzp26OCby6rdfjdvlyA6AGnWLqOVLNWhGOaaclkalZJpPWye/RGNY+pGGtVOTrShLSK6NJztv01ypK/MDeEZFmzWWa1r21ty+LNZQxNapKEOkgrwlJuKUr2nZcbareZdq4ipDIqejlmSsk22ldKza036gXwajrtVVsjlFOLgnGTisyaV3vvvbtZcCI46soqbanmhVajltrB6AbgGmp4+q46VISvKmk+y7ZnZ3UXu5GWpi5061ODqqXajGayxXpXs997+rQDZxkmrpprwJNDh6+SF3JU1GnOTnlTa/qvT/gmptGpClCTrRlO2aUUotWutG78Lpaa3A3oNLWxMr1lKpGVq1NRg1HROVPXnxMkdoTzp54XdXo+ht2ks1s3Pd2uVveBtgavZ+LqylRzyUlVhN2UbZXFq1vebUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADHiPw5/6X+xziZ0so3TT3PQq/wyl+l+ZgaO5Fzefwuj+l+Zj+F0f0vzMDSJnpSNz/AAuj+l+Zj+GUv0vzMDSuRhq1FFXbSOgey6P6X5mV5/Z3DS3xk/XUn8wOJ23iIVIrJdzi9Hu0e+xrMNhXvfu5H0R/ZbB3v0cv/wCk/me4/ZvCrdCS/wC+XzFJcvtw2HoTT0udTsykopNX7STv48TcQ2PQjuhu8WZY4CmlZJr1NnO811ncjnsVip0pRjCdpJvThbxRao7aX/2R05x/ui9LYGHcnJxk5PW+eXzD2Dh/0S88vmbkyOPV6t2PeHxdOp6Ek/3Mxhp7GoR9GLXqnL5lyFJJW19ruUm/thIZYcER0SIrIACiJRTVmrrxPMacUrJJLkloVtq1ZQw9SUW1JLRretSrhMc4ucZynJKUFHPFRqdt5btWXZvxtzA2fRRsllVluVlYOnHXsrXfotfWVKm0bTUY05TbqODs4qzUc3FnnaVaalRhDMlUm1KUct0lFu2vq9yYF6MEtyS4FXG4BVmm3ZpNWcYyWvg1v03mPD7RzZEoTm3CEm0krKV1d6+G48raydOM40pyUpqCV48fbo/BgXKOHjCMI2vkSSctZaeJkUFyWm4lPTkazBbT/px6VSTySnnaVpKL13etAbFU4rdFLW+5b+YdOLd2k3zsVHtNL06c4PR2kl6LaWbR7k2r8iae06cpZY3b6To7c3a7fq0evgBadKL0yq3qRHQQ3ZI+5FfG4zJeMYylPI5dm3ZS4u75mGntJKnFuM55YRdSaStG8U9f30AvunG98qv6kTkV81lfnbUx1sSoZL7pyy34K60v693tRUjtmk4Kfat229NUo8X67xt/qQF9QStZLTdpuPRVwWNjWzW0cWrq8Xv1WqbR5/iMLRdpaua4fkvf/wAWBcIKMdqRytuE49mMop2vJSdo2s999DHR2hJTqqcZ5ukUYU+zm/DUnre3N7wNmQYcPiVUi2k04tqUXvTXD9veUIbSnN0JRpzSmpvJePask073A2wNbU21SiovWzgpv0Vli+ab1e/RX3FvE4pU1HRycnaMY2vJ2vx8E2BnBSntC2nRVHJRUpRSjeCd9+ur0eiuQ9pwvpGTj2LzVsqz2yvffigLxBRe1adldSvaV1bWLjJRs/FydkeMRj20koypzVSkmpWu4ymlwurb0BsQU3tKOWMlGTzZ7LT8l78fAxx2krRnNSgnTlPK0nuceKf/AFbgNiQUZbTUU81OcZLL2Xlu1KWVNWdt5jxWMlKCVPNCr0qhlai9fSae/TLd6AbMEEgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACCSAJAAGHFYdVacoSbSkt63ld7Mi8zlOcpvL221eOV5laytv13F4AUv4bG2k5qWdzzXV7tZXwta3gZ6uHU5Qk73g217YuOvsbMwAq4bBRpei36EYa8o3t7dTF/C42l255pSjLN2bpx3cLe9F8AYcPRcM15ud5XV+Cslb4X9phWzaeWEXdxjCULN71K17+4uACnDZ8e1nlOo3Fw7bWkXvSskTQ2fTpyhKK1hDo0/Df7y2AK2JwaqPNmlCWVxbjbVPg7pmGWy4WspTUXFRlFNWmkra6ctNLF8AYcTho1acqc12ZK3/owvZtJuo8v4kVGVtNForcuHuRcAGHD0HBO9Sc78ZW09yRXWzIXvmna82o3Vlnvmtp4svACnLZ0GrNy0hGC13ZXdP13PK2ZHV9JNzcs+e8cyeXLppa1tNxeAGHDYdU00m2280pPfJ838DDh9nxpuFpSahdRTtZJ8NxcAFGOzIxUck5wcYqN4tXkluvdeL18TPicMqijdyi4u8ZResXa37Nr2mcAUp7OT16SopOOWUk1ea136eL1Vj1/D4WlFXSeTRcMlrW9yLYAqS2dTbqu2tW2Zp8Y7muXM8rZ0d8pznK8Hmk1fsO8VorWuXQBSjsyCknmm0nO0W1ZZ75uF+LIWy4WUZSnNKDgrtaRduSW7Ki8AKP8Ni7uc5zk8vak1dKMsySsrb0ZlhUpSkpSTlNTe7XsqNvVoWABBIAAAAAQAJAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABBIAAEACQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAIAkhySV3okajHbehC8aUXUmnZ8Ip7nrx9hzO1MbXqv+rO8HuS0ivBr+7LjHXc5dxh8TTqpypzjNJ2bi76mY+e7MxdWjUz0fVJPSElyfzW47jA46FeGaO9elF74vxFicdzpaBBJHRDdgafb+KcOjhF63ze7d8f2NrQqqcIzW6STJrM624yAArQAAAAAAAAAAAAAAEMCTxUqRgnKTUUuLdkabG7fSuqMcz/VLRexb37bGixOKnVeaUpTkuHBeFtyLjl18sn03uL+0Cu40Y3a/NK6XsW9/AtbK2rGusrsqq3rg/FfI5KWqvJ5bfD28RQr3aydlx1TWntii44z5ut2u/Bqdk7XVX+nNpVV7pf8+BtTL1SyzYkhuwNR9oMU4xhCLs283u3fH9iW4dXJrcAxYasqlOM1+ZJmUqgAAAAAAAAAAAAAAAAAAAAAAAABAEggkAAQBIIAEkEgDS7Z2Xn7dJLpXvjuU9L68npv/wAXOOje6nrwcWrJeDXzO3WtRv8ASre16v4WKuP2bRqZqko3kovi1fTS64llce/i8vccvhcPUm8sIuUd2bhHhZv5XOg2dsroKkZzneTTXZ0ivB8/byLWPxVGhStOcaat2Vx9kUe8NiYYmip05XT98X4+KC8fHzzf5WgeKU8y13rRrkz2R1aTbOBvJVHN9qUYWtuTNpgcN0NNQzZkm7Nor7X9Cn/uw/cvkz2xJPK1IIBW0gAAAQBIIAEgAAAABBIA0u2Nj9JepT0n+aK0U/8An9zm3F37Ky20d1b2WO9NVtfZCrduGlTityn4Px8SyuHyfFvuOTnCM1xc1716+B5pYbXtN5uS/tzN1g9h1Klm/wClFaa734W+ZuMFgqVFwcUnNqzbd5Xtf2bnuLrnz8XV/hp9n7Gq1EnL+lHen+Z8mlw9p1EI2STbdlve9+J5p6Nx8br1P/m5kMvRxxOfpBpdtYG7VVzerjFK25Nm7KG2Pwo/7kP3Jfpe5sZsBhehp5M2ZXbV1uLJBJVkwAAUAAAAAAAAAAAAAAAAAAAAADXbdx8sNhp1YKOZOKTlfLHNJRzS8Fe5sTzOKaakk09GnuYGohj6lHLGpVhiZ1JKMFSioWbjKTveTVrRdmeKX2mpzyZKVRxkqet4qzqXyrfzjYvR2XhVTdNYeiqcmm4KnHLJ8G1bUw47EYXDyipwTnKzjGFJzm8nou0U3aN9HwAq0/tRTnFOFKpK6k0nlXoQUqm9745kvXfkecN9o05VXJOULydOys8saEKut+PaZs44fD16UL0qcqcn0kYypre9XLK1o7t+J6q4DD1LqdGlO8szzQi7yta/rtp6gNU9vyk3am4QVahDNpJvpFCVmrq2k9+v9j3D7T02o2pT7apumrx7cak8kXv014MsKWDeJVLoodNZWbo2TyWaUZ2s8uj0ensMuFo4WU6sadKnmhUi6loJduynGW7V6p3AzbOxixFKNRJxu2mna6abi1p4plluyuzBOVPD0pSyqMI3bUY83duy8TntobfnUThSXRxatmdnJ+zcvia54vX0z13Oftu6uOpYemp1pqOa8rfmd9bJb3y9hzm0vtVOpGUaEckWn2pWcn6luXxNFXlLO3Ubc3+ZttyMDT4afuztPjk+3G/Lb9Pc6zbzVJOUn+Zu7Zb2ZtKrhqmeG5+lF7pr+z8SlHLlT5riFJ7uHNm8mY57719EwOPp1kqtN6S7M098ZcL/ALe4vnzXB4qdCeeD1taSe6S5P/NDvNkbSjiaSktJrSUXvXj6nzPP3x4vRx35G1/Qp/7sP3LxQ2v6FP8A3YfuXzm1PusONquFGpOO+MJNetJtHOYb7Q1KUaU8ROFWFTDSrtU4WnTypOz7TTTvZbtTqJxTTTSaas09zRWw+Aw9KMlSo0qcZaSUYRSfrtvK0p09uZpwpqhU6Sbl2ZWjaMct5Xla67a3ePIxS+01NK/RVLNNw9G80qipvjprJbzPjaGCw9KPSUaMaaneEVST7b3ZYpay9RkwdPC1ozqQoxWeSz56WSUpJ3WZSSbfECrH7SQzRg6U1OUpQUey7uE3GpbX8qWb1GKX2izql0cHBzlRl2rPNTqNpPR6PsvQ3McPSi7qEE05S0SunL0n63fU12Lr4PCSUZUVHPNSvCg2nO+jvGPpX9oGCp9pouNN06MpOoqDSbirKtJxXtWV+9Ev7RKn0meEpuHSylZRWWFOSi+Or7S9fgXqWBwsqbaw9JQqJOUXSis2t1mTXNvfxMs9n0JZVKjSeWWaKcIu0uMl4+IFbC7ajUr9Eqc1eVSMZPLZum0paXvxRtDBDD0lJSUIKV5NNJXvL0nfxtrzM2Ze4CQeJVEldvRK/sK2E2nSrRnKDklTdpKUZRlF2vqmk9zTAuAxYbERq04VIO8JxUovddNXRM6qj8lqwMhjqVVFPjZXst/+aHmWZ67lyW9+3cjFU1j/AE0u1ZX4P+74geqabjlvlaWtrX9f7mKMrwikktd+trbrri954xuOo0lmqztLhF6y5+iv3+JqY7bdeDUP6aT117S158EXKmxv3O00m1fd7Hu9WpnNZgcbGvB07JT+D45o89dS7Sq7lJ62/wCNfbcis5Q2x+FH/ch+5eKO2Pwo/wC5D9yX6Z6+l4kgkrQAAAAAAAAAAAAAAAAAAAAAAAAUtrbPWJpKm2kukhJ3V01GSk1bxtYugDm/5UWnah2fw+x+H/XdVZddNHl0/wCC5X2ZXdZYinWpxr5HTlmptwlDM5RVs101fffU3AA0VTYM5141p1YuSdNylktNOF7qDv2YyvqvXzKtP7JKNLLCqoSVOlFThCzzwzKU/XKM3E6cAaLE7DqTqNRqwhQVB0YQUHmppxteMr2vdR4blbmWti7K6qqv4a6SSllpwyRjaEY6K7/Tf2mzAEHM7a2I4XqUF2PzQS1j4x8PDgdOQa56vN2M9czqZXzudODWvvvr7GU5xkna1uTfH2HX7Y2ErutQjrvlBfvH5f4+cn21ZLTm/wC3E9fPU7mx5OubxcrXxjZJ8ba3M1Ok5rRWXj8jPRoxhpLV8JP/ADRmyweya1dqUI5Y8Zy0TXgt7/zUZJNqe7fTWwoxpu71X6nw/wA5m42XgsRKcalFZLfnlpFrirb5L/Lm8wOw6NK0pLpJrjLcvUt39zZnLr5v1zHbn4v3VDa3oU/92H7l8obX9Cn/ALsP3L55nafdYcZQ6WlUp3tnhKN+V1a5o6f2Vgmk3TdPOp9H0aytqg6T03XbeY6MFaaN7ErdFQj08ekw+R0p5G90Mks6b1vrutY84/YVXExj01anKajUj+E8sc9rSgnLSato78Wb4Ac/L7LwlKcpSV5yqOUsvbalFKKcv+lpS9ZnjsRrD0KXSXlTrRrTm1+JJSzTfhdt+o3JAHPV/supUZwTp5qlWpOc5U1JuMnJqKu9LZt68eYp/Zl51UlODqZk3LI03FUeicb3vZu0t50RAHI/yvU6SnTbg4RpSSq9GrwfSqSUNbqaj+Z38S7P7MXlVbnFqaqflalPPNS/qSTvLLay/wAR0JIGgwv2dlTrU6rqRnKEYK+RxacU12crSUXfd4sxv7O1ZwarVaNSTqyqPNSbjNyi49qLlrZWy8rHRgCts3C9Bh6NG+bo6cYXta+VJX+B6acN258XfT189TOQBXcVF/q/6Vw13peviV9o0a1Sk5UKipz3rd2tLavg/FFrK4eillv5f+Dy0k73zX1t7tUvYB84rqeeWfN0ifaz3vfxvqycIpOSyJuafu191jt9q7JhikqjtGceN7XXGMn/AJY1+E2VOStGHRZZNXkrceX5v28Tt/kmOH+O6rQnJ2zvJJa9l6+tM3+zq85RanC13pJ6Kd1rZb76X5O+8UMBShvvKotU3ZtcLxW5f5cuZJSVpaLknq9/Hhw3HKusiYScWot3vu/vpy3FXbH4Uf8Ach+5djFLciltj8KP+5D9zN+jr6XiSCStAAAAAAAAAAAAAAAAAAAAAAAAAINdQ2tGTqZlGKg7WzXnfNlSlC10291r3A2QKsMfSavm3LVNNNa5dVzuRHaNJtJOTbbWkJPc7N7t19L7gLYK1LHU5u0W3ut2ZWafFaarx3CeMjFyTT7Pg9ezm99r+4LJqyCtHGxd9JLVL0Xd9nN+x7jiYO9m3a25PjZ/3QMrMCvLFJb1pd6+ppfu7EPGR03u7tud0721QPGrBptqbCVWeek1CTfaT9F+Pr/c2VHFxklvTdtGnx/9MLGRcra8LOztru9Reerzdidcb6sU8DsKjSs5f1J85bl6l/7ZszFLERTab3b3Z2XhfmeXjILe3x4O6ta99NN694vVvuk5z6iwQYetR08XbW6trb92kRLFxTsrt3S0T0vLLv8AeRcrzjsO6kYpNK04y18CyYXioWTve6TVk23e9v2ZCxkGrpt7raO7ur6KwTxv2sAwSxUMuZO/Lx7Ob9iFi48dPY3xtqFyrAMCxKvbXfZWTfhd8tbr2ELFwfF8LaPW+63PcDKsEGKGJg7We9pLfxV/2PVWtGCvLd6mwZXskrVcZGKb1dr3snw5cwsZDW91Zvg9bO2nwB41ZBXWMg+L9qfO1vXfQjrkb2V+GrTS1llt67gyrIMdKqp6q9vU1f1GQIAACDFKOS7itG7ta+1rm/AzEAV5K2t80uS487K+m/ezI6bbv6Pq3vfo3y1ue4wSvZJX1duJ6A8xiluJJAArY7DurBRTStKL18GWQCzUEgAAQSAAAAAAAAAAAAAAAAAAAAAAYusQ5/BlGeDpSlmlUqSdrRu/Q7SlppzjHffcDXPbFNV6lFpp0tZt7oxyqWb3yStvA2DwdH9c7/md9Z65u1pz5W5GSNCknFxnOLjfd+ZOWZp6brmt/jFD9Ulo3Z06l1Z2s1lundpJPV3Vt5ip7dpO+ZTjbcsk3J9qcfRUbr8OT/ewG2wmFo0dKbcVpZJLRL8u69vWK0MzbU42bvrGX6cvPkUqO0aVSp0cJNye7sTyvRN2la17NaX4lbD7cpTUpWkoxlkbScm569hRim27K+79nYsuNl0Mrpqslre+R/py8+RMaTTTVSKsrLsPRe8189t4dJtSlK1vRpzd7wzqzS/Tq+XGxMdr0uypNxcnZWjNpXaSu0rLWSWpMa862DpvLbpIblbsS4O6e/meY0ZW1qxve98kt978yvg9oUq7fRybyqLd4yjpK+Vq6V08r1RSe36ak4ZJ51dW09JVOjy38fS9SGHnW36J2VqkVZJJqErq3t8TyqLVv6sbaaZJWdndX15lD+OYW2bpVa9r5Zcr33ejbjuPVDatOpTqzim3Sz5orV9lyVr7rvLe19zV94w86vunJ3/qxs96yS1fPfv0RHQvW9SLbvduEru9vH/pRU2bj1iIOai42ll3pp6J3TXrLgw86lwfa/qQ7W/sS9emvieeielqsUll0yS1yu6vqSBiedRTouLX9WLta14S0tey3+LCpNJWqxTSSTUJXVlbn4kgYvnXnoOHSRtyySt6OW+/kelTev8AUhr/ANEud+ZBIxPOpUZJpqrFWVnaEtVv119fvPMKTTT6SLta14S0SvZb/EkDDzpGm01JVIXSsuxL6t+/3itCU/Sqw3NaU5bnv4gDF86Tptq3SQ/N+SXHfxDpt76kOL9CXFpvjzQAxPOonSzb6kOP5JcXm58x0L0/qQ0t+R62eZceZIGL51mwssitKopLh2WreBSxn2nw1GpOnJVW4WzONOTirq6u0ZjitqY+pHadbDZrUsR0cJrTRuKUZXfJ29ZU3b7dQ/tlhElJqvZ7n0MrO2+zLuz9vUMRKUYdJGUUm1OEo6Pc9fUcFSoYmpVlgqtSChhU6k0mrJaZsr4vXjuubL7I7Uq4vE4mrVd3kgor9MbytHxtfeMsL4/p3XWIc/gx1iHP4MoAMr/WIc/gx1iHP4MogC91iHP4MdYhz+DKIAvdYhz+DHWIc/gyiAL3WIc/gx1iHP4MogC91iHP4MdYhz+DKIAvdYhz+DHWIc/gyiAL3WIc/gx1iHP4MogC91iHP4MdYhz+DKIAvdYhz+DHWIc/gyiAL3WIc/gx1iHP4MogC91iHP4MdYhz+DKIAvdYhz+DHWIc/gyiYsTUcKc5pZnGLdr2vbxA2fWIc/gx1iHP4M1VKrKU5RajaKWqb3vg/G1n7UZgPfRvkVKuyqU5SlKndybbd3reOR313ZUlbdouJtABqlsikouPRtpqzblNyet75m73ulre+iFPY9KLTVN3XFyk3+Z8X/8Akn7zagDT0Njxp1uljmVlZQ/KtEr+u0V/e+h6lsai/wD62vGMpRe9u90731lrybW42wA1MtjUXHL0Vle/ZlKOuVQ3p3tlSVjItmU+75cXwakuPNI2QA02A2LGg3JZm9LatJJKSSSXDtPTd4KxmeyqTnndJZs/SX19LLlv7jZgDUx2LRSilTaUXeNpz04WWvo6LTce4bKpRVRKnZVE1NXdpXbbur7+09fkjZgDX4XARopqnFq7u25Sk27Wu3JtvRJewz9G+RZAFbo3yHRvkWQBW6N8h0b5FkAVujfIdG+RZIAr9G+Q6N8iwSBW6N8h0b5FkAVujfIdG+RZAFbo3yHRvkWQBW6N8jh/tL9mcZiMZUq0qSlCSjZucVuik9Gz6CAPn+K+zuLngqdNUJdYbSqyc6eWUIX6NXvwTXu8EXvsdsLE4WdZ16eVTUUrSi72bvufidkQBX6N8h0b5FgAV+jfIdG+RZIAr9G+Q6N8iwAK/RvkOjfIsACv0b5Do3yLAAr9G+Q6N8iwAK/RvkOjfIsACv0b5Do3yLAAr9G+Q6N8iwAK/RvkOjfIsEgVujfIdG+RYAFfo3yHRvkWABX6N8iJUW0043TVmuZZAFWNG17Rtd3fj/lj10b5FgkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAgkgkAAAAAAAAAAAAAAgkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADD1ql3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y61S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgD7l1ul3tPzx+Y63S72n54/M+GgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAD//2Q==", + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Convolutional Autoencoders\n", + "\n", + "video = YouTubeVideo(id=\"mzHY6rW_4Eo\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ozE6CZkXv6jM" + }, + "source": [ + "The `nn.Linear` layer by default has a \"bias\" term, which is a learnable offset parameter separate for each output unit. Just like the PCA encoder \"centered\" the data by subtracting off the average image (`mu`) before encoding and added it back in during decoding, a bias term in the decoder can effectively account for the first moment of the data (AKA the average of all images in the training set). Convolution layers do have bias parameters, but the bias is applied per filter rather than per pixel location. If we're generating RGB images, then `Conv2d` will learn only 3 biases: one for each of R, G, and B.\n", + "\n", + "For some conceptual continuity with both PCA and the `nn.Linear` layers above, the next block defines a custom layer for adding a learnable per-pixel offset. This custom layer will be used twice: as the first stage of the encoder and as the final stage of the decoder. Ideally, this means that the rest of the neural net can focus on fitting more interesting fine-grained structure." + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "id": "raWUBjnUwAs6" + }, + "outputs": [], + "source": [ + "class BiasLayer(nn.Module):\n", + " def __init__(self, shape):\n", + " super(BiasLayer, self).__init__()\n", + " init_bias = torch.zeros(shape)\n", + " self.bias = nn.Parameter(init_bias, requires_grad=True)\n", + " \n", + " def forward(self, x):\n", + " return x + self.bias" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "KwhsR5WWxfdN" + }, + "source": [ + "With that out of the way, we will next define a **nonlinear** and **convolutional** autoencoder. Here's a quick tour of the architecture:\n", + "\n", + "1. The **encoder** once again maps from images to $\\mathbf{h}\\in\\mathbb{R}^K$. This will use a `BiasLayer` followed by two convolutional layers (`nn.Conv2D`), followed by flattening and linearly projecting down to $K$ dimensions. The convolutional layers will have `ReLU` nonlinearities on their outputs. \n", + "1. The **decoder** inverts this process, taking in vectors of length $K$ and outputting images. Roughly speaking, its architecture is a \"mirror image\" of the encoder: the first decoder layer is linear, followed by two **deconvolution** layers (`nn.ConvTranspose2d`). The `ConvTranspose2d` layers will have `ReLU` nonlinearities on their _inputs_. This \"mirror image\" between the encoder and decoder is a useful and near-ubiquitous convention. The idea is that the decoder can then learn to approximately invert the encoder, but it is not a strict requirement (and it does not guarantee the decoder will be an exact inverse of the encoder!).\n", + "\n", + "Below is a schematic of the architecture for MNIST. Notice that the width and height dimensions of the image planes reduce after each `nn.Conv2d` and increase after each `nn.ConvTranspose2d`. With CIFAR10, the architecture is the same but the exact sizes will differ a bit.\n", + "\n", + "![image](https://user-images.githubusercontent.com/693511/225031474-1a2df523-4ca7-4154-8921-e5ee3516f98e.png)\n", + "\n", + "We will not go into detail about `ConvTranspose2d` here. For now, just know that it acts a bit like, but not exactly, an inverse to `Conv2d`. The following code demonstrates this change in sizes:" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" }, + "id": "_j3LZPFJ2yh_", + "outputId": "1af0bba9-e343-4ff1-865e-f95ae668d6f4" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "Kl3x376LldRq" - }, - "source": [ - "### Exercise 1\n", - "### Fill in the missing parts of the `LinearAutoEncoder` class and training loop\n", - "\n", - "1. The `LinearAutoEncoder` as two stages: an `encoder` which linearly maps from inputs to a hidden layer of size `K` (with no nonlinearity), and a `decoder` which maps back from `K` up to the number of pixels in each image (`my_dataset_dim`).\n", - "2. The training loop will minimize MSE loss, as written above." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Size of image is torch.Size([1, 1, 28, 28])\n", + "Size of Conv2D(image) torch.Size([1, 1, 24, 24])\n", + "Size of ConvTranspose2D(image) torch.Size([1, 1, 32, 32])\n", + "Size of ConvTranspose2D(Conv2D(image)) torch.Size([1, 1, 28, 28])\n" + ] + } + ], + "source": [ + "dummy_image = torch.zeros(my_dataset_size).unsqueeze(0)\n", + "channels = my_dataset_size[0]\n", + "dummy_conv = nn.Conv2d(in_channels=channels, out_channels=channels, kernel_size=5)\n", + "dummy_conv_transpose = nn.ConvTranspose2d(in_channels=channels, out_channels=channels, kernel_size=5)\n", + "\n", + "print(f'Size of image is {dummy_image.size()}')\n", + "print(f'Size of Conv2D(image) {dummy_conv(dummy_image).size()}')\n", + "print(f'Size of ConvTranspose2D(image) {dummy_conv_transpose(dummy_image).size()}')\n", + "print(f'Size of ConvTranspose2D(Conv2D(image)) {dummy_conv_transpose(dummy_conv(dummy_image)).size()}')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "VfY8DpGx28pt" + }, + "source": [ + "### Exercise 2\n", + "### Fill in code for the `ConvAutoEncoder` module\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "id": "mjH_LETh7hgn" + }, + "outputs": [], + "source": [ + "class ConvAutoEncoder(nn.Module):\n", + " def __init__(self, K, num_filters=32, filter_size=5):\n", + " super(ConvAutoEncoder, self).__init__()\n", + "\n", + " # With padding=0, the number of pixels cut off from each image dimension\n", + " # is filter_size // 2. Double it to get the amount of pixels lost in\n", + " # width and height per Conv2D layer, or added back in per\n", + " # ConvTranspose2D layer.\n", + " filter_reduction = 2 * (filter_size // 2)\n", + "\n", + " # After passing input through two Conv2d layers, the shape will be\n", + " # 'shape_after_conv'. This is also the shape that will go into the first\n", + " # deconvolution layer in the decoder\n", + " self.shape_after_conv = (\n", + " num_filters,\n", + " my_dataset_size[1] - 2 * filter_reduction,\n", + " my_dataset_size[2] - 2 * filter_reduction,\n", + " )\n", + " flat_size_after_conv = (\n", + " self.shape_after_conv[0]\n", + " * self.shape_after_conv[1]\n", + " * self.shape_after_conv[2]\n", + " )\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your class\n", + " raise NotImplementedError(\"Please complete the ConvAutoEncoder class!\")\n", + " ####################################################################\n", + " # Your code here\n", + " ... # Create encoder layers (BiasLayer, Conv2d, Conv2d, Flatten, Linear)\n", + " ... # Create decoder layers (Linear, Unflatten(-1, self.shape_after_conv), ConvTranspose2d, ConvTranspose2d, BiasLayer)\n", + "\n", + " def encode(self, x):\n", + " ... # Your code here: encode batch of images (don't forget ReLUs!)\n", + " return h\n", + "\n", + " def decode(self, h):\n", + " ... # Your code here: decode batch of h vectors (don't forget ReLUs!)\n", + " return x_prime\n", + "\n", + " def forward(self, x):\n", + " return self.decode(self.encode(x))\n", + "\n", + "\n", + "# Uncomment to test your solution\n", + "# conv_ae = ConvAutoEncoder(K=K)\n", + "# assert conv_ae.encode(my_dataset[0][0].unsqueeze(0)).numel() == K, \\\n", + "# \"Encoder output size should be K!\"\n", + "# conv_losses = train_autoencoder(conv_ae, my_dataset)\n", + "# plt.figure()\n", + "# plt.plot(lin_losses)\n", + "# plt.plot(conv_losses)\n", + "# plt.legend(['Lin AE', 'Conv AE'])\n", + "# plt.xlabel('Training batch')\n", + "# plt.ylabel('MSE Loss')\n", + "# plt.ylim([0,2*max(torch.as_tensor(conv_losses).median(), torch.as_tensor(lin_losses).median())])\n", + "# plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "n48WL4b8yxUm" + }, + "source": [ + "You should see that the `ConvAutoEncoder` achieved lower MSE loss than the linear one. If not, you may need to retrain it (or run another few training epochs from where it left off). We make fewer guarantees on this working with CIFAR10, but it should definitely work with MNIST.\n", + "\n", + "Now let's visually compare the reconstructed images from the linear and nonlinear autoencoders. Keep in mind that both have the same dimensionality for $\\mathbf{h}$!" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 318 }, + "id": "bmC-u5zEbpmF", + "outputId": "c641ccd4-836d-4dbb-eda5-7babc7d77cf1" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 16, - "metadata": { - "id": "ejGv1nxRmHCp" - }, - "outputs": [], - "source": [ - "class LinearAutoEncoder(nn.Module):\n", - " def __init__(self, K):\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your class\n", - " raise NotImplementedError(\"Please complete the LinearAutoEncoder class!\")\n", - " #################################################################### \n", - " super(LinearAutoEncoder, self).__init__()\n", - " self.enc_lin = ... # your code here\n", - " self.dec_lin = ... # your code here\n", - " \n", - " def encode(self, x):\n", - " h = ... # your code here\n", - " return h\n", - " \n", - " def decode(self, h):\n", - " x_prime = ... # your code here\n", - " return x_prime\n", - "\n", - " def forward(self, x):\n", - " flat_x = x.view(x.size()[0], -1)\n", - " h = self.encode(flat_x)\n", - " return self.decode(h).view(x.size())\n", - "\n", - "def train_autoencoder(autoencoder, dataset, epochs=20, batch_size=250):\n", - " autoencoder.to(DEVICE)\n", - " optim = torch.optim.Adam(autoencoder.parameters(), lr=1e-3, weight_decay=1e-5)\n", - " loss_fn = nn.MSELoss()\n", - " loader = DataLoader(dataset, batch_size=batch_size, shuffle=True,\n", - " pin_memory=True, num_workers=2)\n", - " mse_loss = torch.zeros(epochs*len(dataset)//batch_size, device=DEVICE)\n", - " i = 0\n", - " for epoch in trange(epochs, desc='Epoch'):\n", - " for im_batch, _ in loader:\n", - " im_batch = im_batch.to(DEVICE)\n", - " optim.zero_grad()\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your function\n", - " raise NotImplementedError(\"Please complete the train_autoencoder function!\")\n", - " #################################################################### \n", - " loss = ... # your code here\n", - " loss.backward()\n", - " optim.step()\n", - "\n", - " mse_loss[i] = loss.detach()\n", - " i += 1\n", - " # After training completes, make sure the model is on CPU so we can easily\n", - " # do more visualizations and demos.\n", - " autoencoder.to('cpu')\n", - " return mse_loss.cpu()\n", - "\n", - "# Uncomment to test your code\n", - "# lin_ae = LinearAutoEncoder(K)\n", - "# lin_losses = train_autoencoder(lin_ae, my_dataset)\n", - "\n", - "# plt.figure()\n", - "# plt.plot(lin_losses)\n", - "# plt.ylim([0, 2*torch.as_tensor(lin_losses).median()])\n", - "# plt.xlabel('Training batch')\n", - "# plt.ylabel('MSE Loss')\n", - "# plt.show()" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 409, + "width": 974 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "n_plot = 7\n", + "plt.figure(figsize=(10,4.5))\n", + "for i in range(n_plot):\n", + " idx = torch.randint(len(my_dataset), size=())\n", + " image, _ = my_dataset[idx]\n", + " with torch.no_grad():\n", + " # Get reconstructed image from linear autoencoder\n", + " lin_recon = lin_ae(image.unsqueeze(0))[0]\n", + " \n", + " # Get reconstruction from deep (nonlinear) autoencoder\n", + " nonlin_recon = conv_ae(image.unsqueeze(0))[0]\n", + " \n", + " plt.subplot(3,n_plot,i+1)\n", + " plot_torch_image(image)\n", + " if i == 0:\n", + " plt.ylabel('Original\\nImage')\n", + " \n", + " plt.subplot(3,n_plot,i+1+n_plot)\n", + " plot_torch_image(lin_recon)\n", + " if i == 0:\n", + " plt.ylabel(f'Lin AE\\n(K={K})')\n", + " \n", + " plt.subplot(3,n_plot,i+1+2*n_plot)\n", + " plot_torch_image(nonlin_recon)\n", + " if i == 0:\n", + " plt.ylabel(f'NonLin AE\\n(K={K})')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "bSpvDpLXrLD5" + }, + "source": [ + "## Inspecting the hidden representations\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "k7OGAEnI0J8o", + "outputId": "965f5b27-a311-4fec-b20d-f0e04ad878ca" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "UxSA-0UgPNc1" - }, - "source": [ - "One way to think about AutoEncoders is that they automatically discover good dimensionality-reduction of the data. Another easy and common technique for dimensionality reduction is to project data onto the top $K$ **principal components** (Principal Component Analysis or PCA). For comparison, let's also do PCA." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=HcvTrvCntBY\n" + ] }, { - "cell_type": "code", - "execution_count": 18, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 17, - "referenced_widgets": [ - "80e074ada4d642d58c690fdd14020d13", - "69b3eb3b86c0451984fc07a02958dd45", - "d825e4a7719649f7b5a8f5bb2e8ccef4", - "a7501605ea394d47884111fdb2de00ea", - "22c8ca666f614b7dbb9ac0fa3f4e095a", - "76952d837cf7418795fb34158c80bd27", - "311f5429f3b146edbc9b8f6f528681d1", - "f8a4466e613344cd9a0f4f654726d3e7", - "441952e7c48e4366a3044537aadb330b", - "6067d9f4878e4a7597d7980fb4f57457", - "a30b5754bc1c49e7a0d6c0cda84a23e9" - ] - }, - "id": "1At-bwcmPzwx", - "outputId": "a8cc9263-70e9-4d2a-ee25-40602b6418e9" - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "55cec385711c4b96a2fc1224e9326bb6", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Computing pixel mean and covariance...: 0%| | 0/1875 [00:00\n", + " " ], - "source": [ - "# PCA requires finding the top K eigenvectors of the data covariance. Start by\n", - "# finding the mean and covariance of the pixels in our dataset\n", - "loader = DataLoader(my_dataset, batch_size=32, pin_memory=True)\n", - "mu, cov = image_moments((im for im, _ in loader), n_batches=len(my_dataset)//32)\n", - "pca_encode, pca_decode = pca_encoder_decoder(mu, cov, K)" + "text/plain": [ + "" ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Latent Space\n", + "\n", + "video = YouTubeVideo(id=\"HcvTrvCntBY\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "TaAkIZpZ9nAG" + }, + "source": [ + "Let's start by plotting points in the hidden space ($\\mathbf{h}$), colored by class of the image (which, of course, the autoencoder didn't know about during training!)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 433 }, + "id": "eSDlEhzC95rc", + "outputId": "ed185eb9-0009-4248-d453-2331044ef06f" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "M7DCDLnIg-Mk" - }, - "source": [ - "Let's visualize some of the reconstructions ($\\mathbf{x'}$) side-by-side with the input images ($\\mathbf{x}$)." - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n" + ] }, { - "cell_type": "code", - "execution_count": 19, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 315 - }, - "id": "36iI09hNhN2n", - "outputId": "f0014660-66b3-46ea-d5bd-6c6b3f53d92e" - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 409, - "width": 974 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "n_plot = 7\n", - "plt.figure(figsize=(10,4.5))\n", - "for i in range(n_plot):\n", - " idx = torch.randint(len(my_dataset), size=())\n", - " image, _ = my_dataset[idx]\n", - " # Get reconstructed image from autoencoder\n", - " with torch.no_grad():\n", - " reconstruction = lin_ae(image.unsqueeze(0)).reshape(image.size())\n", - " \n", - " # Get reconstruction from PCA dimensionality reduction\n", - " h_pca = pca_encode(image)\n", - " recon_pca = pca_decode(h_pca).reshape(image.size())\n", - " \n", - " plt.subplot(3,n_plot,i+1)\n", - " plot_torch_image(image)\n", - " if i == 0:\n", - " plt.ylabel('Original\\nImage')\n", - " \n", - " plt.subplot(3,n_plot,i+1+n_plot)\n", - " plot_torch_image(reconstruction)\n", - " if i == 0:\n", - " plt.ylabel(f'Lin AE\\n(K={K})')\n", - " \n", - " plt.subplot(3,n_plot,i+1+2*n_plot)\n", - " plot_torch_image(recon_pca)\n", - " if i == 0:\n", - " plt.ylabel(f'PCA\\n(K={K})')\n", - "plt.show()" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 577, + "width": 638 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "h_vectors = torch.zeros(len(my_valset), K, device=DEVICE)\n", + "labels = torch.zeros(len(my_valset), dtype=torch.int32)\n", + "loader = DataLoader(my_valset, batch_size=200, pin_memory=True)\n", + "conv_ae.to(DEVICE)\n", + "i = 0\n", + "for im, la in loader:\n", + " b = im.size()[0]\n", + " h_vectors[i : i + b, :] = conv_ae.encode(im.to(DEVICE))\n", + " labels[i : i + b] = la\n", + " i += b\n", + "conv_ae.to(\"cpu\")\n", + "h_vectors = h_vectors.detach().cpu()\n", + "_, _, h_pcs = torch.pca_lowrank(h_vectors, q=2)\n", + "h_xy = h_vectors @ h_pcs\n", + "\n", + "with plt.xkcd():\n", + " plt.figure(figsize=(7, 6))\n", + " plt.scatter(h_xy[:, 0], h_xy[:, 1], c=labels, cmap=\"hsv\")\n", + " plt.title(\"2D projection of h, colored by class\")\n", + " plt.colorbar()\n", + " plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2vhNusJZ01KR" + }, + "source": [ + "To explore the hidden representations, $\\mathbf{h}$, we're going to pick two random images from the dataset and interpolate them 3 different ways. Let's introduce some notation for this: we'll use a variable $t \\in [0,1]$ to gradually transition from image $\\mathbf{x}_1$ at $t=0$ to image $\\mathbf{x}_2$ at $t=1$. Using $\\mathbf{x}(t)$ to denote the interpolated output, the three methods will be\n", + "\n", + "1. interpolate the raw pixels, so $$\\mathbf{x}(t) = (1-t) \\cdot \\mathbf{x}_1 + t \\cdot \\mathbf{x}_2$$\n", + "2. interpolate their encodings from the **linear** AE, so $$\\mathbf{x}(t) = \\text{linear_decoder}((1-t) \\cdot \\text{linear_encoder}(\\mathbf{x}_1) + t \\cdot \\text{linear_encoder}(\\mathbf{x}_2))$$\n", + "3. interpolate their encodings from the **nonlinear** AE, so $$\\mathbf{x}(t) = \\text{conv_decoder}((1-t) \\cdot \\text{conv_encoder}(\\mathbf{x}_1) + t \\cdot \\text{conv_encoder}(\\mathbf{x}_2))$$\n", + "\n", + "Note: This demo will likely look better using MNIST than using CIFAR, but you can answer the question below for either one of them. " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "h-74e-ruJZRc" + }, + "source": [ + "## Quiz Question 2\n", + "\n", + "What do you notice about the \"interpolated\" images, especially around $t \\approx 1/2$? How many distinct classes do you see in the bottom row?\n", + "Re-run the above cell a few times to look at multiple examples." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "id": "a8ZsxDhYJRdE" + }, + "outputs": [], + "source": [ + "interp_observations = \"\" #@param{type:'string'}" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 316 }, + "id": "S_NGi5P11Dj5", + "outputId": "3ad05528-0ea8-4f6a-f395-d7dc10ee7e87" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "9m5arq_hqdLJ" - }, - "source": [ - "## Quiz Question 1\n", - "\n", - "Compare the PCA-based reconstructions to those from the linear autoencoder. Is one better than the other? Are they equally good? Equally bad?" