microsoft / microsoft/dstoolkit-mlops-v2
Configuration Usability issues with many model implementations
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 33
- Forks
- 17
- PR merge metrics
- No merged PRs in 30d
Description
Some users may find that use of a single configuration file, config/config.yaml, could become cumbersome and prone to error as more models are supported by the Model Factory. There is an opportunity to adopt a more modular approach to configuration that leverages a common configuration file and model-specific configuration files. Under this approach, all properties common across all models would be defined one-time in a common-config.yaml file, and all model-specific properties would be placed in a single file per model (ie {model}_config.yaml). We welcome contributors to raise a pull request that implements this approach for consideration by the project leadership.
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by examining config/config.yaml and the Model Factory to understand which properties are shared and which are model-specific. The proposed result is a common-config.yaml plus one {model}_config.yaml per model, with configuration loading and behavior remaining correct; the issue does not name tests or other entry points.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning, tooling
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100