[BUG] Confusing machine names in Jenkins CI
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Description
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My PR for a new tutorial: https://github.com/pytorch/tutorials/pull/3763/
Describe the bug
THe Jenkins CI has a few hard-coded behaviors that are confusing. The linux.16xlarge.nvidia.gpu label in Jenkins appears to be a legacy label that means "needs multi-GPU". It doesn't describe the actual hardware that is used.
get_files_to_run.py has a hard-coded check for this exact key, which routes it to shard 0. Shard 0 maps to WORKER_ID=1 in the matrix (also confusing), and then shard 1's runner is a linux.g5.12xlarge.nvidia.gpu, not a 16xl.
Reporting this since it resulted in some confusion while getting my CI for my PR to pass. If it were me, the key should be '4-gpu' instead of linux.16xlarge.nvidia.gpu.
Describe your environment
PyTorch tutorial CI
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 with .jenkins/metadata.json at line 27 and .jenkins/get_files_to_run.py at lines 43-45, then inspect the CI matrix mapping described in the issue. Verify the label and shard/WORKER_ID relationship, including the linux.g5.12xlarge.nvidia.gpu runner. Done means the machine naming and routing consistently describe the multi-GPU CI behavior without breaking tutorial CI.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ci-cd, devops
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 45/100