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 406, + "width": 1377 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "idx1 = torch.randint(len(my_dataset), size=())\n", + "idx2 = torch.randint(len(my_dataset), size=())\n", + "x1, _ = my_dataset[idx1]\n", + "x2, _ = my_dataset[idx2]\n", + "n_interp = 11\n", + "\n", + "with torch.no_grad():\n", + " h1_lin = lin_ae.encode(x1.reshape(1, -1))\n", + " h2_lin = lin_ae.encode(x2.reshape(1, -1))\n", + " h1_conv = conv_ae.encode(x1.unsqueeze(0))\n", + " h2_conv = conv_ae.encode(x2.unsqueeze(0))\n", + "\n", + "plt.figure(figsize=(14, 4.5))\n", + "for i in range(n_interp):\n", + " t = i / (n_interp - 1)\n", + " pixel_interp = (1 - t) * x1 + t * x2\n", + " plt.subplot(3, n_interp, i + 1)\n", + " plot_torch_image(pixel_interp)\n", + " if i == 0:\n", + " plt.ylabel(\"Raw\\nPixels\")\n", + " plt.title(f\"t={i}/{n_interp-1}\")\n", + "\n", + " with torch.no_grad():\n", + " lin_ae_interp = lin_ae.decode((1 - t) * h1_lin + t * h2_lin)\n", + " plt.subplot(3, n_interp, i + 1 + n_interp)\n", + " plot_torch_image(lin_ae_interp.reshape(my_dataset_size))\n", + " if i == 0:\n", + " plt.ylabel(\"Lin AE\")\n", + "\n", + " with torch.no_grad():\n", + " conv_ae_interp = conv_ae.decode((1 - t) * h1_conv + t * h2_conv)[0]\n", + " plt.subplot(3, n_interp, i + 1 + 2 * n_interp)\n", + " plot_torch_image(conv_ae_interp)\n", + " if i == 0:\n", + " plt.ylabel(\"NonLin AE\")\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "RP_0Hcyflj3w" + }, + "source": [ + "---\n", + "# Section 3: Generative models and density networks\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "rjpZAX0mrUg_", + "outputId": "dc3f7808-89ed-4fd1-d7a8-a4a945add2c1" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "cellView": "form", - "id": "9iqm4O6VnK6i" - }, - "outputs": [], - "source": [ - "linear_ae_vs_pca = \"\" #@param{type:'string'}" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=h96JaT5Jyi4\n" + ] }, { - "cell_type": "markdown", - "metadata": { - "id": "Z80iE-ssiwsW" - }, - "source": [ - "If you're interested, Appendix C includes a plot of explained-variance as a function of $K$, as well as some discussion of why fraction of explained variance using PCA is a rough and not very good guide to choosing $K$ for a given dataset." + "data": { + "image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEABALDBoYFhsaGRoeHRsfISklIyIiHzEnLSYtLikyMzcyNy01SFBONThLOTIuRWFFS1NWW11bOEJlbWVYbFBZW1cBERISGRYZLxsbLVc/OD1XV1dXV1dXV1ddV1dXXVdXV1dXV1dXV1dXV11XV1dXV1ddV1deV1ddXV1XV1dXV1dXV//AABEIAWgB4AMBIgACEQEDEQH/xAAbAAEAAgMBAQAAAAAAAAAAAAAABAUBAgMGB//EAEMQAAIBAgMFBQQJAwMDAwUAAAECAAMRBBIhBRMxQVEUIlNhkgZxgaEVFyMyUpGx0dIWQnIzYsGCk7JD4fEHJWNzov/EABcBAQEBAQAAAAAAAAAAAAAAAAABAgP/xAAgEQEBAQACAgMBAQEAAAAAAAAAARECIRITAyJBMbEE/9oADAMBAAIRAxEAPwD5/ERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9h9XGN8XD+t/4x9XGN8XD+t/4wPHxPYfVxjfFw/rf+MfVxjfFw/rf+MDx8T2H1cY3xcP63/jH1cY3xcP63/jA8fE9c/wD9OsYoJNXD2Av99/4yv/pLEfjpepv2gxQxL/8ApHEfjo+pv4x/SOI/HS9TftJq5VBEv/6RxH46Pqb+Mf0jiPx0fU38Y0xQRL/+kcR+Ol6m/aP6RxH46Xqb9o0xQRL/APpHEfjpepv2j+kcR+Ol6m/aXUxQRL/+kcR+Ol6m/aP6RxH46Xqb9o0UES//AKRxH46Xqb9pj+ksR+Ol6m/aBQxL7+k8R+Ol6m/aY/pTEfjpepv2gUUS8/pWv+Ol6m/aan2Yr/jpfm37QPs0RMQMxOQxCFygdS4FyuYXA90zWrJTXM7KijmxAH5mB0icGxlIMFNVAx4AuLn3Cd4CJyaugcUywDsCQt9SBxNviJ0gZiYnOviUp2zuq5iFFza5PADqYHWJiIGYmIgZiYiBmJxp4lGdkV1ZktmANyt+F+nCdYGYmJzpV0ctlYNlYq1jwI5Hz1gdYnIYhN5u867wDMVvqB1tOkDMTEQMxMRAzExEDMTE50a6VBmRgwuRcG+oNiPzgdYmIgZiYiBmJiCbC54QMxOWHxCVVD02V1N7MpuDY2OvviviEp5c7quYhVubXJ4AdTA6xMRAzERA5Yr/AE3/AMT+k8kGnrcV/pP/AIn9J5ALM1ri3zTOaahJtkkaM0ZpsKc23cI55ovOuSZyQON4zTsVmi1UPBhLjNrTNF/Kd0KngQZvlg1G16GLHpJOWCsCLlPSalD0kvLMFYRENMznVpkAmTCs0ZYHrpiZmJoee24pTEdqT72HSmxHWmWcOPy1+E09pagrUbqb06bUTccCzutvyU3/AOoS77Kd67lgVZAhXLyBJ4/9RkN9hJ2VcMjlEDBr2uSQwYfoPhM468eU638a48f/AHHBf4V/0SW8gYnZzPWpVt7lakrADJcHNa99fITvQw7hy71M5IsBlyhev56flKxcsjjVxTLjKdKylXpu17d4FSul+ms47L2ma72zICAd5TylXptcWBBOo462kmtgc2IStntkRkC25Na+vwE50dmkVadWo+d6aFFbLlJBt948+HlzhfrjfFYwivToJbM6s5JFwFWw4aXJJHzlRtHGvUotTdV3tHFUVNrhWu6lSONrg8NbecuMZgd5Up1VbJVp3yta4IbiCOY0H5ThV2QrU3Bc53qLVLgD7ykW06DKBaLq8bxmODbSr0qlalURHdaRq0zTBGYA2IKknUG3DjMptgGkaiulVS9NEygghnbLZlJuLXB5SWcAxLuan2rKFDqtsoBvoLnnxuZwq7ESpvjUbv1Ql2QZLFDdWHHvXPH3R2bx/WtTHYimKxalmVQrI6oRe5swKXJJHHTjNTtYigayulWnnUZ6ak5VPEst73Ek08BVCWbEs1Tu2fKBYA3+6ON+cwmzCrPUWoFqO4ZiEspspFst/PXWOz6uQ2mStLKyVDVdgjoCVyqpN7X46WteajaNZQqVKYWo9bd02tZWW2bPlvcWAOl+I46zZ9hqU7rmnV3pqh0AGViLGy9COIm9fZJqIuasxrI4datgLMBb7vDLa4t5x2fVx2cGGPxmcqTko6qLXHf5a6yRiMXUTEpTJQU6iMVYqbh1todehJ+Bm+EwBp1qlZqhdqiorDKAO7e1vzM32hgExCor3GVw4I8uI9xBI+MJbLUPZ20qlenSPcFQ1GVxlPdC3vpf/HX/AHDSRcZjqzYbFEFEanXFO6qdVJQdePe4/wDzLahgEp16tYfeqZbjkLC1x77C/uEjNse9PEUzUP21TeXyjutpw6juiO1l464VVq9vARk3nZj3ipy/6n4b3+cn7JxZr4enVYAMw1A4XBsbeWk0XAMK4rGrdhT3eqix1vfTznXZ2D3FFaWbMFvYkW4m/wDzCcrLFdiNr1AlWoir9nXFHIQcxuwW9wf9wIFuHvnSvj6xNZaKhno2BBUkO2UNYG4y6EC5vIALNVqOtVkql2sj4XOwtoLNppbz58ZYnZbmrvkrNReoq75VAYMQLXF+B5XkaskaNjsQ1d6SLTQiglUZwWILFgVIBF+HWMPtZqqUMi5Xq0t4e6XC2sLWBF9T15SSuzstZqqvYtSWnYi9gpJBvfU3JkZdhZadAU6zJUoKVVwoN1Nrhl58BL2n1aNtHFDsytTRKlV3Rg1yO6rEMLHgbA2+HnGO2lXoU3Z91mporWAJz/iIF7ovIE3kp9mEtQY1SWpMXuQDmJBU36Cx4CcsXsXeHEfbMq11AZQoNiFsCCeVuUdkvHWFq1TtBkDrkFBXC5T/AHMQdb8dBrOH0pWGENcLTGSqy1AFNgi1CpYa8QNZPXZxFdawqnMKYptoO8ASR7tSZnBbOFKk1JjnVmcm4t98kkfMwbx/xpiseae8bRkXIo01LuQLX6ary5zbCV65rMlRL08oK1AuTW9ipBJ995hdkJ2TsrFmXLYtfvE/iv1vN8Fg6lPWrXasQLAlQth7hxPnCdY5YvFVRiUo092A9N2DMCbFSo4Ai473DT3yEu1sRuVrMKWVa26qKA12+1yZlN+71sb++WdXBFsQlbPYojKFtxDEE/oJFOxfsGo702NXe3y63z57e68drLx/WzY6rU7QaOT7BstmBOdgoYi4OnG3OYwu1DiGQUbLeitVi4Jtm0VbAjobm/Lz06HZhD1Wp1Mgrf6gy31tbMvQ29/Ca/RASpTeg5pFKYpEWzBkHAEHmOsdn1Qdj4tkw1GmAM9SpXN7EgBarX00vqQOMztCtVfDpvkyMuLogEaBhvFswFza/SSBsK1JFWs4qU3Z0qWFxnJJFuYNzO1fZbVKao1YlhUWoWKjUqQQLchoNJMuNeXHy1zfaZ7SaF0Rgy5VdT9opAuVa9r8dPLzlqJX4nZhqkh6mZN4rgZdVK20Vr6C46czLCVzufjMRErLlif9N/8AE/pPLKs9TiP9N/8AE/pPOKJmtcWgSbhJuFnQLI05BJnJOwWbBIRxyTliKgpi5k0JK7bwC0L/AO4AfGa45vbPLc6VOMxgJa7acQJBXHWvbUX0nXDYDeHvay8wns9StqPd5TrfmnHqOU/57ym2qfD402B4S52fic+h48pl9kqgP6ympVThqobVgDYi2tpZznySxm/Fy+KyvT7uMkkBYyTg7o+SalJJyTGSERd3NTTkvJNWSQXkRE2ERMQMxMRAzExMwExMzEBMxEBERAREQEREBMTMxAREQETMQMTMRARExAzExMwEREDEzMRAzETEBETMBERAREQOWI/03/xP6TzqT0df7jf4n9J59BM1qN1E6ATVZ0EishZuBAmwEBaUu2MfRU1KdViuVLL3Se84Njp5C3xMu54X2trK2KORr2UBrdQTpLErphdpimLquYn5fGd6PtEwzBu6baDX5SDg1pGkM4PwBP6Sbs6jQbfZiqqyZUuNRx73kf2mbjtx3JjUbXrsSS3d/DcD5Tmu1MlYNu7j7pDG1r6HUSVhnpgjPRu44lbZSeolbth7MugFyzWHnymuP9Y+SddvZbGxJrUA5/EwHuBsPlJ9pC9nqRXBUbixK5vzJP6Sxyy1ycssxlnXLFpBxKzVlnciakQLGVHtHt5Nn0VqMhcs2VVBtrYnU8uEt5Gx+Ao4lN3XprUS97Hr18pocdi7UTGYZK6AqGvoeIINiPlJ05YbDJRprTpqERRYKBYCdoFJikxlKhvDVDtSpoxVV++yMS/wZdPIicDtd+0iuHHYcwonhbMVzby/TNZPiZ6GQfoeh2U4XINyQRl95v8ArAqaG0sQKlFyr1BWpVqopLlFlDJk+9bUKfzYyxXbaGpRXI2WsBu3uveumb7t78OdrXkupgkaotTW6oyC3CzFb/8AiJCpbApIyMr1RkyEDMLXRcovcfh0tw+MCRsnHtiKW8ak1LUgAspvYkcj5TjsrGHshq1mvlNUsx6K7foBJOBwK0AwV3Kk3CsQQtyTYacLnneZw+Ap06JogFkOa4bW+ckkfMwIrbWcUTVOGqKNCAzUx3SCbklrD3HmROVX2hRVzilUZBRSuzDKMqOW1sTckZSbCdRsRcqqa1chGDJmYHLZSthca6MeNz5wuwaQpPSzVCr0FoEki+RS1uXHvHX3QH0yN6ae6fKK25NTu2zlQw0ve2oF7TWntxWyHdVAlW+6c5bVCFLADW4uASL24SR9F07k3bWsKx1/uAA/LQTnh9i0qbKQ1QolzTps10p3BHdHuJAuTYHS0Dps3aBrYZK70zSDIHsSDoVBvccvfrI4239kKrYeqqO1MU75bvvGyg2vpxBsbcZLwOz1oUt0Gd0AsA5ByrawUacAOusj09ioqKm8qsitTZFZgQm7YMoGl7XA430gcK/tHTpOEqIyPZS4LpdMxIGmbvcL92+kziNvin2gGi+ejTaplLJ3lBtfQnLyOvKS6+zVervRUq02IAbI1g4HC/5nUWM4DYFG73aoVdaiFSwtlqG7DQX4873gcsX7R06GUVabK+TOyl0uq3IH93eJsTZbnSSdrYhkWgUa2avTU25qTqJqdjC6tv64cLlLhwGdb3AOltNbEAEdZLxOEWqEDX7jq4sea8LwOeMx26enTVGqVKlyFUgaLa5JJAAFx+crNmbac4ekDTq16u6FSply90EsBe5Fycp0HSWuMwK1SjZnR0vldDYi/Ea3BBsNCOQkRdg01VVSpWTKm7JV7F1BJAbTzOosdTAkYjaaJhlxCgujZCuXi2cgDjb8Qkf6aGq7mpvhU3e6GW98ge972tlIN7+XGS62z6b0Vo2y01yZQulsjAqPd3RONbY9Nmd8zq7VBUDq1irZAmmnDKOBvA4DbmapSppQcszOrglQaZQAkHXXRgdOUnVcWFrUqRBvUDkHkMtr3/ORRsWmAmV6iurM28Dd5i33rkjW+nusLWtJGMwK1WRszo6E5WQgGx0I1voYFf8A1IhQVBRqlNylZiMvdRyeNzqRlJsJnH7UYuq0lcKuIp03q90LqwutjqdDa9p2TYNEUmpAvlagtA97XIua3x7x1m9TY9NqmfPUUbxahQMMrMtrGxGnAcLQIa+1FAioQCQiVHFmUlhT46A3XyzWkiptko9NGw9RWqMQuZkFwANb5uJv93jodNJk7Dp5KlPeVd06uu7z91Q/G2nnpe9uU77Q2YuIUK7uEHFVIAbUHXTy4ixgRk2w5FY9ne1OoUBzoAbcTcnQe/ymje0KbtaiUajqaO/NsvdTnxOp48LztV2KjMzbyquaoKmUMLBxzAIPHzuPdFLYlJUKZnINI0dSL5SSenHXjAi7U2u1itFXslWgj1RlCgvUpkrYm57rDgP7pPw2Fqq6lqxdQKl1IGuZwV5f2i4nKtsSm7Xz1FBZGZVYZXanlykgg691eFuEsoESptbDIxVsRSVgbEGoAQfdIW367qcMqNVAqVSG3IBcgUnbS+nECXE4V8ItR6Tte9Jiy26lSuvwYwKr6epUClJ94WAXOajIHGY6XW4ueZyjhOlX2ipqjNkclEqNUUWumRstjrxJ4dbSXX2arVd6KlWmxADhGsHA4X/PiLGRaGyBUXFGsuVsUxz5SLhFGVRfrYX95MDZtt5SVahUFTeLTyXW5zqSDe9raHnymKG3Q7KDQqrnNRAe6b1Kd8yaHj3W14aSTU2XTarvSWzZ0fjpdAwH/kZo2xaRUKS9hUq1PvW1qhw3w77W+EDjT28rA2pPnFYUSgZCcxXMO8Da1vOTsBjBXp5wpWzMpU2uGVipGnmJFw+xKdNg2eoxDo+pXiiZBoAP7bD4SXhMItFWVL2Z3c3N9XYsfmYHSv8Acb/E/pKBZf1vuN/if0lAJmrHQGbgzmJteFdQ03DThmmwMDoWnjdv7MvVxFQZrgI6gDQgmzX91iZ60tIOJb7an5q6n5H/AIliPLYWmyUkzC11zDzBM6UcjHSm1/dJ+NpBMJTA4oxUHyuR/wACQsPmvcEfGZv9duN2JauCwCqy5dCCLSzwGwUrOterZ0ylRTI0OvG/5yvbQakEsb6T2NBQEULwAFo4s/JesbqoAAGgHCbWmJsJtxa2mLTeLQOZEwROlpqRIJcRKj2j28mz6K1GRnLNlVQba2J1PwlVbxIGxdqJjMMldAVDX0PEEEg/pJ0BEraWDxBAWtX/APTUE0+6c4JzHUcCCunK0qlq1qeCGI39ao5qqmUldR2kLYCw1K6cecD1ESmq+0CItmpstXemluyyDUKHvmJy2ykHjztxkk7WTsbYvK2RULldM3dvcdL3B52gWESobboW4ehVSqGpruzkJIqEhWBBIIuDz0tD7bKhicNW+zF61ih3Wl9e93jbXu30/KBbxKh9ugOwWhUdVqClmBSxZlDLa5BscwF/OaHbY0YpVGVK5akArG9IqCLg6nXS2hvrAuolLU9oUWnSbdktVDFVFSnYqtrtnzZeYsL3198m1NpUxh1xHeKMFKgDvMXsFFjzJIECZE8/tPbNU0zTSjVpVt5SVlvTzBKj2zA3K62K+R/OWmKxm5FJAr1aj91VBFzYXJJNgLCBNiebwvtGKdBN6rPUKu7jMgKqKjKOJGY6EALfh+c36fpGvugCRmCF7roxFwMt81tRra2vvsFvEqtmbaGI3d6NSkKqZ6ZfKQ4Fr/dJsdRobTniNq7itXzksoNFUW4GrBr6mwHC5ueUC5iUze0KCmlTdPkZsrHMncObLb73e692+k2r7cCdobcVTTw+cO4K2uqhrAE3NwekC3iVJ2tdshSpScVKQKnK1xUvbUEi2hB5i00p+0C5c70qiJkqOrHKcwpnvaA6eV4FzEgbM2j2jeg0mpmmwUhmU6lQ3FSRwYSLhdtAtRp5XdqmY5jkXQOV4XFyLXsNbQLmJAx2PelVo00otU3hOoZRlsP9xF5yo7aVnX7KoKTuUSqcuVmF+V8wBsbEgA/EQLSYkDaG0DTO7p03qVCjPZSoyqOZLEcyABK3C7cNOgr1M9Q7uhf7qgGopOYsbWGmpPlA9FErl2oWqimlCoxAQ1DdAKeYXse93iBqct5xXboNmFCru3vun7tqpAJAAvcXANrgQLeJS1PaSiACoLA7vKbqoLOpYKSxFiFGY36jnNk28HCbqhVqM6s2UFBbI4VtSQOJ5HXlAuIkLH4/cmmopvUeoSFVbDUKW4kgDhIa7YIZ13dV6hqhFpdwFfslc969rAHiTx0F9IFxEpDtapTr1S9KpuwtEkXT7LPcG+uutr2vwl3AzERAREQOdf7jf4n9J58GeiZbgg8DpI30bS/CfUZFVAMzeW30dS/CfUY+jqX4T6jGGqkGbgyz+j6XQ+owdnUjyPqMYKatXVR3mA95lDtbadwpok5ka4NuOlrfOetb2ewxNyrE/wD7G/ecm9lsGeNNv+437ys9vnWLxlSqUW5IAsFHXmffeSKdFxbWe6X2RwQJIpNc/wD5H/edR7NYX8L/APdb95LGpceTwtOwuT8TJa45qb3pOQANeh+E9D/TWF/A/wD3G/eb/wBO4X8Detv3iTE522ZFbhvaMcKqfFf2MtMLtGlV0RxfodDNf6dwv4G9bfvMr7P4YcEb1t+8rEnJMibpRAAGunU3P5zbdiGscpqZ33YjdiDG8jY/AUcTT3demKiXvY9eoPKSYhXLDYdKSLTpqERRYKBYCdYiBiQvounuBR72QOH463FTef8AlJ0QK6tsem7M+Z1dqm9Dq1irZAmnkVHA3mu1MCz4CtQplndqbKpdtSSDxJlnECuXY9O+ZmqO+dGLswud2SVGgtYXPAczM4vZFOq7MWqKKgAqKj2WoALaj3aXFjaWEQII2XTu1swzVVq8f7lCgfCyia/RNPMXDOG+01DWtvCCbfFRaWEQKpdhU1AyvVVwzNvAwDEvbNytY2GluUmVsElSjuXzMthqWOa41Bzcb3AN5JiBWrsanqWao7l0YuzXY7tsyjhYAHkBzMkYzBLWykllZDdXQ2Kkix9+nIyVECqXYdNQmSpVRlBXOrgMwLFiG0sdSeWl52XZarVNRXqLchmQP3WYAC553sBz15yfECm2Dsc0KVA1WdqtOkEszAqlwLhQPcNdTJeI2XTqM7EuGcocytYqUvYj8zJ0QKuvsNKgGarWJylS2YEkEg9NNQOFp2fZdNqVekS2WuWL6695Qpt00EnRAhVNmU2qGoc2YmmeOn2ZJX9TI2L2TagFok50R1S7cnIza9bcD1ltECq2DhalGmyMuWmCN2GCBhprfdgLx+PWbfQlP7MZ6mSmwYLm0LBywJ06nlbzvLOIEXGYJapRszoyElWQ2OosRrfQzhS2PTV1YNUKqxdKZfuKxvqB8ToTYcpYxAh4zZ61iGzOjhSuZGscptcG9wRoOU4LsWmqFUeol1RLhheyKVA1FjodbiWcQK2jsanTZDSapTCqilVfRwgsua9+WlxaKGxqVN0YNUK0yWp0y10pkgi4HuJAve19LSyiBW/QlAUyiAp9qawZTZlck6g+4kW6aTvQwCo6vmd2VCt2a9wxBN/ykuIHCthld6bm96ZJW3mCNfgZFq7HpsWYNUR2qbwOrWKtkCaeWUcDeWMQIDbKQioGZzvFRWJOpycDw4yRhaBphgXZ8zswub2BN8o8hO8QEREBERAREQEREBERAREQEREBERAREQEREBERAREQExMzEDzeC24wwimqtQOcPVqLU7pzbu17C/HUWvJv9Q0hXFGxJzKha66Mygju3uRqLkDn751bYVE00pnNlSlUpDva5als3x0E6DZaCpnV6iXKllV7KxUAAke4C9rXtrA4U9ss9Lerh6mTkxZFBsSDxOg04njFLbgqGmKVGo+8pLV0Kiysba3PKSG2XTNKnSBYCmwZSDqCL/nxMYLZdOgVKljlpimMxv3QxI/WBXYzbDvhhWpU6iIXpFGut6itVUaC+lweduPKd22yudAwemRVdHU5SO7SNTU9LWOk6psSmqbsPV3YKlUL3VMrhgB5XA+Gk6Nsmk1QuQSTUNQgnQk0t2dOmWByG1nNLe9mqBSAVzOgupBNzdu7y0PUTTZ+0N/iQyk7p8LTqKp5FnbX32AnRdiIFVN5WKoylAXvkyggAXGuh535dJ1wOy6dAqULErTFMZjfugkj9YEettwLUZBQqMFqijmBWxdlDAanh3gLwm2w2VUo1Gqk1AaYK3XdsFYlibWuRbrceckNsumSx73erLWOv9yhQPhZRNG2NTvmVqiPndw6tYjeG7DzBIGh6CBGxO289FtxTqM+6dj91TTykqb3PEMCLC/AznQ9oqamnSe7NakrtdfvVFUju3ufvAkgaX8jaW2w6OQKhqU7IyFlfVgxucxN73JJudbk9ZsmyKauGR6qaIGCvYPkAAJHWwA0tcCBD2ftggUabqzvUar3iVGi1WWwuRcgchrYSdj8e1KrRprRNTelhcMBay358ZzbYlIhFLVMiPny5tC2cuCR/keVukk4zBLWyEs6sjXVkaxFwQfhYwKvZe13yhaiVHLVMQEcFe8adR7KBfTuiwv0nT6fJXuUGZxWFFlzpoSoa+a9jofzkhti0Sip3sqmqR3rH7XNm1/6zNV2HTAYB6l2ZHzZgCGRQoIsLfdAHSBJxuO3KIxRmLuqBVte7fKQW9oUWqKT02Vrorgsl1Z+AsDduIuR198sauEVxTDFju2Vgb6kr16zk+zVNU1Q9RC1i4R7B8vC4+WlriBFp7eU6tRqIrbwIxKkOaeYkaG4NlYi45TSp7QqqU2ai670Xph3Rcy5bk3J04gWOuo87Y2fsQBPti5YGrlXNdU3jNqAOeU872uZOq7MRlpKGdDSFkdWswFrW8wR1gRqG3adSoiKjWamKmYlRZTfkTc2tY2va4kel7U0nRmWm5sgdQGUlgWC9e6dRobcffJzbJQvTdnqPu9VDPcXylb663sTztNE2JTCbvPVNOwCoalwoDBgB+Q430gcau3CCqDDuahrbkrmUWO7NQG97G6yZj8fuRStTZ2qvkVVIGuVm4k24KZpX2TTcs13VjUFXMrWKsEyXH/Tp8ZptXAvVOFCMw3dbMzAjMBu3W+vE3Igcxt0MUWnQqvUYVDk7oKmmwVgSTa9z1sZvS2yrMv2VQUncolU5crN7r3AJBAJH6idsLsunSZGXNmVXFy1752DMT1JImlLY1JXVgahVWLrTLkorG+oHxNhwHKBA2PtqocPQFWjUNR6AdWun2tsobW+n3gdbaTb6Zaq9BqNN2u1ZHphl4pYfevYj3HnO6eztEJkLVGATdpme+Rbg2X0rxve1puNhoNRUrK2dnzBxe7/AHuXA2gQcVtreJekzrphmsQO7nxORhfrowPLpJFHbDGrTpLSepnat3iVXKKdQKdOY1Hw+M7/AEHQtYBgMtNfvcqVQ1F48TmJuec2+iKYKMrVFZGqMCraneNmYHyJA/KAwG10xDhUVr7vO97fZnMVyt/uuG9JljK7Y+CNJHd1C1a1Q1KgHIngPgAB77nnLGAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiYgInncTtp2anURaiUDRruG7pzhVBDBfmL9ZMO2wGqoKTMaVPOe8qlu6G0BN7cr8LgiBbRKmntlyKK9mqGpVpmplDLoAVB1vb+7SRBtarv0yLUrLlxF0GRTenVC35cNQPfA9FMSsXblNqbVFViirSYHhcVbW/Wcl2uz5r03pquIFINdWzd7KdOUC4mZV09tKxQ7qoKVQladU2ysQCeF7gGxsSP1nFPaEGkajUKig0d8g7pLLoDwOlrjjyMC6icMHiN7SWpawYXFmDC3UFbgidoCJCw+Fqq4ZqzMoNS6kDXMwKj/pGkzV2thkYq9ekrLxBcAiBMiVu1sS4NClSbIa9TLvLA5VCljYHS5AsLzgmLpYZ6qtia9QomY03W/MC6nKLkkgWvbWBdTEq220EzCrRqU6gylaZysXzNlGUg246G5090NtoC6NRqCsGVRSut2zXIIa9rWDa3/tMC0ieWbalbeKKhqU6Yq13qEMt1WlY5T1XW+nlJLbeFZAKd0YVaF7MrXV6oBF1JAPEEcdYHoJmUmC2q+7Vd3Ur1SarELlFlWqyi5YgcrAeUzV9pqKIXKva1NgLasr3ubf7bPfplMC6iRcLjVq7wr9xHK5uTWAuR5A3HvBlQfaumaVWpTplilI1VGde8oI42JycQbHW3uIgehmJHbEOKO8NJs1v9PMt+PW9vPjK7C7V7RVwzJdVbfqy3B1QgcRoRe9iIFzEqdobRNOrUAuVw+HauwH9x7wVf/5b5SOL01o1a+NrB6hU91Ru7tbuWymy6gXJv5wL6J5raHtAKePVd9TWlTK06lMsMzGp/cB/t7n5t0naptGtRxeIdzmwqMisLa0r0wc/mtzr048LwL+JRptndlgwNTPiHRDmVQALEC5IFzfQc5Y7Qx25FO1NqjVHCKqkDWxPE6cAYEuZlNV9oFSmtQ0nC5ij3KqUYNlIsT3jz7t9J1TbQ3hVqTqgqmkKl1K5h5A3APC9oFpMSipe1NF0dwjELTNRbMrFlBA4A906g2Ouvvkl8dUWtQLI1NartSKMQdcpZWFibcCPj5QLWJiZgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAmJmYgVf0BR4ZqmTI6KmbuoKgs2Xp5dJ1bZFNqgdmdrKVClu6oZcptz1HnaT4gQsJstKTIweo5RCil2vZSVNvhlE4vsKkSCr1UI3mqPYkVHzMPdfpqJaRArKuwqLcC6LlRSiNZSKZuunl/8zf6Ip52bM9mqCpkzd0OCDcDzIlhECtp7FpK4OaoVUlkpl7ohNwSB8Ta/C+k2XZNNVphWqLu6W6Vg1iFup49e6JYRAhYPZqUVRUZ7KXNs33i5uSw95JnUYWwUbypo5e+bU3JOU/7deHkJIiBiIiBwxuDSumSoDa4IIJBUjgQRqD5yGNh0iXNR6tUshp3qPeykg2FrW1AN+OktIgVv0JSIYO1SozZRnd7suU5lykWtY6wNi0srZmqM7Mrb0v3wV4WI4W10tbU9TLKIFbS2LSFsxep/qXzkHNvLZr6eUzT2OgUKalZ1DIyh6l8uRgwA+IHHXzljECtbYtPu5Hq02XMMyPYkMxYg+Vz7xN12RQDUW3YvRRkTnYMLH36fqZPiBHwWCp0KKUaYtTQWAkRNh0hTelmqmkyFN2X7qqeSj9ONuUs4gQ6mz1egaLvUYHixIzaG/G1uPlaaYXZNOkwcM7EM7DMQdals3LqLyfECC+EPahWABDU93UHkCWU/Nh8ZwXYNIZVD1hSVgwpbw5AQbjTjYEDS9paRAiU9m0hRejYslTOXzali5Ja/5zOFwCUs9izFwuYsb3yoF/QayXECoPs7Q3JoKaiUmZiyK2hDcV92mnMcjO21cG9bcBCVyVQxZSAVGRhcX8yJYzECqqez9Fly5qg7rBiG1bMwYkkg63F//aa4LZFqjvVZz9u9REzDLrwaw5+R/KW8QK1NiUxTannq7orlCF+6gveyj9L3tynbE4U1K9Fj9yiS/vcqVHwALH8pNmICZiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAlP7SbeXZ9FajIXLNlVQba2J1PTSXEjY7AUsRTNOtTWol72PXr5QOOxNqLjMMldFKhr908QQSD+knzlh8OlJFp01CIosFAsBOkDzmx8XVyNVZcVUI3nEoKZs5AsSRbTr0M6Nt9TuKxJSmd8rJcMWdCFAFvvXPC3G8s/oyn2c4fvBLk8db5s3H3zimxKIFmzOCahIY3F6hu3z18oHJtvqtUU2psCCi1O8t0ZwCBa92tmW5GgvzsZ32lj9wyE5rZKrlQBrkW/E/wDExT2OisGWpWB7ub7Q9/LoM3U2sL8SAL3nfG4CnXtnvorrobaOtj8oFfU9oMgcth6oCItV+8hy02v3tDqdG0HT3TrU24qVqlOpTdclN6gN1bMqWv3QSRe4Ivxnetsmk4qBs1qlEUW1/sXNb494yNiti23lSizCqd4VDN3b1LZvPWwt005aQOX9SCxzUWV94KYU1E1JTPqwNgAuvGdaO3lqPRRaT/ai/eKrazFSBc94ixJy30sRe4nDZuxmFPd1MyJTKmiQUFRDYgm9MAWINuBvreT32QjGnneqwpsrAM9wWVswJ879LchwgTK9QqjMFLkC4UWufLWw/OV2E22tU0xkIZ6rUj3lYAqhe9wbEWHLrJA2crYU4eqz1FZWViWOYg35/G04jYtPjnq5t5vA2YXDZMhI0tquloEfE7bLUm3NJ2fd1GOqjIFLLckniSDYDpNcJtkhbMKlWoTSRUAUZmaiHNjppa5JPn5SSdhUciqrVFsrJmVzcqxJIPXUnzmx2JRsQM4N0YMGsylECAg/46HrcwO+AxorB+4yOjZHRrXU2B4gkEEEG4PORMdt2nRrGkVLZQpcgqMoY2FgTduBJtynbDbLWlUV0ep/eXuxO8ZsvebzAWw6TfEbMR6hqBqiMQFbI5XMBe1/dc6ix1gQ0241qhOHfSsaNMBlJqMDa3HTgTrylphqjMgZ0NNje6kgka9RcechPsakxfvVAGfeWD2Cve+Zeh/9+sk0cLlyfaVGyBvvNfNc8+tuUCRE4LhbBBnqHKxa5bje+h6jXh5Cd4GYiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIlP7S7eXZ9BahpmoWbKqg21sTqeXCBcRIGxNqLjMMldFKhr908iCQdefCToGYlXhtoMKSl1Ytu2YG472Xj7uInZca2ZVNIi6Fj3hpYj95NbvCxOiV67TGTMabi6Z1GhzDTp7xOpxf2ZfJpkLXuCNOA043jUvCxLiVtTEPTFzd92ig68WY8/db5zPbGSpUzK2UCncXHdzafGNXwqxiQO32IFixLuovYfdNrftN1x4zWKMFzlM2lrj58o1PCpkSuXaylScrWyhhqDcXA5cDqNJ1ONIdENMgtfiRyPv1PO0avhyTIkNceCR3GCM2UPpYn3cbG00XaYy5mRlBQuOBuBbpz1EanhyT4lauNYVHzqw0QKlwTc5v2+U6PtEKLFSHzZcpIHK978LWjV8KnRIVPaIZkUKe+L6kDnY++1uUwm0lIzMjKuVmB0N8vHhGp4ck6JAq7RKqxNJgwXMASNRe3EdLiKu0ghyspBABYXGlz8+HKNXw5J8SH24F93lbOL3HRfxX6GaYfH5ii5WJZA1yQL3HTn8OsanhU+JEoYzNRNV1yKAW430AveO2kKCaTAsQFW4ubi/XThLp41LiQu33sBTbPmKlbgWIF+PS0wm0gRfIwBQut7agceHvk08KnROWHUhFzG7WFz5zrKyREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERASPjcDSxCbutTWol72Yc+vlJEQOWHw6UkWnTUIiiwVRYCdDw04zMxArFwVUBRlpWVWUd5uDceXlMdir903W6ggHO1yDbQ6cNBLSJMdPZVRh8BXVFBK5ggUEu11GnC3DhN0wNYKFGSwN7Z2sTmzXIt1lpEYX5LVc+FrMrqRSs5ue8176cNPITXsdazA7s5styWa5ym45SziMT2VVvgarCxyWLFiA7WJJvrp1mtLBVwxY7s99mClmtc87WltEYvsqrXA1gpXuZeAUu9hY30/Kb18NXqEFt3oQbZmtcG40tLGIw9lVa4GqGB+zsCWC52ygnmB8TM9iq5QpWkQEKDvNwNv2Es4jD2VVdgra3yEm2pdrjLe1jbzMz2Gtb+zNmzZ87Zr2tx92lpaRGHsqsODrkrcocpBF3Y3IN78IGCq5QuWkQAwsWbg3HlLOIw9lVQwFWzBsjXXLdnckDoOkycFXve65rWJFRgWF+enmZaRGHsqs7FVzZ7U89yS2Zrm/I6cPLymFwNYFP9O1O2UF2toLX4dJaRGHsqsTBVguXuFdRlLsRYi1rW4THYa2WxKmxBUmo11t0NpaRGHsqtp4SspBApkgk3LMSSRbXSa9hq2UWp2UWHebhcHp5CWkRh7K1pZsoz2zc7cJvMTMrmREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERAREQEREBERA5doTr8o7QnX5SDK47YpivUokEGlq5voq5Qc35kC3GBf8AaE6/KO0J1+Uovpeh+JhoTY0nuLG1iLaG5AAOpuLcZyp7dpG+YOtuAyMWPeqD7oFx/psf1tA9F2hOvyjtCdflKahtGlUqbtGJYi47jZToDo1rE2I0vzkahtyk4ZrMFVshIBYl9e6FW5JsL8P0Ng9F2hOvyjtCdflKB9t4cAkMz2t92m7XumcWIGvd1PTnaZXa9LuhiVLEAWVmAuQBcgWGpA1gX3aE6/KO0J1+Up8HtClXJ3bE5QpN0ZdGvYi4FwbHUSE236YYpkfOLi2n3hV3dr+f3vcIHpe0J1+UdoTr8pQfTmFtm3ote33W6Xvw+7bnwm1DatOpTquoJNLPmUanulha/C5y3tfmL8YF72hOvyjtCdflKbZuPGIQsFK2bLxBB0B0I98lwJ3aE6/KO0J1+UgxAndoTr8o7QnX5SDECd2hOvyjtCdflIMQJ3aE6/KO0J1+UgxAndoTr8o7QnX5SDECd2hOvyjtCdflIMQJ3aE6/KO0J1+UgxAndoTr8pVYz2nw1Go9NhVJS2YrSZgLi41E7zxG1MfUTadbDBrUsRu0caaEqArXPQ298LM/XqT7ZYQAMRXAPA7lrG3nJuz9vUMQzKm8VlAJD0yujcDr7p4KlQxNSq2Cq1ECYUGo4BFgNL5TzOvPheWXshtOri8TiatU3ORAo/Ct2sPO3WMsW+P4912hOvyjtCdflIEQyn9oTr8o7QnX5SBECf2hOvyjtCdflIEQJ/aE6/KO0J1+UgRAn9oTr8o7QnX5SBECf2hOvyjtCdflIEQJ/aE6/KO0J1+UgRAn9oTr8o7QnX5SBECf2hOvyjtCdflIEQJ/aE6/KO0J1+UgRAn9oTr8o7QnX5SBECf2hOvyjtCdflIEQJ/aE6/KO0J1+UgRAn9oTr8o7QnX5SBEDfdnpIlXZVJ2Zmp3LEkm51umQ8+GUAW4aCWkQKobIpBSu7JDCxJdiTrf7xN73AN730EU9j0kIIpm45lmJ4ueZ1++/wCctYgU9DY606wqrmFlsE5C4Av77KP+b6TZtjUT/wCmR5q7KeJPEG99Tr0JHAy2iBUtsaiVy7qwvfusy65AnEHhlAFpuNmU/D6czyIYc+oEs4gU2A2KtBiy5iTa2pAAUMALDl3jpw6WnU7KpF85pDNvN5fX72XLf8paRAqF2LRAUCmQFN1s7aaWsNdB5cJ0TZdJRUApWFQEOLmzXJJuOveOv7CWcQK/C4BaIIpqRc3JLFiTa2pYknQAfCd92ekkxAjbs9I3Z6STECNuz0jdnpJMQI27PSN2ekkxAjbs9I3Z6STECNuz0jdnpJMQI27PSN2ekkxAjbs9I3Z6STECNuz0nh/aX2ZxmIxlSrSpBkYLYl1HBQOBM+gxA+f4r2dxb4KnTFBu0EgVWLpZkS+QXvyBH5eQk72O2HicK9Y16eUOFAswPAnp757KIEXdnpG7PSSogRd2ekzuz0kmIEXdnpG7PSSogRt2ekbs9JJiBF3Z6Ruz0kqIEXdnpM7s9JJiBG3Z6TG7PSSogRd2ekbs9JKiBF3Z6Ruz0kqIEXdnpG7PSSogRd2ekbs9JKiBF3Z6Ruz0kqIEXdnpG7PSSogRd2ekbs9JKiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiBx7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiB9y7VS8Wn6xHaqXi0/WJ8NiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiAiIgIiICIiB/9k=", + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Generating with Gaussians\n", + "\n", + "try: t3;\n", + "except NameError: t3=time.time()\n", + "\n", + "video = YouTubeVideo(id=\"h96JaT5Jyi4\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "-7PBmLooLeds" + }, + "source": [ + "## Generating novel images from the decoder\n", + "\n", + "If we isolate the decoder part of the AutoEncoder, what we have is a neural network that takes as input a vector of size $K$ and produces as output an image that looks something like our training data. Recall that in our earlier notation, we had an input $\\mathbf{x}$ that was mapped to a low-dimensional hidden representation $\\mathbf{h}$ which was then decoded into a reconstruction of the input, $\\mathbf{x'}$:\n", + "$$\\mathbf{x} \\overset{\\text{encode}}{\\longrightarrow} \\mathbf{h} \\overset{\\text{decode}}{\\longrightarrow} \\mathbf{x'}\\, .$$\n", + "Partly as a matter of convention, and partly to distinguish where we are going next from the previous section, we're going to introduce a new variable, $\\mathbf{z} \\in \\mathbb{R}^K$, which will take the place of $\\mathbf{h}$. The key difference is that while $\\mathbf{h}$ is produced by the encoder for a particular $\\mathbf{x}$, $\\mathbf{z}$ will be drawn out of thin air from a prior of our choosing:\n", + "$$\\mathbf{z} \\sim p(\\mathbf{z})\\\\ \\mathbf{z} \\overset{\\text{decode}}{\\longrightarrow} \\mathbf{x}\\, .$$\n", + "(Note that it is also conventional to drop the \"prime\" on $\\mathbf{x}$ when it is no longer being thought of as a \"reconstruction\")." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "dc0GemsWQYds" + }, + "source": [ + "## Exercise 3\n", + "###Sample $\\mathbf{z}$ from a standard normal and visualize the images produced" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "id": "SYBmyD1JQjoE" + }, + "outputs": [], + "source": [ + "def generate_images(autoencoder, K, n_images=1):\n", + " \"\"\"Generate n_images 'new' images from the decoder part of the given\n", + " autoencoder.\n", + "\n", + " returns (n_images, channels, height, width) tensor of images\n", + " \"\"\"\n", + " # Concatenate tuples to get (n_images, channels, height, width)\n", + " output_shape = (n_images,) + my_dataset_size\n", + " with torch.no_grad():\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your function\n", + " raise NotImplementedError(\"Please complete the generate_images function!\")\n", + " ####################################################################\n", + " ... # Your code here: sample z, pass through autoencoder.decode(), and reshape output.\n", + "\n", + "\n", + "# Uncomment to run it\n", + "# images = generate_images(conv_ae, K, n_images=25)\n", + "# plt.figure(figsize=(5,5))\n", + "# for i in range(25):\n", + "# plt.subplot(5,5,i+1)\n", + "# plot_torch_image(images[i])\n", + "# plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "s-kMt6-ul1iM" + }, + "source": [ + "## Formalizing the problem: density estimation with maximum likelihood\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "1al9VdfYRkt9", + "outputId": "637eb960-b069-43ff-b3e3-5aef49b75636" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "yu1RomPmrAYm" - }, - "source": [ - "## Building a nonlinear convolutional autoencoder\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=rx3IlM4qnvw\n" + ] }, { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "SgKS9x0vS_oR", - "outputId": "7d272c24-6743-463f-d023-f25790aa7870" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=mzHY6rW_4Eo\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "#@title Video: Convolutional Autoencoders\n", - "\n", - "video = YouTubeVideo(id=\"mzHY6rW_4Eo\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" + "text/plain": [ + "" ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Density Networks\n", + "\n", + "video = YouTubeVideo(id=\"rx3IlM4qnvw\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "MqQIy5H7Ud61" + }, + "source": [ + "Note: we've moved the technical details of \"formalizing the problem\" to Appendix A.1 at the end of this notebook. Those who want more of the theoretical/mathematical backstory are encouraged to read it. Those who just want to build a VAE, carry on!" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pRp1gFniPT7B" + }, + "source": [ + "---\n", + "# Section 4: Variational Auto-Encoders (VAEs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "S8jinOmeTT3v", + "outputId": "e8a771de-8ac5-4368-d8cd-08e929c02da5" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "ozE6CZkXv6jM" - }, - "source": [ - "The `nn.Linear` layer by default has a \"bias\" term, which is a learnable offset parameter separate for each output unit. Just like the PCA encoder \"centered\" the data by subtracting off the average image (`mu`) before encoding and added it back in during decoding, a bias term in the decoder can effectively account for the first moment of the data (AKA the average of all images in the training set). Convolution layers do have bias parameters, but the bias is applied per filter rather than per pixel location. If we're generating RGB images, then `Conv2d` will learn only 3 biases: one for each of R, G, and B.\n", - "\n", - "For some conceptual continuity with both PCA and the `nn.Linear` layers above, the next block defines a custom layer for adding a learnable per-pixel offset. This custom layer will be used twice: as the first stage of the encoder and as the final stage of the decoder. Ideally, this means that the rest of the neural net can focus on fitting more interesting fine-grained structure." - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=RgOF3XJL5vw\n" + ] }, { - "cell_type": "code", - "execution_count": 21, - "metadata": { - "id": "raWUBjnUwAs6" - }, - "outputs": [], - "source": [ - "class BiasLayer(nn.Module):\n", - " def __init__(self, shape):\n", - " super(BiasLayer, self).__init__()\n", - " init_bias = torch.zeros(shape)\n", - " self.bias = nn.Parameter(init_bias, requires_grad=True)\n", - " \n", - " def forward(self, x):\n", - " return x + self.bias" + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: VAE Samples\n", + "\n", + "try: t4;\n", + "except NameError: t4=time.time()\n", + "\n", + "video = YouTubeVideo(id=\"RgOF3XJL5vw\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IgROsfdxDbuX" + }, + "source": [ + "## Components of a VAE\n", + "## Recognition models and density networks\n", + "\n", + "Variational AutoEncoders (VAEs) are a lot like the classic AutoEncoders (AEs) you just saw, but where we explicitly think about probability distributions. In the language of VAEs, the __encoder__ is replaced with a __recognition model__, and the __decoder__ is replaced with a __density network__.\n", + "\n", + "Where in a classic autoencoder the encoder maps from images to a single hidden vector,\n", + "$$\\mathbf{x} \\overset{\\text{AE}}{\\longrightarrow} \\mathbf{h} \\, , $$ in a VAE we would say that a recognition model maps from inputs to entire __distributions__ over hidden vectors,\n", + "$$\\mathbf{x} \\overset{\\text{VAE}}{\\longrightarrow} q(\\mathbf{z}) \\, ,$$\n", + "which we will then sample from.\n", + "We'll say more in a moment about what kind of distribution $q(\\mathbf{z})$ is.\n", + "Part of what makes VAEs work is that the loss function will require good reconstructions of the input not just for a single $\\mathbf{z}$, but _on average_ from samples of $\\mathbf{z} \\sim q(\\mathbf{z})$.\n", + "\n", + "In the classic autoencoder, we had a decoder which maps from hidden vectors to reconstructions of the input:\n", + "$$\\mathbf{h} \\overset{\\text{AE}}{\\longrightarrow} \\mathbf{x'} \\, .$$\n", + "In a density network, reconstructions are expressed in terms of a distribution:\n", + "$$\\mathbf{z} \\overset{\\text{VAE}}{\\longrightarrow} p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) $$\n", + "where, as above, $p(\\mathbf{x}|\\mathbf{z};\\mathbf{w})$ is defined by mapping $\\mathbf{z}$ through a density network then treating the resulting $f(\\mathbf{z};\\mathbf{w})$ as the mean of a (Gaussian) distribution over $\\mathbf{x}$." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "svLx5HwJKhdZ" + }, + "source": [ + "## Exercise 4\n", + "### Sampling from $q(\\mathbf{z})$\n", + "\n", + "How can a neural network (the __recognition model__) output an entire probability distribution $$\\mathbf{x} \\longrightarrow q(\\mathbf{z}) \\, ?$$\n", + "One idea would be to make the weights of the neural network stochastic, so that every time the network is run, a different $\\mathbf{z}$ is produced. (In fact, this is quite common in [Bayesian Neural Networks](https://medium.com/neuralspace/bayesian-neural-network-series-post-1-need-for-bayesian-networks-e209e66b70b2), but this isn't what people use in VAEs.)\n", + "\n", + "Instead, we will start by committing to a particular _family_ of distributions. We'll then have the recognition model output the _parameters_ of $q$, which we'll call $\\phi$. A common choice, which we will use throughout, is the family of isotropic multivariate Gaussians$^\\dagger$:\n", + "$$q(\\mathbf{z};\\phi) = \\mathcal{N}(\\mathbf{z};\\boldsymbol{\\mu},\\sigma^2\\mathbf{I}_K) = \\prod_{k=1}^K \\mathcal{N}(z_k; \\mu_k, \\sigma^2)$$\n", + "where the $K+1$ parameters are$^*$\n", + "$$\\phi = \\lbrace{\\mu_1, \\mu_2, \\ldots, \\mu_K, \\log(\\sigma)}\\rbrace \\, .$$\n", + "By defining the last entry of $\\phi$ as the _logarithm_ of $\\sigma$, the last entry can be any real number while enforcing the requirement that $\\sigma > 0$.\n", + "\n", + "A recognition model is a neural network that takes $\\mathbf{x}$ as input and produces $\\phi$ as output. The purpose of the following exercise is not to write a recognition model (that will come later), but to clarify the relationship between $\\phi$ and $q(\\mathbf{z})$. You will write a function, `rsample`, which takes as input a batch $\\phi$s and will output a set of samples of $\\mathbf{z}$ drawn from $q(\\mathbf{z};\\phi)$." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "id": "0ReQnZaDT2i4" + }, + "outputs": [], + "source": [ + "def rsample(phi, n_samples):\n", + " \"\"\"Sample z ~ q(z;phi)\n", + " Ouput z is size [b,n_samples,K] given phi with shape [b,K+1]. The first K\n", + " entries of each row of phi are the mean of q, and phi[:,-1] is the log\n", + " standard deviation\n", + " \"\"\"\n", + " b, kplus1 = phi.size()\n", + " k = kplus1 - 1\n", + " mu, sig = phi[:, :-1], phi[:, -1].exp()\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your function\n", + " raise NotImplementedError(\"Please complete the rsample function!\")\n", + " ####################################################################\n", + " ... # your code here!