adamwawrzynski
commented
1 year ago When I've removed model_deployer from label_studio_annotation/pipelines/training_pipeline.py, and the whole file label_studio_annotation/steps/model_deployers.py, and removed import from steps.model_deployers import model_deployer and passing parameter model_deployer=model_deployer, to training_pipeline function call in run.py script I was able to run `python run.py --train without an issue.
Now command python run.py --inference gave me the same error as older versions I've tested, like 0.35.0 and 0.38.0. It looks like there is a problem with matching filenames in data uploaded to Label Studio and model predictions.
$ python run.py --inference
Registered pipeline inference_pipeline (version 1).
Running pipeline inference_pipeline on stack annotation_gcp (caching enabled)
Step get_or_create_dataset has started.
Step get_or_create_dataset has finished in 0.651s.
Step inference_data_loader has started.
Step inference_data_loader has finished in 4.683s.
Step prediction_service_loader has started.
Step prediction_service_loader has finished in 5.926s.
Step predictor has started.
/home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).
warnings.warn(
Step predictor has finished in 1.982s.
Step data_syncer has started.
Failed to run step data_syncer.
Pipeline run inference_pipeline-2023_05_11-13_26_16_462715 failed.
╭─────────────────────────────── Traceback (most recent call last) ────────────────────────────────╮
│ /home/user/praca/zenml_playground/label_studio/zenml_examples/label_studio_annotation/run.py:82 │
│ in <module> │
│ │
│ 79 │
│ 80 │
│ 81 if __name__ == "__main__": │
│ ❱ 82 │ main() │
│ 83 │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/click/core.py:1 │
│ 130 in __call__ │
│ │
│ 1127 │ │
│ 1128 │ def __call__(self, *args: t.Any, **kwargs: t.Any) -> t.Any: │
│ 1129 │ │ """Alias for :meth:`main`.""" │
│ ❱ 1130 │ │ return self.main(*args, **kwargs) │
│ 1131 │
│ 1132 │
│ 1133 class Command(BaseCommand): │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/click/core.py:1 │
│ 055 in main │
│ │
│ 1052 │ │ try: │
│ 1053 │ │ │ try: │
│ 1054 │ │ │ │ with self.make_context(prog_name, args, **extra) as ctx: │
│ ❱ 1055 │ │ │ │ │ rv = self.invoke(ctx) │
│ 1056 │ │ │ │ │ if not standalone_mode: │
│ 1057 │ │ │ │ │ │ return rv │
│ 1058 │ │ │ │ │ # it's not safe to `ctx.exit(rv)` here! │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/click/core.py:1 │
│ 404 in invoke │
│ │
│ 1401 │ │ │ echo(style(message, fg="red"), err=True) │
│ 1402 │ │ │
│ 1403 │ │ if self.callback is not None: │
│ ❱ 1404 │ │ │ return ctx.invoke(self.callback, **ctx.params) │
│ 1405 │ │
│ 1406 │ def shell_complete(self, ctx: Context, incomplete: str) -> t.List["CompletionItem"]: │
│ 1407 │ │ """Return a list of completions for the incomplete value. Looks │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/click/core.py:7 │
│ 60 in invoke │
│ │
│ 757 │ │ │
