detect_outlier_save_model_try.ipynb

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      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
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    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
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      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.6.4"
    },
    "colab": {
      "name": "detect_outlier.ipynb",
      "provenance": [],
      "include_colab_link": true
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/danielsoy/data/blob/main/detect_outlier_save_model_try.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DU9NXhoiAKjK"
      },
      "source": [
        "import cv2\n",
        "import numpy as np\n",
        "from sklearn.model_selection import train_test_split\n",
        "from tensorflow.keras import Model\n",
        "from tensorflow.keras.datasets import fashion_mnist as fmnist\n",
        "from tensorflow.keras.layers import *"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U0T_FoZtAKjN"
      },
      "source": [
        "SEED = 84\n",
        "np.random.seed(SEED)"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A36S2v1ZAKjN"
      },
      "source": [
        "def build_autoencoder(input_shape=(28, 28, 1),\n",
        "                      encoding_size=96,\n",
        "                      alpha=0.2):\n",
        "    inputs = Input(shape=input_shape)\n",
        "    encoder = Conv2D(filters=32,\n",
        "                     kernel_size=(3, 3),\n",
        "                     strides=2,\n",
        "                     padding='same')(inputs)\n",
        "    encoder = LeakyReLU(alpha=alpha)(encoder)\n",
        "    encoder = BatchNormalization()(encoder)\n",
        "    encoder = Conv2D(filters=64,\n",
        "                     kernel_size=(3, 3),\n",
        "                     strides=2,\n",
        "                     padding='same')(encoder)\n",
        "    encoder = LeakyReLU(alpha=alpha)(encoder)\n",
        "    encoder = BatchNormalization()(encoder)\n",
        "    encoder_output_shape = encoder.shape\n",
        "    encoder = Flatten()(encoder)\n",
        "    encoder_output = Dense(encoding_size)(encoder)\n",
        "    encoder_model = Model(inputs, encoder_output)\n",
        "\n",
        "    # Build decoder\n",
        "    decoder_input = Input(shape=(encoding_size,))\n",
        "    target_shape = tuple(encoder_output_shape[1:])\n",
        "    decoder = Dense(np.prod(target_shape))(decoder_input)\n",
        "    decoder = Reshape(target_shape)(decoder)\n",
        "    decoder = Conv2DTranspose(filters=64,\n",
        "                              kernel_size=(3, 3),\n",
        "                              strides=2,\n",
        "                              padding='same')(decoder)\n",
        "    decoder = LeakyReLU(alpha=alpha)(decoder)\n",
        "    decoder = BatchNormalization()(decoder)\n",
        "    decoder = Conv2DTranspose(filters=32,\n",
        "                              kernel_size=(3, 3),\n",
        "                              strides=2,\n",
        "                              padding='same')(decoder)\n",
        "    decoder = LeakyReLU(alpha=alpha)(decoder)\n",
        "    decoder = BatchNormalization()(decoder)\n",
        "    decoder = Conv2DTranspose(filters=1,\n",
        "                              kernel_size=(3, 3),\n",
        "                              padding='same')(decoder)\n",
        "    outputs = Activation('sigmoid')(decoder)\n",
        "    decoder_model = Model(decoder_input, outputs)\n",
        "    encoder_model_output = encoder_model(inputs)\n",
        "    decoder_model_output = decoder_model(encoder_model_output)\n",
        "    autoencoder_model = Model(inputs, decoder_model_output)\n",
        "    return encoder_model, decoder_model, autoencoder_model"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cGa8o_2hAKjO"
      },
      "source": [
        "def create_anomalous_dataset(features,\n",
        "                             labels,\n",
        "                             regular_label,\n",
        "                             anomaly_label,\n",
        "                             corruption_proportion=0.01):\n",
        "    regular_data_idx = np.where(labels == regular_label)[0]\n",
        "    anomalous_data_idx = np.where(labels == anomaly_label)[0]\n",
        "    np.random.shuffle(regular_data_idx)\n",
        "    np.random.shuffle(anomalous_data_idx)\n",
        "    num_anomalies = int(len(regular_data_idx) *\n",
        "                        corruption_proportion)\n",
        "    anomalous_data_idx = anomalous_data_idx[:num_anomalies]\n",
        "    data = np.vstack([features[regular_data_idx],\n",
        "                      features[anomalous_data_idx]])\n",
        "    np.random.shuffle(data)\n",
        "    return data"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "96AnV5dlAKjP",
        "outputId": "adca1fac-a82d-4715-b6ed-bdc0fbe74d3f"
      },
      "source": [
        "(X_train, y_train), (X_test, y_test) = fmnist.load_data()\n",
        "X = np.vstack([X_train, X_test])\n",
        "y = np.hstack([y_train, y_test])"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n",
            "32768/29515 [=================================] - 0s 0us/step\n",
            "40960/29515 [=========================================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n",
            "26427392/26421880 [==============================] - 0s 0us/step\n",
            "26435584/26421880 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n",
            "16384/5148 [===============================================================================================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n",
            "4423680/4422102 [==============================] - 0s 0us/step\n",
            "4431872/4422102 [==============================] - 0s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "V9TmIuIyAKjQ"
      },
      "source": [
        "REGULAR_LABEL = 5  # Sandal\n",
        "ANOMALY_LABEL = 0  # T-shirt/top"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1pmW4Kc5AKjQ"
      },
      "source": [
        "data = create_anomalous_dataset(X, y,\n",
        "                                REGULAR_LABEL,\n",
        "                                ANOMALY_LABEL)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QF-GsQe7AKjR"
      },
      "source": [
        "data = np.expand_dims(data, axis=-1)\n",
        "data = data.astype('float32') / 255.0"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SBObGtNlAKjR"
      },
      "source": [
        "X_train, X_test = train_test_split(data,\n",
        "                                   train_size=0.8,\n",
        "                                   random_state=SEED)"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GJsOMyX0AKjS"
      },
      "source": [
        "_, _, autoencoder = build_autoencoder(encoding_size=256)\n",
        "autoencoder.compile(optimizer='adam', loss='mse')"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8tkRDmuYAKjS",
        "outputId": "e567aa37-146c-4e7f-ead5-81a20be33a0b"
      },
      "source": [
        "EPOCHS = 1000\n",
        "BATCH_SIZE = 1024\n",
        "autoencoder.fit(X_train, X_train,\n",
        "                epochs=EPOCHS,\n",
        "                batch_size=BATCH_SIZE,\n",
        "                validation_data=(X_test, X_test))"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/1000\n",
            "6/6 [==============================] - 1s 154ms/step - loss: 6.5217e-04 - val_loss: 0.0025\n",
            "Epoch 2/1000\n",
            "6/6 [==============================] - 1s 150ms/step - loss: 7.2473e-04 - val_loss: 0.0025\n",
            "Epoch 3/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 7.0716e-04 - val_loss: 0.0025\n",
            "Epoch 4/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 7.3993e-04 - val_loss: 0.0026\n",
            "Epoch 5/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 6.9295e-04 - val_loss: 0.0025\n",
            "Epoch 6/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.7147e-04 - val_loss: 0.0025\n",
