Eliaaazzz commented on code in PR #37945:
URL: https://github.com/apache/beam/pull/37945#discussion_r2985585544
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sdks/python/apache_beam/ml/inference/base_test.py:
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@@ -2319,6 +2319,234 @@ def test_batching_kwargs_none_values_omitted(self):
self.assertEqual(kwargs['min_batch_size'], 5)
+class PaddingReportingStringModelHandler(base.ModelHandler[str, str,
+ FakeModel]):
+ """Reports each element with the max length of the batch it ran in."""
+ def load_model(self):
+ return FakeModel()
+
+ def run_inference(self, batch, model, inference_args=None):
+ max_len = max(len(s) for s in batch)
+ return [f'{s}:{max_len}' for s in batch]
+
+
+class RunInferenceLengthAwareBatchingTest(unittest.TestCase):
+ """End-to-end tests for PR2 length-aware batching in RunInference."""
+ def test_run_inference_with_length_aware_batch_elements(self):
+ handler = PaddingReportingStringModelHandler(
+ min_batch_size=2,
+ max_batch_size=2,
+ max_batch_duration_secs=60,
+ batch_length_fn=len,
+ batch_bucket_boundaries=[5])
+
+ examples = ['a', 'cccccc', 'bb', 'ddddddd']
+ with TestPipeline('FnApiRunner') as p:
+ results = (
+ p
+ | beam.Create(examples, reshuffle=False)
+ | base.RunInference(handler))
+ assert_that(results, equal_to(['a:2', 'bb:2', 'cccccc:7', 'ddddddd:7']))
+
+
+class HandlerBucketingKwargsForwardingTest(unittest.TestCase):
Review Comment:
Good point. These cases all exercise the same forwarding assertion with
different handler constructors, so I can consolidate them into a single
data-driven test using `subTest`.
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