notebooks/training.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "indoor-outdoor-classification-training.ipynb",
      "version": "0.3.2",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "3_i02rrIH4qU",
        "colab_type": "code",
        "outputId": "fec332c0-fa67-4fdb-b7f3-919fa7b15d79",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "import os\n",
        "import glob\n",
        "import math\n",
        "import shutil\n",
        "import random\n",
        "import tarfile\n",
        "import tensorflow as tf\n",
        "import tensorflow_hub as hub"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING: Logging before flag parsing goes to stderr.\n",
            "W0519 03:33:07.798849 140479845271424 __init__.py:56] Some hub symbols are not available because TensorFlow version is less than 1.14\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vON1wG_PXyeW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "random.seed(0)\n",
        "tf.random.set_random_seed(0)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fr-ybLzUVdko",
        "colab_type": "text"
      },
      "source": [
        "# Data\n",
        "\n",
        "This notebook is meant to be run in Google Colab."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2_oFnfidNt_1",
        "colab_type": "code",
        "outputId": "7c7913ea-9033-4980-f223-1cdc678e97a7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        }
      },
      "source": [
        "try:\n",
        "  # drive\n",
        "  from google.colab import drive\n",
        "  drive.mount('/content/gdrive')\n",
        "  \n",
        "  # tensorboard\n",
        "  !wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip\n",
        "  !unzip -o ngrok-stable-linux-amd64.zip\n",
        "  \n",
        "  # same as model_dir below\n",
        "  log_dir = './log'\n",
        "  get_ipython().system_raw(\n",
        "    'tensorboard --logdir {} --host 0.0.0.0 --port 6006 &'\n",
        "    .format(log_dir)\n",
        "  )\n",
        "  get_ipython().system_raw('./ngrok http 6006 &')\n",
        "  !curl -s http://localhost:4040/api/tunnels | python3 -c \\\n",
        "    \"import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])\"\n",
        "  \n",
        "except ImportError:\n",
        "  print('Module google not found, assuming running locally')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount(\"/content/gdrive\", force_remount=True).\n",
            "--2019-05-19 03:33:08--  https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip\n",
            "Resolving bin.equinox.io (bin.equinox.io)... 52.4.95.48, 52.203.66.95, 3.209.102.29, ...\n",
            "Connecting to bin.equinox.io (bin.equinox.io)|52.4.95.48|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 16529980 (16M) [application/octet-stream]\n",
            "Saving to: ‘ngrok-stable-linux-amd64.zip.26’\n",
            "\n",
            "ngrok-stable-linux- 100%[===================>]  15.76M  20.1MB/s    in 0.8s    \n",
            "\n",
            "2019-05-19 03:33:09 (20.1 MB/s) - ‘ngrok-stable-linux-amd64.zip.26’ saved [16529980/16529980]\n",
            "\n",
            "Archive:  ngrok-stable-linux-amd64.zip\n",
            "  inflating: ngrok                   \n",
            "https://99e5f3d6.ngrok.io\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rdeXRn7YIJfa",
        "colab_type": "code",
        "outputId": "b9c37f7c-5567-4a35-e2f5-ec477ac42bc0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "def maybe_decompress_data(inpath='/content/gdrive/My Drive/indoor-outdoor-classification/data.tar.gz',\n",
        "                          outpath='/content/data'):\n",
        "  if not os.path.exists(outpath):\n",
        "    with tarfile.open(inpath, 'r:gz') as tf:\n",
        "      tf.extractall()\n",
        "  else:\n",
        "    print('{} exists, skipping'.format(outpath))\n",
        "    \n",
        "maybe_decompress_data()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/content/data exists, skipping\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RXpE96y6W9tE",
        "colab_type": "text"
      },
      "source": [
        "For cross-validation, we hold out entire videos' frames."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qzVfq6vqXCrb",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def train_test_split(filenames, class_path_index=-3, n_test_per_class=4):\n",
        "  train = []\n",
        "  test = []\n",
        "  \n",
        "  classnames = [filename.split(os.sep)[class_path_index] for filename in filenames]\n",
        "  videonames = [filename.split(os.sep)[-1].split('-')[0] for filename in filenames]\n",
        "  \n",
        "  for name in set(classnames):\n",
        "    videonames_this_class = set([videoname for classname, videoname in zip(classnames, videonames) if classname == name])\n",
        "    videonames_test = random.sample(videonames_this_class, n_test_per_class)\n",
        "    videonames_train = videonames_this_class - set(videonames_test)\n",
        "    train += [filename for filename, videoname in zip(filenames, videonames) if videoname in videonames_train]\n",
        "    test += [filename for filename, videoname in zip(filenames, videonames) if videoname in videonames_test]\n",
        "    \n",
        "  return train, test\n",
        "\n",
        "train, test = train_test_split(glob.glob('/content/data/**/*.png', recursive=True))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P5-Em_hRViut",
        "colab_type": "text"
      },
      "source": [
        "# Model\n",
        "\n",
        "We start with ResNet_v2_50 and train a binary classifier on top."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fT4xpuCsV_bO",
        "colab_type": "code",
        "outputId": "7c0c3bb1-c1a7-4129-9d44-917eeb273ed6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 22205
        }
      },
      "source": [
        "params = {\n",
        "    'class_path_index': -3,\n",
        "    'batch_size': 128,\n",
        "    'resize_image_size': 448,\n",
        "    'crop_image_size': 224,\n",
        "    'learning_rate': 0.001,\n",
        "    'num_epochs': 50\n",
        "}\n",
        "\n",
        "def model_fn(features, labels, mode, params):\n",
        "  '''\n",
        "  Model function (ResNet_v2_50) transfer learning\n",
        "  '''\n",
        "  learning_rate = params['learning_rate']\n",
        " \n",
        "  module = hub.Module('https://tfhub.dev/google/imagenet/resnet_v2_50/feature_vector/3')\n",
        "  features = module(features)\n",
        "  \n",
        "  logits = tf.layers.dense(features, 1, kernel_initializer=tf.initializers.glorot_uniform())\n",
        "  scores = tf.nn.sigmoid(logits)\n",
        "  \n",
        "  if mode == tf.estimator.ModeKeys.PREDICT:\n",
        "    outputs = {'scores': scores}\n",
        "    predict_outputs = tf.estimator.export.PredictOutput(outputs)\n",
        "    export_outputs = {tf.saved_model.signature_constants.PREDICT_METHOD_NAME: predict_outputs}\n",
        "    return tf.estimator.EstimatorSpec(\n",
        "        mode=mode,\n",
        "        predictions={'scores': scores},\n",
        "        export_outputs=export_outputs\n",
        "    )\n",
        "  \n",
        "  predictions = tf.round(scores)\n",
        "  accuracy = tf.metrics.accuracy(labels, predictions)\n",
        "  tf.summary.scalar('accuracy', accuracy[1])\n",
        "  \n",
        "  nll = tf.nn.sigmoid_cross_entropy_with_logits(labels=tf.cast(labels, tf.float32),\n",
        "                                                logits=tf.squeeze(logits))\n",
        "  loss = tf.reduce_mean(nll)\n",
        "  \n",
        "  optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)                                    \n",
        "  train_op = optimizer.minimize(loss, global_step=tf.train.get_global_step())\n",
        "  \n",
        "  return tf.estimator.EstimatorSpec(\n",
        "      mode=mode,\n",
        "      loss=loss,\n",
        "      train_op=train_op,\n",
        "      predictions={'scores': scores},\n",
        "      eval_metric_ops={'accuracy': accuracy}\n",
        "  )\n",
        "  \n",
        "\n",
        "def load_image(filename, params):\n",
        "  '''\n",
        "  Load and resize an image. \n",
        "  For simplicitly, we will resize it without preserving aspect ratio\n",
        "  '''\n",
        "  resize_image_size = params['resize_image_size']\n",