            "Epoch 7/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.6924e-04 - val_loss: 0.0024\n",
            "Epoch 8/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.3188e-04 - val_loss: 0.0025\n",
            "Epoch 9/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 7.4193e-04 - val_loss: 0.0026\n",
            "Epoch 10/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 6.9334e-04 - val_loss: 0.0025\n",
            "Epoch 11/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.6350e-04 - val_loss: 0.0024\n",
            "Epoch 12/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.2481e-04 - val_loss: 0.0024\n",
            "Epoch 13/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.2134e-04 - val_loss: 0.0024\n",
            "Epoch 14/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 5.9416e-04 - val_loss: 0.0024\n",
            "Epoch 15/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.0957e-04 - val_loss: 0.0024\n",
            "Epoch 16/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.1048e-04 - val_loss: 0.0024\n",
            "Epoch 17/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 5.9829e-04 - val_loss: 0.0025\n",
            "Epoch 18/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.6823e-04 - val_loss: 0.0025\n",
            "Epoch 19/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 6.3277e-04 - val_loss: 0.0024\n",
            "Epoch 20/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.0812e-04 - val_loss: 0.0024\n",
            "Epoch 21/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 6.2101e-04 - val_loss: 0.0025\n",
            "Epoch 22/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 6.1477e-04 - val_loss: 0.0024\n",
            "Epoch 23/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.0266e-04 - val_loss: 0.0025\n",
            "Epoch 24/1000\n",
            "6/6 [==============================] - 1s 150ms/step - loss: 6.2848e-04 - val_loss: 0.0024\n",
            "Epoch 25/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 6.1687e-04 - val_loss: 0.0024\n",
            "Epoch 26/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 5.9226e-04 - val_loss: 0.0024\n",
            "Epoch 27/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.1462e-04 - val_loss: 0.0024\n",
            "Epoch 28/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.0529e-04 - val_loss: 0.0025\n",
            "Epoch 29/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.2137e-04 - val_loss: 0.0024\n",
            "Epoch 30/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.0254e-04 - val_loss: 0.0025\n",
            "Epoch 31/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.0565e-04 - val_loss: 0.0025\n",
            "Epoch 32/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 7.2854e-04 - val_loss: 0.0025\n",
            "Epoch 33/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 6.6762e-04 - val_loss: 0.0025\n",
            "Epoch 34/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 6.5124e-04 - val_loss: 0.0025\n",
            "Epoch 35/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 6.1926e-04 - val_loss: 0.0025\n",
            "Epoch 36/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 6.6206e-04 - val_loss: 0.0025\n",
            "Epoch 37/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.7285e-04 - val_loss: 0.0025\n",
            "Epoch 38/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.5685e-04 - val_loss: 0.0025\n",
            "Epoch 39/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.3179e-04 - val_loss: 0.0025\n",
            "Epoch 40/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 7.5146e-04 - val_loss: 0.0025\n",
            "Epoch 41/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.7970e-04 - val_loss: 0.0025\n",
            "Epoch 42/1000\n",
            "6/6 [==============================] - 1s 150ms/step - loss: 7.5551e-04 - val_loss: 0.0026\n",
            "Epoch 43/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.8664e-04 - val_loss: 0.0025\n",
            "Epoch 44/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.6354e-04 - val_loss: 0.0025\n",
            "Epoch 45/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 6.7049e-04 - val_loss: 0.0025\n",
            "Epoch 46/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.2071e-04 - val_loss: 0.0025\n",
            "Epoch 47/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.0644e-04 - val_loss: 0.0025\n",
            "Epoch 48/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.1947e-04 - val_loss: 0.0025\n",
            "Epoch 49/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 6.1815e-04 - val_loss: 0.0024\n",
            "Epoch 50/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 5.9285e-04 - val_loss: 0.0025\n",
            "Epoch 51/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 6.1538e-04 - val_loss: 0.0025\n",
            "Epoch 52/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.5928e-04 - val_loss: 0.0025\n",
            "Epoch 53/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 7.1883e-04 - val_loss: 0.0025\n",
            "Epoch 54/1000\n",
            "6/6 [==============================] - 1s 148ms/step - loss: 6.3567e-04 - val_loss: 0.0025\n",
            "Epoch 55/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 6.0998e-04 - val_loss: 0.0025\n",
            "Epoch 56/1000\n",
            "6/6 [==============================] - 1s 148ms/step - loss: 5.8309e-04 - val_loss: 0.0025\n",
            "Epoch 57/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 5.8947e-04 - val_loss: 0.0025\n",
            "Epoch 58/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.0204e-04 - val_loss: 0.0025\n",
            "Epoch 59/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 5.5551e-04 - val_loss: 0.0025\n",
            "Epoch 60/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 5.7203e-04 - val_loss: 0.0025\n",
            "Epoch 61/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 5.8480e-04 - val_loss: 0.0026\n",
            "Epoch 62/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.4225e-04 - val_loss: 0.0027\n",
            "Epoch 63/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 7.2991e-04 - val_loss: 0.0026\n",
            "Epoch 64/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 7.2494e-04 - val_loss: 0.0026\n",
            "Epoch 65/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 7.5007e-04 - val_loss: 0.0026\n",
            "Epoch 66/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.6574e-04 - val_loss: 0.0025\n",
            "Epoch 67/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 6.1553e-04 - val_loss: 0.0025\n",
            "Epoch 68/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 5.8672e-04 - val_loss: 0.0024\n",
            "Epoch 69/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 5.6902e-04 - val_loss: 0.0025\n",
            "Epoch 70/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.1167e-04 - val_loss: 0.0025\n",
            "Epoch 71/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 5.8095e-04 - val_loss: 0.0025\n",
            "Epoch 72/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 5.6493e-04 - val_loss: 0.0025\n",
            "Epoch 73/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 5.5564e-04 - val_loss: 0.0025\n",
            "Epoch 74/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.0164e-04 - val_loss: 0.0025\n",
            "Epoch 75/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 5.6504e-04 - val_loss: 0.0025\n",
            "Epoch 76/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.0430e-04 - val_loss: 0.0025\n",
            "Epoch 77/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 5.5560e-04 - val_loss: 0.0025\n",
            "Epoch 78/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 5.6159e-04 - val_loss: 0.0024\n",
            "Epoch 79/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 5.3547e-04 - val_loss: 0.0025\n",
            "Epoch 80/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 5.8873e-04 - val_loss: 0.0026\n",
            "Epoch 81/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 7.0981e-04 - val_loss: 0.0026\n",
