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Enable prism by default (where supported) #26666

GitHub Actions / Test Results failed Apr 11, 2025 in 0s

2 errors, 56 fail, 74 skipped, 354 pass in 24m 4s

  2 files  +  2    2 suites  +2   24m 4s ⏱️ + 24m 4s
486 tests +486  354 ✅ +354  74 💤 +74  56 ❌ +56  2 🔥 +2 
490 runs  +490  352 ✅ +352  78 💤 +78  58 ❌ +58  2 🔥 +2 

Results for commit 3233b69. ± Comparison against earlier commit e28e463.

Annotations

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_run_inference_impl_keyed_mps_incrementing_multi_copy (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 14s]
Raw output 
apache_beam.testing.util.BeamAssertException: Failed assert: [('abc', 1), ('abc', 1), ('abc', 1), ('abc', 1), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 4), ('abc', 4), ('abc', 4), ('abc', 4)] == [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 8), ('abc', 8), ('abc', 8), ('abc', 8)], unexpected elements [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 8), ('abc', 8), ('abc', 8), ('abc', 8)], missing elements [('abc', 1), ('abc', 1), ('abc', 1), ('abc', 1), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 4), ('abc', 4), ('abc', 4), ('abc', 4)] [while running 'assert:inferences/Match']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ...]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7acab04384c0>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [('abc', 1), ('abc', 1), ('abc', 1), ('abc', 1), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 4), ('abc', 4), ('abc', 4), ('abc', 4)] == [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 8), ('abc', 8), ('abc', 8), ('abc', 8)], unexpected elements [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 8), ('abc', 8), ('abc', 8), ('abc', 8)], missing elements [('abc', 1), ('abc', 1), ('abc', 1), ('abc', 1), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 4), ('abc', 4), ('abc', 4), ('abc', 4)]

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_run_inference_impl_keyed_mps_incrementing_multi_copy>

    def test_run_inference_impl_keyed_mps_incrementing_multi_copy(self):
      with TestPipeline() as pipeline:
        examples = [1, 5, 3, 10, 1, 5, 3, 10, 1, 5, 3, 10, 1, 5, 3, 10]
        keyed_examples = [('abc', example) for example in examples]
        expected = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
        keyed_expected = [('abc', val) for val in expected]
        pcoll = pipeline | 'start' >> beam.Create(keyed_examples)
        actual = pcoll | base.RunInference(
            base.KeyedModelHandler(
                FakeModelHandler(
                    multi_process_shared=True,
                    max_copies=4,
                    incrementing=True,
                    max_batch_size=1)))
>       assert_that(actual, equal_to(keyed_expected), label='assert:inferences')

apache_beam/ml/inference/base_test.py:376: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/test_pipeline.py:115: in run
    result = super().run(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:591: in run
    return Pipeline.from_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ...]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7acab04384c0>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [('abc', 1), ('abc', 1), ('abc', 1), ('abc', 1), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 4), ('abc', 4), ('abc', 4), ('abc', 4)] == [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 8), ('abc', 8), ('abc', 8), ('abc', 8)], unexpected elements [('abc', 5), ('abc', 5), ('abc', 5), ('abc', 5), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 6), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 7), ('abc', 8), ('abc', 8), ('abc', 8), ('abc', 8)], missing elements [('abc', 1), ('abc', 1), ('abc', 1), ('abc', 1), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 2), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 3), ('abc', 4), ('abc', 4), ('abc', 4), ('abc', 4)] [while running 'assert:inferences/Match']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_counted_metrics (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 10s]
Raw output 
AssertionError: [] is not true
self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_counted_metrics>

    def test_counted_metrics(self):
      pipeline = TestPipeline()
      examples = [1, 5, 3, 10]
      pcoll = pipeline | 'start' >> beam.Create(examples)
      _ = pcoll | base.RunInference(FakeModelHandler())
      run_result = pipeline.run()
      run_result.wait_until_finish()
    
      metric_results = (
          run_result.metrics().query(MetricsFilter().with_name('num_inferences')))
      num_inferences_counter = metric_results['counters'][0]
      self.assertEqual(num_inferences_counter.committed, 4)
    
      inference_request_batch_size = run_result.metrics().query(
          MetricsFilter().with_name('inference_request_batch_size'))
      self.assertTrue(inference_request_batch_size['distributions'])
      self.assertEqual(
          inference_request_batch_size['distributions'][0].result.sum, 4)
      inference_request_batch_byte_size = run_result.metrics().query(
          MetricsFilter().with_name('inference_request_batch_byte_size'))
      self.assertTrue(inference_request_batch_byte_size['distributions'])
      self.assertGreaterEqual(
          inference_request_batch_byte_size['distributions'][0].result.sum,
          len(pickle.dumps(examples)))
      inference_request_batch_byte_size = run_result.metrics().query(
          MetricsFilter().with_name('model_byte_size'))
>     self.assertTrue(inference_request_batch_byte_size['distributions'])
E     AssertionError: [] is not true

apache_beam/ml/inference/base_test.py:1011: AssertionError

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_runinference_loads_same_model_with_identifier_multi_process_shared (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 13s]
Raw output 
apache_beam.testing.util.BeamAssertException: Failed assert: [4, 5, 6] == [10, 11, 12], unexpected elements [10, 11, 12], missing elements [4, 5, 6] [while running 'assert:inferences/Match']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [10, 11, 12]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7a1d506bd5e0>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [4, 5, 6] == [10, 11, 12], unexpected elements [10, 11, 12], missing elements [4, 5, 6]

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_runinference_loads_same_model_with_identifier_multi_process_shared>

    def test_runinference_loads_same_model_with_identifier_multi_process_shared(
        self):
      mh1 = FakeModelHandler(
          incrementing=True, min_batch_size=3, multi_process_shared=True)
      with TestPipeline() as pipeline:
        pcoll = pipeline | 'start' >> beam.Create([1, 2, 3])
        actual = (
            pcoll
            | 'ri1' >> base.RunInference(
                mh1,
                model_identifier='same_model_with_identifier_multi_process_shared'
            )
            | 'ri2' >> base.RunInference(
                mh1,
                model_identifier='same_model_with_identifier_multi_process_shared'
            ))
>       assert_that(actual, equal_to([4, 5, 6]), label='assert:inferences')

