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)