truss_5x5_zdim2_visualize.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Initial Setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: matplotlib in /home/u0579755/env_dir/lib/python3.6/site-packages (3.0.2)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib) (2.3.1)\n",
      "Requirement already satisfied: numpy>=1.10.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib) (1.16.0)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib) (2.7.5)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib) (1.0.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib) (0.10.0)\n",
      "Requirement already satisfied: six>=1.5 in /home/u0579755/env_dir/lib/python3.6/site-packages (from python-dateutil>=2.1->matplotlib) (1.12.0)\n",
      "Requirement already satisfied: setuptools in /home/u0579755/env_dir/lib/python3.6/site-packages (from kiwisolver>=1.0.1->matplotlib) (40.8.0)\n",
      "\u001b[33mYou are using pip version 19.0.3, however version 19.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n",
      "Requirement already satisfied: scikit-image in /home/u0579755/env_dir/lib/python3.6/site-packages (0.15.0)\n",
      "Requirement already satisfied: PyWavelets>=0.4.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-image) (1.0.3)\n",
      "Requirement already satisfied: matplotlib!=3.0.0,>=2.0.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-image) (3.0.2)\n",
      "Requirement already satisfied: imageio>=2.0.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-image) (2.5.0)\n",
      "Requirement already satisfied: scipy>=0.17.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-image) (1.2.1)\n",
      "Requirement already satisfied: networkx>=2.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-image) (2.3)\n",
      "Requirement already satisfied: pillow>=4.3.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-image) (5.4.1)\n",
      "Requirement already satisfied: numpy>=1.9.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from PyWavelets>=0.4.0->scikit-image) (1.16.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (1.0.1)\n",
      "Requirement already satisfied: cycler>=0.10 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (0.10.0)\n",
      "Requirement already satisfied: python-dateutil>=2.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (2.7.5)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /home/u0579755/env_dir/lib/python3.6/site-packages (from matplotlib!=3.0.0,>=2.0.0->scikit-image) (2.3.1)\n",
      "Requirement already satisfied: decorator>=4.3.0 in /home/u0579755/env_dir/lib/python3.6/site-packages (from networkx>=2.0->scikit-image) (4.3.2)\n",
      "Requirement already satisfied: setuptools in /home/u0579755/env_dir/lib/python3.6/site-packages (from kiwisolver>=1.0.1->matplotlib!=3.0.0,>=2.0.0->scikit-image) (40.8.0)\n",
      "Requirement already satisfied: six in /home/u0579755/env_dir/lib/python3.6/site-packages (from cycler>=0.10->matplotlib!=3.0.0,>=2.0.0->scikit-image) (1.12.0)\n",
      "\u001b[33mYou are using pip version 19.0.3, however version 19.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n",
      "Requirement already satisfied: scikit-learn in /home/u0579755/env_dir/lib/python3.6/site-packages (0.20.3)\n",
      "Requirement already satisfied: numpy>=1.8.2 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-learn) (1.16.0)\n",
      "Requirement already satisfied: scipy>=0.13.3 in /home/u0579755/env_dir/lib/python3.6/site-packages (from scikit-learn) (1.2.1)\n",
      "\u001b[33mYou are using pip version 19.0.3, however version 19.1 is available.\n",
      "You should consider upgrading via the 'pip install --upgrade pip' command.\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "# Install\n",
    "!pip3 install matplotlib\n",
    "!pip3 install scikit-image\n",
    "!pip3 install scikit-learn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import\n",
    "import os \n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import zipfile \n",
    "from skimage import io \n",
    "from torch.utils.data import Dataset\n",
    "import torch \n",
    "import pandas as pd \n",
    "from torchvision import transforms\n",
    "import copy\n",
    "from sklearn.metrics import mean_squared_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# System Check\n",
    "try:\n",
    "  import google.colab\n",
    "  from google.colab import drive\n",
    "  from google.colab import files\n",
    "  IN_COLAB = True\n",
    "except:\n",
    "  IN_COLAB = False\n",
    "try:\n",
    "    hostname = !hostname\n",
    "    if 'lab' in hostname[0] and '.eng.utah.edu' in hostname[0]:\n",
    "        IN_CADE = True\n",
    "    else:\n",
    "        IN_CADE = False\n",
    "except:\n",
    "    IN_CADE = False\n",
    "\n",
    "assert(not IN_CADE or not IN_COLAB)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find GPU\n",
    "def define_gpu_to_use(minimum_memory_mb = 3800):\n",
    "    gpu_to_use = None\n",
    "    try: \n",
    "        os.environ['CUDA_VISIBLE_DEVICES']\n",
    "        print('GPU already assigned before: ' + str(os.environ['CUDA_VISIBLE_DEVICES']))\n",
    "        return\n",
    "    except:\n",
    "        pass\n",
    "    torch.cuda.empty_cache()\n",
    "    for i in range(16):\n",
    "        free_memory = !nvidia-smi --query-gpu=memory.free -i $i --format=csv,nounits,noheader\n",
    "        if free_memory[0] == 'No devices were found':\n",
    "            break\n",
    "        free_memory = int(free_memory[0])\n",
    "        if free_memory>minimum_memory_mb-500:\n",
    "            gpu_to_use = i\n",
    "            break\n",
    "    if gpu_to_use is None:\n",
    "        print('Could not find any GPU available with the required free memory of ' +str(minimum_memory_mb) + 'MB. Please use a different system for this assignment.')\n",
    "    else:\n",