apache_beam/ml/inference/base_test.py:1761: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/test_pipeline.py:115: in run
    result = super().run(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:591: in run
    return Pipeline.from_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [10, 11, 12]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7a1d506bd5e0>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [4, 5, 6] == [10, 11, 12], unexpected elements [10, 11, 12], missing elements [4, 5, 6] [while running 'assert:inferences/Match']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_run_inference_impl_mps_nobatch_incrementing_multi_copy (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 13s]
Raw output 
apache_beam.testing.util.BeamAssertException: Failed assert: [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] == [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], unexpected elements [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], missing elements [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] [while running 'assert:inferences/Match']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [5, 5, 5, 5, 6, 6, ...]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7ac9489c3b80>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] == [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], unexpected elements [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], missing elements [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_run_inference_impl_mps_nobatch_incrementing_multi_copy>

    def test_run_inference_impl_mps_nobatch_incrementing_multi_copy(self):
      with TestPipeline() as pipeline:
        examples = [1, 5, 3, 10, 1, 5, 3, 10, 1, 5, 3, 10, 1, 5, 3, 10]
        expected = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
        batched_examples = [[example] for example in examples]
        pcoll = pipeline | 'start' >> beam.Create(batched_examples)
        actual = pcoll | base.RunInference(
            FakeModelHandler(
                multi_process_shared=True, max_copies=4,
                incrementing=True).with_no_batching())
>       assert_that(actual, equal_to(expected), label='assert:inferences')

apache_beam/ml/inference/base_test.py:360: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/test_pipeline.py:115: in run
    result = super().run(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:591: in run
    return Pipeline.from_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [5, 5, 5, 5, 6, 6, ...]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7ac9489c3b80>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] == [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], unexpected elements [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], missing elements [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] [while running 'assert:inferences/Match']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_run_inference_impl_multi_process_shared_incrementing_multi_copy (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 15s]
Raw output 
apache_beam.testing.util.BeamAssertException: Failed assert: [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] == [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], unexpected elements [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], missing elements [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] [while running 'assert:inferences/Match']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [5, 5, 5, 5, 6, 6, ...]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7acab06698b0>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] == [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], unexpected elements [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], missing elements [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_run_inference_impl_multi_process_shared_incrementing_multi_copy>

    def test_run_inference_impl_multi_process_shared_incrementing_multi_copy(
        self):
      with TestPipeline() as pipeline:
        examples = [1, 5, 3, 10, 1, 5, 3, 10, 1, 5, 3, 10, 1, 5, 3, 10]
        expected = [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4]
        pcoll = pipeline | 'start' >> beam.Create(examples)
        actual = pcoll | base.RunInference(
            FakeModelHandler(
                multi_process_shared=True,
                max_copies=4,
                incrementing=True,
                max_batch_size=1))
>       assert_that(actual, equal_to(expected), label='assert:inferences')

apache_beam/ml/inference/base_test.py:348: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/test_pipeline.py:115: in run
    result = super().run(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:591: in run
    return Pipeline.from_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [5, 5, 5, 5, 6, 6, ...]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7acab06698b0>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] == [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], unexpected elements [5, 5, 5, 5, 6, 6, 6, 6, 7, 7, 7, 7, 8, 8, 8, 8], missing elements [1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 4] [while running 'assert:inferences/Match']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_run_inference_impl_with_keyed_examples_many_mhs_max_models_hint (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 12s]
Raw output 
AssertionError: 1 not greater than 2
self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_run_inference_impl_with_keyed_examples_many_mhs_max_models_hint>

    def test_run_inference_impl_with_keyed_examples_many_mhs_max_models_hint(
        self):
      pipeline = TestPipeline()
      examples = [1, 5, 3, 10, 2, 4, 6, 8, 9, 7, 1, 5, 3, 10, 2, 4, 6, 8, 9, 7]
      metrics_namespace = 'test_namespace'
      keyed_examples = [(i, example) for i, example in enumerate(examples)]
      pcoll = pipeline | 'start' >> beam.Create(keyed_examples)
      mhs = [
          base.KeyModelMapping([0, 2, 4, 6, 8],
                               FakeModelHandler(
                                   state=200, multi_process_shared=True)),
          base.KeyModelMapping(
              [1, 3, 5, 7, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
              FakeModelHandler(multi_process_shared=True))
      ]
      _ = pcoll | base.RunInference(
          base.KeyedModelHandler(mhs, max_models_per_worker_hint=1),
          metrics_namespace=metrics_namespace)
      result = pipeline.run()
      result.wait_until_finish()
    
      metrics_filter = MetricsFilter().with_namespace(namespace=metrics_namespace)
      metrics = result.metrics().query(metrics_filter)
      assert len(metrics['counters']) != 0
      assert len(metrics['distributions']) != 0
    
      metrics_filter = MetricsFilter().with_name('load_model_latency_milli_secs')
      metrics = result.metrics().query(metrics_filter)
      load_latency_dist_aggregate = metrics['distributions'][0]
      # We should flip back and forth between models a bit since
      # max_models_per_worker_hint=1, but we shouldn't thrash forever
      # since most examples belong to the second ModelMapping
>     self.assertGreater(load_latency_dist_aggregate.committed.count, 2)
E     AssertionError: 1 not greater than 2

apache_beam/ml/inference/base_test.py:497: AssertionError

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_run_inference_impl_with_keyed_examples_many_model_handlers_metrics (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 11s]
Raw output 
IndexError: list index out of range
self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_run_inference_impl_with_keyed_examples_many_model_handlers_metrics>

    def test_run_inference_impl_with_keyed_examples_many_model_handlers_metrics(
        self):
      pipeline = TestPipeline()
      examples = [1, 5, 3, 10]
      metrics_namespace = 'test_namespace'
      keyed_examples = [(i, example) for i, example in enumerate(examples)]
      pcoll = pipeline | 'start' >> beam.Create(keyed_examples)
      mhs = [
          base.KeyModelMapping([0],
                               FakeModelHandler(
                                   state=200, multi_process_shared=True)),
          base.KeyModelMapping([1, 2, 3],
                               FakeModelHandler(multi_process_shared=True))
      ]
      _ = pcoll | base.RunInference(
          base.KeyedModelHandler(mhs), metrics_namespace=metrics_namespace)
      result = pipeline.run()
      result.wait_until_finish()
    
      metrics_filter = MetricsFilter().with_namespace(namespace=metrics_namespace)
      metrics = result.metrics().query(metrics_filter)
      assert len(metrics['counters']) != 0
      assert len(metrics['distributions']) != 0
    
      metrics_filter = MetricsFilter().with_name('0-_num_inferences')
      metrics = result.metrics().query(metrics_filter)
      num_inferences_counter_key_0 = metrics['counters'][0]
      self.assertEqual(num_inferences_counter_key_0.committed, 1)
    