        "  \n",
        "  buffer = tf.read_file(filename)\n",
        "  image = tf.image.decode_png(buffer, channels=3)\n",
        "  image = tf.cast(image, tf.float32)\n",
        "  image = tf.image.resize_images(image, (resize_image_size, resize_image_size))\n",
        "\n",
        "  return image\n",
        "\n",
        "def preprocess_image(image, mode, params):\n",
        "  '''\n",
        "  For training, take a random crop and randomly flip left-to-right. \n",
        "  Otherwise, take a center crop.\n",
        "  '''\n",
        "  crop_image_size = params['crop_image_size']\n",
        "  resize_image_size = params['resize_image_size']\n",
        "\n",
        "  if mode == tf.estimator.ModeKeys.TRAIN:\n",
        "    image = tf.image.random_crop(image, (crop_image_size, crop_image_size, 3))\n",
        "    image = tf.image.random_flip_left_right(image)\n",
        "  else:\n",
        "    image = tf.image.central_crop(image, crop_image_size/resize_image_size)\n",
        "    \n",
        "  return image\n",
        "  \n",
        "def _input_fn(filenames, mode, params):\n",
        "  '''\n",
        "  Async input pipeline. Labels are sorted so indoor=0, outdoor=1\n",
        "  '''\n",
        "  class_path_index = params['class_path_index']\n",
        "  batch_size = params['batch_size']\n",
        "  \n",
        "  classnames = [filename.split(os.sep)[class_path_index] for filename in filenames]\n",
        "  lookup = {v: k for k, v in enumerate(sorted(set(classnames)))}\n",
        "  labels = [lookup[classname] for classname in classnames]\n",
        "  \n",
        "  dataset = tf.data.Dataset.from_tensor_slices((filenames, labels))\n",
        "  \n",
        "  if mode == tf.estimator.ModeKeys.TRAIN:\n",
        "    dataset = dataset.shuffle(buffer_size=len(filenames))\n",
        "    dataset = dataset.repeat()\n",
        "    \n",
        "  dataset = dataset.map(\n",
        "      lambda filename, label: (load_image(filename, params), label),\n",
        "      num_parallel_calls=os.cpu_count()\n",
        "  )\n",
        "  dataset = dataset.map(\n",
        "      lambda filename, label: (preprocess_image(filename, mode, params), label),\n",
        "      num_parallel_calls=os.cpu_count()\n",
        "  )\n",
        " \n",
        "  dataset = dataset.batch(batch_size)\n",
        "  dataset = dataset.prefetch(1)\n",
        "\n",
        "  return dataset\n",
        "  \n",
        "def train_input_fn(filenames, params):\n",
        "  return _input_fn(filenames, tf.estimator.ModeKeys.TRAIN, params)\n",
        "\n",
        "def eval_input_fn(filenames, params):\n",
        "  return _input_fn(filenames, tf.estimator.ModeKeys.EVAL, params)\n",
        "\n",
        "def serving_input_receiver_fn(params):\n",
        "  '''\n",
        "  Add preprocessing to serving graph\n",
        "  '''\n",
        "  inputs = tf.placeholder(dtype=tf.float32, shape=[None, None, None, 3])\n",
        "  image = preprocess_image(inputs, tf.estimator.ModeKeys.PREDICT, params)\n",
        "  receivers = {tf.saved_model.signature_constants.PREDICT_INPUTS: inputs}\n",
        "  return tf.estimator.export.TensorServingInputReceiver(image, receivers)\n",
        "\n",
        "model_dir = 'log'\n",
        "shutil.rmtree(model_dir, ignore_errors=True)\n",
        "\n",
        "epoch_steps = math.ceil(len(train)/params['batch_size'])\n",
        "max_steps = epoch_steps * params['num_epochs']\n",
        "\n",
        "config = tf.estimator.RunConfig(\n",
        "    save_checkpoints_steps=epoch_steps\n",
        ")\n",
        "\n",
        "estimator = tf.estimator.Estimator(\n",
        "    model_fn=model_fn,\n",
        "    params=params,\n",
        "    model_dir=model_dir,\n",
        "    config=config\n",
        ")\n",
        "\n",
        "train_spec = tf.estimator.TrainSpec(\n",
        "    input_fn=lambda: train_input_fn(train, params),\n",
        "    max_steps=max_steps\n",
        ")\n",
        "\n",
        "eval_spec = tf.estimator.EvalSpec(\n",
        "    input_fn=lambda: eval_input_fn(test, params),\n",
        "    name='test',\n",
        "    throttle_secs=0\n",
        ")\n",
        "\n",
        "tf.estimator.train_and_evaluate(estimator, train_spec, eval_spec)\n",
        "\n",
        "for filename, split in zip(['images_train.txt', 'images_test.txt'], [train, test]):\n",
        "  with open(os.path.join(model_dir, filename), 'w') as f:\n",
        "    f.write('\\n'.join(split))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Using config: {'_model_dir': 'log', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': 16, '_save_checkpoints_secs': None, '_session_config': allow_soft_placement: true\n",
            "graph_options {\n",
            "  rewrite_options {\n",
            "    meta_optimizer_iterations: ONE\n",
            "  }\n",
            "}\n",
            ", '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fc39d0017b8>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:12.453240 140479845271424 estimator.py:201] Using config: {'_model_dir': 'log', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': 16, '_save_checkpoints_secs': None, '_session_config': allow_soft_placement: true\n",
            "graph_options {\n",
            "  rewrite_options {\n",
            "    meta_optimizer_iterations: ONE\n",
            "  }\n",
            "}\n",
            ", '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7fc39d0017b8>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1}\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Not using Distribute Coordinator.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:12.468725 140479845271424 estimator_training.py:185] Not using Distribute Coordinator.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Running training and evaluation locally (non-distributed).\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:12.477108 140479845271424 training.py:610] Running training and evaluation locally (non-distributed).\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Start train and evaluate loop. The evaluate will happen after every checkpoint. Checkpoint frequency is determined based on RunConfig arguments: save_checkpoints_steps 16 or save_checkpoints_secs None.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:12.480598 140479845271424 training.py:698] Start train and evaluate loop. The evaluate will happen after every checkpoint. Checkpoint frequency is determined based on RunConfig arguments: save_checkpoints_steps 16 or save_checkpoints_secs None.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Colocations handled automatically by placer.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 03:33:12.493043 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_library.py:263: colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Colocations handled automatically by placer.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:12.624333 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:16.186165 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From <ipython-input-6-78079e9cea5c>:19: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use keras.layers.dense instead.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 03:33:16.307957 140479845271424 deprecation.py:323] From <ipython-input-6-78079e9cea5c>:19: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use keras.layers.dense instead.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/metrics_impl.py:455: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 03:33:16.334760 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/metrics_impl.py:455: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 03:33:16.369214 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done calling model_fn.\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:16.498316 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Create CheckpointSaverHook.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:16.502252 140479845271424 basic_session_run_hooks.py:527] Create CheckpointSaverHook.\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Graph was finalized.\n"
          ],
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            "I0519 03:33:17.936243 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
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        },
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        },
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            "I0519 03:33:19.531550 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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        {
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          ],
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            "I0519 03:33:19.622177 140479845271424 session_manager.py:493] Done running local_init_op.\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving checkpoints for 0 into log/model.ckpt.\n"
          ],
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        },
        {
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            "I0519 03:33:23.265944 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 0 into log/model.ckpt.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:loss = 15.229403, step = 0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:33:33.315052 140479845271424 basic_session_run_hooks.py:249] loss = 15.229403, step = 0\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving checkpoints for 16 into log/model.ckpt.\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:01.885350 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 16 into log/model.ckpt.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:03.243717 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:09.668273 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "I0519 03:34:09.946551 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:34:09Z\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:09.971983 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:34:09Z\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Graph was finalized.\n"
          ],
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            "I0519 03:34:10.706301 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/saver.py:1266: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use standard file APIs to check for files with this prefix.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 03:34:10.713814 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/saver.py:1266: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use standard file APIs to check for files with this prefix.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Restoring parameters from log/model.ckpt-16\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:10.720880 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-16\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Running local_init_op.\n"
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            "I0519 03:34:11.402022 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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            "I0519 03:34:11.493532 140479845271424 session_manager.py:493] Done running local_init_op.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Finished evaluation at 2019-05-19-03:34:20\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:20.855419 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:34:20\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving dict for global step 16: accuracy = 0.63125, global_step = 16, loss = 8.71943\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:20.861610 140479845271424 estimator.py:1979] Saving dict for global step 16: accuracy = 0.63125, global_step = 16, loss = 8.71943\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 16: log/model.ckpt-16\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:22.077795 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 16: log/model.ckpt-16\n"
          ],
          "name": "stderr"
        },
        {
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            "INFO:tensorflow:Saving checkpoints for 32 into log/model.ckpt.\n"
          ],
          "name": "stdout"
        },
        {
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            "I0519 03:34:50.002791 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 32 into log/model.ckpt.\n"
          ],
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        },
        {
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            "INFO:tensorflow:Calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "I0519 03:34:51.596478 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:58.354196 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done calling model_fn.\n"
          ],
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        },
        {
          "output_type": "stream",
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            "I0519 03:34:58.747763 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:34:58Z\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:34:58.777967 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:34:58Z\n"
          ],
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        },
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            "INFO:tensorflow:Graph was finalized.\n"
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          ],
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        },
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          ],
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        },
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            "I0519 03:34:59.830137 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-32\n"
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            "I0519 03:35:00.537806 140479845271424 session_manager.py:491] Running local_init_op.\n"
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        {
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        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Finished evaluation at 2019-05-19-03:35:08\n"
          ],
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        },
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          "output_type": "stream",
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            "I0519 03:35:08.859052 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:35:08\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving dict for global step 32: accuracy = 0.6475, global_step = 32, loss = 5.4667916\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:08.863522 140479845271424 estimator.py:1979] Saving dict for global step 32: accuracy = 0.6475, global_step = 32, loss = 5.4667916\n"
          ],
          "name": "stderr"
        },
        {
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 32: log/model.ckpt-32\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:08.870656 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 32: log/model.ckpt-32\n"
          ],
          "name": "stderr"
        },
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          "output_type": "stream",
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            "INFO:tensorflow:Saving checkpoints for 48 into log/model.ckpt.\n"
          ],
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        },
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            "I0519 03:35:35.175410 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 48 into log/model.ckpt.\n"
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:36.760829 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:43.715667 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Done calling model_fn.\n"
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        },
        {
          "output_type": "stream",
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            "I0519 03:35:44.011280 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:35:44Z\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:44.038656 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:35:44Z\n"
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        },
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            "INFO:tensorflow:Graph was finalized.\n"
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          ],
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        },
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:35:44.810387 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-48\n"
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        },
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        },
        {
          "output_type": "stream",
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            "I0519 03:35:45.544242 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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        },
