crf.py 文件源码

def crf_binary_score(tag_indices, sequence_lengths, transition_params):
  """Computes the binary scores of tag sequences.

  Args:
    tag_indices: A [batch_size, max_seq_len] matrix of tag indices.
    sequence_lengths: A [batch_size] vector of true sequence lengths.
    transition_params: A [num_tags, num_tags] matrix of binary potentials.
  Returns:
    binary_scores: A [batch_size] vector of binary scores.
  """
  # Get shape information.
  num_tags = transition_params.get_shape()[0]
  num_transitions = array_ops.shape(tag_indices)[1] - 1

  # Truncate by one on each side of the sequence to get the start and end
  # indices of each transition.
  start_tag_indices = array_ops.slice(tag_indices, [0, 0],
                                      [-1, num_transitions])
  end_tag_indices = array_ops.slice(tag_indices, [0, 1], [-1, num_transitions])

  # Encode the indices in a flattened representation.
  flattened_transition_indices = start_tag_indices * num_tags + end_tag_indices
  flattened_transition_params = array_ops.reshape(transition_params, [-1])

  # Get the binary scores based on the flattened representation.
  binary_scores = array_ops.gather(flattened_transition_params,
                                   flattened_transition_indices)

  masks = _lengths_to_masks(sequence_lengths, array_ops.shape(tag_indices)[1])
  truncated_masks = array_ops.slice(masks, [0, 1], [-1, -1])
  binary_scores = math_ops.reduce_sum(binary_scores * truncated_masks, 1)
  return binary_scores