Hyperparameter_Optimization_Deep_Learning(Regression)_.ipynb

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    "colab": {
      "name": "Hyperparameter Optimization Deep Learning(Regression) .ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyMbcPFmNJ0XRyf5FMZ4FR3/",
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    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/drbilal216/Tensorflow-Datasets-Q3/blob/master/Hyperparameter_Optimization_Deep_Learning(Regression)_.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RcdbCoOn3k-H"
      },
      "source": [
        "## Hyperparameter Tuning of Keras Deep Learning Model in Python\n",
        "\n",
        "https://mc.ai/hyperparameter-tuning-of-keras-deep-learning-model-in-python/"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_DN83ea23lyd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "e5e1d56c-3e2e-42eb-cd7c-48e20580d41d"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "e4ppypxiKX2R"
      },
      "source": [
        "# Download Data from here\n",
        "https://drive.google.com/drive/folders/1gaTtFxrqHY0vBzaHAdcJDghcdhaEimiX?usp=sharing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9iIYWChC3r4E",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 246
        },
        "outputId": "33128e6f-544f-40de-cc8b-f5c12d574c6c"
      },
      "source": [
        "import pandas as pd\n",
        "Input_path = '/content/drive/My Drive/ML and AI/Datasets/compresive_strength_concrete/compresive_strength_concrete.csv'\n",
        "data_df =  pd.read_csv(Input_path)\n",
        "display(data_df.head())"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Cement (component 1)(kg in a m^3 mixture)</th>\n",
              "      <th>Blast Furnace Slag (component 2)(kg in a m^3 mixture)</th>\n",
              "      <th>Fly Ash (component 3)(kg in a m^3 mixture)</th>\n",
              "      <th>Water  (component 4)(kg in a m^3 mixture)</th>\n",
              "      <th>Superplasticizer (component 5)(kg in a m^3 mixture)</th>\n",
              "      <th>Coarse Aggregate  (component 6)(kg in a m^3 mixture)</th>\n",
              "      <th>Fine Aggregate (component 7)(kg in a m^3 mixture)</th>\n",
              "      <th>Age (day)</th>\n",
              "      <th>Concrete compressive strength(MPa, megapascals)</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>540.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>162.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>1040.0</td>\n",
              "      <td>676.0</td>\n",
              "      <td>28</td>\n",
              "      <td>79.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>540.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>162.0</td>\n",
              "      <td>2.5</td>\n",
              "      <td>1055.0</td>\n",
              "      <td>676.0</td>\n",
              "      <td>28</td>\n",
              "      <td>61.89</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>332.5</td>\n",
              "      <td>142.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>228.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>932.0</td>\n",
              "      <td>594.0</td>\n",
              "      <td>270</td>\n",
              "      <td>40.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>332.5</td>\n",
              "      <td>142.5</td>\n",
              "      <td>0.0</td>\n",
              "      <td>228.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>932.0</td>\n",
              "      <td>594.0</td>\n",
              "      <td>365</td>\n",
              "      <td>41.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>198.6</td>\n",
              "      <td>132.4</td>\n",
              "      <td>0.0</td>\n",
              "      <td>192.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>978.4</td>\n",
              "      <td>825.5</td>\n",
              "      <td>360</td>\n",
              "      <td>44.30</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
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            "text/plain": [
              "   Cement (component 1)(kg in a m^3 mixture)  ...  Concrete compressive strength(MPa, megapascals) \n",
              "0                                      540.0  ...                                             79.99\n",
              "1                                      540.0  ...                                             61.89\n",
              "2                                      332.5  ...                                             40.27\n",
              "3                                      332.5  ...                                             41.05\n",
              "4                                      198.6  ...                                             44.30\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-mOqcPuS307o",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "9d10e665-ce2d-4ad4-dfbf-cdc4f234ba96"
      },
      "source": [
        "# Slicing Features and Labels\n",
        "Samples = data_df.iloc[:,:-1]\n",
        "Labels = data_df.iloc[:,-1:]\n",
        "Samples = Samples.values\n",
        "Labels = Labels.values\n",
        "Labels = Labels.ravel()\n",
        "print()\n",
        "print(Labels)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\n",
            "[79.99 61.89 40.27 ... 23.7  32.77 32.4 ]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "keTTxwU84qPY",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 246
        },
        "outputId": "27f80d61-58ec-403c-aeca-5407f14929a5"
      },
      "source": [
        "# Normalizing\n",
        "mean = Samples.mean()\n",
        "std = Samples.std()\n",
        "Samples -= mean\n",
        "Samples /= std\n",