│ 758 │ │ with augment_usage_errors(__self): │
│ 759 │ │ │ with ctx: │
│ ❱ 760 │ │ │ │ return __callback(*args, **kwargs) │
│ 761 │ │
│ 762 │ def forward( │
│ 763 │ │ __self, __cmd: "Command", *args: t.Any, **kwargs: t.Any # noqa: B902 │
│ │
│ /home/user/praca/zenml_playground/label_studio/zenml_examples/label_studio_annotation/run.py:66 │
│ in main │
│ │
│ 63 │ │ │ deployment_trigger=deployment_trigger(), │
│ 64 │ │ ).run() │
│ 65 │ elif pipeline == "inference": │
│ ❱ 66 │ │ inference_pipeline( │
│ 67 │ │ │ get_or_create_dataset=get_or_create_the_dataset, │
│ 68 │ │ │ inference_data_loader=load_image_data( │
│ 69 │ │ │ │ params=LoadImageDataParameters( │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/pipelines │
│ /base_pipeline.py:659 in run │
│ │
│ 656 │ │ │ # unexpected behavior │
│ 657 │ │ │ constants.SHOULD_PREVENT_PIPELINE_EXECUTION = True │
│ 658 │ │ │ try: │
│ ❱ 659 │ │ │ │ stack.deploy_pipeline(deployment=deployment_model) │
│ 660 │ │ │ finally: │
│ 661 │ │ │ │ constants.SHOULD_PREVENT_PIPELINE_EXECUTION = False │
│ 662 │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/stack/sta │
│ ck.py:864 in deploy_pipeline │
│ │
│ 861 │ │ Returns: │
│ 862 │ │ │ The return value of the call to `orchestrator.run_pipeline(...)`. │
│ 863 │ │ """ │
│ ❱ 864 │ │ return self.orchestrator.run(deployment=deployment, stack=self) │
│ 865 │ │
│ 866 │ def _get_active_components_for_step( │
│ 867 │ │ self, step_config: "StepConfiguration" │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/base_orchestrator.py:166 in run │
│ │
│ 163 │ │ │
│ 164 │ │ environment = get_config_environment_vars() │
│ 165 │ │ try: │
│ ❱ 166 │ │ │ result = self.prepare_or_run_pipeline( │
│ 167 │ │ │ │ deployment=deployment, stack=stack, environment=environment │
│ 168 │ │ │ ) │
│ 169 │ │ finally: │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/local/local_orchestrator.py:82 in prepare_or_run_pipeline │
│ │
│ 79 │ │ │ │ │ step.config.name, │
│ 80 │ │ │ │ ) │
│ 81 │ │ │ │
│ ❱ 82 │ │ │ self.run_step( │
│ 83 │ │ │ │ step=step, │
│ 84 │ │ │ ) │
│ 85 │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/base_orchestrator.py:186 in run_step │
│ │
│ 183 │ │ │ step=step, │
│ 184 │ │ │ orchestrator_run_id=self.get_orchestrator_run_id(), │
│ 185 │ │ ) │
│ ❱ 186 │ │ launcher.launch() │
│ 187 │ │
│ 188 │ @staticmethod │
│ 189 │ def requires_resources_in_orchestration_environment( │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/step_launcher.py:197 in launch │
│ │
│ 194 │ │ │ │
│ 195 │ │ │ if execution_needed: │
│ 196 │ │ │ │ try: │
│ ❱ 197 │ │ │ │ │ self._run_step( │
│ 198 │ │ │ │ │ │ pipeline_run=pipeline_run, │
│ 199 │ │ │ │ │ │ step_run=step_run_response, │
│ 200 │ │ │ │ │ ) │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/step_launcher.py:375 in _run_step │
│ │
│ 372 │ │ │ │ │ step_run_info=step_run_info, │
│ 373 │ │ │ │ ) │
│ 374 │ │ │ else: │
│ ❱ 375 │ │ │ │ self._run_step_without_step_operator( │