    "        os.environ['CUDA_VISIBLE_DEVICES'] = str(gpu_to_use)\n",
    "        print('Chosen GPU: ' + str(gpu_to_use))\n",
    "        x = torch.rand((256,1024,minimum_memory_mb-500)).cuda()\n",
    "        x = torch.rand((1,1)).cuda()\n",
    "        del x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chosen GPU: 0\n"
     ]
    }
   ],
   "source": [
    "# Reserve GPU\n",
    "if IN_CADE:\n",
    "    define_gpu_to_use()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load and Visualize Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Opens zip file and places data in datsets folder\n",
    "def open_zip(filename):\n",
    "    zip_ref = zipfile.ZipFile(filename, 'r')\n",
    "    zip_ref.extractall('datasets')\n",
    "    zip_ref.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Return indexes to split data by for train, val, and test\n",
    "# Splits are 70% train, 10% val, 20% test\n",
    "def get_split(array_to_split, split):\n",
    "    np.random.seed(0)\n",
    "    np.random.shuffle(array_to_split)\n",
    "    np.random.seed()\n",
    "    if split == 'train':\n",
    "        array_to_split = array_to_split[:int(len(array_to_split)*0.7)]\n",
    "    elif split == 'val':\n",
    "        array_to_split = array_to_split[int(len(array_to_split)*0.7):int(len(array_to_split)*0.8)]\n",
    "    elif split == 'test':\n",
    "        array_to_split = array_to_split[int(len(array_to_split)*0.8):]\n",
    "    return array_to_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dataset class for Truss (Bracket/Beam) dataset\n",
    "class TrussDataset(Dataset):\n",
    "    def __init__(self, csv_file, root_dir, split='train'):\n",
    "        self.root_dir = root_dir\n",
    "        self.split = split\n",
    "        # Get the split\n",
    "        all_attributes_frame = pd.read_csv(root_dir + csv_file)\n",
    "        ids = get_split(pd.unique(all_attributes_frame['ID']), split)\n",
    "        self.attributes_frame = all_attributes_frame[all_attributes_frame['ID'].isin(ids)]\n",
    "              \n",
    "    def __len__(self):\n",
    "        return len(self.attributes_frame)\n",
    "    \n",
    "    def __getitem__(self, idx):\n",
    "        image_name = os.path.join(self.root_dir, self.attributes_frame.iloc[idx, 1])\n",
    "        image = io.imread(image_name)\n",
    "        image = image.astype(np.float32)\n",
    "        image = image[:,:,:3]\n",
    "        image = image/255\n",
    "        image = np.swapaxes(image, 0, 1)\n",
    "        image = np.swapaxes(image, 0, 2)\n",
    "        attributes = self.attributes_frame.iloc[idx, 2:].values\n",
    "        attributes = attributes.astype('float')\n",
    "        attribute_names = self.attributes_frame.columns[2:].values\n",
    "        return torch.FloatTensor(image), torch.FloatTensor(attributes), list(attribute_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Open zip of dataset\n",
    "open_zip('trussData.zip')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create train, val, and test datasets\n",
    "train_dataset = TrussDataset('truss_data.csv', 'datasets/trussData/')\n",
    "val_dataset = TrussDataset('truss_data.csv', 'datasets/trussData/', split='val')\n",
    "test_dataset = TrussDataset('truss_data.csv', 'datasets/trussData/', split='test')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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37gxiX+w6LTn3r3zlK0F87733BnHHjoXnBvjvl8/Dz507N4h9kei08HPZ/d+MH5fKN2/d/x2l0apVqxLbpkyZEsQzZswIYn8vh78fJN/Ylf+dz6NR56FPAjAq/noUgIm17CsiImVQzLTFhwG8BOA4kmtIXgvgdgDnk1wOYEgci4hIBRXMoZtZsjBiJJtz+UREmqjUr+VSCT7/3aZNmyA+7LDDgvjkk09OnOPCCy8MYp9n9/Pjs8IXLAaAF154IYiff/75IJ43b14Q+zXB862nUY512/2aJn5t8rPOOqvW4/OtN3/99dcHsc/Hbt++vS5NTC0/LnXkkUcm9jnjjDOC2K/D7msdpJXPifv1YZ566qkgfvHFFxPn8Gu7+3Gl/fv3ay0XEZHmRB26iEhGqEMXEckIdegiIhmhQdES+MWLfFFeAOjaNVwN4fOf/3wQDxkyJIj9YkY9evSoTxOblAULFgSxH1TKt0CSv3lj48aNQVzXQdN83+/vfe97QXzjjTfWeg7P3zQEAPfff38Qb9iwIYjTchNVORxyyCFB7H8GZ555ZhBfccUVQdxUF82bPHlyYtuYMWOC+KWXXgridevWaVBURKQ5UYcuIpIR6tBFRDJCOfRG4vPsrVq1CmJf3LpPnz5B7ItbA8mbk77whS/Up4lNRr4Fkh5//PEg9jdv+Bz71q3hkv4+fztiRHJJ/3vuuSeI/c/Q88URbrvttsQ+ixcvDuJyFKxoqvzP6KijjgriL37xi4ljrrzyyoL7pJH//bzzzjuD+Ne//rVy6CIizYk6dBGRjCi1SPStJNeSnB9/DGvcZoqISCGlFom+FcAOM7uztmPznKvZ5NALKVTcOl+xhKOPPjqIBw0aFMQ+x+7n8WaZLwzx8MMPB7EvvOELMtx0002Jc5500km1PueKFSuC+Ac/+EEQ+/n0APDRRx/Vek4pXocOHRLb/N/IOeecE8QjR4aLx+ZbWC+NSDZqkWgREUmZ+uTQrye5ME7J1Fh7i+R1JOeSnFvTPiIiUn+lduj3AjgaQD8A6wH8tqYdzew+M+tfzNsFEREpXUlFoot9LM++yqHXg8+z+3m6PXv2DGJfQMDn2P16Mlni13bxRTUOPfTQIPa51mL4nPmDDz4YxJs3b04c05zWakkDf7/HiSeG3ZRfQ8n/jfi/qXzKURC+wXLoNZy8W054GYBFNe0rIiLlUbCmaFwkejCAziTXAPg3AINJ9gNgAFYC+HYjtlFERIpQapHo0Y3QFhERqQet5ZIhLVq0CGJfqNfnA/08diBZqHfw4MF1akO+tUl87r+p8jny22+/PYiXLFkSxPv27Wv0NkndHHTQQUHcq1evIPbF3X2OHUjm4f1Yls+p+7/LUjRqDl1ERNJHHbqISEaoQxcRyQh16CIiGZGN0SoBkByE++CDD4LYF3147733EufwBZuHDRtWa3z44YcHcb4BIL+tZcuWQewHkRpjUKkUS5cuDeJJkyYF8cqVK4NYg6Dpt2vXriDetGlTEK9evTqI33///cQ5/O+n/32uJF2hi4hkhDp0EZGMUIcuIpIRyqE3Iz7Hmy8/6AtF7NixI4h9DvKiiy4K4t69eyfO6XPgvsiDv7ntwAMPDOI2bdokzlkOPmf++uuvB7GKVaSfz3f7Rdn8AnaXX355EOcrMp2v+Exa6ApdRCQj1KGLiGREMUWijyA5neRikm+SvCHe3onkVJLL48/pfR8iItIMFJND3wvgRjN7nWQ7AK+RnArgGgDTzOx2kjcDuBnAjxuvqdLQ8i3M5rft37+/1scLzSHPd47du3fX+ng5CgYUo6qqKoh37twZxCpWkT6tW7cOYl8M/Pzzzw/ib33rW0Hct2/fxmlYmRRTJHq9mb0ef70dwBIA3QEMBzA23m0sgBGN1UgRESmsTrNc4nJzJwGYA6Crma2PH9oAoGsNx1wH4LrSmygiIsUo+r0tybYAHgPwfTP7MPcxi9575n3/qSLRIiLlUdQVOsmWiDrzB81sQrx5I8luZrY+rjFaVfMZJA18bjrf/O4+ffoEsZ9nfskllwSxL5qRr8DFJ598EsR+PrwvgEEycY5KOO2004J4xowZQezXAcn32qXh+N+TTp06JfY59dRTg/jKK68M4q9//esN37BGMH/+/JKOK2aWCxGVnFtiZr/LeWgSgFHx16MATCypBSIi0iCKuUI/E8DVAN4gWf1v4ycAbgfwKMlrAawCcGUNx4uISBkUUyT6BQA1vQc+r2GbIyIipdJaLhnic89+Tu5hhx0WxD5HDCSLRA8dOjSIfd7dr2fy4YfBeDmAwrl7v3ZLWuahX3zxxUE8e/bsIF61alUQb9myJYg1T71+fPHlY489Noh9QWcAuO66cEKdn4eeVmPHjg3i0aNHl3SedPzliIhIvalDFxHJCHXoIiIZoQ5dRCQjNCjahPjBQj/o2a1btyA++eSTg9jfJHTZZZclnqNdu3Z1apMvkNu5c+fEPv6GkKbCf3+