Handwriting Recognition - Load Model.ipynb

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    "# Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from tensorflow.compat.v1.saved_model import load\n",
    "from tensorflow.compat.v1.saved_model import tag_constants"
   ]
  },
  {
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   "source": [
    "# Constants"
   ]
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   "cell_type": "code",
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   "outputs": [],
   "source": [
    "#data files loaded\n",
    "X_TEST_PATH = 'MNIST/load_xtest.csv'\n",
    "Y_TEST_PATH = 'MNIST/load_ytest.csv'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the Data"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test = np.loadtxt(Y_TEST_PATH, delimiter=',', dtype=int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_test = np.loadtxt(X_TEST_PATH, delimiter=',', dtype=float)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Explore"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
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   "outputs": [
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       "(10000,)"
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "y_test.shape"
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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     "execution_count": 6,
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   "source": [
    "x_test.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create Session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#graph object and session object linked with graph\n",
    "graph = tf.Graph()\n",
    "sess = tf.Session(graph=graph)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-8-203d8fddeaf6>:1: load (from tensorflow.python.saved_model.loader_impl) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "This function will only be available through the v1 compatibility library as tf.compat.v1.saved_model.loader.load or tf.compat.v1.saved_model.load. There will be a new function for importing SavedModels in Tensorflow 2.0.\n",
      "WARNING:tensorflow:From C:\\Users\\rockz\\Anaconda3\\lib\\site-packages\\tensorflow\\python\\training\\saver.py:1276: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use standard file APIs to check for files with this prefix.\n",
      "INFO:tensorflow:Restoring parameters from SavedModel\\variables\\variables\n"
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       "        list {\n",
       "          s: \"loc:@out/B\"\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_output_shapes\"\n",
       "      value {\n",
       "        list {\n",
       "          shape {\n",
       "            dim {\n",
       "              size: 10\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"use_locking\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"validate_shape\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  node {\n",
       "    name: \"save/Assign_16\"\n",
       "    op: \"Assign\"\n",
       "    input: \"out/B/Adam_1\"\n",
       "    input: \"save/RestoreV2:16\"\n",
       "    attr {\n",
       "      key: \"T\"\n",
       "      value {\n",
       "        type: DT_FLOAT\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_class\"\n",
       "      value {\n",
       "        list {\n",
       "          s: \"loc:@out/B\"\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_output_shapes\"\n",
       "      value {\n",
       "        list {\n",
       "          shape {\n",
       "            dim {\n",
       "              size: 10\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"use_locking\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"validate_shape\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  node {\n",
       "    name: \"save/Assign_17\"\n",
       "    op: \"Assign\"\n",
       "    input: \"out/W\"\n",
       "    input: \"save/RestoreV2:17\"\n",
       "    attr {\n",
       "      key: \"T\"\n",
       "      value {\n",
       "        type: DT_FLOAT\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_class\"\n",
       "      value {\n",
       "        list {\n",
       "          s: \"loc:@out/W\"\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_output_shapes\"\n",
       "      value {\n",
       "        list {\n",
       "          shape {\n",
       "            dim {\n",
       "              size: 64\n",
       "            }\n",
       "            dim {\n",
       "              size: 10\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"use_locking\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"validate_shape\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  node {\n",
       "    name: \"save/Assign_18\"\n",
       "    op: \"Assign\"\n",
       "    input: \"out/W/Adam\"\n",
       "    input: \"save/RestoreV2:18\"\n",
       "    attr {\n",
       "      key: \"T\"\n",
       "      value {\n",
       "        type: DT_FLOAT\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_class\"\n",
       "      value {\n",
       "        list {\n",
