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model.add(BatchNormalization()) # Leaky ReLU model.add(LeakyReLU(alpha=0.01)) # Transposed convolution layer, from 14x14x64 to 28x28x1 tensor model.add(Conv2DTranspose( 1, kernel_size = 3, strides = 2, padding='same')) # Tanh activation model.add(Activation('tanh')) z = Input(shape=(z_dim,)) img =