vuuqqIPY3f7z00ktB7G+okpAfDPeD9r64xDXXXBPE55xzTqO0q6Ft3rw5iO++++7EPhMmTAjid999t6Tn0hW6iEhGqEMXEckIdegiIhnRNJObGeTz423btk3s07179yA+5ZRTgnjYsGFB7HPkBx10UH2amJfPoVfKCy+8EMQzZ84M4vbt2wexX6TJ38SSz8CBA4PYL1Tm856rV69OnKO53GzkC4PnW0jL//76As3f+MY3gjitYzF79uwJ4kceeSSIH3vssSB++eWXE+fwefZSF3rTFbqISEaoQxcRyYj6FIm+leRakvPjj2GFziUiIo2nPkWiAeD3ZnZn4zUvO3z+z8/37tGjRxDnWzirULGJrFq4cGFi25QpU4J41qxZQbx8+fIg7tChQxD7OdC+WHAx/DF+XvqkSZMSx+RbvCwL/O+zX0jrggsuSBzjv3++WEpa/fOf/wzi8ePHB7G/H2Ht2rVB/PHHHyfO2VBjK8Usn7sewPr46+0kq4tEi4hIitQph+6KRAPA9SQXkryfZMcajrmO5FySc+vVUhERqVV9ikTfC+BoAP0QXcH/Nt9xKhItIlIeJReJNrONOY//CcDkRmlhCvlCEvnmx3bsGL5hOfroo4P4zDPPDGKfDz/rrLPq08RU27FjRxC/+OKLQeznkM+ZMwfeW2+9FcR+Hq9fR6VVq1ZB/NBDDwXxCSeckHiOM844I7Etl5+77osr5FuP49VXX621nWlVaN2VQYMGBbFfd+Xcc89tlHY1NP+79te//jWxj//99IVOdu7cGcT79+9voNYVVnKRaJK5K0FdBmBRwzdPRESKVZ8i0SNJ9gNgAFYC+HajtFBERIpSnyLRTzZ8c0REpFTpXByhwnyO3Odf/Zrfxx13XOIcgwcPDuJLL700iPv27VuPFqaHzw/my3f7HLnfZ9myZUG8bt26IM43d9uvn1FoHq+f+ztv3rwg/uMf/5g4xv+MfHFrz6/ffcUVVyT2Wb9+fRD7/Ou+fftqfY5y+OxnP5vY5tfW9+uufPOb3wxiv5ZLWvg54b4Y81NPPRXES5cuTZxj27ZtQVzOHHkhuvVfRCQj1KGLiGSEOnQRkYxQhy4ikhEs54L7JCu+ur8vJAEkCz907do1iP1NJ+edd14QjxgxInHOprLQUCF+EOmZZ54JYr8o1qJFydsR/Dnef//9IPY311RikOmII45IbLv++uuD+KabbqrTOf0NJgBwyy23BLFf2Gnjxo1B3BjfC39DVCkLafnF5NLC92djx44NYl9sYu7ccEWSLVu2BLEffK+g14q5215X6CIiGaEOXUQkI9Shi4hkROZuLCpUSMIXWgaAfv36BfHQoUOD2C+c5YslNFULFixIbHviiSeC+Pnnnw9ifxNQVVVVEOdbvD9NN17UxN/MBAATJ04MYl8kutACavluRPJ5eX+Tii/c4XO6xXwvW7duHcT+d97fADVq1KggPvvssws+Rxr4300A+Mtf/hLEfozHj+fs3r07iJt6EW9doYuIZIQ6dBGRjChm+dyDSL5CckFcJPq2ePtRJOeQfJvkIyRbFTqXiIg0nmJy6LsBnGtmO+JCFy+QnALgXxEViR5H8o8ArkVUxahB+YWy/EL7fqEsX0jCFynIN8e2qeQM68rnGH1x29mzZyeOWbFiRRD7OeN1XRSrqci3KJYfLxg3blwQ9+nTJ4jzLWrl+Tnf1157bRBv3749iH0OeNeuXYlz+r+BU045JYiHDx8exFdffXUQ+7+xtFizZk0Q/+lPfwpiv5AWkPyZ+e9nUxjPqY+CV+gWqS4x0zL+MADnAqi+K2IsgOTdNSIiUjZF5dBJtoiLW1QBmApgBYAPzGxvvMsaAMnpI1CRaBGRcimqQzezfWbWD8DhAAYA6FPgkNxjVSRaRKQM6jQP3cw+IDkdwOkAOpA8IL5KPxzA2tqPTvKL4Ldt2zaxj59D6+eMDxkyJIgvvvjiIO7SpUtdm9Vk+DnLkyeHdbpffvnlIF65cmUQ5yscsXfv3sS2LPJ543xr/Pg1ZnyxgxkzZgSxv1/BzwfPx4/xvPfee0Hsxyjy5bv9fPiRI0cGsV+bKC38axszZkwQ13XdFaD5/P7WpJhZLl1Idoi/bg3gfABLAEwHUF2SZRSAifnPICIi5VDMFXo3AGNJtkD0D+BRM5tMcjGAcST/HcA8AKNrO4mIiDSuYopELwRwUp7t7yDKp4uISAqUdS2Xli1bBvm8I488MnjcF1YGkmuNn3rqqY3Stkrz82VnzpyZ2Mevs+KLLfv8qz9nMflYXxC7UK65mFy03+ZjP5ZSKAaSa/YUiv3r8mvgH3zwwYnn6NixYxD36tUriP3r2Lp1axDny10XaqcfA/L3VeQbE+rdu3diW9po3ZXy0K3/IiIZoQ5dRCQj1KGLiGSEOnQRkYwoa5HoY445xu66665PY19s2S+8lWWLFy8OYl9sYsmSJYljfBGGjz76KIj9AKUfTPQDcC1btkw8R6F9CsV+8DHftkKx/z3Id06/jx/kLBT7QdB8xSj8Nn+jkI+zUvikFH4hrT//+c9B7G+CA7SQVh2pSLSISHOiDl1EJCPUoYuIZERZc+j9+/c3v8BOc+ULKvjCET6XXdM2kUp44IEHgvjvf/97EPu/882bNyfO0dwX0qoj5dBFRJoTdegiIhlRnyLRY0i+S3J+/NGv0LlERKTx1KdINAD8yMzG13Ks1KCYBahEKuHVV19NbPMFmn1xDz8P3Rez1kJa5VHM8rkGIF+RaBERSZGSikSbWfW6rb8kuZDk70nmvc0zt0j0pk2bGqjZIiLilVQkmuSJAG5BVCz6VACdAPy4hmM/LRKd5fqeIiKVVmqR6AvN7M54826SfwHwwwZvnYg0OF8c3K+7MnFisjzwwoULaz2H1l1Jh1KLRC8l2S3eRgAjACxqzIaKiEjt6lMk+jmSXQAQwHwA32nEdoqISAH1KRJ9bqO0SERESqLFQUQybtq0aUE8ZsyYIPbFmTds2JA4xyeffNLg7ZKGp1v/RUQyQh26iEhGqEMXEckIdegiIhmhQVGRJu6NN94I4vHjw/XynnrqqSBeunRpEPvizFpIq+nSFbqISEaoQxcRyQh16CIiGaEcukiKvfXWW0H83HPPJfbx23yBinXr1gWxbhLKLl2hi4hkhDp0EZGMUIcuIpIRLOecU5KbAKwC0BnA5rI9cenUzobVFNrZFNoIqJ0NLe3t7GFmBUu+lbVD//RJyblm1r/sT1xHamfDagrtbAptBNTOhtZU2lmIUi4iIhmhDl1EJCMq1aHfV6HnrSu1s2E1hXY2hTYCamdDayrtrFVFcugiItLwlHIREckIdegiIhlR9g6d5IUkl5F8m+TN5X7+mpC8n2QVyUU52zqRnEpyefy5Y4XbeATJ6SQXk3yT5A0pbedBJF8huSBu523x9qNIzol/9o+QbFXJdlYj2YLkPJKT4zh17SS5kuQbJOeTnBtvS9XPPW5TB5LjSS4luYTk6WlqJ8nj4u9h9ceHJL+fpjbWR1k7dJItAPwBwJcAHA9gJMnjy9mGWowBcKHbdjOAaWZ2DIBpcVxJewHcaGbHAxgI4Lvx9y9t7dwN4Fwz6wugH4ALSQ4EcAeA35tZbwDvA7i2gm3MdQOAJTn+EQHUAAADBElEQVRxWtt5jpn1y5kvnbafOwDcBeApM+sDoC+i72tq2mlmy+LvYT8ApwD4CMDjaWpjvZhZ2T4AnA7g6Zz4FgC3lLMNBdrXE8CinHgZgG7x190ALKt0G117JwI4P83tBHAwgNcBnIboTrwD8v0uVLB9hyP6Az4XwGQATGk7VwLo7Lal6ucOoD2AdxFPtkhrO3PaNRTA7DS3sa4f5U65dAewOideE29Lq65mtj7+egOArpVsTC6SPQGcBGAOUtjOOI0xH0AVgKkAVgD4wMz2xruk5Wf/HwBuArA/jg9FOttpAJ4h+RrJ6+Jtafu5HwVgE4C/xCmsP5Nsg/S1s9pVAB6Ov05rG+tEg6JFsuhfdyrmeJJsC+AxAN83sw9zH0tLO81sn0Vvaw8HMABAnwo3KYHkxQCqzOy1SrelCIPM7GRE6crvkjwr98GU/NwPAHAygHvN7CQAO+FSFylpJ+JxkUsB/N0/lpY2lqLcHfpaAEfkxIfH29JqI8luABB/rqpwe0CyJaLO/EEzmxBvTl07q5nZBwCmI0pddCBZXVQlDT/7MwFcSnIlgHGI0i53IX3thJmtjT9XIcr5DkD6fu5rAKwxszlxPB5RB5+2dgLRP8bXzWxjHKexjXVW7g79VQDHxLMIWiF6yzOpzG2oi0kARsVfj0KUs64YkgQwGsASM/tdzkNpa2cXkh3ir1sjyvMvQdSxXxHvVvF2mtktZna4mfVE9Lv4nJl9FSlrJ8k2JNtVf40o97sIKfu5m9kGAKtJHhdvOg/AYqSsnbGR+O90C5DONtZdBQYihgF4C1FO9aeVHkTIadfDANYD2IPoSuNaRPnUaQCWA3gWQKcKt3EQoreCCwHMjz+GpbCdXwAwL27nIgA/j7f3AvAKgLcRvdU9sNI/95w2DwYwOY3tjNuzIP54s/rvJm0/97hN/QDMjX/2/wDQMW3tBNAGwBYA7XO2paqNpX7o1n8RkYzQoKiISEaoQxcRyQh16CIiGaEOXUQkI9Shi4hkhDp0EZGMUIcuIpIR/x9gCt7diZIpAQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Visualing a few cases of the training set\n",
    "for batch_idx, (image, attribute, name) in enumerate(train_dataset):\n",
    "    if batch_idx%250 == 0: \n",
    "        plt.figure()\n",
    "        plt.title(str(name) + ' ' + str(attribute.cpu().numpy()))\n",
    "        plt.imshow(image[:,:,:].permute([1, 2, 0]).cpu().numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculates L2 for images and MSE for regression - want both close to 0\n",
    "def get_score_model(model, data_loader):\n",
    "    model.eval()\n",
    "    \n",
    "    with torch.no_grad():\n",
    "        distances = []\n",
    "        mse = []\n",
    "        for image, attribute, name in data_loader:\n",
    "            image = image.cuda()\n",
    "            recon, mu, logvar, reg = model(image)\n",
    "            # Reconstruction Score\n",
    "            euclidean_dist = torch.pow(torch.sum(torch.pow((image - recon), 2)), 0.5)\n",
    "            distances.append(euclidean_dist.cpu().numpy())\n",
    "            # Regression Score\n",
    "            y_true = attribute.cpu().numpy()\n",
    "            y_pred = reg.cpu().numpy()         \n",
