{"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.10.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":16017,"databundleVersionId":708189,"sourceType":"competition"}],"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"## **Import Modules** <a id=\"210\"></a>","metadata":{}},{"cell_type":"code","source":"import numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\nimport matplotlib.pyplot as plt # data visualization\nimport seaborn as sns # data visualization\n\nfrom sklearn.model_selection import train_test_split\nfrom keras.utils.np_utils import to_categorical\n\nimport tensorflow as tf\nfrom tensorflow.keras import Sequential\nfrom tensorflow.keras.layers import Conv2D, Dropout, Dense, Flatten, BatchNormalization, MaxPooling2D,LeakyReLU\nfrom tensorflow.keras.optimizers import RMSprop,Nadam,Adadelta\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\nfrom tensorflow.keras.callbacks import ReduceLROnPlateau, EarlyStopping\nfrom tensorflow.keras.utils import to_categorical\nfrom tensorflow.keras.regularizers import l2\n\nimport warnings\nwarnings.filterwarnings('ignore')\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:09.23149Z","iopub.execute_input":"2024-04-28T13:19:09.231773Z","iopub.status.idle":"2024-04-28T13:19:12.44495Z","shell.execute_reply.started":"2024-04-28T13:19:09.231731Z","shell.execute_reply":"2024-04-28T13:19:12.444168Z"},"trusted":true},"outputs":[{"name":"stderr","text":"Using TensorFlow backend.\n","output_type":"stream"},{"name":"stdout","text":"/kaggle/input/Kannada-MNIST/sample_submission.csv\n/kaggle/input/Kannada-MNIST/Dig-MNIST.csv\n/kaggle/input/Kannada-MNIST/train.csv\n/kaggle/input/Kannada-MNIST/test.csv\n","output_type":"stream"}],"execution_count":1},{"cell_type":"markdown","source":"* With this code below you can check if the kernel use GPU or not.","metadata":{}},{"cell_type":"code","source":"tf.test.gpu_device_name()","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:18.18837Z","iopub.execute_input":"2024-04-28T13:19:18.18888Z","iopub.status.idle":"2024-04-28T13:19:20.545608Z","shell.execute_reply.started":"2024-04-28T13:19:18.188821Z","shell.execute_reply":"2024-04-28T13:19:20.544774Z"},"trusted":true},"outputs":[{"execution_count":2,"output_type":"execute_result","data":{"text/plain":"'/device:GPU:0'"},"metadata":{}}],"execution_count":2},{"cell_type":"markdown","source":"## **Understanding the Data** <a id=\"220\"></a>\n","metadata":{}},{"cell_type":"markdown","source":"* We have training and test set CSV files,\n* In order to evaluate the generalization skill of the model we will split our training set into training and validation sets.\n* After training the data, Kaggle will evaluate the final performance of our data with test set predictions.","metadata":{}},{"cell_type":"markdown","source":"* Let's read csv files","metadata":{}},{"cell_type":"code","source":"raw_train = pd.read_csv('../input/Kannada-MNIST/train.csv')\nraw_test = pd.read_csv('../input/Kannada-MNIST/test.csv')","metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","execution":{"iopub.status.busy":"2024-04-28T13:19:22.010935Z","iopub.execute_input":"2024-04-28T13:19:22.011299Z","iopub.status.idle":"2024-04-28T13:19:28.435071Z","shell.execute_reply.started":"2024-04-28T13:19:22.011235Z","shell.execute_reply":"2024-04-28T13:19:28.434412Z"},"trusted":true},"outputs":[],"execution_count":3},{"cell_type":"markdown","source":"* We have $28$x$28$ dimension handwritten pics.\n* Dataset has been already flattened and has 784-pixel values for each pic.\n* Totaly we have $60000$ pics in training set.","metadata":{}},{"cell_type":"code","source":"raw_train.iloc[[0,-1],[1,-1]] # First and last values of dataset","metadata":{"scrolled":true,"execution":{"iopub.status.busy":"2024-04-28T13:19:30.465283Z","iopub.execute_input":"2024-04-28T13:19:30.465576Z","iopub.status.idle":"2024-04-28T13:19:30.486703Z","shell.execute_reply.started":"2024-04-28T13:19:30.465535Z","shell.execute_reply":"2024-04-28T13:19:30.485955Z"},"trusted":true},"outputs":[{"execution_count":4,"output_type":"execute_result","data":{"text/plain":"       pixel0  pixel783\n0           0         0\n59999       0         0","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>pixel0</th>\n      <th>pixel783</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>59999</th>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}],"execution_count":4},{"cell_type":"markdown","source":"* It is important to know the distribution of data according to the labels they have.\n* This data set is __homogeneously__ distributed as you see below.","metadata":{}},{"cell_type":"code","source":"num = raw_train.label.value_counts()\nsns.barplot(num.index,num)\nnumbers = num.index.values","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:33.363161Z","iopub.execute_input":"2024-04-28T13:19:33.36345Z","iopub.status.idle":"2024-04-28T13:19:33.609318Z","shell.execute_reply.started":"2024-04-28T13:19:33.363408Z","shell.execute_reply":"2024-04-28T13:19:33.608489Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":5},{"cell_type":"markdown","source":"* __If the data wasn't homogeneously__ distributed what would we do?