            "Epoch 82/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.4254e-04 - val_loss: 0.0025\n",
            "Epoch 83/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 6.9751e-04 - val_loss: 0.0026\n",
            "Epoch 84/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 6.5685e-04 - val_loss: 0.0025\n",
            "Epoch 85/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 5.9327e-04 - val_loss: 0.0025\n",
            "Epoch 86/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 5.9940e-04 - val_loss: 0.0025\n",
            "Epoch 87/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 5.8162e-04 - val_loss: 0.0025\n",
            "Epoch 88/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 5.4823e-04 - val_loss: 0.0025\n",
            "Epoch 89/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 5.2777e-04 - val_loss: 0.0025\n",
            "Epoch 90/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.1808e-04 - val_loss: 0.0025\n",
            "Epoch 91/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 5.9144e-04 - val_loss: 0.0025\n",
            "Epoch 92/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.3550e-04 - val_loss: 0.0026\n",
            "Epoch 93/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.2103e-04 - val_loss: 0.0026\n",
            "Epoch 94/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 6.3289e-04 - val_loss: 0.0025\n",
            "Epoch 95/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 5.7127e-04 - val_loss: 0.0025\n",
            "Epoch 96/1000\n",
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            "Epoch 578/1000\n",
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            "Epoch 579/1000\n",
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            "Epoch 580/1000\n",
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            "Epoch 581/1000\n",
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            "Epoch 582/1000\n",
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            "Epoch 583/1000\n",
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            "Epoch 590/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.4706e-04 - val_loss: 0.0028\n",
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            "Epoch 592/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3062e-04 - val_loss: 0.0027\n",
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            "6/6 [==============================] - 1s 142ms/step - loss: 3.4794e-04 - val_loss: 0.0027\n",
            "Epoch 594/1000\n",
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            "Epoch 595/1000\n",
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            "Epoch 596/1000\n",
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            "Epoch 597/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5076e-04 - val_loss: 0.0028\n",
            "Epoch 598/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 4.2942e-04 - val_loss: 0.0028\n",
            "Epoch 599/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5274e-04 - val_loss: 0.0028\n",
            "Epoch 600/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.4410e-04 - val_loss: 0.0028\n",
            "Epoch 601/1000\n",
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            "Epoch 602/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.7817e-04 - val_loss: 0.0028\n",
            "Epoch 603/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.6438e-04 - val_loss: 0.0028\n",
            "Epoch 604/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 3.4297e-04 - val_loss: 0.0028\n",
            "Epoch 605/1000\n",
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            "Epoch 606/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.2928e-04 - val_loss: 0.0027\n",
            "Epoch 607/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.2099e-04 - val_loss: 0.0028\n",
            "Epoch 608/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.5845e-04 - val_loss: 0.0028\n",
            "Epoch 609/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 4.0432e-04 - val_loss: 0.0028\n",
            "Epoch 610/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.4943e-04 - val_loss: 0.0027\n",
            "Epoch 611/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.9773e-04 - val_loss: 0.0028\n",
            "Epoch 612/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.6209e-04 - val_loss: 0.0028\n",
            "Epoch 613/1000\n",
            "6/6 [==============================] - 1s 150ms/step - loss: 3.5777e-04 - val_loss: 0.0028\n",
            "Epoch 614/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.2307e-04 - val_loss: 0.0028\n",
            "Epoch 615/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.4391e-04 - val_loss: 0.0028\n",
            "Epoch 616/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.6692e-04 - val_loss: 0.0028\n",
            "Epoch 617/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 3.7243e-04 - val_loss: 0.0028\n",
            "Epoch 618/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.8304e-04 - val_loss: 0.0028\n",
            "Epoch 619/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.7917e-04 - val_loss: 0.0028\n",
            "Epoch 620/1000\n",
            "6/6 [==============================] - 1s 150ms/step - loss: 4.1694e-04 - val_loss: 0.0028\n",
            "Epoch 621/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 4.5367e-04 - val_loss: 0.0028\n",
            "Epoch 622/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 4.0860e-04 - val_loss: 0.0028\n",
            "Epoch 623/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.8264e-04 - val_loss: 0.0028\n",
            "Epoch 624/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.9859e-04 - val_loss: 0.0028\n",
            "Epoch 625/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.3976e-04 - val_loss: 0.0029\n",
            "Epoch 626/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 4.1104e-04 - val_loss: 0.0028\n",
            "Epoch 627/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.6910e-04 - val_loss: 0.0028\n",
            "Epoch 628/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.4806e-04 - val_loss: 0.0028\n",
            "Epoch 629/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 4.5193e-04 - val_loss: 0.0029\n",
            "Epoch 630/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 4.4606e-04 - val_loss: 0.0030\n",
            "Epoch 631/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 4.3427e-04 - val_loss: 0.0029\n",
            "Epoch 632/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.8334e-04 - val_loss: 0.0028\n",
            "Epoch 633/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.5222e-04 - val_loss: 0.0028\n",
            "Epoch 634/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5453e-04 - val_loss: 0.0029\n",
            "Epoch 635/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.3835e-04 - val_loss: 0.0028\n",
            "Epoch 636/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.2357e-04 - val_loss: 0.0028\n",
            "Epoch 637/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.9694e-04 - val_loss: 0.0028\n",
            "Epoch 638/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.0383e-04 - val_loss: 0.0028\n",
            "Epoch 639/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1715e-04 - val_loss: 0.0028\n",
            "Epoch 640/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.9642e-04 - val_loss: 0.0028\n",
            "Epoch 641/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 3.2742e-04 - val_loss: 0.0028\n",
            "Epoch 642/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.3964e-04 - val_loss: 0.0029\n",
            "Epoch 643/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.6476e-04 - val_loss: 0.0029\n",
            "Epoch 644/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.1680e-04 - val_loss: 0.0029\n",
            "Epoch 645/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 4.1808e-04 - val_loss: 0.0028\n",
            "Epoch 646/1000\n",
