WideDeepModel.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "WideDeepModel.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyP6j6TWDYcHgZ3WiJ2Ty731",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/jvishnuvardhan/Keras_Examples/blob/master/WideDeepModel.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ksGZ-4zQIL53",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 768
        },
        "outputId": "1426ca38-7d25-4201-ebea-6bf31bc17f1c"
      },
      "source": [
        "!pip install tf-nightly"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting tf-nightly\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/be/76/42a2abf70a6d7d50c63c515ee68a14cded571908ac6b6a5a78f68ead7148/tf_nightly-2.2.0.dev20200408-cp36-cp36m-manylinux2010_x86_64.whl (517.5MB)\n",
            "\u001b[K     |████████████████████████████████| 517.5MB 27kB/s \n",
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            "Collecting tf-estimator-nightly\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/e2/ab/9f69dda13e7bd6ac9afc988b922ff53f6cc29716974898a428d3e0531a84/tf_estimator_nightly-2.3.0.dev2020040801-py2.py3-none-any.whl (455kB)\n",
            "\u001b[K     |████████████████████████████████| 460kB 36.6MB/s \n",
            "\u001b[?25hRequirement already satisfied: six>=1.12.0 in /usr/local/lib/python3.6/dist-packages (from tf-nightly) (1.12.0)\n",
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            "Collecting tb-nightly<2.4.0a0,>=2.3.0a0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/2e/70/874df1f50c16f1203ac4044c8fdf061932a955cb825b27d74f1a9b4c66df/tb_nightly-2.3.0a20200408-py3-none-any.whl (3.0MB)\n",
            "\u001b[K     |████████████████████████████████| 3.0MB 39.8MB/s \n",
            "\u001b[?25hRequirement already satisfied: astunparse==1.6.3 in /usr/local/lib/python3.6/dist-packages (from tf-nightly) (1.6.3)\n",
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            "Requirement already satisfied: google-pasta>=0.1.8 in /usr/local/lib/python3.6/dist-packages (from tf-nightly) (0.2.0)\n",
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            "Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (2.21.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (3.2.1)\n",
            "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (1.6.0.post2)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (1.0.1)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.6/dist-packages (from tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (0.4.1)\n",
            "Requirement already satisfied: cachetools<3.2,>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (3.1.1)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (0.2.8)\n",
            "Requirement already satisfied: rsa<4.1,>=3.1.4 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (4.0)\n",
            "Requirement already satisfied: chardet<3.1.0,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (3.0.4)\n",
            "Requirement already satisfied: urllib3<1.25,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (2019.11.28)\n",
            "Requirement already satisfied: idna<2.9,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (2.8)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (1.3.0)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.6/dist-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (0.4.8)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tb-nightly<2.4.0a0,>=2.3.0a0->tf-nightly) (3.1.0)\n",
            "Installing collected packages: tf-estimator-nightly, tb-nightly, tf-nightly\n",
            "Successfully installed tb-nightly-2.3.0a20200408 tf-estimator-nightly-2.3.0.dev2020040801 tf-nightly-2.2.0.dev20200408\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XyRKiF5VIONm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "d5bdbd25-e30a-4d5e-fb36-3b76a35bac6e"
      },
      "source": [
        "import tensorflow as tf\n",
        "tf.__version__"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'2.2.0-dev20200408'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zIVaYuvAIOlx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "outputId": "141d42e9-3829-42e5-825b-8f0689b54cd9"
      },
      "source": [
        "import tensorflow as tf\n",
        "import numpy as np\n",
        "\n",
        "\n",
        "features = np.random.uniform(size=[100, 50])\n",
        "labels = np.random.uniform(size=[100])\n",
        "\n",
        "linear_model = tf.keras.experimental.LinearModel()\n",
        "dnn_model = tf.keras.Sequential([tf.keras.layers.Dense(units=1)])\n",
        "combined_model = tf.keras.experimental.WideDeepModel(linear_model,dnn_model)\n",
        "# Uncomment the following line to test without compilation:\n",
        "combined_model.compile(optimizer=['adagrad','rmsprop'], loss='mse')\n",
        "combined_model.fit([features,features], labels,epochs=10)\n",
        "#tf.saved_model.save(combined_model, \"./saved_model\")"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.8004\n",
            "Epoch 2/10\n",
            "4/4 [==============================] - 0s 3ms/step - loss: 0.5012\n",
            "Epoch 3/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.3903\n",
            "Epoch 4/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.3344\n",
            "Epoch 5/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.3309\n",
            "Epoch 6/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.2581\n",
            "Epoch 7/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.2692\n",
            "Epoch 8/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.2458\n",
            "Epoch 9/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.2934\n",
            "Epoch 10/10\n",
            "4/4 [==============================] - 0s 2ms/step - loss: 0.2237\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<tensorflow.python.keras.callbacks.History at 0x7fccda606128>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i7llrIbEITot",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 307
        },
        "outputId": "3d104f6e-66b7-43f7-d15b-18d35a56fb06"
      },
      "source": [
        "# Throwing an error \n",
        "tf.saved_model.save(combined_model, \"./saved_model\")"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "error",