        "display(Samples)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "array([[ 0.68491213, -0.84750875, -0.84750875, ...,  2.10382035,\n",
              "         1.07085517, -0.76804989],\n",
              "       [ 0.68491213, -0.84750875, -0.84750875, ...,  2.1463876 ,\n",
              "         1.07085517, -0.76804989],\n",
              "       [ 0.09606522, -0.44311991, -0.84750875, ...,  1.79733617,\n",
              "         0.83815422, -0.08129831],\n",
              "       ...,\n",
              "       [-0.42609301, -0.45191714, -0.53932188, ...,  1.68495864,\n",
              "         1.36598808, -0.76804989],\n",
              "       [-0.39601215, -0.31768842, -0.84750875, ...,  1.9607944 ,\n",
              "         1.39124464, -0.76804989],\n",
              "       [-0.10712244, -0.5623082 , -0.62530772, ...,  1.60578356,\n",
              "         1.31348847, -0.76804989]])"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IguGkaRR5-a_",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "74deda73-4008-45cd-afb0-aeccd91e89e4"
      },
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "x_train, x_test, y_train, y_test = train_test_split(Samples, Labels, test_size=0.3, random_state=1)\n",
        "x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, test_size=0.285)\n",
        "\n",
        "print(x_train.shape)\n",
        "print(y_train.shape)\n",
        "print(x_test.shape)\n",
        "print(y_test.shape)\n",
        "print(x_val.shape)\n",
        "print(y_val.shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(515, 8)\n",
            "(515,)\n",
            "(309, 8)\n",
            "(309,)\n",
            "(206, 8)\n",
            "(206,)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4znv4CtZ6GnN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "40cd9f01-3db9-4089-9a3d-3db63a79e8ab"
      },
      "source": [
        "input_shape = x_train.shape[1]\n",
        "print(input_shape)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "8\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nfuHil2B6M-b"
      },
      "source": [
        "###############################"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "amvwGtAw_HRt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "outputId": "a01254ba-fd85-4b9d-b22b-219617491588"
      },
      "source": [
        "# normally we make Sequential model like this\n",
        "from keras.models import Sequential\n",
        "from keras import regularizers #for l2 regularization\n",
        "from keras.layers import Dense, Dropout\n",
        "from keras.optimizers import Adam\n",
        "\n",
        "activation = \"relu\"\n",
        "learning_rate = 0.01\n",
        "opt = Adam(lr=learning_rate)\n",
        "\n",
        "model = Sequential()\n",
        "model.add(Dense(128,activation = activation,input_shape = (8,)))#,activity_regularizer = regularizers.l2(1e-5)))\n",
        "model.add(Dropout(0.50))\n",
        "model.add(Dense(128,activation = activation,activity_regularizer = regularizers.l2(1e-5)))\n",
        "model.add(Dropout(0.50))\n",
        "model.add(Dense(1, activation = activation))# Compile the model\n",
        "\n",
        "model.compile(optimizer = opt,loss = \"mean_absolute_error\",metrics=['mse', \"mape\"])\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense (Dense)                (None, 128)               1152      \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_1 (Dense)              (None, 128)               16512     \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_2 (Dense)              (None, 1)                 129       \n",
            "=================================================================\n",
            "Total params: 17,793\n",
            "Trainable params: 17,793\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YVgYokS1Azbi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "f452156e-2186-4415-e71a-6622f5d6c0c6"
      },
      "source": [
        "history = model.fit(x_train,y_train,epochs=2,validation_data=(x_val,y_val))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/2\n",
            "17/17 [==============================] - 0s 12ms/step - loss: 21.7619 - mse: 735.1840 - mape: 74.5528 - val_loss: 15.2237 - val_mse: 352.1429 - val_mape: 57.9518\n",
            "Epoch 2/2\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 15.6840 - mse: 393.9334 - mape: 60.3261 - val_loss: 14.1004 - val_mse: 294.9263 - val_mape: 60.5009\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XMk6Wtg-_4mz"
      },
      "source": [
        "#####################"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "S5oRK5zZBXWS"
      },
      "source": [
        "### Hyperperameter optimizatoin\n",
        "Lets try it now"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A90yMKG__7EJ"
      },
      "source": [
        "n_cols = x_train.shape[1]\n",
        "input_shape = (n_cols, )# input shape\n",
        "\n",
        "from keras.models import Sequential\n",
        "from keras import regularizers #for l2 regularization\n",
        "from keras.layers import Dense, Dropout\n",
        "from keras.optimizers import Adam\n",
        "\n",
        "def create_model(learning_rate = 0.01, activation = 'relu'):\n",
        " # Create an Adam optimizer with the given learning rate\n",
        " opt = Adam(lr=learning_rate)\n",
        " # Create your binary classification model \n",
        " model = Sequential()\n",
        " model.add(Dense(128,activation = activation,input_shape = input_shape,activity_regularizer = regularizers.l2(1e-5)))\n",
        " model.add(Dropout(0.50))\n",
        " model.add(Dense(128,activation = activation,activity_regularizer = regularizers.l2(1e-5)))\n",
        " model.add(Dropout(0.50))\n",
        " model.add(Dense(1, activation = activation))\n",