            "6/6 [==============================] - 1s 155ms/step - loss: 3.6760e-04 - val_loss: 0.0028\n",
            "Epoch 647/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7308e-04 - val_loss: 0.0028\n",
            "Epoch 648/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.3960e-04 - val_loss: 0.0028\n",
            "Epoch 649/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.4962e-04 - val_loss: 0.0028\n",
            "Epoch 650/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.4432e-04 - val_loss: 0.0028\n",
            "Epoch 651/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.6865e-04 - val_loss: 0.0028\n",
            "Epoch 652/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3317e-04 - val_loss: 0.0028\n",
            "Epoch 653/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.7010e-04 - val_loss: 0.0028\n",
            "Epoch 654/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.7123e-04 - val_loss: 0.0028\n",
            "Epoch 655/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.4959e-04 - val_loss: 0.0029\n",
            "Epoch 656/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.7995e-04 - val_loss: 0.0029\n",
            "Epoch 657/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.8698e-04 - val_loss: 0.0028\n",
            "Epoch 658/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.3925e-04 - val_loss: 0.0028\n",
            "Epoch 659/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1733e-04 - val_loss: 0.0029\n",
            "Epoch 660/1000\n",
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            "Epoch 661/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7555e-04 - val_loss: 0.0028\n",
            "Epoch 662/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.5103e-04 - val_loss: 0.0028\n",
            "Epoch 663/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.4094e-04 - val_loss: 0.0028\n",
            "Epoch 664/1000\n",
            "6/6 [==============================] - 1s 153ms/step - loss: 3.1088e-04 - val_loss: 0.0028\n",
            "Epoch 665/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.1489e-04 - val_loss: 0.0028\n",
            "Epoch 666/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.2248e-04 - val_loss: 0.0028\n",
            "Epoch 667/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0789e-04 - val_loss: 0.0028\n",
            "Epoch 668/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.1464e-04 - val_loss: 0.0028\n",
            "Epoch 669/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.6673e-04 - val_loss: 0.0028\n",
            "Epoch 670/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.6510e-04 - val_loss: 0.0029\n",
            "Epoch 671/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.5485e-04 - val_loss: 0.0029\n",
            "Epoch 672/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7749e-04 - val_loss: 0.0028\n",
            "Epoch 673/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.4809e-04 - val_loss: 0.0028\n",
            "Epoch 674/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.6555e-04 - val_loss: 0.0028\n",
            "Epoch 675/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.5920e-04 - val_loss: 0.0028\n",
            "Epoch 676/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7133e-04 - val_loss: 0.0028\n",
            "Epoch 677/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.2029e-04 - val_loss: 0.0028\n",
            "Epoch 678/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.4848e-04 - val_loss: 0.0028\n",
            "Epoch 679/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.6972e-04 - val_loss: 0.0028\n",
            "Epoch 680/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.9613e-04 - val_loss: 0.0028\n",
            "Epoch 681/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.4397e-04 - val_loss: 0.0028\n",
            "Epoch 682/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.3747e-04 - val_loss: 0.0028\n",
            "Epoch 683/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5847e-04 - val_loss: 0.0028\n",
            "Epoch 684/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5128e-04 - val_loss: 0.0028\n",
            "Epoch 685/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.6811e-04 - val_loss: 0.0028\n",
            "Epoch 686/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.8017e-04 - val_loss: 0.0028\n",
            "Epoch 687/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.7067e-04 - val_loss: 0.0028\n",
            "Epoch 688/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.3240e-04 - val_loss: 0.0028\n",
            "Epoch 689/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1804e-04 - val_loss: 0.0028\n",
            "Epoch 690/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.3176e-04 - val_loss: 0.0028\n",
            "Epoch 691/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.5986e-04 - val_loss: 0.0028\n",
            "Epoch 692/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.7441e-04 - val_loss: 0.0028\n",
            "Epoch 693/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.6447e-04 - val_loss: 0.0029\n",
            "Epoch 694/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7175e-04 - val_loss: 0.0029\n",
            "Epoch 695/1000\n",
            "6/6 [==============================] - 1s 156ms/step - loss: 3.3708e-04 - val_loss: 0.0029\n",
            "Epoch 696/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.5566e-04 - val_loss: 0.0028\n",
            "Epoch 697/1000\n",
            "6/6 [==============================] - 1s 148ms/step - loss: 3.5884e-04 - val_loss: 0.0028\n",
            "Epoch 698/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.2156e-04 - val_loss: 0.0028\n",
            "Epoch 699/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1442e-04 - val_loss: 0.0029\n",
            "Epoch 700/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.3542e-04 - val_loss: 0.0028\n",
            "Epoch 701/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.2478e-04 - val_loss: 0.0028\n",
            "Epoch 702/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.0344e-04 - val_loss: 0.0029\n",
            "Epoch 703/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.5587e-04 - val_loss: 0.0028\n",
            "Epoch 704/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1333e-04 - val_loss: 0.0029\n",
            "Epoch 705/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1752e-04 - val_loss: 0.0028\n",
            "Epoch 706/1000\n",
            "6/6 [==============================] - 1s 144ms/step - loss: 3.2787e-04 - val_loss: 0.0029\n",
            "Epoch 707/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.5663e-04 - val_loss: 0.0028\n",
            "Epoch 708/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.2766e-04 - val_loss: 0.0028\n",
            "Epoch 709/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.2076e-04 - val_loss: 0.0028\n",
            "Epoch 710/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.6854e-04 - val_loss: 0.0029\n",
            "Epoch 711/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.8382e-04 - val_loss: 0.0029\n",
            "Epoch 712/1000\n",
            "6/6 [==============================] - 1s 150ms/step - loss: 3.5815e-04 - val_loss: 0.0028\n",
            "Epoch 713/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5659e-04 - val_loss: 0.0029\n",
            "Epoch 714/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.9912e-04 - val_loss: 0.0029\n",
            "Epoch 715/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 4.3424e-04 - val_loss: 0.0030\n",
            "Epoch 716/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.2467e-04 - val_loss: 0.0030\n",
            "Epoch 717/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.6251e-04 - val_loss: 0.0029\n",
            "Epoch 718/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.6186e-04 - val_loss: 0.0028\n",
            "Epoch 719/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.5089e-04 - val_loss: 0.0029\n",
            "Epoch 720/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 4.3352e-04 - val_loss: 0.0029\n",
