neural_style.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import scipy.io\n",
    "import scipy.misc\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import time\n",
    "from IPython.display import Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "content_file_name = 'hfwu.jpg'\n",
    "style_file_name = 'style3.jpg'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "data = scipy.io.loadmat('./imagenet-vgg-verydeep-19.mat')\n",
    "\n",
    "image_content = scipy.misc.imread('./images/'+content_file_name)\n",
    "image_content = image_content.astype('float32')\n",
    "image_content = np.ndarray.reshape(image_content,((1,) + image_content.shape)) # 1 means batch_size\n",
    "#image_content = np.ndarray.reshape(image_content.shape + (1,)) it is needed to handle gray scale image \n",
    "\n",
    "image_style = scipy.misc.imread('./images/'+style_file_name)\n",
    "image_style = image_style.astype('float32')\n",
    "image_style = np.ndarray.reshape(image_style,((1,) + image_style.shape)) # 1 means batch_size\n",
    "#image_style = np.ndarray.reshape(image_style.shape + (1,)) it is needed to handle gray scale image "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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IHReKvGXhnxqmqeBdUtdW8GXcmJbGey81F1G1dmZ2QkLh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2NKeBlBudKV79z8qotQbSGkuI5GuNUmyJr1uoUZG2Mfwr06ew9jd8D2TN4qsZ5FZpVuUdn3djwR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\nFanKeajJ5oDkEfWgZYzkUE4FNB+9TZHIAqRol3UwnbTYnJNJKcGgR//Z\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# content image\n",
    "Image(filename = './images/'+content_file_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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ccVT8221bTolgDo/kKcwpsxhNmNpJ4zz355xzV0b8qdia1OMppN6It+HJvPgv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\nNpxnjBxnNdJdtDdwpJBO0ccybF82NmKEkYxtOR0+n5VjRxHN7souL7a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TXsyx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\n3bcI4xhV9AKh/gX6CoZohwxmhev4CmhMDjOOcUd/zoYH/9k=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# style image\n",
    "Image(filename = './images/'+style_file_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def _conv_layer(input, weights, bias):\n",
    "    conv = tf.nn.conv2d(input, tf.constant(weights), strides=(1, 1, 1, 1),\n",
    "            padding='SAME')\n",
    "    return tf.nn.bias_add(conv, bias)\n",
    "\n",
    "def _pool_layer(input):\n",
    "    return tf.nn.max_pool(input, ksize=(1, 2, 2, 1), strides=(1, 2, 2, 1),\n",
    "            padding='SAME')\n",
    "\n",
    "def preprocess(image, mean_pixel):\n",
    "    return (image - mean_pixel).astype('float32')\n",
    "\n",
    "def unprocess(image, mean_pixel):\n",
    "    return (image + mean_pixel).astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def net(input_image):\n",
    "    layers = (\n",
    "        'conv1_1', 'relu1_1', 'conv1_2', 'relu1_2', 'pool1',\n",
    "\n",
    "        'conv2_1', 'relu2_1', 'conv2_2', 'relu2_2', 'pool2',\n",
    "\n",
    "        'conv3_1', 'relu3_1', 'conv3_2', 'relu3_2', 'conv3_3',\n",
    "        'relu3_3', 'conv3_4', 'relu3_4', 'pool3',\n",
    "\n",
    "        'conv4_1', 'relu4_1', 'conv4_2', 'relu4_2', 'conv4_3',\n",
    "        'relu4_3', 'conv4_4', 'relu4_4', 'pool4',\n",
    "\n",
    "        'conv5_1', 'relu5_1', 'conv5_2', 'relu5_2', 'conv5_3',\n",
    "        'relu5_3', 'conv5_4', 'relu5_4'\n",
    "    )\n",
    "    weight = data['layers'][0]\n",
    "    net = {}\n",
    "    current = input_image\n",
    "    for i, name in enumerate(layers):\n",
    "        kind = name[:4]\n",
    "        if kind == 'conv':\n",
    "            kernels, bias = weight[i][0][0][0][0]\n",
    "            # matconvnet: weights are [width, height, in_channels, out_channels]\n",
    "            # tensorflow: weights are [height, width, in_channels, out_channels]\n",
    "            kernels = np.transpose(kernels, (1, 0, 2, 3))\n",
    "            bias = bias.reshape(-1)\n",
    "            current = _conv_layer(current, kernels, bias)\n",
    "        elif kind == 'relu':\n",
    "            current = tf.nn.relu(current)\n",
    "        elif kind == 'pool':\n",
    "            current = _pool_layer(current)\n",
    "        net[name] = current\n",
    "\n",
    "    assert len(net) == len(layers)\n",
    "    return net#, mean_pixel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "mean = data['normalization'][0][0][0]\n",
    "mean_pixel = np.mean(mean, axis=(0, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# CONTENT_LAYER = 'relu4_2'\n",
    "# content_features = {}\n",
    "\n",
    "# with tf.Session() as sess:\n",
    "#     content_pre = preprocess(image_content, mean_pixel)\n",
    "#     content_net = net(np.squeeze(data['layers']), content_pre)\n",
    "#     content_features[CONTENT_LAYER] = content_net[CONTENT_LAYER].eval()\n",
    "\n",
    "CONTENT_LAYERS = ('conv1_1', 'conv2_1', 'conv4_1', 'conv4_2')\n",
    "content_features = {}\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    content_pre = preprocess(image_content, mean_pixel)\n",
    "    content_net = net(content_pre)\n",
    "    for layer in CONTENT_LAYERS:\n",
    "        content_features[layer] = content_net[layer].eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "STYLE_LAYERS = ('conv3_1','conv5_1')\n",
    "style_features = {}\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    style_pre = preprocess(image_style, mean_pixel)\n",
    "    style_net = net(style_pre)\n",
    "    for layer in STYLE_LAYERS:\n",
    "        features = style_net[layer].eval()\n",
    "        features = np.reshape(features, (-1, features.shape[3]))\n",
    "        gram = np.matmul(features.T, features) / features.size\n",
    "        style_features[layer] = gram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# make stylized image using backpropogation\n",
    "initial = None\n",
    "#initial = scipy.misc.imread('./images/cat.jpg')\n",
    "if initial is None:\n",
    "    noise = np.random.normal(size=image_content.shape, scale=np.std(image_content) * 0.1)\n",
    "    initial = tf.random_normal(image_content.shape) * 0.256\n",
    "else:\n",
    "    initial = np.array([preprocess(initial, mean_pixel)])\n",
    "    initial = initial.astype('float32')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "image = tf.Variable(initial)\n",
    "image_net = net(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "content_weight = 5e0\n",