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            "INFO:tensorflow:Done running local_init_op.\n"
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            "I0519 03:35:45.644317 140479845271424 session_manager.py:493] Done running local_init_op.\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Finished evaluation at 2019-05-19-03:35:53\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:53.858260 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:35:53\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving dict for global step 48: accuracy = 0.63875, global_step = 48, loss = 6.329616\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:53.860606 140479845271424 estimator.py:1979] Saving dict for global step 48: accuracy = 0.63875, global_step = 48, loss = 6.329616\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 48: log/model.ckpt-48\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:35:53.869268 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 48: log/model.ckpt-48\n"
          ],
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        },
        {
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            "INFO:tensorflow:Saving checkpoints for 64 into log/model.ckpt.\n"
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        },
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            "I0519 03:36:21.382886 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 64 into log/model.ckpt.\n"
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        },
        {
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          ],
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        },
        {
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            "I0519 03:36:23.045181 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
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        {
          "output_type": "stream",
          "text": [
            "I0519 03:36:29.998724 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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        },
        {
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            "INFO:tensorflow:Done calling model_fn.\n"
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          "output_type": "stream",
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          ],
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        },
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          "output_type": "stream",
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            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:36:30Z\n"
          ],
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        },
        {
          "output_type": "stream",
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            "I0519 03:36:30.342230 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:36:30Z\n"
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        },
        {
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        },
        {
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          ],
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        },
        {
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          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:36:31.395705 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-64\n"
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        },
        {
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        },
        {
          "output_type": "stream",
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            "I0519 03:36:32.126993 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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        {
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          ],
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        {
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          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Finished evaluation at 2019-05-19-03:36:40\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
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          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving dict for global step 64: accuracy = 0.67375, global_step = 64, loss = 6.051637\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:36:40.543566 140479845271424 estimator.py:1979] Saving dict for global step 64: accuracy = 0.67375, global_step = 64, loss = 6.051637\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 64: log/model.ckpt-64\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:36:40.553875 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 64: log/model.ckpt-64\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving checkpoints for 80 into log/model.ckpt.\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:37:07.106626 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 80 into log/model.ckpt.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/saver.py:966: remove_checkpoint (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use standard file APIs to delete files with this prefix.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 03:37:07.417532 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/saver.py:966: remove_checkpoint (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use standard file APIs to delete files with this prefix.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Calling model_fn.\n"
          ],
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        },
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          "output_type": "stream",
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            "I0519 03:37:08.793458 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
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        },
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            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
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        },
        {
          "output_type": "stream",
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            "I0519 03:37:15.557816 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
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        },
        {
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            "INFO:tensorflow:Done calling model_fn.\n"
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            "I0519 03:37:15.867559 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
          "name": "stderr"
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        {
          "output_type": "stream",
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            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:37:15Z\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:37:15.900007 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:37:15Z\n"
          ],
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        },
        {
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            "INFO:tensorflow:Graph was finalized.\n"
          ],
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            "I0519 03:37:16.931186 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Restoring parameters from log/model.ckpt-80\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:37:16.943513 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-80\n"
          ],
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        },
        {
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            "I0519 03:37:17.672086 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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        },
        {
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        },
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          ],
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          ],
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        },
        {
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            "INFO:tensorflow:Saving dict for global step 80: accuracy = 0.68875, global_step = 80, loss = 4.0918727\n"
          ],
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        },
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            "I0519 03:37:26.911725 140479845271424 estimator.py:1979] Saving dict for global step 80: accuracy = 0.68875, global_step = 80, loss = 4.0918727\n"
          ],
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        },
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 80: log/model.ckpt-80\n"
          ],
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        },
        {
          "output_type": "stream",
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            "I0519 03:37:26.917316 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 80: log/model.ckpt-80\n"
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            "INFO:tensorflow:Saving checkpoints for 96 into log/model.ckpt.\n"
          ],
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            "I0519 03:37:53.853948 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 96 into log/model.ckpt.\n"
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            "I0519 03:38:02.283145 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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          "output_type": "stream",
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            "I0519 03:38:02.593609 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:38:02Z\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
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            "I0519 03:38:02.620178 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:38:02Z\n"
          ],
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        },
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            "INFO:tensorflow:Graph was finalized.\n"
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          ],
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        },
        {
          "output_type": "stream",
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            "I0519 03:38:03.361530 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-96\n"
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        },
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          "output_type": "stream",
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          "output_type": "stream",
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            "I0519 03:38:04.103084 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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            "I0519 03:38:12.360645 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:38:12\n"
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving dict for global step 96: accuracy = 0.67, global_step = 96, loss = 3.8621547\n"
          ],
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            "I0519 03:38:12.367729 140479845271424 estimator.py:1979] Saving dict for global step 96: accuracy = 0.67, global_step = 96, loss = 3.8621547\n"
          ],
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        },
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 96: log/model.ckpt-96\n"
          ],
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        },
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          "output_type": "stream",
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            "I0519 03:38:12.371004 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 96: log/model.ckpt-96\n"
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            "INFO:tensorflow:global_step/sec: 0.352556\n"
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        {
          "output_type": "stream",
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            "INFO:tensorflow:loss = 3.1106138, step = 100 (283.631 sec)\n"
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            "I0519 03:38:16.946010 140479845271424 basic_session_run_hooks.py:247] loss = 3.1106138, step = 100 (283.631 sec)\n"
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            "I0519 03:38:39.168857 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 112 into log/model.ckpt.\n"
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        },
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:38:40.666052 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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        },
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          "output_type": "stream",
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            "I0519 03:38:48.220799 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Done calling model_fn.\n"
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          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:38:48.558896 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:38:48Z\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:38:48.591020 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:38:48Z\n"
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        },
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            "I0519 03:38:49.446211 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
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        },
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        },
        {
          "output_type": "stream",
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            "I0519 03:38:49.459839 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-112\n"
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        },
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        },
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            "I0519 03:38:50.272526 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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        },
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            "I0519 03:38:59.012915 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:38:59\n"
          ],
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        },
        {
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          ],
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        },
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            "I0519 03:38:59.015266 140479845271424 estimator.py:1979] Saving dict for global step 112: accuracy = 0.68875, global_step = 112, loss = 4.1200314\n"
          ],
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        },
        {
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          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:38:59.024981 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 112: log/model.ckpt-112\n"
          ],
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        },
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            "INFO:tensorflow:Saving checkpoints for 128 into log/model.ckpt.\n"
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        },
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            "I0519 03:39:26.668110 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 128 into log/model.ckpt.\n"
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        },
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        },
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          "output_type": "stream",
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            "I0519 03:39:28.213066 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
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        },
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          "output_type": "stream",
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            "I0519 03:39:35.547390 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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        },
        {
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            "INFO:tensorflow:Done calling model_fn.\n"
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          "output_type": "stream",
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          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:39:35Z\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:39:35.889016 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:39:35Z\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Graph was finalized.\n"
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:39:36.628328 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Restoring parameters from log/model.ckpt-128\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:39:36.642378 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-128\n"
