ch14/ch14_part3.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Vc6_2ntY1bf7"
   },
   "source": [
    "# 머신 러닝 교과서 3판"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "zDc0-lf51bgB"
   },
   "source": [
    "# 14장 - 텐서플로의 구조 자세히 알아보기 (3/3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5uWGlsyu1bgB"
   },
   "source": [
    "**아래 링크를 통해 이 노트북을 주피터 노트북 뷰어(nbviewer.jupyter.org)로 보거나 구글 코랩(colab.research.google.com)에서 실행할 수 있습니다.**\n",
    "\n",
    "<table class=\"tfo-notebook-buttons\" align=\"left\">\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://nbviewer.jupyter.org/github/rickiepark/python-machine-learning-book-3rd-edition/blob/master/ch14/ch14_part3.ipynb\"><img src=\"https://jupyter.org/assets/main-logo.svg\" width=\"28\" />주피터 노트북 뷰어로 보기</a>\n",
    "  </td>\n",
    "  <td>\n",
    "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/rickiepark/python-machine-learning-book-3rd-edition/blob/master/ch14/ch14_part3.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />구글 코랩(Colab)에서 실행하기</a>\n",
    "  </td>\n",
    "</table>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "MNC_qLbl1bgC"
   },
   "source": [
    "### 목차"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "hRk4nqAW1bgC"
   },
   "source": [
    "- 텐서플로 추정기\n",
    "  - 추정기를 사용해 MNIST 손글씨 숫자 분류하기\n",
    "  - 케라스 모델에서 추정기 만들기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "UoxDNsX-1bgC"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import tensorflow_datasets as tfds\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 37
    },
    "id": "OE8GOBaS1dzc",
    "outputId": "9c5d1dfe-9c30-4a3f-ae47-6024b1a52979"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "string"
      },
      "text/plain": [
       "'2.4.0'"
      ]
     },
     "execution_count": 2,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ajj9IQD71bgD"
   },
   "source": [
    "### 추정기를 사용해 MNIST 손글씨 숫자 분류하기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "Y6Bayxva1bgD"
   },
   "outputs": [],
   "source": [
    "BUFFER_SIZE = 10000\n",
    "BATCH_SIZE = 64\n",
    "NUM_EPOCHS = 20\n",
    "steps_per_epoch = np.ceil(60000 / BATCH_SIZE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "WYZ_v7tC1bgD"
   },
   "outputs": [],
   "source": [
    "def preprocess(item):\n",
    "    image = item['image']\n",
    "    label = item['label']\n",
    "    image = tf.image.convert_image_dtype(\n",
    "        image, tf.float32)\n",
    "    image = tf.reshape(image, (-1,))\n",
    "\n",
    "    return {'image-pixels':image}, label[..., tf.newaxis]\n",
    "\n",
    "# 단계 1: 입력 함수 두 개를 정의합니다(하나는 훈련용이고 다른 하나는 평가용입니다).\n",
    "## 훈련용 입력 함수\n",
    "def train_input_fn():\n",
    "    datasets = tfds.load(name='mnist')\n",
    "    mnist_train = datasets['train']\n",
    "\n",
    "    dataset = mnist_train.map(preprocess)\n",
    "    dataset = dataset.shuffle(BUFFER_SIZE)\n",
    "    dataset = dataset.batch(BATCH_SIZE)\n",
    "    return dataset.repeat()\n",
    "\n",
    "## 평가용 입력 함수\n",
    "def eval_input_fn():\n",
    "    datasets = tfds.load(name='mnist')\n",
    "    mnist_test = datasets['test']\n",
    "    dataset = mnist_test.map(preprocess).batch(BATCH_SIZE)\n",
    "    return dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "c5NL8mgz1bgD"
   },
   "outputs": [],
   "source": [
    "## 단계 2: 특성 열을 정의합니다.\n",
    "image_feature_column = tf.feature_column.numeric_column(\n",
    "    key='image-pixels', shape=(28*28))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000,
     "referenced_widgets": [
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    },
    "id": "h1mC7Kl71bgE",
    "outputId": "9a5a8bdb-de13-4039-8bfb-5eff0ec5c262"
   },
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using default config.\n",
      "INFO:tensorflow:Using config: {'_model_dir': 'models/mnist-dnn/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_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, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_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",
      "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.\n",
      "\u001b[1mDownloading and preparing dataset mnist/3.0.1 (download: 11.06 MiB, generated: 21.00 MiB, total: 32.06 MiB) to /root/tensorflow_datasets/mnist/3.0.1...\u001b[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:absl:Dataset mnist is hosted on GCS. It will automatically be downloaded to your\n",
      "local data directory. If you'd instead prefer to read directly from our public\n",
      "GCS bucket (recommended if you're running on GCP), you can instead pass\n",
      "`try_gcs=True` to `tfds.load` or set `data_dir=gs://tfds-data/datasets`.\n",
      "\n"
     ]
    },
    {
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       "HBox(children=(FloatProgress(value=0.0, description='Dl Completed...', max=4.0, style=ProgressStyle(descriptio…"
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     "text": [
      "\n",
      "\n",
      "\u001b[1mDataset mnist downloaded and prepared to /root/tensorflow_datasets/mnist/3.0.1. Subsequent calls will reuse this data.\u001b[0m\n",
      "INFO:tensorflow:Calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/optimizer_v2/adagrad.py:83: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Call initializer instance with the dtype argument instead of passing it to the constructor\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/optimizer_v2/adagrad.py:83: calling Constant.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Call initializer instance with the dtype argument instead of passing it to the constructor\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Create CheckpointSaverHook.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Create CheckpointSaverHook.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done 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": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 0 into models/mnist-dnn/model.ckpt.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 0 into models/mnist-dnn/model.ckpt.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 2.3745456, step = 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 2.3745456, step = 0\n"
     ]
    },
    {
     "name": "stdout",
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     "text": [
      "INFO:tensorflow:global_step/sec: 117.623\n"
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     "text": [
      "INFO:tensorflow:global_step/sec: 117.623\n"
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      "INFO:tensorflow:loss = 2.2450244, step = 100 (0.852 sec)\n"
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     "text": [
      "INFO:tensorflow:loss = 2.2450244, step = 100 (0.852 sec)\n"
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      "INFO:tensorflow:loss = 2.1949458, step = 200 (0.829 sec)\n"
