Deep Learning Projects/MNIST_Using_Conv2D_Dilation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from tensorflow.keras.layers import Dense, Dropout, Input, Conv2D, MaxPooling2D, Flatten, concatenate\n",
        "from tensorflow.keras.models import Model\n",
        "from tensorflow.keras.datasets import mnist\n",
        "from tensorflow.keras.utils import to_categorical, plot_model"
      ],
      "metadata": {
        "id": "rjeJ1z9PhKZH"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "(x_train, y_train), (x_test, y_test) = mnist.load_data()\n",
        "num_labels = len(np.unique(y_train))\n",
        "y_train = to_categorical(y_train)\n",
        "y_test = to_categorical(y_test)\n",
        "image_size = x_train.shape[1]\n",
        "x_train = np.reshape(x_train,[-1, image_size, image_size, 1])\n",
        "x_test = np.reshape(x_test,[-1, image_size, image_size, 1])\n",
        "x_train = x_train.astype('float32') / 255\n",
        "x_test = x_test.astype('float32') / 255"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UqvcmLZxlIPN",
        "outputId": "75bd4b21-3265-4ed4-8588-afff7218db2a"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz\n",
            "11490434/11490434 [==============================] - 0s 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "input_shape = (image_size, image_size, 1)\n",
        "batch_size = 32\n",
        "kernel_size = 3\n",
        "dropout = 0.4\n",
        "n_filters = 32"
      ],
      "metadata": {
        "id": "iqlvOKe7lS-e"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "left_inputs = Input(shape = input_shape)\n",
        "x = left_inputs\n",
        "filters = n_filters\n",
        "\n",
        "for i in range(3):\n",
        "  x = Conv2D(filters = filters, kernel_size = kernel_size, padding = \"same\", activation = \"relu\")(x)\n",
        "  x = Dropout(dropout)(x)\n",
        "  x = MaxPooling2D()(x)\n",
        "  filters *=2\n",
        "\n",
        "right_inputs = Input(shape = input_shape)\n",
        "y = right_inputs\n",
        "filters = n_filters\n",
        "\n",
        "for i in range(3):\n",
        "  y = Conv2D(filters = filters, kernel_size = kernel_size, padding = \"same\", activation = \"relu\", dilation_rate = 2)(y)\n",
        "  y = Dropout(dropout)(y)\n",
        "  y = MaxPooling2D()(y)\n",
        "  filters *= 2\n",
        "\n",
        "y = concatenate([x, y])\n",
        "y = Flatten()(y)\n",
        "y = Dropout(dropout)(y)\n",
        "outputs = Dense(num_labels, activation = \"softmax\")(y)\n",
        "\n",
        "\n",
        "model = Model([left_inputs, right_inputs], outputs)\n",
        "model.summary()\n",
        "plot_model(model, show_shapes = True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "4D-qZ7k9lifS",
        "outputId": "0a0d138c-d028-4f7a-9723-f6eae665a621"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"model_2\"\n",
            "__________________________________________________________________________________________________\n",
            " Layer (type)                Output Shape                 Param #   Connected to                  \n",
            "==================================================================================================\n",
            " input_5 (InputLayer)        [(None, 28, 28, 1)]          0         []                            \n",
            "                                                                                                  \n",
            " input_6 (InputLayer)        [(None, 28, 28, 1)]          0         []                            \n",
            "                                                                                                  \n",
            " conv2d_12 (Conv2D)          (None, 28, 28, 32)           320       ['input_5[0][0]']             \n",
            "                                                                                                  \n",
            " conv2d_15 (Conv2D)          (None, 28, 28, 32)           320       ['input_6[0][0]']             \n",
            "                                                                                                  \n",
            " dropout_14 (Dropout)        (None, 28, 28, 32)           0         ['conv2d_12[0][0]']           \n",
            "                                                                                                  \n",
            " dropout_17 (Dropout)        (None, 28, 28, 32)           0         ['conv2d_15[0][0]']           \n",
