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Add an info log when xgboost autologging metric names are sanitized #5459
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autoformat |
Signed-off-by: mlflow-automation <mlflow-automation@users.noreply.github.com>
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LGTM!
( | ||
first_pos_arg, | ||
second_pos_arg, | ||
) = mock_info_log.call_args[0] |
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first_pos_arg, second_pos_arg = mock_info_log.call_args[0]
nit: can we remove ()
? I think this is easier to read and shorter.
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Done!
Signed-off-by: dbczumar <corey.zumar@databricks.com>
autoformat |
Signed-off-by: mlflow-automation <mlflow-automation@users.noreply.github.com>
…lflow#5459) * Warning Signed-off-by: dbczumar <corey.zumar@databricks.com> * Use info instead, test Signed-off-by: dbczumar <corey.zumar@databricks.com> * Negative Signed-off-by: dbczumar <corey.zumar@databricks.com> * Fix Signed-off-by: dbczumar <corey.zumar@databricks.com> * Autoformat: https://github.com/mlflow/mlflow/actions/runs/1939434612 Signed-off-by: mlflow-automation <mlflow-automation@users.noreply.github.com> * Parens Signed-off-by: dbczumar <corey.zumar@databricks.com> * Autoformat: https://github.com/mlflow/mlflow/actions/runs/1948083518 Signed-off-by: mlflow-automation <mlflow-automation@users.noreply.github.com> Co-authored-by: mlflow-automation <mlflow-automation@users.noreply.github.com>
What changes are proposed in this pull request?
Add an info log when xgboost autologging metric names are sanitized
How is this patch tested?
Unit tests
Does this PR change the documentation?
ci/circleci: build_doc
check. If it's successful, proceed to thenext step, otherwise fix it.
Details
on the right to open the job page of CircleCI.Artifacts
tab.docs/build/html/index.html
.Release Notes
Add an info log when xgboost autologging metric names are sanitized
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/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models
: MLmodel format, model serialization/deserialization, flavorsarea/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/breaking-change
- The PR will be mentioned in the "Breaking Changes" sectionrn/none
- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" 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