\n    1. Then we could use data augmentation techniques to generate new data for low quantity labels,\n    2. Or if we have enough data we can discard some high quantity labels","metadata":{}},{"cell_type":"markdown","source":"#### **Image of Handwritten Character** <a id=\"2\"></a>\n","metadata":{}},{"cell_type":"code","source":"num=6\nnumber = raw_train.iloc[num,1:].values.reshape(28,28)\nprint(\"Picture of \"+ str(num) + \"in Kannada style\")\nplt.imshow(number, cmap=plt.get_cmap('gray'))\nplt.show()\n","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:37.243193Z","iopub.execute_input":"2024-04-28T13:19:37.243508Z","iopub.status.idle":"2024-04-28T13:19:37.387305Z","shell.execute_reply.started":"2024-04-28T13:19:37.243462Z","shell.execute_reply":"2024-04-28T13:19:37.386553Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Picture of 6in Kannada style\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":6},{"cell_type":"markdown","source":"## **Data Preprocessing** <a id=\"230\"></a>\n### **Normalizing Data** <a id=\"231\"></a>\n","metadata":{}},{"cell_type":"code","source":"x = raw_train.iloc[:, 1:].values.astype('float32') / 255\ny = raw_train.iloc[:, 0] # labels","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:39.729036Z","iopub.execute_input":"2024-04-28T13:19:39.72938Z","iopub.status.idle":"2024-04-28T13:19:39.936748Z","shell.execute_reply.started":"2024-04-28T13:19:39.72933Z","shell.execute_reply":"2024-04-28T13:19:39.93602Z"},"trusted":true},"outputs":[],"execution_count":7},{"cell_type":"markdown","source":"### **Cross Validation - Training- Validation Set Split** <a id=\"232\"></a>\n","metadata":{}},{"cell_type":"code","source":"x_train, x_val, y_train, y_val = train_test_split(x, y, test_size = 0.2, random_state=42) ","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:50.189332Z","iopub.execute_input":"2024-04-28T13:19:50.189658Z","iopub.status.idle":"2024-04-28T13:19:50.691282Z","shell.execute_reply.started":"2024-04-28T13:19:50.189611Z","shell.execute_reply":"2024-04-28T13:19:50.690624Z"},"trusted":true},"outputs":[],"execution_count":8},{"cell_type":"markdown","source":"### **Reshape Data to Fit Model** <a id=\"233\"></a>\n","metadata":{}},{"cell_type":"code","source":"x_train.shape","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:52.480569Z","iopub.execute_input":"2024-04-28T13:19:52.480861Z","iopub.status.idle":"2024-04-28T13:19:52.485921Z","shell.execute_reply.started":"2024-04-28T13:19:52.480819Z","shell.execute_reply":"2024-04-28T13:19:52.485019Z"},"trusted":true},"outputs":[{"execution_count":9,"output_type":"execute_result","data":{"text/plain":"(48000, 784)"},"metadata":{}}],"execution_count":9},{"cell_type":"code","source":"x_train = x_train.reshape(-1, 28, 28,1)\nx_val = x_val.reshape(-1, 28, 28,1)\ny_train = to_categorical(y_train)\ny_val = to_categorical(y_val)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:19:54.168631Z","iopub.execute_input":"2024-04-28T13:19:54.169026Z","iopub.status.idle":"2024-04-28T13:19:54.175779Z","shell.execute_reply.started":"2024-04-28T13:19:54.168957Z","shell.execute_reply":"2024-04-28T13:19:54.175095Z"},"trusted":true},"outputs":[],"execution_count":10},{"cell_type":"markdown","source":"* You can leave one unknown dimension as -1.\n* Whenever numpy has -1 value on reshape method it will calculate the dimension which denoted with -1 automatically.","metadata":{}},{"cell_type":"markdown","source":"## **Building and Training a CNN Model** <a id=\"250\"></a>\n","metadata":{}},{"cell_type":"code","source":"model = tf.keras.models.Sequential([\n    tf.keras.layers.Conv2D(64, (3,3), padding='same', input_shape=(28, 28, 1)),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n    tf.keras.layers.Conv2D(64,  (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n    tf.keras.layers.Conv2D(64,  (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n\n    tf.keras.layers.MaxPooling2D(2, 2),\n    tf.keras.layers.Dropout(0.25),\n    \n    tf.keras.layers.Conv2D(128, (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n    tf.keras.layers.Conv2D(128, (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n    tf.keras.layers.Conv2D(128, (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n    \n    tf.keras.layers.MaxPooling2D(2,2),\n    tf.keras.layers.Dropout(0.25),    \n    \n    tf.keras.layers.Conv2D(256, (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n    tf.keras.layers.Conv2D(256, (3,3), padding='same'),\n    tf.keras.layers.BatchNormalization(momentum=0.9, epsilon=1e-5, gamma_initializer=\"uniform\"),##\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n\n    tf.keras.layers.MaxPooling2D(2,2),\n    tf.keras.layers.Dropout(0.25),\n    \n    \n    tf.keras.layers.Flatten(),\n    tf.keras.layers.Dense(256),\n    tf.keras.layers.LeakyReLU(alpha=0.1),\n \n    tf.keras.layers.BatchNormalization(),\n    tf.keras.layers.Dense(10, activation='softmax')\n])","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:20:11.547193Z","iopub.execute_input":"2024-04-28T13:20:11.547521Z","iopub.status.idle":"2024-04-28T13:20:12.768977Z","shell.execute_reply.started":"2024-04-28T13:20:11.547462Z","shell.execute_reply":"2024-04-28T13:20:12.768325Z"},"trusted":true},"outputs":[],"execution_count":11},{"cell_type":"markdown","source":"### **Model - Compile** <a id=\"252\"></a>\n","metadata":{}},{"cell_type":"code","source":"optimizer = RMSprop(learning_rate=0.002,###########optimizer = RMSprop(learning_rate=0.0025,###########\n    rho=0.9,\n    momentum=0.1,\n    epsilon=1e-07,\n    centered=True,\n    name='RMSprop')\nmodel.compile(loss='categorical_crossentropy',\n              optimizer=optimizer,\n              metrics=['accuracy'])","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:20:46.076393Z","iopub.execute_input":"2024-04-28T13:20:46.076742Z","iopub.status.idle":"2024-04-28T13:20:46.128877Z","shell.execute_reply.started":"2024-04-28T13:20:46.076691Z","shell.execute_reply":"2024-04-28T13:20:46.128133Z"},"trusted":true},"outputs":[],"execution_count":13},{"cell_type":"code","source":"batch_size = 1024\nnum_classes = 10\nepochs = 40\n","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:20:50.186206Z","iopub.execute_input":"2024-04-28T13:20:50.186496Z","iopub.status.idle":"2024-04-28T13:20:50.190547Z","shell.execute_reply.started":"2024-04-28T13:20:50.186459Z","shell.execute_reply":"2024-04-28T13:20:50.189589Z"},"trusted":true},"outputs":[],"execution_count":14},{"cell_type":"markdown","source":"#### **On-the-Fly Data Augmentation** <a id=\"257\"></a>\nOn classification tasks on image datasets data augmentation is a common way to increase the generalization of the model. \nWith the ImageDataGenerator on Keras, we can handle this objective easily.