[FR] Hydra Support

[AgrawalAmey]

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Willingness to contribute

The MLflow Community encourages new feature contributions. Would you or another member of your organization be willing to contribute an implementation of this feature (either as an MLflow Plugin or an enhancement to the MLflow code base)?

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• [ ] Yes. I would be willing to contribute this feature with guidance from the MLflow community.
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Proposal Summary

Hydra is great for config management and I guess some helper functions to automatically track hyper logged parameters could be pretty useful.

Motivation

• What is the use case for this feature?
• Why is this use case valuable to support for MLflow users in general?
• Why is this use case valuable to support for your project(s) or organization?
• Why is it currently difficult to achieve this use case? (please be as specific as possible about why related MLflow features and components are insufficient)

What component(s), interfaces, languages, and integrations does this feature affect?

Components

• [ ] area/artifacts: Artifact stores and artifact logging
• [ ] area/build: Build and test infrastructure for MLflow
• [ ] area/docs: MLflow documentation pages
• [ ] area/examples: Example code
• [ ] area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• [ ] area/models: MLmodel format, model serialization/deserialization, flavors
• [x] area/projects: MLproject format, project running backends
• [ ] area/scoring: Local serving, model deployment tools, spark UDFs
• [x ] area/tracking: Tracking Service, tracking client APIs, autologging

Interfaces

• [ ] area/uiux: Front-end, user experience, JavaScript, plotting
• [ ] area/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Models
• [ ] area/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registry
• [ ] area/windows: Windows support

Languages

• [ ] language/r: R APIs and clients
• [ ] language/java: Java APIs and clients

Integrations

• [ ] integrations/azure: Azure and Azure ML integrations
• [ ] integrations/sagemaker: SageMaker integrations

Details

I suppose we could just implement a decorator function that can be used alongside hyrda's.