import tensorflow as tf import matplotlib . pyplot as plt from tensorflow.keras import datasets, layers, models, losses ( x_train , y_train ), ( x_test , y_test )= tf .keras.datasets.mnist.load_data() x_train = tf .pad( x_train , [[ 0 , 0 ], [ 2 , 2 ], [ 2 , 2 ]])/ 255 x_test = tf .pad( x_test , [[ 0 , 0 ], [ 2 , 2 ], [ 2 , 2 ]])/ 255 x_train = tf .expand_dims( x_train , axis = 3 , name = None ) x_test = tf .expand_dims( x_test , axis = 3 , name = None ) x_train = tf .repeat( x_train , 3 , axis = 3 ) x_test = tf .repeat( x_test , 3 , axis = 3 ) x_val = x_train [- 2000 :,:,:,:] y_val = y_train [- 2000 :] x_train = x_train [:- 2000 ,:,:,:] y_train = y_train [:- 2000 ] def inception ( x , filters_1x1 , filters_3x3_reduce , filters_3x3 , filters_5x5_reduce , filters_5x5 , filters_pool ): path1 = layers.Conv2D( filters_1x1 , ( 1 , 1 ), padding = 'same' , activation = 'relu' )( x ) path2 = layers.Conv2D( filters_3...
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