      metrics_filter = MetricsFilter().with_name('1-_num_inferences')
      metrics = result.metrics().query(metrics_filter)
      num_inferences_counter_key_1 = metrics['counters'][0]
      self.assertEqual(num_inferences_counter_key_1.committed, 3)
    
      metrics_filter = MetricsFilter().with_name('num_inferences')
      metrics = result.metrics().query(metrics_filter)
      num_inferences_counter_aggregate = metrics['counters'][0]
      self.assertEqual(num_inferences_counter_aggregate.committed, 4)
    
      metrics_filter = MetricsFilter().with_name('0-_failed_batches_counter')
      metrics = result.metrics().query(metrics_filter)
      failed_batches_counter_key_0 = metrics['counters']
      self.assertEqual(len(failed_batches_counter_key_0), 0)
    
      metrics_filter = MetricsFilter().with_name('failed_batches_counter')
      metrics = result.metrics().query(metrics_filter)
      failed_batches_counter_aggregate = metrics['counters']
      self.assertEqual(len(failed_batches_counter_aggregate), 0)
    
      metrics_filter = MetricsFilter().with_name(
          '0-_load_model_latency_milli_secs')
      metrics = result.metrics().query(metrics_filter)
>     load_latency_dist_key_0 = metrics['distributions'][0]
E     IndexError: list index out of range

apache_beam/ml/inference/base_test.py:457: IndexError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_on_list_dict (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 31s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba46c70e880>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpess2vptp/f8c83f/tftransform_tmp/4fc5bb338ef64f32930c063a131e7825'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_on_list_dict>

    @unittest.skipIf(tft is None, 'tft module is not installed.')
    def test_ml_transform_on_list_dict(self):
      transforms = [tft.ScaleTo01(columns=['x'])]
      data = [{'x': [1, 2, 3]}, {'x': [4, 5, 6]}]
      with beam.Pipeline() as p:
        result = (
            p
            | beam.Create(data)
            | base.MLTransform(
                transforms=transforms,
                write_artifact_location=self.artifact_location))
        expected_output = [
            np.array([0, 0.2, 0.4], dtype=np.float32),
            np.array([0.6, 0.8, 1], dtype=np.float32),
        ]
        actual_output = result | beam.Map(lambda x: x.x)
>       assert_that(
            actual_output, equal_to(expected_output, equals_fn=np.array_equal))

apache_beam/ml/transforms/base_test.py:133: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba46c70e880>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpess2vptp/f8c83f/tftransform_tmp/4fc5bb338ef64f32930c063a131e7825'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.inference.base_test.RunInferenceBaseTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_run_inference_loads_different_models_multi_process_shared (apache_beam.ml.inference.base_test.RunInferenceBaseTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 14s]
Raw output 
apache_beam.testing.util.BeamAssertException: Failed assert: [1, 2, 3] == [4, 5, 6], unexpected elements [4, 5, 6], missing elements [1, 2, 3] [while running 'assert:inferences/Match']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [4, 5, 6]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7ac93c1fe040>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [1, 2, 3] == [4, 5, 6], unexpected elements [4, 5, 6], missing elements [1, 2, 3]

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.inference.base_test.RunInferenceBaseTest testMethod=test_run_inference_loads_different_models_multi_process_shared>

    def test_run_inference_loads_different_models_multi_process_shared(self):
      mh1 = FakeModelHandler(
          incrementing=True, min_batch_size=3, multi_process_shared=True)
      with TestPipeline() as pipeline:
        pcoll = pipeline | 'start' >> beam.Create([1, 2, 3])
        actual = (
            pcoll
            | 'ri1' >> base.RunInference(mh1)
            | 'ri2' >> base.RunInference(mh1))
>       assert_that(actual, equal_to([1, 2, 3]), label='assert:inferences')

apache_beam/ml/inference/base_test.py:1743: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/test_pipeline.py:115: in run
    result = super().run(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:591: in run
    return Pipeline.from_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1055: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.process_method(*args_for_process, **kwargs_for_process),
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/transforms/core.py:2084: in <lambda>
    wrapper = lambda x, *args, **kwargs: [fn(x, *args, **kwargs)]
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

actual = [4, 5, 6]
equals_fn = <function equal_to.<locals>._equal.<locals>.<lambda> at 0x7ac93c1fe040>

    def _equal(actual, equals_fn=equals_fn):
      expected_list = list(expected)
    
      # Try to compare actual and expected by sorting. This fails with a
      # TypeError in Python 3 if different types are present in the same
      # collection. It can also raise false negatives for types that don't have
      # a deterministic sort order, like pyarrow Tables as of 0.14.1
      if not equals_fn:
        equals_fn = lambda e, a: e == a
        try:
          sorted_expected = sorted(expected)
          sorted_actual = sorted(actual)
          if sorted_expected == sorted_actual:
            return
        except TypeError:
          pass
      # Slower method, used in two cases:
      # 1) If sorted expected != actual, use this method to verify the inequality.
      #    This ensures we don't raise any false negatives for types that don't
      #    have a deterministic sort order.
      # 2) As a fallback if we encounter a TypeError in python 3. this method
      #    works on collections that have different types.
      unexpected = []
      for element in actual:
        found = False
        for i, v in enumerate(expected_list):
          if equals_fn(v, element):
            found = True
            expected_list.pop(i)
            break
        if not found:
          unexpected.append(element)
      if unexpected or expected_list:
        msg = 'Failed assert: %r == %r' % (expected, actual)
        if unexpected:
          msg = msg + ', unexpected elements %r' % unexpected
        if expected_list:
          msg = msg + ', missing elements %r' % expected_list
>       raise BeamAssertException(msg)
E       apache_beam.testing.util.BeamAssertException: Failed assert: [1, 2, 3] == [4, 5, 6], unexpected elements [4, 5, 6], missing elements [1, 2, 3] [while running 'assert:inferences/Match']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/util.py:192: BeamAssertException

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_dict_output_pcoll_schema_0 (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 29s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b79e85970a0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpk_gde9c6/8ec42c/tftransform_tmp/23ab8c7d9239496e86dc5550a1a3fff6'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

a = (<apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_dict_output_pcoll_schema_0>,)
kw = {}

    @wraps(func)
    def standalone_func(*a, **kw):
>       return func(*(a + p.args), **p.kwargs, **kw)

