Check ImportError and surface early #10189
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Signed-off-by: Ann Zhang <[email protected]>
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Signed-off-by: Ann Zhang <[email protected]>
harupy
reviewed
Oct 27, 2023
mlflow/metrics/genai/genai_metric.py
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| raise MlflowException(e) | ||
| return None, f"Failed to score model on payload. Error: {e!s}" | ||
| raise e | ||
| elif isinstance(e, ImportError): |
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We can add a handler for ImportError instead of using isinstance
try:
...
except ImportError:
raise
except Exepction:
...
sunishsheth2009
approved these changes
Oct 27, 2023
Signed-off-by: Ann Zhang <[email protected]>
Signed-off-by: Ann Zhang <[email protected]>
Signed-off-by: Ann Zhang <[email protected]>
Signed-off-by: Ann Zhang <[email protected]>
harupy
reviewed
Oct 27, 2023
harupy
reviewed
Oct 27, 2023
prithvikannan
approved these changes
Oct 27, 2023
Co-authored-by: Harutaka Kawamura <[email protected]> Signed-off-by: Ann Zhang <[email protected]>
Co-authored-by: Harutaka Kawamura <[email protected]> Signed-off-by: Ann Zhang <[email protected]>
KonakanchiSwathi
pushed a commit
to KonakanchiSwathi/mlflow
that referenced
this pull request
Nov 29, 2023
Signed-off-by: Ann Zhang <[email protected]> Co-authored-by: Harutaka Kawamura <[email protected]> Signed-off-by: swathi <[email protected]>
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Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
How is this PR tested?
Used to be error only visible in justification:
Now fails:
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/docs: MLflow documentation pagesarea/examples: Example codearea/gateway: AI Gateway service, Gateway client APIs, third-party Gateway integrationsarea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes