Machine Learning, Data Science, Deep Learning, Artificial Intelligence, Towards Data Science.
kernel_size=kernel, strides=2, padding='same')(model) model = Activation('tanh')(model) model = Model(X, model) model.compile(loss='binary_crossentropy', optimizer=Adam(lr=0.0001, beta_1=0.5), metrics=['accuracy']) return model def discriminator(kernel, filter, rows, columns, channel): X =