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/parameterized/parameterized.py:620: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/ml/transforms/base_test.py:204: in test_ml_transform_dict_output_pcoll_schema
    self.assertEqual(expected_dtype[name], typ)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b79e85970a0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpk_gde9c6/8ec42c/tftransform_tmp/23ab8c7d9239496e86dc5550a1a3fff6'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_on_multiple_columns_single_transform (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 28s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba639e48ca0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmp16htm2x9/de9291/tftransform_tmp/c22c374409394d77872b6117bf1d857c'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_on_multiple_columns_single_transform>

    @unittest.skipIf(tft is None, 'tft module is not installed.')
    def test_ml_transform_on_multiple_columns_single_transform(self):
      transforms = [tft.ScaleTo01(columns=['x', 'y'])]
      data = [{'x': [1, 2, 3], 'y': [1.0, 10.0, 20.0]}]
      with beam.Pipeline() as p:
        result = (
            p
            | beam.Create(data)
            | base.MLTransform(
                transforms=transforms,
                write_artifact_location=self.artifact_location))
        expected_output_x = [
            np.array([0, 0.5, 1], dtype=np.float32),
        ]
        expected_output_y = [np.array([0, 0.47368422, 1], dtype=np.float32)]
        actual_output_x = result | beam.Map(lambda x: x.x)
        actual_output_y = result | beam.Map(lambda x: x.y)
        assert_that(
            actual_output_x,
            equal_to(expected_output_x, equals_fn=np.array_equal))
>       assert_that(
            actual_output_y,
            equal_to(expected_output_y, equals_fn=np.array_equal),
            label='y')

apache_beam/ml/transforms/base_test.py:242: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba639e48ca0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmp16htm2x9/de9291/tftransform_tmp/c22c374409394d77872b6117bf1d857c'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_dict_output_pcoll_schema_1 (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 24s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b7a8803f640>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmph9hqg5ml/1bbb79/tftransform_tmp/6a03035416ac403eac5fd068ef92be2d'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

a = (<apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_dict_output_pcoll_schema_1>,)
kw = {}

    @wraps(func)
    def standalone_func(*a, **kw):
>       return func(*(a + p.args), **p.kwargs, **kw)

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/parameterized/parameterized.py:620: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/ml/transforms/base_test.py:204: in test_ml_transform_dict_output_pcoll_schema
    self.assertEqual(expected_dtype[name], typ)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b7a8803f640>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmph9hqg5ml/1bbb79/tftransform_tmp/6a03035416ac403eac5fd068ef92be2d'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

1 out of 2 runs failed: test_consume_mode_with_extra_columns_in_the_input (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest) 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 1m 0s]
Raw output 
RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7c719c73ef10>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmp7g3hrdy9/tftransform_tmp/7d1b380c82794cd88cbffab444bfcf4a'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest testMethod=test_consume_mode_with_extra_columns_in_the_input>

    def test_consume_mode_with_extra_columns_in_the_input(self):
      with beam.Pipeline() as p:
        raw_data = (
            p
            | beam.Create([{
                'x': np.array([1, 3])
            }, {
                'x': np.array([4, 6])
            }]))
        process_handler = handlers.TFTProcessHandler(
            transforms=[tft.ScaleTo01(columns=['x'])],
            artifact_location=self.artifact_location,
        )
>       _ = raw_data | process_handler

apache_beam/ml/transforms/handlers_test.py:527: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7c719c73ef10>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmp7g3hrdy9/tftransform_tmp/7d1b380c82794cd88cbffab444bfcf4a'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check failure on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

1 out of 2 runs with error: test_consume_mode_with_extra_columns_in_the_input (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest) 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 0s]
Raw output 
failed on teardown with "OSError: [Errno 39] Directory not empty: 'tftransform_tmp'"
self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest testMethod=test_consume_mode_with_extra_columns_in_the_input>

    def tearDown(self):
>     shutil.rmtree(self.artifact_location)

apache_beam/ml/transforms/handlers_test.py:79: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
/opt/hostedtoolcache/Python/3.9.22/x64/lib/python3.9/shutil.py:734: in rmtree
    _rmtree_safe_fd(fd, path, onerror)
/opt/hostedtoolcache/Python/3.9.22/x64/lib/python3.9/shutil.py:673: in _rmtree_safe_fd
    onerror(os.rmdir, fullname, sys.exc_info())
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

topfd = 22, path = '/tmp/tmp7g3hrdy9'
onerror = <function rmtree.<locals>.onerror at 0x7c71181498b0>

    def _rmtree_safe_fd(topfd, path, onerror):
        try:
            with os.scandir(topfd) as scandir_it:
                entries = list(scandir_it)
        except OSError as err:
            err.filename = path
            onerror(os.scandir, path, sys.exc_info())
            return
        for entry in entries:
            fullname = os.path.join(path, entry.name)
            try:
                is_dir = entry.is_dir(follow_symlinks=False)
            except OSError:
                is_dir = False
            else:
                if is_dir:
                    try:
                        orig_st = entry.stat(follow_symlinks=False)
                        is_dir = stat.S_ISDIR(orig_st.st_mode)
                    except OSError:
                        onerror(os.lstat, fullname, sys.exc_info())
                        continue
            if is_dir:
                try:
                    dirfd = os.open(entry.name, os.O_RDONLY, dir_fd=topfd)
                    dirfd_closed = False
                except OSError:
                    onerror(os.open, fullname, sys.exc_info())
                else:
                    try:
                        if os.path.samestat(orig_st, os.fstat(dirfd)):
                            _rmtree_safe_fd(dirfd, fullname, onerror)
                            try:
                                os.close(dirfd)
                                dirfd_closed = True
>                               os.rmdir(entry.name, dir_fd=topfd)
E                               OSError: [Errno 39] Directory not empty: 'tftransform_tmp'

/opt/hostedtoolcache/Python/3.9.22/x64/lib/python3.9/shutil.py:671: OSError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transforms_on_multiple_columns_multiple_transforms (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 1m 21s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba63a099640>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
y: large_list<item: large_binary>
  child 0, item: large_binary
saved_model_dir = '/tmp/tmp8opskph1/00ad55/tftransform_tmp/ae4867d07f0b4c588f281715da53191c'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transforms_on_multiple_columns_multiple_transforms>