\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 227 }, + "id": "5ebTNwLKUFHY", + "outputId": "67ba1fe6-a40e-45e2-d207-75161d9e23b8" + }, + "outputs": [ { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "id": "KwhsR5WWxfdN" - }, - "source": [ - "With that out of the way, we will next define a **nonlinear** and **convolutional** autoencoder. Here's a quick tour of the architecture:\n", - "\n", - "1. The **encoder** once again maps from images to $\\mathbf{h}\\in\\mathbb{R}^K$. This will use a `BiasLayer` followed by two convolutional layers (`nn.Conv2D`), followed by flattening and linearly projecting down to $K$ dimensions. The convolutional layers will have `ReLU` nonlinearities on their outputs. \n", - "1. The **decoder** inverts this process, taking in vectors of length $K$ and outputting images. Roughly speaking, its architecture is a \"mirror image\" of the encoder: the first decoder layer is linear, followed by two **deconvolution** layers (`nn.ConvTranspose2d`). The `ConvTranspose2d` layers will have `ReLU` nonlinearities on their _inputs_. This \"mirror image\" between the encoder and decoder is a useful and near-ubiquitous convention. The idea is that the decoder can then learn to approximately invert the encoder, but it is not a strict requirement (and it does not guarantee the decoder will be an exact inverse of the encoder!).\n", - "\n", - "Below is a schematic of the architecture for MNIST. Notice that the width and height dimensions of the image planes reduce after each `nn.Conv2d` and increase after each `nn.ConvTranspose2d`. With CIFAR10, the architecture is the same but the exact sizes will differ a bit.\n", - "\n", - "![image](https://user-images.githubusercontent.com/693511/225031474-1a2df523-4ca7-4154-8921-e5ee3516f98e.png)\n", - "\n", - "We will not go into detail about `ConvTranspose2d` here. For now, just know that it acts a bit like, but not exactly, an inverse to `Conv2d`. The following code demonstrates this change in sizes:" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n" + ] }, { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/" - }, - "id": "_j3LZPFJ2yh_", - "outputId": "1af0bba9-e343-4ff1-865e-f95ae668d6f4" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Size of image is torch.Size([1, 1, 28, 28])\n", - "Size of Conv2D(image) torch.Size([1, 1, 24, 24])\n", - "Size of ConvTranspose2D(image) torch.Size([1, 1, 32, 32])\n", - "Size of ConvTranspose2D(Conv2D(image)) torch.Size([1, 1, 28, 28])\n" - ] - } - ], - "source": [ - "dummy_image = torch.zeros(my_dataset_size).unsqueeze(0)\n", - "channels = my_dataset_size[0]\n", - "dummy_conv = nn.Conv2d(in_channels=channels, out_channels=channels, kernel_size=5)\n", - "dummy_conv_transpose = nn.ConvTranspose2d(in_channels=channels, out_channels=channels, kernel_size=5)\n", - "\n", - "print(f'Size of image is {dummy_image.size()}')\n", - "print(f'Size of Conv2D(image) {dummy_conv(dummy_image).size()}')\n", - "print(f'Size of ConvTranspose2D(image) {dummy_conv_transpose(dummy_image).size()}')\n", - "print(f'Size of ConvTranspose2D(Conv2D(image)) {dummy_conv_transpose(dummy_conv(dummy_image)).size()}')" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 293, + "width": 1166 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# Testing rsample()\n", + "phi = torch.randn(4, 3, device=DEVICE)\n", + "zs = rsample(phi, 100)\n", + "assert zs.size() == (4, 100, 2), \"rsample size is incorrect!\"\n", + "assert zs.device == phi.device, \"rsample device doesn't match phi device!\"\n", + "zs = zs.cpu()\n", + "\n", + "with plt.xkcd():\n", + " plt.figure(figsize=(12, 3))\n", + " for i in range(4):\n", + " plt.subplot(1, 4, i + 1)\n", + " plt.scatter(zs[i, :, 0], zs[i, :, 1], marker=\".\")\n", + " th = torch.linspace(0, 6.28318, 100)\n", + " x, y = torch.cos(th), torch.sin(th)\n", + " # Draw 2-sigma contours\n", + " plt.plot(\n", + " 2 * x * phi[i, 2].exp().item() + phi[i, 0].item(),\n", + " 2 * y * phi[i, 2].exp().item() + phi[i, 1].item(),\n", + " )\n", + " # plt.title(f'mu={phi[i,0].item():.2f},{phi[i,1].item():.2f}, sig={phi[i,2].exp().item():.3f}')\n", + " plt.xlim(-5, 5)\n", + " plt.ylim(-5, 5)\n", + " plt.grid()\n", + " plt.axis(\"equal\")\n", + " plt.suptitle(\n", + " \"If rsample() is correct, then most but not all points should lie in the circles\"\n", + " )\n", + " plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "nKZgt0ebP5Pe" + }, + "source": [ + "---\n", + "\n", + "$^\\dagger$ PyTorch has a `MultivariateNormal` class which handles multivariate Gaussian distributions with arbitrary covariance matrices. It is not very beginner-friendly, though, so we will write our own functions to work with $\\phi$, which will both teach you some implementation details and is not very hard especially if we use only an isotropic ($\\sigma$) or diagonal ($\\lbrace{\\sigma_1, \\ldots, \\sigma_K}\\rbrace$) covariance\n", + "\n", + "$^*$ Another common parameterization is to use a separate $\\sigma$ for each dimension of $\\mathbf{z}$, in which case $\\phi$ would instead contain $2K$ parameters:\n", + "$$\\phi = \\lbrace{\\mu_1, \\mu_2, \\ldots, \\mu_K, \\log(\\sigma_1), \\ldots, \\log(\\sigma_K)}\\rbrace \\, .$$" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LlQfA-aiK_LS" + }, + "source": [ + "## VAE training: maximize the Evidence Lower BOund (ELBO)\n", + "\n", + "\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "r64ZiPHZc7tb", + "outputId": "be7e6811-cb95-41e2-8072-a0e836efc144" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "VfY8DpGx28pt" - }, - "source": [ - "### Exercise 2\n", - "### Fill in code for the `ConvAutoEncoder` module\n" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=-99NskgKDo0\n" + ] }, { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "id": "mjH_LETh7hgn" - }, - "outputs": [], - "source": [ - "class ConvAutoEncoder(nn.Module):\n", - " def __init__(self, K, num_filters=32, filter_size=5):\n", - " super(ConvAutoEncoder, self).__init__()\n", - "\n", - " # With padding=0, the number of pixels cut off from each image dimension\n", - " # is filter_size // 2. Double it to get the amount of pixels lost in\n", - " # width and height per Conv2D layer, or added back in per\n", - " # ConvTranspose2D layer.\n", - " filter_reduction = 2 * (filter_size // 2)\n", - "\n", - " # After passing input through two Conv2d layers, the shape will be\n", - " # 'shape_after_conv'. This is also the shape that will go into the first\n", - " # deconvolution layer in the decoder\n", - " self.shape_after_conv = (\n", - " num_filters,\n", - " my_dataset_size[1] - 2 * filter_reduction,\n", - " my_dataset_size[2] - 2 * filter_reduction,\n", - " )\n", - " flat_size_after_conv = (\n", - " self.shape_after_conv[0]\n", - " * self.shape_after_conv[1]\n", - " * self.shape_after_conv[2]\n", - " )\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your class\n", - " raise NotImplementedError(\"Please complete the ConvAutoEncoder class!\")\n", - " ####################################################################\n", - " # Your code here\n", - " ... # Create encoder layers (BiasLayer, Conv2d, Conv2d, Flatten, Linear)\n", - " ... # Create decoder layers (Linear, Unflatten(-1, self.shape_after_conv), ConvTranspose2d, ConvTranspose2d, BiasLayer)\n", - "\n", - " def encode(self, x):\n", - " ... # Your code here: encode batch of images (don't forget ReLUs!)\n", - " return h\n", - "\n", - " def decode(self, h):\n", - " ... # Your code here: decode batch of h vectors (don't forget ReLUs!)\n", - " return x_prime\n", - "\n", - " def forward(self, x):\n", - " return self.decode(self.encode(x))\n", - "\n", - "\n", - "# Uncomment to test your solution\n", - "# conv_ae = ConvAutoEncoder(K=K)\n", - "# assert conv_ae.encode(my_dataset[0][0].unsqueeze(0)).numel() == K, \\\n", - "# \"Encoder output size should be K!\"\n", - "# conv_losses = train_autoencoder(conv_ae, my_dataset)\n", - "# plt.figure()\n", - "# plt.plot(lin_losses)\n", - "# plt.plot(conv_losses)\n", - "# plt.legend(['Lin AE', 'Conv AE'])\n", - "# plt.xlabel('Training batch')\n", - "# plt.ylabel('MSE Loss')\n", - "# plt.ylim([0,2*max(torch.as_tensor(conv_losses).median(), torch.as_tensor(lin_losses).median())])\n", - "# plt.show()\n" + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: ELBO\n", + "\n", + "video = YouTubeVideo(id=\"-99NskgKDo0\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CiS0Z8ZOetw9" + }, + "source": [ + "A full derivation and further explanation of the ELBO can be found in Appendix A.2 at the end of this notebook. In the following few sections, we provide implementations of `log_p_x` and `kl_q_p` for you, since the technical details of each can be somewhat opaque." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "uyBiFvRac-fE" + }, + "source": [ + "\n", + "\n", + "First, we'll implement the $\\color{blue}{\\mathbb{E}_{q(\\mathbf{z};\\phi)}\\left[\\log p(\\mathbf{x}_i|\\mathbf{z};\\mathbf{w}) \\right]}$ term in PyTorch in a function called `log_p_x`.\n", + "Earlier, we introduced the density network with $p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) = \\mathcal{N}\\left(f(\\mathbf{z};\\mathbf{w}), \\sigma^2_x\\mathbf{I}_P\\right)$. The $\\log$ of this is\n", + "\\begin{align}\\log p(\\mathbf{x}_i|\\mathbf{z};\\mathbf{w}) &= -\\frac{1}{2} \\frac{||\\mathbf{x}_i - f(\\mathbf{z};\\mathbf{w})||_2^2}{\\sigma_\\mathbf{x}^2} - P \\log(\\sigma_\\mathbf{x}) \\\\\n", + "&= -\\sum_{j=1}^P \\left(\\frac{(x_{ij} - f(\\mathbf{z};\\mathbf{w})_j)^2}{2\\sigma_\\mathbf{x}^2} + \\log \\sigma_\\mathbf{x}\\right)\\end{align}\n", + "where $j$ indexes individual pixels in the image." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "id": "xWDsqABzgZ36" + }, + "outputs": [], + "source": [ + "def log_p_x(x, mu_xs, sig_x):\n", + " \"\"\"Given [batch, ...] input x and [batch, n, ...] reconstructions, compute\n", + " pixel-wise log Gaussian probability\n", + "\n", + " Sum over pixel dimensions, but mean over batch and samples.\n", + " \"\"\"\n", + " b, n = mu_xs.size()[:2]\n", + " # Flatten out pixels and add a singleton dimension [1] so that x will be\n", + " # implicitly expanded when combined with mu_xs\n", + " x = x.reshape(b, 3, -1) if my_dataset_name == \"CIFAR\" else x.reshape(b, 1, -1)\n", + " \n", + " _, _, p = x.size()\n", + " squared_error = (x - mu_xs.view(b, n, -1)) ** 2 / (2 * sig_x**2)\n", + "\n", + " # Size of squared_error is [b,n,p]. log prob is by definition sum over [p].\n", + " # Expected value requires mean over [n]. Handling different size batches\n", + " # requires mean over [b].\n", + " return -(squared_error + torch.log(sig_x)).sum(dim=2).mean(dim=(0, 1))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FIvFgXZNiZjY" + }, + "source": [ + "Next, we will implement the $\\color{green}{KL(q(\\mathbf{z};\\phi)||p(\\mathbf{z}))}$ term in a function called `kl_q_p`. While we could plug in the exact formula for $KL$ between two Gaussians, a more general (but more variable) approach is to write\n", + "$$KL(q(\\mathbf{z};\\phi)||p(\\mathbf{z})) = \\mathbb{E}_{q(\\mathbf{z};\\phi)}\\left[\\log q(\\mathbf{z};\\phi) - \\log p(\\mathbf{z})\\right]$$\n", + "and approximate this expectation with samples of $\\mathbf{z} \\sim q(\\mathbf{z};\\phi)$ just like we did for the reconstruction term." + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "id": "p0wOSNHuiYb4" + }, + "outputs": [], + "source": [ + "def kl_q_p(zs, phi):\n", + " \"\"\"Given [b,n,k] samples of z drawn from q, compute estimate of KL(q||p).\n", + " phi must be size [b,k+1]\n", + "\n", + " This uses mu_p = 0 and sigma_p = 1, which simplifies the log(p(zs)) term to\n", + " just -1/2*(zs**2)\n", + " \"\"\"\n", + " b, n, k = zs.size()\n", + " mu_q, log_sig_q = phi[:, :-1], phi[:, -1]\n", + " log_p = -0.5 * (zs**2)\n", + " log_q = -0.5 * (zs - mu_q.view(b, 1, k)) ** 2 / log_sig_q.exp().view(\n", + " b, 1, 1\n", + " ) ** 2 - log_sig_q.view(b, 1, -1)\n", + " # Size of log_q and log_p is [b,n,k]. Sum along [k] but mean along [b,n]\n", + " return (log_q - log_p).sum(dim=2).mean(dim=(0, 1))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PGtTMpqJq-8n" + }, + "source": [ + "Finally, we will implement the ELBO in a function called, well, `elbo`. Recall from the video that $$\\text{ELBO}(\\mathbf{x}_i,\\phi,\\mathbf{w}) = \\color{blue}{\\mathbb{E}_{q(\\mathbf{z};\\phi)}\\left[\\log p(\\mathbf{x}_i|\\mathbf{z};\\mathbf{w}) \\right]} - \\color{green}{KL(q(\\mathbf{z};\\phi)||p(\\mathbf{z}))} \\, \\,$$\n", + "and that we have two functions for this: `log_p_x` for the first term and `kl_q_p` for the second term. At a high level, the `elbo` function simply computes each of these terms and takes their difference!\n", + "\n", + "For a bit more detail, `elbo` it will have five inputs:\n", + "\n", + "* `x`, which is a _batch_ of input images of size `[batch,channels,height,width]`\n", + "* `phi`, which as before is a batch of _parameters_ of $q(\\mathbf{z};\\phi)$ with size `[batch,k+1]`\n", + "* `density_net`, which takes in $\\mathbf{z}$s and outputs reconstructed $\\mathbf{x}$s. (For those who dove into Appendix A.1 it really outputs the mean of a distribution over each $\\mathbf{x}$. This is the $f(\\mathbf{z};\\mathbf{w})$ in the mathematical notation in the Appendix.)\n", + "* `sig_x`, which is the amount of \"pixel noise\" in the generative model ($\\sigma_\\mathbf{x}$ in the appendix). Intuitively, larger `sig_x` means that the model can be sloppier in its reconstructions, since errors are attributed to _noise_.\n", + "* `n`: the number of samples of `z` that will be sampled per input image." + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "id": "5SPSu2ZdrOIu" + }, + "outputs": [], + "source": [ + "def elbo(x, phi, density_net, sig_x, n):\n", + " # Start by drawing n samples of z from q(z;phi)\n", + " zs = rsample(phi, n)\n", + " # Density net expects just [b,k] inputs, so we'll collapse together batch\n", + " # and samples dimensions to get [b*n,k] samples of z, then expand back out\n", + " # separate [b,n,p] dimensions in the result\n", + " b = x.size()[0]\n", + " mu_xs = density_net(zs.view(b * n, -1)).view(b, n, -1)\n", + " # Compute reconstruction and regularization terms. ELBO = diff. between them\n", + " return log_p_x(x, mu_xs, sig_x) - kl_q_p(zs, phi)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LnOSPFb5oNHS" + }, + "source": [ + "### See the ELBO in action\n", + "\n", + "What's cool about the ELBO is that it is a single objective which solves two problems at once:\n", + "\n", + "1. When we maximize the ELBO with respect to $\\phi$, we are making $q(\\mathbf{z};\\phi)$ closer to $p(\\mathbf{z}|\\mathbf{x};\\mathbf{w})$. This approximately solves the \"needle in a haystack\" problem of finding which $\\mathbf{z}$s are \"relevant\" for each $\\mathbf{x}_i$. This is the probabilistic equivalent of the _encoder_ from before, which simply mapped from $\\mathbf{x}$ to $\\mathbf{h}$, except now we have an entire distribution $q(\\mathbf{z};\\phi)$.\n", + "2. When we maximize the ELBO with respect to $\\mathbf{w}$, we are improving the generative model, making $p(\\mathbf{x};\\mathbf{w})$ closer to the distribution of training examples of $\\mathbf{x}$. In other words, we are getting better at _generating new $\\mathbf{x}$ from $\\mathbf{z}$_.\n", + "\n", + "(Further details and explanations can be found in Appendix A.2)\n", + "\n", + "To see the ELBO in action, we'll use it to infer $\\mathbf{z}$ for a single $\\mathbf{x}$ using the decoder part of the convolutional autoencoder you built in the first part. This section may also need to be run multiple times, or with larger `steps` (especially if you chose a large $K$)." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 325, + "referenced_widgets": [ + "83e45f5dd5b144018e175f6753b389de", + "90ab04273a9e41eda658baacbac07acd", + "374d595cfc1748cb80d6384791588795", + "42b8cc64de9546e1bb8a2b852a417279", + "9137662d519043f4b63a79a1e9d42671", + "cef45f2502b24609af4c9162442a15ab", + "d15d1a79f8d74a5eafaa85a11db1d8df", + "6774ef7b87f24ad8a5602c5a7595938e", + "0661ed223ab04813b9648f4bb65c2d06", + "b4a6a58e517146cbad3b5ba7e8afdb98", + "c2e32eec26bd4e86bb70b508a46e88d7" + ] }, + "id": "fKgahgnzoeoO", + "outputId": "04ab03a0-fd11-4d29-b375-76129b2a214b" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "n48WL4b8yxUm" + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b37a8c6dcbe24bac834e899e4a34019a", + "version_major": 2, + "version_minor": 0 }, - "source": [ - "You should see that the `ConvAutoEncoder` achieved lower MSE loss than the linear one. If not, you may need to retrain it (or run another few training epochs from where it left off). We make fewer guarantees on this working with CIFAR10, but it should definitely work with MNIST.\n", - "\n", - "Now let's visually compare the reconstructed images from the linear and nonlinear autoencoders. Keep in mind that both have the same dimensionality for $\\mathbf{h}$!" + "text/plain": [ + " 0%| | 0/4000 [00:00" - ] - }, - "metadata": { - "image/png": { - "height": 409, - "width": 974 - } - }, - "output_type": "display_data" - } - ], - "source": [ - "n_plot = 7\n", - "plt.figure(figsize=(10,4.5))\n", - "for i in range(n_plot):\n", - " idx = torch.randint(len(my_dataset), size=())\n", - " image, _ = my_dataset[idx]\n", - " with torch.no_grad():\n", - " # Get reconstructed image from linear autoencoder\n", - " lin_recon = lin_ae(image.unsqueeze(0))[0]\n", - " \n", - " # Get reconstruction from deep (nonlinear) autoencoder\n", - " nonlin_recon = conv_ae(image.unsqueeze(0))[0]\n", - " \n", - " plt.subplot(3,n_plot,i+1)\n", - " plot_torch_image(image)\n", - " if i == 0:\n", - " plt.ylabel('Original\\nImage')\n", - " \n", - " plt.subplot(3,n_plot,i+1+n_plot)\n", - " plot_torch_image(lin_recon)\n", - " if i == 0:\n", - " plt.ylabel(f'Lin AE\\n(K={K})')\n", - " \n", - " plt.subplot(3,n_plot,i+1+2*n_plot)\n", - " plot_torch_image(nonlin_recon)\n", - " if i == 0:\n", - " plt.ylabel(f'NonLin AE\\n(K={K})')\n", - "plt.show()" - ] + "name": "stderr", + "output_type": "stream", + "text": [ + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family ['xkcd', 'xkcd Script', 'Humor Sans', 'Comic Neue', 'Comic Sans MS'] not found. Falling back to DejaVu Sans.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family ['xkcd', 'xkcd Script', 'Humor Sans', 'Comic Neue', 'Comic Sans MS'] not found. Falling back to DejaVu Sans.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family ['xkcd', 'xkcd Script', 'Humor Sans', 'Comic Neue', 'Comic Sans MS'] not found. Falling back to DejaVu Sans.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n", + "findfont: Font family 'xkcd' not found.\n", + "findfont: Font family 'xkcd Script' not found.\n", + "findfont: Font family 'Humor Sans' not found.\n", + "findfont: Font family 'Comic Neue' not found.\n", + "findfont: Font family 'Comic Sans MS' not found.\n" + ] }, { - "cell_type": "markdown", - "metadata": { - "id": "bSpvDpLXrLD5" - }, - "source": [ - "## Inspecting the hidden representations\n", - "\n" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 428, + "width": 978 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "# Pick a random image from the validation set\n", + "idx = torch.randint(len(my_valset), size=())\n", + "x_i, _ = my_valset[idx]\n", + "\n", + "# Solve for q(z;phi) by maximizing the ELBO by gradient ascent\n", + "steps = 4000\n", + "phi = torch.zeros(1, K + 1, requires_grad=True, device=DEVICE)\n", + "# sig_x controls amount of 'pixel noise'.\n", + "# Lower --> more 'strict' reconstructions, so q(z) will be narrower.\n", + "# Higher --> more 'lax' reconstructions, so q(z) will be wider.\n", + "sig_x = torch.tensor(0.5, device=DEVICE)\n", + "optim = torch.optim.Adam([phi], lr=0.001)\n", + "elbo_vals = torch.zeros(steps, device=DEVICE)\n", + "x_i = x_i.to(DEVICE).unsqueeze(0)\n", + "conv_ae.to(DEVICE)\n", + "for iter in trange(steps, leave=False):\n", + " optim.zero_grad()\n", + " loss = -elbo(x_i, phi, density_net=conv_ae.decode, sig_x=sig_x, n=16)\n", + " loss.backward()\n", + " optim.step()\n", + " elbo_vals[iter] = -loss.detach()\n", + "x_i = x_i.to(\"cpu\")\n", + "conv_ae.to(\"cpu\")\n", + "phi = phi.detach().cpu().flatten()\n", + "\n", + "mu_q = phi[:-1]\n", + "sig_q = torch.exp(phi[-1]) * torch.ones(K)\n", + "\n", + "# For comparison, what would our AE encoder have produced?\n", + "h = conv_ae.encode(x_i).detach().flatten()\n", + "\n", + "# Plot\n", + "with plt.xkcd():\n", + " plt.figure(figsize=(10, 4.5))\n", + " plt.subplot(1, 2, 1)\n", + " plt.plot(elbo_vals.cpu())\n", + " plt.xlabel(\"Iterations\")\n", + " plt.ylabel(\"ELBO\")\n", + " plt.title(\"ELBO gradient ascent w.r.t. $\\phi$\")\n", + " plt.subplot(1, 2, 2)\n", + " plt.plot(torch.arange(1, K + 1), h, marker=\".\", color=\"k\", linestyle=\"-\")\n", + " plt.errorbar(\n", + " torch.arange(1, K + 1), mu_q, sig_q, marker=\".\", linestyle=\"-\", color=\"b\"\n", + " )\n", + " plt.legend([\"h\", \"q(z;$\\phi$)\"])\n", + " plt.xlabel(\"hidden dimension (k)\")\n", + " plt.ylabel(\"z_k\")\n", + " plt.title(\"q(z) gets close to h\")\n", + " plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "otcFWoujtmDP" + }, + "source": [ + "Hopefully you see that we successfully maximized the ELBO by ascending its gradient with respect to $\\phi$, and that the resulting distribution $q(\\mathbf{z};\\phi)$ is close to the vector $\\mathbf{h}$ that our original autoencoder produces for the same image.\n", + "\n", + "Remember that in a VAE, we are thinking in terms of _distributions_. Rather than a single $\\mathbf{h}$, we have an entire distribution of $\\mathbf{z}$s. We should be able to sample $\\mathbf{z} \\sim q(\\mathbf{z};\\phi)$ and get decent reconstructions of $\\mathbf{x}_i$ for all of them. Let's take a look:" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 137 }, + "id": "5LlIucKSs8sE", + "outputId": "197c59a7-0172-47bb-f1ee-30c6cf151347" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "k7OGAEnI0J8o", - "outputId": "965f5b27-a311-4fec-b20d-f0e04ad878ca" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=HcvTrvCntBY\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#@title Video: Latent Space\n", - "\n", - "video = YouTubeVideo(id=\"HcvTrvCntBY\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 166, + "width": 975 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 3))\n", + "plt.subplot(1, 7, 1)\n", + "plot_torch_image(x_i[0])\n", + "plt.title(\"$x_i$\")\n", + "\n", + "orig_reconstruction = conv_ae.decode(h.view(1, K))[0].detach()\n", + "plt.subplot(1, 7, 2)\n", + "plot_torch_image(orig_reconstruction)\n", + "plt.title(\"h --> $x'$\")\n", + "\n", + "zs = rsample(phi.view(1, -1), 5)[0]\n", + "q_reconstructions = conv_ae.decode(zs).detach()\n", + "for i in range(5):\n", + " plt.subplot(1, 7, 3 + i)\n", + " plot_torch_image(q_reconstructions[i])\n", + " plt.title(f\"$z_{i+1}$ --> $x'$\")\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "wEmc1SLvvWnf" + }, + "source": [ + "You should see that the reconstructions from each sampled $\\mathbf{z}$ vary slightly from each other, but that all are plausible reconstructions of the original $\\mathbf{x}_i$. This proves that maximizing the ELBO by doing gradient descent on $\\phi$ gives us the ability to reconstruct $\\mathbf{x}$ a few different ways based on a __distribution__ of $\\mathbf{z}$s.\n", + "\n", + "(Your results may vary, depending on the dataset, $K$, number of optimization steps, etc)." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "9N1Uz_OxEyEP" + }, + "source": [ + "## Build a VAE\n", + "\n", + "You now have all the ingredients you need to build a VAE! The architecture in this example will be nearly identical to the `ConvAutoEncoder` from earlier, with a few key differences reflecting the fact that we're now thinking _distributionally_:\n", + "\n", + "* The encoder is now a \"recognition model\" that outputs $\\phi$ for each input rather than $\\mathbf{h}$. All this means in the code is that the final linear layer which previously projected down to `K` dimensions will now project down to `K+1` dimensions (the size of $\\phi$).\n", + "* The model will store `sig_x` as an extra parameter for the density network. In fact, we'll make `sig_x` learned from data as well.\n", + "* We'll train to maximize the ELBO" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "XPytk4mmMXor", + "outputId": "f1993205-c3da-4996-8935-6fe98e70f18a" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "TaAkIZpZ9nAG" - }, - "source": [ - "Let's start by plotting points in the hidden space ($\\mathbf{h}$), colored by class of the image (which, of course, the autoencoder didn't know about during training!)" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=QPPCjiN7UIk\n" + ] }, { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 433 - }, - "id": "eSDlEhzC95rc", - "outputId": "ed185eb9-0009-4248-d453-2331044ef06f" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 577, - "width": 638 - } - }, - "output_type": "display_data" - } + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "h_vectors = torch.zeros(len(my_valset), K, device=DEVICE)\n", - "labels = torch.zeros(len(my_valset), dtype=torch.int32)\n", - "loader = DataLoader(my_valset, batch_size=200, pin_memory=True)\n", - "conv_ae.to(DEVICE)\n", - "i = 0\n", - "for im, la in loader:\n", - " b = im.size()[0]\n", - " h_vectors[i : i + b, :] = conv_ae.encode(im.to(DEVICE))\n", - " labels[i : i + b] = la\n", - " i += b\n", - "conv_ae.to(\"cpu\")\n", - "h_vectors = h_vectors.detach().cpu()\n", - "_, _, h_pcs = torch.pca_lowrank(h_vectors, q=2)\n", - "h_xy = h_vectors @ h_pcs\n", - "\n", - "with plt.xkcd():\n", - " plt.figure(figsize=(7, 6))\n", - " plt.scatter(h_xy[:, 0], h_xy[:, 1], c=labels, cmap=\"hsv\")\n", - " plt.title(\"2D projection of h, colored by class\")\n", - " plt.colorbar()\n", - " plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "2vhNusJZ01KR" - }, - "source": [ - "To explore the hidden representations, $\\mathbf{h}$, we're going to pick two random images from the dataset and interpolate them 3 different ways. Let's introduce some notation for this: we'll use a variable $t \\in [0,1]$ to gradually transition from image $\\mathbf{x}_1$ at $t=0$ to image $\\mathbf{x}_2$ at $t=1$. Using $\\mathbf{x}(t)$ to denote the interpolated output, the three methods will be\n", - "\n", - "1. interpolate the raw pixels, so $$\\mathbf{x}(t) = (1-t) \\cdot \\mathbf{x}_1 + t \\cdot \\mathbf{x}_2$$\n", - "2. interpolate their encodings from the **linear** AE, so $$\\mathbf{x}(t) = \\text{linear_decoder}((1-t) \\cdot \\text{linear_encoder}(\\mathbf{x}_1) + t \\cdot \\text{linear_encoder}(\\mathbf{x}_2))$$\n", - "3. interpolate their encodings from the **nonlinear** AE, so $$\\mathbf{x}(t) = \\text{conv_decoder}((1-t) \\cdot \\text{conv_encoder}(\\mathbf{x}_1) + t \\cdot \\text{conv_encoder}(\\mathbf{x}_2))$$\n", - "\n", - "Note: This demo will likely look better using MNIST than using CIFAR, but you can answer the question below for either one of them. " + "text/plain": [ + "" ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: VAEs: the big picture\n", + "\n", + "video = YouTubeVideo(id=\"QPPCjiN7UIk\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pRJiI7l6xmHY" + }, + "source": [ + "### Exercise 5\n", + "\n", + "### Write a VAE with otherwise the same architecture as `ConvAutoEncoder`\n", + "\n", + "Note that we're actually not using `elbo()` from above, but rewriting it to be a member function of the `ConvVAE` class. This is simply to reduce the amount of reshaping you need to worry about, but they're functionally the same." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "lUEOIel7PJZh" + }, + "outputs": [], + "source": [ + "class ConvVAE(nn.Module):\n", + " def __init__(self, K, num_filters=32, filter_size=5):\n", + " super(ConvVAE, self).__init__()\n", + "\n", + " # With padding=0, the number of pixels cut off from each image dimension\n", + " # is filter_size // 2. Double it to get the amount of pixels lost in\n", + " # width and height per Conv2D layer, or added back in per\n", + " # ConvTranspose2D layer.\n", + " filter_reduction = 2 * (filter_size // 2)\n", + "\n", + " # After passing input through two Conv2d layers, the shape will be\n", + " # 'shape_after_conv'. This is also the shape that will go into the first\n", + " # deconvolution layer in the decoder\n", + " self.shape_after_conv = (\n", + " num_filters,\n", + " my_dataset_size[1] - 2 * filter_reduction,\n", + " my_dataset_size[2] - 2 * filter_reduction,\n", + " )\n", + " flat_size_after_conv = (\n", + " self.shape_after_conv[0]\n", + " * self.shape_after_conv[1]\n", + " * self.shape_after_conv[2]\n", + " )\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your class\n", + " raise NotImplementedError(\"Please complete the ConvVAE class!\")\n", + " ####################################################################\n", + " # Define the recognition model (encoder or q) part\n", + " ... # YOUR CODE HERE (BiasLayer, nn.Conv2d x2, nn.Flatten, nn.Linear)\n", + "\n", + " # Define the generative model (decoder or p) part\n", + " ... # YOUR CODE HERE (nn.Linear, nn.Unflatten(-1, self.shape_after_conv), nn.ConvTranspose2d x2, BiasLayer)\n", + "\n", + " # Define a special extra parameter to learn scalar sig_x for all pixels.\n", + " self.log_sig_x = nn.Parameter(torch.zeros(()))\n", + "\n", + " def infer(self, x):\n", + " \"\"\"Map (batch of) x to (batch of) phi which can then be passed to\n", + " rsample to get z\n", + " \"\"\"\n", + " ... # YOUR CODE HERE. Analogous to conv_ae.encode(). Output should be size [b,k+1]\n", + "\n", + " def generate(self, zs):\n", + " \"\"\"Map [b,n,k] sized samples of z to [b,n,p] sized images\"\"\"\n", + " b, n, k = zs.size()\n", + " ... # YOUR CODE HERE. Analogous to conv_ae.decode(). Hint: requires zs.reshape() or zs.view() since nn.Linear expects (?, k) size inputs\n", + "\n", + " def forward(self, x):\n", + " # VAE.forward() is not used for training, but we'll treat it like a\n", + " # classic autoencoder by taking a single sample of z ~ q\n", + " phi = self.infer(x)\n", + " zs = rsample(phi, 1)\n", + " return self.generate(zs).view(x.size())\n", + "\n", + " def elbo(self, x, n=1):\n", + " \"\"\"Run input end to end through the VAE and compute the ELBO using n\n", + " samples of z\n", + " \"\"\"\n", + " phi = self.infer(x)\n", + " zs = rsample(phi, n)\n", + " mu_xs = self.generate(zs)\n", + " return log_p_x(x, mu_xs, self.log_sig_x.exp()) - kl_q_p(zs, phi)\n", + "\n", + "\n", + "def train_vae(vae, dataset, epochs=10, n_samples=16):\n", + " opt = torch.optim.Adam(vae.parameters(), lr=0.001, weight_decay=1e-6)\n", + " elbo_vals = []\n", + " vae.to(DEVICE)\n", + " vae.train()\n", + " loader = DataLoader(dataset, batch_size=100, shuffle=True, pin_memory=True)\n", + " for epoch in trange(epochs, desc=\"Epochs\"):\n", + " for im, _ in tqdm(\n", + " loader, total=len(dataset) // 100, desc=\"Batches\", leave=False\n", + " ):\n", + " im = im.to(DEVICE)\n", + " opt.zero_grad()\n", + " ####################################################################\n", + " # Fill in all missing code below (...),\n", + " # then remove or comment the line below to test your function\n", + " raise NotImplementedError(\"Please complete the train_vae function!\")\n", + " ####################################################################\n", + " loss = ... # YOUR CODE HERE (hint: use vae.elbo())\n", + " loss.backward()\n", + " opt.step()\n", + "\n", + " elbo_vals.append(-loss.item())\n", + " vae.to(\"cpu\")\n", + " vae.eval()\n", + " return elbo_vals\n", + "\n", + "\n", + "# Uncomment to train\n", + "# vae = ConvVAE(K=K)\n", + "# elbo_vals = train_vae(vae, my_dataset, n_samples=10)\n", + "\n", + "# print(f'Learned sigma_x is {torch.exp(vae.log_sig_x)}')\n", + "\n", + "# plt.figure()\n", + "# plt.plot(elbo_vals)\n", + "# plt.xlabel('Batch #')\n", + "# plt.ylabel('ELBO')\n", + "# plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_b-uEhPf3LSb" + }, + "source": [ + "## We can generate new images!\n", + "\n", + "Remember that earlier we tried sampling $\\mathbf{z} \\sim p(\\mathbf{z})$ and passing those through the `conv_ae.decode` function, and the results were ugly. The original autoencoder was never designed to work purely as a generative model.\n", + "\n", + "Although we didn't go into details of the derivation (see Appendix A), VAEs and the ELBO objective come from applying the logic of generative models and maximum likelihood learning to autoencoders. So: do generated images now look like plausible \"new images\" or samples from the distribution of training images?\n", + "\n", + "You can re-run this cell multiple times to see more examples." + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 359 }, + "id": "iXRy9D6e3Vu3", + "outputId": "f6c72d1a-bb1a-4c8b-d62b-cc4935bef35d" + }, + "outputs": [ { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "id": "h-74e-ruJZRc" - }, - "source": [ - "## Quiz Question 2\n", - "\n", - "What do you notice about the \"interpolated\" images, especially around $t \\approx 1/2$? How many distinct classes do you see in the bottom row?\n", - "Re-run the above cell a few times to look at multiple examples." + "data": { + "image/png": "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", + "text/plain": [ + "
