meta-pytorch / meta-pytorch/data
Ability to track buffer statistics for `.fork` `.shuffle` `.demux` and similar pipes
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- Dominant language
- Python
- Stars
- 1.3k
- Forks
- 179
- Avg merge
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- Merged PRs (30d)
- 2
Description
🚀 The feature
Ability to get statistics like maximum used size, elements passed etc.
Motivation, pitch
Lots of unoptimized datasets had to use infinite buffer of some kind and it is important to know how bad situation is.
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 locating the implementations and tests for the .fork, .shuffle, and .demux pipes. Determine how buffer usage and elements passed can be observed, then define and verify statistics such as maximum buffer size and total elements passed for finite and infinite-buffer cases.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100