tf.contrib.crf.crf_log_likelihood(inputs, tag_indices, sequence_lengths, transition_params=None)

tf.contrib.crf.crf_log_likelihood(inputs, tag_indices, sequence_lengths, transition_params=None)

See the guide: CRF (contrib)

Computes the log-likelihood of tag sequences in a CRF.

Args:

  • inputs: A [batch_size, max_seq_len, num_tags] tensor of unary potentials to use as input to the CRF layer.
  • tag_indices: A [batch_size, max_seq_len] matrix of tag indices for which we compute the log-likelihood.
  • sequence_lengths: A [batch_size] vector of true sequence lengths.
  • transition_params: A [num_tags, num_tags] transition matrix, if available. Returns:
  • log_likelihood: A scalar containing the log-likelihood of the given sequence of tag indices.
  • transition_params: A [num_tags, num_tags] transition matrix. This is either provided by the caller or created in this function.

Defined in tensorflow/contrib/crf/python/ops/crf.py.