See <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/5703/display/redirect>
Changes: ------------------------------------------ [...truncated 1.07 MB...] [gw5] linux -- Python 3.8.10 <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/target/.tox-py38-pytorch-19/py38-pytorch-19/bin/python> self = <apache_beam.ml.inference.pytorch_test.PytorchRunInferenceTest testMethod=test_pipeline_gcs_model> def test_pipeline_gcs_model(self): with TestPipeline() as pipeline: examples = torch.from_numpy( np.array([1, 5, 3, 10], dtype="float32").reshape(-1, 1)) expected_predictions = [ PredictionResult(ex, pred) for ex, pred in zip( examples, torch.Tensor([example * 2.0 + 0.5 for example in examples]).reshape(-1, 1)) ] gs_pth = 'gs://apache-beam-ml/pytorch_lin_reg_model_2x+0.5_state_dict.pth' model_loader = PytorchModelLoader( state_dict_path=gs_pth, model_class=PytorchLinearRegression, model_params={ 'input_dim': 1, 'output_dim': 1 }) pcoll = pipeline | 'start' >> beam.Create(examples) predictions = pcoll | RunInference(model_loader) > assert_that( predictions, equal_to(expected_predictions, equals_fn=_compare_prediction_result)) apache_beam/ml/inference/pytorch_test.py:191: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ apache_beam/pipeline.py:596: in __exit__ self.result = self.run() apache_beam/testing/test_pipeline.py:112: in run result = super().run( apache_beam/pipeline.py:546: in run return Pipeline.from_runner_api( apache_beam/pipeline.py:573: in run return self.runner.run_pipeline(self, self._options) apache_beam/runners/direct/direct_runner.py:131: in run_pipeline return runner.run_pipeline(pipeline, options) apache_beam/runners/portability/fn_api_runner/fn_runner.py:199: in run_pipeline self._latest_run_result = self.run_via_runner_api( apache_beam/runners/portability/fn_api_runner/fn_runner.py:208: in run_via_runner_api return self.run_stages(stage_context, stages) apache_beam/runners/portability/fn_api_runner/fn_runner.py:408: in run_stages bundle_results = self._execute_bundle( apache_beam/runners/portability/fn_api_runner/fn_runner.py:736: in _execute_bundle self._run_bundle( apache_beam/runners/portability/fn_api_runner/fn_runner.py:965: in _run_bundle result, splits = bundle_manager.process_bundle( apache_beam/runners/portability/fn_api_runner/fn_runner.py:1275: in process_bundle result_future = self._worker_handler.control_conn.push(process_bundle_req) apache_beam/runners/portability/fn_api_runner/worker_handlers.py:378: in push response = self.worker.do_instruction(request) apache_beam/runners/worker/sdk_worker.py:597: in do_instruction return getattr(self, request_type)( apache_beam/runners/worker/sdk_worker.py:628: in process_bundle bundle_processor = self.bundle_processor_cache.get( apache_beam/runners/worker/sdk_worker.py:458: in get processor = bundle_processor.BundleProcessor( apache_beam/runners/worker/bundle_processor.py:872: in __init__ op.setup() apache_beam/runners/worker/operations.py:882: in setup self.dofn_runner.setup() apache_beam/runners/common.py:1458: in setup self._invoke_lifecycle_method(self.do_fn_invoker.invoke_setup) apache_beam/runners/common.py:1454: in _invoke_lifecycle_method self._reraise_augmented(exn) apache_beam/runners/common.py:1494: in _reraise_augmented raise new_exn.with_traceback(tb) apache_beam/runners/common.py:1452: in _invoke_lifecycle_method lifecycle_method() apache_beam/runners/common.py:551: in invoke_setup self.signature.setup_lifecycle_method.method_value() apache_beam/ml/inference/base.py:210: in setup self._model = self._load_model() apache_beam/ml/inference/base.py:204: in _load_model return self._shared_model_handle.acquire(load) apache_beam/utils/shared.py:305: in acquire return _shared_map.acquire(self._key, constructor_fn, tag) apache_beam/utils/shared.py:246: in acquire result = control_block.acquire(constructor_fn, tag) apache_beam/utils/shared.py:139: in acquire result = constructor_fn() apache_beam/ml/inference/base.py:194: in load model = self._model_loader.load_model() apache_beam/ml/inference/pytorch.py:109: in load_model file = FileSystems.open(self._state_dict_path, 'rb') apache_beam/io/filesystems.py:244: in open return filesystem.open(path, mime_type, compression_type) apache_beam/io/gcp/gcsfilesystem.py:192: in open return self._path_open(path, 'rb', mime_type, compression_type) apache_beam/io/gcp/gcsfilesystem.py:153: in _path_open raw_file = self._gcsIO().open(path, mode, mime_type=mime_type) apache_beam/io/gcp/gcsio.py:236: in open downloader = GcsDownloader( _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ self = <apache_beam.io.gcp.gcsio.GcsDownloader object at 0x7fd71f55e370> client = <apache_beam.io.gcp.internal.clients.storage.storage_v1_client.StorageV1 object at 0x7fd71f5649d0> path = 'gs://apache-beam-ml/pytorch_lin_reg_model_2x+0.5_state_dict.pth' buffer_size = 16777216 get_project_number = <bound method GcsIO.get_project_number of <apache_beam.io.gcp.gcsio.GcsIO object at 0x7fd71f55e2e0>> def __init__(self, client, path, buffer_size, get_project_number): self._client = client self._path = path self._bucket, self._name = parse_gcs_path(path) self._buffer_size = buffer_size self._get_project_number = get_project_number # Create a request count metric resource = resource_identifiers.GoogleCloudStorageBucket(self._bucket) labels = { monitoring_infos.SERVICE_LABEL: 'Storage', monitoring_infos.METHOD_LABEL: 'Objects.get', monitoring_infos.RESOURCE_LABEL: resource, monitoring_infos.GCS_BUCKET_LABEL: self._bucket } project_number = self._get_project_number(self._bucket) if project_number: labels[monitoring_infos.GCS_PROJECT_ID_LABEL] = str(project_number) else: _LOGGER.debug( 'Possibly missing