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tf.contrib.crf.crf_multitag_sequence_score

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Computes the unnormalized score of all tag sequences matching tag_bitmap.

tf.contrib.crf.crf_multitag_sequence_score(
    inputs,
    tag_bitmap,
    sequence_lengths,
    transition_params
)

tag_bitmap enables more than one tag to be considered correct at each time step. This is useful when an observed output at a given time step is consistent with more than one tag, and thus the log likelihood of that observation must take into account all possible consistent tags.

Using one-hot vectors in tag_bitmap gives results identical to crf_sequence_score.

Args:

  • inputs: A [batch_size, max_seq_len, num_tags] tensor of unary potentials to use as input to the CRF layer.
  • tag_bitmap: A [batch_size, max_seq_len, num_tags] boolean tensor representing all active tags at each index for which to calculate 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.