│ 376 │ │ │ │ │ step_run_info=step_run_info, │
│ 377 │ │ │ │ │ input_artifacts=step_run.input_artifacts, │
│ 378 │ │ │ │ │ output_artifact_uris=output_artifact_uris, │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/step_launcher.py:445 in _run_step_without_step_operator │
│ │
│ 442 │ │ │ output_artifact_uris: The output artifact URIs of the current step. │
│ 443 │ │ """ │
│ 444 │ │ runner = StepRunner(step=self._step, stack=self._stack) │
│ ❱ 445 │ │ runner.run( │
│ 446 │ │ │ input_artifacts=input_artifacts, │
│ 447 │ │ │ output_artifact_uris=output_artifact_uris, │
│ 448 │ │ │ step_run_info=step_run_info, │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/orchestra │
│ tors/step_runner.py:133 in run │
│ │
│ 130 │ │ │ self._stack.prepare_step_run(info=step_run_info) │
│ 131 │ │ │ step_failed = False │
│ 132 │ │ │ try: │
│ ❱ 133 │ │ │ │ return_values = step_entrypoint(**function_params) │
│ 134 │ │ │ except BaseException as step_exception: # noqa: E722 │
│ 135 │ │ │ │ step_failed = True │
│ 136 │ │ │ │ failure_hook_source = self.configuration.failure_hook_source │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/integrati │
│ ons/label_studio/steps/label_studio_standard_steps.py:240 in sync_new_data_to_label_studio │
│ │
│ 237 │ │ │ filename_reference = TASK_TO_FILENAME_REFERENCE_MAPPING[ │
│ 238 │ │ │ │ params.label_config_type │
│ 239 │ │ │ ] │
│ ❱ 240 │ │ │ preds_with_task_ids = convert_pred_filenames_to_task_ids( │
│ 241 │ │ │ │ predictions, │
│ 242 │ │ │ │ dataset.tasks, │
│ 243 │ │ │ │ filename_reference, │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/integrati │
│ ons/label_studio/label_studio_utils.py:51 in convert_pred_filenames_to_task_ids │
│ │
│ 48 │ │ │ {"filename": quote(pred["filename"]), "result": pred["result"]} │
│ 49 │ │ │ for pred in preds │
│ 50 │ │ ] │
│ ❱ 51 │ return [ │
│ 52 │ │ { │
│ 53 │ │ │ "task": int( │
│ 54 │ │ │ │ filename_id_mapping[os.path.basename(pred["filename"])] │
│ │
│ /home/user/praca/zenml_playground/label_studio/.venv/lib/python3.8/site-packages/zenml/integrati │
│ ons/label_studio/label_studio_utils.py:54 in <listcomp> │
│ │
│ 51 │ return [ │
│ 52 │ │ { │
│ 53 │ │ │ "task": int( │
│ ❱ 54 │ │ │ │ filename_id_mapping[os.path.basename(pred["filename"])] │
│ 55 │ │ │ ), │
│ 56 │ │ │ "result": pred["result"], │
│ 57 │ │ } │
╰──────────────────────────────────────────────────────────────────────────────────────────────────╯
KeyError: 'ARIA_IMG_1481.jpeg'
fa9r
strickvl
Contact Details [Optional]
adamwawrzynski@wp.pl
System Information