" ] + }, + "metadata": { + "image/png": { + "height": 475, + "width": 474 + } + }, + "output_type": "display_data" + } + ], + "source": [ + "zs = torch.randn(1, 25, K)\n", + "vae_images = vae.generate(zs).reshape((25,) + my_dataset_size)\n", + "\n", + "plt.figure(figsize=(5,5))\n", + "for i in range(25):\n", + " plt.subplot(5,5,i+1)\n", + " plot_torch_image(vae_images[i])\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "myaU0gjj46N7" + }, + "source": [ + "These won't be perfect, but hopefully they look a lot more like plausible \"new\" images!\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 518 }, + "id": "i_aH2ts-3sQO", + "outputId": "fba76ab0-246e-4e65-f5cf-7a797c2106cb" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "id": "a8ZsxDhYJRdE" - }, - "outputs": [], - "source": [ - "interp_observations = \"\" #@param{type:'string'}" - ] + "name": "stdout", + "output_type": "stream", + "text": [ + "Video available at https://youtube.com/watch?v=IDTq8muSySQ\n" + ] }, { - "cell_type": "code", - "execution_count": 28, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 316 - }, - "id": "S_NGi5P11Dj5", - "outputId": "3ad05528-0ea8-4f6a-f395-d7dc10ee7e87" - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 406, - "width": 1377 - } - }, - "output_type": "display_data" - } + "data": { + "image/jpeg": "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", + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "idx1 = torch.randint(len(my_dataset), size=())\n", - "idx2 = torch.randint(len(my_dataset), size=())\n", - "x1, _ = my_dataset[idx1]\n", - "x2, _ = my_dataset[idx2]\n", - "n_interp = 11\n", - "\n", - "with torch.no_grad():\n", - " h1_lin = lin_ae.encode(x1.reshape(1, -1))\n", - " h2_lin = lin_ae.encode(x2.reshape(1, -1))\n", - " h1_conv = conv_ae.encode(x1.unsqueeze(0))\n", - " h2_conv = conv_ae.encode(x2.unsqueeze(0))\n", - "\n", - "plt.figure(figsize=(14, 4.5))\n", - "for i in range(n_interp):\n", - " t = i / (n_interp - 1)\n", - " pixel_interp = (1 - t) * x1 + t * x2\n", - " plt.subplot(3, n_interp, i + 1)\n", - " plot_torch_image(pixel_interp)\n", - " if i == 0:\n", - " plt.ylabel(\"Raw\\nPixels\")\n", - " plt.title(f\"t={i}/{n_interp-1}\")\n", - "\n", - " with torch.no_grad():\n", - " lin_ae_interp = lin_ae.decode((1 - t) * h1_lin + t * h2_lin)\n", - " plt.subplot(3, n_interp, i + 1 + n_interp)\n", - " plot_torch_image(lin_ae_interp.reshape(my_dataset_size))\n", - " if i == 0:\n", - " plt.ylabel(\"Lin AE\")\n", - "\n", - " with torch.no_grad():\n", - " conv_ae_interp = conv_ae.decode((1 - t) * h1_conv + t * h2_conv)[0]\n", - " plt.subplot(3, n_interp, i + 1 + 2 * n_interp)\n", - " plot_torch_image(conv_ae_interp)\n", - " if i == 0:\n", - " plt.ylabel(\"NonLin AE\")\n", - "plt.show()\n" + "text/plain": [ + "" ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#@title Video: Wrapping up and interesting VAE examples\n", + "\n", + "video = YouTubeVideo(id=\"IDTq8muSySQ\", width=854, height=480, fs=1)\n", + "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", + "\n", + "video" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "P5-HZSWcCbr3" + }, + "source": [ + "---\n", + "# Submit responses" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 421 }, + "id": "FCJJf7OFk8SU", + "outputId": "828b9a4c-6a0a-4f7f-8319-cb9626f8bee5" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "RP_0Hcyflj3w" - }, - "source": [ - "---\n", - "# Section 3: Generative models and density networks\n", - "\n" + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import time\n", + "import numpy as np\n", + "from IPython.display import IFrame\n", + "#@markdown #Run Cell to Show Airtable Form\n", + "#@markdown Confirm your answers and then click \"Submit\". \n", + "# If you're having issues, use this link and manually fill in your answers: https://airtable.com/shrh6lPiM4PlflEzj\n", + "\n", + "def prefill_form(src, fields: dict):\n", + " '''\n", + " src: the original src url to embed the form\n", + " fields: a dictionary of field:value pairs,\n", + " e.g. {\"pennkey\": my_pennkey, \"location\": my_location}\n", + " '''\n", + " prefills = \"&\".join([\"prefill_%s=%s\"%(key, fields[key]) for key in fields])\n", + " src = src + prefills\n", + " src = \"+\".join(src.split(\" \"))\n", + " return src\n", + "\n", + "#autofill time if it is not present\n", + "try: t0;\n", + "except NameError: t0 = time.time()\n", + "try: t1;\n", + "except NameError: t1 = time.time()\n", + "\n", + "#autofill fields if they are not present\n", + "#a missing pennkey and pod will result in an Airtable warning\n", + "#which is easily fixed user-side.\n", + "try: my_pennkey;\n", + "except NameError: my_pennkey = \"\"\n", + "\n", + "try: my_pod;\n", + "except NameError: my_pod = \"Select\"\n", + "\n", + "try: my_email;\n", + "except NameError: my_email = \"\"\n", + "\n", + "try: linear_ae_vs_pca;\n", + "except NameError: linear_ae_vs_pca = \"\"\n", + "\n", + "try: interp_observations;\n", + "except NameError: interp_observations = \"\"\n", + "\n", + "times = np.array([t1])-t0\n", + "\n", + "fields = {\"pennkey\": my_pennkey,\n", + " \"pod\": my_pod,\n", + " \"tutorial\": tutorial,\n", + " \"email\": my_email,\n", + " \"linear_ae_vs_pca\": linear_ae_vs_pca,\n", + " \"interp_observations\": interp_observations,\n", + " \"cumulative_times\": times}\n", + "\n", + "src = \"https://airtable.com/embed/shrh6lPiM4PlflEzj?\"\n", + "\n", + "#now instead of the original source url, we do: src = prefill_form(src, fields)\n", + "display(IFrame(src = prefill_form(src, fields), width = 800, height = 400))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "HKn5d3CCC05w" + }, + "source": [ + "## Feedback\n", + "How could this session have been better? How happy are you in your group? How do you feel right now?\n", + "\n", + "Feel free to use the embeded form below or use this link:\n", + "https://airtable.com/shr1TzujOOOY21kFQ" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "cellView": "form", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 421 }, + "id": "HIvhG6VZ8zez", + "outputId": "66162276-6279-493a-ee7c-dad77edc0afc" + }, + "outputs": [ { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "rjpZAX0mrUg_", - "outputId": "dc3f7808-89ed-4fd1-d7a8-a4a945add2c1" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=h96JaT5Jyi4\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } + "data": { + "text/html": [ + "\n", + " \n", + " " ], - "source": [ - "#@title Video: Generating with Gaussians\n", - "\n", - "try: t3;\n", - "except NameError: t3=time.time()\n", - "\n", - "video = YouTubeVideo(id=\"h96JaT5Jyi4\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] - }, - { - "cell_type": "markdown", - "metadata": { - "id": "-7PBmLooLeds" - }, - "source": [ - "## Generating novel images from the decoder\n", - "\n", - "If we isolate the decoder part of the AutoEncoder, what we have is a neural network that takes as input a vector of size $K$ and produces as output an image that looks something like our training data. Recall that in our earlier notation, we had an input $\\mathbf{x}$ that was mapped to a low-dimensional hidden representation $\\mathbf{h}$ which was then decoded into a reconstruction of the input, $\\mathbf{x'}$:\n", - "$$\\mathbf{x} \\overset{\\text{encode}}{\\longrightarrow} \\mathbf{h} \\overset{\\text{decode}}{\\longrightarrow} \\mathbf{x'}\\, .$$\n", - "Partly as a matter of convention, and partly to distinguish where we are going next from the previous section, we're going to introduce a new variable, $\\mathbf{z} \\in \\mathbb{R}^K$, which will take the place of $\\mathbf{h}$. The key difference is that while $\\mathbf{h}$ is produced by the encoder for a particular $\\mathbf{x}$, $\\mathbf{z}$ will be drawn out of thin air from a prior of our choosing:\n", - "$$\\mathbf{z} \\sim p(\\mathbf{z})\\\\ \\mathbf{z} \\overset{\\text{decode}}{\\longrightarrow} \\mathbf{x}\\, .$$\n", - "(Note that it is also conventional to drop the \"prime\" on $\\mathbf{x}$ when it is no longer being thought of as a \"reconstruction\")." + "text/plain": [ + "" ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# @title Feedback form\n", + "display(IFrame(src=\"https://airtable.com/embed/shr1TzujOOOY21kFQ\", width = 800, height = 400))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "3yqyggnJTFsv" + }, + "source": [ + "---\n", + "# Appendices" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_eIXWPrUa68q" + }, + "source": [ + "## Appendix A: Formalizing the problem and deriving the ELBO\n", + "\n", + "### Part A.1: maximum likelihood with neural networks\n", + "\n", + "Let's state clearly the goal of learning a density network:\n", + "\n", + "__Given:__\n", + "\n", + "1. A latent space $\\mathbf{z} \\in \\mathbb{R}^K$ with prior $p(\\mathbf{z})$\n", + "2. Data points, $\\lbrace{\\mathbf{x}_1, \\mathbf{x}_2, \\ldots, \\mathbf{x}_N\\rbrace}$ that live in $\\mathbb{R}^P$ drawn (iid) from some unknown distribution $p_{true}(\\mathbf{x})$ for instance, a set of training images sampled from the world, where $P$ is the number of pixels $\\times$ color channels per image (e.g. $P=1\\times 28 \\times 28 = 784$ for MNIST, and $P=3\\times 32 \\times 32 = 3072$ for CIFAR).\n", + "3. A differentiable function (a neural network, say) with parameters $\\mathbf{w}$ that maps from $\\mathbb{R}^K$ to $\\mathbb{R}^P$, $$\\mathbf{x} = f(\\mathbf{z};\\mathbf{w}) \\, .^\\dagger$$ The decoder part of the AutoEncoder is an example of such an $f$.\n", + "4. A \"noise model\" on $\\mathbf{x}$. Often this is simply chosen to be independent Gaussian pixel noise with $f(\\mathbf{z};\\mathbf{w})$ as the mean: $$p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) = \\mathcal{N}\\left(f(\\mathbf{z};\\mathbf{w}), \\sigma^2_x\\mathbf{I}_P\\right)$$\n", + "where $\\mathbf{I}_P$ is the $P\\times P$ identity matrix and is used to express the assumption that noise is independent across pixels.$^*$\n", + "\n", + "Given all of this, a density network defines a distribution on $\\mathbf{x}$:\n", + "$$p(\\mathbf{x};\\mathbf{w}) \\equiv \\int p(\\mathbf{z}) p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) \\, {\\rm d}\\mathbf{z} \\, .$$\n", + "\n", + "Now, we can succinctly state that the __goal__ of learning a density network is to minimize the KL divergence from $p(\\mathbf{x};\\mathbf{w})$ to $p_{true}(\\mathbf{x})$, or equivalently, to maximize the likelihood\n", + "$$\\mathbf{w}^* = \\arg\\max_\\mathbf{w} \\sum_{i=1}^N \\log p(\\mathbf{x}_i;\\mathbf{w}) \\, .$$\n", + "\n", + "But this is hard to do and requires approximations, which leads us to the ELBO.\n", + "\n", + "---\n", + "\n", + "### Part A.2: ELBO Derivation\n", + "\n", + "The goal of training a density net is to maximize the (log) likelihood of points in the training set, or\n", + "$$\\sum_{i=1}^N \\log p(\\mathbf{x}_i;\\mathbf{w}) \\, .$$\n", + "\n", + "We already know all about minimizing sums of losses (e.g. minibatching and SGD), so let's focus on the loss for a single data point, $\\log p(\\mathbf{x}_i;\\mathbf{w})$. With a bit of algebraic sleight of hand, we can pull out a $\\mathbf{z}$ and start turning this into something more tractable$^\\#$:\n", + "$$\\log p(\\mathbf{x}_i) = \\log \\left[ p(\\mathbf{x}_i) \\frac{p(\\mathbf{z}|\\mathbf{x}_i)}{p(\\mathbf{z}|\\mathbf{x}_i)} \\right]\\qquad\\text{for all $\\mathbf{z}$}$$\n", + "This step introduced a $\\mathbf{z}$ out of nowhere. Since we are effectively multiplying and dividing by $1$, this holds no matter what $\\mathbf{z}$ we plug in (we'll just ignore the possibility that $p(\\mathbf{z}|\\mathbf{x}_i)=0$). Next, we'll introduce a brand new auxiliary distribution, $q(\\mathbf{z})$, and integrate it:\n", + " $$\\ldots = \\int q(\\mathbf{z}) \\log \\left[ p(\\mathbf{x}_i) \\frac{p(\\mathbf{z}|\\mathbf{x}_i)}{p(\\mathbf{z}|\\mathbf{x}_i)} \\right] {\\rm d} \\mathbf{z}$$\n", + "This step initially seems odd: do we really get to pick _any_ $q(\\mathbf{z})$ here? It works because we took an expression that was true _for all $\\mathbf{z}$_, i.e. a constant function of $\\mathbf{z}$, and integrated it with an arbitrary distribution on $\\mathbf{z}$, which by definition has to integrate to its constant integrand. \n", + "\n", + "Next, we'll sneak $q$ inside the $\\log$ using the same trick that got $p(\\mathbf{z}|\\mathbf{x}_i)$ in there, and we'll combine $p(\\mathbf{z}|\\mathbf{x}_i)p(\\mathbf{x}_i)$ into a single $p(\\mathbf{x}_i,\\mathbf{z})$:\n", + " $$\\ldots = \\int q(\\mathbf{z}) \\log \\left[ \\frac{p(\\mathbf{x}_i,\\mathbf{z})}{p(\\mathbf{z}|\\mathbf{x}_i)}\\frac{q(\\mathbf{z})}{q(\\mathbf{z})} \\right] {\\rm d} \\mathbf{z}$$\n", + "If you are beginning to think that this looks a bit like KL-divergence, then you would be right! Let's complete the transformation by pulling out $KL$:\n", + "$$\\log p(\\mathbf{x}_i) = KL\\left(q(\\mathbf{z})||p(\\mathbf{z}|\\mathbf{x}_i)\\right) + \\underbrace{\\int q(\\mathbf{z}) \\log \\left[ \\frac{p(\\mathbf{x}_i,\\mathbf{z})}{q(\\mathbf{z})} \\right] {\\rm d} \\mathbf{z}}_\\text{ELBO}$$\n", + "\n", + "Re-arranging, notice that\n", + "$$\\text{ELBO} = \\log p(\\mathbf{x}_i) - KL\\left(q(\\mathbf{z})||p(\\mathbf{z}|\\mathbf{x}_i)\\right) \\, .$$\n", + "We can get a lot of intuition out of this one expression. First, maximizing the ELBO has two effects, since there are two terms on the right hand side. The first effect is to make $KL(q(z)||p(z|x))$ smaller, which means that by maximizing the ELBO, $q$ becomes a better approximation to the true posterior distribution over $z$. If $q$ were a _perfect fit_, that is if $q(z) = p(z|x)$, then maximizing the ELBO would be _equivalent_ to maximizing the thing we set out to maximize: the log likelihood of the data. Put another way: once $q$ is a good approximation to the posterior $p(z|x)$, then maximizing the ELBO makes $p(x|z)$ a better _generative_ model.\n", + "\n", + "The ELBO gets its name because it is a **Lower BOund** on the **Evidence**. \"Evidence\" is just another term for the log likelihood, or $\\log p(\\mathbf{x}_i)$. We know that it is a lower bound beause $KL$ is always non-negative. This one formula is the work-horse of nearly all variational inference:\n", + "$$\\color{red}{\\log p(\\mathbf{x}_i) \\geq \\underbrace{\\int q(\\mathbf{z}) \\log \\left[ \\frac{p(\\mathbf{x}_i,\\mathbf{z})}{q(\\mathbf{z})} \\right] {\\rm d} \\mathbf{z}}_\\text{ELBO}}$$\n", + "\n", + "\n", + "\n", + "Note that other texts often derive the ELBO in fewer steps using Jensen's inequality, but arguably some of the clarity and cleverness of the whole idea is lost when done that way. Here, we see behind the curtain a bit more: we see that $q(\\mathbf{z})$ was introduced as a totally arbitrary distribution, but that we do \"better\" by making it agree more closely with $p(\\mathbf{z}|\\mathbf{x};\\mathbf{w})$. We also see where the \"Lower BOund\" comes from: the ELBO is always a lower bound on $\\log p(\\mathbf{x}_i; \\mathbf{w})$ precisely because $KL(q(\\mathbf{z})||p(\\mathbf{z}|\\mathbf{x}_i;\\mathbf{w}))$ is always positive. In fact, this tells us that the ELBO is **equal** to the log likelihood of the data (the bound is \"tight\") when $q(\\mathbf{z})$ is equal to the correct posterior on $\\mathbf{z}$, i.e. when $q(\\mathbf{z}) = p(\\mathbf{z}|\\mathbf{x}_i)$. This means we can think about the problem of creating \"tighter bounds\" as a problem of making $q(\\mathbf{z})$ closer to $p(\\mathbf{z}|\\mathbf{x}_i)$.\n", + "\n", + "---\n", + "\n", + "$^\\dagger$ A notational convention is that $p(a|b)$ is used when $a$ and $b$ are both random variables and $a$ is \"conditioned on\" $b$, while $p(a;c)$ is used when $c$ is not a random variable, but a parameter controlling the shape of the distribution. This is sometimes written $p_c(a)$.\n", + "\n", + "$^*$ In practice, we don't explicitly use $\\mathbf{I}_P$. The assumption that pixel noise is independent instead appears as a sum of log-likelihoods per pixel.\n", + "\n", + "$^\\#$ these derivations drop the \"$\\mathbf{w}$\" from all $p$s just to reduce clutter." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "jDXSWpZoqlxb" + }, + "source": [ + "## Appendix B: Tricks\n", + "\n", + "There are a few \"tricks\" behind VAEs in particular had a big impact on the field, and in this lesson we haven't dived into all of the interesting and non-obvious details.\n", + "\n", + "1. The first \"trick\" was to recognize that the ELBO contains a \"reconstruction\" term and a \"regularization\" term, and that this naturally maps onto a kind of regularized auto-encoder. The original VAE paper is \"Auto-Encoding Variational Bayes\" because Variational Bayes and the ELBO had existed previously, but this was the first time it was built end-to-end with neural networks.\n", + "\n", + "2. The second \"trick\" we introduced above without talking about it is the __reparameterization trick__. When we computed the ELBO, we simply called\n", + "\n", + " zs = rsample(phi, n)\n", + " elbo = log_p_x(...) - kl_q_p(...)\n", + "\n", + " where each `...` depended on the sampled `zs`. Something sneaky is happening inside `rsample` which allows us to use Monte Carlo estimates of $\\mathbb{E}_{q(\\mathbf{z};\\phi)}[\\ldots]$ (as in the ELBO) but then take gradients of all of it with respect to $\\phi$. Inside the `torch.distributions` package, you'll find both `sample` and `rsample` functions. The key difference is that you can take gradients through `rsample` but not through `sample`. Magic! (The \"r\" in \"rsample\" stands for \"reparameterized sample\".)\n", + "\n", + " For some extra history, before this simple trick came along, people generally thought of taking gradients with respect to $\\phi$ in this kind of example as a hard problem. Keyword to search: score function estimators. Or see [here](http://blog.shakirm.com/2015/10/machine-learning-trick-of-the-day-4-reparameterisation-tricks/) and [here](http://blog.shakirm.com/2015/11/machine-learning-trick-of-the-day-5-log-derivative-trick/) for some blog posts on the topic.\n", + "\n", + "3. The third \"trick\" was when we stopped taking gradients of $\\phi$ directly and instead used a __recognition model__ to map from $\\mathbf{x}$ to $\\phi$. This trick is also called \"amortized inference\" since the recognition model learns _on average_ to produce an estimate of $\\phi$ for each $\\mathbf{x}$." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ILEgdYHaeRK-" + }, + "source": [ + "## Appendix C: fraction of variance, eigenspectra, and selecting $K$\n", + "\n", + "**tl;dr** one heuristic for choosing $K$ is to look at how much of the total variance in the data lies in the first $K$ principal components. But despite comparable variance-vs-K curves, you'll find that MNIST digits are legible with $K \\approx 15$ while CIFAR images are unrecognizable until about $K \\approx 80$. Reality is more complicated than percent variance explained!" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "4g9HMk2Qw3_g" + }, + "source": [ + "Let's pause to think about our choice of the dimensionality of the bottleneck layer, $\\mathbf{h}\\in\\mathbb{R}^K$. Dimensionality reduction by PCA works by projecting images onto the eigenvectors of the pixel covariance that have the largest eigenvalues. These eigenvalues, in turn, represent the amount of variance in the data along each of those vectors. So, we can visualize a rough, *linear* estimate of the intrinsic dimensionality of our datset by looking at its *eigenspectrum*.\n", + "\n", + "Imagine we have a 3-dimensional dataset, and the eigenvalues of the covariance are, in descending order, $[3, 2, 1]$. Then the total variance would be $3+2+1=6$, and we would say that the first principal component accounts for $3/6=50\\%$ of the total variance, while the first $K=2$ principal components account for a total of $(3+2)/6=83.3\\%$ of the total variance.\n", + "\n", + "MNIST is $28\\times 28 = 784$-dimensional, and CIFAR is $32\\times 32\\times 3=3072$-dimensional. The following plot estimates the _fraction_ of that variance distributed across the first $K$ modes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 430 }, + "id": "8llUJ9kkfKdX", + "outputId": "fc730ae6-b7df-42a0-dda4-ecf138e44d78" + }, + "outputs": [ { - "cell_type": "markdown", - "metadata": { - "id": "dc0GemsWQYds" - }, - "source": [ - "## Exercise 3\n", - "###Sample $\\mathbf{z}$ from a standard normal and visualize the images produced" + "data": { + "image/png": "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", + "text/plain": [ + "
" ] - }, - { - "cell_type": "code", - "execution_count": 29, - "metadata": { - "id": "SYBmyD1JQjoE" + }, + "metadata": { + "image/png": { + "height": 413, + "width": 558 }, - "outputs": [], - "source": [ - "def generate_images(autoencoder, K, n_images=1):\n", - " \"\"\"Generate n_images 'new' images from the decoder part of the given\n", - " autoencoder.\n", - "\n", - " returns (n_images, channels, height, width) tensor of images\n", - " \"\"\"\n", - " # Concatenate tuples to get (n_images, channels, height, width)\n", - " output_shape = (n_images,) + my_dataset_size\n", - " with torch.no_grad():\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your function\n", - " raise NotImplementedError(\"Please complete the generate_images function!\")\n", - " ####################################################################\n", - " ... # Your code here: sample z, pass through autoencoder.decode(), and reshape output.\n", - "\n", - "\n", - "# Uncomment to run it\n", - "# images = generate_images(conv_ae, K, n_images=25)\n", - "# plt.figure(figsize=(5,5))\n", - "# for i in range(25):\n", - "# plt.subplot(5,5,i+1)\n", - "# plot_torch_image(images[i])\n", - "# plt.show()\n" - ] + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "def plot_fraction_variance_eigenspectrum(cov, max_K=200, annotate_K=None, ax=None):\n", + " ax = plt.gca() if ax is None else ax\n", + " _, s, _ = torch.svd_lowrank(cov, q=max_K)\n", + " rank = torch.arange(max_K+1)\n", + " total_variance = cov.diag().sum()\n", + " frac_variance = torch.cat([torch.zeros((1,)), torch.cumsum(s, dim=0) / total_variance])\n", + " line = ax.plot(rank[:max_K], frac_variance[:max_K])\n", + " if annotate_K is not None:\n", + " y = frac_variance[K]\n", + " ax.plot([K, K], [0, y], '-r')\n", + " ax.plot([0, K], [y, y], '-r')\n", + " ax.text(x=K+.5, y=y-.03, s=f'{100*y:.1f}% at K={K}')\n", + " return line\n", + "\n", + "plot_fraction_variance_eigenspectrum(cov, annotate_K=K)\n", + "plt.ylim([0., 1.])\n", + "plt.grid()\n", + "plt.xlabel('number of hidden dimensions (K)')\n", + "plt.ylabel('fraction of variance accounted for')\n", + "plt.title(f'% variance in top K dimensions for {my_dataset_name}')\n", + "plt.show()" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [ + "VVCR7EVyFkWS" + ], + "machine_shape": "hm", + "name": "CIS_522_W8D1_Tutorial_–_TA_Version.ipynb", + "provenance": [], + "toc_visible": true + }, + "kernel": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "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": "3.9.1" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "01ce56b63fd84c5eb054d3756df55322": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_c121d101a456463285a86a5d55373e43", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_551623ea5966495a8377a4b05a5aef12", + "value": 600 + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "s-kMt6-ul1iM" - }, - "source": [ - "## Formalizing the problem: density estimation with maximum likelihood\n", - "\n" - ] + "029331ef8bd64b27a6c5385ce3e0f4b4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "1al9VdfYRkt9", - "outputId": "637eb960-b069-43ff-b3e3-5aef49b75636" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=rx3IlM4qnvw\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#@title Video: Density Networks\n", - "\n", - "video = YouTubeVideo(id=\"rx3IlM4qnvw\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] + "04e9719240b14b3385c8cf2334fdcbe2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b1e189b199bc490eafc7eb2ecc1daaf5", + "placeholder": "​", + "style": "IPY_MODEL_2ba5313ece19405daadd3a3a4d5734a3", + "value": "Batches: 100%" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "MqQIy5H7Ud61" - }, - "source": [ - "Note: we've moved the technical details of \"formalizing the problem\" to Appendix A.1 at the end of this notebook. Those who want more of the theoretical/mathematical backstory are encouraged to read it. Those who just want to build a VAE, carry on!" - ] + "059f7a541366419b8da3b7bac5a482dd": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "pRp1gFniPT7B" - }, - "source": [ - "---\n", - "# Section 4: Variational Auto-Encoders (VAEs)" - ] + "0661ed223ab04813b9648f4bb65c2d06": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "S8jinOmeTT3v", - "outputId": "e8a771de-8ac5-4368-d8cd-08e929c02da5" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=RgOF3XJL5vw\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } + "06a120793142465fbd3b12cab677cc09": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_35bb8a89785648afa099763e8703d4a8", + "placeholder": "​", + "style": "IPY_MODEL_527a4fdd54cc445c9a8922dc9006bf4b", + "value": "Batches: 100%" + } + }, + "08bba96f8f9d4737a949725883a92671": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "0a068f4e30b8480aa1a71db83f15d638": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_fe9ae7dcf5184f49b9c962101ba67d91", + "placeholder": "​", + "style": "IPY_MODEL_205536ba56b9456ab9fa114825753a24", + "value": "Batches: 100%" + } + }, + "0aaadb652a6341f7ae4b6d0e1c8ac66f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_04e9719240b14b3385c8cf2334fdcbe2", + "IPY_MODEL_63b7bbe958834089988377ef880e1818", + "IPY_MODEL_569c655751824fc59b479f2e4e27e118" ], - "source": [ - "#@title Video: VAE Samples\n", - "\n", - "try: t4;\n", - "except NameError: t4=time.time()\n", - "\n", - "video = YouTubeVideo(id=\"RgOF3XJL5vw\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] + "layout": "IPY_MODEL_890252af17464d64ae0c21ec804bc223" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "IgROsfdxDbuX" - }, - "source": [ - "## Components of a VAE\n", - "## Recognition models and density networks\n", - "\n", - "Variational AutoEncoders (VAEs) are a lot like the classic AutoEncoders (AEs) you just saw, but where we explicitly think about probability distributions. In the language of VAEs, the __encoder__ is replaced with a __recognition model__, and the __decoder__ is replaced with a __density network__.\n", - "\n", - "Where in a classic autoencoder the encoder maps from images to a single hidden vector,\n", - "$$\\mathbf{x} \\overset{\\text{AE}}{\\longrightarrow} \\mathbf{h} \\, , $$ in a VAE we would say that a recognition model maps from inputs to entire __distributions__ over hidden vectors,\n", - "$$\\mathbf{x} \\overset{\\text{VAE}}{\\longrightarrow} q(\\mathbf{z}) \\, ,$$\n", - "which we will then sample from.\n", - "We'll say more in a moment about what kind of distribution $q(\\mathbf{z})$ is.\n", - "Part of what makes VAEs work is that the loss function will require good reconstructions of the input not just for a single $\\mathbf{z}$, but _on average_ from samples of $\\mathbf{z} \\sim q(\\mathbf{z})$.