    "style_weight = 1e4\n",
    "tv_weight = 1e3\n",
    "learning_rate = 1e0\n",
    "iterations =  100\n",
    "checkpoint_iterations = 10\n",
    "print_iterations = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "try:\n",
    "    reduce\n",
    "except NameError:\n",
    "    from functools import reduce"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# content loss\n",
    "# content_loss = content_weight * (2 * tf.nn.l2_loss(\n",
    "#         image_net[CONTENT_LAYER] - content_features[CONTENT_LAYER]) / \n",
    "#         content_features[CONTENT_LAYER].size)\n",
    "content_loss = 0\n",
    "content_losses = []\n",
    "for content_layer in CONTENT_LAYERS:\n",
    "    content_losses.append(2 * tf.nn.l2_loss(\n",
    "                          image_net[content_layer] - content_features[content_layer]) / \n",
    "                          content_features[content_layer].size)\n",
    "content_loss += content_weight * reduce(tf.add, content_losses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# style loss\n",
    "style_loss = 0\n",
    "style_losses = []\n",
    "for style_layer in STYLE_LAYERS:\n",
    "    layer = image_net[style_layer]\n",
    "    _, height, width, number = map(lambda i: i.value, layer.get_shape())\n",
    "    size = height * width * number\n",
    "    feats = tf.reshape(layer, (-1, number))\n",
    "    gram = tf.matmul(tf.transpose(feats), feats) / size\n",
    "    style_gram = style_features[style_layer]\n",
    "    style_losses.append(2 * tf.nn.l2_loss(gram - style_gram) / style_gram.size)\n",
    "style_loss += style_weight * reduce(tf.add, style_losses)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def _tensor_size(tensor):\n",
    "    from operator import mul\n",
    "    return reduce(mul, (d.value for d in tensor.get_shape()), 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# total variation denoising\n",
    "tv_y_size = _tensor_size(image[:,1:,:,:])\n",
    "tv_x_size = _tensor_size(image[:,:,1:,:])\n",
    "tv_loss = tv_weight * 2 * (\n",
    "        (tf.nn.l2_loss(image[:,1:,:,:] - image[:,:image_content.shape[1]-1,:,:]) /\n",
    "            tv_y_size) +\n",
    "        (tf.nn.l2_loss(image[:,:,1:,:] - image[:,:,:image_content.shape[2]-1,:]) /\n",
    "            tv_x_size))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# overall loss\n",
    "loss = content_loss + style_loss + tv_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# optimizer setup\n",
    "train_step = tf.train.AdamOptimizer(learning_rate).minimize(loss)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def imsave(path, img):\n",
    "    img = np.clip(img, 0, 255).astype(np.uint8)\n",
    "    scipy.misc.imsave(path, img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "ename": "MemoryError",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mMemoryError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-25-2724015ae30c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSession\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msess\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m     \u001b[0msess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minitialize_all_variables\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0miterations\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m         \u001b[0mtrain_step\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m    380\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    381\u001b[0m       result = self._run(None, fetches, feed_dict, options_ptr,\n\u001b[0;32m--> 382\u001b[0;31m                          run_metadata_ptr)\n\u001b[0m\u001b[1;32m    383\u001b[0m       \u001b[0;32mif\u001b[0m \u001b[0mrun_metadata\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    384\u001b[0m         \u001b[0mproto_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtf_session\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTF_GetBuffer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrun_metadata_ptr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m_run\u001b[0;34m(self, handle, fetches, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m    653\u001b[0m     \u001b[0mmovers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_update_with_movers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeed_dict_string\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeed_map\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    654\u001b[0m     results = self._do_run(handle, target_list, unique_fetches,\n\u001b[0;32m--> 655\u001b[0;31m                            feed_dict_string, options, run_metadata)\n\u001b[0m\u001b[1;32m    656\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    657\u001b[0m     \u001b[0;31m# User may have fetched the same tensor multiple times, but we\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m_do_run\u001b[0;34m(self, handle, target_list, fetch_list, feed_dict, options, run_metadata)\u001b[0m\n\u001b[1;32m    721\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mhandle\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    722\u001b[0m       return self._do_call(_run_fn, self._session, feed_dict, fetch_list,\n\u001b[0;32m--> 723\u001b[0;31m                            target_list, options, run_metadata)\n\u001b[0m\u001b[1;32m    724\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    725\u001b[0m       return self._do_call(_prun_fn, self._session, handle, feed_dict,\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m_do_call\u001b[0;34m(self, fn, *args)\u001b[0m\n\u001b[1;32m    728\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_do_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    729\u001b[0m     \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 730\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    731\u001b[0m     \u001b[0;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mOpError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    732\u001b[0m       \u001b[0mmessage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompat\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mas_text\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmessage\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m_run_fn\u001b[0;34m(session, feed_dict, fetch_list, target_list, options, run_metadata)\u001b[0m\n\u001b[1;32m    706\u001b[0m                 run_metadata):\n\u001b[1;32m    707\u001b[0m       \u001b[0;31m# Ensure any changes to the graph are reflected in the runtime.