8eff453c5032faea52c82edd2365371a42643687,opennmt/layers/transformer.py,,build_future_mask,#Any#Any#Any#Any#,47

Before Change

    sequence_length = tile_sequence_length(sequence_length, num_heads)
  if maximum_length is None:
    maximum_length = tf.reduce_max(sequence_length)
  mask = tf.map_fn(
      lambda x: tf.sequence_mask(
          tf.minimum(tf.range(maximum_length) + 1, x),
          maxlen=maximum_length,
          dtype=dtype),
      sequence_length,
      dtype=dtype)
  if num_heads is not None:
    mask = tf.reshape(mask, [-1, num_heads, tf.shape(mask)[1], tf.shape(mask)[2]])
  return mask

After Change

  sequence_mask = tf.sequence_mask(sequence_length, maxlen=maximum_length, dtype=dtype)
  shape = tf.shape(sequence_mask)
  batch_size = shape[0]
  max_time = shape[1]
  mask = tf.ones([batch_size, max_time, max_time], dtype=dtype)
  mask = tf.matrix_band_part(mask, -1, 0)
  mask *= tf.expand_dims(sequence_mask, axis=1)
  if num_heads is not None:

Instances