code: def time_to_channels(embedded_video):
    
    video_shape = common_layers.shape_list(embedded_video)
    if len(video_shape) != 5:
      raise ValueError("Assuming videos given as tensors in the format "
                       "[batch, time, height, width, channels] but got one "
                       "of shape: %s" % str(video_shape))
    transposed = tf.transpose(embedded_video, [0, 2, 3, 1, 4])
    return tf.reshape(transposed, [
        video_shape[0], video_shape[2], video_shape[3],
        video_shape[1] * video_shape[4]
    ])
docs: Put time dimension on channels in an embedded video.