\n","metadata":{}},{"cell_type":"code","source":"# An observation code for our dataset\ndatagen_try = ImageDataGenerator(rotation_range=15,\n                             width_shift_range = 0.15,\n                             height_shift_range = 0.15,\n                             shear_range = 0.15,\n                             zoom_range = 0.4,)\n# fit parameters from data\ndatagen_try.fit(x_train)\n# configure batch size and retrieve one batch of images\nfor x_batch, y_batch in datagen_try.flow(x_train, y_train, batch_size=9):\n\t# create a grid of 3x3 images\n\tfor i in range(0, 9):\n\t\tplt.subplot(330 + 1 + i)\n\t\tplt.imshow(x_batch[i].reshape(28, 28), cmap=plt.get_cmap('gray'))\n\t# show the plot\n\tplt.show()\n\tbreak","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:21:12.570833Z","iopub.execute_input":"2024-04-28T13:21:12.57116Z","iopub.status.idle":"2024-04-28T13:21:13.408882Z","shell.execute_reply.started":"2024-04-28T13:21:12.571091Z","shell.execute_reply":"2024-04-28T13:21:13.408141Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 9 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":15},{"cell_type":"code","source":"datagen_train = ImageDataGenerator(rotation_range = 10,\n                                   width_shift_range = 0.25,\n                                   height_shift_range = 0.25,\n                                   shear_range = 0.1,\n                                   zoom_range = 0.4,\n                                   horizontal_flip = False)\n\ndatagen_val = ImageDataGenerator() \n\n\nstep_train = x_train.shape[0] // batch_size\nstep_val = x_val.shape[0] // batch_size\n\nlearning_rate_reduction = tf.keras.callbacks.ReduceLROnPlateau( \n    monitor='loss',    # Quantity to be monitored.\n    factor=0.25,       # Factor by which the learning rate will be reduced. new_lr = lr * factor\n    patience=2,        # The number of epochs with no improvement after which learning rate will be reduced.\n    verbose=1,         # 0: quiet - 1: update messages.\n    mode=\"auto\",       # {auto, min, max}. In min mode, lr will be reduced when the quantity monitored has stopped decreasing; \n                       # in the max mode it will be reduced when the quantity monitored has stopped increasing; \n                       # in auto mode, the direction is automatically inferred from the name of the monitored quantity.\n    min_delta=0.0001,  # threshold for measuring the new optimum, to only focus on significant changes.\n    cooldown=0,        # number of epochs to wait before resuming normal operation after learning rate (lr) has been reduced.\n    min_lr=0.00001     # lower bound on the learning rate.\n    )\n\nes = EarlyStopping(monitor='val_loss', mode='min', verbose=1, patience=300, restore_best_weights=True)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:21:55.85984Z","iopub.execute_input":"2024-04-28T13:21:55.860196Z","iopub.status.idle":"2024-04-28T13:21:55.869261Z","shell.execute_reply.started":"2024-04-28T13:21:55.860112Z","shell.execute_reply":"2024-04-28T13:21:55.868199Z"},"trusted":true},"outputs":[],"execution_count":17},{"cell_type":"markdown","source":"### **Model - Fit** <a id=\"259\"></a>\n","metadata":{}},{"cell_type":"code","source":"history = model.fit_generator(datagen_train.flow(x_train, y_train, batch_size=batch_size),\n                              steps_per_epoch=len(x_train)//batch_size,\n                              epochs=epochs,\n                              validation_data=(x_val, y_val),\n                              validation_steps=50,\n                              callbacks=[learning_rate_reduction, es],\n                              verbose=2)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:21:58.49838Z","iopub.execute_input":"2024-04-28T13:21:58.498679Z","iopub.status.idle":"2024-04-28T13:33:16.230314Z","shell.execute_reply.started":"2024-04-28T13:21:58.498636Z","shell.execute_reply":"2024-04-28T13:33:16.228797Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Epoch 1/40\n46/46 - 19s - loss: 1.2287 - accuracy: 0.5846 - val_loss: 2.3258 - val_accuracy: 0.0981\nEpoch 2/40\n46/46 - 17s - loss: 0.3500 - accuracy: 0.8849 - val_loss: 1.3479 - val_accuracy: 0.8069\nEpoch 3/40\n46/46 - 17s - loss: 0.1906 - accuracy: 0.9368 - val_loss: 0.7398 - val_accuracy: 0.8728\nEpoch 4/40\n46/46 - 17s - loss: 0.1344 - accuracy: 0.9544 - val_loss: 0.2959 - val_accuracy: 0.9898\nEpoch 5/40\n46/46 - 17s - loss: 0.1140 - accuracy: 0.9617 - val_loss: 0.1360 - val_accuracy: 0.9927\nEpoch 6/40\n46/46 - 17s - loss: 0.0954 - accuracy: 0.9673 - val_loss: 0.0748 - val_accuracy: 0.9837\nEpoch 7/40\n46/46 - 17s - loss: 0.0898 - accuracy: 0.9701 - val_loss: 0.0394 - val_accuracy: 0.9930\nEpoch 8/40\n46/46 - 17s - loss: 0.0822 - accuracy: 0.9734 - val_loss: 0.0337 - val_accuracy: 0.9901\nEpoch 9/40\n46/46 - 17s - loss: 0.0784 - accuracy: 0.9736 - val_loss: 0.0261 - val_accuracy: 0.9920\nEpoch 10/40\n46/46 - 17s - loss: 0.0749 - accuracy: 0.9738 - val_loss: 0.0165 - val_accuracy: 0.9951\nEpoch 11/40\n46/46 - 17s - loss: 0.0714 - accuracy: 0.9764 - val_loss: 0.0309 - val_accuracy: 0.9897\nEpoch 12/40\n46/46 - 17s - loss: 0.0660 - accuracy: 0.9773 - val_loss: 0.0181 - val_accuracy: 0.9946\nEpoch 13/40\n46/46 - 17s - loss: 0.0658 - accuracy: 0.9781 - val_loss: 0.0307 - val_accuracy: 0.9912\nEpoch 14/40\n46/46 - 17s - loss: 0.0634 - accuracy: 0.9786 - val_loss: 0.0182 - val_accuracy: 0.9945\nEpoch 15/40\n46/46 - 17s - loss: 0.0572 - accuracy: 0.9805 - val_loss: 0.0140 - val_accuracy: 0.9958\nEpoch 16/40\n46/46 - 17s - loss: 0.0605 - accuracy: 0.9796 - val_loss: 0.0117 - val_accuracy: 0.9967\nEpoch 17/40\n\nEpoch 00017: ReduceLROnPlateau reducing learning rate to 0.0005000000237487257.