Support padding in RLSSM
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 124
- Forks
- 24
- Avg merge
- 19h 32m
- Merged PRs (30d)
- 60
Description
If padding support is needed, we could approach it two ways:
Option 1: User-side preprocessing
Provide a separate utility tool for users to pad/mask their data before passing it to the model. This keeps the core codebase simple while giving users control over how padding is handled for their specific research context.
Option 2: Built-in support (separate PR)
Add padding as a core feature, which would require:
- General masking API across RL models (not model-specific)
- Updated validation to conditionally allow non-uniform trials when masks are provided
- Documentation on RL state propagation implications
- Comprehensive tests
Recommendation: Option 1 avoids adding complexity to the core codebase while still supporting use cases that need padding.
_Originally posted by @cpaniaguam in https://github.com/lnccbrown/HSSM/pull/864#discussion_r2665485469_
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 locating the RLSSM data-input and validation entry points, then read the linked pull request discussion. Confirm with maintainers whether the intended scope is the recommended user-side padding utility or built-in masking support; the issue does not define files, tests, or completion criteria.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100