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Computes the unnormalized score of all tag sequences matching
tfa.text.crf_multitag_sequence_score(
inputs: tfa.types.TensorLike
,
tag_bitmap: tfa.types.TensorLike
,
sequence_lengths: tfa.types.TensorLike
,
transition_params: tfa.types.TensorLike
) -> tf.Tensor
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.
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. |