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     "text": [
      "INFO:tensorflow:loss = 2.1949458, step = 200 (0.829 sec)\n"
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      "INFO:tensorflow:global_step/sec: 125.525\n"
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      "INFO:tensorflow:loss = 2.125176, step = 300 (0.803 sec)\n"
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     "text": [
      "INFO:tensorflow:loss = 2.125176, step = 300 (0.803 sec)\n"
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      "INFO:tensorflow:loss = 2.0118675, step = 500 (0.876 sec)\n"
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      "INFO:tensorflow:loss = 1.655839, step = 1100 (0.746 sec)\n"
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      "INFO:tensorflow:loss = 0.3673002, step = 14000 (0.224 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.3673002, step = 14000 (0.224 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 14044 vs previous value: 14044. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 14044 vs previous value: 14044. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 97.3443\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 97.3443\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.64235765, step = 14100 (1.022 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.64235765, step = 14100 (1.022 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 161.691\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 161.691\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.57091296, step = 14200 (0.625 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.57091296, step = 14200 (0.625 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 158.723\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 158.723\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.594911, step = 14300 (0.624 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.594911, step = 14300 (0.624 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 149.79\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 149.79\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.40149018, step = 14400 (0.668 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.40149018, step = 14400 (0.668 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 151.292\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 151.292\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.38391197, step = 14500 (0.663 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.38391197, step = 14500 (0.663 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 156.033\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 156.033\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.47121108, step = 14600 (0.641 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.47121108, step = 14600 (0.641 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 160.147\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 160.147\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.65337807, step = 14700 (0.622 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.65337807, step = 14700 (0.622 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 161.759\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 161.759\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5360933, step = 14800 (0.617 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5360933, step = 14800 (0.617 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 256.466\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 256.466\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.30715466, step = 14900 (0.391 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.30715466, step = 14900 (0.391 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 14979 vs previous value: 14979. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 14979 vs previous value: 14979. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 533.056\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 533.056\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.48428002, step = 15000 (0.188 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.48428002, step = 15000 (0.188 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 73.5392\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 73.5392\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.62933755, step = 15100 (1.365 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.62933755, step = 15100 (1.365 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 144.306\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 144.306\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5120175, step = 15200 (0.689 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5120175, step = 15200 (0.689 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 152.991\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 152.991\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.39085543, step = 15300 (0.652 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.39085543, step = 15300 (0.652 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 154.27\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 154.27\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.36357474, step = 15400 (0.649 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.36357474, step = 15400 (0.649 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 164.581\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 164.581\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5996799, step = 15500 (0.610 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5996799, step = 15500 (0.610 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 154.143\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 154.143\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.58591247, step = 15600 (0.645 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.58591247, step = 15600 (0.645 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 156.68\n"
     ]
    },
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 156.68\n"
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    },
    {
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     "text": [
      "INFO:tensorflow:loss = 0.53077835, step = 15700 (0.641 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.53077835, step = 15700 (0.641 sec)\n"
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      "INFO:tensorflow:global_step/sec: 171.021\n"
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      "INFO:tensorflow:loss = 0.61571926, step = 15800 (0.581 sec)\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.61571926, step = 15800 (0.581 sec)\n"
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     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 631.134\n"
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      "INFO:tensorflow:global_step/sec: 631.134\n"
