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 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)