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[CI/Build] add EP dependencies to docker (#21976)
Co-authored-by: Simon Mo <simon.mo@hey.com>
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@ -843,3 +843,10 @@ steps:
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commands:
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- export VLLM_WORKER_MULTIPROC_METHOD=spawn
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- pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large.txt --tp-size=4
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- label: Qwen MoE EP Test # optional
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gpu: h200
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optional: true
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num_gpus: 2
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commands:
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- CUDA_VISIBLE_DEVICES=1,2 VLLM_ALL2ALL_BACKEND=deepep_high_throughput VLLM_USE_DEEP_GEMM=1 VLLM_LOGGING_LEVEL=DEBUG python3 /vllm-workspace/examples/offline_inference/data_parallel.py --model Qwen/Qwen1.5-MoE-A2.7B --tp-size=1 --dp-size=2 --max-model-len 2048
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@ -458,6 +458,14 @@ RUN --mount=type=cache,target=/root/.cache/uv bash - <<'BASH'
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fi
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BASH
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# Install EP kernels(pplx-kernels and DeepEP), NixL
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COPY tools/ep_kernels/install_python_libraries.sh install_python_libraries.sh
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COPY tools/install_nixl.sh install_nixl.sh
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ENV CUDA_HOME=/usr/local/cuda
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RUN export TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST:-9.0a+PTX}" \
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&& bash install_python_libraries.sh \
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&& bash install_nixl.sh --force
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#################### vLLM installation IMAGE ####################
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#################### TEST IMAGE ####################
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