meta-pytorch / meta-pytorch/data
[feature request] Upstream to core PyTorch `StatefulDataLoader` and `StatefulDistributedSampler`
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- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 179
- Avg merge
- 6d 1h
- Merged PRs (30d)
- 2
Description
🚀 The feature
Being able to precisely recover the state of data loading is a popular feature. Would be great to have it in core to increase visibility of its existence :)
Motivation, pitch
N/A
Alternatives
No response
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
Start by reviewing the existing StatefulDataLoader and StatefulDistributedSampler implementations and how they relate to core PyTorch data loading. Clarify the upstreaming scope and acceptance criteria with maintainers; done would mean an agreed, integrated implementation in core PyTorch.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100