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      "INFO:tensorflow:loss = 0.33066207, step = 15900 (0.166 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.33066207, step = 15900 (0.166 sec)\n"
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    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 89.9981\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 89.9981\n"
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    },
    {
     "name": "stdout",
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      "INFO:tensorflow:loss = 0.3109601, step = 16000 (1.105 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.3109601, step = 16000 (1.105 sec)\n"
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 145.478\n"
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     "name": "stderr",
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     "text": [
      "INFO:tensorflow:global_step/sec: 145.478\n"
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      "INFO:tensorflow:loss = 0.44818595, step = 16100 (0.692 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.44818595, step = 16100 (0.692 sec)\n"
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    {
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     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 152.831\n"
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      "INFO:tensorflow:global_step/sec: 152.831\n"
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      "INFO:tensorflow:loss = 0.525775, step = 16200 (0.649 sec)\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.525775, step = 16200 (0.649 sec)\n"
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      "INFO:tensorflow:global_step/sec: 150.748\n"
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      "INFO:tensorflow:global_step/sec: 150.748\n"
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      "INFO:tensorflow:loss = 0.5727228, step = 16300 (0.667 sec)\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5727228, step = 16300 (0.667 sec)\n"
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      "INFO:tensorflow:global_step/sec: 148.968\n"
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      "INFO:tensorflow:global_step/sec: 148.968\n"
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      "INFO:tensorflow:loss = 0.3581483, step = 16400 (0.669 sec)\n"
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     "output_type": "stream",
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      "INFO:tensorflow:loss = 0.3581483, step = 16400 (0.669 sec)\n"
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     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 166.312\n"
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      "INFO:tensorflow:loss = 0.58668566, step = 16500 (0.601 sec)\n"
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.3792737, step = 17000 (0.616 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.3792737, step = 17000 (0.616 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 145.834\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 145.834\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.725876, step = 17100 (0.688 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.725876, step = 17100 (0.688 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 156.911\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 156.911\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.47041312, step = 17200 (0.640 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.47041312, step = 17200 (0.640 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 149.129\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 149.129\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.41194725, step = 17300 (0.666 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.41194725, step = 17300 (0.666 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 151.994\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 151.994\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.4596197, step = 17400 (0.661 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.4596197, step = 17400 (0.661 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 141.009\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 141.009\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.34824252, step = 17500 (0.709 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.34824252, step = 17500 (0.709 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 132.65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 132.65\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.38039792, step = 17600 (0.751 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.38039792, step = 17600 (0.751 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 158.937\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 158.937\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.46841413, step = 17700 (0.631 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.46841413, step = 17700 (0.631 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 550.064\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 550.064\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5052744, step = 17800 (0.183 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5052744, step = 17800 (0.183 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 66.2099\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 66.2099\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.39078936, step = 17900 (1.507 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.39078936, step = 17900 (1.507 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 138.364\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 138.364\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.35378784, step = 18000 (0.723 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.35378784, step = 18000 (0.723 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 137.132\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 137.132\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.29212296, step = 18100 (0.731 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.29212296, step = 18100 (0.731 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 135.889\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 135.889\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5791725, step = 18200 (0.735 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.5791725, step = 18200 (0.735 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 135.995\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 135.995\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.56055355, step = 18300 (0.734 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.56055355, step = 18300 (0.734 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 134.282\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 134.282\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.4056707, step = 18400 (0.746 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.4056707, step = 18400 (0.746 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 131.121\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 131.121\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.44950137, step = 18500 (0.765 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.44950137, step = 18500 (0.765 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 143.416\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 143.416\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.42948082, step = 18600 (0.698 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.42948082, step = 18600 (0.698 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 540.982\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 540.982\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.47041813, step = 18700 (0.179 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.47041813, step = 18700 (0.179 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 18760...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 18760...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 18760 into models/mnist-dnn/model.ckpt.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 18760 into models/mnist-dnn/model.ckpt.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 18760...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 18760...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Loss for final step: 0.3330472.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Loss for final step: 0.3330472.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow_estimator.python.estimator.canned.dnn.DNNClassifierV2 at 0x7fa06c7e4e80>"
      ]
     },
     "execution_count": 6,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 단계 3: 추정기 객체를 만듭니다.\n",
    "dnn_classifier = tf.estimator.DNNClassifier(\n",
    "    feature_columns=[image_feature_column],\n",
    "    hidden_units=[32, 16],\n",
    "    n_classes=10,\n",
    "    model_dir='models/mnist-dnn/')\n",
    "\n",
    "\n",
    "## 단계 4: 훈련합니다.\n",
    "dnn_classifier.train(\n",
    "    input_fn=train_input_fn,\n",
    "    steps=NUM_EPOCHS * steps_per_epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "aXaMFToY1bgF",
    "outputId": "ab5dba80-ea0f-4c1d-9d95-4fdd355448c9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Starting evaluation at 2021-01-02T16:05:09Z\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Starting evaluation at 2021-01-02T16:05:09Z\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from models/mnist-dnn/model.ckpt-18760\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from models/mnist-dnn/model.ckpt-18760\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done 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": [
      "INFO:tensorflow:Inference Time : 1.71688s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Inference Time : 1.71688s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Finished evaluation at 2021-01-02-16:05:11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Finished evaluation at 2021-01-02-16:05:11\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving dict for global step 18760: accuracy = 0.8872, average_loss = 0.4232459, global_step = 18760, loss = 0.42350507\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving dict for global step 18760: accuracy = 0.8872, average_loss = 0.4232459, global_step = 18760, loss = 0.42350507\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 18760: models/mnist-dnn/model.ckpt-18760\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 18760: models/mnist-dnn/model.ckpt-18760\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'accuracy': 0.8872, 'average_loss': 0.4232459, 'loss': 0.42350507, 'global_step': 18760}\n"
     ]
    }
   ],
   "source": [
    "eval_result = dnn_classifier.evaluate(\n",
    "    input_fn=eval_input_fn)\n",
    "\n",
    "print(eval_result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "PRBS6RHT1bgG"
   },
   "source": [
    "### 케라스 모델에서 추정기 만들기"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "xhBhmPZE1bgG"
   },
   "outputs": [],
   "source": [
    "## 결과 재현을 위한 랜덤 시드\n",
    "tf.random.set_seed(1)\n",
    "np.random.seed(1)\n",
    "\n",
    "## 데이터 생성\n",
    "x = np.random.uniform(low=-1, high=1, size=(200, 2))\n",
    "y = np.ones(len(x))\n",
    "y[x[:, 0] * x[:, 1]<0] = 0\n",
    "\n",
    "x_train = x[:100, :]\n",
    "y_train = y[:100]\n",
    "x_valid = x[100:, :]\n",
    "y_valid = y[100:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "PRu_s75W1bgG"
   },
   "outputs": [],
   "source": [
    "## 단계 1: 입력 함수를 정의합니다.\n",
    "def train_input_fn(x_train, y_train, batch_size=8):\n",
    "    dataset = tf.data.Dataset.from_tensor_slices(\n",
    "        ({'input-features':x_train}, y_train.reshape(-1, 1)))\n",
    "\n",
    "    # 셔플, 반복, 배치\n",
    "    return dataset.shuffle(100).repeat().batch(batch_size)\n",
    "\n",
    "def eval_input_fn(x_test, y_test=None, batch_size=8):\n",
    "    if y_test is None:\n",
    "        dataset = tf.data.Dataset.from_tensor_slices(\n",
    "            {'input-features':x_test})\n",
    "    else:\n",
    "        dataset = tf.data.Dataset.from_tensor_slices(\n",
    "            ({'input-features':x_test}, y_test.reshape(-1, 1)))\n",
    "\n",
    "\n",
    "    # 셔플, 반복, 배치\n",
    "    return dataset.batch(batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "0HQ9pdHf1bgG",
    "outputId": "6f7f2466-4495-46da-d12e-9ec9df44d385"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[NumericColumn(key='input-features:', shape=(2,), default_value=None, dtype=tf.float32, normalizer_fn=None)]"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 단계 2: 특성 열을 정의합니다.\n",
    "features = [\n",
    "    tf.feature_column.numeric_column(\n",
    "        key='input-features:', shape=(2,))\n",
    "]\n",
    "    \n",
    "features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "RcrqbWpI1bgH",
    "outputId": "aac917ba-908d-4e41-e254-827b395173ad"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense (Dense)                (None, 4)                 12        \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 4)                 20        \n",
      "_________________________________________________________________\n",
      "dense_2 (Dense)              (None, 4)                 20        \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 57\n",
