Merge master into branch-2.0#6686
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Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
mlflow/sagemaker/__init__.py
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| } | ||
| mfs.deploy(..., vpc_config=vpc_config) | ||
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| :param data_capture_config: A dictionary specifying the data capture configuration to use when |
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Can we remove this? We have two data_capture_config param descriptions.
Signed-off-by: dbczumar <[email protected]>
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Should we revert the changes in examples/pipelines/sklearn_regression? |
| class PyFuncModelMatcher: | ||
| def __eq__(self, other): | ||
| return isinstance(other, mlflow.pyfunc.PyFuncModel) |
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Can we revert this? This class is used in test_evaluator_evaluation_interface.
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Thanks for catching this - reverted!
tests/models/test_evaluation.py
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| classifier_model = mlflow.pyfunc.load_model(multiclass_logistic_regressor_model_uri) | ||
| with expected_error: | ||
| evaluate( | ||
| classifier_model, |
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| classifier_model, | |
| multiclass_logistic_regressor_model_uri, |
I think this line needs to be fixed. evaluate no longer accepts a pyfunc model.
harupy
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LGTM once remaining comments are addressed!
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We can remove files in |
No, we should update the pipelines submodule to the same commit used on |
Thanks! Removed! |
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar <[email protected]>
Signed-off-by: dbczumar [email protected]
What changes are proposed in this pull request?
Merge master into branch-2.0
How is this patch tested?
Existing CI
Does this PR change the documentation?
Detailslink on thePreview docscheck.Release Notes
Is this a user-facing change?
(Details in 1-2 sentences. You can just refer to another PR with a description if this PR is part of a larger 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/pipelines: Pipelines, Pipeline APIs, Pipeline configs, Pipeline 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/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