    "            mse.append(mean_squared_error(y_true, y_pred))\n",
    "    \n",
    "    return np.mean(distances), np.mean(mse)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Classes to create VAE, ability to change kernel_size of filters for convolution layers\n",
    "# and the latent representation dim\n",
    "class ConvBlock(torch.nn.Module):\n",
    "    def __init__(self, in_channels, out_channels, kernel_size):\n",
    "        super(ConvBlock, self).__init__()\n",
    "        padding = int((kernel_size - 1) / 2)\n",
    "        self.conv = torch.nn.Conv2d(in_channels=in_channels, out_channels=out_channels, kernel_size=kernel_size, padding=padding)\n",
    "        self.batch = torch.nn.BatchNorm2d(num_features=out_channels)\n",
    "        self.relu = torch.nn.ReLU()\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = self.conv(x)\n",
    "        x = self.batch(x)\n",
    "        x = self.relu(x)\n",
    "        return x\n",
    "\n",
    "class TransBlock(torch.nn.Module):\n",
    "    def __init__(self, in_channels, out_channels):\n",
    "        super(TransBlock, self).__init__()\n",
    "        self.convT = torch.nn.ConvTranspose2d(in_channels=in_channels, out_channels=out_channels, kernel_size=2, stride=2)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        x = self.convT(x)\n",
    "        return x\n",
    "\n",
    "class Flatten(torch.nn.Module):\n",
    "    def forward(self, x):\n",
    "        return x.view(x.size(0), -1)\n",
    "\n",
    "class UnFlatten(torch.nn.Module):\n",
    "    def forward(self, x):\n",
    "        return x.view(-1, 32, 5, 10) # see if there is a way to not have this hardcoded"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# VAE with Regression - The reconstruction and regression are done from the\n",
    "# latent variables calculated from the reparametrization (distribution)\n",
    "class VAE_REG(torch.nn.Module):\n",
    "    def __init__(self, kernel_size, z_dim):\n",
    "        super(VAE_REG, self).__init__()\n",
    "        self.encoder = torch.nn.Sequential(\n",
    "        ConvBlock(in_channels=3, out_channels=8, kernel_size=kernel_size),\n",
    "        ConvBlock(in_channels=8, out_channels=8, kernel_size=kernel_size),\n",
    "        torch.nn.MaxPool2d(kernel_size=2),\n",
    "        ConvBlock(in_channels=8, out_channels=16, kernel_size=kernel_size),\n",
    "        ConvBlock(in_channels=16, out_channels=16, kernel_size=kernel_size),\n",
    "        torch.nn.MaxPool2d(kernel_size=2),\n",
    "        ConvBlock(in_channels=16, out_channels=32, kernel_size=kernel_size),\n",
    "        ConvBlock(in_channels=32, out_channels=32, kernel_size=kernel_size),\n",
    "        torch.nn.MaxPool2d(kernel_size=2),\n",
    "        Flatten()) \n",
    "        \n",
    "        self.mu = torch.nn.Linear(1600, z_dim)\n",
    "        self.logvar = torch.nn.Linear(1600, z_dim)\n",
    "        self.fc = torch.nn.Linear(z_dim, 1600)\n",
    "        \n",
    "        self.decoder = torch.nn.Sequential(\n",
    "        UnFlatten(),\n",
    "        TransBlock(in_channels=32, out_channels=32),\n",
    "        ConvBlock(in_channels=32, out_channels=32, kernel_size=kernel_size),\n",
    "        ConvBlock(in_channels=32, out_channels=16, kernel_size=kernel_size),\n",
    "        TransBlock(in_channels=16, out_channels=16),\n",
    "        ConvBlock(in_channels=16, out_channels=16, kernel_size=kernel_size),\n",
    "        ConvBlock(in_channels=16, out_channels=8, kernel_size=kernel_size),\n",
    "        TransBlock(in_channels=8, out_channels=8),\n",
    "        ConvBlock(in_channels=8, out_channels=8, kernel_size=kernel_size),\n",
    "        ConvBlock(in_channels=8, out_channels=3, kernel_size=kernel_size))\n",
    "        \n",
    "        self.regression = torch.nn.Sequential(\n",
    "            torch.nn.Linear(in_features=z_dim, out_features=4),\n",
    "            torch.nn.ReLU(),\n",
    "            torch.nn.Linear(in_features=4, out_features=1))\n",
    "            \n",
    "    def reparametrize(self, mu, logvar):\n",
    "        std = logvar.mul(0.5).exp_()\n",
    "        esp = torch.cuda.FloatTensor(mu.size()).normal_()\n",
    "        z = mu + std * esp\n",
    "        return z\n",
    "    \n",
    "    def bottleneck(self, x):\n",
    "        mu, logvar = self.mu(x), self.logvar(x)\n",
    "        z = self.reparametrize(mu, logvar)\n",
    "        return z, mu, logvar\n",
    "    \n",
    "    def representation(self, x):\n",
    "        return self.bottleneck(self.encoder(x))[0]\n",
    "    \n",
    "    def forward(self, x):\n",
    "        x = self.encoder(x)\n",
    "        z, mu, logvar = self.bottleneck(x) # z is latent representation\n",
    "        x = self.fc(z)\n",
    "        x = torch.sigmoid(self.decoder(x)) # VAE output\n",
    "        r = self.regression(z) # Regression output\n",
    "        return x, mu, logvar, r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Loss function for this task, combines reconstruction and KL for the image task and the MSELoss\n",
    "# for the regression task\n",
    "def loss_function(reconstruction, image, mu, logvar, attributes, r, batch_size):\n",
    "    reconstruction_loss = torch.nn.functional.binary_cross_entropy(reconstruction, image)\n",
    "    kl_loss = -0.5 * torch.sum(1 + logvar - mu.pow(2) - logvar.exp())\n",
    "    kl_loss /=  batch_size * image.shape[1] * image.shape[2] * image.shape[3]\n",
    "    reg_loss =  torch.nn.MSELoss()\n",
    "    return reconstruction_loss, kl_loss, reg_loss(attributes, r)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Starting Training!\n",
      "\n",
      "Epoch: 0\n",
      "Total Loss: 0.7422838270664215\n",
      "Reconstruction Loss: 0.6712782680988312\n",
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      "Trainig Reconstruction Score: 43.70175\n",
      "Training MSE Score: 0.005800901\n",
