def testCrfUnaryScore(self):
inputs = np.array([[4, 5, -3], [3, -1, 3], [-1, 2, 1], [0, 0, 0]],
dtype=np.float32)
for dtype in (np.int32, np.int64):
tag_indices = np.array([1, 2, 1, 0], dtype=dtype)
sequence_lengths = np.array(3, dtype=np.int32)
unary_score = text.crf_unary_score(
tag_indices=tf.expand_dims(tag_indices, 0),
sequence_lengths=tf.expand_dims(sequence_lengths, 0),
inputs=tf.expand_dims(inputs, 0))
unary_score = tf.squeeze(unary_score, [0])
tf_unary_score = self.evaluate(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 test_crf_unary_score(dtype):
inputs = np.array([[4, 5, -3], [3, -1, 3], [-1, 2, 1], [0, 0, 0]], dtype=dtype)
for dtype in (np.int32, np.int64):
tag_indices = np.array([1, 2, 1, 0], dtype=dtype)
sequence_lengths = np.array(3, dtype=np.int32)
unary_score = text.crf_unary_score(
tag_indices=tf.expand_dims(tag_indices, 0),
sequence_lengths=tf.expand_dims(sequence_lengths, 0),
inputs=tf.expand_dims(inputs, 0),
)
unary_score = tf.squeeze(unary_score, [0])
expected_unary_score = sum(
inputs[i][tag_indices[i]] for i in range(sequence_lengths)
)
test_utils.assert_allclose_according_to_type(unary_score, expected_unary_score)