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from tensorflow.keras.layers import BatchNormalization, Dense, Dropout, Flatten, Conv2D, MaxPooling2D

from tensorflow.keras.models import Sequential

model = Sequential([Conv2D(16, (3, 3), padding='same', activation='relu', input_shape=(28, 28, 1)), BatchNormalization(), Conv2D(32, (3, 3), padding='same', activation='relu'), BatchNormalization(), MaxPooling2D(2, 2), Dropout(0.25), Conv2D(64, (3, 3), padding='same', activation='relu'), BatchNormalization(), MaxPooling2D(2, 2), Conv2D(128, (3, 3), padding='same', activation='relu'), BatchNormalization(), MaxPooling2D(2, 2), Flatten(), Dense(256, activation='relu'), BatchNormalization(), Dropout(0.25), Dense(10, activation='softmax')])
model.summary()