XOR_Gate.ipynb

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  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyM087fJtBcnic50/HTf4enl",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sumedhakoranga/Logic_Gates_Neural_Networks/blob/main/XOR_Gate.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Initialization"
      ],
      "metadata": {
        "id": "5tx7Zffh9cZ-"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_Sfaxr2XpWxO"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "import random"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Generating synthetic data"
      ],
      "metadata": {
        "id": "vpARcVZa9jjZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "p0 = [[0, 0, 0] for _ in range(random.randint(100, 150))]\n",
        "p1 = [[0,1,1] for _ in range(random.randint(100, 150))]\n",
        "p2 = [[1,0,1] for _ in range(random.randint(100, 150))]\n",
        "p3 = [[1,1,0] for _ in range(random.randint(100, 150))]\n",
        "X = np.array(p0+p1+p2+p3)\n",
        "np.random.shuffle(X)\n",
        "y = X[:, 2]\n",
        "X = X[:, :2]"
      ],
      "metadata": {
        "id": "XrANmJmhsIbv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oeECbboO0PiN",
        "outputId": "2abd0005-0f30-442e-91ce-1c9e0e01e723"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[0, 1],\n",
              "       [0, 1],\n",
              "       [1, 0],\n",
              "       ...,\n",
              "       [1, 0],\n",
              "       [1, 0],\n",
              "       [0, 0]])"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZcoeDzVV0fE9",
        "outputId": "14ca9213-bf2c-4398-8957-dd5112d88319"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "       0, 1, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0,\n",
              "       1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0,\n",
              "       1, 0, 0, 1, 0, 0, 1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1,\n",
              "       1, 1, 0, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1,\n",
              "       0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 0, 0,\n",
              "       0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 0,\n",
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              "       1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 1,\n",
              "       0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0,\n",
              "       0, 0, 1, 0, 0, 1, 0, 0, 0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0,\n",
              "       0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 0,\n",
              "       0, 1, 0, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1,\n",
              "       1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0,\n",
              "       0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1, 0, 1, 0, 1, 1, 1,\n",
              "       0, 0, 1, 1, 0])"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Training the model"
      ],
      "metadata": {
        "id": "LnToGcN59vDd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model = keras.Sequential([\n",
        "    keras.Input(shape=(2)),\n",
        "    keras.layers.Dense(2,activation=\"sigmoid\"),\n",
        "    keras.layers.Dense(1,activation=\"sigmoid\")]\n",
        ")"
      ],
      "metadata": {
        "id": "lRaxVYrLptcW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xhdYIiqNqzEh",
        "outputId": "8b2bf59b-1f41-4098-b058-14fada5c36bd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense_2 (Dense)             (None, 2)                 6         \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 1)                 3         \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 9\n",
            "Trainable params: 9\n",
            "Non-trainable params: 0\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(loss='binary_crossentropy',optimizer='adam',metrics='accuracy')"
      ],
      "metadata": {
        "id": "cSGVtgSmq2b7"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(X,y,epochs=1000,batch_size=32)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nfJ235KuroQD",
        "outputId": "f3fa321f-1488-42d3-b699-ebbf79f6d47e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/1000\n",
            "16/16 [==============================] - 1s 2ms/step - loss: 0.7910 - accuracy: 0.4579\n",
            "Epoch 2/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7832 - accuracy: 0.4579\n",
            "Epoch 3/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7759 - accuracy: 0.4579\n",
            "Epoch 4/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7685 - accuracy: 0.4579\n",
            "Epoch 5/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7620 - accuracy: 0.4579\n",
            "Epoch 6/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7556 - accuracy: 0.4579\n",
            "Epoch 7/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7496 - accuracy: 0.4579\n",
            "Epoch 8/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7440 - accuracy: 0.4579\n",
            "Epoch 9/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7387 - accuracy: 0.4579\n",
            "Epoch 10/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7338 - accuracy: 0.4579\n",
            "Epoch 11/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7295 - accuracy: 0.4579\n",
            "Epoch 12/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7250 - accuracy: 0.4579\n",
            "Epoch 13/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7214 - accuracy: 0.4579\n",
            "Epoch 14/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7177 - accuracy: 0.4579\n",
            "Epoch 15/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7143 - accuracy: 0.4579\n",
            "Epoch 16/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7113 - accuracy: 0.4579\n",
            "Epoch 17/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7087 - accuracy: 0.4579\n",
            "Epoch 18/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7061 - accuracy: 0.4579\n",