\n46/46 - 16s - loss: 0.0581 - accuracy: 0.9804 - val_loss: 0.0578 - val_accuracy: 0.9836\nEpoch 18/40\n46/46 - 17s - loss: 0.0443 - accuracy: 0.9851 - val_loss: 0.0135 - val_accuracy: 0.9955\nEpoch 19/40\n46/46 - 17s - loss: 0.0408 - accuracy: 0.9861 - val_loss: 0.0114 - val_accuracy: 0.9970\nEpoch 20/40\n46/46 - 16s - loss: 0.0398 - accuracy: 0.9863 - val_loss: 0.0119 - val_accuracy: 0.9965\nEpoch 21/40\n46/46 - 17s - loss: 0.0384 - accuracy: 0.9870 - val_loss: 0.0117 - val_accuracy: 0.9968\nEpoch 22/40\n46/46 - 17s - loss: 0.0367 - accuracy: 0.9875 - val_loss: 0.0101 - val_accuracy: 0.9970\nEpoch 23/40\n46/46 - 16s - loss: 0.0386 - accuracy: 0.9870 - val_loss: 0.0092 - val_accuracy: 0.9973\nEpoch 24/40\n\nEpoch 00024: ReduceLROnPlateau reducing learning rate to 0.0001250000059371814.\n46/46 - 16s - loss: 0.0411 - accuracy: 0.9865 - val_loss: 0.0103 - val_accuracy: 0.9969\nEpoch 25/40\n46/46 - 17s - loss: 0.0365 - accuracy: 0.9880 - val_loss: 0.0089 - val_accuracy: 0.9975\nEpoch 26/40\n46/46 - 17s - loss: 0.0342 - accuracy: 0.9882 - val_loss: 0.0099 - val_accuracy: 0.9973\nEpoch 27/40\n46/46 - 17s - loss: 0.0331 - accuracy: 0.9890 - val_loss: 0.0094 - val_accuracy: 0.9974\nEpoch 28/40\n46/46 - 17s - loss: 0.0363 - accuracy: 0.9878 - val_loss: 0.0092 - val_accuracy: 0.9973\nEpoch 29/40\n46/46 - 17s - loss: 0.0321 - accuracy: 0.9891 - val_loss: 0.0097 - val_accuracy: 0.9973\nEpoch 30/40\n46/46 - 17s - loss: 0.0344 - accuracy: 0.9882 - val_loss: 0.0099 - val_accuracy: 0.9973\nEpoch 31/40\n\nEpoch 00031: ReduceLROnPlateau reducing learning rate to 3.125000148429535e-05.\n46/46 - 17s - loss: 0.0348 - accuracy: 0.9887 - val_loss: 0.0091 - val_accuracy: 0.9973\nEpoch 32/40\n46/46 - 17s - loss: 0.0342 - accuracy: 0.9886 - val_loss: 0.0092 - val_accuracy: 0.9973\nEpoch 33/40\n\nEpoch 00033: ReduceLROnPlateau reducing learning rate to 1e-05.\n46/46 - 17s - loss: 0.0327 - accuracy: 0.9885 - val_loss: 0.0097 - val_accuracy: 0.9973\nEpoch 34/40\n46/46 - 17s - loss: 0.0322 - accuracy: 0.9886 - val_loss: 0.0095 - val_accuracy: 0.9973\nEpoch 35/40\n46/46 - 16s - loss: 0.0330 - accuracy: 0.9890 - val_loss: 0.0095 - val_accuracy: 0.9974\nEpoch 36/40\n46/46 - 17s - loss: 0.0332 - accuracy: 0.9887 - val_loss: 0.0094 - val_accuracy: 0.9973\nEpoch 37/40\n46/46 - 17s - loss: 0.0328 - accuracy: 0.9890 - val_loss: 0.0092 - val_accuracy: 0.9973\nEpoch 38/40\n46/46 - 17s - loss: 0.0343 - accuracy: 0.9885 - val_loss: 0.0094 - val_accuracy: 0.9973\nEpoch 39/40\n46/46 - 17s - loss: 0.0340 - accuracy: 0.9889 - val_loss: 0.0093 - val_accuracy: 0.9973\nEpoch 40/40\n46/46 - 17s - loss: 0.0320 - accuracy: 0.9890 - val_loss: 0.0093 - val_accuracy: 0.9973\n","output_type":"stream"}],"execution_count":18},{"cell_type":"markdown","source":"## **Evaluation of the Model** <a id=\"270\"></a>\n### **Accuracy and Loss Curves** <a id=\"271\"></a>\n","metadata":{}},{"cell_type":"code","source":"tf.keras.utils.plot_model(model, to_file=\"model.png\", show_shapes=True)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:35:21.769754Z","iopub.execute_input":"2024-04-28T13:35:21.770341Z","iopub.status.idle":"2024-04-28T13:35:23.248292Z","shell.execute_reply.started":"2024-04-28T13:35:21.770081Z","shell.execute_reply":"2024-04-28T13:35:23.247341Z"},"trusted":true},"outputs":[{"execution_count":19,"output_type":"execute_result","data":{"image/png":"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\n","text/plain":"<IPython.core.display.Image object>"},"metadata":{}}],"execution_count":19},{"cell_type":"code","source":"plt.plot(history.history['accuracy'])\nplt.plot(history.history['val_accuracy'])\nplt.title('Model accuracy')\nplt.ylabel('Accuracy')\nplt.xlabel('Epoch')\nplt.legend(['Train', 'Validation'], loc='upper left')\nplt.show()\n\n# Plot training & validation loss values\nplt.plot(history.history['loss'])\nplt.plot(history.history['val_loss'])\nplt.title('Model loss')\nplt.ylabel('Loss')\nplt.xlabel('Epoch')\nplt.legend(['Train', 'Validation'], loc='upper left')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:35:28.377605Z","iopub.execute_input":"2024-04-28T13:35:28.377927Z","iopub.status.idle":"2024-04-28T13:35:28.715673Z","shell.execute_reply.started":"2024-04-28T13:35:28.377871Z","shell.execute_reply":"2024-04-28T13:35:28.71496Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 432x288 with 1 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\n"},"metadata":{"needs_background":"light"}},{"output_type":"display_data","data":{"text/plain":"<Figure 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\n"},"metadata":{"needs_background":"light"}}],"execution_count":20},{"cell_type":"markdown","source":"### **Test Set Accuracy Score** <a id=\"272\"></a>\n","metadata":{}},{"cell_type":"code","source":"model.evaluate(x_val, y_val, verbose=2);","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:35:37.2981Z","iopub.execute_input":"2024-04-28T13:35:37.298402Z","iopub.status.idle":"2024-04-28T13:35:39.413082Z","shell.execute_reply.started":"2024-04-28T13:35:37.29836Z","shell.execute_reply":"2024-04-28T13:35:39.412312Z"},"trusted":true},"outputs":[{"name":"stdout","text":"12000/1 - 2s - loss: 0.0048 - accuracy: 0.9973\n","output_type":"stream"}],"execution_count":21},{"cell_type":"markdown","source":"### **Confusion Matrix** <a id=\"273\"></a>\n<mark>[Return Contents](#0)","metadata":{}},{"cell_type":"code","source":"y_predicted = model.predict(x_val)\ny_grand_truth = y_val\ny_predicted = np.argmax(y_predicted,axis=1)\ny_grand_truth = np.argmax(y_grand_truth,axis=1)\nfrom sklearn.metrics import confusion_matrix\ncm = confusion_matrix(y_grand_truth, y_predicted)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:35:42.298477Z","iopub.execute_input":"2024-04-28T13:35:42.298927Z","iopub.status.idle":"2024-04-28T13:35:44.243868Z","shell.execute_reply.started":"2024-04-28T13:35:42.29886Z","shell.execute_reply":"2024-04-28T13:35:44.242788Z"},"trusted":true},"outputs":[],"execution_count":22},{"cell_type":"code","source":"f, ax = plt.subplots(figsize=(10,10))\nsns.heatmap(cm,fmt=\".0f\", annot=True,linewidths=0.1, linecolor=\"purple\", ax=ax)\nplt.xlabel(\"Predicted\")\nplt.ylabel(\"Grand Truth\")\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:35:46.40869Z","iopub.execute_input":"2024-04-28T13:35:46.408978Z","iopub.status.idle":"2024-04-28T13:35:47.001469Z","shell.execute_reply.started":"2024-04-28T13:35:46.408936Z","shell.execute_reply":"2024-04-28T13:35:47.000509Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 720x720 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}],"execution_count":23},{"cell_type":"markdown","source":"### **Evaluate with Another Dataset** <a id=\"275\"></a>","metadata":{}},{"cell_type":"code","source":"raw_dig = pd.read_csv(\"../input/Kannada-MNIST/Dig-MNIST.csv\")\nraw_dig.head()\nx_dig = raw_dig.iloc[:, 1:].values.astype('float32') / 255\ny_dig = raw_dig.iloc[:, 0].values\n\nx_dig = x_dig.reshape(-1,28,28,1)\ny_dig = to_categorical(y_dig)\nmodel.evaluate(x_dig, y_dig, verbose=2)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:35:56.59602Z","iopub.execute_input":"2024-04-28T13:35:56.596376Z","iopub.status.idle":"2024-04-28T13:35:59.182633Z","shell.execute_reply.started":"2024-04-28T13:35:56.596308Z","shell.execute_reply":"2024-04-28T13:35:59.181796Z"},"trusted":true},"outputs":[{"name":"stdout","text":"10240/1 - 1s - loss: 0.8625 - accuracy: 0.9049\n","output_type":"stream"},{"execution_count":25,"output_type":"execute_result","data":{"text/plain":"[0.41002740186931985, 0.9048828]"},"metadata":{}}],"execution_count":25},{"cell_type":"code","source":"","metadata":{},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"### **RESNET 18**","metadata":{}},{"cell_type":"code","source":"import numpy as np \nimport pandas as pd \nimport os\ntrain = pd.read_csv(r'/kaggle/input/Kannada-MNIST/train.csv')\ntrain.head()","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:40:18.076131Z","iopub.execute_input":"2024-04-28T13:40:18.077483Z","iopub.status.idle":"2024-04-28T13:40:25.377144Z","shell.execute_reply.started":"2024-04-28T13:40:18.077425Z","shell.execute_reply":"2024-04-28T13:40:25.375901Z"},"trusted":true},"outputs":[{"execution_count":1,"output_type":"execute_result","data":{"text/plain":"   label  pixel0  pixel1  pixel2  pixel3  pixel4  pixel5  pixel6  pixel7  \\\n0      0       0       0       0       0       0       0       0       0   \n1      1       0       0       0       0       0       0       0       0   \n2      2       0       0       0       0       0       0       0       0   \n3      3       0       0       0       0       0       0       0       0   \n4      4       0       0       0       0       0       0       0       0   \n\n   pixel8  ...  pixel774  pixel775  pixel776  pixel777  pixel778  pixel779  \\\n0       0  ...         0         0         0         0         0         0   \n1       0  ...         0         0         0         0         0         0   \n2       0  ...         0         0         0         0         0         0   \n3       0  ...         0         0         0         0         0         0   \n4       0  ...         0         0         0         0         0         0   \n\n   pixel780  pixel781  pixel782  pixel783  \n0         0         0         0         0  \n1         0         0         0         0  \n2         0         0         0         0  \n3         0         0         0         0  \n4         0         0         0         0  \n\n[5 rows x 785 columns]","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>label</th>\n      <th>pixel0</th>\n      <th>pixel1</th>\n      <th>pixel2</th>\n      <th>pixel3</th>\n      <th>pixel4</th>\n      <th>pixel5</th>\n      <th>pixel6</th>\n      <th>pixel7</th>\n      <th>pixel8</th>\n      <th>...