       "          s: \"loc:@out/W\"\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_output_shapes\"\n",
       "      value {\n",
       "        list {\n",
       "          shape {\n",
       "            dim {\n",
       "              size: 64\n",
       "            }\n",
       "            dim {\n",
       "              size: 10\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"use_locking\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"validate_shape\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  node {\n",
       "    name: \"save/Assign_19\"\n",
       "    op: \"Assign\"\n",
       "    input: \"out/W/Adam_1\"\n",
       "    input: \"save/RestoreV2:19\"\n",
       "    attr {\n",
       "      key: \"T\"\n",
       "      value {\n",
       "        type: DT_FLOAT\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_class\"\n",
       "      value {\n",
       "        list {\n",
       "          s: \"loc:@out/W\"\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"_output_shapes\"\n",
       "      value {\n",
       "        list {\n",
       "          shape {\n",
       "            dim {\n",
       "              size: 64\n",
       "            }\n",
       "            dim {\n",
       "              size: 10\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"use_locking\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "    attr {\n",
       "      key: \"validate_shape\"\n",
       "      value {\n",
       "        b: true\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  node {\n",
       "    name: \"save/restore_shard\"\n",
       "    op: \"NoOp\"\n",
       "    input: \"^save/Assign\"\n",
       "    input: \"^save/Assign_1\"\n",
       "    input: \"^save/Assign_10\"\n",
       "    input: \"^save/Assign_11\"\n",
       "    input: \"^save/Assign_12\"\n",
       "    input: \"^save/Assign_13\"\n",
       "    input: \"^save/Assign_14\"\n",
       "    input: \"^save/Assign_15\"\n",
       "    input: \"^save/Assign_16\"\n",
       "    input: \"^save/Assign_17\"\n",
       "    input: \"^save/Assign_18\"\n",
       "    input: \"^save/Assign_19\"\n",
       "    input: \"^save/Assign_2\"\n",
       "    input: \"^save/Assign_3\"\n",
       "    input: \"^save/Assign_4\"\n",
       "    input: \"^save/Assign_5\"\n",
       "    input: \"^save/Assign_6\"\n",
       "    input: \"^save/Assign_7\"\n",
       "    input: \"^save/Assign_8\"\n",
       "    input: \"^save/Assign_9\"\n",
       "  }\n",
       "  node {\n",
       "    name: \"save/restore_all\"\n",
       "    op: \"NoOp\"\n",
       "    input: \"^save/restore_shard\"\n",
       "  }\n",
       "  library {\n",
       "  }\n",
       "  versions {\n",
       "    producer: 38\n",
       "  }\n",
       "}\n",
       "saver_def {\n",
       "  filename_tensor_name: \"save/Const:0\"\n",
       "  save_tensor_name: \"save/Identity:0\"\n",
       "  restore_op_name: \"save/restore_all\"\n",
       "  max_to_keep: 5\n",
       "  sharded: true\n",
       "  keep_checkpoint_every_n_hours: 10000.0\n",
       "  version: V2\n",
       "}\n",
       "collection_def {\n",
       "  key: \"summaries\"\n",
       "  value {\n",
       "    node_list {\n",
       "      value: \"layer_1/weights:0\"\n",
       "      value: \"layer_1/biases:0\"\n",
       "      value: \"layer_2/weights:0\"\n",
       "      value: \"layer_2/biases:0\"\n",
       "      value: \"out/weights:0\"\n",
       "      value: \"out/biases:0\"\n",
       "      value: \"performance/accuracy:0\"\n",
       "      value: \"performance/cost:0\"\n",
       "      value: \"show_image/image_input:0\"\n",
       "    }\n",
       "  }\n",
       "}\n",
       "collection_def {\n",
       "  key: \"train_op\"\n",
       "  value {\n",
       "    node_list {\n",
       "      value: \"optimizer/Adam\"\n",
       "    }\n",
       "  }\n",
       "}\n",
       "collection_def {\n",
       "  key: \"trainable_variables\"\n",
       "  value {\n",
       "    bytes_list {\n",
       "      value: \"\\n\\013layer_1/W:0\\022\\020layer_1/W/Assign\\032\\020layer_1/W/read:02\\032layer_1/truncated_normal:08\\001\"\n",
       "      value: \"\\n\\013layer_1/B:0\\022\\020layer_1/B/Assign\\032\\020layer_1/B/read:02\\017layer_1/Const:08\\001\"\n",
       "      value: \"\\n\\013layer_2/W:0\\022\\020layer_2/W/Assign\\032\\020layer_2/W/read:02\\032layer_2/truncated_normal:08\\001\"\n",
       "      value: \"\\n\\013layer_2/B:0\\022\\020layer_2/B/Assign\\032\\020layer_2/B/read:02\\017layer_2/Const:08\\001\"\n",
       "      value: \"\\n\\007out/W:0\\022\\014out/W/Assign\\032\\014out/W/read:02\\026out/truncated_normal:08\\001\"\n",
       "      value: \"\\n\\007out/B:0\\022\\014out/B/Assign\\032\\014out/B/read:02\\013out/Const:08\\001\"\n",
       "    }\n",
       "  }\n",
       "}\n",
       "collection_def {\n",
       "  key: \"variables\"\n",
       "  value {\n",
       "    bytes_list {\n",
       "      value: \"\\n\\013layer_1/W:0\\022\\020layer_1/W/Assign\\032\\020layer_1/W/read:02\\032layer_1/truncated_normal:08\\001\"\n",
       "      value: \"\\n\\013layer_1/B:0\\022\\020layer_1/B/Assign\\032\\020layer_1/B/read:02\\017layer_1/Const:08\\001\"\n",