\n", - "\n", - "In the classic autoencoder, we had a decoder which maps from hidden vectors to reconstructions of the input:\n", - "$$\\mathbf{h} \\overset{\\text{AE}}{\\longrightarrow} \\mathbf{x'} \\, .$$\n", - "In a density network, reconstructions are expressed in terms of a distribution:\n", - "$$\\mathbf{z} \\overset{\\text{VAE}}{\\longrightarrow} p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) $$\n", - "where, as above, $p(\\mathbf{x}|\\mathbf{z};\\mathbf{w})$ is defined by mapping $\\mathbf{z}$ through a density network then treating the resulting $f(\\mathbf{z};\\mathbf{w})$ as the mean of a (Gaussian) distribution over $\\mathbf{x}$." - ] + "0b54f345ec964ecb9cf15bd5b8ccc746": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "svLx5HwJKhdZ" - }, - "source": [ - "## Exercise 4\n", - "### Sampling from $q(\\mathbf{z})$\n", - "\n", - "How can a neural network (the __recognition model__) output an entire probability distribution $$\\mathbf{x} \\longrightarrow q(\\mathbf{z}) \\, ?$$\n", - "One idea would be to make the weights of the neural network stochastic, so that every time the network is run, a different $\\mathbf{z}$ is produced. (In fact, this is quite common in [Bayesian Neural Networks](https://medium.com/neuralspace/bayesian-neural-network-series-post-1-need-for-bayesian-networks-e209e66b70b2), but this isn't what people use in VAEs.)\n", - "\n", - "Instead, we will start by committing to a particular _family_ of distributions. We'll then have the recognition model output the _parameters_ of $q$, which we'll call $\\phi$. A common choice, which we will use throughout, is the family of isotropic multivariate Gaussians$^\\dagger$:\n", - "$$q(\\mathbf{z};\\phi) = \\mathcal{N}(\\mathbf{z};\\boldsymbol{\\mu},\\sigma^2\\mathbf{I}_K) = \\prod_{k=1}^K \\mathcal{N}(z_k; \\mu_k, \\sigma^2)$$\n", - "where the $K+1$ parameters are$^*$\n", - "$$\\phi = \\lbrace{\\mu_1, \\mu_2, \\ldots, \\mu_K, \\log(\\sigma)}\\rbrace \\, .$$\n", - "By defining the last entry of $\\phi$ as the _logarithm_ of $\\sigma$, the last entry can be any real number while enforcing the requirement that $\\sigma > 0$.\n", - "\n", - "A recognition model is a neural network that takes $\\mathbf{x}$ as input and produces $\\phi$ as output. The purpose of the following exercise is not to write a recognition model (that will come later), but to clarify the relationship between $\\phi$ and $q(\\mathbf{z})$. You will write a function, `rsample`, which takes as input a batch $\\phi$s and will output a set of samples of $\\mathbf{z}$ drawn from $q(\\mathbf{z};\\phi)$." - ] + "0bc4e7bf12e041598fea2dd433ddb6f2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_4dba7c97bf8045bbbfaf0767ac27120f", + "IPY_MODEL_39ec691122e94b0bad070ea86d8391ca", + "IPY_MODEL_cced2bb02ef74f6283ea2ed19ed83f43" + ], + "layout": "IPY_MODEL_ccf2b5165b494751bdf71b54b9cc66fb" + } }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": { - "id": "0ReQnZaDT2i4" - }, - "outputs": [], - "source": [ - "def rsample(phi, n_samples):\n", - " \"\"\"Sample z ~ q(z;phi)\n", - " Ouput z is size [b,n_samples,K] given phi with shape [b,K+1]. The first K\n", - " entries of each row of phi are the mean of q, and phi[:,-1] is the log\n", - " standard deviation\n", - " \"\"\"\n", - " b, kplus1 = phi.size()\n", - " k = kplus1 - 1\n", - " mu, sig = phi[:, :-1], phi[:, -1].exp()\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your function\n", - " raise NotImplementedError(\"Please complete the rsample function!\")\n", - " ####################################################################\n", - " ... # your code here!\n" - ] + "0be5d717250d4ac9ae9212cb5abce1cb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_4f5e66ca82e7467d90d745730dc4a094", + "placeholder": "​", + "style": "IPY_MODEL_96d7c667d4264043b8bdc10cc5e211a2", + "value": " 598/600 [00:24<00:00, 24.27it/s]" + } }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 227 - }, - "id": "5ebTNwLKUFHY", - "outputId": "67ba1fe6-a40e-45e2-d207-75161d9e23b8" - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n", - "findfont: Font family 'xkcd' not found.\n", - "findfont: Font family 'xkcd Script' not found.\n", - "findfont: Font family 'Humor Sans' not found.\n", - "findfont: Font family 'Comic Neue' not found.\n", - "findfont: Font family 'Comic Sans MS' not found.\n" - ] - }, - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 293, - "width": 1166 - } - }, - "output_type": "display_data" - } + "0d7f6e08f26c4b6abd8ccee2ec192ac6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "0ed1ed13153041109c3e4d172581cab8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_9d5c9161fe064cf9baf5dc0b6a8d7890", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_b41a6b9583f3436a9701983187e7a923", + "value": 600 + } + }, + "0ff62aa332e94a4381f78edf90fcb014": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "133816fc0030431c956f341668c47169": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_80e9fec5ea3449a3a6cc6b75a1771eaa", + "IPY_MODEL_5959b45ae4dd426382e216012ea1d126", + "IPY_MODEL_c18de5d78e7b41949d6956bd87bff700" ], - "source": [ - "# Testing rsample()\n", - "phi = torch.randn(4, 3, device=DEVICE)\n", - "zs = rsample(phi, 100)\n", - "assert zs.size() == (4, 100, 2), \"rsample size is incorrect!\"\n", - "assert zs.device == phi.device, \"rsample device doesn't match phi device!\"\n", - "zs = zs.cpu()\n", - "\n", - "with plt.xkcd():\n", - " plt.figure(figsize=(12, 3))\n", - " for i in range(4):\n", - " plt.subplot(1, 4, i + 1)\n", - " plt.scatter(zs[i, :, 0], zs[i, :, 1], marker=\".\")\n", - " th = torch.linspace(0, 6.28318, 100)\n", - " x, y = torch.cos(th), torch.sin(th)\n", - " # Draw 2-sigma contours\n", - " plt.plot(\n", - " 2 * x * phi[i, 2].exp().item() + phi[i, 0].item(),\n", - " 2 * y * phi[i, 2].exp().item() + phi[i, 1].item(),\n", - " )\n", - " # plt.title(f'mu={phi[i,0].item():.2f},{phi[i,1].item():.2f}, sig={phi[i,2].exp().item():.3f}')\n", - " plt.xlim(-5, 5)\n", - " plt.ylim(-5, 5)\n", - " plt.grid()\n", - " plt.axis(\"equal\")\n", - " plt.suptitle(\n", - " \"If rsample() is correct, then most but not all points should lie in the circles\"\n", - " )\n", - " plt.show()\n" - ] + "layout": "IPY_MODEL_b760230d392f4204b88d998f0c516a98" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "nKZgt0ebP5Pe" - }, - "source": [ - "---\n", - "\n", - "$^\\dagger$ PyTorch has a `MultivariateNormal` class which handles multivariate Gaussian distributions with arbitrary covariance matrices. It is not very beginner-friendly, though, so we will write our own functions to work with $\\phi$, which will both teach you some implementation details and is not very hard especially if we use only an isotropic ($\\sigma$) or diagonal ($\\lbrace{\\sigma_1, \\ldots, \\sigma_K}\\rbrace$) covariance\n", - "\n", - "$^*$ Another common parameterization is to use a separate $\\sigma$ for each dimension of $\\mathbf{z}$, in which case $\\phi$ would instead contain $2K$ parameters:\n", - "$$\\phi = \\lbrace{\\mu_1, \\mu_2, \\ldots, \\mu_K, \\log(\\sigma_1), \\ldots, \\log(\\sigma_K)}\\rbrace \\, .$$" - ] + "147167a175d94e89b91c9e4744c80599": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "LlQfA-aiK_LS" - }, - "source": [ - "## VAE training: maximize the Evidence Lower BOund (ELBO)\n", - "\n", - "\n", - "" - ] + "155141fa19624e508d2f53184fba8931": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_8972fc6d2e8e4e9ea57e7cf2a61b2f01", + "IPY_MODEL_8b4f010e34a44f7bb4bb4587b01aea8b", + "IPY_MODEL_38c277f235854dd8b4f3aca5ca367e91" + ], + "layout": "IPY_MODEL_3ebe6f717c8543a482d4e139ac7e855d" + } }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "r64ZiPHZc7tb", - "outputId": "be7e6811-cb95-41e2-8072-a0e836efc144" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=-99NskgKDo0\n" - ] - }, - { - "data": { - "image/jpeg": "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", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } + "1ab8190bf5114ab89713358df63b2ec2": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "204ccffdfba6474bbd2041c81c17dc45": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "205536ba56b9456ab9fa114825753a24": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "22c8ca666f614b7dbb9ac0fa3f4e095a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a30b5754bc1c49e7a0d6c0cda84a23e9", + "placeholder": "​", + "style": "IPY_MODEL_6067d9f4878e4a7597d7980fb4f57457", + "value": " 1857/1875 [00:10<00:00, 192.86it/s]" + } + }, + "2633a921fcca4d0c90f5827d84f190f4": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "26a194907cc54022ac497a546d04f488": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "29d32c83475c403b9bc384a09781c725": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2a3af2976d7644718b2381a51799b0f3": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2ba5313ece19405daadd3a3a4d5734a3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "2c78fe51f8b74c6aae1d9a4dc5a61d61": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_8e1fe21f6c204ba483df3999bcb48a67", + "IPY_MODEL_61f424d1767044c19cd4aad5ebc13dc6", + "IPY_MODEL_815caee749e74ce6839ab10f7cd74c09" ], - "source": [ - "#@title Video: ELBO\n", - "\n", - "video = YouTubeVideo(id=\"-99NskgKDo0\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] + "layout": "IPY_MODEL_ee3c86fd9cf1443c8a1fe7e4ef5e00b0" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "CiS0Z8ZOetw9" - }, - "source": [ - "A full derivation and further explanation of the ELBO can be found in Appendix A.2 at the end of this notebook. In the following few sections, we provide implementations of `log_p_x` and `kl_q_p` for you, since the technical details of each can be somewhat opaque." - ] + "2f7962d587a648e690982ffe1fc252e8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_74e2292262954ece8066361b76cb299c", + "placeholder": "​", + "style": "IPY_MODEL_37a14ff89dee477b8097c8f167111871", + "value": " 598/600 [00:25<00:00, 23.85it/s]" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "uyBiFvRac-fE" - }, - "source": [ - "\n", - "\n", - "First, we'll implement the $\\color{blue}{\\mathbb{E}_{q(\\mathbf{z};\\phi)}\\left[\\log p(\\mathbf{x}_i|\\mathbf{z};\\mathbf{w}) \\right]}$ term in PyTorch in a function called `log_p_x`.\n", - "Earlier, we introduced the density network with $p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) = \\mathcal{N}\\left(f(\\mathbf{z};\\mathbf{w}), \\sigma^2_x\\mathbf{I}_P\\right)$. The $\\log$ of this is\n", - "\\begin{align}\\log p(\\mathbf{x}_i|\\mathbf{z};\\mathbf{w}) &= -\\frac{1}{2} \\frac{||\\mathbf{x}_i - f(\\mathbf{z};\\mathbf{w})||_2^2}{\\sigma_\\mathbf{x}^2} - P \\log(\\sigma_\\mathbf{x}) \\\\\n", - "&= -\\sum_{j=1}^P \\left(\\frac{(x_{ij} - f(\\mathbf{z};\\mathbf{w})_j)^2}{2\\sigma_\\mathbf{x}^2} + \\log \\sigma_\\mathbf{x}\\right)\\end{align}\n", - "where $j$ indexes individual pixels in the image." - ] + "311f5429f3b146edbc9b8f6f528681d1": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": { - "id": "xWDsqABzgZ36" - }, - "outputs": [], - "source": [ - "def log_p_x(x, mu_xs, sig_x):\n", - " \"\"\"Given [batch, ...] input x and [batch, n, ...] reconstructions, compute\n", - " pixel-wise log Gaussian probability\n", - "\n", - " Sum over pixel dimensions, but mean over batch and samples.\n", - " \"\"\"\n", - " b, n = mu_xs.size()[:2]\n", - " # Flatten out pixels and add a singleton dimension [1] so that x will be\n", - " # implicitly expanded when combined with mu_xs\n", - " x = x.reshape(b, 1, -1)\n", - " _, _, p = x.size()\n", - " squared_error = (x - mu_xs.view(b, n, -1)) ** 2 / (2 * sig_x**2)\n", - "\n", - " # Size of squared_error is [b,n,p]. log prob is by definition sum over [p].\n", - " # Expected value requires mean over [n]. Handling different size batches\n", - " # requires mean over [b].\n", - " return -(squared_error + torch.log(sig_x)).sum(dim=2).mean(dim=(0, 1))\n" - ] + "34183fa0c5d14e6381b21394365ab92d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_8f0ef0efb0f44a7aa216208211ac49b0", + "placeholder": "​", + "style": "IPY_MODEL_404f2d1a05e649f590d668c6bf759179", + "value": " 598/600 [00:25<00:00, 23.95it/s]" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "FIvFgXZNiZjY" - }, - "source": [ - "Next, we will implement the $\\color{green}{KL(q(\\mathbf{z};\\phi)||p(\\mathbf{z}))}$ term in a function called `kl_q_p`. While we could plug in the exact formula for $KL$ between two Gaussians, a more general (but more variable) approach is to write\n", - "$$KL(q(\\mathbf{z};\\phi)||p(\\mathbf{z})) = \\mathbb{E}_{q(\\mathbf{z};\\phi)}\\left[\\log q(\\mathbf{z};\\phi) - \\log p(\\mathbf{z})\\right]$$\n", - "and approximate this expectation with samples of $\\mathbf{z} \\sim q(\\mathbf{z};\\phi)$ just like we did for the reconstruction term." - ] + "35bb8a89785648afa099763e8703d4a8": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": { - "id": "p0wOSNHuiYb4" - }, - "outputs": [], - "source": [ - "def kl_q_p(zs, phi):\n", - " \"\"\"Given [b,n,k] samples of z drawn from q, compute estimate of KL(q||p).\n", - " phi must be size [b,k+1]\n", - "\n", - " This uses mu_p = 0 and sigma_p = 1, which simplifies the log(p(zs)) term to\n", - " just -1/2*(zs**2)\n", - " \"\"\"\n", - " b, n, k = zs.size()\n", - " mu_q, log_sig_q = phi[:, :-1], phi[:, -1]\n", - " log_p = -0.5 * (zs**2)\n", - " log_q = -0.5 * (zs - mu_q.view(b, 1, k)) ** 2 / log_sig_q.exp().view(\n", - " b, 1, 1\n", - " ) ** 2 - log_sig_q.view(b, 1, -1)\n", - " # Size of log_q and log_p is [b,n,k]. Sum along [k] but mean along [b,n]\n", - " return (log_q - log_p).sum(dim=2).mean(dim=(0, 1))\n" - ] + "374d595cfc1748cb80d6384791588795": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d15d1a79f8d74a5eafaa85a11db1d8df", + "placeholder": "​", + "style": "IPY_MODEL_cef45f2502b24609af4c9162442a15ab", + "value": "100%" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "PGtTMpqJq-8n" - }, - "source": [ - "Finally, we will implement the ELBO in a function called, well, `elbo`. Recall from the video that $$\\text{ELBO}(\\mathbf{x}_i,\\phi,\\mathbf{w}) = \\color{blue}{\\mathbb{E}_{q(\\mathbf{z};\\phi)}\\left[\\log p(\\mathbf{x}_i|\\mathbf{z};\\mathbf{w}) \\right]} - \\color{green}{KL(q(\\mathbf{z};\\phi)||p(\\mathbf{z}))} \\, \\,$$\n", - "and that we have two functions for this: `log_p_x` for the first term and `kl_q_p` for the second term. At a high level, the `elbo` function simply computes each of these terms and takes their difference!\n", - "\n", - "For a bit more detail, `elbo` it will have five inputs:\n", - "\n", - "* `x`, which is a _batch_ of input images of size `[batch,channels,height,width]`\n", - "* `phi`, which as before is a batch of _parameters_ of $q(\\mathbf{z};\\phi)$ with size `[batch,k+1]`\n", - "* `density_net`, which takes in $\\mathbf{z}$s and outputs reconstructed $\\mathbf{x}$s. (For those who dove into Appendix A.1 it really outputs the mean of a distribution over each $\\mathbf{x}$. This is the $f(\\mathbf{z};\\mathbf{w})$ in the mathematical notation in the Appendix.)\n", - "* `sig_x`, which is the amount of \"pixel noise\" in the generative model ($\\sigma_\\mathbf{x}$ in the appendix). Intuitively, larger `sig_x` means that the model can be sloppier in its reconstructions, since errors are attributed to _noise_.\n", - "* `n`: the number of samples of `z` that will be sampled per input image." - ] + "37a14ff89dee477b8097c8f167111871": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": { - "id": "5SPSu2ZdrOIu" - }, - "outputs": [], - "source": [ - "def elbo(x, phi, density_net, sig_x, n):\n", - " # Start by drawing n samples of z from q(z;phi)\n", - " zs = rsample(phi, n)\n", - " # Density net expects just [b,k] inputs, so we'll collapse together batch\n", - " # and samples dimensions to get [b*n,k] samples of z, then expand back out\n", - " # separate [b,n,p] dimensions in the result\n", - " b = x.size()[0]\n", - " mu_xs = density_net(zs.view(b * n, -1)).view(b, n, -1)\n", - " # Compute reconstruction and regularization terms. ELBO = diff. between them\n", - " return log_p_x(x, mu_xs, sig_x) - kl_q_p(zs, phi)\n" - ] + "38c277f235854dd8b4f3aca5ca367e91": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_3f3a533f2bc942478a0efadd5cde2f10", + "placeholder": "​", + "style": "IPY_MODEL_e3ef8be847324359a83fdb22622956d4", + "value": " 599/600 [00:24<00:00, 24.58it/s]" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "LnOSPFb5oNHS" - }, - "source": [ - "### See the ELBO in action\n", - "\n", - "What's cool about the ELBO is that it is a single objective which solves two problems at once:\n", - "\n", - "1. When we maximize the ELBO with respect to $\\phi$, we are making $q(\\mathbf{z};\\phi)$ closer to $p(\\mathbf{z}|\\mathbf{x};\\mathbf{w})$. This approximately solves the \"needle in a haystack\" problem of finding which $\\mathbf{z}$s are \"relevant\" for each $\\mathbf{x}_i$. This is the probabilistic equivalent of the _encoder_ from before, which simply mapped from $\\mathbf{x}$ to $\\mathbf{h}$, except now we have an entire distribution $q(\\mathbf{z};\\phi)$.\n", - "2. When we maximize the ELBO with respect to $\\mathbf{w}$, we are improving the generative model, making $p(\\mathbf{x};\\mathbf{w})$ closer to the distribution of training examples of $\\mathbf{x}$. In other words, we are getting better at _generating new $\\mathbf{x}$ from $\\mathbf{z}$_.\n", - "\n", - "(Further details and explanations can be found in Appendix A.2)\n", - "\n", - "To see the ELBO in action, we'll use it to infer $\\mathbf{z}$ for a single $\\mathbf{x}$ using the decoder part of the convolutional autoencoder you built in the first part. This section may also need to be run multiple times, or with larger `steps` (especially if you chose a large $K$)." - ] + "39ec691122e94b0bad070ea86d8391ca": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_8cc33ef056d74afc9f3bd1b3c8988311", + "max": 20, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_204ccffdfba6474bbd2041c81c17dc45", + "value": 20 + } }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 325, - "referenced_widgets": [ - "83e45f5dd5b144018e175f6753b389de", - "90ab04273a9e41eda658baacbac07acd", - "374d595cfc1748cb80d6384791588795", - "42b8cc64de9546e1bb8a2b852a417279", - "9137662d519043f4b63a79a1e9d42671", - "cef45f2502b24609af4c9162442a15ab", - "d15d1a79f8d74a5eafaa85a11db1d8df", - "6774ef7b87f24ad8a5602c5a7595938e", - "0661ed223ab04813b9648f4bb65c2d06", - "b4a6a58e517146cbad3b5ba7e8afdb98", - "c2e32eec26bd4e86bb70b508a46e88d7" - ] - }, - "id": "fKgahgnzoeoO", - "outputId": "04ab03a0-fd11-4d29-b375-76129b2a214b" - }, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "b37a8c6dcbe24bac834e899e4a34019a", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - " 0%| | 0/4000 [00:00" - ] - }, - "metadata": { - "image/png": { - "height": 428, - "width": 978 - } - }, - "output_type": "display_data" - } + "3a259488152f431498bcd9adc731f89d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "3d21e3947dc04917a814c6f2d04ccefb": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "3e2d6740b993473bb7691d7773baa74b": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "3ebe6f717c8543a482d4e139ac7e855d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "3f3a533f2bc942478a0efadd5cde2f10": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "404f2d1a05e649f590d668c6bf759179": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "414eba0f0473491990dc8871529a8907": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "42b8cc64de9546e1bb8a2b852a417279": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_0661ed223ab04813b9648f4bb65c2d06", + "max": 4000, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_6774ef7b87f24ad8a5602c5a7595938e", + "value": 4000 + } + }, + "43b2acb6a30c40d18ec70ffbd288675f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_3d21e3947dc04917a814c6f2d04ccefb", + "placeholder": "​", + "style": "IPY_MODEL_ea335e3e8b7a425995f4aaca9899a018", + "value": " 599/600 [00:24<00:00, 24.51it/s]" + } + }, + "43c8e2457cba4fdc937bdb37a8575e29": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "441952e7c48e4366a3044537aadb330b": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "49e1682fc7bb47c7b297d0c1f042919c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_8b1e4fafa4bd4ef38621db8a286d6c05", + "placeholder": "​", + "style": "IPY_MODEL_f943a6707a2746668cc897d3b5378ab7", + "value": " 20/20 [03:18<00:00, 9.90s/it]" + } + }, + "4dba7c97bf8045bbbfaf0767ac27120f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_ffcab833aec74408b5cca57f090ec931", + "placeholder": "​", + "style": "IPY_MODEL_e13fa64818ab41d68a65a73312572c99", + "value": "Epoch: 100%" + } + }, + "4f5e66ca82e7467d90d745730dc4a094": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "52064c4872c843c4bcfedfe12a4d1213": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "527a4fdd54cc445c9a8922dc9006bf4b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "54f2282cf9a040fd84cc4861fac08efb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_9b19aa560c0a45b5a03976bf2ab20434", + "IPY_MODEL_e856ef4698c94b79bdc559f91b710b17", + "IPY_MODEL_8b947f0af507406aa2177b16d791921f" ], - "source": [ - "# Pick a random image from the validation set\n", - "idx = torch.randint(len(my_valset), size=())\n", - "x_i, _ = my_valset[idx]\n", - "\n", - "# Solve for q(z;phi) by maximizing the ELBO by gradient ascent\n", - "steps = 4000\n", - "phi = torch.zeros(1, K + 1, requires_grad=True, device=DEVICE)\n", - "# sig_x controls amount of 'pixel noise'.\n", - "# Lower --> more 'strict' reconstructions, so q(z) will be narrower.\n", - "# Higher --> more 'lax' reconstructions, so q(z) will be wider.\n", - "sig_x = torch.tensor(0.5, device=DEVICE)\n", - "optim = torch.optim.Adam([phi], lr=0.001)\n", - "elbo_vals = torch.zeros(steps, device=DEVICE)\n", - "x_i = x_i.to(DEVICE).unsqueeze(0)\n", - "conv_ae.to(DEVICE)\n", - "for iter in trange(steps, leave=False):\n", - " optim.zero_grad()\n", - " loss = -elbo(x_i, phi, density_net=conv_ae.decode, sig_x=sig_x, n=16)\n", - " loss.backward()\n", - " optim.step()\n", - " elbo_vals[iter] = -loss.detach()\n", - "x_i = x_i.to(\"cpu\")\n", - "conv_ae.to(\"cpu\")\n", - "phi = phi.detach().cpu().flatten()\n", - "\n", - "mu_q = phi[:-1]\n", - "sig_q = torch.exp(phi[-1]) * torch.ones(K)\n", - "\n", - "# For comparison, what would our AE encoder have produced?\n", - "h = conv_ae.encode(x_i).detach().flatten()\n", - "\n", - "# Plot\n", - "with plt.xkcd():\n", - " plt.figure(figsize=(10, 4.5))\n", - " plt.subplot(1, 2, 1)\n", - " plt.plot(elbo_vals.cpu())\n", - " plt.xlabel(\"Iterations\")\n", - " plt.ylabel(\"ELBO\")\n", - " plt.title(\"ELBO gradient ascent w.r.t. $\\phi$\")\n", - " plt.subplot(1, 2, 2)\n", - " plt.plot(torch.arange(1, K + 1), h, marker=\".\", color=\"k\", linestyle=\"-\")\n", - " plt.errorbar(\n", - " torch.arange(1, K + 1), mu_q, sig_q, marker=\".\", linestyle=\"-\", color=\"b\"\n", - " )\n", - " plt.legend([\"h\", \"q(z;$\\phi$)\"])\n", - " plt.xlabel(\"hidden dimension (k)\")\n", - " plt.ylabel(\"z_k\")\n", - " plt.title(\"q(z) gets close to h\")\n", - " plt.show()\n" - ] + "layout": "IPY_MODEL_6b497d8b2a804e1883e1711cb84fec90" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "otcFWoujtmDP" - }, - "source": [ - "Hopefully you see that we successfully maximized the ELBO by ascending its gradient with respect to $\\phi$, and that the resulting distribution $q(\\mathbf{z};\\phi)$ is close to the vector $\\mathbf{h}$ that our original autoencoder produces for the same image.\n", - "\n", - "Remember that in a VAE, we are thinking in terms of _distributions_. Rather than a single $\\mathbf{h}$, we have an entire distribution of $\\mathbf{z}$s. We should be able to sample $\\mathbf{z} \\sim q(\\mathbf{z};\\phi)$ and get decent reconstructions of $\\mathbf{x}_i$ for all of them. Let's take a look:" - ] + "551623ea5966495a8377a4b05a5aef12": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 137 - }, - "id": "5LlIucKSs8sE", - "outputId": "197c59a7-0172-47bb-f1ee-30c6cf151347" - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 166, - "width": 975 - } - }, - "output_type": "display_data" - } + "569c655751824fc59b479f2e4e27e118": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d6b5e3a56ea248aeb55c4ae76aec0002", + "placeholder": "​", + "style": "IPY_MODEL_b79e494f2e474a42a5c4f871dae09dd9", + "value": " 599/600 [00:25<00:00, 24.02it/s]" + } + }, + "5959b45ae4dd426382e216012ea1d126": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_fbcefc642f18403db6d8c816131b3b0e", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_08bba96f8f9d4737a949725883a92671", + "value": 600 + } + }, + "597c6657347441e68304cf74d4c6a217": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "59df81b1dd7f414ca1e1d009f222cfa3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_d8d7f92934f94acd94d87b72b40852f1", + "max": 10, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_c4e8724ef9594d69b18fb1b33d7989cd", + "value": 10 + } + }, + "5cbbe232d6124c6aaad533dae40de75e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_0a068f4e30b8480aa1a71db83f15d638", + "IPY_MODEL_a04cb13e1c9946d08f2a5730574523ee", + "IPY_MODEL_34183fa0c5d14e6381b21394365ab92d" ], - "source": [ - "plt.figure(figsize=(10, 3))\n", - "plt.subplot(1, 7, 1)\n", - "plot_torch_image(x_i[0])\n", - "plt.title(\"$x_i$\")\n", - "\n", - "orig_reconstruction = conv_ae.decode(h.view(1, K))[0].detach()\n", - "plt.subplot(1, 7, 2)\n", - "plot_torch_image(orig_reconstruction)\n", - "plt.title(\"h --> $x'$\")\n", - "\n", - "zs = rsample(phi.view(1, -1), 5)[0]\n", - "q_reconstructions = conv_ae.decode(zs).detach()\n", - "for i in range(5):\n", - " plt.subplot(1, 7, 3 + i)\n", - " plot_torch_image(q_reconstructions[i])\n", - " plt.title(f\"$z_{i+1}$ --> $x'$\")\n" - ] + "layout": "IPY_MODEL_da343bece953454fa206c38c28f8d9ff" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "wEmc1SLvvWnf" - }, - "source": [ - "You should see that the reconstructions from each sampled $\\mathbf{z}$ vary slightly from each other, but that all are plausible reconstructions of the original $\\mathbf{x}_i$. This proves that maximizing the ELBO by doing gradient descent on $\\phi$ gives us the ability to reconstruct $\\mathbf{x}$ a few different ways based on a __distribution__ of $\\mathbf{z}$s.\n", - "\n", - "(Your results may vary, depending on the dataset, $K$, number of optimization steps, etc)." - ] + "5dd6c30df3d943888ac630d68f84f948": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "9N1Uz_OxEyEP" - }, - "source": [ - "## Build a VAE\n", - "\n", - "You now have all the ingredients you need to build a VAE! The architecture in this example will be nearly identical to the `ConvAutoEncoder` from earlier, with a few key differences reflecting the fact that we're now thinking _distributionally_:\n", - "\n", - "* The encoder is now a \"recognition model\" that outputs $\\phi$ for each input rather than $\\mathbf{h}$. All this means in the code is that the final linear layer which previously projected down to `K` dimensions will now project down to `K+1` dimensions (the size of $\\phi$).\n", - "* The model will store `sig_x` as an extra parameter for the density network. In fact, we'll make `sig_x` learned from data as well.