    @unittest.skipIf(tft is None, 'tft module is not installed.')
    def test_ml_transforms_on_multiple_columns_multiple_transforms(self):
      transforms = [
          tft.ScaleTo01(columns=['x']),
          tft.ComputeAndApplyVocabulary(columns=['y'])
      ]
      data = [{'x': [1, 2, 3], 'y': ['a', 'b', 'c']}]
      with beam.Pipeline() as p:
        result = (
            p
            | beam.Create(data)
            | base.MLTransform(
                transforms=transforms,
                write_artifact_location=self.artifact_location))
        expected_output_x = [
            np.array([0, 0.5, 1], dtype=np.float32),
        ]
        expected_output_y = [np.array([2, 1, 0])]
        actual_output_x = result | beam.Map(lambda x: x.x)
        actual_output_y = result | beam.Map(lambda x: x.y)
    
        assert_that(
            actual_output_x,
            equal_to(expected_output_x, equals_fn=np.array_equal))
>       assert_that(
            actual_output_y,
            equal_to(expected_output_y, equals_fn=np.array_equal),
            label='actual_output_y')

apache_beam/ml/transforms/base_test.py:271: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba63a099640>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
y: large_list<item: large_binary>
  child 0, item: large_binary
saved_model_dir = '/tmp/tmp8opskph1/00ad55/tftransform_tmp/ae4867d07f0b4c588f281715da53191c'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_dict_output_pcoll_schema_2 (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 1m 8s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b7c4cd566d0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpdirgn_yf/e69497/tftransform_tmp/02129cdfbd264bfa94f51ce3e4550371'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

a = (<apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_dict_output_pcoll_schema_2>,)
kw = {}

    @wraps(func)
    def standalone_func(*a, **kw):
>       return func(*(a + p.args), **p.kwargs, **kw)

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/parameterized/parameterized.py:620: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/ml/transforms/base_test.py:204: in test_ml_transform_dict_output_pcoll_schema
    self.assertEqual(expected_dtype[name], typ)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b7c4cd566d0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpdirgn_yf/e69497/tftransform_tmp/02129cdfbd264bfa94f51ce3e4550371'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_tft_process_handler_unused_column (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 1m 4s]
Raw output 
RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7acab096f9d0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpar5dnqng/tftransform_tmp/abb8c35ac471406e8b4213bf95cc8dc3'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest testMethod=test_tft_process_handler_unused_column>

    def test_tft_process_handler_unused_column(self):
      data = [
          {
              'x': [5, 1], 'y': 2
          },
          {
              'x': [8, 4], 'y': 5
          },
          {
              'x': [9, 5], 'y': 6
          },
          {
              'x': [10, 6], 'y': 7
          },
          {
              'x': [11, 7], 'y': 8
          },
          {
              'x': [12, 8], 'y': 9
          },
          {
              'x': [13, 9], 'y': 10
          },
          {
              'x': [14, 10], 'y': 11
          },
          {
              'x': [15, 11], 'y': 12
          },
          {
              'x': [16, 12], 'y': 13
          },
          {
              'x': [17, 13], 'y': 14
          },
          {
              'x': [18, 14], 'y': 15
          },
          {
              'x': [19, 15], 'y': 16
          },
          {
              'x': [20, 16], 'y': 17
          },
          {
              'x': [21, 17], 'y': 18
          },
          {
              'x': [22, 18], 'y': 19
          },
          {
              'x': [23, 19], 'y': 20
          },
          {
              'x': [24, 20], 'y': 21
          },
          {
              'x': [25, 21], 'y': 22
          },
      ]
      # pylint: disable=line-too-long
      expected_data = [
          beam.Row(
              x=np.array([0.16666667, 0.], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=2),
          beam.Row(
              x=np.array([0.29166666, 0.125], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=5),
          beam.Row(
              x=np.array([0.33333334, 0.16666667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=6),
          beam.Row(
              x=np.array([0.375, 0.20833333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=7),
          beam.Row(
              x=np.array([0.41666666, 0.25], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=8),
          beam.Row(
              x=np.array([0.45833334, 0.29166666], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=9),
          beam.Row(
              x=np.array([0.5, 0.33333334], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=10),
          beam.Row(
              x=np.array([0.5416667, 0.375], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=11),
          beam.Row(
              x=np.array([0.5833333, 0.41666666], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=12),
          beam.Row(
              x=np.array([0.625, 0.45833334], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=13),
          beam.Row(
              x=np.array([0.6666667, 0.5], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=14),
          beam.Row(
              x=np.array([0.7083333, 0.5416667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=15),
          beam.Row(
              x=np.array([0.75, 0.5833333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=16),
          beam.Row(
              x=np.array([0.7916667, 0.625], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=17),
          beam.Row(
              x=np.array([0.8333333, 0.6666667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=18),
          beam.Row(
              x=np.array([0.875, 0.7083333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=19),
          beam.Row(
              x=np.array([0.9166667, 0.75], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=20),
          beam.Row(
              x=np.array([0.9583333, 0.7916667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=21),
          beam.Row(
              x=np.array([1., 0.8333333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=22),
      ]
      # pylint: enable=line-too-long
    
      expected_data_x = [row.x for row in expected_data]
      expected_data_y = [row.y for row in expected_data]
    
      scale_to_0_1_fn = tft.ScaleTo01(columns=['x'])
      with beam.Pipeline() as p:
        raw_data = p | beam.Create(data)
        process_handler = handlers.TFTProcessHandler(
            transforms=[scale_to_0_1_fn],
            artifact_location=self.artifact_location,
        )
        transformed_pcoll = raw_data | process_handler
        transformed_pcoll_x = transformed_pcoll | beam.Map(lambda x: x.x)
        transformed_pcoll_y = transformed_pcoll | beam.Map(lambda x: x.y)
        assert_that(
            transformed_pcoll_x,
            equal_to(expected_data_x, equals_fn=np.array_equal),
            label='transformed data')
    
>       assert_that(
            transformed_pcoll_y,
            equal_to(expected_data_y, equals_fn=np.array_equal),
            label='unused column')

apache_beam/ml/transforms/handlers_test.py:509: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7acab096f9d0>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpar5dnqng/tftransform_tmp/abb8c35ac471406e8b4213bf95cc8dc3'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_dict_output_pcoll_schema_3 (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 23s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b79b84fe910>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpa22nmvez/20b5ba/tftransform_tmp/285a2589a63d4acf9dcfa27e4df611f9'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

a = (<apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_dict_output_pcoll_schema_3>,)
kw = {}

    @wraps(func)
    def standalone_func(*a, **kw):
>       return func(*(a + p.args), **p.kwargs, **kw)