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 708\u001b[0;31m       \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_extend_graph\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    709\u001b[0m       \u001b[0;32mwith\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_exception_on_not_ok_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mstatus\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    710\u001b[0m         return tf_session.TF_Run(session, options,\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/tensorflow/python/client/session.py\u001b[0m in \u001b[0;36m_extend_graph\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    755\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mraise_exception_on_not_ok_status\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mstatus\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    756\u001b[0m           tf_session.TF_ExtendGraph(\n\u001b[0;32m--> 757\u001b[0;31m               self._session, graph_def.SerializeToString(), status)\n\u001b[0m\u001b[1;32m    758\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_opened\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    759\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mSerializeToString\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1062\u001b[0m           'Message %s is missing required fields: %s' % (\n\u001b[1;32m   1063\u001b[0m           self.DESCRIPTOR.full_name, ','.join(self.FindInitializationErrors())))\n\u001b[0;32m-> 1064\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSerializePartialToString\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1065\u001b[0m   \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSerializeToString\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSerializeToString\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1066\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mSerializePartialToString\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1071\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mSerializePartialToString\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1072\u001b[0m     \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mBytesIO\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1073\u001b[0;31m     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_InternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mout\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1074\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mout\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgetvalue\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1075\u001b[0m   \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSerializePartialToString\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mSerializePartialToString\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mInternalSerialize\u001b[0;34m(self, write_bytes)\u001b[0m\n\u001b[1;32m   1077\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mInternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1078\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mListFields\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1079\u001b[0;31m       \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1080\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mtag_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue_bytes\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unknown_fields\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1081\u001b[0m       \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/encoder.py\u001b[0m in \u001b[0;36mEncodeRepeatedField\u001b[0;34m(write, value)\u001b[0m\n\u001b[1;32m    755\u001b[0m         \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    756\u001b[0m         \u001b[0mlocal_EncodeVarint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0melement\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mByteSize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 757\u001b[0;31m         \u001b[0melement\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_InternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    758\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mEncodeRepeatedField\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    759\u001b[0m   \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mInternalSerialize\u001b[0;34m(self, write_bytes)\u001b[0m\n\u001b[1;32m   1077\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mInternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1078\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mListFields\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1079\u001b[0;31m       \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1080\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mtag_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue_bytes\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unknown_fields\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1081\u001b[0m       \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/encoder.py\u001b[0m in \u001b[0;36mEncodeField\u001b[0;34m(write, value)\u001b[0m\n\u001b[1;32m    819\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mkey\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    820\u001b[0m       \u001b[0mentry_msg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmessage_type\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_concrete_class\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 821\u001b[0;31m       \u001b[0mencode_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentry_msg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    822\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    823\u001b[0m   \u001b[0;32mreturn\u001b[0m \u001b[0mEncodeField\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/encoder.py\u001b[0m in \u001b[0;36mEncodeField\u001b[0;34m(write, value)\u001b[0m\n\u001b[1;32m    761\u001b[0m       \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    762\u001b[0m       \u001b[0mlocal_EncodeVarint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mByteSize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 763\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_InternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    764\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mEncodeField\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    765\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mInternalSerialize\u001b[0;34m(self, write_bytes)\u001b[0m\n\u001b[1;32m   