mlcommons / mlcommons/inference
script aborts with 521 Killed
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- Dominant language
- Python
- Stars
- 1.6k
- Forks
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- Avg merge
- 1d 22h
- Merged PRs (30d)
- 6
Description
running:
cm run script --tags=run-mlperf,inference,_find-performance,_full,_r4.1 --model=llama2-70b-99 --implementation=reference --framework=pytorch --category=datacenter --scenario=Offline --execution_mode=test --device=cpu --docker --quiet --test_query_count=50
results in several hours of silence after which this error is produced
git clone --recurse-submodules https://huggingface.co/meta-llama/Llama-2-70b-chat-hf --depth 5 repo
Cloning into 'repo'...
Username for 'https://huggingface.co': howudodat
Password for 'https://howudodat@huggingface.co':
remote: Enumerating objects: 58, done.
remote: Counting objects: 100% (58/58), done.
remote: Compressing objects: 100% (56/56), done.
remote: Total 58 (delta 9), reused 42 (delta 2), pack-reused 0 (from 0)
Unpacking objects: 100% (58/58), 511.53 KiB | 5.12 MiB/s, done.
Username for 'https://huggingface.co': howudodat
Password for 'https://howudodat@huggingface.co':
/home/cmuser/CM/repos/mlcommons@cm4mlops/script/get-git-repo/run.sh: line 51: 521 Killed ${CM_GIT_CLONE_CMD}
CM error: Portable CM script failed (name = get-git-repo, return code = 256)
Any ideas?
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 /home/cmuser/CM/repos/mlcommons@cm4mlops/script/get-git-repo/run.sh around line 51, then rerun the reported cm command and inspect the clone output and exit status. Done means the Llama-2 repository clone completes without the process being killed and the CM script no longer returns error 256.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- docker, git, huggingface, python, pytorch
- Domain
- machine-learning, tooling
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100