</th>\n      <th>pixel774</th>\n      <th>pixel775</th>\n      <th>pixel776</th>\n      <th>pixel777</th>\n      <th>pixel778</th>\n      <th>pixel779</th>\n      <th>pixel780</th>\n      <th>pixel781</th>\n      <th>pixel782</th>\n      <th>pixel783</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 785 columns</p>\n</div>"},"metadata":{}}],"execution_count":1},{"cell_type":"code","source":"label = train['label']\ntrain.drop('label', inplace = True, axis = \"columns\")\nprint(label.shape)\nprint(label.head())\nprint(train.shape)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:40:27.652633Z","iopub.execute_input":"2024-04-28T13:40:27.653003Z","iopub.status.idle":"2024-04-28T13:40:27.779896Z","shell.execute_reply.started":"2024-04-28T13:40:27.652974Z","shell.execute_reply":"2024-04-28T13:40:27.778742Z"},"trusted":true},"outputs":[{"name":"stdout","text":"(60000,)\n0    0\n1    1\n2    2\n3    3\n4    4\nName: label, dtype: int64\n(60000, 784)\n","output_type":"stream"}],"execution_count":2},{"cell_type":"code","source":"import torch\nimport torchvision\nimport torch.nn as nn\nfrom torch.utils.data import TensorDataset, Dataset, DataLoader, Subset, random_split\nfrom sklearn.model_selection import train_test_split\nfrom torchvision import transforms, models\nimport torch.optim as optim\nfrom torch.optim import lr_scheduler\nfrom torchvision.transforms import v2\n\nimport matplotlib.pyplot as plt","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:40:30.030512Z","iopub.execute_input":"2024-04-28T13:40:30.030934Z","iopub.status.idle":"2024-04-28T13:40:38.763735Z","shell.execute_reply.started":"2024-04-28T13:40:30.030903Z","shell.execute_reply":"2024-04-28T13:40:38.762652Z"},"trusted":true},"outputs":[],"execution_count":3},{"cell_type":"code","source":"train_tensor = torch.tensor(train.to_numpy() / 255, dtype=torch.float32)\nlabel_tensor = torch.tensor(label.to_numpy(), dtype=torch.int64)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:40:48.203239Z","iopub.execute_input":"2024-04-28T13:40:48.203984Z","iopub.status.idle":"2024-04-28T13:40:48.480752Z","shell.execute_reply.started":"2024-04-28T13:40:48.203942Z","shell.execute_reply":"2024-04-28T13:40:48.479479Z"},"trusted":true},"outputs":[],"execution_count":4},{"cell_type":"code","source":"plt.figure(figsize=(4, 4))\nplt.imshow(train_tensor[99].reshape(28, 28), cmap=\"binary\")\nplt.title(f'Target label for this image: {label_tensor[99]}')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:40:59.388743Z","iopub.execute_input":"2024-04-28T13:40:59.389173Z","iopub.status.idle":"2024-04-28T13:40:59.757456Z","shell.execute_reply.started":"2024-04-28T13:40:59.38914Z","shell.execute_reply":"2024-04-28T13:40:59.75591Z"},"trusted":true},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 400x400 with 1 Axes>","image/png":"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"},"metadata":{}}],"execution_count":5},{"cell_type":"code","source":"train_tensor = train_tensor.reshape(train_tensor.shape[0], 28, 28)\nprint(train_tensor.shape)\ntrain_tensor = torch.unsqueeze(train_tensor, 1)\nprint(train_tensor.shape)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:41:13.982679Z","iopub.execute_input":"2024-04-28T13:41:13.983285Z","iopub.status.idle":"2024-04-28T13:41:14.004439Z","shell.execute_reply.started":"2024-04-28T13:41:13.983244Z","shell.execute_reply":"2024-04-28T13:41:14.002724Z"},"trusted":true},"outputs":[{"name":"stdout","text":"torch.Size([60000, 28, 28])\ntorch.Size([60000, 1, 28, 28])\n","output_type":"stream"}],"execution_count":6},{"cell_type":"code","source":"mnist_dataset = TensorDataset(train_tensor, label_tensor) ","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:41:27.236807Z","iopub.execute_input":"2024-04-28T13:41:27.237254Z","iopub.status.idle":"2024-04-28T13:41:27.243303Z","shell.execute_reply.started":"2024-04-28T13:41:27.237221Z","shell.execute_reply":"2024-04-28T13:41:27.242104Z"},"trusted":true},"outputs":[],"execution_count":7},{"cell_type":"code","source":"training_set, validation_set = random_split(mnist_dataset, [50000, 10000], generator=torch.Generator().manual_seed(1))\n\nbatch_size = 256\ntorch.manual_seed(1)\n\ntrain_dl = DataLoader(training_set, batch_size, shuffle=True)\nvalid_dl = DataLoader(validation_set, batch_size, shuffle=True)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:41:43.354728Z","iopub.execute_input":"2024-04-28T13:41:43.355152Z","iopub.status.idle":"2024-04-28T13:41:43.370648Z","shell.execute_reply.started":"2024-04-28T13:41:43.355119Z","shell.execute_reply":"2024-04-28T13:41:43.369255Z"},"trusted":true},"outputs":[],"execution_count":9},{"cell_type":"code","source":"class Block(nn.Module):\n    \n    def __init__(self, in_channels, out_channels, identity_downsample=None, stride=1):\n        super(Block, self).__init__()\n        self.conv1 = nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=stride, padding=1)\n        self.bn1 = nn.BatchNorm2d(out_channels)\n        self.conv2 = nn.Conv2d(out_channels, out_channels, kernel_size=3, stride=1, padding=1)\n        self.bn2 = nn.BatchNorm2d(out_channels)\n        self.relu = nn.ReLU()\n        self.identity_downsample = identity_downsample\n        \n    def forward(self, x):\n        identity = x\n        x = self.conv1(x)\n        x = self.bn1(x)\n        x = self.relu(x)\n        x = self.conv2(x)\n        x = self.bn2(x)\n        if self.identity_downsample is not None:\n            identity = self.identity_downsample(identity)\n        x += identity\n        x = self.relu(x)\n        return x","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:41:57.855665Z","iopub.execute_input":"2024-04-28T13:41:57.856051Z","iopub.status.idle":"2024-04-28T13:41:57.867734Z","shell.execute_reply.started":"2024-04-28T13:41:57.856022Z","shell.execute_reply":"2024-04-28T13:41:57.866356Z"},"trusted":true},"outputs":[],"execution_count":10},{"cell_type":"code","source":"class ResNet_18(nn.Module):\n    \n    def __init__(self, image_channels, num_classes):\n        \n        super(ResNet_18, self).__init__()\n        self.in_channels = 64\n        self.conv1 = nn.Conv2d(image_channels, 64, kernel_size=7, stride=2, padding=3)\n        self.bn1 = nn.BatchNorm2d(64)\n        self.relu = nn.ReLU()\n        self.maxpool = nn.MaxPool2d(kernel_size=3, stride=2, padding=1)\n        \n        #resnet layers\n        self.layer1 = self.__make_layer(64, 64, stride=1)\n        self.layer2 = self.