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/parameterized/parameterized.py:620: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/ml/transforms/base_test.py:204: in test_ml_transform_dict_output_pcoll_schema
    self.assertEqual(expected_dtype[name], typ)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b79b84fe910>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: int64>
  child 0, item: int64
y: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpa22nmvez/20b5ba/tftransform_tmp/285a2589a63d4acf9dcfa27e4df611f9'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_handler_with_same_input_elements (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 26s]
Raw output 
RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7c71ca91e400>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: large_binary>
  child 0, item: large_binary
saved_model_dir = '/tmp/tmp_gy7aqbv/tftransform_tmp/822d940a561348ba937ffb152527ba0c'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest testMethod=test_handler_with_same_input_elements>

    def test_handler_with_same_input_elements(self):
      with beam.Pipeline() as p:
        data = [
            {
                'x': 'I'
            },
            {
                'x': 'love'
            },
            {
                'x': 'Beam'
            },
            {
                'x': 'Beam'
            },
            {
                'x': 'is'
            },
            {
                'x': 'awesome'
            },
        ]
        raw_data = (p | beam.Create(data))
        process_handler = handlers.TFTProcessHandler(
            transforms=[tft.ComputeAndApplyVocabulary(columns=['x'])],
            artifact_location=self.artifact_location,
        )
        transformed_data = raw_data | process_handler
    
        expected_data = [
            beam.Row(x=np.array([4])),
            beam.Row(x=np.array([1])),
            beam.Row(x=np.array([0])),
            beam.Row(x=np.array([0])),
            beam.Row(x=np.array([2])),
            beam.Row(x=np.array([3])),
        ]
    
        expected_data_x = [row.x for row in expected_data]
        actual_data_x = transformed_data | beam.Map(lambda x: x.x)
    
>       assert_that(
            actual_data_x,
            equal_to(expected_data_x, equals_fn=np.array_equal),
            label='transformed data')

apache_beam/ml/transforms/handlers_test.py:617: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7c71ca91e400>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: large_binary>
  child 0, item: large_binary
saved_model_dir = '/tmp/tmp_gy7aqbv/tftransform_tmp/822d940a561348ba937ffb152527ba0c'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_mltransform_with_counter (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 29s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba4d107d910>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
y: large_list<item: large_binary>
  child 0, item: large_binary
saved_model_dir = '/tmp/tmp0vlg2d7r/4b2c84/tftransform_tmp/ee2f3e9ec7664158a11ae43b82b7fd6e'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_mltransform_with_counter>

    @unittest.skipIf(tft is None, 'tft module is not installed.')
    def test_mltransform_with_counter(self):
      transforms = [
          tft.ComputeAndApplyVocabulary(columns=['y']),
          tft.ScaleTo01(columns=['x'])
      ]
      data = [{'x': [1, 2, 3], 'y': ['a', 'b', 'c']}]
      with beam.Pipeline() as p:
>       _ = (
            p | beam.Create(data)
            | base.MLTransform(
                transforms=transforms,
                write_artifact_location=self.artifact_location))

apache_beam/ml/transforms/base_test.py:284: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1282: in process_bundle
    op.finish()
apache_beam/runners/worker/operations.py:981: in apache_beam.runners.worker.operations.DoOperation.finish
    def finish(self):
apache_beam/runners/worker/operations.py:984: in apache_beam.runners.worker.operations.DoOperation.finish
    with self.scoped_finish_state:
apache_beam/runners/worker/operations.py:985: in apache_beam.runners.worker.operations.DoOperation.finish
    self.dofn_runner.finish()
apache_beam/runners/common.py:1573: in apache_beam.runners.common.DoFnRunner.finish
    self._invoke_bundle_method(self.do_fn_invoker.invoke_finish_bundle)
apache_beam/runners/common.py:1554: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    self._reraise_augmented(exn)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1552: in apache_beam.runners.common.DoFnRunner._invoke_bundle_method
    bundle_method()
apache_beam/runners/common.py:615: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    def invoke_finish_bundle(self):
apache_beam/runners/common.py:620: in apache_beam.runners.common.DoFnInvoker.invoke_finish_bundle
    self.output_handler.finish_bundle_outputs(
apache_beam/runners/common.py:1844: in apache_beam.runners.common._OutputHandler.finish_bundle_outputs
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ba4d107d910>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
y: large_list<item: large_binary>
  child 0, item: large_binary
saved_model_dir = '/tmp/tmp0vlg2d7r/4b2c84/tftransform_tmp/ee2f3e9ec7664158a11ae43b82b7fd6e'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_tft_process_handler_verify_artifacts (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 22s]
Raw output 
RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ac92c746460>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpqt6gvlik/tftransform_tmp/3cc5ed1baad74005a543dd954882533b'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTest testMethod=test_tft_process_handler_verify_artifacts>

    def test_tft_process_handler_verify_artifacts(self):
      with beam.Pipeline() as p:
        raw_data = (
            p
            | beam.Create([{
                'x': np.array([1, 3])
            }, {
                'x': np.array([4, 6])
            }]))
        process_handler = handlers.TFTProcessHandler(
            transforms=[tft.ScaleTo01(columns=['x'])],
            artifact_location=self.artifact_location,
        )
        _ = raw_data | process_handler
    
        self.assertTrue(
            FileSystems.exists(
                # To check the gcs directory with FileSystems, the dir path must
                # end with /
                os.path.join(
                    self.artifact_location,
                    handlers.RAW_DATA_METADATA_DIR + '/')))
>       self.assertTrue(
            FileSystems.exists(
                os.path.join(
                    self.artifact_location,
                    handlers.RAW_DATA_METADATA_DIR,
                    handlers.SCHEMA_FILE)))

apache_beam/ml/transforms/handlers_test.py:311: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ac92c746460>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpqt6gvlik/tftransform_tmp/3cc5ed1baad74005a543dd954882533b'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTestWithGCSLocation

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_tft_process_handler_unused_column (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTestWithGCSLocation) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 40s]
Raw output 
RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7a1d504d8a90>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = 'gs://temp-storage-for-perf-tests/tft_handler/1ac2ab07a52848f1a059ec65834a55f0/tftransform_tmp/928447f849f546528f8732254ad736a2'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTestWithGCSLocation testMethod=test_tft_process_handler_unused_column>

