liferoad commented on code in PR #31501:
URL: https://github.com/apache/beam/pull/31501#discussion_r1627672538
##########
sdks/python/apache_beam/ml/transforms/base_test.py:
##########
@@ -500,6 +507,87 @@ def test_handler_with_inconsistent_keys(self):
self.embedding_conig))
+class FakeImageModel:
+ def __call__(self, example: List[PIL_Image]) -> List[PIL_Image]:
+ for i in range(len(example)):
+ if not isinstance(example[i], PIL_Image):
+ raise TypeError('Input must be an Image')
+ return example
+
+
+class FakeImageModelHandler(ModelHandler):
+ def run_inference(
+ self,
+ batch: Sequence[PIL_Image],
+ model: Any,
+ inference_args: Optional[Dict[str, Any]] = None):
+ return model(batch)
+
+ def load_model(self):
+ return FakeImageModel()
+
+
+class FakeImageEmbeddingsManager(base.EmbeddingsManager):
+ def __init__(self, columns, **kwargs):
+ super().__init__(columns=columns, **kwargs)
+
+ def get_model_handler(self) -> ModelHandler:
+ FakeModelHandler.__repr__ = lambda x: 'FakeImageEmbeddingsManager' #
type: ignore[assignment]
+ return FakeImageModelHandler()
+
+ def get_ptransform_for_processing(self, **kwargs) -> beam.PTransform:
+ return (RunInference(model_handler=base._ImageEmbeddingHandler(self)))
+
+ def __repr__(self):
+ return 'FakeImageEmbeddingsManager'
+
+
+class TestImageEmbeddingHandler(unittest.TestCase):
+ def setUp(self) -> None:
+ self.embedding_config = FakeImageEmbeddingsManager(columns=['x'])
+ self.artifact_location = tempfile.mkdtemp()
+
+ def tearDown(self) -> None:
+ shutil.rmtree(self.artifact_location)
+
+ @unittest.skipIf(PIL is None, 'PIL module is not installed.')
+ def test_handler_with_incompatible_datatype(self):
+ text_handler = base._ImageEmbeddingHandler(
Review Comment:
you mean image_handler?
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