XNOR_Gate.ipynb

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      "authorship_tag": "ABX9TyOh/NdpTW9pUjyHn7tAbFss",
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      "cell_type": "markdown",
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        "<a href=\"https://colab.research.google.com/github/sumedhakoranga/Logic_Gates_Neural_Networks/blob/main/XNOR_Gate.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "# Initialization"
      ],
      "metadata": {
        "id": "wkYyccZf_MF0"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "HZiyAt11493k"
      },
      "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": {
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    {
      "cell_type": "code",
      "source": [
        "p0 = [[0, 0,1] for _ in range(random.randint(100, 150))]\n",
        "p1 = [[0,1,0] for _ in range(random.randint(100, 150))]\n",
        "p2 = [[1,0,0] for _ in range(random.randint(100, 150))]\n",
        "p3 = [[1,1,1] for _ in range(random.randint(100, 150))]\n",
        "X = np.array(p0+p1+p2+p3)\n",
        "np.random.shuffle(X)\n",
        "y = X[:, 1]\n",
        "X = X[:, :2]"
      ],
      "metadata": {
        "id": "sF1oAwl05Em9"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
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      "source": [
        "X"
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      "execution_count": 8,
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          "metadata": {},
          "execution_count": 8
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y"
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      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wYggZXHQ5UZp",
        "outputId": "3b983888-c6f0-4188-9c1a-63a56fdc495b"
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    },
    {
      "cell_type": "markdown",
      "source": [
        "# Training the model"
      ],
      "metadata": {
        "id": "DrptVCWV_bMR"
      }
    },
    {
      "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": "KxsN6At85Uyg"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "llNuyQXE5aYD",
        "outputId": "5093c6fe-a856-445f-b131-0cac97cc6452"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential_1\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense_1 (Dense)             (None, 2)                 6         \n",
            "                                                                 \n",
            " dense_2 (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": "bYIV3fZC5c8i"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.fit(X,y,epochs=1000,batch_size=32)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DsK1hQD45gek",
        "outputId": "40194265-e0bc-4295-8421-8ec37989916d"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/1000\n",
            "15/15 [==============================] - 1s 3ms/step - loss: 0.6773 - accuracy: 0.6842\n",
            "Epoch 2/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6762 - accuracy: 0.7200\n",
            "Epoch 3/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6751 - accuracy: 0.7200\n",
            "Epoch 4/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6740 - accuracy: 0.7200\n",
            "Epoch 5/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6729 - accuracy: 0.7200\n",
            "Epoch 6/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6717 - accuracy: 0.7200\n",
            "Epoch 7/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6706 - accuracy: 0.7200\n",
            "Epoch 8/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6695 - accuracy: 0.7200\n",
            "Epoch 9/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6682 - accuracy: 0.7200\n",
            "Epoch 10/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.6669 - accuracy: 0.7200\n",
            "Epoch 11/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6656 - accuracy: 0.7200\n",
            "Epoch 12/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6643 - accuracy: 0.7200\n",
            "Epoch 13/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6629 - accuracy: 0.7200\n",
            "Epoch 14/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6615 - accuracy: 0.7200\n",
            "Epoch 15/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6600 - accuracy: 0.7200\n",
            "Epoch 16/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6585 - accuracy: 0.7200\n",
            "Epoch 17/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6569 - accuracy: 0.7200\n",
            "Epoch 18/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6552 - accuracy: 0.7200\n",
            "Epoch 19/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6536 - accuracy: 0.7200\n",
            "Epoch 20/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6518 - accuracy: 0.7200\n",
            "Epoch 21/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6500 - accuracy: 0.7200\n",
            "Epoch 22/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.6482 - accuracy: 0.7200\n",
            "Epoch 23/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6463 - accuracy: 0.7200\n",
            "Epoch 24/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6444 - accuracy: 0.7200\n",
            "Epoch 25/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6424 - accuracy: 0.8547\n",
            "Epoch 26/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.6403 - accuracy: 1.0000\n",
            "Epoch 27/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6382 - accuracy: 1.0000\n",
            "Epoch 28/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6360 - accuracy: 1.0000\n",
            "Epoch 29/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6338 - accuracy: 1.0000\n",
            "Epoch 30/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6315 - accuracy: 1.0000\n",
            "Epoch 31/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6292 - accuracy: 1.0000\n",
            "Epoch 32/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6268 - accuracy: 1.0000\n",
            "Epoch 33/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6243 - accuracy: 1.0000\n",
            "Epoch 34/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.6218 - accuracy: 1.0000\n",
            "Epoch 35/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6192 - accuracy: 1.0000\n",
            "Epoch 36/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6166 - accuracy: 1.0000\n",
            "Epoch 37/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6139 - accuracy: 1.0000\n",
            "Epoch 38/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6112 - accuracy: 1.0000\n",
            "Epoch 39/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6084 - accuracy: 1.0000\n",
            "Epoch 40/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6056 - accuracy: 1.0000\n",
            "Epoch 41/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.6027 - accuracy: 1.0000\n",
            "Epoch 42/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5997 - accuracy: 1.0000\n",
            "Epoch 43/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5967 - accuracy: 1.0000\n",
            "Epoch 44/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.5937 - accuracy: 1.0000\n",
            "Epoch 45/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5905 - accuracy: 1.0000\n",
            "Epoch 46/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5874 - accuracy: 1.0000\n",
            "Epoch 47/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5842 - accuracy: 1.0000\n",
            "Epoch 48/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5809 - accuracy: 1.0000\n",
            "Epoch 49/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5777 - accuracy: 1.0000\n",
            "Epoch 50/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5743 - accuracy: 1.0000\n",
            "Epoch 51/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5709 - accuracy: 1.0000\n",
            "Epoch 52/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5675 - accuracy: 1.0000\n",
            "Epoch 53/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.5640 - accuracy: 1.0000\n",
            "Epoch 54/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5605 - accuracy: 1.0000\n",
            "Epoch 55/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5569 - accuracy: 1.0000\n",
            "Epoch 56/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5533 - accuracy: 1.0000\n",
            "Epoch 57/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5496 - accuracy: 1.0000\n",
            "Epoch 58/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5460 - accuracy: 1.0000\n",
            "Epoch 59/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.5423 - accuracy: 1.0000\n",
            "Epoch 60/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5385 - accuracy: 1.0000\n",
            "Epoch 61/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5347 - accuracy: 1.0000\n",
            "Epoch 62/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5309 - accuracy: 1.0000\n",
            "Epoch 63/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5270 - accuracy: 1.0000\n",
            "Epoch 64/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.5231 - accuracy: 1.0000\n",
            "Epoch 65/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5193 - accuracy: 1.0000\n",
            "Epoch 66/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5153 - accuracy: 1.0000\n",
            "Epoch 67/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5114 - accuracy: 1.0000\n",
            "Epoch 68/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5074 - accuracy: 1.0000\n",
            "Epoch 69/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.5034 - accuracy: 1.0000\n",
            "Epoch 70/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.4994 - accuracy: 1.0000\n",
            "Epoch 71/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4954 - accuracy: 1.0000\n",
            "Epoch 72/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4914 - accuracy: 1.0000\n",
            "Epoch 73/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4874 - accuracy: 1.0000\n",
            "Epoch 74/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4833 - accuracy: 1.0000\n",
            "Epoch 75/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.4792 - accuracy: 1.0000\n",
            "Epoch 76/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4752 - accuracy: 1.0000\n",
            "Epoch 77/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4711 - accuracy: 1.0000\n",
            "Epoch 78/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4669 - accuracy: 1.0000\n",
            "Epoch 79/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4629 - accuracy: 1.0000\n",
            "Epoch 80/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4587 - accuracy: 1.0000\n",
            "Epoch 81/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4546 - accuracy: 1.0000\n",
            "Epoch 82/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4506 - accuracy: 1.0000\n",
            "Epoch 83/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4464 - accuracy: 1.0000\n",
            "Epoch 84/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4423 - accuracy: 1.0000\n",