      "Trainable params: 57\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "INFO:tensorflow:Using default config.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using default config.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using the Keras model provided.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using the Keras model provided.\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/backend.py:434: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn('`tf.keras.backend.set_learning_phase` is deprecated and '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Using config: {'_model_dir': 'models/estimator-for-XOR/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_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, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_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:Using config: {'_model_dir': 'models/estimator-for-XOR/', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': None, '_save_checkpoints_secs': 600, '_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, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_checkpoint_save_graph_def': True, '_service': None, '_cluster_spec': ClusterSpec({}), '_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"
     ]
    }
   ],
   "source": [
    "## 단계 3: 케라스 모델을 변환하여 추정기를 만듭니다.\n",
    "model = tf.keras.Sequential([\n",
    "    tf.keras.layers.Input(shape=(2,), name='input-features'),\n",
    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
    "    tf.keras.layers.Dense(units=4, activation='relu'),\n",
    "    tf.keras.layers.Dense(1, activation='sigmoid')\n",
    "])\n",
    "\n",
    "model.summary()\n",
    "\n",
    "model.compile(optimizer=tf.keras.optimizers.SGD(),\n",
    "              loss=tf.keras.losses.BinaryCrossentropy(),\n",
    "              metrics=[tf.keras.metrics.BinaryAccuracy()])\n",
    "\n",
    "my_estimator = tf.keras.estimator.model_to_estimator(\n",
    "    keras_model=model,\n",
    "    model_dir='models/estimator-for-XOR/')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "ZIj9G3201bgH",
    "outputId": "b836d237-9d01-4a45-f0cd-2206f4b807cd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/backend.py:434: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn('`tf.keras.backend.set_learning_phase` is deprecated and '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-starting with WarmStartSettings: WarmStartSettings(ckpt_to_initialize_from='models/estimator-for-XOR/keras/keras_model.ckpt', vars_to_warm_start='.*', var_name_to_vocab_info={}, var_name_to_prev_var_name={})\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-starting with WarmStartSettings: WarmStartSettings(ckpt_to_initialize_from='models/estimator-for-XOR/keras/keras_model.ckpt', vars_to_warm_start='.*', var_name_to_vocab_info={}, var_name_to_prev_var_name={})\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-starting from: models/estimator-for-XOR/keras/keras_model.ckpt\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-starting from: models/estimator-for-XOR/keras/keras_model.ckpt\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-starting variables only in TRAINABLE_VARIABLES.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-starting variables only in TRAINABLE_VARIABLES.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-started 8 variables.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Warm-started 8 variables.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Create CheckpointSaverHook.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Create CheckpointSaverHook.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done 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": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 0 into models/estimator-for-XOR/model.ckpt.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 0 into models/estimator-for-XOR/model.ckpt.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 0...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.7503817, step = 0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.7503817, step = 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 802.489\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 802.489\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6779643, step = 100 (0.128 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6779643, step = 100 (0.128 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1162.97\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1162.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6667501, step = 200 (0.090 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6667501, step = 200 (0.090 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1003.14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1003.14\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6554606, step = 300 (0.098 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6554606, step = 300 (0.098 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1008.33\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1008.33\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6337532, step = 400 (0.096 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6337532, step = 400 (0.096 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1028.02\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1028.02\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6987753, step = 500 (0.097 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6987753, step = 500 (0.097 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1231.95\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1231.95\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.649707, step = 600 (0.082 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.649707, step = 600 (0.082 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 983.789\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 983.789\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6921682, step = 700 (0.099 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6921682, step = 700 (0.099 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 787 vs previous value: 787. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 787 vs previous value: 787. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 991.918\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 991.918\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6778245, step = 800 (0.104 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6778245, step = 800 (0.104 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1246.05\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1246.