       "      value: \"\\n\\013layer_2/W:0\\022\\020layer_2/W/Assign\\032\\020layer_2/W/read:02\\032layer_2/truncated_normal:08\\001\"\n",
       "      value: \"\\n\\013layer_2/B:0\\022\\020layer_2/B/Assign\\032\\020layer_2/B/read:02\\017layer_2/Const:08\\001\"\n",
       "      value: \"\\n\\007out/W:0\\022\\014out/W/Assign\\032\\014out/W/read:02\\026out/truncated_normal:08\\001\"\n",
       "      value: \"\\n\\007out/B:0\\022\\014out/B/Assign\\032\\014out/B/read:02\\013out/Const:08\\001\"\n",
       "      value: \"\\n\\027optimizer/beta1_power:0\\022\\034optimizer/beta1_power/Assign\\032\\034optimizer/beta1_power/read:02%optimizer/beta1_power/initial_value:0\"\n",
       "      value: \"\\n\\027optimizer/beta2_power:0\\022\\034optimizer/beta2_power/Assign\\032\\034optimizer/beta2_power/read:02%optimizer/beta2_power/initial_value:0\"\n",
       "      value: \"\\n\\020layer_1/W/Adam:0\\022\\025layer_1/W/Adam/Assign\\032\\025layer_1/W/Adam/read:02\\\"layer_1/W/Adam/Initializer/zeros:0\"\n",
       "      value: \"\\n\\022layer_1/W/Adam_1:0\\022\\027layer_1/W/Adam_1/Assign\\032\\027layer_1/W/Adam_1/read:02$layer_1/W/Adam_1/Initializer/zeros:0\"\n",
       "      value: \"\\n\\020layer_1/B/Adam:0\\022\\025layer_1/B/Adam/Assign\\032\\025layer_1/B/Adam/read:02\\\"layer_1/B/Adam/Initializer/zeros:0\"\n",
       "      value: \"\\n\\022layer_1/B/Adam_1:0\\022\\027layer_1/B/Adam_1/Assign\\032\\027layer_1/B/Adam_1/read:02$layer_1/B/Adam_1/Initializer/zeros:0\"\n",
       "      value: \"\\n\\020layer_2/W/Adam:0\\022\\025layer_2/W/Adam/Assign\\032\\025layer_2/W/Adam/read:02\\\"layer_2/W/Adam/Initializer/zeros:0\"\n",
       "      value: \"\\n\\022layer_2/W/Adam_1:0\\022\\027layer_2/W/Adam_1/Assign\\032\\027layer_2/W/Adam_1/read:02$layer_2/W/Adam_1/Initializer/zeros:0\"\n",
       "      value: \"\\n\\020layer_2/B/Adam:0\\022\\025layer_2/B/Adam/Assign\\032\\025layer_2/B/Adam/read:02\\\"layer_2/B/Adam/Initializer/zeros:0\"\n",
       "      value: \"\\n\\022layer_2/B/Adam_1:0\\022\\027layer_2/B/Adam_1/Assign\\032\\027layer_2/B/Adam_1/read:02$layer_2/B/Adam_1/Initializer/zeros:0\"\n",
       "      value: \"\\n\\014out/W/Adam:0\\022\\021out/W/Adam/Assign\\032\\021out/W/Adam/read:02\\036out/W/Adam/Initializer/zeros:0\"\n",
       "      value: \"\\n\\016out/W/Adam_1:0\\022\\023out/W/Adam_1/Assign\\032\\023out/W/Adam_1/read:02 out/W/Adam_1/Initializer/zeros:0\"\n",
       "      value: \"\\n\\014out/B/Adam:0\\022\\021out/B/Adam/Assign\\032\\021out/B/Adam/read:02\\036out/B/Adam/Initializer/zeros:0\"\n",
       "      value: \"\\n\\016out/B/Adam_1:0\\022\\023out/B/Adam_1/Assign\\032\\023out/B/Adam_1/read:02 out/B/Adam_1/Initializer/zeros:0\"\n",
       "    }\n",
       "  }\n",
       "}\n",
       "signature_def {\n",
       "  key: \"serving_default\"\n",
       "  value {\n",
       "    inputs {\n",
       "      key: \"X\"\n",
       "      value {\n",
       "        name: \"X:0\"\n",
       "        dtype: DT_FLOAT\n",
       "        tensor_shape {\n",
       "          dim {\n",
       "            size: -1\n",
       "          }\n",
       "          dim {\n",
       "            size: 784\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    outputs {\n",
       "      key: \"accuracy_calc/prediction\"\n",
       "      value {\n",
       "        name: \"accuracy_calc/prediction:0\"\n",
       "        dtype: DT_INT64\n",
       "        tensor_shape {\n",
       "          dim {\n",
       "            size: -1\n",
       "          }\n",
       "        }\n",
       "      }\n",
       "    }\n",
       "    method_name: \"tensorflow/serving/predict\"\n",
       "  }\n",
       "}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "load(sess=sess, tags=[tag_constants.SERVING], export_dir='SavedModel')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Run Session & Make a Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#inputs to make prediction\n",
    "X = graph.get_tensor_by_name('X:0')\n",
    "\n",
    "#outputs to make prediction\n",
    "y_pred = graph.get_tensor_by_name('accuracy_calc/prediction:0')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "prediction = sess.run(fetches=y_pred, feed_dict={X: x_test})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Testing and Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Percentage correctness: 97.74%\n"
     ]
    }
   ],
   "source": [
    "# Compares the two arrays having same shape\n",
    "nr_correct = sum(np.equal(prediction, y_test))\n",
    "\n",
    "pcorrect = nr_correct/len(prediction)\n",
    "print(f'Percentage correctness: {pcorrect:0.2%}')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sample testing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 2, 1, 0, 4])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([7, 2, 1, 0, 4], dtype=int64)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prediction[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Reset functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "sess.close()\n",
    "tf.reset_default_graph()"
   ]
  }
 ],
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