    def test_tft_process_handler_unused_column(self):
      data = [
          {
              'x': [5, 1], 'y': 2
          },
          {
              'x': [8, 4], 'y': 5
          },
          {
              'x': [9, 5], 'y': 6
          },
          {
              'x': [10, 6], 'y': 7
          },
          {
              'x': [11, 7], 'y': 8
          },
          {
              'x': [12, 8], 'y': 9
          },
          {
              'x': [13, 9], 'y': 10
          },
          {
              'x': [14, 10], 'y': 11
          },
          {
              'x': [15, 11], 'y': 12
          },
          {
              'x': [16, 12], 'y': 13
          },
          {
              'x': [17, 13], 'y': 14
          },
          {
              'x': [18, 14], 'y': 15
          },
          {
              'x': [19, 15], 'y': 16
          },
          {
              'x': [20, 16], 'y': 17
          },
          {
              'x': [21, 17], 'y': 18
          },
          {
              'x': [22, 18], 'y': 19
          },
          {
              'x': [23, 19], 'y': 20
          },
          {
              'x': [24, 20], 'y': 21
          },
          {
              'x': [25, 21], 'y': 22
          },
      ]
      # pylint: disable=line-too-long
      expected_data = [
          beam.Row(
              x=np.array([0.16666667, 0.], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=2),
          beam.Row(
              x=np.array([0.29166666, 0.125], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=5),
          beam.Row(
              x=np.array([0.33333334, 0.16666667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=6),
          beam.Row(
              x=np.array([0.375, 0.20833333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=7),
          beam.Row(
              x=np.array([0.41666666, 0.25], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=8),
          beam.Row(
              x=np.array([0.45833334, 0.29166666], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=9),
          beam.Row(
              x=np.array([0.5, 0.33333334], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=10),
          beam.Row(
              x=np.array([0.5416667, 0.375], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=11),
          beam.Row(
              x=np.array([0.5833333, 0.41666666], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=12),
          beam.Row(
              x=np.array([0.625, 0.45833334], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=13),
          beam.Row(
              x=np.array([0.6666667, 0.5], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=14),
          beam.Row(
              x=np.array([0.7083333, 0.5416667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=15),
          beam.Row(
              x=np.array([0.75, 0.5833333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=16),
          beam.Row(
              x=np.array([0.7916667, 0.625], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=17),
          beam.Row(
              x=np.array([0.8333333, 0.6666667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=18),
          beam.Row(
              x=np.array([0.875, 0.7083333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=19),
          beam.Row(
              x=np.array([0.9166667, 0.75], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=20),
          beam.Row(
              x=np.array([0.9583333, 0.7916667], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=21),
          beam.Row(
              x=np.array([1., 0.8333333], dtype=np.float32),
              x_max=np.array([25.], dtype=np.float32),
              x_min=np.array([1.], dtype=np.float32),
              y=22),
      ]
      # pylint: enable=line-too-long
    
      expected_data_x = [row.x for row in expected_data]
      expected_data_y = [row.y for row in expected_data]
    
      scale_to_0_1_fn = tft.ScaleTo01(columns=['x'])
      with beam.Pipeline() as p:
        raw_data = p | beam.Create(data)
        process_handler = handlers.TFTProcessHandler(
            transforms=[scale_to_0_1_fn],
            artifact_location=self.artifact_location,
        )
        transformed_pcoll = raw_data | process_handler
        transformed_pcoll_x = transformed_pcoll | beam.Map(lambda x: x.x)
        transformed_pcoll_y = transformed_pcoll | beam.Map(lambda x: x.y)
        assert_that(
            transformed_pcoll_x,
            equal_to(expected_data_x, equals_fn=np.array_equal),
            label='transformed data')
    
>       assert_that(
            transformed_pcoll_y,
            equal_to(expected_data_y, equals_fn=np.array_equal),
            label='unused column')

apache_beam/ml/transforms/handlers_test.py:509: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7a1d504d8a90>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = 'gs://temp-storage-for-perf-tests/tft_handler/1ac2ab07a52848f1a059ec65834a55f0/tftransform_tmp/928447f849f546528f8732254ad736a2'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.base_test.BaseMLTransformTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_ml_transform_on_dict (apache_beam.ml.transforms.base_test.BaseMLTransformTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 27s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b7a081e7340>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpw3c6y31g/ce4d72/tftransform_tmp/eff711741fa94a0b8b044baa2c85d029'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.base_test.BaseMLTransformTest testMethod=test_ml_transform_on_dict>

    @unittest.skipIf(tft is None, 'tft module is not installed.')
    def test_ml_transform_on_dict(self):
      transforms = [tft.ScaleTo01(columns=['x'])]
      data = [{'x': 1}, {'x': 2}]
      with beam.Pipeline() as p:
        result = (
            p
            | beam.Create(data)
            | base.MLTransform(
                write_artifact_location=self.artifact_location,
                transforms=transforms))
        expected_output = [
            np.array([0.0], dtype=np.float32),
            np.array([1.0], dtype=np.float32),
        ]
        actual_output = result | beam.Map(lambda x: x.x)
>       assert_that(
            actual_output, equal_to(expected_output, equals_fn=np.array_equal))

apache_beam/ml/transforms/base_test.py:114: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7b7a081e7340>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmpw3c6y31g/ce4d72/tftransform_tmp/eff711741fa94a0b8b044baa2c85d029'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.tft_test.ScaleToGaussianTest

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_gaussian_skewed (apache_beam.ml.transforms.tft_test.ScaleToGaussianTest) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 27s]
Raw output 
RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7c717c0de490>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmplmbk2m7x/6fd4fa/tftransform_tmp/fc97b9f85e6348aca935fb746201ebc1'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.tft_test.ScaleToGaussianTest testMethod=test_gaussian_skewed>

    def test_gaussian_skewed(self):
      data = [
          {
              'x': 1
          },
          {
              'x': 2
          },
          {
              'x': 4
          },
          {
              'x': 8
          },
          {
              'x': 16
          },
          {
              'x': 32
          },
      ]
    
      with beam.Pipeline() as p:
        result = (
            p
            | "Create" >> beam.Create(data)
            | "MLTransform" >> base.MLTransform(
                write_artifact_location=self.artifact_location).with_transform(
                    tft.ScaleToZScore(columns=['x'])))
        expected_data = [
            np.array([-0.87733847], dtype=np.float32),
            np.array([-0.78498703], dtype=np.float32),
            np.array([-0.6002842], dtype=np.float32),
            np.array([-0.23087855], dtype=np.float32),
            np.array([0.5079328], dtype=np.float32),
            np.array([1.9855555], dtype=np.float32),
        ]
    
        actual_data = (result | beam.Map(lambda x: x.x))
>       assert_that(actual_data, equal_to(expected_data, equals_fn=np.allclose))

apache_beam/ml/transforms/tft_test.py:281: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7c717c0de490>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = '/tmp/tmplmbk2m7x/6fd4fa/tftransform_tmp/fc97b9f85e6348aca935fb746201ebc1'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'MLTransform/TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError

Check warning on line 0 in apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTestWithGCSLocation

See this annotation in the file changed.