\n", - "* We'll train to maximize the ELBO" - ] + "6067d9f4878e4a7597d7980fb4f57457": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "XPytk4mmMXor", - "outputId": "f1993205-c3da-4996-8935-6fe98e70f18a" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=QPPCjiN7UIk\n" - ] - }, - { - "data": { - "image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEABALDBoYFhwaGBkeHRwdIS4jIyEhIiYqKykvLyoyOC0nLS84QlBCODlLRS0yR2FFS1NWW11dMkFlbWRYbFBZW1cBERISGRYZLRsbMFc/NUJeV1dfV1dXV1dXV1dXV1dXV1dXV1dXV1dXV1dXXVdXXVdXV1dXV1dXV1dXV11XV1dXV//AABEIAWgB4AMBIgACEQEDEQH/xAAcAAEAAQUBAQAAAAAAAAAAAAAABAEDBQYHAgj/xABHEAACAQIDBAYGBgcIAgIDAAAAAQIDEQQSIQUxQVETFCJTktEyYXGRodIGF1KBsbIWIyRCcnOTFTM0Q2KClMFV8KLxB2Ph/8QAGAEBAQEBAQAAAAAAAAAAAAAAAAECAwT/xAAiEQEBAAIBBQEAAwEAAAAAAAAAAQIRIQMSMUFRIhNhcQT/2gAMAwEAAhEDEQA/AOfgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng3D6uMb3uH8VT5B9XGN73D+Kp8gGng2zEf/j7GU6c5yq4e0IuTtKd7JX07JqYAAysfo/WaTzU9VffLyAxQMuvo5W+1T98vI9L6NV/tU/fLyGzTDAzS+jFf7dL3y8j0voriPt0vfLyJs0wYM8voliPt0vfL5T0vohiPt0fFL5Rsa+DYf0OxP26Pil8pVfQzE/bo+KfyjY10GyL6FYrvKPin8pX9CMV3lHxT+UbGtA2X9CMV3lHxT+U8VvoZiYQlNzo2jFydpT4K/2Rsa6ACj6AAKAVBZWKp5+j6SGf7GZZvdvKyxEFNQc4qb1UXJXfsQNLoPKmm2k1db1fd7S1VxlKDyzqwi+UpJP4gXwWqOJp1L9HUhO2/LJO3tsXAKgoW6uJhCUYynFSm7RTavJ+pcQLoKACoLUcRBzdNTi5xV3FNXSfFoVa8IOKlJRc5ZY3e98l69ALoKACoKHilXhNyUJKThLLKz3Pk/XqBcBQAVBQAVBQqBQAj4STbq3d7VGl6lZaAXp1LPc9zfuPDrWTlwuep07tN8mre3/6DpJ7917/AHk5CM7tetXLh4jBJ/dZHsoAAAAAAAAAAAAAAAAibV/wtf8AlT/KzhR3Xav+Fr/yp/lZwoAb1Qj2I/wr8DRToFCPYj/CvwJVisYF2NMrGJejAy08Rpl2NI9xie5vLFvkBSNJ+o95bOzau/WYDH7UbklF2S5cSA8ReTd7u99TpOn9cr1NeG5Kky5GkzWsLtOdvTdlZ6/gZvZu0s7yy38xenYTqS8J6pPke1SfIupFxI5uiP0T5EfaFJ9Xraf5c/ysyJY2j/hq38qf5WEcVABtH0AUKgDC7ZXQV6GMW6L6Kr/BN6P7pW97JcJxdSrXlpCknBP1LWcvfZf7CTi8NGtSnSn6M4uL+9EaWzrUKdGE8sYZbu182Vp2fttr7SN7ljE4Ov0WNhNyv1yNpr7FSOsF4W4/7SVtJtbQwjjHM+jraXS+wTtqbP6zTUM7g1KM1JJNpxd01ct19nSnWpVultKlGUV2NHmtdvX1E013Tz/rzXxM6dKtW6G04tRsu08qa7Wm+2aTsuViuHxdStRnOhUo1Hm/VytLLbS6kr3T3/AuzwdSWZuu1J5crUUlG0rvTje1n6jxHZriqzhVyVK0lJzhBWVrLSLvy48ys8aS67lkllaUrOzaur+zQ1yNSpPD7MnKSlOVWLTaa30Z799/gbM43TT4mLpbFcaeHh0zaw8lKF4rhFxSf3NimNkeKe1akY1Y1FGVSnWjSTgmk86i07Nt6Zt1+BLwVetKpUjVh2FZwqJON774uLb1XP1lirsWM1XUqj/XTjUvFWcJRSyuL/2olYLCzhrVrOrK1ruKikvYvxBe3XDHYhVf7RmqLgpdVhrNNr+8nwTV/eKe15zhhpOEE6ld0aid3llHPdxf+34k+tgW6/T06mWTgqbTjmTSbatqrPVlqWyI5aMYTcVRqdLqk3KWt2/bmY5XeN8o2L2vUjHEzhGH7POMMsk7yuou976XzaaPd69MpUnKNJy7OdRvxtexgZtyxFWXSypVM9ownhukdlonGVtztfR8TNzlLqzdSyl0fatuvbUGUnDF0Nq4jLhatSNLosRli1HNmjKa0d27Neq2nNl2G1JKNbNGGZYhUY2uk21Gzl7/AIHnY2Dc8LhHUldUoxkoZbNSUbdrna74IvT2JGUK0JVH+tqdKmlZwkrWcfZlROVvbvSztetiaeGxLvBKMU4VIp3d/SWW+jXO/HcSYYqrHEU6EnBqdGU7qLVnFxXN6dr4Cey5VKFSnWrSqOpHK5ZVGy9SWhWps2TnSqKs1UpxcHLLHtRk02rcNyt/2VNxDhtatKnRko081SvKjL0raSkrrX/SXnja95UlkdWnCMpNQk4tyzWSWa6XZ5vf6hT2JlhTiqz/AFdZ1leK3tt29naZexWzJSrdNSrSozcVCdoqSkk9Lp8Vd6jk/KXhKkp04SnDo5uKcoN3yvirl1ux5pU8kVG7duL3v1sg42vd24L4smWXbNudul+pjYrcrkbDYvK6nZ9Kbe/1IgymeYyPPetXLvrPUq8Z7t/IumCpVHda/eZjD1c8b8eJ2wz7m5ltdAB0aAAAAAAAAAAAAAAAARNq/wCFr/yp/lZwo7rtX/C1/wCVP8rOFADo+Hj2I/wr8DnB0vDLsR/hX4EqxchAvRgUgi9FGVIwI+1dMPN+omox21asJQnCU0owjmnrrzjH36/d6yzyXw1ShhZVHq7Iy2H2FB75SIOGxajvjJ+xeZkcNtqkk73TXC2oytbwwx1ykLYcUtGY2g5UsSlU0ipK/LeZWltqE9FTqe5eZGdJYubhCVs/F8LLib6eV9ufWwx1uNxjHQuKJA2DTlTw6ozlmnSbi7e26t6rGTSOdHjKR9pR/Zq/8qf5WTbEbaa/Zq/8qf5WBw8AG0fQAAAAAAUKgChUAAAAAAAAACgKgChUAAAABbrVciu1J6/uxbfwLhQCK8cu7q/05GLqVL8H96ZnrGGxNOza5M49bwxmiNlD1JEbGYjo46b2eRyvCVFk/B4rLfszd+UGzAYDHOc1GXE2fAQsm+eiO3R8tYXb3HGptLJV1505EgA9bsqAAAAAAAAAAAAAAACLtRfs1b+VP8rOEndtpv8AZq38qf5WcJAHTMP6EP4V+BzM6Xh5diP8K/AlWJMGXYsjqR6UxpUnMaR9KJftc1w7L/8Aijb+lNE2hh6iXTSd1UlJavXRta+4RKlqMGrtyv7JErA4K9Cc1FZ8ylHnZcPv195Yw9VZNeK3kvA0qa/zd/8AqtqZd5I94ahTvpKom/3csvKxa2zg4wjBq6nNvMr89bfcZyk0YXa1KrXxEaVGLnKMHKysMbynUk02X6IylUp1Ks0k5SjBJcFCCS/E2JGM2Dg3QwtOE/Ttml7Xrb7t33GTRquD0Rtp/wCGr/yp/lZJI20/8NX/AJU/ysg4aADQ+gAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAj4nD51dbyQCWb4GFq0GnqrELEYPpU1ezTNmaIuCSvW0/zX+WJxvRjFw2wuy9iZal5Naa2467vwM68RCKdv3U9P4d6RaoUF1irVTd2lB66aK//f4nqeEu9HaNp3Xrlq2vvN4Y9s4Mce2cPfWoqShJ9t6aJ8rsPFLOorc1d6PRu2Veq9ynVU59I281ktHppwX4nl4XtRvqt8td7VrN+74I3y1yv0p3vfenZlwt0oWTvvbuy4VQAAAAAAAAAAAABF2n/hq38uX5WcJO7bTf7NW/lT/KzhIA6NQfYj/CvwOcnQqD7Ef4V+AElSGYt3KOQHjGYno6cpcka5j8dCVOFOMc1rPM+fGxn67umnuZr2Kw1KkneXSSv2Y7klfiFXKlTPlnlS6RXstyabTt6tCfgoNrWKaMQq9SaUpcNIpJJJckidg8a07JGa643TNUWouyVlyNnwuHjBR0WZK2a2vNq5q2EjKXae/kWdm/SCthpuliE6ii7avtL2PivaMUzreosuIx+zto0sRHNSle2+PFe1E5M05LiI20/wDDV/5U/wArJCZG2k/2av8Ayp/lYHDwAB9AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAoRYpqU409XKWaUnujdLT1vTcSZSsm3uWpawkbU03vl2n7XqQe6VNQjZa8297fFs9lQUUBUAUKgAAAAAAAAAAAAAAETav+Fr/AMqf5WcKO+VqSnCUJejJOL9jVma/+guzu5l/Un5gcjN/ovsR/hX4Gd/QXZ3cy/qT8zIR+j+GSSUJaaenLzA1bORMRtGnDRyu+S1Nyq/R3DSi4uErPlUmvimRP0KwHdT/AKtTzKNExW13JNQjlvxb1MXHV6nT/wBCcB3U/wCrU8yi+hOz+6n/AFanmQaZhsPFpZXryMjT2buaW82lfRPBr/Llp/8Asn5lyP0cwy0SqJfzqnmTTUz+sHRpqCvJpJcWaztuvGWIzQ3WtfnY6DL6M4V74zftqzf/AGWav0PwM3eVKX9Sp5iTRllbw53TqNSzJtPmjM7P+keIou0pdJHlN39z3m0/oZgO7n/VqeZ6X0PwK/y5/wBWp5mtsPey9tUsTpF5Z/Ylv+7mSdpP9mr/AMqf5WWKX0XwkJKUITUk7pqpPT4mSq4WE4ShJNqScXq9zVmBwYHXP0F2d3Mv6k/MfoLs7uZf1J+ZFbIAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACxjf7qfri179C8i3UtJ5Hf7XuaLhBUFAUVAAAAAUBCo1a81mXRJZpJJqTekmufqKYmtXpU5VJOllgnJ6SWi363Angi/wBo0O/peOPmW4bUpvK5fq4zWaE5uKjJaarX1p2dmBOBCltOm3an+uaWaXRuLyrm9fhv0JcJqUVJO6aun6mB6AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAW69aNOLlJ2S+/foklxZYWNaa6SlUpqTspSyNXe5PK3a4EsFCk5qKbbSSV23wA9Ahdf0zOjVVPfnajovtON81vuv6iYnfVbgIbw76a6e95nLjZW7Jd6vbW99ORbxrblSgpOKnJ3cXZ2UW7J8DHTrwu8rxU4rTNGorPna8k37vZcxllMfLFsnllKkZtWVlmdm+KWV6r13sUwuEVOUmoxjmSXZXLi2WMJNKrFQqSnTqU3NZm3ZpxXHVb93qMgWNRUAoaVUoWHXcnamr23yforzLVfC1Z5f18oWld5Elf1a3+JZPrUn1TCV4U6Sc5xjeU/SaX78uZXasv2Ws0s36ttJW103EN7PdejCOdJRnNyvG+ftuyeq0uk2uNktxdxUaipYlTbcciyt217Oui3akZY6j0lRtQhUove6EXBJa/vXmnrzjlXtMJtbEvDyw1WFXJJQkpUIuX6pdnsq8rKztHgvU1obhiqlOq8sabqyi9HHRQfPpOD/h19RpX0oa6KhFxbnGMs1W82puyTmrpKV/++QF/Z2MeJxVWVTESgoQlCMJt3qPNrF5JWdrL0d+bRcXtOBxyilGb7Nlv0lTv+5UT19kuPHm9L+izUKldTpNyyuN7Sjkam96inlte9+HDcbRjJZ6aWZ13bLGShFJtr92W93/0343sBsB5lVipKDklKSbSvq0rXaXquveYjC4HEU8CqU6k51r9mUWlku9E2/SjHjfV8iZs+jJxjOtBqtHMm3JS3tXcdfRdlZcAJwKACoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAChHxGJs+jppSqNXtwivtSfBfjw4gWtpVbdHZOc1NSVNb5JaSfqsne742XFETa21KfRdGsynWThHNCcUtNW3JWVlr93IlTpOlFZZZqtWSi6jXtei4JJOy/HUhbdwElhpVI1Kkp0v1qUmnmcddNNG1dK3PcwJNGWZ5XiK0J/YmqSf3PLaXtTZFx9W9KeStUqri2qfR/wuSj2r7rRuzHUcVR6P8Aa5dJSW+nkkowb3NR3uL9beV3S9VraNeUko053v2Y05qTVNS3LPztq272WiavdhnVt6jKhGqs9qllFShJJuTsk5Wy2vpe9vWeMJGVOEKVWvWpSSUUmqeV2VuzLLr6k3cuYjY+bDul0s/Ryrdl03LJusrL16b+JjNm7RhWo5cZVajGOsLSUXFb88rXlbjuTTTtqBKx87VIKOIqTcXLNbolk7Du3LLZffrbgQ8BilKmoqE24dhqNObV0ludv/rjYj7Rrxio9A8kU26dGUZcn20rdlt6RW5b2uBK2fCpGhBdLKLte0LJJvV2TWu/jc8v/R2a/bz9bt1+mR2fQlTq01PSTp1ZNcs1SLt91zLmJwOIdWrSlK2ZU6kXbc3GpFNrle24yx3w1rh2x1rhQsV5OUuji7XV5NcF5v8A6ZdqTUYuT3JXZbw0Gk5S9KTu/VyX3I6T63Pq7CKSSSsluSPRQqREXZ391/un+eR42wl1SvmV10crq17q2qtxIdDATqJzU4RTnPRRq/bfKol8DzjMDKlSnUlOm4wi5NNVbNLV3vUAx8cMoq1GjKnSW6E8PUlO3+mWVqP+7N9xCx+AqV+qLNLoFTlKFNrpJRVoqKmoxvonZ7/bfU2yG06EknGrBp7mndP2FjD42kmpunGkq0c8Z6dtaau2563A13Z+z6tHEVnSnkhKk3OOV0k7SdsueDel3ztda7rbRs/DJRjUlrJxSXKEbaQiuHre9+5K1XxdOo7Rpxr5Fnfo9leq/Hy3k+nNSipLdJJr7wPQKgC3WdoSadnZ6lvAqaow6RtzyrM3pqXwF3xpUABAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAoeaqvF6N6bk7N/fwMXgsJiI0qsJTaqNWp1XJzssvZTi97i9L/vWvxsBJxuNUbxjKKkvSnL0YX3X5vlH8Dxh8yVqEHq7yq1rpyf2su9+zsrkYnZdOpR7Na0asPSqODq7/AN697pPfdK3N3uZqEa0kpRr05J7mqd1+YDzWwUcrlWqSbj2s7eVQtrmitytzdzGbTxMnS7Va8FJPL0NSm6iXBSvq9ztGzdt3AyGLp1UoyqTjOnGalOMabTsuPpPc7PdwPO1sZRlh5RU4Sc1aCTT1/df3Oz+4DXY4ypTr56cenqXeWhe8o5ruUXJLK3rmT5OVuN7dGsssu1ng4uOSN1kU7XlLc3GTWi0SUfs7qVI1Z1Kaws4Kpf8AZ7QcFTj2nKM1fs3V2otPS26xTCSj0S9FwUW6dNweeLaWa8s3Zcknabdt+69gM5Wr1OruPW00oW6XomlJ8f1vo66624mOq46DlGbWVrK4UYp3clpCco8FK2Sz3NR42tsdTaGH6Fyc4uGX0eL09HLvv6jVqzpqnGEYu6yqMYvLJYjsx6Z/6c1k3xlrZ3uBJliak6qnUyxd5NxjJ5otRfZct6UU0nlV7ydtWZDCbJqRpwi6yhf9xwTa5Ri78FzuY3Z7jHEQ6WLUo1X0zl2s1VZv1sXwgrr2XWitd7LirdLQva+d2vTcn6D3S/c9r37uJi4Y5cZRi4zLys06EaeIpQjuVGft9OF2/WzISdld7jH4ynKWJpqFRwfRT1ST/ehpqeZYWsneUlVXrWq9kW7fgdMMZ9dMcZ9SV+tkn/lp3X+p8H7F8fxkkam5yV41I+B6ep6nrJV+3DwP5i2LYkFCxlq/ah4H5lrEQxPZ6OdNdrW8Xu95JP7Jjv28YbF06VG9ScYLNUd27aKbuy5tWT6rWcVd9G2le19NNSJHAdPRpqU2slScmklaTU5WunwTs0uaXI84ihUhDEubfR9HaN6jle17yae56/BEZRIU6tWbU4qjUlq6Knli/arfrPW0/cYPbk+gnhqqlKNVRmqlNQcYxuldU3ws7c9Nbm318TCsslOEaq+1JpU01xvxf8KftRpX0mjloUI9HF2i/wBclK9XRdttre9+9vVu63gXdk144rFVZ1Jz7NOUYRV6qn23dSaXajuS3Xu9242rC47orRqNqNtVK+anzTv6UF9pbuPM036LRaqYhSoRqO0lKU1dwtN3fZT146b+D0stoxLc6cYRlVrZksrmqaUmlvinG7530X+oDYEeJV4qcYN9qSbiuaVr/iveYrC7KqUsEsO6s5zvpJSccl3ple/LHk95M2fh5RhF1l+tjmTlmbvdq8lyTsnbhuAmgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAKAqALGJwynZp5Zx9Ga3rzXNEOnTjKbTvQr2u3DRTX2knpJe1XX3q+SLWIw8ais7pp3jJaOL5pgRquIrU7RlCM3J5Yyi7K/+qL1S37r7iJtXCVFQm3KEovWrFU0m48ba/fZ77WJM3KVqVRqFVPNTml2ZNcUvZe8d9r25mM23tFzoSpKpRUpvo30dRSlr6W9Wikk2272SftAxk8LGrUyVqqp01dRqqSc0ru+ep9qTVr8VDfqr0pU3lcXFZVeUIwtGTksreZaXTbUo7mszdrqyn0cPTpxisTRjKm9YxhTvOb3Z50tZWSskle2924R8dhnKmpwjFQWkJxyyqOz0hJq6UlrZ6t3a9K1wztbC4l0m1Up9M4WdoWT01Sle69vwMDUpUEoQTjKlZPNLR0m4q8uahGMtFwc1wu1k623P2dzjVoNuClFxlebzejan9ptpWvvLeAwawVGLr04TzJXsl0i45VH996t6a3bsmBEqUeiqRpSqqcbtJXipSWWWWd/Rk2uy1Le4q+9E3B4vEdFB54rTRODbtwzO972t/wD0gY6lCatRUadLNL0oLPB5W2nG14R3Ptax32sXtnzvTpxVajmfYSqTyzTjo048fusefrfya/Dj1O/X4ZbC4npa1KdrPoqia5NTgnrxV0ZMxuGw6pV6UE72pVG3zbnBt+9mTO2O9cumO/aNXjkfSR/3rmuftRITugyxh+y3TfDWP8PL7t3uN+W/MSCgKkRF2d/df7p/nkedrpdVrXWZdHK63303EOhs2NVObcU3Oeip0/tvmjzjNmwpUp1Lp5IuVuipvdrwVwISwT/cwzpQ4UnTjJ+zPrk9ivbgQcVs6WIlhbSvThTk1RTc3S0SSknvtqtbPRmzw2rRks0eklHmqVVr35SzQ2rF5JSglGvHPTcLzk1p6UUr3s1zXr5hgcPs2VDEVJxqKjCVJ3jJdGp2k7Ril6Nk7aXaurGzYDDKMVN+nKKvdWyq2kEuCXIs1doKUnGFPM4R6SXSqVOyXLNHV/BE+lNSipK9pJPX1gegVAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAALdetGnCU5yUYRV23uS5gXAeYyTSad09Uz0BC2rCMoQU0ujdSOe/K+nxsvY2W9r0IPDvsrNG3Rbk1O/YS5a2RPlFNNNXT0aZYpYGlCSlGCTW7e8v8N933AR6FOrTvkw9JN7260m37W4XZG2jQqShOTowi3HtShVbk48ezktLS+jMyVAhzoUFQtaCoqN01ayS1Uk/jciYCnXjCM3RhKo4rNOdV53prfsaexaE1bPoqV1TW+9uF73vl3X9ZKAwuOhVnVpN0YKd5KLjVafovS+XcaEob867Tbz3S38U1/0dPxWHc8rjLLODum1daqzTX3mJWzKeKfTJ4Wrd2z9C3dp217etrcTnljaxlNvP0dqTlDDOo230NSzercekjkd/ZY2AiUMNNTz1JqUlHKsscqSbTfF8l7iWbjUCzXpN2cdJR1Xk/Uy8CqtUayl6pLfF70XS1VoRnZtarc1o17GR6+GrPL0ddxs7vNFPTlwNSStSSrVHG06NG9SVlmqPc3opu709q95e2q31Ws47+jdr6cNLkangI16NPPKSyVJyWW1nLPKzaae7euTs+BbxWFlShiakpLI6Vt7fo5u077tH8OBllDeHqTn+0RhCtJ6LO4wbW5JZXGf+679SMD9IZRpTo1Ly6wlJVrRjGLejaTS5687K909Tbam1KVZONOVKUJLWdSUcjXqjvl8F6zUfpOpKhhoqC6OMJRp1cii5qys08ztfe01qrv1AU2LWpYjFVJ1HJtRapKPbV8++8ld3srOXrvyW2YfGdBljUTjF74S3wfHI90oepO69mi1H6J5+kxCjTVS8JRnJqNRrty1vdZk9+m+zNnrXnCMKXSSzxtHpZvtKy7WT7PNyt7HogM/GSaTTunqmi3PERjUjTbeaak1o90bX1/3IxeH2J0WCWGUukd75pNrLd6uFr2twXxJmzsLKnTSqKGeLfbj+9d6yeis3ZNoCaAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAHirTjOMoTSlGSaae5p70z2AMBDYFaisuDx1SlTW6nUjGrGPqV9UvVcr/Z+0v8AyFP/AI0fMzxaxNZU6c5tNqEXJpWvouAGG/s/aX/kKf8Axo+ZXqW046rG0ZvlKhZe9MnT2pGObNCayelonbRtbvUl7193ue0IxzKUZJwjnlu0jz9fH3MDDPbeNjPq0sHF4p6xlGf6lx4zbeqty3l9YPaktZYyhB8oUMy97dyd/akbu0JtJxTen703Bb3zXutzKVdpW1jFvR9nTeqmR63Ahf2ftL/yFP8A40fMf2ftL/yFP/jR8zIrG/rJQs3K9ktPsKT1v/7f7zzh9qQqOKipWnJRjLSzvT6RevcBj5bDxVVZcTtCpKHGNGEaV1ycld2MzhcNCjTjTpRUYQVlFcC6VAsYyq4U5Sja6Wl1f7iJiMVUhGLUoyzXd1HlayV3/wBmRFjUsnpqWT0x9TGyVVR3R0TunfWN7+zcixHH1ct247k/Ql/o9f8AqfuMvY8VaUZxyyV195Zlj8amWPxBniW4XlL0akUpRzRUldX05av3FZYyfTZUllvG1/3k1q1/7wMgo2A7p8TunxD2fViqWsl6c+K+3I87VrR6tWs1J5JaJrXTcecBVw2Ki5wpwupOM4yjHNGSbTUlwZKWEpLdSh4UYYYR4Su7uNGrRj3VOVJwftedNf7cv3mNq7LdeeHazNQhLNQpt/qW8qy9qSWmqtpe25rQ3MAafHZbpYidSU50lKm/7zdUea+W1OdvuVr5nZbzZ8Dh1CKk125JZm9+70fUlwS/7ZJAABsi4DHwxCm6V3GE3DNwk1a7i+K4X9QEsAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA8VaanFxkrxkrNc0ewBZeGg98U7qzvxXJ89/Eo8JT07N7c7+581pxL5i6qr9LK3SZHU0tltk6Hhx9P8A9sBep7Oinq3Jb7XerzJqT13prhY9xwtG8klFtJpq+7M82vK71IdN4tx1Vp6WvbLbolfNbjnvu4WCp1ukbSmovJmbtd2jO9rP7TQE2OGoycrJNp2dnqmla3qdmelgqSkpKCTTzK3BqOVP3aewt7Ppzi6udO7mndpLN+rim7LdqmTAKFQAAAAAAAUKgDFY36PYavUdWUHGo986c5Qb9uV6ln9F6He4n/kVPMyeNrunTzKOZ5or2ZpJOT9Svd+pGOw2NmpShHLLtzd29NJrsrXTR34geP0Xod7iv+RU8yxW2bjqDUMJiZ1KdR5W69pyo8eki9M3Kz4tEyG1ZNboSbvZJ23VHHi7cL70eY46bnCzSUqsc91J6Og5Wtfs6pAW4/RiD1qYrF1JPe3Xkvco2SK/ovQ73E/8ip5mRwdec3NTSWRuLsnvvdNerK4v7yHPasouStGVnUStwySirvXlK79gFp/RTDS0m69SP2Z16jT9quZihRhThGFOKjGKsopWSRDoYmbrKMnFRcXZJXu1J63vytpwMgAAAAAAAAAAAAAAAAAAAAAAAAAAAFrrEOfwY6xDn8GQDHva9NVqlFpp0u1Nvco5U83/AMkrbwM/1iHP4MdYhz+DMF/bFDjKS0bs6dS6s7WatdO7Vk9XdW3lqnt2k75lKNtyyTcn2qi9FK6/u2/xsBsXWIc/gx1iHP4Mw1DaVKpU6OEm5NXTyTyvRN2lazdmtL8SNQ25SmpStJRjLI2k5Nz17EYxTbdlfd+DsGxdYhz+DHWIc/gzAT23h0m1KU7W9GnUd7wzpJpfZ1fK+tisdr0tFJuLk7JKM5JXaSzNKy1klqBnusQ5/BjrEOfwZh8HtClXb6KTeVJu8ZR0lfLJXSunleqIT2/TUnDJLMm1bT0lVyZb+v0vYgNl6xDn8GOsQ5/BmA/tzC2zdKrXt6MuV77vRtx3HqhtWnUp1ZxUn0WbNFavsuStfdd5b2vxV94Gd6xDn8GOsQ5/BmF2bj1iIOSi42ll3pp6J3TXtJYE/rEOfwY6xDn8GQCoE7rEOfwY6xDn8GQQBO6xDn8GOsQ5/BkEATusQ5/BjrEOfwZBAE7rEOfwY6xDn8GQQBO6xDn8GOsQ5/BkEATusQ5/BjrEOfwZBAE7rEOfwZisZ9J8NRqTpyVVunbM405SSurq7ReNK2pj6kdp1sMp2pYnJCa00bilGV3ydvaFmvbaH9M8IkpNV7Pc+hlZ232ZN2ft6hiJSjDpIyglJqcJR0e5q/sNCpUMTUqywVWrBQwqdSaTVktM2V8Xrx3XMl9ENp1MXicTVqu7yQUV9mN5Wj67X3jVi3t9N66xDn8GOsQ5/BkAqGU7rEOfwZTrEOfwZCAEulUpwVovRe1/FnvrEOfwZBAE7rEOfwY6xDn8GQQBO6xDn8GOsQ5/BkEATusQ5/BjrEOfwZBAE7rEOfwY6xDn8GQCoE7rEOfwY6xDn8GQQBO6xDn8GOsQ5/BkAqBO6xDn8GOsQ5/BkEATusQ5/BjrEOfwZBAE7rEOfwY6xDn8GQABP6xDn8GOsQ5/BkAjY3GKllva8pJau2mZJv7r7gMx1iHP4MdYhz+DMVSqyc5xaXZtqm3vvo9N+5/eXgPfRvkRKmyqU5SlKldyd27vW8crvruslpu0XEyhQDFrZFJRcejbUlZtym5PW98zd73Sd730Qp7HpRaapu64uUm/3+b1/vJe8ygAxFDY8adbpY5laNlD91XSV/baK/7voepbGov/AC2vXGUove3e6d79p68m1uZlQBipbGouOXorK9+zKUdcihvTvbKkrHtbLp93y4vg01x5pe4yQAw+A2LGhJyjmbdratJKKkkkuXaem7kkXXsqk553SWbP0l9fSy5b+4yYAxUdi0UopU2lF3j256aWstdFpu3HunsulFVEqVlVTU1d2ldtu6v/AKnr5IyQAgYXARopqnFq7u25Sk27Wu3JtvRJfcX+jfIkACN0b5FejfIkACP0b5Do3yJAAjdG+RXo3yJAAj9G+Q6N8iQAI/RvkU6N8iSAI3RvkOjfIkgCP0b5FOjfIkgCN0b5GkfSX6M4zEYypVpUlKElGzc4rdFJ6NnQABoGK+juLngqdNUJdYbSqyc6dpQhfo1v4XXuXJE76HbDxOFnWdenlU1FK0ovc3fd7TcQBG6N8h0b5EkARujfIdG+RJAEbo3yHRvkSQBG6N8h0b5EkARujfIdG+RJAEbo3yHRvkSQBG6N8h0b5EkARujfIdG+RJAEbo3yHRvkSQBH6N8h0b5EgAR+jfIdG+RIKgRujfIdG+RJAEbo3yPMqN1ZxutH7ndfgSwBBpYRQvkhlvq7f++su9G+RJAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAFnrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrdLvafjj5jrdLvafjj5nDQB3LrVLvafjj5jrVLvafjj5nDQB3LrVLvafjj5jrVLvafjj5nDQB3LrVLvafjj5jrVLvafjj5nDQB3LrVLvafjj5jrVLvafjj5nDQB3LrVLvafjj5jrVLvafjj5nDQAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAB//Z", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } + "61f424d1767044c19cd4aad5ebc13dc6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_147167a175d94e89b91c9e4744c80599", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_9008ee39326d432da956d9617c537f26", + "value": 600 + } + }, + "633885d3801d4f9b89e7040a2dcbbe6d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "6366e4a1c096487681a79cc77d71a523": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_71419896de504961bc169af2ebb40a01", + "placeholder": "​", + "style": "IPY_MODEL_7447e907d8154178bb40a37ee73d5ba9", + "value": "Batches: 100%" + } + }, + "63b7bbe958834089988377ef880e1818": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_26a194907cc54022ac497a546d04f488", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_863a55349a074ce489590a9c7b56f1e7", + "value": 600 + } + }, + "646379c7e3aa41a588bd603d07ab8e28": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6514dcde9f6a4970becfd4d314e30b4f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "653ae70ab5a14a8bb6d43144ee326c9d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_b86732b760144edbb430e2052bb29813", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_5dd6c30df3d943888ac630d68f84f948", + "value": 600 + } + }, + "65e00761711a44d58f234fb932268eb5": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6774ef7b87f24ad8a5602c5a7595938e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "692db0c9d7c54bf68ff111c33e96e496": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "69b3eb3b86c0451984fc07a02958dd45": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6b497d8b2a804e1883e1711cb84fec90": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6c2e4d62cdfc4e4eab0832dc49d577bc": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "712fe0055d7b454f8d342ef3ca68d830": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_29d32c83475c403b9bc384a09781c725", + "placeholder": "​", + "style": "IPY_MODEL_43c8e2457cba4fdc937bdb37a8575e29", + "value": "Batches: 100%" + } + }, + "71419896de504961bc169af2ebb40a01": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "7447e907d8154178bb40a37ee73d5ba9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "74dc5373e7d34b5eb0d391c015603191": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_fadffa82791e4fb5a59e27ace0f46374", + "placeholder": "​", + "style": "IPY_MODEL_0d7f6e08f26c4b6abd8ccee2ec192ac6", + "value": "Epochs: 100%" + } + }, + "74e2292262954ece8066361b76cb299c": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "7548747e11ad4c6aa8dccc9de8328f7d": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "76952d837cf7418795fb34158c80bd27": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "77401b52c114406a9c596e02c8420951": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "78bf30aea545485484cfec8fe69a3767": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "7916f752329348cb814eff14758a3b0a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_8bdebe8c64274e19ad20e184c2034c9e", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_9594bfe8f09e4301b34cf4ea897ce6a4", + "value": 600 + } + }, + "7c61ec46b16c430b83c7fc7839ae5815": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a3693a9258aa4e85869f01e763f41a63", + "IPY_MODEL_d044017d68d34b78a7366a235769c2dc", + "IPY_MODEL_49e1682fc7bb47c7b297d0c1f042919c" ], - "source": [ - "#@title Video: VAEs: the big picture\n", - "\n", - "video = YouTubeVideo(id=\"QPPCjiN7UIk\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] + "layout": "IPY_MODEL_52064c4872c843c4bcfedfe12a4d1213" + } }, - { - "attachments": {}, - "cell_type": "markdown", - "metadata": { - "id": "pRJiI7l6xmHY" - }, - "source": [ - "### Exercise 5\n", - "\n", - "### Write a VAE with otherwise the same architecture as `ConvAutoEncoder`\n", - "\n", - "Note that we're actually not using `elbo()` from above, but rewriting it to be a member function of the `ConvVAE` class. This is simply to reduce the amount of reshaping you need to worry about, but they're functionally the same." - ] + "80e074ada4d642d58c690fdd14020d13": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_d825e4a7719649f7b5a8f5bb2e8ccef4", + "IPY_MODEL_a7501605ea394d47884111fdb2de00ea", + "IPY_MODEL_22c8ca666f614b7dbb9ac0fa3f4e095a" + ], + "layout": "IPY_MODEL_69b3eb3b86c0451984fc07a02958dd45" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "id": "lUEOIel7PJZh" - }, - "outputs": [], - "source": [ - "class ConvVAE(nn.Module):\n", - " def __init__(self, K, num_filters=32, filter_size=5):\n", - " super(ConvVAE, self).__init__()\n", - "\n", - " # With padding=0, the number of pixels cut off from each image dimension\n", - " # is filter_size // 2. Double it to get the amount of pixels lost in\n", - " # width and height per Conv2D layer, or added back in per\n", - " # ConvTranspose2D layer.\n", - " filter_reduction = 2 * (filter_size // 2)\n", - "\n", - " # After passing input through two Conv2d layers, the shape will be\n", - " # 'shape_after_conv'. This is also the shape that will go into the first\n", - " # deconvolution layer in the decoder\n", - " self.shape_after_conv = (\n", - " num_filters,\n", - " my_dataset_size[1] - 2 * filter_reduction,\n", - " my_dataset_size[2] - 2 * filter_reduction,\n", - " )\n", - " flat_size_after_conv = (\n", - " self.shape_after_conv[0]\n", - " * self.shape_after_conv[1]\n", - " * self.shape_after_conv[2]\n", - " )\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your class\n", - " raise NotImplementedError(\"Please complete the ConvVAE class!\")\n", - " ####################################################################\n", - " # Define the recognition model (encoder or q) part\n", - " ... # YOUR CODE HERE (BiasLayer, nn.Conv2d x2, nn.Flatten, nn.Linear)\n", - "\n", - " # Define the generative model (decoder or p) part\n", - " ... # YOUR CODE HERE (nn.Linear, nn.Unflatten(-1, self.shape_after_conv), nn.ConvTranspose2d x2, BiasLayer)\n", - "\n", - " # Define a special extra parameter to learn scalar sig_x for all pixels.\n", - " self.log_sig_x = nn.Parameter(torch.zeros(()))\n", - "\n", - " def infer(self, x):\n", - " \"\"\"Map (batch of) x to (batch of) phi which can then be passed to\n", - " rsample to get z\n", - " \"\"\"\n", - " ... # YOUR CODE HERE. Analogous to conv_ae.encode(). Output should be size [b,k+1]\n", - "\n", - " def generate(self, zs):\n", - " \"\"\"Map [b,n,k] sized samples of z to [b,n,p] sized images\"\"\"\n", - " b, n, k = zs.size()\n", - " ... # YOUR CODE HERE. Analogous to conv_ae.decode(). Hint: requires zs.reshape() or zs.view() since nn.Linear expects (?, k) size inputs\n", - "\n", - " def forward(self, x):\n", - " # VAE.forward() is not used for training, but we'll treat it like a\n", - " # classic autoencoder by taking a single sample of z ~ q\n", - " phi = self.infer(x)\n", - " zs = rsample(phi, 1)\n", - " return self.generate(zs).view(x.size())\n", - "\n", - " def elbo(self, x, n=1):\n", - " \"\"\"Run input end to end through the VAE and compute the ELBO using n\n", - " samples of z\n", - " \"\"\"\n", - " phi = self.infer(x)\n", - " zs = rsample(phi, n)\n", - " mu_xs = self.generate(zs)\n", - " return log_p_x(x, mu_xs, self.log_sig_x.exp()) - kl_q_p(zs, phi)\n", - "\n", - "\n", - "def train_vae(vae, dataset, epochs=10, n_samples=16):\n", - " opt = torch.optim.Adam(vae.parameters(), lr=0.001, weight_decay=1e-6)\n", - " elbo_vals = []\n", - " vae.to(DEVICE)\n", - " vae.train()\n", - " loader = DataLoader(dataset, batch_size=100, shuffle=True, pin_memory=True)\n", - " for epoch in trange(epochs, desc=\"Epochs\"):\n", - " for im, _ in tqdm(\n", - " loader, total=len(dataset) // 100, desc=\"Batches\", leave=False\n", - " ):\n", - " im = im.to(DEVICE)\n", - " opt.zero_grad()\n", - " ####################################################################\n", - " # Fill in all missing code below (...),\n", - " # then remove or comment the line below to test your function\n", - " raise NotImplementedError(\"Please complete the train_vae function!\")\n", - " ####################################################################\n", - " loss = ... # YOUR CODE HERE (hint: use vae.elbo())\n", - " loss.backward()\n", - " opt.step()\n", - "\n", - " elbo_vals.append(-loss.item())\n", - " vae.to(\"cpu\")\n", - " vae.eval()\n", - " return elbo_vals\n", - "\n", - "\n", - "# Uncomment to train\n", - "# vae = ConvVAE(K=K)\n", - "# elbo_vals = train_vae(vae, my_dataset, n_samples=10)\n", - "\n", - "# print(f'Learned sigma_x is {torch.exp(vae.log_sig_x)}')\n", - "\n", - "# plt.figure()\n", - "# plt.plot(elbo_vals)\n", - "# plt.xlabel('Batch #')\n", - "# plt.ylabel('ELBO')\n", - "# plt.show()\n" - ] + "80e9fec5ea3449a3a6cc6b75a1771eaa": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e72254b889824fc7a175dffda4291657", + "placeholder": "​", + "style": "IPY_MODEL_b002b4b85c7e4d9aa3d86791a5b2f801", + "value": "Batches: 100%" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "_b-uEhPf3LSb" - }, - "source": [ - "## We can generate new images!\n", - "\n", - "Remember that earlier we tried sampling $\\mathbf{z} \\sim p(\\mathbf{z})$ and passing those through the `conv_ae.decode` function, and the results were ugly. The original autoencoder was never designed to work purely as a generative model.\n", - "\n", - "Although we didn't go into details of the derivation (see Appendix A), VAEs and the ELBO objective come from applying the logic of generative models and maximum likelihood learning to autoencoders. So: do generated images now look like plausible \"new images\" or samples from the distribution of training images?\n", - "\n", - "You can re-run this cell multiple times to see more examples." - ] + "815caee749e74ce6839ab10f7cd74c09": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_1ab8190bf5114ab89713358df63b2ec2", + "placeholder": "​", + "style": "IPY_MODEL_6514dcde9f6a4970becfd4d314e30b4f", + "value": " 598/600 [00:25<00:00, 23.96it/s]" + } }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 359 - }, - "id": "iXRy9D6e3Vu3", - "outputId": "f6c72d1a-bb1a-4c8b-d62b-cc4935bef35d" - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 475, - "width": 474 - } - }, - "output_type": "display_data" - } + "8205e3bef7ec43549fa19653028019ac": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "83e45f5dd5b144018e175f6753b389de": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_374d595cfc1748cb80d6384791588795", + "IPY_MODEL_42b8cc64de9546e1bb8a2b852a417279", + "IPY_MODEL_9137662d519043f4b63a79a1e9d42671" ], - "source": [ - "zs = torch.randn(1, 25, K)\n", - "vae_images = vae.generate(zs).reshape((25,) + my_dataset_size)\n", - "\n", - "plt.figure(figsize=(5,5))\n", - "for i in range(25):\n", - " plt.subplot(5,5,i+1)\n", - " plot_torch_image(vae_images[i])\n", - "plt.show()" - ] + "layout": "IPY_MODEL_90ab04273a9e41eda658baacbac07acd" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "myaU0gjj46N7" - }, - "source": [ - "These won't be perfect, but hopefully they look a lot more like plausible \"new\" images!\n", - "\n" - ] + "863a55349a074ce489590a9c7b56f1e7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 518 - }, - "id": "i_aH2ts-3sQO", - "outputId": "fba76ab0-246e-4e65-f5cf-7a797c2106cb" - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Video available at https://youtube.com/watch?v=IDTq8muSySQ\n" - ] - }, - { - "data": { - "image/jpeg": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wCEABALDBoXFhsaGBoeHRodHx8fHSAfHicfHyUdLicxMC0nLS01PVBCNThLOS0vRWFFS1NWW1xbNUJlbmRYbFBZW1cBERISGRYZLRsaL1c2Nz1XV1dXV1dXV1dXV1dXXVdXV1dXV1dXV1dXV1dXV1dXV1dXV11XV1dXV1dXV1daV1dXV//AABEIAWgB4AMBIgACEQEDEQH/xAAbAAEAAQUBAAAAAAAAAAAAAAAABQECAwQGB//EAEMQAAIBAgIFBgwFAwQCAwEAAAABAgMRBBIFITFRkhMUQVOh0QYXIjJSYXFygZGx0hUWM7LBI1SCNUJi8CQlNEOTB//EABkBAQEBAQEBAAAAAAAAAAAAAAABAgMEBf/EACARAQADAAMBAQADAQAAAAAAAAABAhEDEjEhMhNBUQT/2gAMAwEAAhEDEQA/APPwAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdh4uMb1uH46n2DxcY3rcPx1PsA48HYeLjG9bh+Op9g8XGN63D8dT7AOPB2Hi4xvW4fjqfYPFxjetw/HU+wDjwdfL/+c41JvlcPq1+fP7DV/JGK6yhxT+0LjmgdL+SMV1lDin9o/JOK6yjxT+0mmS5oHSfknFdZR4p/aU/JWJ6yjxT+0aZLnAdF+TMT6dHin9o/JuJ9OjxS+0aY50HQ/k7E+nR4pfaU/J+J9OjxS+0qOfBP/lDEenR4pfaPyliPTpcUvtAgAT35TxHp0uKX2lPypiPTpcUvtAggTn5Vr+nS4pfaU/K9f06XFL7QIQE0/Bmv6dL5y7i1+Dlb0qfzl3Ae0AFAMVbFU6duUnGF9maSV/mZITUleLTW9O6IbHqvh8RPEQp8vSnCMakI/qwy31xXStewwyxKdHCcznGNKpXs04vVdylltdWSfQTW+nx0BjeIgpqm5RztNqN/KaW12I9aQnCtWp1siUKSq03GL8qOtS6dqdtXrRhm588wTq5VU5HEOeVOyf8AT1IakVTRZWrwpq85xgt8mortIyjpKtUdGcKealUkk0oNShB7J5m7PourdPqHhV/p+I91fVDViv2IlI0sXSqO0KkJP/jJS+hc68FNQzLO05KN9birJu27WiM8IsPB4OpUso1KUHUpzWqUZxV1Z9hTC6QqTrYeMoR/qYV1m7eWpeRePs8oaddjYS5UhMLpvNTnVlKFqdKU6tKzjVpzX+1pvX0q9ugz0sZiHUinTThKEnmySgoTSuk7vyk96tsGp0lJgg8HpavOODqTjT5PE+S4xUsyllck732eTa1viVweKxCp4qblTm415wV1kjFJxV23LYlrt2jVmkwmypB1NMVI0sY0oSlh0pReWUYyi45tj19us2KWOqrExpVVBxqUpVIZE80XFpOLu9fneoanSUmY6VeE3JQlGTi8srNO0tz9ZE0tLVZrCzjGGXEykstnmhZN63fXss9S1llDFKhPHTtd85pxiv8AlKFOK7WNXpKdKkNX0jiKcMRJ001TpOpCbhKEW1e8Gm27+srz7EctSp2pWrUpTg7S8iUct76/KXleoanSUwCGoaXm6cVKMeWlWqUbxi3G8LtyUb32LZfpLa+k8TTpuUqUbqvTpptSjGcJySzJbU9dtY1ekpoEJisfXjHGU26aqUaSqwnGLtlkpamm9qyvX2EngM3IwztN5Y60mtVvW2NSa42QAVkAAAFGYcJioVoZ6burta1Zproa6AuT6zgAIAAAAAAAAAAAAAMdfzJe6/oQCmT9fzJe6/oc8ombN1X5xmKZCvJmVUcy3MZOT9Q5MowuRa2bGQZAjWcixyNpwKZCstVstbNtRGUGtOz3Mo4vczcaLXEqNJwe4tcHuNxxLJIDTdNmGtBpN7tZuyRinEDuChUFGnPDVFUnOnVSz5bxnDPFNK11Zp3+JrvQ0VThGE3GcKzr57J3qNtyutzuyUAxe0oevCnicRSis7lhptzk4uKtbzb2s7vK9Xom5XwTniKVbNbk4zjly3up2vrv/wAUbgJi9kXgtEyovLGvN0FJyjScVq13y5tuW/QbGlcDzmhOjmyqatJ2u7X6DcAw7Tuo/E6OddKFepmpppyhCORTt0S1ttepWLqmBzYiNZTtlpzpqOXok02732+SjeBcTtKL/CFOSlXkqjVKVFtQyOUJWvmd3d6vVtZdgtHVKUVGWIlUjFNU1KKVtVk5NedZewkgTF7SiaWh8lPDU1U1YaSlF5NctTVnr3NirobNGrFVpJVKqrRWVPLUzKWverrYSwGHaURV0M5rEZqzfOIRjPyFqsrXXw/6zNWwko1I182Z0qU4KEYa5Xs3bXt8lWJEDDtLmdHOayOlWjOerPCWGanrflKU9Vn62vgSVTQ0ZrERnNtV5KepZZQmkkmn6sqZKAYs3nfiLejKk6NSnVxDqSnB082RRSi9ryra/WZPw98rQqcor0YShbLqkna72+pEgBidpQ8tCXptcq4zVaVenUjFJwnK91bpWtqxlraMnUpqM6zlLPCo5ZEl5DTSUU9SuiTAw7Sjaui8868pT1V6SpSSjayV7NO+3ymbeEounTjGU87SSvZR2eozgqTMyAAIAAChpOnyVdSWqFXVPdyi2P460bxgxdPNTlbata9q1oNVn6zFS2EsyTWxq5cGQAAAAAAAAAAAABjreZL3X9CFUCbreZL2P6EQjNmqrVEuUS9IuSMtMeUOJlsMpUYcpbUeVXNjKYsTFcnK+yzb+RYSULpDSUY6rtans1O5F/iMVK6136XtM2F0by9V5n5CJ6h4P4aK1wu97es6zyxT5DlHBa8bMoGlj/Na1Pa7dKJTB4xVHa+vo9fqK47RFOMGo6vW9pzyrPDTTazKLvt126TUXryRLnPHbjmPrrHEtcS+jUjUhGcdcZJNexlZI4uzBJGKSNhoxyiBryiYpI2ZIxSQHYAAqqHDVPDqspSXIU9Ta86XQzuTx6pHype9L6gdP+e63UU+KRVeHVbqKfFI5dRL1ADpfz1W6inxSKrw5rdRT4pHNZAoE0dN+eK3UU+KQ/PFbqKfFI5vIXxpjR0X52rdRT4pFV4a1upp8Ujn4wRTkxo6P86Vupp8TKLw1rdTT4mQGTUW5Ro6L851upp8TC8M63Uw4mc9lLrDR0P5xrdTDiZ0uiMa8Rh4VZJRcr6ls1No84S6Dv8AwaX/AIVP/L9zESJUAFAAAAAAAAAAoBUoRmLxlSNSUYvUrdC3GHn9X0uxGe0OU81YnEphtUcvotr4X1dhmIOOOqKT8rbZ7F7P4Luf1fS7ETvBPPXU0CPwGJnOTUndWvsW8kDUTrdbRaNgABWgAAAAAAAFlbzJex/Qh4smKvmS9j+hERRmWqskS9ItiZERoSK2KoBFGROndIQoQip5ss208u3Kldr46l8WSzOS8Nq0f6UL+Usza/4vV/BYSWp+LTpxbp5UpXfS2lu2bS2OmsQ6drSu27St5Opa7esYWtahFqEW2tTd/oZquOhKlSpQjJTpycoy23l039t2ZnNdoiYhrU9J1kvKnyi15otu6+aLI4uPOIurTbSeuDtr3X6CQ59eDjyUE5apNbbdKITSVa9TZ638TVZ+uXJDt8BUUlOMUslObhFrY0kn2Xt8DYaNXQEGsJTbVnJOWy216uyxuyiac2BoskjM0WSRBgkjFJGxJGKSKjqQAGlDyOUfKl70vqeuHk6jeUrelL6kkWKJfyZnhF3L+QMTZWvGkXRp3Njkugvp0dZnsuNWraEczI+eInO9tS9RIWWIxKpvzInWU9HUVCySM35Y4/Wq07PO23vZlpYqUem63MndOYCEfNOdnGx1paLxrNq9ZTOHmqkbr4+oucLMi9H18lRbnqZOOafSSfhDDk1FMtjM7C1zOrjFlO78G/8A4dP/AC/czh7Hc+Dq/wDDp/5fuZussykwAbQAAAAAAAAKFSgELj/1pfD6I1zYx/60vh9EadarkV8spe7bV69bRwn14L/qV72r2MqYsPWVSEJpNKWtKSs7GUJLe0V58vd/klSK0V58vd/klDrTx6+H8qgA06gAAAAAAALKvmy9j+hExJar5svY/oRCZmWoZUy9Mwpl2YisqkVzGLMMxUXtnPaf0Zy9XZeXITyJO39RSVv3E65HNab026NaSpry4xUE2tSvaTfr/wBq+ZYRFYSU6dGGrbmt7FJpmejVlF5lCLl0eVrFCcqmCU5q1q08r2XUtb7bmKg6e13v7TE+u1bbVlq1M2tqz6Ub2C8G4VJcrWeaE6aairxalq6V6vqRMpZm7bDtcO/6cLbMsfoaq5XllhFRSS1JJJL1FWW3KXNOajRZJF7ZYwMckYpIzMxyA6QABpQ8flXtOdvTl9T2A8YqfqTf/OX1A26eId1I2uf7LEapItcjM1iTU9hq0KstWp7jLjZxp0pNec9RBYfFOErrdYuq4yUotSd9xz/j+tayaHrxp1JSm/ZvOljpelyTqdC+dzndA4aFaU4z26rPaSuK0dGlh3CL1Ocbv2HLlis2yXbj2KsGI0rTnrcWr7CExklJ3irI6eeiqLhGcnsS1WRzmk6ic/JSSW43xTXcqzyROfWlckadX1kabtON7P8Ak9Di3VX1o249BFZXu7Tep1/JSepnO1f8WJZqrtssdt4Nu+Dp/wCX7mcBKon06zvvBh/+FS/y/cy1glLAA2gAAAAAAAAUKlAIXH/rS+H0RH43DurDIpKKbWa8cylH0WrrUyQx/wCtL4fRGucZ9eC3y0tR4lwahJOc9t4Ryxtrexv1CjjlOSjkkrva7W6ftNti5E2G9orz5e7/ACSpFaK8+Xu/ySh1p49fD+VQAadQAAAAAAAFlbzJex/QhFInZK6aex6jW/D6e58TJMLEo1SGYkuYU9z+bHMKe58TJi6jsxXMSHMKe58TDwNPc+JlxNRk6qWttJesgNJzwkqvKyi6k4q1l5kmtl951U9BYeXnRk/bUl3mGXgxhHtpy/8A0n3hHJTxDnRjDVZXdkrK/wD1kdKjZnfR8GcItkJf/pPvKvwbwr/+t8cu8z1lvtGY4vB0rskpYl0pRVObuvOV7x+R0sfB/DJWUJL2Tl3lq8HcL6EuOXeWIYtOxkIWjprrI/GPcbtLHU5+bJX3PUzd/LuF9CXHLvK/l7C+g+OXeac4izWcijZJw0bSirJO3rk2Xcwp7n82GsRDZjkTX4dS3PiY/DaXoviYMbYADSh4vW8+fvy+p7QeLYh/1J+/L6gEXXLEyoFSyZekVqR8m4GXRtdwq3T2krpLETlCOWUlF65Jx139pz6diYw+kqUqWWtC81sdzlev3cdaW+ZLaqY2UqS1WSSXt9ZA13rNitib6lqRqSdzVK4ze2rTNT2GEz0NhthemzIpt9JY7FAL3M9I8EX/AOvpf5/uZ5rFHpXgh/p9L/P97AmgAAAAAFCkZJq61oC4AAChUoBBaRrRVaaclfV9Ea3Lw9JG3j4rlp6l0fRGvkW5fI4T68F/1KzloekvmV5aHpL5lci3L5Dk47l8gjd0RUi6kkmn5PQ/WS5E6JglUlZJeTu9ZLHWnj18P5VKFSM8IZPmsqcW1KtKFFNOzWeSi2vZFt/A06pIHKYuhiILDUK9X+nGuowyu8qlKmnUzVH7sErLp1+okJabqQVOpVpwjRq06lSKU26kYRg55pK1rWWu2xtbQJsEJT0tXTcKkaUZ8lRmknNpSm5LI9V5PyW7Ld8TbwOkXPB84qpRtGpJ2vbLFu0lfWrpXt6wJAHMYXG1KFCUsjcqUKSqu85RjOp/VqycFtUcy2a9e43/AMWqcvQppUpxqSUJuDm7Pk3Nu9rLo1PXZ3AmARukMdVhVVOjGm7Up1akqjajGKaSWrfeWv8A4mrS05OdTDWhFRrZVON5OdNuk6jzO2VWslbbr6AJwHNx01VVGdSlCLSo85lnlNvy5S5OEd14r4XRnr6YrQliJ5IOlTnToU4LNnnWko9O680nq6HtAnQQ1LSleUlSdKKqzlLI5KUIOlGMXKbi9epyUbdJZo7Funga+LqNNzdWt5N3FxWqGX1OMY/MCcBzWH0jWwVHkq0aclQp4Z1JxlJtRnLLNyv0qzkS9PHtYapiKsckYxnUinfNySV05bm0r26L2A3gcpiNHRo4GnNXjj5qDhKMpKcsRJ3ta+tXbunqsmbuI05OEq9owlThQq1YShmflRkoxV2rSzO+zZa2sCeBFaDhljOGtqiqdBScm8zhBOUrbE80mvgaK01UVKpUpwg0qNTEyzzlLyMzVNL3owb9QHRg1sTKDoN1m4QcU52k00ulXWv1aiAw2GcZQoSzUqFedbEOm5NOFCEYJU276ruWZr2reB1AOYw15YTB0lmy18S5Q1u6w0ZyqxXsyxiviW6ZoVp4xQspSqTpOhNVWpUKcbOpLIlvT1315kvUB1JUjNG4ebrV8RNOHKuMI0235kLpTa6G77N1um5JgAABQ8Wr/qT9+X1PaTxiuv6k/fl9QLIxZltbaWResvSuBdGSFSSszDLaWz2AWGXDQvNatXSX4PDOrUjBdJ2mjtBwpRvZNs5cnLFI+t1pMuVqaPaepFtbBtRvY7RaPjm2EdpagowdktjONf8Ao2cdJ44cdlL6UrF0ukxRPW4NpSi96KwgpbC2hKLetG0or/bYkyQwOCPR/BH/AE+l/n+5nnjh8j0PwRX/AK+l/n+9iBNAEZjsTONS0ZWVluEzjNrRWNlJAhee1fTfyQ57V9N/JGe8OX89U0Q2GxTpyfTFvWv5RTntT038ka5mbf4535dyYdDCakk07plxC4TFOm98XtX8omITUkmndM3E670vFoXAA06ITH/rS+H0Rrmxj/1pfD6I1zhPrwX/AFIACMt7RXny93+SVIrRXny93+SVO1PHs4fyGOrQjNwcopuEs8b9ErNXXwb+ZkBp1Yp0ISlGcopyipKLfQnt+hrUtDYaEZxjQpqM1lklHbH0fZ6thvADVraPo1JZp04uTcZXa13iml2Sa+LKxwNJUeQUI8jly5P9uXd7DZAGnW0Vh6l89KErycndbZNJO/tSS+BWOjaCqKqqUVUTclK2tNqzfxSRtgCNqaHp1MRUrVoxqZo04QTV1GMbvWunypN/IzS0XQc3N0o525NvpvJWk/ijbKgav4fRyuPJxyyyXVtTyWyfKyLKmisPPlM1GD5W3KXXnWtrfyXyRugDReiMM4RhyMMsW5RVtkntd9t2ZpYKk6PIOnF0cqhkt5OVbFY2ABGz0RDyIQUYUFLlKkIrXUmrZcz6V0+uy6Ddr0I1YShUipQkrSi9jW4yFQNPCaKw9CTlSowhJq2ZR8q26+2xbT0PhoebRgtUVqX+2MsyXsT1m8AMVPDwjFxjFJScpNLplJtyfxbZiWjqKi4qnFRcYQatqyQ82PsRtADWxmBpYiKjWgpxTvZ7L7zA9CYV04U3h6bhBuUYuN0m9vzJAAYpUIOcZuKzQUlF9KTte3yQhh4RnOcYRU52zyS1ysrK79hlAGKhQhSgoU4qMI7EtiMoAAAAUPGcT+rU9+f1PZjxnEv+tU9+f1Ati2nczxqRktxijFbS5OK6O0zK4tqLKrv4GDay6rVcvYtiFNFR1vg7ojK1Vlu1HTx3HEaN8IalCKg0pwW/aTWC8JqNv6ilGXsuj5vPx8lrbL0VtGfE5ydjn9Pu0WiRl4Q4a11URzGmNNctJ5VaK+bJw8V+3izaIj6i40HK+4ulShBecr+rWa8q0nqvq3IxST6T6WS8+r5Ts9RnpYl7kaZdFmsRIwxCerKj0bwV/wDg0tVvP/czy+LPTfBB30fRv/z/AHMkQspoh9Jfqv2ImCH0l+q/YjN/HDm/KNxvKcjN0v1FFuF1dOS12+Owh6+mZyg50ZJKpKMKN45vNjmqSdtb1tR9pPmOnh4QtlhGOVNKySsm7u3tZiJeasxHsId6Rq1asOSc1CVGnUtGNJtSk5J3ztbratxOGvPAUJedRpvbtgntd32tmwSS0xPgbWBryjJRSun0fya8IOTSSu2TGEwqprfJ7X/BqsTrXFWZnYbBUoVOr2oTH/rS+H0RH4/9J/0+Veq0HHMr72ty2khj/wBaXw+iNc4z68Fv1LUwEYUqagrx2t5lkcpPW5W/6ug2lJPY0Yq2GhNpyV2rW17tn1ZSjg6dN3grPLl29BEnJSuivPl7v8kqRWivPl7v8kqdaePXw/kABp1AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAABQ8WxX6s/fl9T2k8ZxNuVnf05fUC2LaE5uzMsakTDXqX2GW9+MJfGWosFzTDLGZc5mG4TAzcoYZTbKNlAL4uxkUb7TFHaXupZAJpIxhyuVTAyU2rHp/ga76Oo/5/vZ5dTkkz1HwOf8A66jb/n+9gThinh4Sd5RTfrMoCTG+sHNKfoR+Q5pT9CPyM4JkJ1j/ABg5pT9CPyIVQcpWiru+o6AwYXCqnr2ye1/wSa6534+2YphMKqa3ye1/wbAKmvHWIiIyAABUJj/1ZfD6I1zLpGtFVppyV9X0RrcvD0kcJ9eC/wCpZAWctD0l8xy0fSXzDKR0V58vd/klCI0RUi6kkmn5P8kudaePZw/lUAGnUAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAFDxfFr+rP3pfU9oPGMY/6k/el9QMLkW2CMih89wFrRYZXT9pjYAAo2EWlQAqqBQqARVFABU9U8DP9Oo/5/vZ5UeqeBb/9dR/z/ewJ0AAAAAAAAAAChUoBCaQiuWnqXR0epGvkW5fI2cf+tL4fRGucZ9eC/wCpW5I7l8kOTj6K+SLgRluaJglUlZJeTu9ZLEXorz5e7/JKHWnj2cP5VABp1UI16coZrR5WcU8rnCjUnTT95Kz+Bm0xRqVMJXhRdqkqc4w121tb+g18DpC8Y06eFrwyxtllS5OELLZd6nst5NwJOUkk29SWtmGGMhKjGtd8nKMZptO+V7NW3pOYlLEzwsVkxF4YWcal6c80q9WSjJqO2WVKb+KsbFDDVIyXIxxEcPKpRtGcqjmo04ynKVpO8VJqEcrtfcB01zHicRClBzm8sVa79bdkvm0cqqFSVCpykMTKE8TTzT/rKpKjfM70r3jr8h2SVtexHUwoR5OMMt4pKym3N6tl27tv2gatbTFGOpOU5Zpxy04SqSbhbNqS2K6Te9m5RqqcYyje0kpK6cXZrVdPWiD0zSbqx5vSqwxUHelUhD+jJTazqo9ltWu+vVqNaVN8piJSo4nlKldwbTrqEaKXktZXrTy/7dmazaVwOoBzejMHVrQoRruvGEMNeSz1KbdScr5W75m4qNtvSUr4acMBUrznVjiZRqOmnUmrTnO9OmoXte+WO8DpTWwekKVd1VSnmdKbp1Fa1pr/ALtMWDp1KdKdSteVad5yjFuSjZaqcF6tnrd30kLU0fiMNhqVehByxPJZMRBbZud3m9sZyb9jYHQYXHU6yTg280XJamrxva5fPExVWNK/lyjKaVn5sWk3f/JHLYrPh0qSdRQjKlSUIuov/Gp0XebcE5QTm/OS15Ur2uV/DZunNwlWm406FKjUjOp5UpyUpVU73lFZ47W15DA6nE140qc6k35MIynKyu8qV3q+BZhsXCq5qOa8MqleLjrlFSW3bqaI3RmGTxWKnUhVzudln5TkuSyxSSu8stak9Wy7WokMfOVOhVlSg5TUJOMYrXKdtXbYDNSqxnHNF3Tv0NbHbpLpzUU5N2STbfqRzctH12vOr5oVcLRpyzzSyQyupUaTs73mrv1Erp2E5YWpTpqTlVSpeStaU5KLl8E2/gBfV0rSjSpVfLca1uTUacpTd4uXmpX2JssxOmqFFRdRzjmiptcnJuEG7KVTV5Cvvtse5mjp2m5ZKVCniFiKcf8Ax6kE40oyateUtlktqfRsMNbDVatTF4eVOd69Wnmq5bU+aqEbpS33U1bfK+wCXnpaiq6ouTzuWS6hJwU8uZQcrWUrK9jLhcbCs6kYN3pT5OacXFqVk+narNO5AYSjVlCnGVKpDm9WtiK0nBvPWefKoL/em531bkvZO6Nwqo0klmcpeXOUvPlN63KXr9XRs6ANsAAAABQ8Wxv6s/el9T2k8Xx36s/fl9QMCZsRnq+Gs1itwNlT/wC7jqNGwoQpK8YuTWttXZx+Zm/QdW17PKvocuWnaPcdOOclM43RlKd2lbdbUQmL0Y4K8Hm9RK0MVq2l0q7t5KTluOVZtX47zSsuacWtTVi0mcVOnWjsyzW1MjuRitrZ6ItrzWpjWKpmdQSLZxW41qYxNhFGVuEVPU/Ar/TaP+f72eV3PVPAr/TaP+f72BPAAAAAAAAAAAUKlAIXH/rS+H0Rrmxj/wBaXw+iI/HzUaUm4ynstGOa7l0ebrscZ9eC320tgGro6CjSSTlJ3eZyU43k9bspa7bjaT7NTIzMY3tFefL3f5JQi9FefL3f5JQ608ezh/KoANOoAAAAAAAAAABiq4eE5QlJXdNuUPVK1r232bMoAoVAA1cTo6lWlmqRu7ZbqUo3j6Ls9a9TNiMUkklZLUktiRcAAAAAAAAAAAAAAAAAKHimM/Wqe/L6ntZ4rjFatU9+X1AwlSiKhGbC6patvQTGDmrNbV0veyCjKzNp4m0LR2vazF6660tjJVnkm7PUZYV1La8s15suh+ojZS3lLl6p3blWoqm3VP6mtKb2MxuTLZXZYhJtrJnLWywFZV2iwsVSAoeqeBP+m0f8/wB7PLLHqfgT/ptH/P8AewJ4AAAAAAAAAAChUoBC4/8AWl8PojXNjH/rS+H0RrnCfXgv+pa+IwkajTe1Ky1JrbfWUw+CjTkpJyby2d3e+zX7dRsgJst7RXny93+SUIvRXny93+SUOtPHr4fyqADTqAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAACh4rjP1qnvy+p7UeS4vQWLdWo1hqrTnJp5HsuBFAkPwLGf2tXgY/AsZ/a1eBgR4uSH4FjP7WrwMfgOM/tqvAwI8tuSX4DjP7arwMp+AYz+2q8DAjbi5I/gGM/tqvAyv4BjP7WrwMCMKkl+AYz+2q8DKfgGN/tavAwI8qjf/AMb/a1eBlXoHGf2tXgYEfJnqfgT/ptH/P97PPPwHGf2tXgZ6P4I4edLR9KFSLhNZ7xkrNeUwJoAAAAAAAAAAChUAQmP/Wl8PojXJqrgoTk5O936yz8Op+v5nOay8tuG0zMogEv+HU/X8x+HU/X8ydJT+GzW0V58vd/klDDQwkKbvG92ra2ZjdYyHfjrNa5KoANOgAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAADFziG/sY5xDf2M0SOemKarVKLTTpeVUbeqNPKpZvnJKwE/ziG/sZRV4+l2EH+MUOmUlqbadKopKztZrLdO7SSet3Vtpip6dpO+ZTjbYsk5TbzVI+ao3X6bf1sB0XOIb+xjnEN/YyGoaRpVKnJwk3Jq68iai9SbtK1m7Nar9JrYfTtKalK0lGMuTbSc26uvyIxim27K+z6OwdC68fS7CvOIb+xkBPTeHSbUpStbzac5XbhnSTS1+Tre7psVjpel5Kk3FyaSSjOSV2kszSstcktYE6q8fS7CvOIb+xkPg9IUq7apSbyqMneEo+TK+WSuldPK9aNJ6fpqThknnTatq89VeTy39fnexAdLziG/sZTl4+l2ED+OYW2blVa9r5Zbr32ebbp2F1DStOpTqzim3S5TPFa35LkrX2XeW9r9KvtAnecQ39jKKvH0uwhtG49YiDkouNpZdqaepO6a9ptgb3Lx9LsK84hv7GaAA3+cQ39jHOIb+xmgAN/nEN/YxziG/sZoADf5xDf2Mc4hv7GaAA3+cQ39jHOIb+xmgAN/nEN/YxziG/sZoADf5xDf2Mc4hv7GaAA3+cQ39jIrGeE+Go1J05Kq3Ty53GlKUVdXV2jOcTpTH1IaTrYZStRxPJU5rVqk4JRld7nb2hYz+3UPwywiSk1XUXez5GVnbbZm7o/T1DEylGHKRlBRk1OnKDtLY1f2HBUqGJq1pYKrUioYVSqTSaso6s2V9Ld+nZckvBDSlXGYnE1ar15KaiuiMM0rR9dr7Rkws9f6d1ziG/sY5xDf2M0AGW/ziG/sY5xDf2M0ABv8AOIb+xjnEN/YzQAG/ziG/sY5xDf2M0ABv84hv7GOcQ39jNAAb/OIb+xjnEN/YzQAG/wA4hv7GOcQ39jNAAb/OIb+xjnEN/YzQAG/ziG/sY5xDf2M0ABv84hv7GOcQ39jNAAb/ADiG/sY5xDf2M0ABv84hv7GOcQ39jNAAb/OIb+xjnEN/YzQAG/ziG/sY5xDf2M0CoF3JvcalXRVKcpSlTu5NuTu9bcMjvr2ZUlbZqXSSZUCKWiKSi48m2pKzbnJyeu98zd73S13vqQp6HpRaapu66XKTf+99L1/qT+ZKgCHoaHjTrcrHMrRcYw/2q6Sv7bRX831F0tDUX/8AW164zlF7W73Tvfynr3NrYSwAiZaGouOXkrRupeTKUdeRQ2p7MqSsX/hdPq93S+iSkunekSYAhsBoWNBuSzNvLbW0lGKkkkl0eU9WzdYyvRVJzzuks3KKrfX+ply3+RKACIjoWilFKm0ou8bTnq1Wstfm6tmwyQ0VTiqiVJJVU1UV3aV227q//J6+5EmAI/C4CNFNU4tXd5NylOTdkrtybb1JL4Gfk3uNkAa3JvcOTe42QBrcm9w5N7jZAGtyb3Dk3uNkAa3JvcOTe42QBrcm9w5N7jZAGtyb3Dk3uNkAa3JvcOTe42QBrcm9xw/hL4M4zEYypVpUlKElBJucVsik9TZ6CUA4DFeDuLngqdNUJc4bSrSc6eWVOF+TV79Ca+S3I3vA7QWJwk6zr08qnGCjaUZbG77H6zsgBrcm9w5N7jZAGtyb3Dk3uNkAa3JvcOTe42QBrcm9w5N7jZAGtyb3Dk3uNkAa3JvcOTe42QBrcm9w5N7jZAGtyb3Dk3uNkAa3JvcOTe42QBrcm9w5N7jZAGtyb3Dk3uNkAa3JvcOTe42QBrcm9w5N7jZAGtyb3Dk3uNkAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAYed0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAPcud0utp8ce8c7pdbT44954aAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAP/Z", - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } + "890252af17464d64ae0c21ec804bc223": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "8972fc6d2e8e4e9ea57e7cf2a61b2f01": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_0b54f345ec964ecb9cf15bd5b8ccc746", + "placeholder": "​", + "style": "IPY_MODEL_a8fa78c120d34ca1823c338dd4c5f57b", + "value": "Batches: 100%" + } + }, + "89b84e2e1b064470a9b6a0339284d09a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "8b1e4fafa4bd4ef38621db8a286d6c05": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "8b4f010e34a44f7bb4bb4587b01aea8b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_059f7a541366419b8da3b7bac5a482dd", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_fe9d81983e774e9cab05c242937458f7", + "value": 600 + } + }, + "8b947f0af507406aa2177b16d791921f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_8205e3bef7ec43549fa19653028019ac", + "placeholder": "​", + "style": "IPY_MODEL_029331ef8bd64b27a6c5385ce3e0f4b4", + "value": " 598/600 [00:24<00:00, 24.49it/s]" + } + }, + "8bdebe8c64274e19ad20e184c2034c9e": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "8cc33ef056d74afc9f3bd1b3c8988311": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "8e1fe21f6c204ba483df3999bcb48a67": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_646379c7e3aa41a588bd603d07ab8e28", + "placeholder": "​", + "style": "IPY_MODEL_78bf30aea545485484cfec8fe69a3767", + "value": "Batches: 100%" + } + }, + "8f0ef0efb0f44a7aa216208211ac49b0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "9008ee39326d432da956d9617c537f26": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "90ab04273a9e41eda658baacbac07acd": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "9137662d519043f4b63a79a1e9d42671": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_c2e32eec26bd4e86bb70b508a46e88d7", + "placeholder": "​", + "style": "IPY_MODEL_b4a6a58e517146cbad3b5ba7e8afdb98", + "value": " 3980/4000 [00:18<00:00, 209.68it/s]" + } + }, + "9594bfe8f09e4301b34cf4ea897ce6a4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "96d7c667d4264043b8bdc10cc5e211a2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "98a1068b601f4528a18d0e370561c225": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "9a1e781d578f47b79ea6bcd33171a552": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "9b19aa560c0a45b5a03976bf2ab20434": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e4ba21babc2b4397ac312efbf6c1093a", + "placeholder": "​", + "style": "IPY_MODEL_98a1068b601f4528a18d0e370561c225", + "value": "Batches: 100%" + } + }, + "9d5c9161fe064cf9baf5dc0b6a8d7890": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a04cb13e1c9946d08f2a5730574523ee": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e56f708646e241baa9688021f73e4be7", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_414eba0f0473491990dc8871529a8907", + "value": 600 + } + }, + "a30b5754bc1c49e7a0d6c0cda84a23e9": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a3693a9258aa4e85869f01e763f41a63": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_65e00761711a44d58f234fb932268eb5", + "placeholder": "​", + "style": "IPY_MODEL_3a259488152f431498bcd9adc731f89d", + "value": "Epoch: 100%" + } + }, + "a7501605ea394d47884111fdb2de00ea": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_441952e7c48e4366a3044537aadb330b", + "max": 1875, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_f8a4466e613344cd9a0f4f654726d3e7", + "value": 1875 + } + }, + "a86cf0c588534aa69cb41b4fa42b9d59": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "a8fa78c120d34ca1823c338dd4c5f57b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "a9c0ce203d234c5581feb0845d185524": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_e25987997fef4a44ba5a9c03a2c84622", + "placeholder": "​", + "style": "IPY_MODEL_cc5557baaa5a4c9498723e9a84bb3cfe", + "value": "Batches: 100%" + } + }, + "b002b4b85c7e4d9aa3d86791a5b2f801": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "b1b73880981d4869b77a8458be0073c6": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b1e189b199bc490eafc7eb2ecc1daaf5": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b41a6b9583f3436a9701983187e7a923": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "b4a6a58e517146cbad3b5ba7e8afdb98": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "b760230d392f4204b88d998f0c516a98": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b79e494f2e474a42a5c4f871dae09dd9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "b86732b760144edbb430e2052bb29813": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "b98dac30df354891a42fc170b5cd52b4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a9c0ce203d234c5581feb0845d185524", + "IPY_MODEL_653ae70ab5a14a8bb6d43144ee326c9d", + "IPY_MODEL_f25a6ad483ea48f69b8a77688020f790" ], - "source": [ - "#@title Video: Wrapping up and interesting VAE examples\n", - "\n", - "video = YouTubeVideo(id=\"IDTq8muSySQ\", width=854, height=480, fs=1)\n", - "print(\"Video available at https://youtube.com/watch?v=\" + video.id)\n", - "\n", - "video" - ] + "layout": "IPY_MODEL_2633a921fcca4d0c90f5827d84f190f4" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "P5-HZSWcCbr3" - }, - "source": [ - "---\n", - "# Submit responses" - ] + "c121d101a456463285a86a5d55373e43": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 421 - }, - "id": "FCJJf7OFk8SU", - "outputId": "828b9a4c-6a0a-4f7f-8319-cb9626f8bee5" - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } + "c18de5d78e7b41949d6956bd87bff700": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_3e2d6740b993473bb7691d7773baa74b", + "placeholder": "​", + "style": "IPY_MODEL_77401b52c114406a9c596e02c8420951", + "value": " 599/600 [00:24<00:00, 24.37it/s]" + } + }, + "c2e32eec26bd4e86bb70b508a46e88d7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "c4e8724ef9594d69b18fb1b33d7989cd": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "cb2b4a308ee64751988432c423e3bb4d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_89b84e2e1b064470a9b6a0339284d09a", + "placeholder": "​", + "style": "IPY_MODEL_f938e62be3764dfeba067e9812f4cae0", + "value": " 10/10 [04:07<00:00, 24.90s/it]" + } + }, + "cb574ed2062d4ba2b62b5b333be30f45": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "cc5557baaa5a4c9498723e9a84bb3cfe": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "cced2bb02ef74f6283ea2ed19ed83f43": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_a86cf0c588534aa69cb41b4fa42b9d59", + "placeholder": "​", + "style": "IPY_MODEL_692db0c9d7c54bf68ff111c33e96e496", + "value": " 20/20 [02:44<00:00, 8.32s/it]" + } + }, + "ccf2b5165b494751bdf71b54b9cc66fb": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "cd1273324d0e47a183807c6eeca6ec0e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_6366e4a1c096487681a79cc77d71a523", + "IPY_MODEL_0ed1ed13153041109c3e4d172581cab8", + "IPY_MODEL_2f7962d587a648e690982ffe1fc252e8" ], - "source": [ - "import time\n", - "import numpy as np\n", - "from IPython.display import IFrame\n", - "#@markdown #Run Cell to Show Airtable Form\n", - "#@markdown Confirm your answers and then click \"Submit\". \n", - "# If you're having issues, use this link and manually fill in your answers: https://airtable.com/shrh6lPiM4PlflEzj\n", - "\n", - "def prefill_form(src, fields: dict):\n", - " '''\n", - " src: the original src url to embed the form\n", - " fields: a dictionary of field:value pairs,\n", - " e.g. {\"pennkey\": my_pennkey, \"location\": my_location}\n", - " '''\n", - " prefills = \"&\".join([\"prefill_%s=%s\"%(key, fields[key]) for key in fields])\n", - " src = src + prefills\n", - " src = \"+\".join(src.split(\" \"))\n", - " return src\n", - "\n", - "#autofill time if it is not present\n", - "try: t0;\n", - "except NameError: t0 = time.time()\n", - "try: t1;\n", - "except NameError: t1 = time.time()\n", - "\n", - "#autofill fields if they are not present\n", - "#a missing pennkey and pod will result in an Airtable warning\n", - "#which is easily fixed user-side.\n", - "try: my_pennkey;\n", - "except NameError: my_pennkey = \"\"\n", - "\n", - "try: my_pod;\n", - "except NameError: my_pod = \"Select\"\n", - "\n", - "try: my_email;\n", - "except NameError: my_email = \"\"\n", - "\n", - "try: linear_ae_vs_pca;\n", - "except NameError: linear_ae_vs_pca = \"\"\n", - "\n", - "try: interp_observations;\n", - "except NameError: interp_observations = \"\"\n", - "\n", - "times = np.array([t1])-t0\n", - "\n", - "fields = {\"pennkey\": my_pennkey,\n", - " \"pod\": my_pod,\n", - " \"tutorial\": tutorial,\n", - " \"email\": my_email,\n", - " \"linear_ae_vs_pca\": linear_ae_vs_pca,\n", - " \"interp_observations\": interp_observations,\n", - " \"cumulative_times\": times}\n", - "\n", - "src = \"https://airtable.com/embed/shrh6lPiM4PlflEzj?\"\n", - "\n", - "#now instead of the original source url, we do: src = prefill_form(src, fields)\n", - "display(IFrame(src = prefill_form(src, fields), width = 800, height = 400))\n" - ] + "layout": "IPY_MODEL_b1b73880981d4869b77a8458be0073c6" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "HKn5d3CCC05w" - }, - "source": [ - "## Feedback\n", - "How could this session have been better? How happy are you in your group? How do you feel right now?\n", - "\n", - "Feel free to use the embeded form below or use this link:\n", - "https://airtable.com/shr1TzujOOOY21kFQ" - ] + "cef45f2502b24609af4c9162442a15ab": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "cellView": "form", - "colab": { - "base_uri": "https://localhost:8080/", - "height": 421 - }, - "id": "HIvhG6VZ8zez", - "outputId": "66162276-6279-493a-ee7c-dad77edc0afc" - }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " " - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } + "d044017d68d34b78a7366a235769c2dc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_6c2e4d62cdfc4e4eab0832dc49d577bc", + "max": 20, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_633885d3801d4f9b89e7040a2dcbbe6d", + "value": 20 + } + }, + "d15d1a79f8d74a5eafaa85a11db1d8df": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d6b5e3a56ea248aeb55c4ae76aec0002": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "d825e4a7719649f7b5a8f5bb2e8ccef4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_311f5429f3b146edbc9b8f6f528681d1", + "placeholder": "​", + "style": "IPY_MODEL_76952d837cf7418795fb34158c80bd27", + "value": "Computing pixel mean and covariance...: 99%" + } + }, + "d8d7f92934f94acd94d87b72b40852f1": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "da343bece953454fa206c38c28f8d9ff": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "dcd7f5ddaa9c4541b8b483f8f97ea4b1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_712fe0055d7b454f8d342ef3ca68d830", + "IPY_MODEL_01ce56b63fd84c5eb054d3756df55322", + "IPY_MODEL_0be5d717250d4ac9ae9212cb5abce1cb" ], - "source": [ - "# @title Feedback form\n", - "display(IFrame(src=\"https://airtable.com/embed/shr1TzujOOOY21kFQ\", width = 800, height = 400))" - ] + "layout": "IPY_MODEL_9a1e781d578f47b79ea6bcd33171a552" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "3yqyggnJTFsv" - }, - "source": [ - "---\n", - "# Appendices" - ] + "e13fa64818ab41d68a65a73312572c99": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "_eIXWPrUa68q" - }, - "source": [ - "## Appendix A: Formalizing the problem and deriving the ELBO\n", - "\n", - "### Part A.1: maximum likelihood with neural networks\n", - "\n", - "Let's state clearly the goal of learning a density network:\n", - "\n", - "__Given:__\n", - "\n", - "1. A latent space $\\mathbf{z} \\in \\mathbb{R}^K$ with prior $p(\\mathbf{z})$\n", - "2. Data points, $\\lbrace{\\mathbf{x}_1, \\mathbf{x}_2, \\ldots, \\mathbf{x}_N\\rbrace}$ that live in $\\mathbb{R}^P$ drawn (iid) from some unknown distribution $p_{true}(\\mathbf{x})$ for instance, a set of training images sampled from the world, where $P$ is the number of pixels $\\times$ color channels per image (e.g. $P=1\\times 28 \\times 28 = 784$ for MNIST, and $P=3\\times 32 \\times 32 = 3072$ for CIFAR).\n", - "3. A differentiable function (a neural network, say) with parameters $\\mathbf{w}$ that maps from $\\mathbb{R}^K$ to $\\mathbb{R}^P$, $$\\mathbf{x} = f(\\mathbf{z};\\mathbf{w}) \\, .^\\dagger$$ The decoder part of the AutoEncoder is an example of such an $f$.\n", - "4. A \"noise model\" on $\\mathbf{x}$. Often this is simply chosen to be independent Gaussian pixel noise with $f(\\mathbf{z};\\mathbf{w})$ as the mean: $$p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) = \\mathcal{N}\\left(f(\\mathbf{z};\\mathbf{w}), \\sigma^2_x\\mathbf{I}_P\\right)$$\n", - "where $\\mathbf{I}_P$ is the $P\\times P$ identity matrix and is used to express the assumption that noise is independent across pixels.$^*$\n", - "\n", - "Given all of this, a density network defines a distribution on $\\mathbf{x}$:\n", - "$$p(\\mathbf{x};\\mathbf{w}) \\equiv \\int p(\\mathbf{z}) p(\\mathbf{x}|\\mathbf{z};\\mathbf{w}) \\, {\\rm d}\\mathbf{z} \\, .$$\n", - "\n", - "Now, we can succinctly state that the __goal__ of learning a density network is to minimize the KL divergence from $p(\\mathbf{x};\\mathbf{w})$ to $p_{true}(\\mathbf{x})$, or equivalently, to maximize the likelihood\n", - "$$\\mathbf{w}^* = \\arg\\max_\\mathbf{w} \\sum_{i=1}^N \\log p(\\mathbf{x}_i;\\mathbf{w}) \\, .$$\n", - "\n", - "But this is hard to do and requires approximations, which leads us to the ELBO.\n", - "\n", - "---\n", - "\n", - "### Part A.2: ELBO Derivation\n", - "\n", - "The goal of training a density net is to maximize the (log) likelihood of points in the training set, or\n", - "$$\\sum_{i=1}^N \\log p(\\mathbf{x}_i;\\mathbf{w}) \\, .$$\n", - "\n", - "We already know all about minimizing sums of losses (e.g. minibatching and SGD), so let's focus on the loss for a single data point, $\\log p(\\mathbf{x}_i;\\mathbf{w})$. With a bit of algebraic sleight of hand, we can pull out a $\\mathbf{z}$ and start turning this into something more tractable$^\\#$:\n", - "$$\\log p(\\mathbf{x}_i) = \\log \\left[ p(\\mathbf{x}_i) \\frac{p(\\mathbf{z}|\\mathbf{x}_i)}{p(\\mathbf{z}|\\mathbf{x}_i)} \\right]\\qquad\\text{for all $\\mathbf{z}$}$$\n", - "This step introduced a $\\mathbf{z}$ out of nowhere. Since we are effectively multiplying and dividing by $1$, this holds no matter what $\\mathbf{z}$ we plug in (we'll just ignore the possibility that $p(\\mathbf{z}|\\mathbf{x}_i)=0$). Next, we'll introduce a brand new auxiliary distribution, $q(\\mathbf{z})$, and integrate it:\n", - " $$\\ldots = \\int q(\\mathbf{z}) \\log \\left[ p(\\mathbf{x}_i) \\frac{p(\\mathbf{z}|\\mathbf{x}_i)}{p(\\mathbf{z}|\\mathbf{x}_i)} \\right] {\\rm d} \\mathbf{z}$$\n", - "This step initially seems odd: do we really get to pick _any_ $q(\\mathbf{z})$ here? It works because we took an expression that was true _for all $\\mathbf{z}$_, i.e. a constant function of $\\mathbf{z}$, and integrated it with an arbitrary distribution on $\\mathbf{z}$, which by definition has to integrate to its constant integrand. \n", - "\n", - "Next, we'll sneak $q$ inside the $\\log$ using the same trick that got $p(\\mathbf{z}|\\mathbf{x}_i)$ in there, and we'll combine $p(\\mathbf{z}|\\mathbf{x}_i)p(\\mathbf{x}_i)$ into a single $p(\\mathbf{x}_i,\\mathbf{z})$:\n", - " $$\\ldots = \\int q(\\mathbf{z}) \\log \\left[ \\frac{p(\\mathbf{x}_i,\\mathbf{z})}{p(\\mathbf{z}|\\mathbf{x}_i)}\\frac{q(\\mathbf{z})}{q(\\mathbf{z})} \\right] {\\rm d} \\mathbf{z}$$\n", - "If you are beginning to think that this looks a bit like KL-divergence, then you would be right! Let's complete the transformation by pulling out $KL$:\n", - "$$\\log p(\\mathbf{x}_i) = KL\\left(q(\\mathbf{z})||p(\\mathbf{z}|\\mathbf{x}_i)\\right) + \\underbrace{\\int q(\\mathbf{z}) \\log \\left[ \\frac{p(\\mathbf{x}_i,\\mathbf{z})}{q(\\mathbf{z})} \\right] {\\rm d} \\mathbf{z}}_\\text{ELBO}$$\n", - "\n", - "Re-arranging, notice that\n", - "$$\\text{ELBO} = \\log p(\\mathbf{x}_i) - KL\\left(q(\\mathbf{z})||p(\\mathbf{z}|\\mathbf{x}_i)\\right) \\, .$$\n", - "We can get a lot of intuition out of this one expression. First, maximizing the ELBO has two effects, since there are two terms on the right hand side. The first effect is to make $KL(q(z)||p(z|x))$ smaller, which means that by maximizing the ELBO, $q$ becomes a better approximation to the true posterior distribution over $z$. If $q$ were a _perfect fit_, that is if $q(z) = p(z|x)$, then maximizing the ELBO would be _equivalent_ to maximizing the thing we set out to maximize: the log likelihood of the data. Put another way: once $q$ is a good approximation to the posterior $p(z|x)$, then maximizing the ELBO makes $p(x|z)$ a better _generative_ model.\n", - "\n", - "The ELBO gets its name because it is a **Lower BOund** on the **Evidence**. \"Evidence\" is just another term for the log likelihood, or $\\log p(\\mathbf{x}_i)$. We know that it is a lower bound beause $KL$ is always non-negative. This one formula is the work-horse of nearly all variational inference:\n", - "$$\\color{red}{\\log p(\\mathbf{x}_i) \\geq \\underbrace{\\int q(\\mathbf{z}) \\log \\left[ \\frac{p(\\mathbf{x}_i,\\mathbf{z})}{q(\\mathbf{z})} \\right] {\\rm d} \\mathbf{z}}_\\text{ELBO}}$$\n", - "\n", - "\n", - "\n", - "Note that other texts often derive the ELBO in fewer steps using Jensen's inequality, but arguably some of the clarity and cleverness of the whole idea is lost when done that way. Here, we see behind the curtain a bit more: we see that $q(\\mathbf{z})$ was introduced as a totally arbitrary distribution, but that we do \"better\" by making it agree more closely with $p(\\mathbf{z}|\\mathbf{x};\\mathbf{w})$. We also see where the \"Lower BOund\" comes from: the ELBO is always a lower bound on $\\log p(\\mathbf{x}_i; \\mathbf{w})$ precisely because $KL(q(\\mathbf{z})||p(\\mathbf{z}|\\mathbf{x}_i;\\mathbf{w}))$ is always positive. In fact, this tells us that the ELBO is **equal** to the log likelihood of the data (the bound is \"tight\") when $q(\\mathbf{z})$ is equal to the correct posterior on $\\mathbf{z}$, i.e. when $q(\\mathbf{z}) = p(\\mathbf{z}|\\mathbf{x}_i)$. This means we can think about the problem of creating \"tighter bounds\" as a problem of making $q(\\mathbf{z})$ closer to $p(\\mathbf{z}|\\mathbf{x}_i)$.\n", - "\n", - "---\n", - "\n", - "$^\\dagger$ A notational convention is that $p(a|b)$ is used when $a$ and $b$ are both random variables and $a$ is \"conditioned on\" $b$, while $p(a;c)$ is used when $c$ is not a random variable, but a parameter controlling the shape of the distribution. This is sometimes written $p_c(a)$.\n", - "\n", - "$^*$ In practice, we don't explicitly use $\\mathbf{I}_P$. The assumption that pixel noise is independent instead appears as a sum of log-likelihoods per pixel.\n", - "\n", - "$^\\#$ these derivations drop the \"$\\mathbf{w}$\" from all $p$s just to reduce clutter." - ] + "e25987997fef4a44ba5a9c03a2c84622": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "jDXSWpZoqlxb" - }, - "source": [ - "## Appendix B: Tricks\n", - "\n", - "There are a few \"tricks\" behind VAEs in particular had a big impact on the field, and in this lesson we haven't dived into all of the interesting and non-obvious details.\n", - "\n", - "1. The first \"trick\" was to recognize that the ELBO contains a \"reconstruction\" term and a \"regularization\" term, and that this naturally maps onto a kind of regularized auto-encoder. The original VAE paper is \"Auto-Encoding Variational Bayes\" because Variational Bayes and the ELBO had existed previously, but this was the first time it was built end-to-end with neural networks.\n", - "\n", - "2. The second \"trick\" we introduced above without talking about it is the __reparameterization trick__. When we computed the ELBO, we simply called\n", - "\n", - " zs = rsample(phi, n)\n", - " elbo = log_p_x(...) - kl_q_p(...)\n", - "\n", - " where each `...` depended on the sampled `zs`. Something sneaky is happening inside `rsample` which allows us to use Monte Carlo estimates of $\\mathbb{E}_{q(\\mathbf{z};\\phi)}[\\ldots]$ (as in the ELBO) but then take gradients of all of it with respect to $\\phi$. Inside the `torch.distributions` package, you'll find both `sample` and `rsample` functions. The key difference is that you can take gradients through `rsample` but not through `sample`. Magic! (The \"r\" in \"rsample\" stands for \"reparameterized sample\".)\n", - "\n", - " For some extra history, before this simple trick came along, people generally thought of taking gradients with respect to $\\phi$ in this kind of example as a hard problem. Keyword to search: score function estimators. Or see [here](http://blog.shakirm.com/2015/10/machine-learning-trick-of-the-day-4-reparameterisation-tricks/) and [here](http://blog.shakirm.com/2015/11/machine-learning-trick-of-the-day-5-log-derivative-trick/) for some blog posts on the topic.\n", - "\n", - "3. The third \"trick\" was when we stopped taking gradients of $\\phi$ directly and instead used a __recognition model__ to map from $\\mathbf{x}$ to $\\phi$. This trick is also called \"amortized inference\" since the recognition model learns _on average_ to produce an estimate of $\\phi$ for each $\\mathbf{x}$." - ] + "e3ef8be847324359a83fdb22622956d4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "ILEgdYHaeRK-" - }, - "source": [ - "## Appendix C: fraction of variance, eigenspectra, and selecting $K$\n", - "\n", - "**tl;dr** one heuristic for choosing $K$ is to look at how much of the total variance in the data lies in the first $K$ principal components. But despite comparable variance-vs-K curves, you'll find that MNIST digits are legible with $K \\approx 15$ while CIFAR images are unrecognizable until about $K \\approx 80$. Reality is more complicated than percent variance explained!" - ] + "e4ba21babc2b4397ac312efbf6c1093a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "markdown", - "metadata": { - "id": "4g9HMk2Qw3_g" - }, - "source": [ - "Let's pause to think about our choice of the dimensionality of the bottleneck layer, $\\mathbf{h}\\in\\mathbb{R}^K$. Dimensionality reduction by PCA works by projecting images onto the eigenvectors of the pixel covariance that have the largest eigenvalues. These eigenvalues, in turn, represent the amount of variance in the data along each of those vectors. So, we can visualize a rough, *linear* estimate of the intrinsic dimensionality of our datset by looking at its *eigenspectrum*.\n", - "\n", - "Imagine we have a 3-dimensional dataset, and the eigenvalues of the covariance are, in descending order, $[3, 2, 1]$. Then the total variance would be $3+2+1=6$, and we would say that the first principal component accounts for $3/6=50\\%$ of the total variance, while the first $K=2$ principal components account for a total of $(3+2)/6=83.3\\%$ of the total variance.