          ],
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        },
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        },
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            "I0519 03:39:37.381573 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
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            "INFO:tensorflow:Done running local_init_op.\n"
          ],
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        },
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          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Saving dict for global step 128: accuracy = 0.68125, global_step = 128, loss = 3.7493992\n"
          ],
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 03:39:45.755824 140479845271424 estimator.py:1979] Saving dict for global step 128: accuracy = 0.68125, global_step = 128, loss = 3.7493992\n"
          ],
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        },
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 128: log/model.ckpt-128\n"
          ],
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:39:45.758268 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 128: log/model.ckpt-128\n"
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        },
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        },
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            "I0519 03:40:13.637547 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 144 into log/model.ckpt.\n"
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            "I0519 03:40:22.289895 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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        },
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          ],
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            "I0519 03:42:05.094790 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 176: log/model.ckpt-176\n"
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            "I0519 03:42:52.490837 140479845271424 estimator.py:1979] Saving dict for global step 192: accuracy = 0.6975, global_step = 192, loss = 3.4202063\n"
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          "text": [
            "I0519 03:42:52.499229 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 192: log/model.ckpt-192\n"
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            "I0519 03:43:29.403220 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-208\n"
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        },
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          ],
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        },
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          ],
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            "I0519 03:44:25.772509 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 224: log/model.ckpt-224\n"
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        },
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            "I0519 03:45:10.751853 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 240: log/model.ckpt-240\n"
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          "output_type": "stream",
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            "I0519 03:47:19.287194 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
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        },
        {
          "output_type": "stream",
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            "INFO:tensorflow:Done calling model_fn.\n"
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            "I0519 03:47:19.585928 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
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        },
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            "I0519 03:47:19.614932 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:47:19Z\n"
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        },
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        },
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          ],
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        },
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          "output_type": "stream",
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            "I0519 03:47:20.379080 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-288\n"
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        },
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            "I0519 03:47:29.361092 140479845271424 estimator.py:1979] Saving dict for global step 288: accuracy = 0.715, global_step = 288, loss = 3.2361302\n"
          ],
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        },
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            "I0519 03:47:29.366627 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 288: log/model.ckpt-288\n"
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            "INFO:tensorflow:global_step/sec: 0.351223\n"
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        },
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            "INFO:tensorflow:loss = 1.1095605, step = 300 (284.663 sec)\n"
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        },
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            "I0519 03:48:05.776262 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-304\n"
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            "I0519 03:48:16.098172 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:48:16\n"
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            "INFO:tensorflow:Saving dict for global step 304: accuracy = 0.71875, global_step = 304, loss = 3.1743648\n"
          ],
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            "I0519 03:48:16.100398 140479845271424 estimator.py:1979] Saving dict for global step 304: accuracy = 0.71875, global_step = 304, loss = 3.1743648\n"
          ],
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 304: log/model.ckpt-304\n"
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            "I0519 03:48:16.112215 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 304: log/model.ckpt-304\n"
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        },
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            "I0519 03:48:42.223201 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 320 into log/model.ckpt.\n"
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            "I0519 03:48:43.873804 140479845271424 estimator.py:1111] Calling model_fn.\n"
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            "I0519 03:48:52.243152 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-320\n"
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            "I0519 03:48:53.007281 140479845271424 session_manager.py:491] Running local_init_op.\n"
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            "I0519 03:49:01.262637 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:49:01\n"
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            "I0519 03:49:01.266921 140479845271424 estimator.py:1979] Saving dict for global step 320: accuracy = 0.7225, global_step = 320, loss = 3.278376\n"
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          "name": "stderr"
        },
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 320: log/model.ckpt-320\n"
          ],
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:49:01.271525 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 320: log/model.ckpt-320\n"
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            "INFO:tensorflow:Saving checkpoints for 336 into log/model.ckpt.\n"
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            "I0519 03:49:27.642379 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 336 into log/model.ckpt.\n"
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            "I0519 03:49:29.534858 140479845271424 estimator.py:1111] Calling model_fn.\n"
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            "I0519 03:49:37.894930 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:49:38Z\n"
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            "I0519 03:49:38.220462 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:49:38Z\n"