@github-actions github-actions / Test Results

test_consume_mode_with_extra_columns_in_the_input (apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTestWithGCSLocation) failed 

sdks/python/test-suites/tox/py39/build/srcs/sdks/python/pytest_py39-ml.xml [took 34s]
Raw output 
RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']
>   return self.do_fn_invoker.invoke_process(windowed_value)

apache_beam/runners/common.py:1495: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ac93c643e50>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = 'gs://temp-storage-for-perf-tests/tft_handler/74384a5f1d644c2d920f99cb35b65c9d/tftransform_tmp/03bbf14c856647c4bdbd389d0694c5bc'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     AssertionError

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: AssertionError

During handling of the above exception, another exception occurred:

self = <apache_beam.ml.transforms.handlers_test.TFTProcessHandlerTestWithGCSLocation testMethod=test_consume_mode_with_extra_columns_in_the_input>

    def test_consume_mode_with_extra_columns_in_the_input(self):
      with beam.Pipeline() as p:
        raw_data = (
            p
            | beam.Create([{
                'x': np.array([1, 3])
            }, {
                'x': np.array([4, 6])
            }]))
        process_handler = handlers.TFTProcessHandler(
            transforms=[tft.ScaleTo01(columns=['x'])],
            artifact_location=self.artifact_location,
        )
>       _ = raw_data | process_handler

apache_beam/ml/transforms/handlers_test.py:527: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:644: in __exit__
    self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:618: in run
    return self.runner.run_pipeline(self, self._options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/direct/direct_runner.py:190: in run_pipeline
    return runner.run_pipeline(pipeline, options)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:196: in run_pipeline
    self._latest_run_result = self.run_via_runner_api(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:223: in run_via_runner_api
    return self.run_stages(stage_context, stages)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:470: in run_stages
    bundle_results = self._execute_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:795: in _execute_bundle
    self._run_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1034: in _run_bundle
    result, splits = bundle_manager.process_bundle(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/fn_runner.py:1360: in process_bundle
    result_future = self._worker_handler.control_conn.push(process_bundle_req)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/portability/fn_api_runner/worker_handlers.py:386: in push
    response = self.worker.do_instruction(request)
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:658: in do_instruction
    return getattr(self, request_type)(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/sdk_worker.py:696: in process_bundle
    bundle_processor.process_bundle(instruction_id))
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:1274: in process_bundle
    input_op_by_transform_id[element.transform_id].process_encoded(
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/runners/worker/bundle_processor.py:237: in process_encoded
    self.output(decoded_value)
apache_beam/runners/worker/operations.py:566: in apache_beam.runners.worker.operations.Operation.output
    def output(self, windowed_value, output_index=0):
apache_beam/runners/worker/operations.py:568: in apache_beam.runners.worker.operations.Operation.output
    _cast_to_receiver(self.receivers[output_index]).receive(windowed_value)
apache_beam/runners/worker/operations.py:259: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    def receive(self, windowed_value):
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:348: in apache_beam.runners.worker.operations.GeneralPurposeConsumerSet.receive
    _cast_to_operation(consumer).process(windowed_value)
apache_beam/runners/worker/operations.py:947: in apache_beam.runners.worker.operations.DoOperation.process
    def process(self, o):
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1585: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:683: in apache_beam.runners.common.SimpleInvoker.invoke_process
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1680: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    self._write_value_to_tag(tag, windowed_value, watermark_estimator)
apache_beam/runners/common.py:1793: in apache_beam.runners.common._OutputHandler._write_value_to_tag
    self.main_receivers.receive(windowed_value)
apache_beam/runners/worker/operations.py:262: in apache_beam.runners.worker.operations.SingletonElementConsumerSet.receive
    self.consumer.process(windowed_value)
apache_beam/runners/worker/operations.py:949: in apache_beam.runners.worker.operations.DoOperation.process
    with self.scoped_process_state:
apache_beam/runners/worker/operations.py:950: in apache_beam.runners.worker.operations.DoOperation.process
    delayed_applications = self.dofn_runner.process(o)
apache_beam/runners/common.py:1497: in apache_beam.runners.common.DoFnRunner.process
    self._reraise_augmented(exn, windowed_value)
apache_beam/runners/common.py:1606: in apache_beam.runners.common.DoFnRunner._reraise_augmented
    raise new_exn
apache_beam/runners/common.py:1495: in apache_beam.runners.common.DoFnRunner.process
    return self.do_fn_invoker.invoke_process(windowed_value)
apache_beam/runners/common.py:911: in apache_beam.runners.common.PerWindowInvoker.invoke_process
    self._invoke_process_per_window(
apache_beam/runners/common.py:1053: in apache_beam.runners.common.PerWindowInvoker._invoke_process_per_window
    self.output_handler.handle_process_outputs(
apache_beam/runners/common.py:1670: in apache_beam.runners.common._OutputHandler.handle_process_outputs
    for result in results:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 

self = <tensorflow_transform.beam.impl._RunMetaGraphDoFn object at 0x7ac93c643e50>
batch = pyarrow.RecordBatch
CODED_SAMPLE: large_list<item: large_binary>
  child 0, item: large_binary
x: large_list<item: float>
  child 0, item: float
saved_model_dir = 'gs://temp-storage-for-perf-tests/tft_handler/74384a5f1d644c2d920f99cb35b65c9d/tftransform_tmp/03bbf14c856647c4bdbd389d0694c5bc'

    def process(self, batch, saved_model_dir):
      """Runs the given graph to realize the outputs.
    
      Runs the graph in a TF session for computing the output values of the
      `Tensor`s, `SparseTensor`s, or `RaggedTensor`s, given an input row of data
      (input `Tensor`s, `SparseTensor`s, or `RaggedTensor`s).
    
      Args:
        batch: the batch of elements being processed by the DoFn
        saved_model_dir: Directory containing saved model.
    
      Yields:
        A representation of output features as a dict mapping keys (logical column
        names) to values.
      """
      if not hasattr(self, '_graph_state'):
        # If available, acquire will return a cached _GraphStateCommon, since
        # calling _make_graph_state is expensive.
        self._graph_state = self._shared_graph_state_handle.acquire(
            lambda: self._make_graph_state(saved_model_dir))
    
      # This should remain true throughout the lifetime of this DoFn, regardless
      # of whether or not self._graph_state was cached.
>     assert self._graph_state.saved_model_dir == saved_model_dir
E     RuntimeError: AssertionError [while running 'TFTProcessHandler/AnalyzeDataset/ApplySavedModel[Phase0]/ApplySavedModel']

target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/tensorflow_transform/beam/impl.py:413: RuntimeError
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