        " # Compile the model\n",
        " model.compile(optimizer = opt,loss = \"mean_absolute_error\",metrics=['mse', \"mape\"])\n",
        " return model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XNWlYlkX_7Np"
      },
      "source": [
        "# Create a KerasClassifier object\n",
        "from keras.wrappers.scikit_learn import KerasRegressor\n",
        "from sklearn.model_selection import RandomizedSearchCV\n",
        "from sklearn.model_selection import KFold\n",
        "#from sklearn.model_selection import cross_val_score\n",
        "\n",
        "model = KerasRegressor(build_fn = create_model,verbose = 0)# Define the hyperparameter space\n",
        "params = {'activation': [\"relu\", \"tanh\"],\n",
        "          'batch_size': [16, 32, 64], \n",
        "          'epochs': [5, 10], # [50, 100]\n",
        "          'learning_rate': [0.01, 0.001, 0.0001]}# Create a randomize search cv object \n",
        "\n",
        "random_search = RandomizedSearchCV(model,param_distributions = params,cv = KFold(10))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8qQQrgHYE2YR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 864
        },
        "outputId": "577fd468-ad12-4b0a-a90b-c26bf3eb2669"
      },
      "source": [
        "random_search_results = random_search.fit(x_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:5 out of the last 357 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4fc0b70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 359 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4734488> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a713d510> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a82ae400> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a813be18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a7083b70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a1b386a8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4aed378> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a75a1158> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a6ed82f0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a6fdc510> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7aac99e18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a47a2f28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a2c54950> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4fc0f28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a71880d0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a38c1268> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a3705158> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a492bb70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a2362730> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a21dc400> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a3e45b70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7aac75ea0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a3a3e730> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a3679048> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a3ba31e0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a019a488> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4f57400> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a82ae0d0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7cc1c9620> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4bc9e18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a4997730> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a487de18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7aafd8e18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a21dce18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a36c76a8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a1f26268> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a1d919d8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7aacf1d90> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a1875378> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a1ed7ae8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a39a1f28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7aaeaf2f0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7aa8b4a60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a3cf28c8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a2362730> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7ff7a1e13ae8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oo1M7NIE_7QS",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "1f946857-3893-4c17-d84a-0afcaf843913"
      },
      "source": [
        "print(\"Best Score: \",random_search_results.best_score_,\n",
        " \"and Best Params: \",random_search_results.best_params_)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Best Score:  -12.119218921661377 and Best Params:  {'learning_rate': 0.01, 'epochs': 5, 'batch_size': 16, 'activation': 'relu'}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0Ud377RbGQRX",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "407c772d-cc53-4615-d6ed-ce3fa6af70d9"
      },
      "source": [
        "# we can use the best model above directly of ML\n",
        "\n",
        "prediction = random_search.predict(x_test)\n",
        "#prediction\n",
        "\n",
        "import numpy as np\n",
        "predict = 41\n",
        "print(\"Predicted Value :\",prediction[predict])\n",
        "print(\"Actual Value :\",prediction[predict])"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Predicted Value : 35.460598\n",
            "Actual Value : 35.460598\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "h-wAdehb8IIC"
      },
      "source": [
        "### Now using those parameters\n",
        "Making and running new model with same parameter in Deep Learning\n",
        "\n",