            "Epoch 19/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7038 - accuracy: 0.6575\n",
            "Epoch 20/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.7016 - accuracy: 0.7065\n",
            "Epoch 21/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6999 - accuracy: 0.7065\n",
            "Epoch 22/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6981 - accuracy: 0.7065\n",
            "Epoch 23/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6965 - accuracy: 0.7065\n",
            "Epoch 24/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6951 - accuracy: 0.7065\n",
            "Epoch 25/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6939 - accuracy: 0.7065\n",
            "Epoch 26/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6926 - accuracy: 0.5225\n",
            "Epoch 27/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6916 - accuracy: 0.4560\n",
            "Epoch 28/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6907 - accuracy: 0.4560\n",
            "Epoch 29/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6898 - accuracy: 0.4560\n",
            "Epoch 30/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6890 - accuracy: 0.4560\n",
            "Epoch 31/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6882 - accuracy: 0.4560\n",
            "Epoch 32/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6875 - accuracy: 0.4560\n",
            "Epoch 33/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6869 - accuracy: 0.4560\n",
            "Epoch 34/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6863 - accuracy: 0.4560\n",
            "Epoch 35/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6858 - accuracy: 0.4560\n",
            "Epoch 36/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6853 - accuracy: 0.4560\n",
            "Epoch 37/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6848 - accuracy: 0.4560\n",
            "Epoch 38/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6843 - accuracy: 0.4560\n",
            "Epoch 39/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6839 - accuracy: 0.4560\n",
            "Epoch 40/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6834 - accuracy: 0.4560\n",
            "Epoch 41/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6830 - accuracy: 0.4560\n",
            "Epoch 42/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6826 - accuracy: 0.4560\n",
            "Epoch 43/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6822 - accuracy: 0.4560\n",
            "Epoch 44/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6818 - accuracy: 0.5440\n",
            "Epoch 45/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6814 - accuracy: 0.7495\n",
            "Epoch 46/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6810 - accuracy: 0.7495\n",
            "Epoch 47/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6806 - accuracy: 0.7495\n",
            "Epoch 48/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6803 - accuracy: 0.6204\n",
            "Epoch 49/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6799 - accuracy: 0.5558\n",
            "Epoch 50/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6795 - accuracy: 0.5421\n",
            "Epoch 51/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6791 - accuracy: 0.5421\n",
            "Epoch 52/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6787 - accuracy: 0.5421\n",
            "Epoch 53/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6783 - accuracy: 0.5421\n",
            "Epoch 54/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6779 - accuracy: 0.5421\n",
            "Epoch 55/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6775 - accuracy: 0.5656\n",
            "Epoch 56/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6771 - accuracy: 0.5421\n",
            "Epoch 57/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6767 - accuracy: 0.5421\n",
            "Epoch 58/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6763 - accuracy: 0.5421\n",
            "Epoch 59/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6758 - accuracy: 0.5421\n",
            "Epoch 60/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6755 - accuracy: 0.6517\n",
            "Epoch 61/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6750 - accuracy: 0.7495\n",
            "Epoch 62/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6745 - accuracy: 0.7495\n",
            "Epoch 63/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6741 - accuracy: 0.7495\n",
            "Epoch 64/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6737 - accuracy: 0.7495\n",
            "Epoch 65/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6732 - accuracy: 0.7495\n",
            "Epoch 66/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6728 - accuracy: 0.7495\n",
            "Epoch 67/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6723 - accuracy: 0.7495\n",
            "Epoch 68/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6719 - accuracy: 0.7495\n",
            "Epoch 69/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6715 - accuracy: 0.7495\n",
            "Epoch 70/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6710 - accuracy: 0.7495\n",
            "Epoch 71/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6705 - accuracy: 0.7495\n",
            "Epoch 72/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6701 - accuracy: 0.7495\n",
            "Epoch 73/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6695 - accuracy: 0.7495\n",
            "Epoch 74/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6691 - accuracy: 0.7495\n",
            "Epoch 75/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6686 - accuracy: 0.7495\n",
            "Epoch 76/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6681 - accuracy: 0.7495\n",
            "Epoch 77/1000\n",
            "16/16 [==============================] - 0s 4ms/step - loss: 0.6676 - accuracy: 0.7495\n",