storage.buckets.get permission to ' 'bucket %s. Label %s is not added to the counter because it ' 'cannot be identified.', self._bucket, monitoring_infos.GCS_PROJECT_ID_LABEL) service_call_metric = ServiceCallMetric( request_count_urn=monitoring_infos.API_REQUEST_COUNT_URN, base_labels=labels) # Get object state. self._get_request = ( storage.StorageObjectsGetRequest( bucket=self._bucket, object=self._name)) try: metadata = self._get_object_metadata(self._get_request) except HttpError as http_error: service_call_metric.call(http_error) if http_error.status_code == 404: > raise IOError(errno.ENOENT, 'Not found: %s' % self._path) E RuntimeError: FileNotFoundError: [Errno 2] Not found: gs://apache-beam-ml/pytorch_lin_reg_model_2x+0.5_state_dict.pth [while running 'RunInference/ParDo(_RunInferenceDoFn)'] apache_beam/io/gcp/gcsio.py:661: RuntimeError ----------------------------- Captured stderr call ----------------------------- WARNING:root:Make sure that locally built Python SDK docker image has Python 3.8 interpreter. ------------------------------ Captured log call ------------------------------- WARNING root:environments.py:371 Make sure that locally built Python SDK docker image has Python 3.8 interpreter. =============================== warnings summary =============================== target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py>:331: PytestUnknownMarkWarning: Unknown pytest.mark.uses_java_expansion_service - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/latest/mark.html warnings.warn( target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py:42 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py:42 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py:42 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py:42 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py:42 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py:42 <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/tenacity/_asyncio.py>:42: DeprecationWarning: "@coroutine" decorator is deprecated since Python 3.8, use "async def" instead def call(self, fn, *args, **kwargs): target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py:331 <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/target/.tox-py38-pytorch-19/py38-pytorch-19/lib/python3.8/site-packages/_pytest/mark/structures.py>:331: PytestUnknownMarkWarning: Unknown pytest.mark.uses_python_expansion_service - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/latest/mark.html warnings.warn( apache_beam/io/filesystems_test.py:54 apache_beam/io/filesystems_test.py:54 <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/apache_beam/io/filesystems_test.py>:54: DeprecationWarning: invalid escape sequence \c self.assertIsNone(FileSystems.get_scheme('c:\\abc\cdf')) # pylint: disable=anomalous-backslash-in-string apache_beam/io/filesystems_test.py:62 apache_beam/io/filesystems_test.py:62 <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/apache_beam/io/filesystems_test.py>:62: DeprecationWarning: invalid escape sequence \d self.assertTrue(isinstance(FileSystems.get_filesystem('c:\\abc\def'), # pylint: disable=anomalous-backslash-in-string -- Docs: https://docs.pytest.org/en/latest/warnings.html - generated xml file: <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/pytest_py38-pytorch-19.xml> - =============== 1 failed, 6 passed, 28 warnings in 20.01 seconds =============== [31mERROR: InvocationError for command <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/target/.tox-py38-pytorch-19/py38-pytorch-19/bin/pytest> -o junit_suite_name=py38-pytorch-19 --junitxml=pytest_py38-pytorch-19.xml -n 6 -m uses_pytorch (exited with code 1) [0m[1mpy38-pytorch-19 run-test-post: commands[0] | bash <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/ws/src/sdks/python/test-suites/tox/py38/build/srcs/sdks/python/scripts/run_tox_cleanup.sh> [0m___________________________________ summary ____________________________________ [31mERROR: py38-pytorch-19: commands failed [0m > Task :sdks:python:test-suites:tox:py38:testPy38pytorch-19 FAILED FAILURE: Build completed with 2 failures. 1: Task failed with an exception. ----------- * What went wrong: Execution failed for task ':sdks:python:test-suites:tox:py38:testPy38pytorch-110'. > Process 'command 'sh'' finished with non-zero exit value 1 * Try: > Run with --stacktrace option to get the stack trace. > Run with --info or --debug option to get more log output. > Run with --scan to get full insights. ============================================================================== 2: Task failed with an exception. ----------- * What went wrong: Execution failed for task ':sdks:python:test-suites:tox:py38:testPy38pytorch-19'. > Process 'command 'sh'' finished with non-zero exit value 1 * Try: > Run with --stacktrace option to get the stack trace. > Run with --info or --debug option to get more log output. > Run with --scan to get full insights. ============================================================================== * Get more help at https://help.gradle.org Deprecated Gradle features were used in this build, making it incompatible with Gradle 8.0. You can use '--warning-mode all' to show the individual deprecation warnings and determine if they come from your own scripts or plugins. See https://docs.gradle.org/7.4/userguide/command_line_interface.html#sec:command_line_warnings BUILD FAILED in 57m 25s 124 actionable tasks: 89 executed, 33 from cache, 2 up-to-date Publishing build scan... https://gradle.com/s/5zwvkf7sh2np4 Build step 'Invoke Gradle script' changed build result to FAILURE Build step 'Invoke Gradle script' marked build as failure --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
