5a6928a1c19fa0756cec6340224434c0a9f37367,opennmt/layers/transformer.py,,combine_heads,#Any#,89

Before Change

  depth = static_shape[-1]
  num_heads = static_shape[1]
  outputs = tf.transpose(inputs, perm=[0, 2, 1, 3])
  outputs = tf.reshape(outputs, [tf.shape(outputs)[0], tf.shape(outputs)[1], depth * num_heads])
  return outputs

def dot_product_attention(queries,

After Change

  Returns:
    A ``tf.Tensor`` of shape :math:`[B, T, D * H]`.
  
  shape = misc.shape_list(inputs)
  outputs = tf.transpose(inputs, perm=[0, 2, 1, 3])
  outputs = tf.reshape(outputs, [shape[0], shape[2], shape[1] * shape[3]])
  return outputs

Instances