(episode_representation)
return tf.repeat(dataset_ids, repeats)
Decompresses an episode representation into a dataset ID stream.

  Args:
    episode_representation: tensor of shape [None, 2]. Its first column
      represents dataset IDs and its second column represents the number of
      times they're repeated in the sequence.

  Returns:
    1D tensor, decompressed sequence of dataset IDs.
Decompresses an episode representation into a dataset ID stream.
Decompresses an episode representation into a dataset ID stream .
def decompress_episode_representation(episode_representation):
  """Decompresses an episode representation into a dataset ID stream.

  Args:
    episode_representation: tensor of shape [None, 2]. Its first column
      represents dataset IDs and its second column represents the number of
      times they're repeated in the sequence.

  Returns:
    1D tensor, decompressed sequence of dataset IDs.
  """
  episode_representation.set_shape([None, 2])
  dataset_ids, repeats = tf.unstack(episode_representation, axis=1)
  return tf.repeat(dataset_ids, repeats)
def decompress_episode_representation ( episode_representation ) : episode_representation . set_shape ( [ None , 2 ] ) dataset_ids , repeats = tf . unstack ( episode_representation , axis = 1 ) return tf . repeat ( dataset_ids , repeats )