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Posted to builds@beam.apache.org by Apache Jenkins Server <je...@builds.apache.org> on 2022/06/01 07:53:00 UTC
Build failed in Jenkins: beam_PreCommit_Python_Cron #5702
See <https://ci-beam.apache.org/job/beam_PreCommit_Python_Cron/5702/display/redirect>
Changes:
------------------------------------------
[...truncated 1.11 MB...]
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 0x7f488808cb80>
client = <apache_beam.io.gcp.internal.clients.storage.storage_v1_client.StorageV1 object at 0x7f488807ed90>
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 0x7f4888075820>>
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 ===============================
apache_beam/io/filesystems_test.py:54
apache_beam/io/filesystems_test.py:54
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
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
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(
-- 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, 32 warnings in 17.64 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 53m 37s
124 actionable tasks: 89 executed, 33 from cache, 2 up-to-date
Publishing build scan...
https://gradle.com/s/6ohklsmgw3qvm
Build step 'Invoke Gradle script' changed build result to FAILURE
Build step 'Invoke Gradle script' marked build as failure
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Build failed in Jenkins: beam_PreCommit_Python_Cron #5703
Posted by Apache Jenkins Server <je...@builds.apache.org>.
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
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