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The prebuilt vllm 0.14.1+cpu wheel requires SIMD instructions (AVX-512 VNNI/BF16) that stock ubuntu-latest GitHub runners don't support — vllm.model_executor.models.registry SIGILLs on import during LoadModel. Source compilation works but takes 30-40 minutes per CI run, which is too slow for an e2e smoke test. Instead, switch tests-vllm-grpc to the bigger-runner self-hosted label (already used by backend.yml for the llama-cpp CUDA build) — that hardware has the required SIMD baseline and the prebuilt wheel runs cleanly. FROM_SOURCE=true is kept as an opt-in escape hatch: - install.sh still has the CPU source-build path for hosts that need it - backend/Dockerfile.python still declares the ARG + ENV - Makefile docker-build-backend still forwards the build-arg when set Default CI path uses the fast prebuilt wheel; source build can be re-enabled by exporting FROM_SOURCE=true in the environment.
69 lines
3.1 KiB
Bash
Executable File
69 lines
3.1 KiB
Bash
Executable File
#!/bin/bash
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set -e
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EXTRA_PIP_INSTALL_FLAGS="--no-build-isolation"
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# Avoid to overcommit the CPU during build
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# https://github.com/vllm-project/vllm/issues/20079
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# https://docs.vllm.ai/en/v0.8.3/serving/env_vars.html
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# https://docs.redhat.com/it/documentation/red_hat_ai_inference_server/3.0/html/vllm_server_arguments/environment_variables-server-arguments
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export NVCC_THREADS=2
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export MAX_JOBS=1
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backend_dir=$(dirname $0)
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if [ -d $backend_dir/common ]; then
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source $backend_dir/common/libbackend.sh
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else
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source $backend_dir/../common/libbackend.sh
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fi
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# This is here because the Intel pip index is broken and returns 200 status codes for every package name, it just doesn't return any package links.
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# This makes uv think that the package exists in the Intel pip index, and by default it stops looking at other pip indexes once it finds a match.
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# We need uv to continue falling through to the pypi default index to find optimum[openvino] in the pypi index
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# the --upgrade actually allows us to *downgrade* torch to the version provided in the Intel pip index
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if [ "x${BUILD_PROFILE}" == "xintel" ]; then
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EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
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fi
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# CPU builds need unsafe-best-match to pull torch==2.10.0+cpu from the
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# pytorch test channel while still resolving transformers/vllm from pypi.
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if [ "x${BUILD_PROFILE}" == "xcpu" ]; then
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EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
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fi
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# FROM_SOURCE=true on a CPU build skips the prebuilt vllm wheel in
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# requirements-cpu-after.txt and compiles vllm locally against the host's
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# actual CPU. Not used by default because it takes ~30-40 minutes, but
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# kept here for hosts where the prebuilt wheel SIGILLs (CPU without the
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# required SIMD baseline, e.g. AVX-512 VNNI/BF16). Default CI uses a
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# bigger-runner with compatible hardware instead.
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if [ "x${BUILD_TYPE}" == "x" ] && [ "x${FROM_SOURCE:-}" == "xtrue" ]; then
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# Temporarily hide the prebuilt wheel so installRequirements doesn't
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# pull it — the rest of the requirements files (base deps, torch,
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# transformers) are still installed normally.
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_cpu_after="${backend_dir}/requirements-cpu-after.txt"
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_cpu_after_bak=""
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if [ -f "${_cpu_after}" ]; then
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_cpu_after_bak="${_cpu_after}.from-source.bak"
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mv "${_cpu_after}" "${_cpu_after_bak}"
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fi
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installRequirements
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if [ -n "${_cpu_after_bak}" ]; then
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mv "${_cpu_after_bak}" "${_cpu_after}"
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fi
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# Build vllm from source against the installed torch.
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# https://docs.vllm.ai/en/latest/getting_started/installation/cpu/
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_vllm_src=$(mktemp -d)
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trap 'rm -rf "${_vllm_src}"' EXIT
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git clone --depth 1 https://github.com/vllm-project/vllm "${_vllm_src}/vllm"
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pushd "${_vllm_src}/vllm"
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uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} wheel packaging ninja "setuptools>=49.4.0" numpy typing-extensions pillow setuptools-scm
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# Respect pre-installed torch version — skip vllm's own requirements-build.txt torch pin.
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VLLM_TARGET_DEVICE=cpu uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps .
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popd
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else
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installRequirements
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fi
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