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kernel_constraint=max_norm(max_norm_value), activation='sigmoid', padding='same')) model.summary() # Compile and fit data model.compile(optimizer='adam', loss='binary_crossentropy') model.fit(noisy_input, pure_input, epochs=no_epochs, batch_size=batch_size, validation_split=validation_split) #