def testSplitV1(self, input, expected, input_is_ragged=False, **kwargs): # pylint: disable=redefined-builtin
# Prepare the input tensor.
if input_is_ragged:
input = ragged_factory_ops.constant(input, dtype=dtypes.string)
else:
input = constant_op.constant(input, dtype=dtypes.string)
expected_ragged = ragged_factory_ops.constant(expected)
actual_ragged_v1 = ragged_string_ops.strings_split_v1(
input, result_type="RaggedTensor", **kwargs)
actual_ragged_v1_input_kwarg = ragged_string_ops.strings_split_v1(
input=input, result_type="RaggedTensor", **kwargs)
actual_ragged_v1_source_kwarg = ragged_string_ops.strings_split_v1(
source=input, result_type="RaggedTensor", **kwargs)
self.assertAllEqual(expected_ragged, actual_ragged_v1)
self.assertAllEqual(expected_ragged, actual_ragged_v1_input_kwarg)
self.assertAllEqual(expected_ragged, actual_ragged_v1_source_kwarg)
expected_sparse = self.evaluate(expected_ragged.to_sparse())
actual_sparse_v1 = ragged_string_ops.strings_split_v1(
input, result_type="SparseTensor", **kwargs)
self.assertEqual(expected_sparse.indices.tolist(),
self.evaluate(actual_sparse_v1.indices).tolist())
self.assertEqual(expected_sparse.values.tolist(),
self.evaluate(actual_sparse_v1.values).tolist())
self.assertEqual(expected_sparse.dense_shape.tolist(),
self.evaluate(actual_sparse_v1.dense_shape).tolist())
def testSplitV2(self, input, expected, input_is_ragged=False, **kwargs): # pylint: disable=redefined-builtin
# Check that we are matching the behavior of Python's str.split:
self.assertEqual(expected, self._py_split(input, **kwargs))
# Prepare the input tensor.
if input_is_ragged:
input = ragged_factory_ops.constant(input, dtype=dtypes.string)
else:
input = constant_op.constant(input, dtype=dtypes.string)
# Check that the public version (which returns a RaggedTensor) works
# correctly.
expected_ragged = ragged_factory_ops.constant(
expected, ragged_rank=input.shape.ndims)
actual_ragged_v1 = ragged_string_ops.strings_split_v1(
input, result_type="RaggedTensor", **kwargs)
actual_ragged_v2 = ragged_string_ops.string_split_v2(input, **kwargs)
self.assertRaggedEqual(expected_ragged, actual_ragged_v1)
self.assertRaggedEqual(expected_ragged, actual_ragged_v2)
# Check that the internal version (which returns a SparseTensor) works
# correctly. Note: the internal version oly supports vector inputs.
if input.shape.ndims == 1:
expected_sparse = self.evaluate(expected_ragged.to_sparse())
actual_sparse_v1 = ragged_string_ops.strings_split_v1(
input, result_type="SparseTensor", **kwargs)
actual_sparse_v2 = string_ops.string_split_v2(input, **kwargs)
for actual_sparse in [actual_sparse_v1, actual_sparse_v2]:
self.assertEqual(expected_sparse.indices.tolist(),
self.evaluate(actual_sparse.indices).tolist())
self.assertEqual(expected_sparse.values.tolist(),
self.evaluate(actual_sparse.values).tolist())
self.assertEqual(
expected_sparse.dense_shape.tolist(),
self.evaluate(actual_sparse.dense_shape).tolist())
def testSplitV2(self,
input,
expected,
input_is_ragged=False,
**kwargs): # pylint: disable=redefined-builtin
# Check that we are matching the behavior of Python's str.split:
self.assertEqual(expected, self._py_split(input, **kwargs))
# Prepare the input tensor.
if input_is_ragged:
input = ragged_factory_ops.constant(input, dtype=dtypes.string)
else:
input = constant_op.constant(input, dtype=dtypes.string)
# Check that the public version (which returns a RaggedTensor) works
# correctly.
expected_ragged = ragged_factory_ops.constant(
expected, ragged_rank=input.shape.ndims)
actual_ragged_v1 = ragged_string_ops.strings_split_v1(
input, result_type="RaggedTensor", **kwargs)
actual_ragged_v1_input_kwarg = ragged_string_ops.strings_split_v1(
input=input, result_type="RaggedTensor", **kwargs)
actual_ragged_v1_source_kwarg = ragged_string_ops.strings_split_v1(
source=input, result_type="RaggedTensor", **kwargs)
actual_ragged_v2 = ragged_string_ops.string_split_v2(input, **kwargs)
actual_ragged_v2_input_kwarg = ragged_string_ops.string_split_v2(
input=input, **kwargs)
self.assertRaggedEqual(expected_ragged, actual_ragged_v1)
self.assertRaggedEqual(expected_ragged, actual_ragged_v1_input_kwarg)
self.assertRaggedEqual(expected_ragged, actual_ragged_v1_source_kwarg)
self.assertRaggedEqual(expected_ragged, actual_ragged_v2)
self.assertRaggedEqual(expected_ragged, actual_ragged_v2_input_kwarg)
# Check that the internal version (which returns a SparseTensor) works
# correctly. Note: the internal version oly supports vector inputs.
if input.shape.ndims == 1:
expected_sparse = self.evaluate(expected_ragged.to_sparse())
actual_sparse_v1 = ragged_string_ops.strings_split_v1(
input, result_type="SparseTensor", **kwargs)
actual_sparse_v2 = string_ops.string_split_v2(input, **kwargs)
for actual_sparse in [actual_sparse_v1, actual_sparse_v2]:
self.assertEqual(expected_sparse.indices.tolist(),
self.evaluate(actual_sparse.indices).tolist())
self.assertEqual(expected_sparse.values.tolist(),
self.evaluate(actual_sparse.values).tolist())
self.assertEqual(expected_sparse.dense_shape.tolist(),
self.evaluate(actual_sparse.dense_shape).tolist())
def testSplitV1BadResultType(self):
with self.assertRaisesRegex(ValueError, "result_type must be .*"):
ragged_string_ops.strings_split_v1("foo",
result_type="BouncyTensor")