        "Note: (these steps below are not needed because we already have the model adove)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-FU2OOhO8G8T",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        },
        "outputId": "12cb82aa-cc51-4a38-f8c6-c67c37c567a8"
      },
      "source": [
        "learning_rate = 0.01\n",
        "activation = 'relu'\n",
        "epochs = 50\n",
        "batch_size = 32 \n",
        "\n",
        "model = create_model(learning_rate, activation)\n",
        "#model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential_307\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "dense_921 (Dense)            (None, 128)               1152      \n",
            "_________________________________________________________________\n",
            "dropout_614 (Dropout)        (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_922 (Dense)            (None, 128)               16512     \n",
            "_________________________________________________________________\n",
            "dropout_615 (Dropout)        (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_923 (Dense)            (None, 1)                 129       \n",
            "=================================================================\n",
            "Total params: 17,793\n",
            "Trainable params: 17,793\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EkWJbcL18POm",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "253b5ab4-6fc7-4f62-fedd-20a59cdc18d5"
      },
      "source": [
        "history = model.fit(x_train,y_train, epochs=epochs, batch_size = batch_size,\n",
        "                    validation_data=(x_val,y_val), verbose = 1)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/50\n",
            "17/17 [==============================] - 0s 11ms/step - loss: 20.7899 - mse: 674.1634 - mape: 74.7627 - val_loss: 16.1468 - val_mse: 401.6671 - val_mape: 56.1916\n",
            "Epoch 2/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 15.1645 - mse: 349.0859 - mape: 63.4318 - val_loss: 14.5092 - val_mse: 320.8870 - val_mape: 55.5158\n",
            "Epoch 3/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 14.1700 - mse: 314.9036 - mape: 58.1071 - val_loss: 14.1083 - val_mse: 310.8538 - val_mape: 49.9547\n",
            "Epoch 4/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 13.8001 - mse: 288.5428 - mape: 56.3754 - val_loss: 12.9969 - val_mse: 248.9715 - val_mape: 54.7970\n",
            "Epoch 5/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 13.4697 - mse: 283.9972 - mape: 53.8828 - val_loss: 13.6866 - val_mse: 294.5759 - val_mape: 45.8589\n",
            "Epoch 6/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 13.5122 - mse: 283.4504 - mape: 52.7597 - val_loss: 12.5075 - val_mse: 236.5335 - val_mape: 50.3286\n",
            "Epoch 7/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 13.5454 - mse: 282.6750 - mape: 54.5033 - val_loss: 12.3257 - val_mse: 231.5214 - val_mape: 48.8815\n",
            "Epoch 8/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 13.1667 - mse: 257.6855 - mape: 52.0203 - val_loss: 12.0176 - val_mse: 215.2209 - val_mape: 50.1550\n",
            "Epoch 9/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.2056 - mse: 233.8634 - mape: 51.6325 - val_loss: 12.0243 - val_mse: 225.5426 - val_mape: 43.9562\n",
            "Epoch 10/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.4090 - mse: 233.4636 - mape: 52.0459 - val_loss: 11.8986 - val_mse: 220.7121 - val_mape: 42.5377\n",
            "Epoch 11/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.0139 - mse: 222.9424 - mape: 45.7641 - val_loss: 11.3386 - val_mse: 199.2177 - val_mape: 43.8015\n",
            "Epoch 12/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.1096 - mse: 222.8463 - mape: 49.3237 - val_loss: 14.4577 - val_mse: 326.1330 - val_mape: 39.8603\n",
            "Epoch 13/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.7329 - mse: 256.4974 - mape: 48.9178 - val_loss: 10.7199 - val_mse: 177.6426 - val_mape: 43.3178\n",
            "Epoch 14/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 11.1426 - mse: 194.2802 - mape: 46.8932 - val_loss: 11.6441 - val_mse: 206.6751 - val_mape: 39.0491\n",
            "Epoch 15/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.0065 - mse: 235.3678 - mape: 50.5739 - val_loss: 13.9934 - val_mse: 304.0959 - val_mape: 38.7677\n",
            "Epoch 16/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 14.2757 - mse: 307.3064 - mape: 49.6630 - val_loss: 11.7456 - val_mse: 213.4065 - val_mape: 38.3017\n",
            "Epoch 17/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 12.8003 - mse: 242.8588 - mape: 47.1375 - val_loss: 11.3488 - val_mse: 198.1833 - val_mape: 39.6799\n",
            "Epoch 18/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 11.6239 - mse: 205.9134 - mape: 46.2006 - val_loss: 10.3580 - val_mse: 163.3384 - val_mape: 39.5464\n",
            "Epoch 19/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 11.4955 - mse: 203.3470 - mape: 45.9884 - val_loss: 10.2586 - val_mse: 159.7835 - val_mape: 40.1345\n",
            "Epoch 20/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.8143 - mse: 185.4747 - mape: 41.3500 - val_loss: 10.6881 - val_mse: 172.9879 - val_mape: 37.2201\n",
            "Epoch 21/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 11.1907 - mse: 197.0984 - mape: 44.1450 - val_loss: 10.2863 - val_mse: 158.4220 - val_mape: 37.1829\n",
            "Epoch 22/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 11.2129 - mse: 195.8838 - mape: 41.9687 - val_loss: 9.4403 - val_mse: 137.1414 - val_mape: 38.6664\n",
            "Epoch 23/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 11.3015 - mse: 204.6074 - mape: 43.6093 - val_loss: 11.0083 - val_mse: 177.8633 - val_mape: 53.5096\n",