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6792611, step = 900 (0.078 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6792611, step = 900 (0.078 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1002.38\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1002.38\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6941427, step = 1000 (0.102 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6941427, step = 1000 (0.102 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 990.779\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 990.779\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.62097406, step = 1100 (0.104 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.62097406, step = 1100 (0.104 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1110.77\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1110.77\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6947959, step = 1200 (0.083 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6947959, step = 1200 (0.083 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1040.56\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1040.56\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.61258924, step = 1300 (0.100 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.61258924, step = 1300 (0.100 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1059.05\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 1059.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6516306, step = 1400 (0.096 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6516306, step = 1400 (0.096 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 1431 vs previous value: 1431. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 1431 vs previous value: 1431. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 752.966\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 752.966\n"
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     "name": "stdout",
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     "text": [
      "INFO:tensorflow:loss = 0.6547507, step = 1500 (0.133 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6547507, step = 1500 (0.133 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1002.64\n"
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     "name": "stdout",
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     "text": [
      "INFO:tensorflow:loss = 0.6475719, step = 1600 (0.101 sec)\n"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6475719, step = 1600 (0.101 sec)\n"
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    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 904.237\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 904.237\n"
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     "name": "stdout",
     "output_type": "stream",
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      "INFO:tensorflow:loss = 0.7144604, step = 1700 (0.110 sec)\n"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.7144604, step = 1700 (0.110 sec)\n"
     ]
    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 1703 vs previous value: 1703. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 1703 vs previous value: 1703. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 856.27\n"
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     "text": [
      "INFO:tensorflow:loss = 0.74359596, step = 1800 (0.120 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.74359596, step = 1800 (0.120 sec)\n"
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    },
    {
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     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 1063.77\n"
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      "INFO:tensorflow:global_step/sec: 1063.77\n"
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      "INFO:tensorflow:loss = 0.71242565, step = 1900 (0.087 sec)\n"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.71242565, step = 1900 (0.087 sec)\n"
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     "name": "stdout",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 1114.27\n"
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      "INFO:tensorflow:global_step/sec: 1114.27\n"
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      "INFO:tensorflow:loss = 0.70595634, step = 2000 (0.090 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.70595634, step = 2000 (0.090 sec)\n"
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    },
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     "name": "stdout",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 1022.71\n"
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      "INFO:tensorflow:loss = 0.6558761, step = 2100 (0.102 sec)\n"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6558761, step = 2100 (0.102 sec)\n"
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     "output_type": "stream",
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      "INFO:tensorflow:loss = 0.6091065, step = 2200 (0.102 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.6091065, step = 2200 (0.102 sec)\n"
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    },
    {
     "name": "stdout",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 942.392\n"
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     "name": "stderr",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 942.392\n"
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      "INFO:tensorflow:loss = 0.7193948, step = 2300 (0.103 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.7193948, step = 2300 (0.103 sec)\n"
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     "name": "stdout",
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      "INFO:tensorflow:global_step/sec: 1030.46\n"
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      "INFO:tensorflow:global_step/sec: 1030.46\n"
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     "name": "stdout",
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      "INFO:tensorflow:loss = 0.76715994, step = 2400 (0.101 sec)\n"
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.76715994, step = 2400 (0.101 sec)\n"
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 919.959\n"
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      "INFO:tensorflow:global_step/sec: 919.959\n"
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      "INFO:tensorflow:loss = 0.603531, step = 2500 (0.107 sec)\n"
     ]
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.603531, step = 2500 (0.107 sec)\n"
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     "text": [
      "INFO:tensorflow:loss = 0.50442475, step = 2600 (0.095 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1136.09\n"
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      "INFO:tensorflow:loss = 0.49875396, step = 2700 (0.092 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.49875396, step = 2700 (0.092 sec)\n"
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    },
    {
     "name": "stdout",
     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 989.963\n"
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     "output_type": "stream",
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      "INFO:tensorflow:global_step/sec: 989.963\n"
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      "INFO:tensorflow:loss = 0.45686096, step = 2800 (0.097 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.45686096, step = 2800 (0.097 sec)\n"
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    },
