modelscope / modelscope/DiffSynth-Studio
nproc_per_node issue
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Description
torchrun --standalone --nproc_per_node=1 examples/wanvideo/acceleration/unified_sequence_parallel.py
why is much slower than normally run 'python unified_sequence_parallel.py'
which leads '--nproc_per_node=2 examples/wanvideo/acceleration/unified_sequence_parallel.py' gain small speedup than normally run 'python unified_sequence_parallel.py'.
Contributor guide
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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 reproducing the two commands against examples/wanvideo/acceleration/unified_sequence_parallel.py and compare their timings with nproc_per_node set to 1 and 2. Read that entry point and the torchrun-related setup it uses; done means the performance difference is explained and any required change is verified with comparable runs.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- distributed-systems, machine-learning, performance
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100