meta-pytorch / meta-pytorch/data
[RFC] Remove the need for super().__init__() call in BaseNode subclasses to better support dataclasses
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- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 179
- Avg merge
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- Merged PRs (30d)
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Description
🚀 The feature
Stop requiring BaseNode implementations to call super().init()
Motivation, pitch
Currently we require users to call super().init() but this can't be done easily with dataclasses, except in post_init. See eg nn.Module:
Alternatives
We could just leave it as-is, since DataClasses have a viable workaround with __post_init__. Right now we're only setting up a flag but it may be useful for other things in the future, such as registration with a global thread executor. Alternatively we could use a Loader wrapper class to register with an executor.
Additional context
No response
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
No file or test is named. Start by locating BaseNode, its subclasses, and the current super().init() flag setup, then compare dataclass initialization and the alternatives described in the RFC. Done means a decided design and implementation that removes the required call without breaking existing subclasses.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 30/100