            "Epoch 85/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4382 - accuracy: 1.0000\n",
            "Epoch 86/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.4341 - accuracy: 1.0000\n",
            "Epoch 87/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4301 - accuracy: 1.0000\n",
            "Epoch 88/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4260 - accuracy: 1.0000\n",
            "Epoch 89/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4219 - accuracy: 1.0000\n",
            "Epoch 90/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4179 - accuracy: 1.0000\n",
            "Epoch 91/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4138 - accuracy: 1.0000\n",
            "Epoch 92/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4098 - accuracy: 1.0000\n",
            "Epoch 93/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4058 - accuracy: 1.0000\n",
            "Epoch 94/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.4019 - accuracy: 1.0000\n",
            "Epoch 95/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3979 - accuracy: 1.0000\n",
            "Epoch 96/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.3939 - accuracy: 1.0000\n",
            "Epoch 97/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3900 - accuracy: 1.0000\n",
            "Epoch 98/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3860 - accuracy: 1.0000\n",
            "Epoch 99/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3821 - accuracy: 1.0000\n",
            "Epoch 100/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3783 - accuracy: 1.0000\n",
            "Epoch 101/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3744 - accuracy: 1.0000\n",
            "Epoch 102/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.3706 - accuracy: 1.0000\n",
            "Epoch 103/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3668 - accuracy: 1.0000\n",
            "Epoch 104/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.3630 - accuracy: 1.0000\n",
            "Epoch 105/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3592 - accuracy: 1.0000\n",
            "Epoch 106/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3555 - accuracy: 1.0000\n",
            "Epoch 107/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3518 - accuracy: 1.0000\n",
            "Epoch 108/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3481 - accuracy: 1.0000\n",
            "Epoch 109/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3445 - accuracy: 1.0000\n",
            "Epoch 110/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3408 - accuracy: 1.0000\n",
            "Epoch 111/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3373 - accuracy: 1.0000\n",
            "Epoch 112/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3337 - accuracy: 1.0000\n",
            "Epoch 113/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3301 - accuracy: 1.0000\n",
            "Epoch 114/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3266 - accuracy: 1.0000\n",
            "Epoch 115/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3231 - accuracy: 1.0000\n",
            "Epoch 116/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3197 - accuracy: 1.0000\n",
            "Epoch 117/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3163 - accuracy: 1.0000\n",
            "Epoch 118/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3129 - accuracy: 1.0000\n",
            "Epoch 119/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3095 - accuracy: 1.0000\n",
            "Epoch 120/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3062 - accuracy: 1.0000\n",
            "Epoch 121/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.3030 - accuracy: 1.0000\n",
            "Epoch 122/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.2997 - accuracy: 1.0000\n",
            "Epoch 123/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.2964 - accuracy: 1.0000\n",
            "Epoch 124/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.2932 - accuracy: 1.0000\n",
            "Epoch 125/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2900 - accuracy: 1.0000\n",
            "Epoch 126/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2869 - accuracy: 1.0000\n",
            "Epoch 127/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2838 - accuracy: 1.0000\n",
            "Epoch 128/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2807 - accuracy: 1.0000\n",
            "Epoch 129/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2777 - accuracy: 1.0000\n",
            "Epoch 130/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2746 - accuracy: 1.0000\n",
            "Epoch 131/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2717 - accuracy: 1.0000\n",
            "Epoch 132/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2687 - accuracy: 1.0000\n",
            "Epoch 133/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2658 - accuracy: 1.0000\n",
            "Epoch 134/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2629 - accuracy: 1.0000\n",
            "Epoch 135/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2600 - accuracy: 1.0000\n",
            "Epoch 136/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2572 - accuracy: 1.0000\n",
            "Epoch 137/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.2544 - accuracy: 1.0000\n",
            "Epoch 138/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2516 - accuracy: 1.0000\n",
            "Epoch 139/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2489 - accuracy: 1.0000\n",