            "Epoch 78/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6671 - accuracy: 0.7495\n",
            "Epoch 79/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6666 - accuracy: 0.7495\n",
            "Epoch 80/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6662 - accuracy: 0.7495\n",
            "Epoch 81/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6656 - accuracy: 0.7495\n",
            "Epoch 82/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6651 - accuracy: 0.7495\n",
            "Epoch 83/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6646 - accuracy: 0.7495\n",
            "Epoch 84/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6641 - accuracy: 0.7495\n",
            "Epoch 85/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6635 - accuracy: 0.7495\n",
            "Epoch 86/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6630 - accuracy: 0.7495\n",
            "Epoch 87/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6626 - accuracy: 0.7495\n",
            "Epoch 88/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6622 - accuracy: 0.7495\n",
            "Epoch 89/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6614 - accuracy: 0.7495\n",
            "Epoch 90/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6608 - accuracy: 0.7495\n",
            "Epoch 91/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6603 - accuracy: 0.7495\n",
            "Epoch 92/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6597 - accuracy: 0.7495\n",
            "Epoch 93/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6592 - accuracy: 0.7495\n",
            "Epoch 94/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6585 - accuracy: 0.7495\n",
            "Epoch 95/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6580 - accuracy: 0.7495\n",
            "Epoch 96/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6574 - accuracy: 0.7495\n",
            "Epoch 97/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6568 - accuracy: 0.7495\n",
            "Epoch 98/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.6562 - accuracy: 0.7495\n",
            "Epoch 99/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6556 - accuracy: 0.7495\n",
            "Epoch 100/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6550 - accuracy: 0.7495\n",
            "Epoch 101/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6544 - accuracy: 0.7495\n",
            "Epoch 102/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6537 - accuracy: 0.7495\n",
            "Epoch 103/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.6531 - accuracy: 0.7495\n",
            "Epoch 104/1000\n",
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            "Epoch 660/1000\n",
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            "Epoch 662/1000\n",
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            "Epoch 664/1000\n",
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            "Epoch 665/1000\n",
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            "Epoch 666/1000\n",
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            "Epoch 670/1000\n",
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            "Epoch 671/1000\n",
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            "Epoch 672/1000\n",
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            "Epoch 674/1000\n",
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            "Epoch 675/1000\n",
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            "Epoch 676/1000\n",
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            "Epoch 678/1000\n",
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            "Epoch 679/1000\n",
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            "Epoch 680/1000\n",
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            "Epoch 681/1000\n",
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            "Epoch 682/1000\n",
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            "Epoch 683/1000\n",
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            "Epoch 684/1000\n",
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            "Epoch 685/1000\n",
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            "Epoch 686/1000\n",
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            "Epoch 687/1000\n",
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            "Epoch 688/1000\n",
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            "Epoch 689/1000\n",
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            "Epoch 690/1000\n",
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            "Epoch 691/1000\n",
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            "Epoch 692/1000\n",
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            "Epoch 693/1000\n",
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            "Epoch 694/1000\n",
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            "Epoch 695/1000\n",
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            "Epoch 696/1000\n",
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            "Epoch 697/1000\n",
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            "Epoch 698/1000\n",
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            "Epoch 699/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3955 - accuracy: 0.7495\n",
            "Epoch 700/1000\n",
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            "Epoch 701/1000\n",
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            "Epoch 702/1000\n",
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            "Epoch 703/1000\n",
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            "Epoch 704/1000\n",
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            "Epoch 705/1000\n",
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            "Epoch 706/1000\n",
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            "Epoch 707/1000\n",
