Add documentation for copy_model_version API
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Signed-off-by: Jerry Liang <[email protected]>
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Signed-off-by: Jerry Liang <[email protected]>
BenWilson2
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Oct 26, 2023
BenWilson2
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Oct 26, 2023
| and deployment for the model. In MLflow, you can use registered models to set up environments for your | ||
| MLflow Models, where each registered model corresponds to a specific environment. Furthermore, you can | ||
| configure access controls for the registered models using :ref:`MLflow Authentication <auth>`. Then, | ||
| to promote MLflow Models across environments, you can use the :meth:`~mlflow.client.MlflowClient.copy_model_version` method |
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do we need to use :py:meth: here instead of :meth: to get the proper reference? I'm actually not sure.
spoiler alert: it renders just fine. Pretty good inference on the part of sphinx.
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Co-authored-by: Ben Wilson <[email protected]> Signed-off-by: Jerry Liang <[email protected]>
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Signed-off-by: Jerry Liang <[email protected]> Signed-off-by: Jerry Liang <[email protected]> Co-authored-by: Ben Wilson <[email protected]>
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Signed-off-by: Jerry Liang <[email protected]> Signed-off-by: Jerry Liang <[email protected]> Co-authored-by: Ben Wilson <[email protected]> Signed-off-by: swathi <[email protected]>
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#xxxWhat changes are proposed in this pull request?
As title.
How is this PR tested?
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