ZENML_LOCAL_VERSION: 0.39.1 ZENML_SERVER_VERSION: 0.39.1 ZENML_SERVER_DATABASE: sqlite ZENML_SERVER_DEPLOYMENT_TYPE: other ZENML_CONFIG_DIR: /home/user/.config/zenml ZENML_LOCAL_STORE_DIR: /home/user/.config/zenml/local_stores ZENML_SERVER_URL: sqlite:////home/user/.config/zenml/local_stores/default_zen_store/zenml.db ZENML_ACTIVE_REPOSITORY_ROOT: /home/user/praca/zenml_playground/label_studio/zenml_examples/label_studio_annotation PYTHON_VERSION: 3.8.16 ENVIRONMENT: native SYSTEM_INFO: {'os': 'linux', 'linux_distro': 'ubuntu', 'linux_distro_like': 'debian', 'linux_distro_version': '22.04'} ACTIVE_WORKSPACE: default ACTIVE_STACK: annotation_gcp ACTIVE_USER: default TELEMETRY_STATUS: enabled ANALYTICS_CLIENT_ID: 57f7fb12-7d7f-45e7-8425-422a67baee43 ANALYTICS_USER_ID: f76122fb-e645-423c-b5e0-459bc7c11e1f ANALYTICS_SERVER_ID: 57f7fb12-7d7f-45e7-8425-422a67baee43 INTEGRATIONS: ['gcp', 'kaniko', 'kubeflow', 'kubernetes', 'label_studio', 'pillow', 'pytorch', 'seldon'] PACKAGES: {'certifi': '2023.5.7', 'regex': '2023.5.5', 'gcsfs': '2023.5.0', 'fsspec': '2023.5.0', 'tzdata': '2023.3', 'pytz': '2019.3', 'setuptools': '65.6.3', 'cryptography': '40.0.2', 'pyzmq': '25.0.2', 'pip': '23.1.2', 'packaging': '23.1', 'attrs': '23.1.0', 'argon2-cffi': '21.3.0', 'argon2-cffi-bindings': '21.2.0', 'isoduration': '20.11.0', 'kubernetes': '18.20.0', 'lit': '16.0.3', 'azure-storage-blob': '12.16.0', 'rich': '12.6.0', 'nvidia-cublas-cu11': '11.10.3.66', 'nvidia-cuda-cupti-cu11': '11.7.101', 'nvidia-cuda-runtime-cu11': '11.7.99', 'nvidia-cuda-nvrtc-cu11': '11.7.99', 'nvidia-nvtx-cu11': '11.7.91', 'nvidia-cusparse-cu11': '11.7.4.91', 'nvidia-cusolver-cu11': '11.4.0.1', 'websockets': '11.0.3', 'nvidia-cufft-cu11': '10.9.0.58', 'nvidia-curand-cu11': '10.2.10.91', 'pillow': '9.5.0', 'ipython': '8.12.2', 'nvidia-cudnn-cu11': '8.5.0.96', 'jupyter-client': '8.2.0', 'click': '8.1.3', 'ipywidgets': '7.7.5', 'nbconvert': '7.4.0', 'launchdarkly-server-sdk': '7.3.0', 'ipykernel': '6.23.0', 'importlib-metadata': '6.6.0', 'notebook': '6.5.4', 'tornado': '6.3.1', 'multidict': '6.0.4', 'docker': '6.0.1', 'bleach': '6.0.0', 'importlib-resources': '5.12.0', 'psutil': '5.9.5', 'traitlets': '5.9.0', 'nbformat': '5.8.0', 'ujson': '5.7.0', 'pyyaml': '5.4.1', 'jupyter-core': '5.3.0', 'cachetools': '5.3.0', 'decorator': '5.1.1', 'smmap': '5.0.0', 'tqdm': '4.65.0', 'beautifulsoup4': '4.12.2', 'lxml': '4.9.2', 'rsa': '4.9', 'pexpect': '4.8.0', 'redis': '4.5.5', 'typing-extensions': '4.5.0', 'django-model-utils': '4.1.1', 'gitdb': '4.0.10', 'async-timeout': '4.0.2', 'ordered-set': '4.0.2', 'bcrypt': '4.0.1', 'cmake': '3.26.3', 'protobuf': '3.20.3', 'simplejson': '3.19.1', 'google-cloud-build': '3.16.0', 'zipp': '3.15.0', 'djangorestframework': '3.13.1', 'filelock': '3.12.0', 'google-cloud-bigquery': '3.10.0', 'orjson': '3.8.12', 'aiohttp': '3.8.4', 'nltk': '3.6.7', 'widgetsnbextension': '3.6.4', 'anyio': '3.6.2', 'django-cors-headers': '3.6.0', 'asgiref': '3.6.0', 'platformdirs': '3.5.0', 'idna': '3.4', 'python-jose': '3.3.0', 'django': '3.2.14', 'oauthlib': '3.2.2', 'django-debug-toolbar': '3.2.1', 'jsonschema': '3.2.0', 'gitpython': '3.1.31', 'jinja2': '3.1.2', 'django-extensions': '3.1.0', 'networkx': '3.1', 'prompt-toolkit': '3.0.38', 'uritemplate': '3.0.1', 'boto': '2.49.0', 'requests': '2.27.1', 'pycparser': '2.21', 'google-auth': '2.18.0', 