            "Epoch 140/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 0.2461 - accuracy: 1.0000\n",
            "Epoch 141/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2435 - accuracy: 1.0000\n",
            "Epoch 142/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2408 - accuracy: 1.0000\n",
            "Epoch 143/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2382 - accuracy: 1.0000\n",
            "Epoch 144/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2356 - accuracy: 1.0000\n",
            "Epoch 145/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2330 - accuracy: 1.0000\n",
            "Epoch 146/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2305 - accuracy: 1.0000\n",
            "Epoch 147/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2280 - accuracy: 1.0000\n",
            "Epoch 148/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2255 - accuracy: 1.0000\n",
            "Epoch 149/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2230 - accuracy: 1.0000\n",
            "Epoch 150/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2206 - accuracy: 1.0000\n",
            "Epoch 151/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.2182 - accuracy: 1.0000\n",
            "Epoch 152/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2159 - accuracy: 1.0000\n",
            "Epoch 153/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2135 - accuracy: 1.0000\n",
            "Epoch 154/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 0.2112 - accuracy: 1.0000\n",
            "Epoch 155/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2089 - accuracy: 1.0000\n",
            "Epoch 156/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2067 - accuracy: 1.0000\n",
            "Epoch 157/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2044 - accuracy: 1.0000\n",
            "Epoch 158/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2022 - accuracy: 1.0000\n",
            "Epoch 159/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.2001 - accuracy: 1.0000\n",
            "Epoch 160/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 0.1979 - accuracy: 1.0000\n",
            "Epoch 161/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.1958 - accuracy: 1.0000\n",
            "Epoch 162/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.1937 - accuracy: 1.0000\n",
            "Epoch 163/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 0.1916 - accuracy: 1.0000\n",
            "Epoch 164/1000\n",
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            "Epoch 884/1000\n",
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            "15/15 [==============================] - 0s 3ms/step - loss: 8.6509e-04 - accuracy: 1.0000\n",
            "Epoch 886/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.5953e-04 - accuracy: 1.0000\n",
            "Epoch 887/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 8.5400e-04 - accuracy: 1.0000\n",
            "Epoch 888/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.4856e-04 - accuracy: 1.0000\n",
            "Epoch 889/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 8.4307e-04 - accuracy: 1.0000\n",
            "Epoch 890/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 8.3765e-04 - accuracy: 1.0000\n",
            "Epoch 891/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.3227e-04 - accuracy: 1.0000\n",
            "Epoch 892/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.2692e-04 - accuracy: 1.0000\n",
            "Epoch 893/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 8.2161e-04 - accuracy: 1.0000\n",
            "Epoch 894/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.1633e-04 - accuracy: 1.0000\n",
            "Epoch 895/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.1109e-04 - accuracy: 1.0000\n",
            "Epoch 896/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.0589e-04 - accuracy: 1.0000\n",
            "Epoch 897/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 8.0070e-04 - accuracy: 1.0000\n",
            "Epoch 898/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.9556e-04 - accuracy: 1.0000\n",
            "Epoch 899/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.9047e-04 - accuracy: 1.0000\n",
            "Epoch 900/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.8539e-04 - accuracy: 1.0000\n",
            "Epoch 901/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.8034e-04 - accuracy: 1.0000\n",
            "Epoch 902/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.7533e-04 - accuracy: 1.0000\n",
            "Epoch 903/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.7037e-04 - accuracy: 1.0000\n",
            "Epoch 904/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.6543e-04 - accuracy: 1.0000\n",
            "Epoch 905/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.6051e-04 - accuracy: 1.0000\n",
            "Epoch 906/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.5563e-04 - accuracy: 1.0000\n",
            "Epoch 907/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.5077e-04 - accuracy: 1.0000\n",
            "Epoch 908/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 7.4597e-04 - accuracy: 1.0000\n",
            "Epoch 909/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.4121e-04 - accuracy: 1.0000\n",
            "Epoch 910/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.3642e-04 - accuracy: 1.0000\n",
            "Epoch 911/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.3170e-04 - accuracy: 1.0000\n",
            "Epoch 912/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.2700e-04 - accuracy: 1.0000\n",
