generator_output.py

def generator_output(sess, n_images, input_z, output_channel_dim, image_mode, image_path):
    """
    Save output from the generator.
    
    Arguments:
    ----------
    :param sess: TensorFlow session
    :param n_images: Number of Images to display
    :param input_z: Input Z Tensor (noise vector)
    :param output_channel_dim: The number of channels in the output image
    :param image_mode: The mode to use for images ("RGB" or "L")
    :param image_path: Path to save the generated image
    ----------
    """
    cmap = None if image_mode == 'RGB' else 'gray'
    z_dimension = input_z.get_shape().as_list()[-1]
    example_z = np.random.uniform(-1, 1, size=[n_images, z_dimension])

    samples = sess.run(
        build_generator(input_z, output_channel_dim, False),
        feed_dict={input_z: example_z})

    images_grid = helper.images_square_grid(samples, image_mode)
    
    # Save image to the image path
    images_grid.save(image_path, 'JPEG')