Warning: This project is deprecated. TensorFlow Addons has stopped development, The project will only be providing minimal maintenance releases until May 2024. See the full announcement here or on github.


Computes the unnormalized score of all tag sequences matching tag_bitmap.

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.

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.

sequence_scores A [batch_size] vector of unnormalized sequence scores.