            "Epoch 24/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.8581 - mse: 191.6742 - mape: 43.7469 - val_loss: 12.1383 - val_mse: 212.5323 - val_mape: 61.6975\n",
            "Epoch 25/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 12.0947 - mse: 228.0219 - mape: 46.7565 - val_loss: 11.1041 - val_mse: 181.5689 - val_mape: 55.9833\n",
            "Epoch 26/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 11.3759 - mse: 196.4584 - mape: 46.4555 - val_loss: 9.4150 - val_mse: 136.7736 - val_mape: 39.2168\n",
            "Epoch 27/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.1905 - mse: 167.1616 - mape: 39.6274 - val_loss: 9.4284 - val_mse: 137.0708 - val_mape: 40.8363\n",
            "Epoch 28/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.4853 - mse: 168.4651 - mape: 40.2415 - val_loss: 10.4451 - val_mse: 162.3786 - val_mape: 35.8663\n",
            "Epoch 29/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.4331 - mse: 170.2498 - mape: 41.0844 - val_loss: 10.2842 - val_mse: 155.5012 - val_mape: 37.5935\n",
            "Epoch 30/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 10.3075 - mse: 167.8519 - mape: 40.4089 - val_loss: 9.6398 - val_mse: 136.8059 - val_mape: 35.3893\n",
            "Epoch 31/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 9.5803 - mse: 145.8012 - mape: 36.9646 - val_loss: 9.2844 - val_mse: 134.4938 - val_mape: 42.7277\n",
            "Epoch 32/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 9.8202 - mse: 151.5814 - mape: 39.9149 - val_loss: 9.5012 - val_mse: 134.6471 - val_mape: 37.2567\n",
            "Epoch 33/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.3249 - mse: 169.2015 - mape: 38.8074 - val_loss: 9.1675 - val_mse: 128.2278 - val_mape: 38.2093\n",
            "Epoch 34/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 9.9164 - mse: 155.3023 - mape: 38.4888 - val_loss: 9.2070 - val_mse: 127.6200 - val_mape: 37.4978\n",
            "Epoch 35/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 10.3025 - mse: 168.6699 - mape: 38.7231 - val_loss: 9.2717 - val_mse: 129.1271 - val_mape: 35.5849\n",
            "Epoch 36/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.8126 - mse: 195.5815 - mape: 41.0391 - val_loss: 9.3538 - val_mse: 136.4074 - val_mape: 43.5295\n",
            "Epoch 37/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 9.9819 - mse: 162.4068 - mape: 40.6562 - val_loss: 9.4456 - val_mse: 131.2505 - val_mape: 38.2355\n",
            "Epoch 38/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 9.7955 - mse: 153.3736 - mape: 38.3084 - val_loss: 9.1657 - val_mse: 126.6125 - val_mape: 35.1954\n",
            "Epoch 39/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 9.9826 - mse: 159.7301 - mape: 38.5236 - val_loss: 10.0219 - val_mse: 146.9388 - val_mape: 36.1133\n",
            "Epoch 40/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.5308 - mse: 172.8907 - mape: 41.9399 - val_loss: 11.2970 - val_mse: 187.9863 - val_mape: 35.9696\n",
            "Epoch 41/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.5843 - mse: 178.7709 - mape: 41.8750 - val_loss: 9.8697 - val_mse: 141.7185 - val_mape: 37.9666\n",
            "Epoch 42/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 10.1707 - mse: 161.7079 - mape: 40.6793 - val_loss: 9.0548 - val_mse: 126.6292 - val_mape: 39.3893\n",
            "Epoch 43/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 10.0603 - mse: 161.7911 - mape: 38.8755 - val_loss: 9.1847 - val_mse: 127.9243 - val_mape: 38.0423\n",
            "Epoch 44/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.0762 - mse: 159.3272 - mape: 40.8715 - val_loss: 9.9621 - val_mse: 145.9331 - val_mape: 36.1585\n",
            "Epoch 45/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.4033 - mse: 176.3242 - mape: 41.0377 - val_loss: 10.5905 - val_mse: 164.2781 - val_mape: 36.0211\n",
            "Epoch 46/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 10.0746 - mse: 161.6337 - mape: 41.4045 - val_loss: 10.0388 - val_mse: 146.4097 - val_mape: 35.8743\n",
            "Epoch 47/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 9.9369 - mse: 160.8226 - mape: 38.1295 - val_loss: 9.3327 - val_mse: 129.7287 - val_mape: 38.9061\n",
            "Epoch 48/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 10.3456 - mse: 170.2930 - mape: 42.2307 - val_loss: 9.3666 - val_mse: 131.7757 - val_mape: 41.0559\n",
            "Epoch 49/50\n",
            "17/17 [==============================] - 0s 5ms/step - loss: 10.2186 - mse: 164.5034 - mape: 39.9511 - val_loss: 9.1602 - val_mse: 124.8206 - val_mape: 35.1879\n",
            "Epoch 50/50\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 9.9089 - mse: 155.9446 - mape: 38.8391 - val_loss: 9.2210 - val_mse: 128.4671 - val_mape: 39.3109\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iS6cdnuvJnpy"
      },
      "source": [
        "### Another great article about above example\n",
        "https://machinelearningmastery.com/hyperparameter-optimization-with-random-search-and-grid-search/"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OerS7y1tsiBQ"
      },
      "source": [
        "################################"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mejB_XxIJy5u"
      },
      "source": [
        "### Lets try same practice in Functional API"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8gD-yUlkADf1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "outputId": "b17fc1f8-6cd5-4ca4-943f-c4a598715a02"
      },
      "source": [
        "from keras import Input, layers, Model\n",
        "from keras.optimizers import Adam\n",
        "\n",
        "activation = \"relu\"\n",
        "learning_rate = 0.01\n",
        "opt = Adam(lr=learning_rate)\n",
        "\n",
        "input_tensor = Input(shape=(8,))\n",