\n", - "\n", - "MNIST is $28\\times 28 = 784$-dimensional, and CIFAR is $32\\times 32\\times 3=3072$-dimensional. The following plot estimates the _fraction_ of that variance distributed across the first $K$ modes." - ] + "e56f708646e241baa9688021f73e4be7": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "colab": { - "base_uri": "https://localhost:8080/", - "height": 430 - }, - "id": "8llUJ9kkfKdX", - "outputId": "fc730ae6-b7df-42a0-dda4-ecf138e44d78" - }, - "outputs": [ - { - "data": { - "image/png": "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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "image/png": { - "height": 413, - "width": 558 - }, - "needs_background": "light" - }, - "output_type": "display_data" - } + "e72254b889824fc7a175dffda4291657": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "e856ef4698c94b79bdc559f91b710b17": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "ProgressView", + "bar_style": "", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_2a3af2976d7644718b2381a51799b0f3", + "max": 600, + "min": 0, + "orientation": "horizontal", + "style": "IPY_MODEL_cb574ed2062d4ba2b62b5b333be30f45", + "value": 600 + } + }, + "ea335e3e8b7a425995f4aaca9899a018": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "ee3c86fd9cf1443c8a1fe7e4ef5e00b0": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "f122311b612d4249a08d72b7b55714f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_06a120793142465fbd3b12cab677cc09", + "IPY_MODEL_7916f752329348cb814eff14758a3b0a", + "IPY_MODEL_43b2acb6a30c40d18ec70ffbd288675f" ], - "source": [ - "def plot_fraction_variance_eigenspectrum(cov, max_K=200, annotate_K=None, ax=None):\n", - " ax = plt.gca() if ax is None else ax\n", - " _, s, _ = torch.svd_lowrank(cov, q=max_K)\n", - " rank = torch.arange(max_K+1)\n", - " total_variance = cov.diag().sum()\n", - " frac_variance = torch.cat([torch.zeros((1,)), torch.cumsum(s, dim=0) / total_variance])\n", - " line = ax.plot(rank[:max_K], frac_variance[:max_K])\n", - " if annotate_K is not None:\n", - " y = frac_variance[K]\n", - " ax.plot([K, K], [0, y], '-r')\n", - " ax.plot([0, K], [y, y], '-r')\n", - " ax.text(x=K+.5, y=y-.03, s=f'{100*y:.1f}% at K={K}')\n", - " return line\n", - "\n", - "plot_fraction_variance_eigenspectrum(cov, annotate_K=K)\n", - "plt.ylim([0., 1.])\n", - "plt.grid()\n", - "plt.xlabel('number of hidden dimensions (K)')\n", - "plt.ylabel('fraction of variance accounted for')\n", - "plt.title(f'% variance in top K dimensions for {my_dataset_name}')\n", - "plt.show()" - ] - } - ], - "metadata": { - "accelerator": "GPU", - "colab": { - "collapsed_sections": [ - "VVCR7EVyFkWS" + "layout": "IPY_MODEL_0ff62aa332e94a4381f78edf90fcb014" + } + }, + "f19cf785ca1d4e00b46193b7a0c98a81": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_74dc5373e7d34b5eb0d391c015603191", + "IPY_MODEL_59df81b1dd7f414ca1e1d009f222cfa3", + "IPY_MODEL_cb2b4a308ee64751988432c423e3bb4d" ], - "machine_shape": "hm", - "name": "CIS_522_W8D1_Tutorial_–_TA_Version.ipynb", - "provenance": [], - "toc_visible": true - }, - "kernel": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "kernelspec": { - "display_name": "Python 3", - "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": "3.10.6" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "01ce56b63fd84c5eb054d3756df55322": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_c121d101a456463285a86a5d55373e43", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_551623ea5966495a8377a4b05a5aef12", - "value": 600 - } - }, - "029331ef8bd64b27a6c5385ce3e0f4b4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "04e9719240b14b3385c8cf2334fdcbe2": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_b1e189b199bc490eafc7eb2ecc1daaf5", - "placeholder": "​", - "style": "IPY_MODEL_2ba5313ece19405daadd3a3a4d5734a3", - "value": "Batches: 100%" - } - }, - "059f7a541366419b8da3b7bac5a482dd": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "0661ed223ab04813b9648f4bb65c2d06": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "06a120793142465fbd3b12cab677cc09": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_35bb8a89785648afa099763e8703d4a8", - "placeholder": "​", - "style": "IPY_MODEL_527a4fdd54cc445c9a8922dc9006bf4b", - "value": "Batches: 100%" - } - }, - "08bba96f8f9d4737a949725883a92671": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "0a068f4e30b8480aa1a71db83f15d638": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_fe9ae7dcf5184f49b9c962101ba67d91", - "placeholder": "​", - "style": "IPY_MODEL_205536ba56b9456ab9fa114825753a24", - "value": "Batches: 100%" - } - }, - "0aaadb652a6341f7ae4b6d0e1c8ac66f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_04e9719240b14b3385c8cf2334fdcbe2", - "IPY_MODEL_63b7bbe958834089988377ef880e1818", - "IPY_MODEL_569c655751824fc59b479f2e4e27e118" - ], - "layout": "IPY_MODEL_890252af17464d64ae0c21ec804bc223" - } - }, - "0b54f345ec964ecb9cf15bd5b8ccc746": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "0bc4e7bf12e041598fea2dd433ddb6f2": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_4dba7c97bf8045bbbfaf0767ac27120f", - "IPY_MODEL_39ec691122e94b0bad070ea86d8391ca", - "IPY_MODEL_cced2bb02ef74f6283ea2ed19ed83f43" - ], - "layout": "IPY_MODEL_ccf2b5165b494751bdf71b54b9cc66fb" - } - }, - "0be5d717250d4ac9ae9212cb5abce1cb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_4f5e66ca82e7467d90d745730dc4a094", - "placeholder": "​", - "style": "IPY_MODEL_96d7c667d4264043b8bdc10cc5e211a2", - "value": " 598/600 [00:24<00:00, 24.27it/s]" - } - }, - "0d7f6e08f26c4b6abd8ccee2ec192ac6": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "0ed1ed13153041109c3e4d172581cab8": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_9d5c9161fe064cf9baf5dc0b6a8d7890", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_b41a6b9583f3436a9701983187e7a923", - "value": 600 - } - }, - "0ff62aa332e94a4381f78edf90fcb014": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "133816fc0030431c956f341668c47169": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_80e9fec5ea3449a3a6cc6b75a1771eaa", - "IPY_MODEL_5959b45ae4dd426382e216012ea1d126", - "IPY_MODEL_c18de5d78e7b41949d6956bd87bff700" - ], - "layout": "IPY_MODEL_b760230d392f4204b88d998f0c516a98" - } - }, - "147167a175d94e89b91c9e4744c80599": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "155141fa19624e508d2f53184fba8931": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_8972fc6d2e8e4e9ea57e7cf2a61b2f01", - "IPY_MODEL_8b4f010e34a44f7bb4bb4587b01aea8b", - "IPY_MODEL_38c277f235854dd8b4f3aca5ca367e91" - ], - "layout": "IPY_MODEL_3ebe6f717c8543a482d4e139ac7e855d" - } - }, - "1ab8190bf5114ab89713358df63b2ec2": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "204ccffdfba6474bbd2041c81c17dc45": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "205536ba56b9456ab9fa114825753a24": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "22c8ca666f614b7dbb9ac0fa3f4e095a": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_a30b5754bc1c49e7a0d6c0cda84a23e9", - "placeholder": "​", - "style": "IPY_MODEL_6067d9f4878e4a7597d7980fb4f57457", - "value": " 1857/1875 [00:10<00:00, 192.86it/s]" - } - }, - "2633a921fcca4d0c90f5827d84f190f4": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "26a194907cc54022ac497a546d04f488": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "29d32c83475c403b9bc384a09781c725": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "2a3af2976d7644718b2381a51799b0f3": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "2ba5313ece19405daadd3a3a4d5734a3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "2c78fe51f8b74c6aae1d9a4dc5a61d61": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_8e1fe21f6c204ba483df3999bcb48a67", - "IPY_MODEL_61f424d1767044c19cd4aad5ebc13dc6", - "IPY_MODEL_815caee749e74ce6839ab10f7cd74c09" - ], - "layout": "IPY_MODEL_ee3c86fd9cf1443c8a1fe7e4ef5e00b0" - } - }, - "2f7962d587a648e690982ffe1fc252e8": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_74e2292262954ece8066361b76cb299c", - "placeholder": "​", - "style": "IPY_MODEL_37a14ff89dee477b8097c8f167111871", - "value": " 598/600 [00:25<00:00, 23.85it/s]" - } - }, - "311f5429f3b146edbc9b8f6f528681d1": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "34183fa0c5d14e6381b21394365ab92d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_8f0ef0efb0f44a7aa216208211ac49b0", - "placeholder": "​", - "style": "IPY_MODEL_404f2d1a05e649f590d668c6bf759179", - "value": " 598/600 [00:25<00:00, 23.95it/s]" - } - }, - "35bb8a89785648afa099763e8703d4a8": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "374d595cfc1748cb80d6384791588795": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_d15d1a79f8d74a5eafaa85a11db1d8df", - "placeholder": "​", - "style": "IPY_MODEL_cef45f2502b24609af4c9162442a15ab", - "value": "100%" - } - }, - "37a14ff89dee477b8097c8f167111871": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "38c277f235854dd8b4f3aca5ca367e91": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_3f3a533f2bc942478a0efadd5cde2f10", - "placeholder": "​", - "style": "IPY_MODEL_e3ef8be847324359a83fdb22622956d4", - "value": " 599/600 [00:24<00:00, 24.58it/s]" - } - }, - "39ec691122e94b0bad070ea86d8391ca": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_8cc33ef056d74afc9f3bd1b3c8988311", - "max": 20, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_204ccffdfba6474bbd2041c81c17dc45", - "value": 20 - } - }, - "3a259488152f431498bcd9adc731f89d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "3d21e3947dc04917a814c6f2d04ccefb": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "3e2d6740b993473bb7691d7773baa74b": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "3ebe6f717c8543a482d4e139ac7e855d": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "3f3a533f2bc942478a0efadd5cde2f10": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "404f2d1a05e649f590d668c6bf759179": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "414eba0f0473491990dc8871529a8907": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "42b8cc64de9546e1bb8a2b852a417279": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_0661ed223ab04813b9648f4bb65c2d06", - "max": 4000, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_6774ef7b87f24ad8a5602c5a7595938e", - "value": 4000 - } - }, - "43b2acb6a30c40d18ec70ffbd288675f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_3d21e3947dc04917a814c6f2d04ccefb", - "placeholder": "​", - "style": "IPY_MODEL_ea335e3e8b7a425995f4aaca9899a018", - "value": " 599/600 [00:24<00:00, 24.51it/s]" - } - }, - "43c8e2457cba4fdc937bdb37a8575e29": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "441952e7c48e4366a3044537aadb330b": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "49e1682fc7bb47c7b297d0c1f042919c": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_8b1e4fafa4bd4ef38621db8a286d6c05", - "placeholder": "​", - "style": "IPY_MODEL_f943a6707a2746668cc897d3b5378ab7", - "value": " 20/20 [03:18<00:00, 9.90s/it]" - } - }, - "4dba7c97bf8045bbbfaf0767ac27120f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_ffcab833aec74408b5cca57f090ec931", - "placeholder": "​", - "style": "IPY_MODEL_e13fa64818ab41d68a65a73312572c99", - "value": "Epoch: 100%" - } - }, - "4f5e66ca82e7467d90d745730dc4a094": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "52064c4872c843c4bcfedfe12a4d1213": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "527a4fdd54cc445c9a8922dc9006bf4b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "54f2282cf9a040fd84cc4861fac08efb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_9b19aa560c0a45b5a03976bf2ab20434", - "IPY_MODEL_e856ef4698c94b79bdc559f91b710b17", - "IPY_MODEL_8b947f0af507406aa2177b16d791921f" - ], - "layout": "IPY_MODEL_6b497d8b2a804e1883e1711cb84fec90" - } - }, - "551623ea5966495a8377a4b05a5aef12": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "569c655751824fc59b479f2e4e27e118": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_d6b5e3a56ea248aeb55c4ae76aec0002", - "placeholder": "​", - "style": "IPY_MODEL_b79e494f2e474a42a5c4f871dae09dd9", - "value": " 599/600 [00:25<00:00, 24.02it/s]" - } - }, - "5959b45ae4dd426382e216012ea1d126": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_fbcefc642f18403db6d8c816131b3b0e", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_08bba96f8f9d4737a949725883a92671", - "value": 600 - } - }, - "597c6657347441e68304cf74d4c6a217": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "59df81b1dd7f414ca1e1d009f222cfa3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_d8d7f92934f94acd94d87b72b40852f1", - "max": 10, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_c4e8724ef9594d69b18fb1b33d7989cd", - "value": 10 - } - }, - "5cbbe232d6124c6aaad533dae40de75e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0a068f4e30b8480aa1a71db83f15d638", - "IPY_MODEL_a04cb13e1c9946d08f2a5730574523ee", - "IPY_MODEL_34183fa0c5d14e6381b21394365ab92d" - ], - "layout": "IPY_MODEL_da343bece953454fa206c38c28f8d9ff" - } - }, - "5dd6c30df3d943888ac630d68f84f948": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "6067d9f4878e4a7597d7980fb4f57457": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "61f424d1767044c19cd4aad5ebc13dc6": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_147167a175d94e89b91c9e4744c80599", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_9008ee39326d432da956d9617c537f26", - "value": 600 - } - }, - "633885d3801d4f9b89e7040a2dcbbe6d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "6366e4a1c096487681a79cc77d71a523": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_71419896de504961bc169af2ebb40a01", - "placeholder": "​", - "style": "IPY_MODEL_7447e907d8154178bb40a37ee73d5ba9", - "value": "Batches: 100%" - } - }, - "63b7bbe958834089988377ef880e1818": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_26a194907cc54022ac497a546d04f488", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_863a55349a074ce489590a9c7b56f1e7", - "value": 600 - } - }, - "646379c7e3aa41a588bd603d07ab8e28": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "6514dcde9f6a4970becfd4d314e30b4f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "653ae70ab5a14a8bb6d43144ee326c9d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_b86732b760144edbb430e2052bb29813", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_5dd6c30df3d943888ac630d68f84f948", - "value": 600 - } - }, - "65e00761711a44d58f234fb932268eb5": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "6774ef7b87f24ad8a5602c5a7595938e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "692db0c9d7c54bf68ff111c33e96e496": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "69b3eb3b86c0451984fc07a02958dd45": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "6b497d8b2a804e1883e1711cb84fec90": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "6c2e4d62cdfc4e4eab0832dc49d577bc": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "712fe0055d7b454f8d342ef3ca68d830": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_29d32c83475c403b9bc384a09781c725", - "placeholder": "​", - "style": "IPY_MODEL_43c8e2457cba4fdc937bdb37a8575e29", - "value": "Batches: 100%" - } - }, - "71419896de504961bc169af2ebb40a01": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "7447e907d8154178bb40a37ee73d5ba9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "74dc5373e7d34b5eb0d391c015603191": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_fadffa82791e4fb5a59e27ace0f46374", - "placeholder": "​", - "style": "IPY_MODEL_0d7f6e08f26c4b6abd8ccee2ec192ac6", - "value": "Epochs: 100%" - } - }, - "74e2292262954ece8066361b76cb299c": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "7548747e11ad4c6aa8dccc9de8328f7d": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "76952d837cf7418795fb34158c80bd27": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "77401b52c114406a9c596e02c8420951": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "78bf30aea545485484cfec8fe69a3767": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "7916f752329348cb814eff14758a3b0a": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_8bdebe8c64274e19ad20e184c2034c9e", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_9594bfe8f09e4301b34cf4ea897ce6a4", - "value": 600 - } - }, - "7c61ec46b16c430b83c7fc7839ae5815": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_a3693a9258aa4e85869f01e763f41a63", - "IPY_MODEL_d044017d68d34b78a7366a235769c2dc", - "IPY_MODEL_49e1682fc7bb47c7b297d0c1f042919c" - ], - "layout": "IPY_MODEL_52064c4872c843c4bcfedfe12a4d1213" - } - }, - "80e074ada4d642d58c690fdd14020d13": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_d825e4a7719649f7b5a8f5bb2e8ccef4", - "IPY_MODEL_a7501605ea394d47884111fdb2de00ea", - "IPY_MODEL_22c8ca666f614b7dbb9ac0fa3f4e095a" - ], - "layout": "IPY_MODEL_69b3eb3b86c0451984fc07a02958dd45" - } - }, - "80e9fec5ea3449a3a6cc6b75a1771eaa": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_e72254b889824fc7a175dffda4291657", - "placeholder": "​", - "style": "IPY_MODEL_b002b4b85c7e4d9aa3d86791a5b2f801", - "value": "Batches: 100%" - } - }, - "815caee749e74ce6839ab10f7cd74c09": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_1ab8190bf5114ab89713358df63b2ec2", - "placeholder": "​", - "style": "IPY_MODEL_6514dcde9f6a4970becfd4d314e30b4f", - "value": " 598/600 [00:25<00:00, 23.96it/s]" - } - }, - "8205e3bef7ec43549fa19653028019ac": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "83e45f5dd5b144018e175f6753b389de": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_374d595cfc1748cb80d6384791588795", - "IPY_MODEL_42b8cc64de9546e1bb8a2b852a417279", - "IPY_MODEL_9137662d519043f4b63a79a1e9d42671" - ], - "layout": "IPY_MODEL_90ab04273a9e41eda658baacbac07acd" - } - }, - "863a55349a074ce489590a9c7b56f1e7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "890252af17464d64ae0c21ec804bc223": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "8972fc6d2e8e4e9ea57e7cf2a61b2f01": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_0b54f345ec964ecb9cf15bd5b8ccc746", - "placeholder": "​", - "style": "IPY_MODEL_a8fa78c120d34ca1823c338dd4c5f57b", - "value": "Batches: 100%" - } - }, - "89b84e2e1b064470a9b6a0339284d09a": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "8b1e4fafa4bd4ef38621db8a286d6c05": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "8b4f010e34a44f7bb4bb4587b01aea8b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_059f7a541366419b8da3b7bac5a482dd", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_fe9d81983e774e9cab05c242937458f7", - "value": 600 - } - }, - "8b947f0af507406aa2177b16d791921f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_8205e3bef7ec43549fa19653028019ac", - "placeholder": "​", - "style": "IPY_MODEL_029331ef8bd64b27a6c5385ce3e0f4b4", - "value": " 598/600 [00:24<00:00, 24.49it/s]" - } - }, - "8bdebe8c64274e19ad20e184c2034c9e": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "8cc33ef056d74afc9f3bd1b3c8988311": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "8e1fe21f6c204ba483df3999bcb48a67": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_646379c7e3aa41a588bd603d07ab8e28", - "placeholder": "​", - "style": "IPY_MODEL_78bf30aea545485484cfec8fe69a3767", - "value": "Batches: 100%" - } - }, - "8f0ef0efb0f44a7aa216208211ac49b0": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "9008ee39326d432da956d9617c537f26": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "90ab04273a9e41eda658baacbac07acd": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "9137662d519043f4b63a79a1e9d42671": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_c2e32eec26bd4e86bb70b508a46e88d7", - "placeholder": "​", - "style": "IPY_MODEL_b4a6a58e517146cbad3b5ba7e8afdb98", - "value": " 3980/4000 [00:18<00:00, 209.68it/s]" - } - }, - "9594bfe8f09e4301b34cf4ea897ce6a4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "96d7c667d4264043b8bdc10cc5e211a2": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "98a1068b601f4528a18d0e370561c225": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "9a1e781d578f47b79ea6bcd33171a552": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "9b19aa560c0a45b5a03976bf2ab20434": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_e4ba21babc2b4397ac312efbf6c1093a", - "placeholder": "​", - "style": "IPY_MODEL_98a1068b601f4528a18d0e370561c225", - "value": "Batches: 100%" - } - }, - "9d5c9161fe064cf9baf5dc0b6a8d7890": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "a04cb13e1c9946d08f2a5730574523ee": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_e56f708646e241baa9688021f73e4be7", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_414eba0f0473491990dc8871529a8907", - "value": 600 - } - }, - "a30b5754bc1c49e7a0d6c0cda84a23e9": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "a3693a9258aa4e85869f01e763f41a63": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_65e00761711a44d58f234fb932268eb5", - "placeholder": "​", - "style": "IPY_MODEL_3a259488152f431498bcd9adc731f89d", - "value": "Epoch: 100%" - } - }, - "a7501605ea394d47884111fdb2de00ea": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_441952e7c48e4366a3044537aadb330b", - "max": 1875, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_f8a4466e613344cd9a0f4f654726d3e7", - "value": 1875 - } - }, - "a86cf0c588534aa69cb41b4fa42b9d59": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "a8fa78c120d34ca1823c338dd4c5f57b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "a9c0ce203d234c5581feb0845d185524": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_e25987997fef4a44ba5a9c03a2c84622", - "placeholder": "​", - "style": "IPY_MODEL_cc5557baaa5a4c9498723e9a84bb3cfe", - "value": "Batches: 100%" - } - }, - "b002b4b85c7e4d9aa3d86791a5b2f801": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "b1b73880981d4869b77a8458be0073c6": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "b1e189b199bc490eafc7eb2ecc1daaf5": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "b41a6b9583f3436a9701983187e7a923": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "b4a6a58e517146cbad3b5ba7e8afdb98": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "b760230d392f4204b88d998f0c516a98": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "b79e494f2e474a42a5c4f871dae09dd9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "b86732b760144edbb430e2052bb29813": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "b98dac30df354891a42fc170b5cd52b4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_a9c0ce203d234c5581feb0845d185524", - "IPY_MODEL_653ae70ab5a14a8bb6d43144ee326c9d", - "IPY_MODEL_f25a6ad483ea48f69b8a77688020f790" - ], - "layout": "IPY_MODEL_2633a921fcca4d0c90f5827d84f190f4" - } - }, - "c121d101a456463285a86a5d55373e43": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "c18de5d78e7b41949d6956bd87bff700": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_3e2d6740b993473bb7691d7773baa74b", - "placeholder": "​", - "style": "IPY_MODEL_77401b52c114406a9c596e02c8420951", - "value": " 599/600 [00:24<00:00, 24.37it/s]" - } - }, - "c2e32eec26bd4e86bb70b508a46e88d7": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "c4e8724ef9594d69b18fb1b33d7989cd": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "cb2b4a308ee64751988432c423e3bb4d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_89b84e2e1b064470a9b6a0339284d09a", - "placeholder": "​", - "style": "IPY_MODEL_f938e62be3764dfeba067e9812f4cae0", - "value": " 10/10 [04:07<00:00, 24.90s/it]" - } - }, - "cb574ed2062d4ba2b62b5b333be30f45": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "cc5557baaa5a4c9498723e9a84bb3cfe": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "cced2bb02ef74f6283ea2ed19ed83f43": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_a86cf0c588534aa69cb41b4fa42b9d59", - "placeholder": "​", - "style": "IPY_MODEL_692db0c9d7c54bf68ff111c33e96e496", - "value": " 20/20 [02:44<00:00, 8.32s/it]" - } - }, - "ccf2b5165b494751bdf71b54b9cc66fb": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "cd1273324d0e47a183807c6eeca6ec0e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_6366e4a1c096487681a79cc77d71a523", - "IPY_MODEL_0ed1ed13153041109c3e4d172581cab8", - "IPY_MODEL_2f7962d587a648e690982ffe1fc252e8" - ], - "layout": "IPY_MODEL_b1b73880981d4869b77a8458be0073c6" - } - }, - "cef45f2502b24609af4c9162442a15ab": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "d044017d68d34b78a7366a235769c2dc": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_6c2e4d62cdfc4e4eab0832dc49d577bc", - "max": 20, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_633885d3801d4f9b89e7040a2dcbbe6d", - "value": 20 - } - }, - "d15d1a79f8d74a5eafaa85a11db1d8df": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "d6b5e3a56ea248aeb55c4ae76aec0002": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "d825e4a7719649f7b5a8f5bb2e8ccef4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_311f5429f3b146edbc9b8f6f528681d1", - "placeholder": "​", - "style": "IPY_MODEL_76952d837cf7418795fb34158c80bd27", - "value": "Computing pixel mean and covariance...: 99%" - } - }, - "d8d7f92934f94acd94d87b72b40852f1": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "da343bece953454fa206c38c28f8d9ff": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "dcd7f5ddaa9c4541b8b483f8f97ea4b1": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_712fe0055d7b454f8d342ef3ca68d830", - "IPY_MODEL_01ce56b63fd84c5eb054d3756df55322", - "IPY_MODEL_0be5d717250d4ac9ae9212cb5abce1cb" - ], - "layout": "IPY_MODEL_9a1e781d578f47b79ea6bcd33171a552" - } - }, - "e13fa64818ab41d68a65a73312572c99": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "e25987997fef4a44ba5a9c03a2c84622": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "e3ef8be847324359a83fdb22622956d4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "e4ba21babc2b4397ac312efbf6c1093a": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "e56f708646e241baa9688021f73e4be7": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "e72254b889824fc7a175dffda4291657": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "e856ef4698c94b79bdc559f91b710b17": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "ProgressView", - "bar_style": "", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_2a3af2976d7644718b2381a51799b0f3", - "max": 600, - "min": 0, - "orientation": "horizontal", - "style": "IPY_MODEL_cb574ed2062d4ba2b62b5b333be30f45", - "value": 600 - } - }, - "ea335e3e8b7a425995f4aaca9899a018": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "ee3c86fd9cf1443c8a1fe7e4ef5e00b0": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "f122311b612d4249a08d72b7b55714f7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_06a120793142465fbd3b12cab677cc09", - "IPY_MODEL_7916f752329348cb814eff14758a3b0a", - "IPY_MODEL_43b2acb6a30c40d18ec70ffbd288675f" - ], - "layout": "IPY_MODEL_0ff62aa332e94a4381f78edf90fcb014" - } - }, - "f19cf785ca1d4e00b46193b7a0c98a81": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_74dc5373e7d34b5eb0d391c015603191", - "IPY_MODEL_59df81b1dd7f414ca1e1d009f222cfa3", - "IPY_MODEL_cb2b4a308ee64751988432c423e3bb4d" - ], - "layout": "IPY_MODEL_597c6657347441e68304cf74d4c6a217" - } - }, - "f25a6ad483ea48f69b8a77688020f790": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "1.5.0", - "_view_name": "HTMLView", - "description": "", - "description_tooltip": null, - "layout": "IPY_MODEL_7548747e11ad4c6aa8dccc9de8328f7d", - "placeholder": "​", - "style": "IPY_MODEL_f64ba494e08047e99499497894c49147", - "value": " 598/600 [00:22<00:00, 26.23it/s]" - } - }, - "f64ba494e08047e99499497894c49147": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "f8a4466e613344cd9a0f4f654726d3e7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "f938e62be3764dfeba067e9812f4cae0": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "f943a6707a2746668cc897d3b5378ab7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "DescriptionStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "DescriptionStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "description_width": "" - } - }, - "fadffa82791e4fb5a59e27ace0f46374": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "fbcefc642f18403db6d8c816131b3b0e": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "fe9ae7dcf5184f49b9c962101ba67d91": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "fe9d81983e774e9cab05c242937458f7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "1.5.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "1.5.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "ffcab833aec74408b5cca57f090ec931": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "1.2.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "1.2.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "1.2.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "overflow_x": null, - "overflow_y": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - } - } + "layout": "IPY_MODEL_597c6657347441e68304cf74d4c6a217" + } + }, + "f25a6ad483ea48f69b8a77688020f790": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "1.5.0", + "_view_name": "HTMLView", + "description": "", + "description_tooltip": null, + "layout": "IPY_MODEL_7548747e11ad4c6aa8dccc9de8328f7d", + "placeholder": "​", + "style": "IPY_MODEL_f64ba494e08047e99499497894c49147", + "value": " 598/600 [00:22<00:00, 26.23it/s]" + } + }, + "f64ba494e08047e99499497894c49147": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "f8a4466e613344cd9a0f4f654726d3e7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "f938e62be3764dfeba067e9812f4cae0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "f943a6707a2746668cc897d3b5378ab7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "DescriptionStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "DescriptionStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "description_width": "" + } + }, + "fadffa82791e4fb5a59e27ace0f46374": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "fbcefc642f18403db6d8c816131b3b0e": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "fe9ae7dcf5184f49b9c962101ba67d91": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "fe9d81983e774e9cab05c242937458f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "1.5.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "1.5.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "ffcab833aec74408b5cca57f090ec931": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "1.2.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "1.2.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "1.2.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "overflow_x": null, + "overflow_y": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } } - }, - "nbformat": 4, - "nbformat_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 1 }