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            "Epoch 708/1000\n",
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            "Epoch 709/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3949 - accuracy: 0.7495\n",
            "Epoch 710/1000\n",
            "16/16 [==============================] - 0s 4ms/step - loss: 0.3949 - accuracy: 0.7495\n",
            "Epoch 711/1000\n",
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            "Epoch 712/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3947 - accuracy: 0.7495\n",
            "Epoch 713/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3947 - accuracy: 0.7495\n",
            "Epoch 714/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3946 - accuracy: 0.7495\n",
            "Epoch 715/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3946 - accuracy: 0.7495\n",
            "Epoch 716/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3946 - accuracy: 0.7495\n",
            "Epoch 717/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3945 - accuracy: 0.7495\n",
            "Epoch 718/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3945 - accuracy: 0.7495\n",
            "Epoch 719/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3944 - accuracy: 0.7495\n",
            "Epoch 720/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3943 - accuracy: 0.7495\n",
            "Epoch 721/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3943 - accuracy: 0.7495\n",
            "Epoch 722/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3942 - accuracy: 0.7495\n",
            "Epoch 723/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3942 - accuracy: 0.7495\n",
            "Epoch 724/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3942 - accuracy: 0.7495\n",
            "Epoch 725/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3941 - accuracy: 0.7495\n",
            "Epoch 726/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3940 - accuracy: 0.7495\n",
            "Epoch 727/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3940 - accuracy: 0.7495\n",
            "Epoch 728/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3939 - accuracy: 0.7495\n",
            "Epoch 729/1000\n",
            "16/16 [==============================] - 0s 14ms/step - loss: 0.3939 - accuracy: 0.7495\n",
            "Epoch 730/1000\n",
            "16/16 [==============================] - 0s 4ms/step - loss: 0.3939 - accuracy: 0.7495\n",
            "Epoch 731/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3938 - accuracy: 0.7495\n",
            "Epoch 732/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3937 - accuracy: 0.7495\n",
            "Epoch 733/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3937 - accuracy: 0.7495\n",
            "Epoch 734/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3936 - accuracy: 0.7495\n",
            "Epoch 735/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3936 - accuracy: 0.7495\n",
            "Epoch 736/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3935 - accuracy: 0.7495\n",
            "Epoch 737/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3935 - accuracy: 0.7495\n",
            "Epoch 738/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3935 - accuracy: 0.7495\n",
            "Epoch 739/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3934 - accuracy: 0.7495\n",
            "Epoch 740/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3934 - accuracy: 0.7495\n",
            "Epoch 741/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3933 - accuracy: 0.7495\n",
            "Epoch 742/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3933 - accuracy: 0.7495\n",
            "Epoch 743/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3932 - accuracy: 0.7495\n",
            "Epoch 744/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3932 - accuracy: 0.7495\n",
            "Epoch 745/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3931 - accuracy: 0.7495\n",
            "Epoch 746/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3931 - accuracy: 0.7495\n",
            "Epoch 747/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3930 - accuracy: 0.7495\n",
            "Epoch 748/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3930 - accuracy: 0.7495\n",
            "Epoch 749/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3929 - accuracy: 0.7495\n",
            "Epoch 750/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3929 - accuracy: 0.7495\n",
            "Epoch 751/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3929 - accuracy: 0.7495\n",
            "Epoch 752/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3928 - accuracy: 0.7495\n",
            "Epoch 753/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3928 - accuracy: 0.7495\n",
            "Epoch 754/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3927 - accuracy: 0.7495\n",
            "Epoch 755/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3927 - accuracy: 0.7495\n",
            "Epoch 756/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3926 - accuracy: 0.7495\n",
            "Epoch 757/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3926 - accuracy: 0.7495\n",
            "Epoch 758/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3925 - accuracy: 0.7495\n",
            "Epoch 759/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3925 - accuracy: 0.7495\n",
            "Epoch 760/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3925 - accuracy: 0.7495\n",
            "Epoch 761/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3924 - accuracy: 0.7495\n",
            "Epoch 762/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3924 - accuracy: 0.7495\n",
            "Epoch 763/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3923 - accuracy: 0.7495\n",
            "Epoch 764/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3923 - accuracy: 0.7495\n",
            "Epoch 765/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3923 - accuracy: 0.7495\n",
            "Epoch 766/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3922 - accuracy: 0.7495\n",
            "Epoch 767/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3922 - accuracy: 0.7495\n",
            "Epoch 768/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3921 - accuracy: 0.7495\n",
            "Epoch 769/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3921 - accuracy: 0.7495\n",
            "Epoch 770/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3920 - accuracy: 0.7495\n",
            "Epoch 771/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3920 - accuracy: 0.7495\n",
            "Epoch 772/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3920 - accuracy: 0.7495\n",
            "Epoch 773/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3919 - accuracy: 0.7495\n",
            "Epoch 774/1000\n",
            "16/16 [==============================] - 0s 4ms/step - loss: 0.3919 - accuracy: 0.7495\n",
            "Epoch 775/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3918 - accuracy: 0.7495\n",
            "Epoch 776/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3918 - accuracy: 0.7495\n",
            "Epoch 777/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3917 - accuracy: 0.7495\n",
            "Epoch 778/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3917 - accuracy: 0.7495\n",
            "Epoch 779/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3917 - accuracy: 0.7495\n",
            "Epoch 780/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3917 - accuracy: 0.7495\n",
            "Epoch 781/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3916 - accuracy: 0.7495\n",
            "Epoch 782/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3916 - accuracy: 0.7495\n",
            "Epoch 783/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3915 - accuracy: 0.7495\n",
            "Epoch 784/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3915 - accuracy: 0.7495\n",
            "Epoch 785/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3914 - accuracy: 0.7495\n",
            "Epoch 786/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3914 - accuracy: 0.7495\n",
            "Epoch 787/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3914 - accuracy: 0.7495\n",
            "Epoch 788/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3913 - accuracy: 0.7495\n",
            "Epoch 789/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3913 - accuracy: 0.7495\n",
            "Epoch 790/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3913 - accuracy: 0.7495\n",
            "Epoch 791/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3913 - accuracy: 0.7495\n",
            "Epoch 792/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3912 - accuracy: 0.7495\n",
            "Epoch 793/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3911 - accuracy: 0.7495\n",
            "Epoch 794/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3911 - accuracy: 0.7495\n",
            "Epoch 795/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3911 - accuracy: 0.7495\n",
            "Epoch 796/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3911 - accuracy: 0.7495\n",
            "Epoch 797/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3910 - accuracy: 0.7495\n",
            "Epoch 798/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3909 - accuracy: 0.7495\n",
            "Epoch 799/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3909 - accuracy: 0.7495\n",
            "Epoch 800/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3910 - accuracy: 0.7495\n",
            "Epoch 801/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3908 - accuracy: 0.7495\n",
            "Epoch 802/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3908 - accuracy: 0.7495\n",
            "Epoch 803/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3908 - accuracy: 0.7495\n",
            "Epoch 804/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3908 - accuracy: 0.7495\n",
            "Epoch 805/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3907 - accuracy: 0.7495\n",
            "Epoch 806/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3907 - accuracy: 0.7495\n",
            "Epoch 807/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3906 - accuracy: 0.7495\n",
            "Epoch 808/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3906 - accuracy: 0.7495\n",
            "Epoch 809/1000\n",
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            "Epoch 810/1000\n",
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            "Epoch 811/1000\n",
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            "Epoch 813/1000\n",
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            "Epoch 815/1000\n",
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            "Epoch 816/1000\n",
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            "Epoch 817/1000\n",
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            "Epoch 818/1000\n",
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            "Epoch 819/1000\n",
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            "Epoch 820/1000\n",
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            "Epoch 821/1000\n",
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            "Epoch 822/1000\n",
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            "Epoch 824/1000\n",
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            "Epoch 825/1000\n",
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            "Epoch 826/1000\n",
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            "Epoch 827/1000\n",
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            "Epoch 828/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3899 - accuracy: 0.7495\n",
            "Epoch 829/1000\n",
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            "Epoch 830/1000\n",
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            "Epoch 831/1000\n",
