def testCrfUnaryScore(self):
inputs = np.array([[4, 5, -3], [3, -1, 3], [-1, 2, 1], [0, 0, 0]],
dtype=np.float32)
tag_indices = np.array([1, 2, 1, 0], dtype=np.int32)
sequence_lengths = np.array(3, dtype=np.int32)
with self.test_session() as sess:
unary_score = crf.crf_unary_score(
tag_indices=array_ops.expand_dims(tag_indices, 0),
sequence_lengths=array_ops.expand_dims(sequence_lengths, 0),
inputs=array_ops.expand_dims(inputs, 0))
unary_score = array_ops.squeeze(unary_score, [0])
tf_unary_score = sess.run(unary_score)
expected_unary_score = sum(inputs[i][tag_indices[i]]
for i in range(sequence_lengths))
self.assertAllClose(tf_unary_score, expected_unary_score)
def testCrfUnaryScore(self):
inputs = np.array(
[[4, 5, -3], [3, -1, 3], [-1, 2, 1], [0, 0, 0]], dtype=np.float32)
tag_indices = np.array([1, 2, 1, 0], dtype=np.int32)
sequence_lengths = np.array(3, dtype=np.int32)
with self.test_session() as sess:
unary_score = crf.crf_unary_score(
tag_indices=array_ops.expand_dims(tag_indices, 0),
sequence_lengths=array_ops.expand_dims(sequence_lengths, 0),
inputs=array_ops.expand_dims(inputs, 0))
unary_score = array_ops.squeeze(unary_score, [0])
tf_unary_score = sess.run(unary_score)
expected_unary_score = sum(inputs[i][tag_indices[i]]
for i in range(sequence_lengths))
self.assertAllClose(tf_unary_score, expected_unary_score)
def crf_sequence_score(inputs, tag_indices, sequence_lengths, transitions):
"""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.
"""
# Compute the scores of the given tag sequence.
unary_scores = crf_unary_score(tag_indices, sequence_lengths, inputs)
binary_scores = crf_binary_score(tag_indices, sequence_lengths,
transitions)
sequence_scores = unary_scores + binary_scores
return sequence_scores