__make_layer(64, 128, stride=2)\n        self.layer3 = self.__make_layer(128, 256, stride=2)\n        self.layer4 = self.__make_layer(256, 512, stride=2)\n        \n        self.avgpool = nn.AdaptiveAvgPool2d((1, 1))\n        self.fc = nn.Linear(512, num_classes)\n        \n    def __make_layer(self, in_channels, out_channels, stride):\n        \n        identity_downsample = None\n        if stride != 1:\n            identity_downsample = self.identity_downsample(in_channels, out_channels)\n            \n        return nn.Sequential(\n            Block(in_channels, out_channels, identity_downsample=identity_downsample, stride=stride), \n            Block(out_channels, out_channels)\n        )\n        \n    def forward(self, x):\n        \n        x = self.conv1(x)\n        x = self.bn1(x)\n        x = self.relu(x)\n        x = self.maxpool(x)\n        \n        x = self.layer1(x)\n        x = self.layer2(x)\n        x = self.layer3(x)\n        x = self.layer4(x)\n        \n        x = self.avgpool(x)\n        x = x.view(x.shape[0], -1)\n        x = self.fc(x)\n        return x \n    \n    def identity_downsample(self, in_channels, out_channels):\n        \n        return nn.Sequential(\n            nn.Conv2d(in_channels, out_channels, kernel_size=3, stride=2, padding=1), \n            nn.BatchNorm2d(out_channels)\n        )","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:42:12.155116Z","iopub.execute_input":"2024-04-28T13:42:12.155598Z","iopub.status.idle":"2024-04-28T13:42:12.173244Z","shell.execute_reply.started":"2024-04-28T13:42:12.155548Z","shell.execute_reply":"2024-04-28T13:42:12.171799Z"},"trusted":true},"outputs":[],"execution_count":11},{"cell_type":"code","source":"model_ft = ResNet_18(1,10)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:42:26.595004Z","iopub.execute_input":"2024-04-28T13:42:26.595475Z","iopub.status.idle":"2024-04-28T13:42:26.737491Z","shell.execute_reply.started":"2024-04-28T13:42:26.595411Z","shell.execute_reply":"2024-04-28T13:42:26.736305Z"},"trusted":true},"outputs":[],"execution_count":12},{"cell_type":"code","source":"loss_fn = nn.CrossEntropyLoss()\noptimizer = torch.optim.Adam(model_ft.parameters(), lr=0.001)\nnum_epochs = 10","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:42:47.925562Z","iopub.execute_input":"2024-04-28T13:42:47.926018Z","iopub.status.idle":"2024-04-28T13:42:47.9352Z","shell.execute_reply.started":"2024-04-28T13:42:47.925986Z","shell.execute_reply":"2024-04-28T13:42:47.93362Z"},"trusted":true},"outputs":[],"execution_count":14},{"cell_type":"code","source":"def train(model, num_epochs, train_dl, valid_dl):\n\n    loss_hist_train = [0] * num_epochs\n    accuracy_hist_train = [0] * num_epochs\n    loss_hist_valid = [0] * num_epochs\n    accuracy_hist_valid = [0] * num_epochs\n    \n    for epoch in range(num_epochs):\n        \n        model.train()\n\n        for x_batch, y_batch in train_dl:\n\n            pred = model(x_batch)   # Get predicted values for this batch       \n            loss = loss_fn(pred, y_batch)   # Calculate the loss\n            loss.backward()   # Compute gradients\n            optimizer.step()   # Update parameters\n            optimizer.zero_grad()   # Reset grads to zero\n            #exp_lr_scheduler.step()\n            loss_hist_train[epoch] += loss.item()*y_batch.size(0)    \n            \n            is_correct = (torch.argmax(pred, dim=1) == y_batch).float()   \n            \n            accuracy_hist_train[epoch] += is_correct.sum()    \n\n        loss_hist_train[epoch] /= len(train_dl.dataset)    \n        accuracy_hist_train[epoch] /= len(train_dl.dataset)    \n        \n        \n        \n        # Put model in eval mode for evaluating on validation set\n        model.eval()  \n        \n        with torch.no_grad():  \n            for x_batch, y_batch in valid_dl:\n\n                pred = model(x_batch)\n                loss = loss_fn(pred, y_batch)\n                loss_hist_valid[epoch] += loss.item()*y_batch.size(0)\n                is_correct = (torch.argmax(pred, dim=1) == y_batch).float()\n                accuracy_hist_valid[epoch] += is_correct.sum()\n                \n        loss_hist_valid[epoch] /= len(valid_dl.dataset)\n        accuracy_hist_valid[epoch] /= len(valid_dl.dataset)\n                \n        print(f'Epoch {epoch + 1}    Train Accuracy: {accuracy_hist_train[epoch]:.4f}    Validation Accuracy: {accuracy_hist_valid[epoch]:.4f}     Train Loss: {loss_hist_train[epoch]:.4f}    Validation Loss: {loss_hist_valid[epoch]:.4f} ')\n        \n    return loss_hist_train, loss_hist_valid, accuracy_hist_train, accuracy_hist_valid","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:43:40.166208Z","iopub.execute_input":"2024-04-28T13:43:40.166689Z","iopub.status.idle":"2024-04-28T13:43:40.195732Z","shell.execute_reply.started":"2024-04-28T13:43:40.16665Z","shell.execute_reply":"2024-04-28T13:43:40.194228Z"},"trusted":true},"outputs":[],"execution_count":15},{"cell_type":"code","source":"hist = train(model_ft, num_epochs, train_dl, valid_dl)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T13:43:56.976734Z","iopub.execute_input":"2024-04-28T13:43:56.977151Z","iopub.status.idle":"2024-04-28T14:40:16.729528Z","shell.execute_reply.started":"2024-04-28T13:43:56.97712Z","shell.execute_reply":"2024-04-28T14:40:16.728266Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Epoch 1    Train Accuracy: 0.9662    Validation Accuracy: 0.9878     Train Loss: 0.1072    Validation Loss: 0.0377 \nEpoch 2    Train Accuracy: 0.9901    Validation Accuracy: 0.9897     Train Loss: 0.0313    Validation Loss: 0.0323 \nEpoch 3    Train