def testRuntimeError(self, rt_inputs, axis, error, message, ragged_ranks=None): rt_inputs = [ array_ops.placeholder_with_default(rt, shape=None) for rt in rt_inputs ] concatenated = ragged.concat(rt_inputs, axis) with self.test_session(): self.assertRaisesRegexp(error, message, concatenated.eval)
def testSingleTensorInput(self): """Tests ragged_concat with a single tensor input. Usually, we pass a list of values in for rt_inputs. However, you can also pass in a single value (as with tf.concat), in which case it simply returns that tensor. This test exercises that path. """ rt_inputs = ragged.constant([[1, 2], [3, 4]]) concatenated = ragged.concat(rt_inputs, 0) self.assertRaggedEqual(concatenated, [[1, 2], [3, 4]])
def testSingleTensorInput(self): """Tests ragged_concat with a single tensor input. Usually, we pass a list of values in for rt_inputs. However, you can also pass in a single value (as with tf.concat), in which case it simply returns that tensor. This test exercises that path. """ rt_inputs = ragged.constant([[1, 2], [3, 4]]) concatenated = ragged.concat(rt_inputs, 0) with self.test_session(): self.assertEqual(concatenated.eval().tolist(), [[1, 2], [3, 4]])
def testRuntimeError(self, rt_inputs, axis, error, message, ragged_ranks=None): if context.executing_eagerly(): return rt_inputs = [ array_ops.placeholder_with_default(rt, shape=None) for rt in rt_inputs ] concatenated = ragged.concat(rt_inputs, axis) with self.assertRaisesRegexp(error, message): self.evaluate(concatenated)
def testRaggedConcat(self, descr, rt_inputs, axis, expected, ragged_ranks=None, expected_ragged_rank=None, expected_shape=None): rt_inputs = self._rt_inputs_to_tensors(rt_inputs, ragged_ranks) concatenated = ragged.concat(rt_inputs, axis) if expected_ragged_rank is not None: self.assertEqual(concatenated.ragged_rank, expected_ragged_rank) if expected_shape is not None: self.assertEqual(concatenated.shape.as_list(), expected_shape) self.assertRaggedEqual(concatenated, expected)
def testRaggedConcat(self, descr, rt_inputs, axis, expected, ragged_ranks=None, expected_ragged_rank=None, expected_shape=None): rt_inputs = self._rt_inputs_to_tensors(rt_inputs, ragged_ranks) concatenated = ragged.concat(rt_inputs, axis) if expected_ragged_rank is not None: self.assertEqual(concatenated.ragged_rank, expected_ragged_rank) if expected_shape is not None: self.assertEqual(concatenated.shape.as_list(), expected_shape) with self.test_session(): self.assertEqual(concatenated.eval().tolist(), expected)