'fastjsonschema': '2.16.3', 'google-cloud-secret-manager': '2.16.1', 'pygments': '2.15.1', 'nvidia-nccl-cu11': '2.14.3', 'semver': '2.13.0', 'google-api-core': '2.11.0', 'google-cloud-scheduler': '2.11.0', 'psycopg2-binary': '2.9.1', 'python-dateutil': '2.8.2', 'google-cloud-logging': '2.7.2', 'django-rq': '2.5.1', 'jupyter-server': '2.5.0', 'google-cloud-storage': '2.5.0', 'pyparsing': '2.4.7', 'soupsieve': '2.4.1', 'django-filter': '2.4.0', 'google-resumable-media': '2.3.3', 'coreapi': '2.3.3', 'google-cloud-core': '2.3.2', 'jsonpointer': '2.3', 'termcolor': '2.3.0', 'asttokens': '2.2.1', 'cloudpickle': '2.2.1', 'django-rest-swagger': '2.2.0', 'rules': '2.2', 'user-agents': '2.2.0', 'markupsafe': '2.1.2', 'charset-normalizer': '2.0.12', 'mistune': '2.0.5', 'python-json-logger': '2.0.4', 'greenlet': '2.0.2', 'torch': '2.0.1', 'triton': '2.0.0', 'googleapis-common-protos': '1.56.4', 'grpcio': '1.54.0', 'grpcio-status': '1.48.2', 'urllib3': '1.26.15', 'azure-core': '1.26.4', 'google-cloud-aiplatform': '1.25.0', 'numpy': '1.24.3', 'proto-plus': '1.22.2', 'sentry-sdk': '1.22.2', 'drf-yasg': '1.20.0', 'botocore': '1.19.63', 'boto3': '1.16.63', 'six': '1.16.0', 'cffi': '1.15.1', 'wrapt': '1.15.0', 'webcolors': '1.13', 'google-api-python-client': '1.12.11', 'sympy': '1.12', 'google-cloud-functions': '1.12.0', 'pydantic': '1.10.7', 'rq': '1.10.1', 'backoff': '1.10.0', 'google-cloud-resource-manager': '1.10.0', 'yarl': '1.9.2', 'kfp': '1.8.16', 'shapely': '1.8.5.post1', 'kfp-server-api': '1.8.5', 'send2trash': '1.8.2', 'alembic': '1.8.1', 'distro': '1.8.0', 'passlib': '1.7.4', 'debugpy': '1.6.7', 'monotonic': '1.6', 'label-studio': '1.6.0', 'nest-asyncio': '1.5.6', 'websocket-client': '1.5.1', 'fqdn': '1.5.1', 'pandocfilters': '1.5.0', 'google-crc32c': '1.5.0', 'sqlalchemy': '1.4.41', 'appdirs': '1.4.4', 'analytics-python': '1.4.post1', 'absl-py': '1.4.0', 'pkgutil-resolve-name': '1.3.10', 'pandas': '1.3.5', 'frozenlist': '1.3.3', 'openapi-codec': '1.3.2', 'requests-oauthlib': '1.3.1', 'aiosignal': '1.3.1', 'sniffio': '1.3.0', 'mpmath': '1.3.0', 'deprecated': '1.2.13', 'mako': '1.2.4', 'arrow': '1.2.3', 'tinycss2': '1.2.1', 'itypes': '1.2.0', 'executing': '1.2.0', 'uri-template': '1.2.0', 'joblib': '1.2.0', 'expiringdict': '1.1.4', 'jupyterlab-widgets': '1.1.4', 'google-cloud-appengine-logging': '1.1.0', 'pyrfc3339': '1.1', 'pymysql': '1.0.3', 'google-auth-oauthlib': '1.0.0', 'python-dotenv': '1.0.0', 'nbclassic': '1.0.0', 'fastapi': '0.75.2', 'zenml': '0.39.1', 'wheel': '0.38.4', 'sqlalchemy-utils': '0.38.3', 'pyrsistent': '0.19.3', 'httplib2': '0.19.1', 'validators': '0.18.2', 'jedi': '0.18.2', 'ecdsa': '0.18.0', 'ruamel.yaml': '0.17.26', 'uvicorn': '0.17.6', 'starlette': '0.17.1', 'terminado': '0.17.1', 'uvloop': '0.17.0', 'ua-parser': '0.16.1', 'prometheus-client': '0.16.0', 'torchvision': '0.15.2', 'docstring-parser': '0.15', 'h11': '0.14.0', 'grpc-google-iam-v1': '0.12.6', 