Lightning-AI / Lightning-AI/pytorch-lightning
Dynamic/variable batch size support
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- Dominant language
- Python
- Stars
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- Forks
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- Avg merge
- 6d 7h
- Merged PRs (30d)
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Description
### Description & Motivation
Support like:
GPU1: batch-size=24
GPU2: batch-size=12
GPU3: batch-size=16
GPU4: batch-size=24
---
As different batch has different length
See
https://github.com/microsoft/DeepSpeed/issues/1051
https://github.com/facebookresearch/fairseq/blob/b5a039c292facba9c73f59ff34621ec131d82341/fairseq/data/data_utils.py#L282
### Pitch
_No response_
### Alternatives
_No response_
### Additional context
_No response_
cc @borda
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 reading the linked DeepSpeed issue and the referenced fairseq data_utils.py section, then trace how batch sizes are configured across GPUs in this repository. Done means the project supports the requested per-GPU batch-size variation, with the relevant behavior and tests identified during implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- distributed-systems, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100