            "Epoch 913/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.2236e-04 - accuracy: 1.0000\n",
            "Epoch 914/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.1770e-04 - accuracy: 1.0000\n",
            "Epoch 915/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.1311e-04 - accuracy: 1.0000\n",
            "Epoch 916/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.0854e-04 - accuracy: 1.0000\n",
            "Epoch 917/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 7.0399e-04 - accuracy: 1.0000\n",
            "Epoch 918/1000\n",
            "15/15 [==============================] - 0s 5ms/step - loss: 6.9948e-04 - accuracy: 1.0000\n",
            "Epoch 919/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.9498e-04 - accuracy: 1.0000\n",
            "Epoch 920/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 6.9054e-04 - accuracy: 1.0000\n",
            "Epoch 921/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 6.8611e-04 - accuracy: 1.0000\n",
            "Epoch 922/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 6.8171e-04 - accuracy: 1.0000\n",
            "Epoch 923/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.7735e-04 - accuracy: 1.0000\n",
            "Epoch 924/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.7301e-04 - accuracy: 1.0000\n",
            "Epoch 925/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 6.6870e-04 - accuracy: 1.0000\n",
            "Epoch 926/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.6442e-04 - accuracy: 1.0000\n",
            "Epoch 927/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.6017e-04 - accuracy: 1.0000\n",
            "Epoch 928/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 6.5593e-04 - accuracy: 1.0000\n",
            "Epoch 929/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.5174e-04 - accuracy: 1.0000\n",
            "Epoch 930/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.4756e-04 - accuracy: 1.0000\n",
            "Epoch 931/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.4340e-04 - accuracy: 1.0000\n",
            "Epoch 932/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 6.3933e-04 - accuracy: 1.0000\n",
            "Epoch 933/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.3519e-04 - accuracy: 1.0000\n",
            "Epoch 934/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.3113e-04 - accuracy: 1.0000\n",
            "Epoch 935/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.2711e-04 - accuracy: 1.0000\n",
            "Epoch 936/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.2307e-04 - accuracy: 1.0000\n",
            "Epoch 937/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.1908e-04 - accuracy: 1.0000\n",
            "Epoch 938/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 6.1512e-04 - accuracy: 1.0000\n",
            "Epoch 939/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.1119e-04 - accuracy: 1.0000\n",
            "Epoch 940/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 6.0728e-04 - accuracy: 1.0000\n",
            "Epoch 941/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 6.0339e-04 - accuracy: 1.0000\n",
            "Epoch 942/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.9952e-04 - accuracy: 1.0000\n",
            "Epoch 943/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.9569e-04 - accuracy: 1.0000\n",
            "Epoch 944/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.9188e-04 - accuracy: 1.0000\n",
            "Epoch 945/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.8810e-04 - accuracy: 1.0000\n",
            "Epoch 946/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.8434e-04 - accuracy: 1.0000\n",
            "Epoch 947/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.8060e-04 - accuracy: 1.0000\n",
            "Epoch 948/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.7689e-04 - accuracy: 1.0000\n",
            "Epoch 949/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.7324e-04 - accuracy: 1.0000\n",
            "Epoch 950/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.6952e-04 - accuracy: 1.0000\n",
            "Epoch 951/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.6591e-04 - accuracy: 1.0000\n",
            "Epoch 952/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.6227e-04 - accuracy: 1.0000\n",
            "Epoch 953/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.5868e-04 - accuracy: 1.0000\n",
            "Epoch 954/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.5510e-04 - accuracy: 1.0000\n",
            "Epoch 955/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.5157e-04 - accuracy: 1.0000\n",
            "Epoch 956/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.4804e-04 - accuracy: 1.0000\n",
            "Epoch 957/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.4455e-04 - accuracy: 1.0000\n",
            "Epoch 958/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.4105e-04 - accuracy: 1.0000\n",
            "Epoch 959/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.3759e-04 - accuracy: 1.0000\n",
            "Epoch 960/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.3417e-04 - accuracy: 1.0000\n",
            "Epoch 961/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.3074e-04 - accuracy: 1.0000\n",
            "Epoch 962/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.2735e-04 - accuracy: 1.0000\n",
            "Epoch 963/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.2398e-04 - accuracy: 1.0000\n",
            "Epoch 964/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.2067e-04 - accuracy: 1.0000\n",