            "Epoch 721/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.7781e-04 - val_loss: 0.0029\n",
            "Epoch 722/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 4.1057e-04 - val_loss: 0.0029\n",
            "Epoch 723/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.7099e-04 - val_loss: 0.0028\n",
            "Epoch 724/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.5477e-04 - val_loss: 0.0028\n",
            "Epoch 725/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.4052e-04 - val_loss: 0.0028\n",
            "Epoch 726/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.2855e-04 - val_loss: 0.0028\n",
            "Epoch 727/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.2023e-04 - val_loss: 0.0028\n",
            "Epoch 728/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.4562e-04 - val_loss: 0.0028\n",
            "Epoch 729/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1773e-04 - val_loss: 0.0028\n",
            "Epoch 730/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.0451e-04 - val_loss: 0.0028\n",
            "Epoch 731/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.1026e-04 - val_loss: 0.0028\n",
            "Epoch 732/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.9567e-04 - val_loss: 0.0028\n",
            "Epoch 733/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.1243e-04 - val_loss: 0.0030\n",
            "Epoch 734/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.7189e-04 - val_loss: 0.0029\n",
            "Epoch 735/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.9191e-04 - val_loss: 0.0030\n",
            "Epoch 736/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.0636e-04 - val_loss: 0.0029\n",
            "Epoch 737/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.6756e-04 - val_loss: 0.0029\n",
            "Epoch 738/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3403e-04 - val_loss: 0.0028\n",
            "Epoch 739/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.4283e-04 - val_loss: 0.0029\n",
            "Epoch 740/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.3991e-04 - val_loss: 0.0028\n",
            "Epoch 741/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1041e-04 - val_loss: 0.0028\n",
            "Epoch 742/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.1552e-04 - val_loss: 0.0029\n",
            "Epoch 743/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1232e-04 - val_loss: 0.0028\n",
            "Epoch 744/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3684e-04 - val_loss: 0.0029\n",
            "Epoch 745/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.7990e-04 - val_loss: 0.0028\n",
            "Epoch 746/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.3930e-04 - val_loss: 0.0028\n",
            "Epoch 747/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.5344e-04 - val_loss: 0.0029\n",
            "Epoch 748/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.5441e-04 - val_loss: 0.0029\n",
            "Epoch 749/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.2452e-04 - val_loss: 0.0028\n",
            "Epoch 750/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1630e-04 - val_loss: 0.0029\n",
            "Epoch 751/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.0885e-04 - val_loss: 0.0028\n",
            "Epoch 752/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.0320e-04 - val_loss: 0.0029\n",
            "Epoch 753/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.6702e-04 - val_loss: 0.0028\n",
            "Epoch 754/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.4472e-04 - val_loss: 0.0028\n",
            "Epoch 755/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 3.5794e-04 - val_loss: 0.0029\n",
            "Epoch 756/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 3.4861e-04 - val_loss: 0.0029\n",
            "Epoch 757/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.4283e-04 - val_loss: 0.0028\n",
            "Epoch 758/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 3.1826e-04 - val_loss: 0.0029\n",
            "Epoch 759/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1867e-04 - val_loss: 0.0028\n",
            "Epoch 760/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.5933e-04 - val_loss: 0.0029\n",
            "Epoch 761/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.4834e-04 - val_loss: 0.0029\n",
            "Epoch 762/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1077e-04 - val_loss: 0.0028\n",
            "Epoch 763/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.3689e-04 - val_loss: 0.0029\n",
            "Epoch 764/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.4652e-04 - val_loss: 0.0029\n",
            "Epoch 765/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1635e-04 - val_loss: 0.0028\n",
            "Epoch 766/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.2076e-04 - val_loss: 0.0029\n",
            "Epoch 767/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7000e-04 - val_loss: 0.0029\n",
            "Epoch 768/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3139e-04 - val_loss: 0.0029\n",
            "Epoch 769/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1344e-04 - val_loss: 0.0028\n",
            "Epoch 770/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 3.1891e-04 - val_loss: 0.0029\n",
            "Epoch 771/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.0646e-04 - val_loss: 0.0028\n",
            "Epoch 772/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.9366e-04 - val_loss: 0.0029\n",
            "Epoch 773/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.2854e-04 - val_loss: 0.0029\n",
            "Epoch 774/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.1020e-04 - val_loss: 0.0029\n",
            "Epoch 775/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.9597e-04 - val_loss: 0.0028\n",
            "Epoch 776/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.0932e-04 - val_loss: 0.0029\n",
            "Epoch 777/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.6962e-04 - val_loss: 0.0029\n",
            "Epoch 778/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.7455e-04 - val_loss: 0.0030\n",
            "Epoch 779/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 4.0372e-04 - val_loss: 0.0030\n",
            "Epoch 780/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.6366e-04 - val_loss: 0.0029\n",
            "Epoch 781/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.5442e-04 - val_loss: 0.0029\n",
            "Epoch 782/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.9238e-04 - val_loss: 0.0030\n",
            "Epoch 783/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 4.5324e-04 - val_loss: 0.0029\n",
            "Epoch 784/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.6415e-04 - val_loss: 0.0029\n",
            "Epoch 785/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.6487e-04 - val_loss: 0.0030\n",
            "Epoch 786/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.9313e-04 - val_loss: 0.0029\n",
            "Epoch 787/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3261e-04 - val_loss: 0.0029\n",
            "Epoch 788/1000\n",
            "6/6 [==============================] - 1s 145ms/step - loss: 3.2175e-04 - val_loss: 0.0029\n",
            "Epoch 789/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0468e-04 - val_loss: 0.0028\n",
            "Epoch 790/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.0320e-04 - val_loss: 0.0028\n",
            "Epoch 791/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.9001e-04 - val_loss: 0.0029\n",
            "Epoch 792/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0217e-04 - val_loss: 0.0028\n",
            "Epoch 793/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.1224e-04 - val_loss: 0.0029\n",
            "Epoch 794/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.2437e-04 - val_loss: 0.0029\n",
            "Epoch 795/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.0140e-04 - val_loss: 0.0029\n",
            "Epoch 796/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.5524e-04 - val_loss: 0.0029\n",
