wehub-resource-sync
90 lines
3.1 KiB
Bash
Executable File
90 lines
3.1 KiB
Bash
Executable File
#!/bin/bash
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set -e
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PYTHON_VERSION="3.12"
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PYTHON_PATCH="12"
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PY_STANDALONE_TAG="20251120"
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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 $backend_dir/../common/libbackend.sh
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fi
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# Handle l4t build profiles (Python 3.12, pip fallback) if needed.
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# Since PyTorch 2.11 (April 2026) PyPI ships aarch64 + cu130 manylinux wheels
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# directly for torch/torchvision/torchaudio and an aarch64 vllm wheel pinned
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# to that torch, so the jetson-ai-lab mirror is no longer needed.
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# https://pytorch.org/blog/vllm-and-pytorch-work-together-to-improve-the-developer-experience-on-aarch64/
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if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
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PYTHON_VERSION="3.12"
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PYTHON_PATCH="12"
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PY_STANDALONE_TAG="20251120"
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fi
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if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
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USE_PIP=true
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fi
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# Install base requirements first
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installRequirements
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# Install vllm based on build type. vllm-omni tracks vllm master from
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# source (cloned below) so we leave the upstream vllm dependency unpinned
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# — vllm 0.19+ ships cu130 wheels by default, which is what we want for
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# cublas13. Older cuda12/rocm/cpu paths still resolve a compatible wheel
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# from the relevant channel.
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if [ "x${BUILD_TYPE}" == "xhipblas" ]; then
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# ROCm
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if [ "x${USE_PIP}" == "xtrue" ]; then
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pip install vllm==0.14.0 --extra-index-url https://wheels.vllm.ai/rocm/0.14.0/rocm700
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else
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uv pip install vllm==0.14.0 --extra-index-url https://wheels.vllm.ai/rocm/0.14.0/rocm700
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fi
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elif [ "x${BUILD_PROFILE}" == "xcublas13" ] || [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
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# cublas13 (x86_64) and l4t13 (aarch64) both pull vllm from PyPI now:
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# vllm 0.19+ defaults to cu130 wheels on x86_64 and vllm 0.20+ ships an
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# aarch64 manylinux wheel pinned to torch==2.11.0. No extra index needed
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# in either case.
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if [ "x${USE_PIP}" == "xtrue" ]; then
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pip install vllm --torch-backend=auto
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else
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uv pip install vllm --torch-backend=auto
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fi
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elif [ "x${BUILD_TYPE}" == "xcublas" ] || [ "x${BUILD_TYPE}" == "x" ]; then
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# cuda12 / CPU — keep the 0.14.0 pin for compatibility with the existing
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# cuda12 vllm-omni image; bumping should be its own change.
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if [ "x${USE_PIP}" == "xtrue" ]; then
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pip install vllm==0.14.0 --torch-backend=auto
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else
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uv pip install vllm==0.14.0 --torch-backend=auto
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fi
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else
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echo "Unsupported build type: ${BUILD_TYPE}" >&2
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exit 1
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fi
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# Clone and install vllm-omni from source
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if [ ! -d vllm-omni ]; then
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git clone https://github.com/vllm-project/vllm-omni.git
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fi
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cd vllm-omni/
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# fa3-fwd ships no aarch64 wheels and there is no source distribution, so on
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# aarch64 (e.g. l4t13 / SBSA cu130) the upstream requirements/cuda.txt is
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# unsatisfiable. Drop it before resolving — vllm-omni does not hard-require
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# the fused FA3 kernel at import time on Jetson/SBSA targets.
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if [ "$(uname -m)" = "aarch64" ] && [ -f requirements/cuda.txt ]; then
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sed -i '/^fa3-fwd[[:space:]]*==/d' requirements/cuda.txt
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fi
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if [ "x${USE_PIP}" == "xtrue" ]; then
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pip install ${EXTRA_PIP_INSTALL_FLAGS:-} -e .
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else
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uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} -e .
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fi
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cd ..
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