def testSplitTFIDFWithEmptyInput(self):
with tf.Graph().as_default():
tfidf = tf.SparseTensor(
values=tf.constant([], shape=[0], dtype=tf.float32),
indices=tf.constant([], shape=[0, 2], dtype=tf.int64),
dense_shape=[2, 0])
_, weights = mappers._split_tfidfs_to_outputs(tfidf)
with self.test_session() as sess:
weights_shape = sess.run(weights.dense_shape)
self.assertAllEqual(weights_shape, [2, 0])
def testSplitTFIDFWithEmptyInput(self):
# TODO(b/123242111): rewrite this test using public functions.
with tf.compat.v1.Graph().as_default():
tfidf = tf.SparseTensor(
values=tf.constant([], shape=[0], dtype=tf.float32),
indices=tf.constant([], shape=[0, 2], dtype=tf.int64),
dense_shape=[2, 0])
_, weights = mappers._split_tfidfs_to_outputs(tfidf)
with self.test_session() as sess:
weights_shape = sess.run(weights.dense_shape)
self.assertAllEqual(weights_shape, [2, 0])
def testSplitTFIDF(self):
tfidfs = tf.SparseTensor(
[[0, 0], [0, 1], [2, 1], [2, 2]],
[0.23104906, 0.19178806, 0.14384104, 0.34657359], [3, 4])
out_index, out_weight = mappers._split_tfidfs_to_outputs(tfidfs)
self.assertSparseOutput(expected_indices=[[0, 0], [0, 1], [2, 0],
[2, 1]],
expected_values=[0, 1, 1, 2],
expected_shape=[3, 2],
actual_sparse_tensor=out_index,
close_values=False)
self.assertSparseOutput(
expected_indices=[[0, 0], [0, 1], [2, 0], [2, 1]],
expected_values=[0.23104906, 0.19178806, 0.14384104, 0.34657359],
expected_shape=[3, 2],
actual_sparse_tensor=out_weight,
close_values=True)