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 949.597\n"
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     "name": "stderr",
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      "INFO:tensorflow:global_step/sec: 949.597\n"
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      "INFO:tensorflow:loss = 0.54105663, step = 2900 (0.111 sec)\n"
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    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.54105663, step = 2900 (0.111 sec)\n"
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     "name": "stdout",
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      "INFO:tensorflow:global_step/sec: 984.541\n"
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      "INFO:tensorflow:loss = 0.693802, step = 3000 (0.099 sec)\n"
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.693802, step = 3000 (0.099 sec)\n"
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      "INFO:tensorflow:loss = 0.4986161, step = 3100 (0.102 sec)\n"
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      "INFO:tensorflow:loss = 0.36797154, step = 3200 (0.091 sec)\n"
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     "text": [
      "INFO:tensorflow:loss = 0.7761768, step = 3300 (0.104 sec)\n"
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      "INFO:tensorflow:loss = 0.159751, step = 3400 (0.101 sec)\n"
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     "name": "stderr",
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     "text": [
      "INFO:tensorflow:loss = 0.159751, step = 3400 (0.101 sec)\n"
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      "INFO:tensorflow:loss = 0.45062476, step = 3700 (0.097 sec)\n"
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      "INFO:tensorflow:loss = 0.551943, step = 3800 (0.091 sec)\n"
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     "name": "stderr",
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      "INFO:tensorflow:loss = 0.41990617, step = 4000 (0.100 sec)\n"
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      "INFO:tensorflow:loss = 0.00096759945, step = 7700 (0.103 sec)\n"
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    },
    {
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      "INFO:tensorflow:loss = 0.00096759945, step = 7700 (0.103 sec)\n"
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      "INFO:tensorflow:global_step/sec: 909.96\n"
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      "INFO:tensorflow:loss = 0.03266611, step = 7800 (0.108 sec)\n"
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    {
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      "INFO:tensorflow:loss = 0.03266611, step = 7800 (0.108 sec)\n"
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      "INFO:tensorflow:global_step/sec: 955.914\n"
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      "INFO:tensorflow:loss = 0.04881368, step = 7900 (0.107 sec)\n"
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    },
    {
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      "INFO:tensorflow:loss = 0.04881368, step = 7900 (0.107 sec)\n"
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      "INFO:tensorflow:global_step/sec: 938.871\n"
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      "INFO:tensorflow:loss = 0.014034062, step = 8000 (0.105 sec)\n"
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    {
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      "INFO:tensorflow:loss = 0.014034062, step = 8000 (0.105 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1047.11\n"
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      "INFO:tensorflow:loss = 0.017952912, step = 8100 (0.093 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1086.11\n"
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      "INFO:tensorflow:loss = 0.012858342, step = 8200 (0.094 sec)\n"
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    {
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      "INFO:tensorflow:loss = 0.012858342, step = 8200 (0.094 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1241.77\n"
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      "INFO:tensorflow:loss = 1.6861412e-06, step = 8300 (0.082 sec)\n"
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    {
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      "INFO:tensorflow:loss = 1.6861412e-06, step = 8300 (0.082 sec)\n"
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      "INFO:tensorflow:global_step/sec: 966.706\n"
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      "INFO:tensorflow:loss = 0.0037871243, step = 8400 (0.100 sec)\n"
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    },
    {
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     "text": [
      "INFO:tensorflow:loss = 0.0037871243, step = 8400 (0.100 sec)\n"
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      "INFO:tensorflow:global_step/sec: 990.751\n"
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      "INFO:tensorflow:loss = 0.0061268713, step = 8500 (0.104 sec)\n"
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    {
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     "text": [
      "INFO:tensorflow:loss = 0.0061268713, step = 8500 (0.104 sec)\n"
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      "INFO:tensorflow:global_step/sec: 970.048\n"
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      "INFO:tensorflow:loss = 0.0064428123, step = 8600 (0.101 sec)\n"
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    {
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     "text": [
      "INFO:tensorflow:loss = 0.0064428123, step = 8600 (0.101 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1154.54\n"
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      "INFO:tensorflow:loss = 0.005529093, step = 8700 (0.085 sec)\n"
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      "INFO:tensorflow:loss = 0.005529093, step = 8700 (0.085 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1172.42\n"
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      "INFO:tensorflow:loss = 0.005308636, step = 8800 (0.089 sec)\n"
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     "text": [
      "INFO:tensorflow:loss = 0.005308636, step = 8800 (0.089 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1019.95\n"
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      "INFO:tensorflow:loss = 0.0151312, step = 8900 (0.096 sec)\n"
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      "INFO:tensorflow:loss = 0.0151312, step = 8900 (0.096 sec)\n"
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      "INFO:tensorflow:loss = 0.0050628264, step = 9000 (0.104 sec)\n"
