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copybara-service merged 1 commit into from
Oct 22, 2026
Merged

Automated Code Change #935

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77 changes: 45 additions & 32 deletions tensorflow_gnn/runner/utils/parsing_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,9 @@
# limitations under the License.
# ==============================================================================
"""Tests for parsing."""
from collections.abc import Callable
import functools
from typing import Union

from absl.testing import parameterized
import tensorflow as tf
Expand Down Expand Up @@ -88,42 +90,47 @@ def _assert_graph_tensors_equal(self, a: GraphTensor, b: GraphTensor):
@parameterized.named_parameters([
dict(
testcase_name="SerializedGraphTensorElement",
ds=ds_from_tensor(random_serialized_graph_tensor()),
spec=random_graph_tensor().spec,
expected=random_graph_tensor(),
ds=lambda: ds_from_tensor(random_serialized_graph_tensor()),
spec=lambda: random_graph_tensor().spec,
expected=random_graph_tensor,
),
dict(
testcase_name="GraphTensorElement",
ds=ds_from_tensor(random_graph_tensor()),
spec=random_graph_tensor().spec,
expected=random_graph_tensor(),
ds=lambda: ds_from_tensor(random_graph_tensor()),
spec=lambda: random_graph_tensor().spec,
expected=random_graph_tensor,
),
dict(
testcase_name="SerializedGraphTensorElements",
ds=ds_from_tensor(random_serialized_graph_tensor()).repeat().batch(4),
spec=random_graph_tensor().spec,
expected=next(
iter(
ds_from_tensor(random_graph_tensor()).repeat().batch(4)
)
),
ds=lambda: ds_from_tensor(random_serialized_graph_tensor())
.repeat()
.batch(4),
spec=lambda: random_graph_tensor().spec,
expected=lambda: next(
iter(ds_from_tensor(random_graph_tensor()).repeat().batch(4))
),
),
dict(
testcase_name="GraphTensorElements",
ds=ds_from_tensor(random_graph_tensor()).repeat().batch(4),
spec=random_graph_tensor().spec,
expected=next(
iter(
ds_from_tensor(random_graph_tensor()).repeat().batch(4)
)
),
ds=lambda: ds_from_tensor(random_graph_tensor()).repeat().batch(4),
spec=lambda: random_graph_tensor().spec,
expected=lambda: next(
iter(ds_from_tensor(random_graph_tensor()).repeat().batch(4))
),
),
])
def test_maybe_parse_graph_tensor_dataset(
self,
ds: tf.data.Dataset,
spec: tfgnn.GraphTensorSpec,
expected: tfgnn.GraphTensor):
ds: Union[tf.data.Dataset, Callable[[], tf.data.Dataset]],
spec: Union[tfgnn.GraphTensorSpec, Callable[[], tfgnn.GraphTensorSpec]],
expected: Union[tfgnn.GraphTensor, Callable[[], tfgnn.GraphTensor]],
):
if callable(ds):
ds = ds()
if callable(spec):
spec = spec()
if callable(expected):
expected = expected()
ds = parsing_utils.maybe_parse_graph_tensor_dataset(ds, spec)
self._assert_graph_tensors_equal(
expected,
Expand All @@ -132,30 +139,36 @@ def test_maybe_parse_graph_tensor_dataset(
@parameterized.named_parameters([
dict(
testcase_name="FloatElement",
ds=ds_from_tensor(tf.constant(8191.)),
spec=random_graph_tensor().spec,
ds=lambda: ds_from_tensor(tf.constant(8191.0)),
spec=lambda: random_graph_tensor().spec,
expected_failure=r"Expected `GraphTensorSpec` \(got .*\)",
),
dict(
testcase_name="IncompatibleGraphTensorElement",
ds=ds_from_tensor(
ds=lambda: ds_from_tensor(
tfgnn.homogeneous(
source=tf.constant((0, 3)),
target=tf.constant((1, 2)),
node_set_sizes=tf.constant((4,))
),
node_set_sizes=tf.constant((4,)),
),
spec=random_graph_tensor().spec,
),
spec=lambda: random_graph_tensor().spec,
expected_failure=r"Graph is not compatible with the graph schema.*",
),
])
def test_maybe_parse_graph_tensor_dataset_fails(
self,
ds: tf.data.Dataset,
spec: tfgnn.GraphTensorSpec,
expected_failure: str):
ds: Union[tf.data.Dataset, Callable[[], tf.data.Dataset]],
spec: Union[tfgnn.GraphTensorSpec, Callable[[], tfgnn.GraphTensorSpec]],
expected_failure: str,
):
if callable(ds):
ds = ds()
if callable(spec):
spec = spec()
with self.assertRaisesRegex(ValueError, expected_failure):
_ = parsing_utils.maybe_parse_graph_tensor_dataset(ds, spec)


if __name__ == "__main__":
tf.test.main()
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