          "ename": "AttributeError",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-4-5fe2106bad1b>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msaved_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcombined_model\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"./saved_model\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/save.py\u001b[0m in \u001b[0;36msave\u001b[0;34m(obj, export_dir, signatures, options)\u001b[0m\n\u001b[1;32m    949\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    950\u001b[0m   _, exported_graph, object_saver, asset_info = _build_meta_graph(\n\u001b[0;32m--> 951\u001b[0;31m       obj, export_dir, signatures, options, meta_graph_def)\n\u001b[0m\u001b[1;32m    952\u001b[0m   \u001b[0msaved_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msaved_model_schema_version\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconstants\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mSAVED_MODEL_SCHEMA_VERSION\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    953\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/save.py\u001b[0m in \u001b[0;36m_build_meta_graph\u001b[0;34m(obj, export_dir, signatures, options, meta_graph_def)\u001b[0m\n\u001b[1;32m   1037\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1038\u001b[0m   object_graph_proto = _serialize_object_graph(saveable_view,\n\u001b[0;32m-> 1039\u001b[0;31m                                                asset_info.asset_index)\n\u001b[0m\u001b[1;32m   1040\u001b[0m   \u001b[0mmeta_graph_def\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mobject_graph_def\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCopyFrom\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobject_graph_proto\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1041\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/save.py\u001b[0m in \u001b[0;36m_serialize_object_graph\u001b[0;34m(saveable_view, asset_file_def_index)\u001b[0m\n\u001b[1;32m    695\u001b[0m   \u001b[0;32mfor\u001b[0m \u001b[0mobj\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mobj_proto\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msaveable_view\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnodes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    696\u001b[0m     _write_object_proto(obj, obj_proto, asset_file_def_index,\n\u001b[0;32m--> 697\u001b[0;31m                         saveable_view.function_name_map)\n\u001b[0m\u001b[1;32m    698\u001b[0m   \u001b[0;32mreturn\u001b[0m \u001b[0mproto\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    699\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/saved_model/save.py\u001b[0m in \u001b[0;36m_write_object_proto\u001b[0;34m(obj, proto, asset_file_def_index, function_name_map)\u001b[0m\n\u001b[1;32m    735\u001b[0m           version=versions_pb2.VersionDef(\n\u001b[1;32m    736\u001b[0m               producer=1, min_consumer=1, bad_consumers=[]),\n\u001b[0;32m--> 737\u001b[0;31m           metadata=obj._tracking_metadata)\n\u001b[0m\u001b[1;32m    738\u001b[0m       \u001b[0;31m# pylint:enable=protected-access\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    739\u001b[0m     \u001b[0mproto\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muser_object\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCopyFrom\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mregistered_type_proto\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py\u001b[0m in \u001b[0;36m_tracking_metadata\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   2707\u001b[0m   \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2708\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_tracking_metadata\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2709\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_trackable_saved_model_saver\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtracking_metadata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2711\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_list_extra_dependencies_for_serialization\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mserialization_cache\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/base_serialization.py\u001b[0m in \u001b[0;36mtracking_metadata\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0;31m# TODO(kathywu): check that serialized JSON can be loaded (e.g., if an\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     53\u001b[0m     \u001b[0;31m# object is in the python property)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 54\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mjson_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mEncoder\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mencode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpython_properties\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     55\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     56\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mlist_extra_dependencies_for_serialization\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mserialization_cache\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/layer_serialization.py\u001b[0m in \u001b[0;36mpython_properties\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     39\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0mpython_properties\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m     \u001b[0;31m# TODO(kathywu): Add python property validator\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 41\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_python_properties_internal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     42\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     43\u001b[0m   \u001b[0;32mdef\u001b[0m \u001b[0m_python_properties_internal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saved_model/model_serialization.py\u001b[0m in \u001b[0;36m_python_properties_internal\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     36\u001b[0m     metadata.update(\n\u001b[1;32m     37\u001b[0m         saving_utils.model_metadata(\n\u001b[0;32m---> 38\u001b[0;31m             self.obj, include_optimizer=True, require_config=False))\n\u001b[0m\u001b[1;32m     39\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mmetadata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     40\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/saving/saving_utils.py\u001b[0m in \u001b[0;36mmodel_metadata\u001b[0;34m(model, include_optimizer, require_config)\u001b[0m\n\u001b[1;32m    186\u001b[0m                 \u001b[0mgeneric_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_registered_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    187\u001b[0m             \u001b[0;34m'config'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 188\u001b[0;31m                 \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_config\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    189\u001b[0m         }\n\u001b[1;32m    190\u001b[0m       \u001b[0mmetadata\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'training_config'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'optimizer_config'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0moptimizer_config\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'ListWrapper' object has no attribute 'get_config'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bY7D6EH6InCo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": 0,
      "outputs": []
    }
  ]
}