            "Epoch 965/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.1732e-04 - accuracy: 1.0000\n",
            "Epoch 966/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.1400e-04 - accuracy: 1.0000\n",
            "Epoch 967/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.1073e-04 - accuracy: 1.0000\n",
            "Epoch 968/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.0747e-04 - accuracy: 1.0000\n",
            "Epoch 969/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 5.0422e-04 - accuracy: 1.0000\n",
            "Epoch 970/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 5.0101e-04 - accuracy: 1.0000\n",
            "Epoch 971/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 4.9781e-04 - accuracy: 1.0000\n",
            "Epoch 972/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 4.9463e-04 - accuracy: 1.0000\n",
            "Epoch 973/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 4.9147e-04 - accuracy: 1.0000\n",
            "Epoch 974/1000\n",
            "15/15 [==============================] - 0s 2ms/step - loss: 4.8834e-04 - accuracy: 1.0000\n",
            "Epoch 975/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.8522e-04 - accuracy: 1.0000\n",
            "Epoch 976/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.8212e-04 - accuracy: 1.0000\n",
            "Epoch 977/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.7904e-04 - accuracy: 1.0000\n",
            "Epoch 978/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.7599e-04 - accuracy: 1.0000\n",
            "Epoch 979/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.7295e-04 - accuracy: 1.0000\n",
            "Epoch 980/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.6993e-04 - accuracy: 1.0000\n",
            "Epoch 981/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.6693e-04 - accuracy: 1.0000\n",
            "Epoch 982/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.6395e-04 - accuracy: 1.0000\n",
            "Epoch 983/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.6099e-04 - accuracy: 1.0000\n",
            "Epoch 984/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.5805e-04 - accuracy: 1.0000\n",
            "Epoch 985/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.5513e-04 - accuracy: 1.0000\n",
            "Epoch 986/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.5223e-04 - accuracy: 1.0000\n",
            "Epoch 987/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.4936e-04 - accuracy: 1.0000\n",
            "Epoch 988/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.4648e-04 - accuracy: 1.0000\n",
            "Epoch 989/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.4363e-04 - accuracy: 1.0000\n",
            "Epoch 990/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.4080e-04 - accuracy: 1.0000\n",
            "Epoch 991/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 4.3799e-04 - accuracy: 1.0000\n",
            "Epoch 992/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.3521e-04 - accuracy: 1.0000\n",
            "Epoch 993/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.3243e-04 - accuracy: 1.0000\n",
            "Epoch 994/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.2967e-04 - accuracy: 1.0000\n",
            "Epoch 995/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.2693e-04 - accuracy: 1.0000\n",
            "Epoch 996/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.2422e-04 - accuracy: 1.0000\n",
            "Epoch 997/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 4.2151e-04 - accuracy: 1.0000\n",
            "Epoch 998/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.1882e-04 - accuracy: 1.0000\n",
            "Epoch 999/1000\n",
            "15/15 [==============================] - 0s 3ms/step - loss: 4.1615e-04 - accuracy: 1.0000\n",
            "Epoch 1000/1000\n",
            "15/15 [==============================] - 0s 4ms/step - loss: 4.1350e-04 - accuracy: 1.0000\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7fe8062e8c10>"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.get_weights()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lwsthYoGBnrF",
        "outputId": "9ff7af80-5528-45cb-eb75-5dccaebadbed"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[array([[ 0.05109422, -0.05123981],\n",
              "        [-7.0921583 ,  7.227747  ]], dtype=float32),\n",
              " array([ 3.4112265, -3.479132 ], dtype=float32),\n",
              " array([[-8.300057],\n",
              "        [ 8.189827]], dtype=float32),\n",
              " array([0.01820502], dtype=float32)]"
            ]
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.get_weight_paths()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3XBbJErkBrZ9",
        "outputId": "556f53aa-94ca-428a-affa-1e3347da8834"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'dense_1.kernel': <tf.Variable 'dense_1/kernel:0' shape=(2, 2) dtype=float32, numpy=\n",
              " array([[ 0.05109422, -0.05123981],\n",
              "        [-7.0921583 ,  7.227747  ]], dtype=float32)>,\n",
              " 'dense_1.bias': <tf.Variable 'dense_1/bias:0' shape=(2,) dtype=float32, numpy=array([ 3.4112265, -3.479132 ], dtype=float32)>,\n",
              " 'dense_2.kernel': <tf.Variable 'dense_2/kernel:0' shape=(2, 1) dtype=float32, numpy=\n",
              " array([[-8.300057],\n",
              "        [ 8.189827]], dtype=float32)>,\n",
              " 'dense_2.bias': <tf.Variable 'dense_2/bias:0' shape=(1,) dtype=float32, numpy=array([0.01820502], dtype=float32)>}"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    }
  ]
}