        "x = layers.Dense(32, activation=activation)(input_tensor)\n",
        "x = layers.Dense(32, activation=activation)(x)\n",
        "output_tensor = layers.Dense(1, activation='softmax')(x)\n",
        "model = Model(input_tensor, output_tensor)\n",
        "model.compile(optimizer = opt,loss = \"mean_absolute_error\",metrics=['mse', \"mape\"])\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"functional_5\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_3 (InputLayer)         [(None, 8)]               0         \n",
            "_________________________________________________________________\n",
            "dense_6 (Dense)              (None, 32)                288       \n",
            "_________________________________________________________________\n",
            "dense_7 (Dense)              (None, 32)                1056      \n",
            "_________________________________________________________________\n",
            "dense_8 (Dense)              (None, 1)                 33        \n",
            "=================================================================\n",
            "Total params: 1,377\n",
            "Trainable params: 1,377\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XHPTOssKADiE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 87
        },
        "outputId": "766f1840-86a8-4578-c8a9-56d8aebaee82"
      },
      "source": [
        "history = model.fit(x_train,y_train,epochs=2,validation_data=(x_val,y_val))"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/2\n",
            "17/17 [==============================] - 0s 10ms/step - loss: 34.4839 - mse: 1483.8734 - mape: 96.1277 - val_loss: 34.7658 - val_mse: 1471.9219 - val_mape: 96.0676\n",
            "Epoch 2/2\n",
            "17/17 [==============================] - 0s 4ms/step - loss: 34.4839 - mse: 1483.8733 - mape: 96.1278 - val_loss: 34.7658 - val_mse: 1471.9219 - val_mape: 96.0676\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dcWC2qBSMFP2"
      },
      "source": [
        "### Hyperperameter optimizatoin (Functional Ali)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DoaGUiLkADkq"
      },
      "source": [
        "n_cols = x_train.shape[1]\n",
        "input_shape = (n_cols, )# input shape\n",
        "\n",
        "#from keras.models import Sequential\n",
        "from keras import regularizers #for l2 regularization\n",
        "from keras.layers import Dense, Dropout\n",
        "#from keras.optimizers import Adam\n",
        "\n",
        "def create_model(learning_rate = 0.01, activation = 'relu'):\n",
        " # Create an Adam optimizer with the given learning rate\n",
        "  opt = Adam(lr=learning_rate)\n",
        "  # Create your binary classification model \n",
        "  input_tensor = Input(shape=(8,))\n",
        "  x = layers.Dense(128, activation=activation,activity_regularizer = regularizers.l2(1e-5))(input_tensor)\n",
        "  x = layers.Dropout(0.50)(x)\n",
        "  x = layers.Dense(128, activation=activation,activity_regularizer = regularizers.l2(1e-5))(x)\n",
        "  x = layers.Dropout(0.50)(x)\n",
        "  output_tensor = layers.Dense(1, activation='softmax')(x)\n",
        "  model = Model(input_tensor, output_tensor)\n",
        "  # Compile the model\n",
        "  model.compile(optimizer = opt,loss = \"mean_absolute_error\",metrics=['mse', \"mape\"])\n",
        "  return model"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xa9wMgFGNy1R",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 369
        },
        "outputId": "7882047f-eeed-4c62-fbee-6f5877875d76"
      },
      "source": [
        "# onlu checking if the model is created corectly\n",
        "learning_rate = 0.01\n",
        "activation = 'relu'\n",
        "#epochs = 50\n",
        "#batch_size = 32 \n",
        "\n",
        "model = create_model(learning_rate, activation)\n",
        "model.summary()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"functional_7\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_4 (InputLayer)         [(None, 8)]               0         \n",
            "_________________________________________________________________\n",
            "dense_9 (Dense)              (None, 128)               1152      \n",
            "_________________________________________________________________\n",
            "dropout (Dropout)            (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_10 (Dense)             (None, 128)               16512     \n",
            "_________________________________________________________________\n",
            "dropout_1 (Dropout)          (None, 128)               0         \n",
            "_________________________________________________________________\n",
            "dense_11 (Dense)             (None, 1)                 129       \n",
            "=================================================================\n",
            "Total params: 17,793\n",
            "Trainable params: 17,793\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OlwZQ9bKNy4q"
      },
      "source": [
        "# Create a KerasClassifier object\n",
        "from keras.wrappers.scikit_learn import KerasRegressor\n",
        "from sklearn.model_selection import RandomizedSearchCV\n",
        "from sklearn.model_selection import KFold\n",
        "#from sklearn.model_selection import cross_val_score\n",
        "\n",
        "model = KerasRegressor(build_fn = create_model,verbose = 0)# Define the hyperparameter space\n",
        "params = {'activation': [\"relu\", \"tanh\"],\n",
        "          'batch_size': [16, 32, 64], \n",
        "          'epochs': [5, 10], # [50, 100]\n",
        "          'learning_rate': [0.01, 0.001, 0.0001]}# Create a randomize search cv object \n",
        "\n",