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            "Epoch 832/1000\n",
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            "Epoch 833/1000\n",
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            "Epoch 834/1000\n",
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            "Epoch 835/1000\n",
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            "Epoch 836/1000\n",
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            "Epoch 837/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3896 - accuracy: 0.7495\n",
            "Epoch 838/1000\n",
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            "Epoch 839/1000\n",
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            "Epoch 840/1000\n",
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            "Epoch 841/1000\n",
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            "Epoch 842/1000\n",
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            "Epoch 843/1000\n",
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            "Epoch 844/1000\n",
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            "Epoch 845/1000\n",
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            "Epoch 846/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3893 - accuracy: 0.7495\n",
            "Epoch 847/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3893 - accuracy: 0.7495\n",
            "Epoch 848/1000\n",
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            "Epoch 849/1000\n",
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            "Epoch 850/1000\n",
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            "Epoch 851/1000\n",
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            "Epoch 852/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3892 - accuracy: 0.7495\n",
            "Epoch 853/1000\n",
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            "Epoch 854/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3891 - accuracy: 0.7495\n",
            "Epoch 855/1000\n",
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            "Epoch 856/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3890 - accuracy: 0.7495\n",
            "Epoch 857/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3891 - accuracy: 0.7495\n",
            "Epoch 858/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3890 - accuracy: 0.7495\n",
            "Epoch 859/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3890 - accuracy: 0.7495\n",
            "Epoch 860/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3889 - accuracy: 0.7495\n",
            "Epoch 861/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3889 - accuracy: 0.7495\n",
            "Epoch 862/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3889 - accuracy: 0.7495\n",
            "Epoch 863/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3889 - accuracy: 0.7495\n",
            "Epoch 864/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3888 - accuracy: 0.7495\n",
            "Epoch 865/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3888 - accuracy: 0.7495\n",
            "Epoch 866/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3887 - accuracy: 0.7495\n",
            "Epoch 867/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3888 - accuracy: 0.7495\n",
            "Epoch 868/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3887 - accuracy: 0.7495\n",
            "Epoch 869/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3887 - accuracy: 0.7495\n",
            "Epoch 870/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3887 - accuracy: 0.7495\n",
            "Epoch 871/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3887 - accuracy: 0.7495\n",
            "Epoch 872/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3886 - accuracy: 0.7495\n",
            "Epoch 873/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3885 - accuracy: 0.7495\n",
            "Epoch 874/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3885 - accuracy: 0.7495\n",
            "Epoch 875/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3885 - accuracy: 0.7495\n",
            "Epoch 876/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3885 - accuracy: 0.7495\n",
            "Epoch 877/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3885 - accuracy: 0.7495\n",
            "Epoch 878/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3884 - accuracy: 0.7495\n",
            "Epoch 879/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3884 - accuracy: 0.7495\n",
            "Epoch 880/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3885 - accuracy: 0.7495\n",
            "Epoch 881/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3883 - accuracy: 0.7495\n",
            "Epoch 882/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3884 - accuracy: 0.7495\n",
            "Epoch 883/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3883 - accuracy: 0.7495\n",
            "Epoch 884/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3883 - accuracy: 0.7495\n",
            "Epoch 885/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3882 - accuracy: 0.7495\n",
            "Epoch 886/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3883 - accuracy: 0.7495\n",
            "Epoch 887/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3882 - accuracy: 0.7495\n",
            "Epoch 888/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3882 - accuracy: 0.7495\n",
            "Epoch 889/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3882 - accuracy: 0.7495\n",
            "Epoch 890/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3881 - accuracy: 0.7495\n",
            "Epoch 891/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3881 - accuracy: 0.7495\n",
            "Epoch 892/1000\n",
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            "Epoch 893/1000\n",
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            "Epoch 894/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3881 - accuracy: 0.7495\n",