      "Validation Reconstruction Score: 43.8819\n",
      "Validation MSE Score: 0.0053316457\n",
      "\n",
      "Epoch: 1\n",
      "Total Loss: 0.6461339780262538\n",
      "Reconstruction Loss: 0.632349671636309\n",
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      "Regression Loss: 0.006870909633913211\n",
      "Trainig Reconstruction Score: 42.395027\n",
      "Training MSE Score: 0.0058184643\n",
      "Validation Reconstruction Score: 42.561962\n",
      "Validation MSE Score: 0.005263525\n",
      "\n",
      "Epoch: 2\n",
      "Total Loss: 0.612678245987211\n",
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      "Regression Loss: 0.006184694919336055\n",
      "Trainig Reconstruction Score: 41.160362\n",
      "Training MSE Score: 0.006418056\n",
      "Validation Reconstruction Score: 41.264294\n",
      "Validation MSE Score: 0.006710895\n",
      "\n",
      "Epoch: 3\n",
      "Total Loss: 0.5852260495935168\n",
      "Reconstruction Loss: 0.5757375751222883\n",
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      "Regression Loss: 0.006567622248881629\n",
      "Trainig Reconstruction Score: 39.829666\n",
      "Training MSE Score: 0.009133355\n",
      "Validation Reconstruction Score: 39.903667\n",
      "Validation MSE Score: 0.0110648135\n",
      "\n",
      "Epoch: 4\n",
      "Total Loss: 0.5650306539876121\n",
      "Reconstruction Loss: 0.5562237458569663\n",
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      "Regression Loss: 0.006415384027474959\n",
      "Trainig Reconstruction Score: 39.820457\n",
      "Training MSE Score: 0.005969998\n",
      "Validation Reconstruction Score: 39.87644\n",
      "Validation MSE Score: 0.005847645\n",
      "\n",
      "Epoch: 5\n",
      "Total Loss: 0.5495829309735979\n",
      "Reconstruction Loss: 0.5414010388510567\n",
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      "Regression Loss: 0.006124740383321685\n",
      "Trainig Reconstruction Score: 38.474007\n",
      "Training MSE Score: 0.0063318233\n",
      "Validation Reconstruction Score: 38.462936\n",
      "Validation MSE Score: 0.006174238\n",
      "\n",
      "Epoch: 6\n",
      "Total Loss: 0.5330650048596518\n",
      "Reconstruction Loss: 0.5250638042177472\n",
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      "Regression Loss: 0.006114774925767311\n",
      "Trainig Reconstruction Score: 38.31966\n",
      "Training MSE Score: 0.0054849456\n",
      "Validation Reconstruction Score: 38.309155\n",
      "Validation MSE Score: 0.0054012593\n",
      "\n",
      "Epoch: 7\n",
      "Total Loss: 0.5240640670061112\n",
      "Reconstruction Loss: 0.5161286967141288\n",
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      "Regression Loss: 0.006144465544327561\n",
      "Trainig Reconstruction Score: 37.593796\n",
      "Training MSE Score: 0.0055376743\n",
      "Validation Reconstruction Score: 37.650055\n",
      "Validation MSE Score: 0.004825099\n",
      "\n",
      "Epoch: 8\n",
      "Total Loss: 0.5182622228349958\n",
      "Reconstruction Loss: 0.5106001538889748\n",
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      "Regression Loss: 0.005900150612329266\n",
      "Trainig Reconstruction Score: 37.450947\n",
      "Training MSE Score: 0.005720019\n",
      "Validation Reconstruction Score: 37.429623\n",
      "Validation MSE Score: 0.005271402\n",
      "\n",
      "Epoch: 9\n",
      "Total Loss: 0.5116468446595328\n",
      "Reconstruction Loss: 0.5043253025838307\n",
      "KL Loss: 0.0016541715977447375\n",
      "Regression Loss: 0.005667373723866019\n",
      "Trainig Reconstruction Score: 37.2306\n",
      "Training MSE Score: 0.0055006123\n",
      "Validation Reconstruction Score: 37.25284\n",
      "Validation MSE Score: 0.0051594013\n",
      "\n",
      "Epoch: 10\n",
      "Total Loss: 0.5086194055421012\n",
      "Reconstruction Loss: 0.5014755525759288\n",
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      "Regression Loss: 0.005563175099502717\n",
      "Trainig Reconstruction Score: 37.175713\n",
      "Training MSE Score: 0.0051844316\n",
      "Validation Reconstruction Score: 37.18481\n",
      "Validation MSE Score: 0.004153429\n",
      "\n",
      "Epoch: 11\n",
      "Total Loss: 0.5044166496821813\n",
      "Reconstruction Loss: 0.49737286056791036\n",
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      "Trainig Reconstruction Score: 36.93953\n",
      "Training MSE Score: 0.0051002204\n",
      "Validation Reconstruction Score: 36.975388\n",
      "Validation MSE Score: 0.0045437277\n",
      "\n",
      "Epoch: 12\n",
      "Total Loss: 0.5011246740818024\n",
      "Reconstruction Loss: 0.4943344048091343\n",
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      "Regression Loss: 0.005226377685487803\n",
      "Trainig Reconstruction Score: 37.062202\n",
      "Training MSE Score: 0.0051030396\n",
      "Validation Reconstruction Score: 37.017403\n",
      "Validation MSE Score: 0.004190114\n",
      "\n",
      "Epoch: 13\n",
      "Total Loss: 0.4985229739121028\n",
      "Reconstruction Loss: 0.49182341865130835\n",
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      "Trainig Reconstruction Score: 36.84727\n",
      "Training MSE Score: 0.0050014476\n",
      "Validation Reconstruction Score: 36.84868\n",
      "Validation MSE Score: 0.0044883653\n",
      "\n",
      "Epoch: 14\n",
      "Total Loss: 0.49888709102358136\n",
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      "Trainig Reconstruction Score: 36.799995\n",
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      "Validation Reconstruction Score: 36.909336\n",
      "Validation MSE Score: 0.004947287\n",
      "\n",
      "Epoch: 15\n",
      "Total Loss: 0.4965775149209159\n",
      "Reconstruction Loss: 0.4899170769112451\n",