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          "output_type": "stream",
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            "I0519 03:49:38.980326 140479845271424 monitored_session.py:222] Graph was finalized.\n"
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            "INFO:tensorflow:Restoring parameters from log/model.ckpt-336\n"
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:49:38.992884 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-336\n"
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            "I0519 03:49:39.729740 140479845271424 session_manager.py:491] Running local_init_op.\n"
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          ],
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          "output_type": "stream",
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            "I0519 03:49:47.914328 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-03:49:47\n"
          ],
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        },
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            "INFO:tensorflow:Saving dict for global step 336: accuracy = 0.7175, global_step = 336, loss = 3.027226\n"
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:49:47.920004 140479845271424 estimator.py:1979] Saving dict for global step 336: accuracy = 0.7175, global_step = 336, loss = 3.027226\n"
          ],
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        },
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 336: log/model.ckpt-336\n"
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:49:47.922658 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 336: log/model.ckpt-336\n"
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            "INFO:tensorflow:Saving checkpoints for 352 into log/model.ckpt.\n"
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            "I0519 03:50:13.771458 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 352 into log/model.ckpt.\n"
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            "I0519 03:50:16.401082 140479845271424 estimator.py:1111] Calling model_fn.\n"
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            "I0519 03:50:22.284457 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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          "output_type": "stream",
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            "INFO:tensorflow:Starting evaluation at 2019-05-19T03:50:22Z\n"
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          "output_type": "stream",
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            "I0519 03:50:22.606604 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T03:50:22Z\n"
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        },
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          "output_type": "stream",
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            "I0519 03:50:23.351305 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
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        },
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          "output_type": "stream",
          "text": [
            "I0519 03:50:23.364218 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-352\n"
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            "I0519 03:50:24.092558 140479845271424 session_manager.py:491] Running local_init_op.\n"
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          ],
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            "I0519 03:52:48.953377 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 400: log/model.ckpt-400\n"
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            "INFO:tensorflow:global_step/sec: 0.333911\n"
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            "I0519 03:54:08.575011 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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          ],
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        },
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        },
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            "I0519 03:57:47.547501 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 512 into log/model.ckpt.\n"
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            "I0519 03:57:55.545274 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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            "I0519 03:58:05.732823 140479845271424 estimator.py:1979] Saving dict for global step 512: accuracy = 0.71375, global_step = 512, loss = 3.0366027\n"
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            "I0519 03:58:05.740880 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 512: log/model.ckpt-512\n"
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 528: log/model.ckpt-528\n"
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            "INFO:tensorflow:Saving checkpoints for 544 into log/model.ckpt.\n"
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            "I0519 03:59:16.370834 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 544 into log/model.ckpt.\n"
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          "output_type": "stream",
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            "I0519 03:59:25.898737 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-544\n"
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            "I0519 03:59:34.620949 140479845271424 estimator.py:1979] Saving dict for global step 544: accuracy = 0.71, global_step = 544, loss = 2.9527817\n"
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 544: log/model.ckpt-544\n"
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        },
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          "text": [
            "I0519 03:59:34.630093 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 544: log/model.ckpt-544\n"
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            "INFO:tensorflow:Saving checkpoints for 560 into log/model.ckpt.\n"
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            "I0519 04:00:01.662659 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 560 into log/model.ckpt.\n"
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            "I0519 04:00:10.742196 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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            "I0519 04:00:11.100543 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T04:00:11Z\n"
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            "I0519 04:00:11.943013 140479845271424 monitored_session.py:222] Graph was finalized.\n"
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          "text": [
            "I0519 04:00:11.963461 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-560\n"
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            "I0519 04:00:21.832834 140479845271424 estimator.py:1979] Saving dict for global step 560: accuracy = 0.68625, global_step = 560, loss = 3.3493466\n"
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            "I0519 04:00:56.577397 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-576\n"
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            "INFO:tensorflow:global_step/sec: 0.359363\n"
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          "output_type": "stream",
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            "I0519 04:03:53.219933 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-640\n"
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            "INFO:tensorflow:Saving checkpoints for 720 into log/model.ckpt.\n"
          ],
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        },
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            "I0519 04:07:26.685304 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 720 into log/model.ckpt.\n"
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            "I0519 04:07:34.920979 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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        },
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            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 736: log/model.ckpt-736\n"
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            "I0519 04:08:54.982265 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 752 into log/model.ckpt.\n"
