44ae6129731ee1d225db8a5f1bafea5fd4b9b542,open_seq2seq/parts/transformer/utils.py,,get_position_encoding,#Any#Any#Any#Any#,28

Before Change

  num_timescales = hidden_size // 2
  log_timescale_increment = (
      math.log(float(max_timescale) / float(min_timescale)) /
      (tf.to_float(num_timescales) - 1))
  inv_timescales = min_timescale * tf.exp(
      tf.to_float(tf.range(num_timescales)) * -log_timescale_increment)
  scaled_time = tf.expand_dims(position, 1) * tf.expand_dims(inv_timescales, 0)

After Change

  Returns:
    Tensor with shape [length, hidden_size]
  
  position = tf.cast(tf.range(length),dtype=tf.float32)
  num_timescales = hidden_size // 2
  log_timescale_increment = (
      math.log(float(max_timescale) / float(min_timescale)) /
      (tf.cast((num_timescales) - 1, dtype=tf.float32)))
  inv_timescales = min_timescale * tf.exp(
      tf.cast(tf.range(num_timescales),dtype=tf.float32 ) * -log_timescale_increment)
  scaled_time = tf.expand_dims(position, 1) * tf.expand_dims(inv_timescales, 0)

Instances