vllm-dp-support #3303
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vllm-dp-support #3303
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
qgallouedec
reviewed
Apr 16, 2025
Comment on lines
+438
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| for dp_rank, batch in enumerate(prompt_batches): | ||
| if batch: # Skip empty batches | ||
| llm_instance = llm_instances[dp_rank] | ||
| batch_outputs = llm_instance.generate(batch, sampling_params=sampling_params) | ||
| all_outputs.extend(batch_outputs) |
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What does this PR do?
In this PR we create multiple LLM instances (one per DP rank) and distribute the prompts among them.
From data_parallel.py, we can see how to set the environment variables for DP communication and how to split the prompts among DP ranks.
So we do;
generateto distribute prompts across DP ranks and collect resultsBefore submitting
Pull Request section?
to it if that's the case.
Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.