            "Epoch 797/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1650e-04 - val_loss: 0.0029\n",
            "Epoch 798/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3999e-04 - val_loss: 0.0029\n",
            "Epoch 799/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.0442e-04 - val_loss: 0.0029\n",
            "Epoch 800/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.9272e-04 - val_loss: 0.0028\n",
            "Epoch 801/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.8961e-04 - val_loss: 0.0029\n",
            "Epoch 802/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.0092e-04 - val_loss: 0.0029\n",
            "Epoch 803/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5715e-04 - val_loss: 0.0029\n",
            "Epoch 804/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.8457e-04 - val_loss: 0.0029\n",
            "Epoch 805/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.5508e-04 - val_loss: 0.0029\n",
            "Epoch 806/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.4437e-04 - val_loss: 0.0029\n",
            "Epoch 807/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.9191e-04 - val_loss: 0.0030\n",
            "Epoch 808/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 3.5538e-04 - val_loss: 0.0029\n",
            "Epoch 809/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.2774e-04 - val_loss: 0.0028\n",
            "Epoch 810/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.9604e-04 - val_loss: 0.0029\n",
            "Epoch 811/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.0290e-04 - val_loss: 0.0029\n",
            "Epoch 812/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.2924e-04 - val_loss: 0.0029\n",
            "Epoch 813/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3598e-04 - val_loss: 0.0029\n",
            "Epoch 814/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.1047e-04 - val_loss: 0.0028\n",
            "Epoch 815/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.8419e-04 - val_loss: 0.0028\n",
            "Epoch 816/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 2.8706e-04 - val_loss: 0.0029\n",
            "Epoch 817/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.7927e-04 - val_loss: 0.0029\n",
            "Epoch 818/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.0920e-04 - val_loss: 0.0029\n",
            "Epoch 819/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.0671e-04 - val_loss: 0.0028\n",
            "Epoch 820/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.1142e-04 - val_loss: 0.0029\n",
            "Epoch 821/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.8715e-04 - val_loss: 0.0029\n",
            "Epoch 822/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.7961e-04 - val_loss: 0.0029\n",
            "Epoch 823/1000\n",
            "6/6 [==============================] - 1s 151ms/step - loss: 2.6550e-04 - val_loss: 0.0028\n",
            "Epoch 824/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.8551e-04 - val_loss: 0.0028\n",
            "Epoch 825/1000\n",
            "6/6 [==============================] - 1s 153ms/step - loss: 2.6876e-04 - val_loss: 0.0029\n",
            "Epoch 826/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.7232e-04 - val_loss: 0.0028\n",
            "Epoch 827/1000\n",
            "6/6 [==============================] - 1s 145ms/step - loss: 3.1953e-04 - val_loss: 0.0028\n",
            "Epoch 828/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.6913e-04 - val_loss: 0.0029\n",
            "Epoch 829/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 3.3936e-04 - val_loss: 0.0029\n",
            "Epoch 830/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1957e-04 - val_loss: 0.0029\n",
            "Epoch 831/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.8938e-04 - val_loss: 0.0029\n",
            "Epoch 832/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1592e-04 - val_loss: 0.0029\n",
            "Epoch 833/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1581e-04 - val_loss: 0.0029\n",
            "Epoch 834/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1387e-04 - val_loss: 0.0029\n",
            "Epoch 835/1000\n",
            "6/6 [==============================] - 1s 156ms/step - loss: 3.2517e-04 - val_loss: 0.0029\n",
            "Epoch 836/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.4324e-04 - val_loss: 0.0030\n",
            "Epoch 837/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.7412e-04 - val_loss: 0.0029\n",
            "Epoch 838/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.3255e-04 - val_loss: 0.0029\n",
            "Epoch 839/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.5488e-04 - val_loss: 0.0031\n",
            "Epoch 840/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 4.9655e-04 - val_loss: 0.0031\n",
            "Epoch 841/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 4.8203e-04 - val_loss: 0.0030\n",
            "Epoch 842/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 4.5510e-04 - val_loss: 0.0029\n",
            "Epoch 843/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 4.3295e-04 - val_loss: 0.0029\n",
            "Epoch 844/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.9331e-04 - val_loss: 0.0029\n",
            "Epoch 845/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.4379e-04 - val_loss: 0.0029\n",
            "Epoch 846/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1938e-04 - val_loss: 0.0029\n",
            "Epoch 847/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3979e-04 - val_loss: 0.0029\n",
            "Epoch 848/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.2844e-04 - val_loss: 0.0030\n",
            "Epoch 849/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.5758e-04 - val_loss: 0.0030\n",
            "Epoch 850/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.4749e-04 - val_loss: 0.0029\n",
            "Epoch 851/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1124e-04 - val_loss: 0.0029\n",
            "Epoch 852/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.5343e-04 - val_loss: 0.0029\n",
            "Epoch 853/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.2982e-04 - val_loss: 0.0030\n",
            "Epoch 854/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.3778e-04 - val_loss: 0.0029\n",
            "Epoch 855/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.4446e-04 - val_loss: 0.0030\n",
            "Epoch 856/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3084e-04 - val_loss: 0.0029\n",
            "Epoch 857/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.1530e-04 - val_loss: 0.0029\n",
            "Epoch 858/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.9077e-04 - val_loss: 0.0029\n",
            "Epoch 859/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.9309e-04 - val_loss: 0.0029\n",
            "Epoch 860/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 3.0967e-04 - val_loss: 0.0030\n",
            "Epoch 861/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1993e-04 - val_loss: 0.0030\n",
            "Epoch 862/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.3637e-04 - val_loss: 0.0029\n",
            "Epoch 863/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1041e-04 - val_loss: 0.0029\n",
            "Epoch 864/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.8865e-04 - val_loss: 0.0029\n",
            "Epoch 865/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.4134e-04 - val_loss: 0.0029\n",
            "Epoch 866/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.7432e-04 - val_loss: 0.0029\n",
            "Epoch 867/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.4326e-04 - val_loss: 0.0029\n",
            "Epoch 868/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3361e-04 - val_loss: 0.0029\n",
            "Epoch 869/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.3108e-04 - val_loss: 0.0029\n",
            "Epoch 870/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.4080e-04 - val_loss: 0.0029\n",
            "Epoch 871/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 3.7244e-04 - val_loss: 0.0030\n",