1077\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mInternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1078\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mListFields\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1079\u001b[0;31m       \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1080\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mtag_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue_bytes\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unknown_fields\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1081\u001b[0m       \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/encoder.py\u001b[0m in \u001b[0;36mEncodeField\u001b[0;34m(write, value)\u001b[0m\n\u001b[1;32m    761\u001b[0m       \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    762\u001b[0m       \u001b[0mlocal_EncodeVarint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mByteSize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 763\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_InternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    764\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mEncodeField\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    765\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mInternalSerialize\u001b[0;34m(self, write_bytes)\u001b[0m\n\u001b[1;32m   1077\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mInternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1078\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mListFields\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1079\u001b[0;31m       \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1080\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mtag_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue_bytes\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unknown_fields\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1081\u001b[0m       \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/encoder.py\u001b[0m in \u001b[0;36mEncodeField\u001b[0;34m(write, value)\u001b[0m\n\u001b[1;32m    761\u001b[0m       \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    762\u001b[0m       \u001b[0mlocal_EncodeVarint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mByteSize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 763\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_InternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    764\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mEncodeField\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    765\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/python_message.py\u001b[0m in \u001b[0;36mInternalSerialize\u001b[0;34m(self, write_bytes)\u001b[0m\n\u001b[1;32m   1077\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mInternalSerialize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1078\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mListFields\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1079\u001b[0;31m       \u001b[0mfield_descriptor\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_encoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfield_value\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1080\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mtag_bytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue_bytes\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_unknown_fields\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1081\u001b[0m       \u001b[0mwrite_bytes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/local/lib/python3.4/site-packages/google/protobuf/internal/encoder.py\u001b[0m in \u001b[0;36mEncodeField\u001b[0;34m(write, value)\u001b[0m\n\u001b[1;32m    719\u001b[0m       \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtag\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    720\u001b[0m       \u001b[0mlocal_EncodeVarint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlocal_len\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 721\u001b[0;31m       \u001b[0;32mreturn\u001b[0m \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    722\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mEncodeField\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    723\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mMemoryError\u001b[0m: "
     ]
    }
   ],
   "source": [
    "# optimization\n",
    "best_loss = float('inf')\n",
    "best = None\n",
    "\n",
    "with tf.Session() as sess:\n",
    "    sess.run(tf.initialize_all_variables())\n",
    "    for i in range(iterations):\n",
    "        train_step.run()\n",
    "        \n",
    "        if i % checkpoint_iterations == 0 or i == iterations - 1:\n",
    "            this_loss = loss.eval()\n",
    "            if this_loss < best_loss:\n",
    "                best_loss = this_loss\n",
    "                best = image.eval()\n",
    "            # save a check point\n",
    "            import os\n",
    "            try:\n",
    "                os.makedirs('./checks/'+str.split(content_file_name,'.')[0])\n",
    "            except OSError:\n",
    "                pass\n",
    "            timestr = time.strftime(\"%Y%m%d_%H%M%S\")\n",
    "            filename_cp = './checks/'+str.split(content_file_name,'.')[0]+'/'+timestr+'.jpg'\n",
    "            cp = unprocess(best.reshape(image_content.shape[1:]), mean_pixel)\n",
    "            imsave(filename_cp, cp)\n",
    "        \n",
    "        if i % print_iterations == 0 or i == iterations - 1:\n",
    "            print('Iteration %d/%d' % (i + 1, iterations))\n",
    "            print('  content loss: %g' % content_loss.eval())\n",
    "            print('    style loss: %g' % style_loss.eval())\n",
    "            print('       tv loss: %g' % tv_loss.eval())\n",
    "            print('    total loss: %g' % loss.eval())\n",
    "\n",
    "    output = unprocess(best.reshape(image_content.shape[1:]), mean_pixel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "imsave('./images/output_'+content_file_name, output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/jpeg": 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gn0rRe6ck3zWTN5WDtgZJ/iJHSq90FhXMgOMDoCegqa3XlF6hjwtN8QW2oLpY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\nX5LhgvyjPQcVV3N5Snccg+tPljKS03LhCaVnL8D/2Q==\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image(filename = './images/output_'+content_file_name)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.4.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}