        "random_search = RandomizedSearchCV(model,param_distributions = params,cv = KFold(10))"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "L6LmqTjHADpy",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "819f5711-f8ab-444f-cb7c-086d4dd9bda0"
      },
      "source": [
        "random_search_results = random_search.fit(x_train, y_train)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:5 out of the last 18 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a00dac80> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 19 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03bac80> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:7 out of the last 20 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a65d378> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 21 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a48ef28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:9 out of the last 22 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a2ecf28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:10 out of the last 23 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a168f28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 24 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a22e158> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f764c1b1ea0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a02d31e0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f764c350158> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fcde8c8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f764c158d90> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fe2a7b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a5e5048> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a039e840> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a755e18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a67d268> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fcd6598> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76306521e0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:7 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a0103268> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:7 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76316d90d0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a2b4ea0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03ba950> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:9 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a22e048> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:9 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fc0b598> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:10 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fcb4f28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:10 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f7630561f28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fcb4950> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a1489d8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03ba730> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a67d400> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 14 calls to <function Model.make_test_function.<locals>.test_function at 0x7f764c1b1510> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fb82a60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fe34ae8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:7 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7f7630007b70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 14 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03ba598> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fe34840> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:9 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fda30d0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:10 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a2dae18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 14 calls to <function Model.make_test_function.<locals>.test_function at 0x7f7630607730> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76302ddbf8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:10 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763041c598> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:9 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76302332f0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f764c2927b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:7 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a1487b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a04b0268> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f763a2fc0d0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03d5e18> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fcb47b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fec7b70> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762f94bf28> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762e6b4ae8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 14 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03ba7b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762f9eebf8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:6 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762f8bba60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:7 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762ff1c598> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 14 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76302ddbf8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76a03d5ae8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:9 out of the last 12 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fec7ea0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:10 out of the last 13 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762fe2a7b8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 14 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762e326620> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:11 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f76302ddbf8> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:8 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762e326a60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n",