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      "INFO:tensorflow:loss = 0.0050628264, step = 9000 (0.104 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1036.06\n"
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      "INFO:tensorflow:loss = 0.0807919, step = 9100 (0.099 sec)\n"
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      "INFO:tensorflow:loss = 0.0807919, step = 9100 (0.099 sec)\n"
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      "INFO:tensorflow:global_step/sec: 997.895\n"
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      "INFO:tensorflow:loss = 0.008847774, step = 9200 (0.098 sec)\n"
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      "INFO:tensorflow:loss = 0.008847774, step = 9200 (0.098 sec)\n"
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      "INFO:tensorflow:loss = 4.6842732e-07, step = 9300 (0.099 sec)\n"
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      "INFO:tensorflow:loss = 4.6842732e-07, step = 9300 (0.099 sec)\n"
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      "INFO:tensorflow:loss = 0.00010276547, step = 9400 (0.103 sec)\n"
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      "INFO:tensorflow:loss = 0.00010276547, step = 9400 (0.103 sec)\n"
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      "INFO:tensorflow:loss = 0.0042115324, step = 9500 (0.095 sec)\n"
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      "INFO:tensorflow:loss = 0.0042115324, step = 9500 (0.095 sec)\n"
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      "INFO:tensorflow:loss = 0.0056473026, step = 9600 (0.105 sec)\n"
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      "INFO:tensorflow:global_step/sec: 888.784\n"
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      "INFO:tensorflow:loss = 0.0039607617, step = 9700 (0.109 sec)\n"
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      "INFO:tensorflow:loss = 0.0039607617, step = 9700 (0.109 sec)\n"
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      "INFO:tensorflow:global_step/sec: 1006.65\n"
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     "text": [
      "INFO:tensorflow:loss = 0.006141499, step = 9800 (0.105 sec)\n"
     ]
    },
    {
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     "output_type": "stream",
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      "INFO:tensorflow:loss = 0.006141499, step = 9800 (0.105 sec)\n"
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    {
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     "text": [
      "INFO:tensorflow:global_step/sec: 832.469\n"
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    },
    {
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     "output_type": "stream",
     "text": [
      "INFO:tensorflow:global_step/sec: 832.469\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.006630741, step = 9900 (0.117 sec)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:loss = 0.006630741, step = 9900 (0.117 sec)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 10000...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners before saving checkpoint 10000...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 10000 into models/estimator-for-XOR/model.ckpt.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving checkpoints for 10000 into models/estimator-for-XOR/model.ckpt.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 10000...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling checkpoint listeners after saving checkpoint 10000...\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Loss for final step: 0.003994444.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Loss for final step: 0.003994444.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<tensorflow_estimator.python.estimator.estimator.EstimatorV2 at 0x7fa02ac7f278>"
      ]
     },
     "execution_count": 12,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## 단계 4: 추정기를 사용합니다: 훈련/평가/예측\n",
    "\n",
    "num_epochs = 200\n",
    "batch_size = 2\n",
    "steps_per_epoch = np.ceil(len(x_train) / batch_size)\n",
    "\n",
    "my_estimator.train(\n",
    "    input_fn=lambda: train_input_fn(x_train, y_train, batch_size),\n",
    "    steps=num_epochs * steps_per_epoch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "YfaQLO_c1bgI",
    "outputId": "5e141df2-81e0-4989-f74d-8278078cb890"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Calling model_fn.\n",
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/backend.py:434: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn('`tf.keras.backend.set_learning_phase` is deprecated and '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py:2325: UserWarning: `Model.state_updates` will be removed in a future version. This property should not be used in TensorFlow 2.0, as `updates` are applied automatically.\n",
      "  warnings.warn('`Model.state_updates` will be removed in a future version. '\n",
      "INFO:tensorflow:Done calling model_fn.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Starting evaluation at 2021-01-02T16:05:23Z\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Starting evaluation at 2021-01-02T16:05:23Z\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Graph was finalized.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from models/estimator-for-XOR/model.ckpt-10000\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from models/estimator-for-XOR/model.ckpt-10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Running local_init_op.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Done 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": [
      "INFO:tensorflow:Inference Time : 0.19938s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Inference Time : 0.19938s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Finished evaluation at 2021-01-02-16:05:23\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Finished evaluation at 2021-01-02-16:05:23\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving dict for global step 10000: binary_accuracy = 0.95, global_step = 10000, loss = 0.089551315\n"
     ]
    },
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     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving dict for global step 10000: binary_accuracy = 0.95, global_step = 10000, loss = 0.089551315\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 10000: models/estimator-for-XOR/model.ckpt-10000\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 10000: models/estimator-for-XOR/model.ckpt-10000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'binary_accuracy': 0.95, 'global_step': 10000, 'loss': 0.089551315}"
      ]
     },
     "execution_count": 13,
     "metadata": {
      "tags": []
     },
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    "    input_fn=lambda: eval_input_fn(x_valid, y_valid, batch_size))"
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