model.py

def model():
    model = Sequential()

    model.add(Conv2D(128, (3, 3), input_shape=x_train.shape[1:]))
    model.add(LeakyReLU(alpha=0.02))
    
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Dropout(0.25))

    model.add(Conv2D(128, (3, 3)))
    model.add(LeakyReLU(alpha=0.02))
    
    model.add(MaxPooling2D(pool_size=(2, 2)))
    model.add(Dropout(0.25))

    model.add(GlobalMaxPooling2D())
    
    model.add(Dense(512))
    model.add(LeakyReLU(alpha=0.02))
    model.add(Dropout(0.5)) 

    model.add(Dense(10))
    model.add(Activation('softmax'))
    
    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
    
    return model

model = model()