[Feature, Hardware] Enable SGLang on XPU GPUs via PyTorch #1480
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liangan1
changed the title
zhyncs
reviewed
Sep 21, 2024
| @@ -22,8 +22,8 @@ dependencies = [ | |||
| [project.optional-dependencies] | |||
| srt = ["aiohttp", "decord", "fastapi", "hf_transfer", "huggingface_hub", "interegular", | |||
| "packaging", "pillow", "psutil", "pydantic", "python-multipart", | |||
| "torch", "torchao", "uvicorn", "uvloop", "zmq", | |||
| "vllm==0.5.5", "outlines>=0.0.44"] | |||
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Why was the vllm dependency removed?
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Pytorch already support XPU device since 2.4 release and xpu is also supported in OpenAI Trition. So, it should works with the Trition attention backend in SGLang. In this PR, We add 'xpu' device into SGLang.
Status
LLama-2-7b works for the latency benchmark.
VLLM_TEST_COMPILE_NO_CUSTOM_OPS=1 python -m sglang.bench_latency --model-path ~/.cache/huggingface/hub/models--meta-llama--Llama-2-7b-hf/snapshots/6fdf2e60f86ff2481f2241aaee459f85b5b0bbb9/ --device xpu
ToDO:
Functionality
Performance