tf.contrib.crf.crf_multitag_sequence_score
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 | |
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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 | |
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sequence_scores | A [batch_size] vector of unnormalized sequence scores. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/crf/crf_multitag_sequence_score