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      "Trainig Reconstruction Score: 37.614437\n",
      "Training MSE Score: 0.0050454275\n",
      "Validation Reconstruction Score: 37.54352\n",
      "Validation MSE Score: 0.004440211\n",
      "\n",
      "Epoch: 16\n",
      "Total Loss: 0.49427244918687\n",
      "Reconstruction Loss: 0.48774197442190986\n",
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      "Trainig Reconstruction Score: 36.729725\n",
      "Training MSE Score: 0.004981063\n",
      "Validation Reconstruction Score: 36.79433\n",
      "Validation MSE Score: 0.0044028806\n",
      "\n",
      "Epoch: 17\n",
      "Total Loss: 0.49213641796793256\n",
      "Reconstruction Loss: 0.4855686677353723\n",
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      "Validation Reconstruction Score: 36.74224\n",
      "Validation MSE Score: 0.004129322\n",
      "\n",
      "Epoch: 18\n",
      "Total Loss: 0.49039450883865354\n",
      "Reconstruction Loss: 0.4839350419385093\n",
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      "Validation Reconstruction Score: 36.483166\n",
      "Validation MSE Score: 0.004996425\n",
      "\n",
      "Epoch: 19\n",
      "Total Loss: 0.4896222067730767\n",
      "Reconstruction Loss: 0.48307785093784333\n",
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      "\n",
      "Epoch: 20\n",
      "Total Loss: 0.48650558505739483\n",
      "Reconstruction Loss: 0.48003985626356943\n",
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      "Validation Reconstruction Score: 36.715256\n",
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      "\n",
      "Epoch: 21\n",
      "Total Loss: 0.4860398130757468\n",
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      "Validation Reconstruction Score: 36.23048\n",
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      "\n",
      "Epoch: 22\n",
      "Total Loss: 0.4879304404769625\n",
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      "Validation Reconstruction Score: 36.26963\n",
      "Validation MSE Score: 0.0042499667\n",
      "\n",
      "Epoch: 23\n",
      "Total Loss: 0.48288093422140393\n",
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      "Validation Reconstruction Score: 36.428844\n",
      "Validation MSE Score: 0.0042270618\n",
      "\n",
      "Epoch: 24\n",
      "Total Loss: 0.47951208182743615\n",
      "Reconstruction Loss: 0.4731487823384149\n",
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      "Validation Reconstruction Score: 36.014454\n",
      "Validation MSE Score: 0.0041651884\n",
      "\n",
      "Epoch: 25\n",
      "Total Loss: 0.4781440258026123\n",
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      "\n",
      "Epoch: 26\n",
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      "Validation Reconstruction Score: 35.863705\n",
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      "\n",
      "Epoch: 27\n",
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     "text": [
      "Trainig Reconstruction Score: 35.58049\n",
      "Training MSE Score: 0.0051095835\n",
      "Validation Reconstruction Score: 35.681667\n",
      "Validation MSE Score: 0.0040906286\n",
      "\n",
      "Epoch: 28\n",
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      "Validation Reconstruction Score: 36.4201\n",
      "Validation MSE Score: 0.0041813543\n",
      "\n",
      "Epoch: 29\n",
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      "Validation Reconstruction Score: 35.50915\n",
      "Validation MSE Score: 0.0041396827\n",
      "\n",
      "Epoch: 30\n",
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      "Validation Reconstruction Score: 35.546227\n",
      "Validation MSE Score: 0.0040266993\n",
      "\n",
      "Epoch: 31\n",
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      "Validation Reconstruction Score: 35.483936\n",
      "Validation MSE Score: 0.0039960076\n",
      "New Best Model Saved!\n",
      "\n",
      "Epoch: 32\n",
      "Total Loss: 0.46733555921486447\n",
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      "Validation MSE Score: 0.004343538\n",
      "New Best Model Saved!\n",
      "\n",
      "Epoch: 33\n",
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      "Validation Reconstruction Score: 35.41255\n",
      "Validation MSE Score: 0.004260473\n",
      "New Best Model Saved!\n",
      "\n",
      "Epoch: 34\n",
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      "Validation Reconstruction Score: 35.27401\n",
      "Validation MSE Score: 0.004099587\n",
      "New Best Model Saved!\n",
      "\n",
      "Epoch: 35\n",
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      "Validation MSE Score: 0.004067494\n",
      "\n",
      "Epoch: 36\n",
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      "Validation MSE Score: 0.0041797156\n",
      "\n",
      "Epoch: 37\n",
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      "Validation Reconstruction Score: 36.009514\n",
      "Validation MSE Score: 0.004152091\n",
      "\n",
      "Epoch: 38\n",
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      "Validation Reconstruction Score: 35.312504\n",
      "Validation MSE Score: 0.004274996\n",
      "\n",
      "Epoch: 39\n",
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      "Validation Reconstruction Score: 35.02842\n",
      "Validation MSE Score: 0.00397161\n",
      "New Best Model Saved!\n",
      "\n",
      "Epoch: 40\n",
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      "Validation Reconstruction Score: 35.036083\n",
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      "\n",
      "Epoch: 41\n",
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      "\n",
      "Epoch: 42\n",
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      "\n",
      "Epoch: 43\n",
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      "\n",