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        },
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            "I0519 04:09:57.686737 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 768: log/model.ckpt-768\n"
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            "I0519 04:10:32.538545 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
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        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:10:34.290753 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done running local_init_op.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:10:34.385842 140479845271424 session_manager.py:493] Done running local_init_op.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Finished evaluation at 2019-05-19-04:10:42\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:10:42.174165 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-04:10:42\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving dict for global step 784: accuracy = 0.72, global_step = 784, loss = 2.7574458\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:10:42.178578 140479845271424 estimator.py:1979] Saving dict for global step 784: accuracy = 0.72, global_step = 784, loss = 2.7574458\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 784: log/model.ckpt-784\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:10:42.181761 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 784: log/model.ckpt-784\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving checkpoints for 800 into log/model.ckpt.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:08.887872 140479845271424 basic_session_run_hooks.py:594] Saving checkpoints for 800 into log/model.ckpt.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:10.316845 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:16.754409 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:17.036507 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Starting evaluation at 2019-05-19T04:11:17Z\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:17.063524 140479845271424 evaluation.py:257] Starting evaluation at 2019-05-19T04:11:17Z\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Graph was finalized.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:17.767454 140479845271424 monitored_session.py:222] Graph was finalized.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Restoring parameters from log/model.ckpt-800\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:17.780039 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-800\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Running local_init_op.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:18.495120 140479845271424 session_manager.py:491] Running local_init_op.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done running local_init_op.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:18.589419 140479845271424 session_manager.py:493] Done running local_init_op.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Finished evaluation at 2019-05-19-04:11:26\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:26.394498 140479845271424 evaluation.py:277] Finished evaluation at 2019-05-19-04:11:26\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving dict for global step 800: accuracy = 0.705, global_step = 800, loss = 3.4521003\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:26.396640 140479845271424 estimator.py:1979] Saving dict for global step 800: accuracy = 0.705, global_step = 800, loss = 3.4521003\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 800: log/model.ckpt-800\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:26.413319 140479845271424 estimator.py:2039] Saving 'checkpoint_path' summary for global step 800: log/model.ckpt-800\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Loss for final step: 0.45407617.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:26.525375 140479845271424 estimator.py:359] Loss for final step: 0.45407617.\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SM-435fYcyST",
        "colab_type": "code",
        "outputId": "9c5007ff-cc22-4be1-df54-47435e2712e7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 666
        }
      },
      "source": [
        "estimator.export_savedmodel(model_dir,\n",
        "                            lambda: serving_input_receiver_fn(params),\n",
        "                            strip_default_attrs=True)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/image_ops_impl.py:618: to_double (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 04:11:26.565722 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/image_ops_impl.py:618: to_double (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.cast instead.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:26.590010 140479845271424 estimator.py:1111] Calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.247717 140479845271424 saver.py:1483] Saver not created because there are no variables in the graph to restore\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Done calling model_fn.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.406103 140479845271424 estimator.py:1113] Done calling model_fn.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/signature_def_utils_impl.py:205: build_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "W0519 04:11:30.408126 140479845271424 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/signature_def_utils_impl.py:205: build_tensor_info (from tensorflow.python.saved_model.utils_impl) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.utils.build_tensor_info or tf.compat.v1.saved_model.build_tensor_info.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Signatures INCLUDED in export for Classify: None\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.411566 140479845271424 export.py:587] Signatures INCLUDED in export for Classify: None\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Signatures INCLUDED in export for Regress: None\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.413892 140479845271424 export.py:587] Signatures INCLUDED in export for Regress: None\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Signatures INCLUDED in export for Predict: ['tensorflow/serving/predict', 'serving_default']\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.417192 140479845271424 export.py:587] Signatures INCLUDED in export for Predict: ['tensorflow/serving/predict', 'serving_default']\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Signatures INCLUDED in export for Train: None\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.420369 140479845271424 export.py:587] Signatures INCLUDED in export for Train: None\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Signatures INCLUDED in export for Eval: None\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.423400 140479845271424 export.py:587] Signatures INCLUDED in export for Eval: None\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Restoring parameters from log/model.ckpt-800\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:30.820382 140479845271424 saver.py:1270] Restoring parameters from log/model.ckpt-800\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:Assets added to graph.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:31.295837 140479845271424 builder_impl.py:654] Assets added to graph.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:No assets to write.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:31.297927 140479845271424 builder_impl.py:449] No assets to write.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "INFO:tensorflow:SavedModel written to: log/temp-b'1558239086'/saved_model.pb\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "I0519 04:11:32.323876 140479845271424 builder_impl.py:414] SavedModel written to: log/temp-b'1558239086'/saved_model.pb\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "b'log/1558239086'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Biz2Gu81in0p",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def compress_model_dir(inpath=model_dir, \n",
        "                       outpath='/content/gdrive/My Drive/indoor-outdoor-classification/{}.tar.gz'.format(model_dir)):\n",
        "  with tarfile.open(outpath, 'w:gz') as tf:\n",
        "    tf.add(inpath)\n",
        "    \n",
        "compress_model_dir()"
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}