NVIDIA / NVIDIA/apex

About bugs in SyncBn

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Dominant language
Python
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Forks
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Avg merge
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Merged PRs (30d)
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Description

Hello, I think there are bugs in SyncBn when the input size between GPUs is different. The same issue in pytorch1.1 is here issue#22192. And someone fix it here. So I think the SyncBn in apex should also fix the bug. Could someone try it?

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the SyncBn implementation in Apex and compare its behavior with PyTorch issue #22192 and commit 29ec4769bbcf545e8727184b413f3b4b6a002b44. Reproduce the failure with different input sizes across GPUs, then verify that SyncBn handles those inputs correctly.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
distributed-systems, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
30/100

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