      "Epoch: 44\n",
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      "\n",
      "Epoch: 45\n",
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      "Validation Reconstruction Score: 35.0079\n",
      "Validation MSE Score: 0.0039531244\n",
      "New Best Model Saved!\n",
      "\n",
      "Epoch: 46\n",
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      "Validation Reconstruction Score: 35.01626\n",
      "Validation MSE Score: 0.0037655653\n",
      "\n",
      "Epoch: 47\n",
      "Total Loss: 0.4515148652451379\n",
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      "\n",
      "Epoch: 48\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
      "Epoch: 104\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
      "Epoch: 108\n"
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     "text": [
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "New Best Model Saved!\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "Total Loss: 0.4201251996415002\n",
      "Reconstruction Loss: 0.4147705273968833\n",
      "KL Loss: 0.001248807124128299\n",
      "Regression Loss: 0.004105863587132522\n",
      "Trainig Reconstruction Score: 33.611294\n",
      "Training MSE Score: 0.00409967\n",
      "Validation Reconstruction Score: 34.048553\n",
      "Validation MSE Score: 0.0036023632\n",
      "\n",
      "Epoch: 194\n",
      "Total Loss: 0.42001631685665675\n",
      "Reconstruction Loss: 0.414649869288717\n",
      "KL Loss: 0.001249203019376312\n",
      "Regression Loss: 0.004117246511824695\n",
      "Trainig Reconstruction Score: 33.62401\n",
      "Training MSE Score: 0.0041047665\n",
      "Validation Reconstruction Score: 34.05492\n",
      "Validation MSE Score: 0.0036038714\n",
      "\n",
      "Epoch: 195\n",
      "Total Loss: 0.4201973182814462\n",
      "Reconstruction Loss: 0.41483664640358514\n",
      "KL Loss: 0.0012483831944077144\n",
      "Regression Loss: 0.004112288421518835\n",
      "Trainig Reconstruction Score: 33.63444\n",
      "Training MSE Score: 0.004103879\n",
      "Validation Reconstruction Score: 34.06109\n",
      "Validation MSE Score: 0.0036110098\n",
      "\n",
      "Epoch: 196\n",
      "Total Loss: 0.4201708802155086\n",
      "Reconstruction Loss: 0.41481023813997\n",
      "KL Loss: 0.0012488653949861016\n",
      "Regression Loss: 0.004111775830720685\n",
      "Trainig Reconstruction Score: 33.609364\n",
      "Training MSE Score: 0.0041072285\n",
      "Validation Reconstruction Score: 34.049088\n",
      "Validation MSE Score: 0.003609286\n",
      "\n",
      "Epoch: 197\n",
      "Total Loss: 0.41996026805468967\n",
      "Reconstruction Loss: 0.414594184075083\n",
      "KL Loss: 0.001248397014569491\n",
      "Regression Loss: 0.004117687036549407\n",
      "Trainig Reconstruction Score: 33.619625\n",
      "Training MSE Score: 0.004105293\n",
      "Validation Reconstruction Score: 34.06039\n",
      "Validation MSE Score: 0.0036131807\n",
      "\n",
      "Epoch: 198\n",
      "Total Loss: 0.4199108191898891\n",
      "Reconstruction Loss: 0.41454580639089855\n",
      "KL Loss: 0.0012477466836571694\n",
      "Regression Loss: 0.004117264698392579\n",
      "Trainig Reconstruction Score: 33.606625\n",
      "Training MSE Score: 0.0040997798\n",
      "Validation Reconstruction Score: 34.0387\n",
      "Validation MSE Score: 0.0035963391\n",
      "\n",
      "Epoch: 199\n",
      "Total Loss: 0.4199937096663884\n",
      "Reconstruction Loss: 0.4146368030990873\n",
      "KL Loss: 0.0012481645215302705\n",
      "Regression Loss: 0.004108741837886295\n",
      "Trainig Reconstruction Score: 33.612644\n",
      "Training MSE Score: 0.0040996675\n",
      "Validation Reconstruction Score: 34.06871\n",
      "Validation MSE Score: 0.0035991096\n"
     ]
    }
   ],
   "source": [
    "# VAE conv kernel size = 7 z_dim=2\n",
    "BATCH_SIZE = 10\n",
    "train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=BATCH_SIZE, shuffle=True, num_workers=0)\n",
    "train_loader_score = torch.utils.data.DataLoader(train_dataset, batch_size=1, shuffle=True, num_workers=0)\n",
    "val_loader = torch.utils.data.DataLoader(val_dataset, batch_size=1, shuffle=False, num_workers=0)\n",
    "test_loader = torch.utils.data.DataLoader(test_dataset, batch_size=1, shuffle=False, num_workers=0)\n",
    "\n",
    "#instantiate your model here:\n",
    "model = VAE_REG(kernel_size=5, z_dim=2)\n",
    "model = model.cuda()\n",
    "\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.01, momentum=0.9, nesterov=True)\n",
    "n_epochs = 200\n",
    "# Learning rate is reduced after plateauing to stabilize the end of training.\n",
    "# use the learning rate scheduler as defined here. Example on how to integrate it to training in\n",
    "# https://pytorch.org/docs/stable/optim.html#torch.optim.lr_scheduler.StepLR\n",
    "scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=150, gamma=0.1)\n",
    "\n",
    "train_recon_scores = []\n",
    "train_r2_scores = []\n",
    "val_recon_scores = []\n",
    "val_r2_scores = []\n",
    "target_score = 35.5 # Want score to be less than this\n",
    "best_score = 50\n",
    "best_model = copy.deepcopy(model)\n",
    "\n",
    "print('Starting Training!')\n",
    "for epoch in range(n_epochs):\n",
    "    print('\\nEpoch: ' + str(epoch))\n",
    "    scheduler.step()\n",
    "    \n",
    "    model.train()\n",
    "    \n",
    "    total_losses = []\n",
    "    reconstruction_losses = []\n",
    "    kl_losses = []\n",
    "    reg_losses = []\n",
    "    for image, attribute, name in train_loader:\n",
    "        optimizer.zero_grad()\n",
    "        image = image.cuda()\n",
    "        attribute = attribute.cuda()\n",
    "        recon, mu, logvar, reg = model(image)\n",
    "        reconstruction_loss, kl_loss, reg_loss = loss_function(recon, image, mu, logvar, attribute, reg, BATCH_SIZE)\n",