'lockfile': '0.12.2', 'django-annoying': '0.10.6', 'requests-toolbelt': '0.10.1', 'python-terraform': '0.10.1', 'jmespath': '0.10.0', 'drf-flex-fields': '0.9.5', 'commonmark': '0.9.1', 'tabulate': '0.9.0', 'typer': '0.9.0', 'parso': '0.8.3', 'watchgod': '0.8.2', 'pickleshare': '0.7.5', 'nbclient': '0.7.4', 'defusedxml': '0.7.1', 'ptyprocess': '0.7.0', 'jupyter-events': '0.6.3', 'stack-data': '0.6.2', 'isodate': '0.6.1', 'webencodings': '0.5.1', 'inflection': '0.5.1', 'httptools': '0.5.0', 'pyasn1': '0.5.0', 'fire': '0.5.0', 'colorama': '0.4.6', 'sqlparse': '0.4.4', 'jupyter-server-terminals': '0.4.4', 'django-user-agents': '0.4.0', 's3transfer': '0.3.7', 'attr': '0.3.1', 'pyasn1-modules': '0.3.0', 'click-params': '0.3.0', 'drf-dynamic-fields': '0.3.0', 'drf-generators': '0.3.0', 'ruamel.yaml.clib': '0.2.7', 'wcwidth': '0.2.6', 'notebook-shim': '0.2.3', 'jupyterlab-pygments': '0.2.2', 'pure-eval': '0.2.2', 'fastapi-utils': '0.2.1', 'ipython-genutils': '0.2.0', 'google-cloud-audit-log': '0.2.0', 'xmljson': '0.2.0', 'backcall': '0.2.0', 'kfp-pipeline-spec': '0.1.16', 'htmlmin': '0.1.12', 'strip-hints': '0.1.10', 'matplotlib-inline': '0.1.6', 'rfc3339-validator': '0.1.4', 'boxing': '0.1.4', 'comm': '0.1.3', 'django-ranged-fileresponse': '0.1.2', 'rfc3986-validator': '0.1.1', 'google-auth-httplib2': '0.1.0', 'label-studio-converter': '0.0.44', 'label-studio-sdk': '0.0.23', 'sqlmodel': '0.0.8', 'python-multipart': '0.0.6', 'coreschema': '0.0.4', 'sqlalchemy2-stubs': '0.0.2a34', 'label-studio-tools': '0.0.1'}
CURRENT STACK
Name: annotation_gcp ID: 74dca47f-cd22-4f0c-8867-d0ddbea65dd4 Shared: No User: default / f76122fb-e645-423c-b5e0-459bc7c11e1f Workspace: default / ef66861d-f662-47f7-8fb2-7f60a7f8e8d3
ORCHESTRATOR: default
Name: default ID: d5a4642a-6849-4f15-a361-0380bdec52a4 Type: orchestrator Flavor: local Configuration: {} Shared: No User: default / f76122fb-e645-423c-b5e0-459bc7c11e1f Workspace: default / ef66861d-f662-47f7-8fb2-7f60a7f8e8d3
ARTIFACT_STORE: gcp_artifact_store
Name: gcp_artifact_store ID: 49628835-50e5-4618-8d51-7f2e57809153 Type: artifact_store Flavor: gcp Configuration: {'authentication_secret': 'GCP_AUTH_SECRET', 'path': 'gs://label_studio_example'} Shared: No User: default / f76122fb-e645-423c-b5e0-459bc7c11e1f Workspace: default / ef66861d-f662-47f7-8fb2-7f60a7f8e8d3
ANNOTATOR: label_studio
Name: label_studio ID: 84ecd3bb-85f3-474b-9f9c-db2ce4ff9856 Type: annotator Flavor: label_studio Configuration: {'authentication_secret': 'LABEL_STUDIO_SECRET', 'instance_url': 'http://localhost', 'port': 8093} Shared: No User: default / f76122fb-e645-423c-b5e0-459bc7c11e1f Workspace: default / ef66861d-f662-47f7-8fb2-7f60a7f8e8d3
What happened?
I've tried to run the example with Label Studio from
zenmlin version0.39.1and I've encountered errors due to missing packages:zenml.artifactsremoved in release0.39.0.Reproduction steps
python run.py --trainRelevant log output
Code of Conduct