Accuracy: 0.9915    Validation Accuracy: 0.9885     Train Loss: 0.0266    Validation Loss: 0.0385 \nEpoch 4    Train Accuracy: 0.9939    Validation Accuracy: 0.9900     Train Loss: 0.0191    Validation Loss: 0.0327 \nEpoch 5    Train Accuracy: 0.9950    Validation Accuracy: 0.9874     Train Loss: 0.0158    Validation Loss: 0.0476 \nEpoch 6    Train Accuracy: 0.9956    Validation Accuracy: 0.9901     Train Loss: 0.0149    Validation Loss: 0.0289 \nEpoch 7    Train Accuracy: 0.9961    Validation Accuracy: 0.9938     Train Loss: 0.0116    Validation Loss: 0.0213 \nEpoch 8    Train Accuracy: 0.9954    Validation Accuracy: 0.9944     Train Loss: 0.0143    Validation Loss: 0.0196 \nEpoch 9    Train Accuracy: 0.9975    Validation Accuracy: 0.9820     Train Loss: 0.0077    Validation Loss: 0.0690 \nEpoch 10    Train Accuracy: 0.9971    Validation Accuracy: 0.9889     Train Loss: 0.0084    Validation Loss: 0.0412 \n","output_type":"stream"}],"execution_count":16},{"cell_type":"code","source":"testing = pd.read_csv(\"../input/Kannada-MNIST/Dig-MNIST.csv\")\n","metadata":{"execution":{"iopub.status.busy":"2024-04-28T14:44:45.747112Z","iopub.execute_input":"2024-04-28T14:44:45.747953Z","iopub.status.idle":"2024-04-28T14:44:46.791105Z","shell.execute_reply.started":"2024-04-28T14:44:45.747915Z","shell.execute_reply":"2024-04-28T14:44:46.789925Z"},"trusted":true},"outputs":[],"execution_count":17},{"cell_type":"code","source":"test_labels = testing['label']\ntesting.drop('label', inplace = True, axis = \"columns\")\nprint(test_labels.shape)\nprint(test_labels.head())\nprint(testing.shape)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T14:45:26.5808Z","iopub.execute_input":"2024-04-28T14:45:26.581857Z","iopub.status.idle":"2024-04-28T14:45:26.611929Z","shell.execute_reply.started":"2024-04-28T14:45:26.58182Z","shell.execute_reply":"2024-04-28T14:45:26.610771Z"},"trusted":true},"outputs":[{"name":"stdout","text":"(10240,)\n0    0\n1    1\n2    2\n3    3\n4    4\nName: label, dtype: int64\n(10240, 784)\n","output_type":"stream"}],"execution_count":18},{"cell_type":"code","source":"\ntest_tensor = torch.tensor(testing.to_numpy() / 255, dtype=torch.float32)\ntest_tensor = test_tensor.reshape(test_tensor.shape[0], 28, 28)\ntest_tensor = torch.unsqueeze(test_tensor, 1)\ntest_tensor.shape","metadata":{"execution":{"iopub.status.busy":"2024-04-28T14:46:58.327736Z","iopub.execute_input":"2024-04-28T14:46:58.328128Z","iopub.status.idle":"2024-04-28T14:46:58.392612Z","shell.execute_reply.started":"2024-04-28T14:46:58.328099Z","shell.execute_reply":"2024-04-28T14:46:58.39154Z"},"trusted":true},"outputs":[{"execution_count":19,"output_type":"execute_result","data":{"text/plain":"torch.Size([10240, 1, 28, 28])"},"metadata":{}}],"execution_count":19},{"cell_type":"code","source":"test_predicted_logits = model_ft(test_tensor)\ntest_predicted_logits.shape","metadata":{"execution":{"iopub.status.busy":"2024-04-28T14:47:27.147938Z","iopub.execute_input":"2024-04-28T14:47:27.14835Z","iopub.status.idle":"2024-04-28T14:47:44.407164Z","shell.execute_reply.started":"2024-04-28T14:47:27.148321Z","shell.execute_reply":"2024-04-28T14:47:44.406248Z"},"trusted":true},"outputs":[{"execution_count":20,"output_type":"execute_result","data":{"text/plain":"torch.Size([10240, 10])"},"metadata":{}}],"execution_count":20},{"cell_type":"code","source":"print(test_predicted_logits[:5])\ntest_predicted_classes = torch.argmax(test_predicted_logits, dim=1)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T14:47:47.072742Z","iopub.execute_input":"2024-04-28T14:47:47.073175Z","iopub.status.idle":"2024-04-28T14:47:47.098655Z","shell.execute_reply.started":"2024-04-28T14:47:47.073143Z","shell.execute_reply":"2024-04-28T14:47:47.097308Z"},"trusted":true},"outputs":[{"name":"stdout","text":"tensor([[ 7.8878,  0.3374,  0.7766, -3.3729, -4.2620, -5.3297, -4.0142, -3.4418,\n         -1.6474, -2.8315],\n        [ 5.3541,  8.4807, -2.1146, -5.5616, -5.8413, -6.5263, -4.6022, -4.2744,\n         -4.2298, -4.3427],\n        [-1.3114, -2.8759, 19.0024, -1.5388, -4.5712, -4.6794, -4.6055, -4.1602,\n         -4.1659, -8.4738],\n        [-2.1511, -4.2236, -2.5442, 11.8482, -2.6329,  1.7191, -4.4562, -1.2856,\n         -6.5566, -6.7386],\n        [-7.0375, -6.6811, -5.0387, -5.1051, 18.4676, -2.7594, -4.2193, -8.0499,\n          1.7702, -1.7526]], grad_fn=<SliceBackward0>)\n","output_type":"stream"}],"execution_count":21},{"cell_type":"code","source":"from sklearn.metrics import confusion_matrix, accuracy_score\n\n\ncm = confusion_matrix(test_labels, test_predicted_classes)\nprint(\"Confusion Matrix:\")\nprint(cm)","metadata":{"execution":{"iopub.status.busy":"2024-04-28T14:52:55.638804Z","iopub.execute_input":"2024-04-28T14:52:55.639262Z","iopub.status.idle":"2024-04-28T14:52:55.652397Z","shell.execute_reply.started":"2024-04-28T14:52:55.639228Z","shell.execute_reply":"2024-04-28T14:52:55.651039Z"},"trusted":true},"outputs":[{"name":"stdout","text":"Confusion Matrix:\n[[574  46  58  10   5  18 197   3  46  67]\n [ 60 846  61   2  18  10   0  16   6   5]\n [  9   4 964   1   6  10  18   4   8   0]\n [  9   6 141 433  44 287  53  48   1   2]\n [  2   6  36   0 778  14  10   3 153  22]\n [  0   5  13   1  24 908   1   2  70   0]\n [  4   3  25   0  54  37 854  13  18  16]\n [  2   1  55   1   4  19 349 581   8   4]\n [  3   3  41   0   2   7  43   1 922   2]\n [  0   6  12   0   0   1  81   0 142 782]]\n","output_type":"stream"}],"execution_count":24},{"cell_type":"markdown","source":"### We can say Resnet18 is perfoming well with the fusion of CNN and optimizing with Genetic Algorithm based on the score","metadata":{}}]}