            "Epoch 872/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.4621e-04 - val_loss: 0.0030\n",
            "Epoch 873/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.3131e-04 - val_loss: 0.0029\n",
            "Epoch 874/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1190e-04 - val_loss: 0.0029\n",
            "Epoch 875/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.0891e-04 - val_loss: 0.0030\n",
            "Epoch 876/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0772e-04 - val_loss: 0.0029\n",
            "Epoch 877/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.2298e-04 - val_loss: 0.0030\n",
            "Epoch 878/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.4533e-04 - val_loss: 0.0029\n",
            "Epoch 879/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.5109e-04 - val_loss: 0.0030\n",
            "Epoch 880/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1140e-04 - val_loss: 0.0030\n",
            "Epoch 881/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.0449e-04 - val_loss: 0.0029\n",
            "Epoch 882/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0721e-04 - val_loss: 0.0029\n",
            "Epoch 883/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.0775e-04 - val_loss: 0.0029\n",
            "Epoch 884/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.8351e-04 - val_loss: 0.0029\n",
            "Epoch 885/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.9275e-04 - val_loss: 0.0029\n",
            "Epoch 886/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 2.9716e-04 - val_loss: 0.0029\n",
            "Epoch 887/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.7697e-04 - val_loss: 0.0029\n",
            "Epoch 888/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.7777e-04 - val_loss: 0.0029\n",
            "Epoch 889/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.5650e-04 - val_loss: 0.0029\n",
            "Epoch 890/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.6492e-04 - val_loss: 0.0029\n",
            "Epoch 891/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 2.7018e-04 - val_loss: 0.0029\n",
            "Epoch 892/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 2.6143e-04 - val_loss: 0.0029\n",
            "Epoch 893/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.4896e-04 - val_loss: 0.0029\n",
            "Epoch 894/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.9074e-04 - val_loss: 0.0029\n",
            "Epoch 895/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.7792e-04 - val_loss: 0.0029\n",
            "Epoch 896/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.5664e-04 - val_loss: 0.0029\n",
            "Epoch 897/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.9275e-04 - val_loss: 0.0030\n",
            "Epoch 898/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.1062e-04 - val_loss: 0.0029\n",
            "Epoch 899/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.8256e-04 - val_loss: 0.0029\n",
            "Epoch 900/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.8991e-04 - val_loss: 0.0029\n",
            "Epoch 901/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.9808e-04 - val_loss: 0.0029\n",
            "Epoch 902/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.8863e-04 - val_loss: 0.0030\n",
            "Epoch 903/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3843e-04 - val_loss: 0.0030\n",
            "Epoch 904/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 4.0163e-04 - val_loss: 0.0029\n",
            "Epoch 905/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.1861e-04 - val_loss: 0.0029\n",
            "Epoch 906/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0123e-04 - val_loss: 0.0029\n",
            "Epoch 907/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.9234e-04 - val_loss: 0.0029\n",
            "Epoch 908/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.8552e-04 - val_loss: 0.0029\n",
            "Epoch 909/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.6945e-04 - val_loss: 0.0029\n",
            "Epoch 910/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.9401e-04 - val_loss: 0.0029\n",
            "Epoch 911/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.7510e-04 - val_loss: 0.0029\n",
            "Epoch 912/1000\n",
            "6/6 [==============================] - 1s 149ms/step - loss: 2.8126e-04 - val_loss: 0.0029\n",
            "Epoch 913/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.7923e-04 - val_loss: 0.0029\n",
            "Epoch 914/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.1702e-04 - val_loss: 0.0030\n",
            "Epoch 915/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.8235e-04 - val_loss: 0.0029\n",
            "Epoch 916/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.8320e-04 - val_loss: 0.0029\n",
            "Epoch 917/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0506e-04 - val_loss: 0.0030\n",
            "Epoch 918/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.5941e-04 - val_loss: 0.0030\n",
            "Epoch 919/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 4.3033e-04 - val_loss: 0.0030\n",
            "Epoch 920/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.8030e-04 - val_loss: 0.0030\n",
            "Epoch 921/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.4660e-04 - val_loss: 0.0030\n",
            "Epoch 922/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.3771e-04 - val_loss: 0.0029\n",
            "Epoch 923/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.2131e-04 - val_loss: 0.0030\n",
            "Epoch 924/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.9263e-04 - val_loss: 0.0029\n",
            "Epoch 925/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 2.7624e-04 - val_loss: 0.0029\n",
            "Epoch 926/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.8641e-04 - val_loss: 0.0029\n",
            "Epoch 927/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.8040e-04 - val_loss: 0.0029\n",
            "Epoch 928/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 2.6529e-04 - val_loss: 0.0029\n",
            "Epoch 929/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.6216e-04 - val_loss: 0.0029\n",
            "Epoch 930/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 2.6553e-04 - val_loss: 0.0029\n",
            "Epoch 931/1000\n",
            "6/6 [==============================] - 1s 156ms/step - loss: 2.8139e-04 - val_loss: 0.0030\n",
            "Epoch 932/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.1392e-04 - val_loss: 0.0029\n",
            "Epoch 933/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.8390e-04 - val_loss: 0.0029\n",
            "Epoch 934/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.7964e-04 - val_loss: 0.0029\n",
            "Epoch 935/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.0348e-04 - val_loss: 0.0029\n",
            "Epoch 936/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.8948e-04 - val_loss: 0.0029\n",
            "Epoch 937/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.8726e-04 - val_loss: 0.0030\n",
            "Epoch 938/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.9023e-04 - val_loss: 0.0029\n",
            "Epoch 939/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.8098e-04 - val_loss: 0.0030\n",
            "Epoch 940/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 2.8400e-04 - val_loss: 0.0029\n",
            "Epoch 941/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.8845e-04 - val_loss: 0.0030\n",
            "Epoch 942/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.0801e-04 - val_loss: 0.0029\n",
            "Epoch 943/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.9353e-04 - val_loss: 0.0029\n",
            "Epoch 944/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.2729e-04 - val_loss: 0.0029\n",
            "Epoch 945/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.6598e-04 - val_loss: 0.0030\n",
            "Epoch 946/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.2843e-04 - val_loss: 0.0030\n",
