W3cubDocs

/TensorFlow Python

tf.contrib.crf.crf_sequence_score(inputs, tag_indices, sequence_lengths, transition_params)

tf.contrib.crf.crf_sequence_score(inputs, tag_indices, sequence_lengths, transition_params)

See the guide: CRF (contrib)

Computes the unnormalized score for a tag sequence.

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 unnormalized score.
  • sequence_lengths: A [batch_size] vector of true sequence lengths.
  • transition_params: A [num_tags, num_tags] transition matrix. Returns:
  • sequence_scores: A [batch_size] vector of unnormalized sequence scores.

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

© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/contrib/crf/crf_sequence_score