            "WARNING:tensorflow:5 out of the last 11 calls to <function Model.make_test_function.<locals>.test_function at 0x7f762e66f158> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/tutorials/customization/performance#python_or_tensor_args and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RCOeEq6dADsT",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "bff59f2c-3f57-48c2-96b5-22819a3761e0"
      },
      "source": [
        "print(\"Best Score: \",random_search_results.best_score_,\n",
        " \"and Best Params: \",random_search_results.best_params_)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Best Score:  -34.48199653625488 and Best Params:  {'learning_rate': 0.01, 'epochs': 10, 'batch_size': 16, 'activation': 'tanh'}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DaxhxA02VQlc"
      },
      "source": [
        "### Predicting in Functional APi\n",
        "https://stackoverflow.com/questions/38971293/get-class-labels-from-keras-functional-model/45176824#45176824"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4aN8e4mRSOiN",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "3c0cad1a-3394-4d27-e1dd-d58d030254db"
      },
      "source": [
        "\"\"\"#random_search.predict(x_test)\n",
        "import keras\n",
        "\n",
        "y_prob = random_search.predict(x_test) \n",
        "y_classes = keras.np_utils.probas_to_classes(y_proba)\n",
        "#y_classes = y_prob.argmax(axis=-1)\n",
        "y_classes\n",
        "\n",
        "#a = random_search.predict(x_test)\n",
        "#np.argmax(a)\n",
        "\n",
        "#y_prob = model.predict(x) \n",
        "#y_classes = y_prob.argmax(axis=-1)\"\"\""
      ],
      "execution_count": null,
      "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-33-1ee1d05bcdf6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0my_prob\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrandom_search\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0my_classes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkeras\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnp_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprobas_to_classes\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my_proba\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      6\u001b[0m \u001b[0;31m#y_classes = y_prob.argmax(axis=-1)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0my_classes\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: module 'keras' has no attribute 'np_utils'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qT6XPhH1SOlF"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1kVn6aYEADu3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        },
        "outputId": "99ac8e0a-7182-4f56-9d89-104e78f58663"
      },
      "source": [
        "\"\"\"# we can use the best model above directly of ML\n",
        "\n",
        "prediction = random_search.predict(x_test)\n",
        "#prediction\n",
        "\n",
        "import numpy as np\n",
        "predict = 41\n",
        "print(\"Predicted Value :\",prediction[predict])\n",
        "print(\"Actual Value :\",prediction[predict])\"\"\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Predicted Value : 1.0\n",
            "Actual Value : 1.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cI3Me8JqQ93v",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "outputId": "51cafe9d-a86c-4bbc-d730-4ebed19187ca"
      },
      "source": [
        "\"\"\"# we can use the best model above directly of ML\n",
        "\n",
        "import numpy as np\n",
        "\n",
        "prediction = random_search.np.argmax(predict(x_test))\n",
        "prediction\n",
        "\n",
        "#import numpy as np\n",
        "#predict = 41\n",
        "a = np.argmax(prediction[predict])\n",
        "#print(\"Predicted Value :\",prediction[predict])\n",
        "#print(\"Actual Value :\",prediction[predict])\n",
        "a\"\"\""
      ],
      "execution_count": null,
      "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-27-c88b31f66791>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m \u001b[0mprediction\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrandom_search\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margmax\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpredict\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx_test\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      6\u001b[0m \u001b[0mprediction\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mAttributeError\u001b[0m: 'RandomizedSearchCV' object has no attribute 'np'"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "smkFSrpVADxM"
      },
      "source": [
        "\"\"\"\n",
        "predict = 7\n",
        "a = np.argmax(final_preds[predict])\n",
        "print(\"Predicted value: \",a)\n",
        "print(\"Actual value: \",np.argmax(y_test[predict]))\"\"\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pa8nFw1V6nPO"
      },
      "source": [
        "####### Prediction codes might be wrong, i will update them later inshallah ##########"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-f6g1M7CcmdE"
      },
      "source": [
        "### 10 Hyperparameter optimization frameworks.\n",
        "https://towardsdatascience.com/10-hyperparameter-optimization-frameworks-8bc87bc8b7e3"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XpwGDT-xDO3k"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}