            "Epoch 947/1000\n",
            "6/6 [==============================] - 1s 134ms/step - loss: 3.2459e-04 - val_loss: 0.0030\n",
            "Epoch 948/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.9488e-04 - val_loss: 0.0029\n",
            "Epoch 949/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.9176e-04 - val_loss: 0.0030\n",
            "Epoch 950/1000\n",
            "6/6 [==============================] - 1s 143ms/step - loss: 3.0017e-04 - val_loss: 0.0029\n",
            "Epoch 951/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 2.9281e-04 - val_loss: 0.0029\n",
            "Epoch 952/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.9257e-04 - val_loss: 0.0030\n",
            "Epoch 953/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 2.7742e-04 - val_loss: 0.0029\n",
            "Epoch 954/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.6067e-04 - val_loss: 0.0029\n",
            "Epoch 955/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.5353e-04 - val_loss: 0.0029\n",
            "Epoch 956/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.4689e-04 - val_loss: 0.0029\n",
            "Epoch 957/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 2.5373e-04 - val_loss: 0.0029\n",
            "Epoch 958/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.4552e-04 - val_loss: 0.0029\n",
            "Epoch 959/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.5586e-04 - val_loss: 0.0029\n",
            "Epoch 960/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.5767e-04 - val_loss: 0.0030\n",
            "Epoch 961/1000\n",
            "6/6 [==============================] - 1s 155ms/step - loss: 2.6860e-04 - val_loss: 0.0029\n",
            "Epoch 962/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.6104e-04 - val_loss: 0.0029\n",
            "Epoch 963/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 3.6083e-04 - val_loss: 0.0030\n",
            "Epoch 964/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.5538e-04 - val_loss: 0.0030\n",
            "Epoch 965/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1303e-04 - val_loss: 0.0030\n",
            "Epoch 966/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 3.3180e-04 - val_loss: 0.0030\n",
            "Epoch 967/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.2840e-04 - val_loss: 0.0030\n",
            "Epoch 968/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.8704e-04 - val_loss: 0.0029\n",
            "Epoch 969/1000\n",
            "6/6 [==============================] - 1s 152ms/step - loss: 2.7677e-04 - val_loss: 0.0030\n",
            "Epoch 970/1000\n",
            "6/6 [==============================] - 1s 135ms/step - loss: 2.6998e-04 - val_loss: 0.0030\n",
            "Epoch 971/1000\n",
            "6/6 [==============================] - 1s 155ms/step - loss: 2.9361e-04 - val_loss: 0.0030\n",
            "Epoch 972/1000\n",
            "6/6 [==============================] - 1s 144ms/step - loss: 2.9205e-04 - val_loss: 0.0029\n",
            "Epoch 973/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.8463e-04 - val_loss: 0.0029\n",
            "Epoch 974/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.1584e-04 - val_loss: 0.0030\n",
            "Epoch 975/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.2677e-04 - val_loss: 0.0030\n",
            "Epoch 976/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.1997e-04 - val_loss: 0.0030\n",
            "Epoch 977/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0448e-04 - val_loss: 0.0030\n",
            "Epoch 978/1000\n",
            "6/6 [==============================] - 1s 142ms/step - loss: 3.5407e-04 - val_loss: 0.0030\n",
            "Epoch 979/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.1162e-04 - val_loss: 0.0030\n",
            "Epoch 980/1000\n",
            "6/6 [==============================] - 1s 153ms/step - loss: 3.3779e-04 - val_loss: 0.0030\n",
            "Epoch 981/1000\n",
            "6/6 [==============================] - 1s 141ms/step - loss: 2.8757e-04 - val_loss: 0.0030\n",
            "Epoch 982/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.7501e-04 - val_loss: 0.0030\n",
            "Epoch 983/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.6946e-04 - val_loss: 0.0030\n",
            "Epoch 984/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 2.5328e-04 - val_loss: 0.0029\n",
            "Epoch 985/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.3791e-04 - val_loss: 0.0030\n",
            "Epoch 986/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.5435e-04 - val_loss: 0.0030\n",
            "Epoch 987/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.7711e-04 - val_loss: 0.0029\n",
            "Epoch 988/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.7336e-04 - val_loss: 0.0029\n",
            "Epoch 989/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 3.0801e-04 - val_loss: 0.0030\n",
            "Epoch 990/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.0998e-04 - val_loss: 0.0030\n",
            "Epoch 991/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 3.1118e-04 - val_loss: 0.0030\n",
            "Epoch 992/1000\n",
            "6/6 [==============================] - 1s 140ms/step - loss: 3.0605e-04 - val_loss: 0.0030\n",
            "Epoch 993/1000\n",
            "6/6 [==============================] - 1s 139ms/step - loss: 3.1107e-04 - val_loss: 0.0030\n",
            "Epoch 994/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 3.0295e-04 - val_loss: 0.0030\n",
            "Epoch 995/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.7773e-04 - val_loss: 0.0029\n",
            "Epoch 996/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.6582e-04 - val_loss: 0.0029\n",
            "Epoch 997/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.7358e-04 - val_loss: 0.0030\n",
            "Epoch 998/1000\n",
            "6/6 [==============================] - 1s 136ms/step - loss: 2.7220e-04 - val_loss: 0.0030\n",
            "Epoch 999/1000\n",
            "6/6 [==============================] - 1s 138ms/step - loss: 2.6932e-04 - val_loss: 0.0029\n",
            "Epoch 1000/1000\n",
            "6/6 [==============================] - 1s 137ms/step - loss: 2.5208e-04 - val_loss: 0.0029\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f57800b0510>"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mnFAAUPTAKjS"
      },
      "source": [
        "decoded = autoencoder.predict(data)\n",
        "mses = []\n",
        "for original, generated in zip(data, decoded):\n",
        "    mse = np.mean((original - generated) ** 2)\n",
        "    mses.append(mse)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qEvV0GSnAKjT",
        "outputId": "ecacf902-9fd1-4f26-b25e-51af1eb22599"
      },
      "source": [
        "threshold = np.quantile(mses, 0.999)\n",
        "outlier_idx = np.where(np.array(mses) >= threshold)[0]\n",
        "print(f'Number of outliers: {len(outlier_idx)}')"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of outliers: 8\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Er302RgWAKjT"
      },
      "source": [
        "decoded = (decoded * 255.0).astype('uint8')\n",
        "data = (data * 255.0).astype('uint8')"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qk3UMbp5AKjT"
      },
      "source": [
        "for i in outlier_idx:\n",
        "    image = np.hstack([data[i].reshape(28, 28),\n",
        "                       decoded[i].reshape(28, 28)])\n",
        "    cv2.imwrite(f'{i}.jpg', image)"
      ],
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zzVASk7sPqPm",
        "outputId": "d243090e-8c12-4910-9d8a-d0d07968f3b2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uRZu65niP2Hy",
        "outputId": "e0f52f81-027c-4835-f4f3-19ccf24d264b",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "source": [
        "%cp /content/yolov5/runs/train/yolov5s_results/weights/best.pt /content/gdrive/My\\ Drive"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "cp: cannot stat '/content/yolov5/runs/train/yolov5s_results/weights/best.pt': No such file or directory\n"
          ]
        }
      ]
    }
  ]
}