            "Epoch 895/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3880 - accuracy: 0.7495\n",
            "Epoch 896/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3880 - accuracy: 0.7495\n",
            "Epoch 897/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3879 - accuracy: 0.7495\n",
            "Epoch 898/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3880 - accuracy: 0.7495\n",
            "Epoch 899/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3879 - accuracy: 0.7495\n",
            "Epoch 900/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3879 - accuracy: 0.7495\n",
            "Epoch 901/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3879 - accuracy: 0.7495\n",
            "Epoch 902/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3878 - accuracy: 0.7495\n",
            "Epoch 903/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3878 - accuracy: 0.7495\n",
            "Epoch 904/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3878 - accuracy: 0.7495\n",
            "Epoch 905/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3877 - accuracy: 0.7495\n",
            "Epoch 906/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3877 - accuracy: 0.7495\n",
            "Epoch 907/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3877 - accuracy: 0.7495\n",
            "Epoch 908/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3877 - accuracy: 0.7495\n",
            "Epoch 909/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3877 - accuracy: 0.7495\n",
            "Epoch 910/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3876 - accuracy: 0.7495\n",
            "Epoch 911/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3876 - accuracy: 0.7495\n",
            "Epoch 912/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3876 - accuracy: 0.7495\n",
            "Epoch 913/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3876 - accuracy: 0.7495\n",
            "Epoch 914/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3875 - accuracy: 0.7495\n",
            "Epoch 915/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3875 - accuracy: 0.7495\n",
            "Epoch 916/1000\n",
            "16/16 [==============================] - 0s 14ms/step - loss: 0.3875 - accuracy: 0.7495\n",
            "Epoch 917/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3875 - accuracy: 0.7495\n",
            "Epoch 918/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3875 - accuracy: 0.7495\n",
            "Epoch 919/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3874 - accuracy: 0.7495\n",
            "Epoch 920/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3874 - accuracy: 0.7495\n",
            "Epoch 921/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3874 - accuracy: 0.7495\n",
            "Epoch 922/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3874 - accuracy: 0.7495\n",
            "Epoch 923/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3873 - accuracy: 0.7495\n",
            "Epoch 924/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3874 - accuracy: 0.7495\n",
            "Epoch 925/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3873 - accuracy: 0.7495\n",
            "Epoch 926/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3872 - accuracy: 0.7495\n",
            "Epoch 927/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3872 - accuracy: 0.7495\n",
            "Epoch 928/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3872 - accuracy: 0.7495\n",
            "Epoch 929/1000\n",
            "16/16 [==============================] - 0s 13ms/step - loss: 0.3872 - accuracy: 0.7495\n",
            "Epoch 930/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3872 - accuracy: 0.7495\n",
            "Epoch 931/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3872 - accuracy: 0.7495\n",
            "Epoch 932/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3871 - accuracy: 0.7495\n",
            "Epoch 933/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3871 - accuracy: 0.7495\n",
            "Epoch 934/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3871 - accuracy: 0.7495\n",
            "Epoch 935/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3870 - accuracy: 0.7495\n",
            "Epoch 936/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3871 - accuracy: 0.7495\n",
            "Epoch 937/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3870 - accuracy: 0.7495\n",
            "Epoch 938/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3870 - accuracy: 0.7495\n",
            "Epoch 939/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3870 - accuracy: 0.7495\n",
            "Epoch 940/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3870 - accuracy: 0.7495\n",
            "Epoch 941/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3869 - accuracy: 0.7495\n",
            "Epoch 942/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3869 - accuracy: 0.7495\n",
            "Epoch 943/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3870 - accuracy: 0.7495\n",
            "Epoch 944/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3869 - accuracy: 0.7495\n",
            "Epoch 945/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3868 - accuracy: 0.7495\n",
            "Epoch 946/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3868 - accuracy: 0.7495\n",
            "Epoch 947/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3868 - accuracy: 0.7495\n",
            "Epoch 948/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3868 - accuracy: 0.7495\n",
            "Epoch 949/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3868 - accuracy: 0.7495\n",
            "Epoch 950/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3867 - accuracy: 0.7495\n",
            "Epoch 951/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3867 - accuracy: 0.7495\n",
            "Epoch 952/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3867 - accuracy: 0.7495\n",