            "                                                                                                  \n",
            " max_pooling2d_12 (MaxPooli  (None, 14, 14, 32)           0         ['dropout_14[0][0]']          \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " max_pooling2d_15 (MaxPooli  (None, 14, 14, 32)           0         ['dropout_17[0][0]']          \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv2d_13 (Conv2D)          (None, 14, 14, 64)           18496     ['max_pooling2d_12[0][0]']    \n",
            "                                                                                                  \n",
            " conv2d_16 (Conv2D)          (None, 14, 14, 64)           18496     ['max_pooling2d_15[0][0]']    \n",
            "                                                                                                  \n",
            " dropout_15 (Dropout)        (None, 14, 14, 64)           0         ['conv2d_13[0][0]']           \n",
            "                                                                                                  \n",
            " dropout_18 (Dropout)        (None, 14, 14, 64)           0         ['conv2d_16[0][0]']           \n",
            "                                                                                                  \n",
            " max_pooling2d_13 (MaxPooli  (None, 7, 7, 64)             0         ['dropout_15[0][0]']          \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " max_pooling2d_16 (MaxPooli  (None, 7, 7, 64)             0         ['dropout_18[0][0]']          \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " conv2d_14 (Conv2D)          (None, 7, 7, 128)            73856     ['max_pooling2d_13[0][0]']    \n",
            "                                                                                                  \n",
            " conv2d_17 (Conv2D)          (None, 7, 7, 128)            73856     ['max_pooling2d_16[0][0]']    \n",
            "                                                                                                  \n",
            " dropout_16 (Dropout)        (None, 7, 7, 128)            0         ['conv2d_14[0][0]']           \n",
            "                                                                                                  \n",
            " dropout_19 (Dropout)        (None, 7, 7, 128)            0         ['conv2d_17[0][0]']           \n",
            "                                                                                                  \n",
            " max_pooling2d_14 (MaxPooli  (None, 3, 3, 128)            0         ['dropout_16[0][0]']          \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " max_pooling2d_17 (MaxPooli  (None, 3, 3, 128)            0         ['dropout_19[0][0]']          \n",
            " ng2D)                                                                                            \n",
            "                                                                                                  \n",
            " concatenate_2 (Concatenate  (None, 3, 3, 256)            0         ['max_pooling2d_14[0][0]',    \n",
            " )                                                                   'max_pooling2d_17[0][0]']    \n",
            "                                                                                                  \n",
            " flatten_2 (Flatten)         (None, 2304)                 0         ['concatenate_2[0][0]']       \n",
            "                                                                                                  \n",
            " dropout_20 (Dropout)        (None, 2304)                 0         ['flatten_2[0][0]']           \n",
            "                                                                                                  \n",
            " dense_2 (Dense)             (None, 10)                   23050     ['dropout_20[0][0]']          \n",
            "                                                                                                  \n",
            "==================================================================================================\n",
            "Total params: 208394 (814.04 KB)\n",
            "Trainable params: 208394 (814.04 KB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "__________________________________________________________________________________________________\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
