Remove deprecated azureml modules#6691
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BenWilson2 merged 4 commits intobranch-2.0from Sep 6, 2022
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Signed-off-by: Ben Wilson <[email protected]>
Signed-off-by: Ben Wilson <[email protected]>
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Signed-off-by: Ben Wilson <[email protected]>
dbczumar
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Sep 2, 2022
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| The MLflow command-line interface (CLI) provides a simple interface to various functionality in MLflow. You can use the CLI to run projects, start the tracking UI, create and list experiments, download run artifacts, | ||
| serve MLflow Python Function and scikit-learn models, and serve models on | ||
| `Microsoft Azure Machine Learning <https://azure.microsoft.com/en-us/services/machine-learning-service/>`_ |
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You can still use the mlflow deployments CLI to deploy on AzureML after installing the azureml-mlflow plugin, so we should leave this here.
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LGTM once https://github.com/mlflow/mlflow/pull/6691/files#r962023045 is addressed. Can we also double check and make sure there are no more docs references to the mlflow.azureml module?
Thanks @BenWilson2 !
Signed-off-by: Ben Wilson <[email protected]>
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Signed-off-by: Ben Wilson [email protected]
Related Issues/PRs
#xxx
What changes are proposed in this pull request?
Remove deprecated
mlflow.azuremlmodule and referencesHow is this patch tested?
Existing tests (mostly validating removal of tests)
Does this PR change the documentation?
Detailslink on thePreview docscheck.Release Notes
Is this a user-facing change?
mlflow.azureml, which has been deprecated since 1.19.0, is now removed.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