            "Epoch 953/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3867 - accuracy: 0.7495\n",
            "Epoch 954/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3867 - accuracy: 0.7495\n",
            "Epoch 955/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3866 - accuracy: 0.7495\n",
            "Epoch 956/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3866 - accuracy: 0.7495\n",
            "Epoch 957/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3866 - accuracy: 0.7495\n",
            "Epoch 958/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3866 - accuracy: 0.7495\n",
            "Epoch 959/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3866 - accuracy: 0.7495\n",
            "Epoch 960/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3865 - accuracy: 0.7495\n",
            "Epoch 961/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3865 - accuracy: 0.7495\n",
            "Epoch 962/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3865 - accuracy: 0.7495\n",
            "Epoch 963/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3865 - accuracy: 0.7495\n",
            "Epoch 964/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3865 - accuracy: 0.7495\n",
            "Epoch 965/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3864 - accuracy: 0.7495\n",
            "Epoch 966/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3864 - accuracy: 0.7495\n",
            "Epoch 967/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3864 - accuracy: 0.7495\n",
            "Epoch 968/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3864 - accuracy: 0.7495\n",
            "Epoch 969/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3864 - accuracy: 0.7495\n",
            "Epoch 970/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3864 - accuracy: 0.7495\n",
            "Epoch 971/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3863 - accuracy: 0.7495\n",
            "Epoch 972/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3863 - accuracy: 0.7495\n",
            "Epoch 973/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3863 - accuracy: 0.7495\n",
            "Epoch 974/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3862 - accuracy: 0.7495\n",
            "Epoch 975/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3863 - accuracy: 0.7495\n",
            "Epoch 976/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3862 - accuracy: 0.7495\n",
            "Epoch 977/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3862 - accuracy: 0.7495\n",
            "Epoch 978/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3862 - accuracy: 0.7495\n",
            "Epoch 979/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3863 - accuracy: 0.7495\n",
            "Epoch 980/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 981/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 982/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 983/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 984/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 985/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 986/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3861 - accuracy: 0.7495\n",
            "Epoch 987/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3860 - accuracy: 0.7495\n",
            "Epoch 988/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3860 - accuracy: 0.7495\n",
            "Epoch 989/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3860 - accuracy: 0.7495\n",
            "Epoch 990/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3860 - accuracy: 0.7495\n",
            "Epoch 991/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 992/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 993/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 994/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 995/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 996/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 997/1000\n",
            "16/16 [==============================] - 0s 3ms/step - loss: 0.3859 - accuracy: 0.7495\n",
            "Epoch 998/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3858 - accuracy: 0.7495\n",
            "Epoch 999/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3858 - accuracy: 0.7495\n",
            "Epoch 1000/1000\n",
            "16/16 [==============================] - 0s 2ms/step - loss: 0.3858 - accuracy: 0.7495\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f2298626eb0>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.get_weights()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lwsthYoGBnrF",
        "outputId": "cf290c60-799f-440a-a729-a8428fd68b48"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[array([[-8.640526,  9.936205],\n",
              "        [12.19848 , 11.800795]], dtype=float32),\n",
              " array([ 4.454284, -3.951037], dtype=float32),\n",
              " array([[-3.8283694],\n",
              "        [ 3.9820979]], dtype=float32),\n",
              " array([-0.31022668], dtype=float32)]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.get_weight_paths()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3XBbJErkBrZ9",
        "outputId": "5303ac86-96cb-49cc-f894-8b15aa7b5550"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'dense_2.kernel': <tf.Variable 'dense_2/kernel:0' shape=(2, 2) dtype=float32, numpy=\n",
              " array([[-8.640526,  9.936205],\n",
              "        [12.19848 , 11.800795]], dtype=float32)>,\n",
              " 'dense_2.bias': <tf.Variable 'dense_2/bias:0' shape=(2,) dtype=float32, numpy=array([ 4.454284, -3.951037], dtype=float32)>,\n",
              " 'dense_3.kernel': <tf.Variable 'dense_3/kernel:0' shape=(2, 1) dtype=float32, numpy=\n",
              " array([[-3.8283694],\n",
              "        [ 3.9820979]], dtype=float32)>,\n",
              " 'dense_3.bias': <tf.Variable 'dense_3/bias:0' shape=(1,) dtype=float32, numpy=array([-0.31022668], dtype=float32)>}"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    }
  ]
}