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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def time_to_channels(embedded_video):
 """Put time dimension on channels in an 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]
  ])