[Hardware][Intel GPU] Add intel GPU pipeline parallel support. #7810
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@youkaichao Please take a review, thanks! |
| mp_method = envs.VLLM_WORKER_MULTIPROC_METHOD | ||
| if mp_method != "spawn": | ||
| raise RuntimeError( | ||
| "XPU multiprocess executor only support spawn as mp method") |
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it will throw such error if use fork
https://github.com/pytorch/pytorch/blob/main/torch/xpu/__init__.py#L114
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did you initialize the gpu somewhere? usually this needs to be avoided, and should already be avoided in vllm.
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"spawn" will not work when users run LLM class directly, without if __name__ == "__main__"
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when you import intel_extension_for_pytorch, it will call xpu initialization implicitly. and will fall into native runtime. I guess it will detect whether the process is started via fork or spawn.
What do you mean "spawn" will not work when users run LLM class directly here?
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oh, got your point. I just tried with offline_inference.py with spawn + mp backend, it will throw same error in this issue. While this works fine with api_server(using _AsyncLLMEngine).
I think ipex& xpu is following earlier CUDA implementation (CUDA also have similar issue long time ago, see pytorch/pytorch#40403) and I believe this(using fork as start method) can be fixed in the future.
So how about change to this way:
if user use LLMEngine on xpu, we will not support use mp as distributed backend.(spawn needs main function call, fork are not supported by torch xpu support yet)
if user use _AsyncLLMEngine, and use mp as backend, please use spawn as start method.
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updated, thanks!
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LGTM, thanks! |
…project#7810) Signed-off-by: Alvant <[email protected]>
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Add intel GPU pipeline parallel support.
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