    "        loss = reconstruction_loss + kl_loss + reg_loss\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        \n",
    "        total_losses.append(loss.item())\n",
    "        reconstruction_losses.append(reconstruction_loss.item())\n",
    "        kl_losses.append(kl_loss.item())\n",
    "        reg_losses.append(reg_loss.item())\n",
    "        \n",
    "    print('Total Loss: ' + str(np.mean(total_losses)))\n",
    "    print('Reconstruction Loss: ' + str(np.mean(reconstruction_losses)))\n",
    "    print('KL Loss: ' + str(np.mean(kl_losses)))\n",
    "    print('Regression Loss: ' + str(np.mean(reg_losses)))\n",
    "    \n",
    "    # Get training data accuracy\n",
    "    train_recon_score, train_r2 = get_score_model(model, train_loader_score)\n",
    "    print('Trainig Reconstruction Score: ' + str(train_recon_score))\n",
    "    print('Training MSE Score: ' + str(train_r2))\n",
    "    train_recon_scores.append(train_recon_score)\n",
    "    train_r2_scores.append(train_r2)\n",
    "    \n",
    "    # Get validation data accuracy\n",
    "    val_recon_score, val_r2 = get_score_model(model, val_loader)\n",
    "    print('Validation Reconstruction Score: ' + str(val_recon_score))\n",
    "    print('Validation MSE Score: ' + str(val_r2))\n",
    "    val_recon_scores.append(val_recon_score)\n",
    "    val_r2_scores.append(val_r2)\n",
    "    \n",
    "    # Save Best Model - Based on Reconstruction Score\n",
    "    if val_recon_score < target_score and val_recon_score < best_score:\n",
    "        best_score = val_recon_score\n",
    "        best_model = copy.deepcopy(model)\n",
    "        print('New Best Model Saved!')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Training and Validation Score\n",
    "plt.plot(range(n_epochs), train_recon_scores, 'b', range(n_epochs), val_recon_scores, 'r')\n",
    "plt.title('L2 Distance for VAE')\n",
    "plt.legend(['Training Data', 'Validation Data'])\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('L2 Distance Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot Training and Validation Score\n",
    "plt.plot(range(n_epochs), train_r2_scores, 'b', range(n_epochs), val_r2_scores, 'r')\n",
    "plt.title('MSE for VAE')\n",
    "plt.legend(['Training Data', 'Validation Data'])\n",
    "plt.xlabel('Epoch Number')\n",
    "plt.ylabel('MSE Score')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show examples of the ground truth image and the reconstruction after\n",
    "# a pass through the autoencoder\n",
    "def get_example_outputs(model, data_loader):\n",
    "    model.eval()\n",
    "    ground_truth = []\n",
    "    model_output = []\n",
    "    with torch.no_grad():\n",
    "        for image, attribute, name in data_loader:\n",
    "            image = image.cuda()\n",
    "            recon, mu, var, reg = model(image)\n",
    "            model_output.append(recon)\n",
    "            ground_truth.append(image)\n",
    "            if len(model_output) == 2:\n",
    "                return model_output, ground_truth\n",
    "            \n",
    "model_out, gt = get_example_outputs(model, val_loader)\n",
    "for idx in range(2):\n",
    "    plt.figure()\n",
    "    plt.title(\"Reconstruction \" + str(idx))\n",
    "    model_out[idx] = model_out[idx].view(model_out[idx].shape[1], model_out[idx].shape[2], model_out[idx].shape[3])\n",
    "    plt.imshow(model_out[idx].permute([1, 2, 0]).cpu().numpy())\n",
    "    plt.figure()\n",
    "    plt.title(\"Original Image \" + str(idx))\n",
    "    gt[idx] = gt[idx].view(gt[idx].shape[1], gt[idx].shape[2], gt[idx].shape[3])\n",
    "    plt.imshow(gt[idx].permute([1, 2, 0]).cpu().numpy())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test L2 Score: 34.210594\n",
      "Test MSE Score: 0.004163136\n"
     ]
    }
   ],
   "source": [
    "test_recon_score, test_mse_score = get_score_model(best_model, test_loader)\n",
    "print('Test L2 Score: ' + str(test_recon_score))\n",
    "print('Test MSE Score: ' + str(test_mse_score))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Gets the twod representation of teh data\n",
    "def get_2D_representation(model, data_loader):\n",
    "    model.eval()\n",
    "    all_frame = pd.DataFrame()\n",
    "    with torch.no_grad():\n",
    "        for image, attribute, name in data_loader:\n",
    "            image = image.cuda()\n",
    "            two_d = model.representation(image)\n",
    "            two_d = two_d.cpu().numpy()\n",
    "            frame = pd.DataFrame(data=two_d, columns=['x', 'y'])\n",
    "            frame['max_stress'] = attribute.cpu().numpy()[0] \n",
    "            all_frame = all_frame.append(frame)\n",
    "    return all_frame\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.lines import Line2D\n",
    "\n",
    "frame = get_2D_representation(best_model, train_loader_score)\n",
    "frame = frame.sort_values('max_stress')\n",
    "minimum = frame.max_stress.min()\n",
    "maximum = frame.max_stress.max()\n",
    "fig, ax = plt.subplots(dpi=200)\n",
    "ax.axes.get_xaxis().set_visible(False)\n",
    "ax.axes.get_yaxis().set_visible(False)\n",
    "blue_cmap = cm.get_cmap('Blues')\n",
    "\n",
    "plt.scatter(frame.x, frame.y, c=frame.max_stress, s=30, cmap=blue_cmap, edgecolors='k')\n",
    "\n",
    "legend_elements = [Line2D([0], [0], marker='o', color='w', label='Minimum', markeredgewidth=1, markeredgecolor='k', markerfacecolor=blue_cmap(0), markersize=6),\n",
    "                   Line2D([0], [0], marker='o', color='w', label='Maximum', markeredgewidth=1, markeredgecolor='k', markerfacecolor=blue_cmap(maximum), markersize=6)]\n",
    "plt.legend(handles=legend_elements)\n",
    "\n",
    "plt.savefig('twodrep.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
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