        "model.fit([x_train, x_train], y_train, validation_data=([x_test, x_test], y_test), epochs=20, batch_size=batch_size)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rBHyyATVnRFu",
        "outputId": "dd4e0b59-9e46-454d-b675-6a2a0cc9b103"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "1875/1875 [==============================] - 253s 134ms/step - loss: 0.1735 - accuracy: 0.9454 - val_loss: 0.1205 - val_accuracy: 0.9887\n",
            "Epoch 2/20\n",
            "1875/1875 [==============================] - 247s 132ms/step - loss: 0.0654 - accuracy: 0.9798 - val_loss: 0.0884 - val_accuracy: 0.9900\n",
            "Epoch 3/20\n",
            "1875/1875 [==============================] - 243s 130ms/step - loss: 0.0514 - accuracy: 0.9840 - val_loss: 0.0790 - val_accuracy: 0.9925\n",
            "Epoch 4/20\n",
            "1875/1875 [==============================] - 243s 130ms/step - loss: 0.0458 - accuracy: 0.9856 - val_loss: 0.0636 - val_accuracy: 0.9924\n",
            "Epoch 5/20\n",
            "1875/1875 [==============================] - 241s 128ms/step - loss: 0.0415 - accuracy: 0.9869 - val_loss: 0.0639 - val_accuracy: 0.9923\n",
            "Epoch 6/20\n",
            "1875/1875 [==============================] - 242s 129ms/step - loss: 0.0386 - accuracy: 0.9878 - val_loss: 0.0665 - val_accuracy: 0.9923\n",
            "Epoch 7/20\n",
            "1875/1875 [==============================] - 242s 129ms/step - loss: 0.0353 - accuracy: 0.9888 - val_loss: 0.0497 - val_accuracy: 0.9933\n",
            "Epoch 8/20\n",
            "1875/1875 [==============================] - 242s 129ms/step - loss: 0.0340 - accuracy: 0.9897 - val_loss: 0.0536 - val_accuracy: 0.9915\n",
            "Epoch 9/20\n",
            "1875/1875 [==============================] - 242s 129ms/step - loss: 0.0324 - accuracy: 0.9899 - val_loss: 0.0296 - val_accuracy: 0.9939\n",
            "Epoch 10/20\n",
            "1875/1875 [==============================] - 241s 129ms/step - loss: 0.0320 - accuracy: 0.9900 - val_loss: 0.0548 - val_accuracy: 0.9922\n",
            "Epoch 11/20\n",
            "1875/1875 [==============================] - 243s 130ms/step - loss: 0.0329 - accuracy: 0.9902 - val_loss: 0.0463 - val_accuracy: 0.9933\n",
            "Epoch 12/20\n",
            "1875/1875 [==============================] - 240s 128ms/step - loss: 0.0318 - accuracy: 0.9899 - val_loss: 0.0435 - val_accuracy: 0.9923\n",
            "Epoch 13/20\n",
            "1875/1875 [==============================] - 243s 130ms/step - loss: 0.0329 - accuracy: 0.9897 - val_loss: 0.0320 - val_accuracy: 0.9932\n",
            "Epoch 14/20\n",
            "1875/1875 [==============================] - 240s 128ms/step - loss: 0.0299 - accuracy: 0.9900 - val_loss: 0.0386 - val_accuracy: 0.9928\n",
            "Epoch 15/20\n",
            "1875/1875 [==============================] - 242s 129ms/step - loss: 0.0311 - accuracy: 0.9906 - val_loss: 0.0532 - val_accuracy: 0.9921\n",
            "Epoch 16/20\n",
            "1875/1875 [==============================] - 241s 128ms/step - loss: 0.0292 - accuracy: 0.9913 - val_loss: 0.0334 - val_accuracy: 0.9919\n",
            "Epoch 17/20\n",
            "1875/1875 [==============================] - 241s 129ms/step - loss: 0.0311 - accuracy: 0.9906 - val_loss: 0.0594 - val_accuracy: 0.9928\n",
            "Epoch 18/20\n",
            "1875/1875 [==============================] - 243s 129ms/step - loss: 0.0300 - accuracy: 0.9911 - val_loss: 0.0441 - val_accuracy: 0.9936\n",
            "Epoch 19/20\n",
            "1875/1875 [==============================] - 240s 128ms/step - loss: 0.0288 - accuracy: 0.9916 - val_loss: 0.0363 - val_accuracy: 0.9934\n",
            "Epoch 20/20\n",
            "1875/1875 [==============================] - 243s 129ms/step - loss: 0.0293 - accuracy: 0.9908 - val_loss: 0.0462 - val_accuracy: 0.9931\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.src.callbacks.History at 0x7fdc3e4d0ee0>"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "score = model.evaluate([x_test, x_test], y_test, batch_size=batch_size, verbose = 1)\n",
        "score"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "czTCxhLwoU_r",
        "outputId": "d663812e-7284-44c4-8845-bc35fd4e6e8b"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "313/313 [==============================] - 10s 33ms/step - loss: 0.0462 - accuracy: 0.9931\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.04624675586819649, 0.9930999875068665]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    }
  ]
}