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sglang_v0.5.2
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hailin 2025-09-19 12:16:08 +08:00
parent 25dd4c4f52
commit 1325489a99
1 changed files with 27 additions and 6 deletions
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@ -49,8 +49,9 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
cmake ninja-build libjpeg-dev libpng-dev ca-certificates \ cmake ninja-build libjpeg-dev libpng-dev ca-certificates \
libopenmpi-dev libopenblas-dev\ libopenmpi-dev libopenblas-dev\
libnccl2=2.22.3-1+cuda12.6 \ libnccl2=2.22.3-1+cuda12.6 \
libnccl-dev=2.22.3-1+cuda12.6 && \ libnccl-dev=2.22.3-1+cuda12.6 \
python3 -m pip install --no-cache-dir --upgrade pip wheel setuptools curl xz-utils \
&& python3 -m pip install --no-cache-dir --upgrade pip wheel setuptools
# ── 安装自编 torch 轮子 ────────────────────────────────────────────────────── # ── 安装自编 torch 轮子 ──────────────────────────────────────────────────────
COPY --from=builder-torch /opt/pytorch/dist /tmp/torch_dist COPY --from=builder-torch /opt/pytorch/dist /tmp/torch_dist
@ -97,18 +98,38 @@ RUN python3 -m pip install ".[srt,openai]" --no-build-isolation && \
# # ── 🔄 下载 sgl-kernel（与 sglang 同步）─────────────────────────────────────── # # ── 🔄 下载 sgl-kernel（与 sglang 同步）───────────────────────────────────────
# RUN pip download --only-binary=:all: --no-deps sgl-kernel==0.3.9.post2 -d /tmp/sgl_kernel_wheels # RUN pip download --only-binary=:all: --no-deps sgl-kernel==0.3.9.post2 -d /tmp/sgl_kernel_wheels
ENV PATH=/usr/local/cuda/bin:${PATH}
# ── 用你本地源码编 sgl-kernel==0.3.9.post2（与自编 torch 完全 ABI 对齐） ────── # ── 用你本地源码编 sgl-kernel==0.3.9.post2（与自编 torch 完全 ABI 对齐） ──────
WORKDIR /sgl/sglang/sgl-kernel WORKDIR /sgl/sglang/sgl-kernel
# 覆盖安装 ptxas 12.8（保留 nvcc 12.6），并打印版本确认
RUN bash -lc '\
set -euo pipefail; \
NVCC_ARCHIVE_VERSION=12.8.93; \
T=cuda_nvcc-linux-x86_64-${NVCC_ARCHIVE_VERSION}-archive; \
curl -fsSLO https://developer.download.nvidia.com/compute/cuda/redist/cuda_nvcc/linux-x86_64/${T}.tar.xz && \
tar -xf ${T}.tar.xz && \
install -m 0755 ${T}/bin/ptxas /usr/local/cuda/bin/ptxas && \
/usr/local/cuda/bin/ptxas --version \
'
# 限制构建并行；避免 ptxas 多线程崩溃
ENV CMAKE_BUILD_PARALLEL_LEVEL=8
ENV SGL_KERNEL_COMPILE_THREADS=1
# 构建 sgl-kernel（保持 FA3；去掉无效的关 90a 标志）
RUN python3 -m pip install --no-cache-dir "cmake>=3.27,<4.0" scikit-build-core==0.11.6 pybind11[global] packaging && \ RUN python3 -m pip install --no-cache-dir "cmake>=3.27,<4.0" scikit-build-core==0.11.6 pybind11[global] packaging && \
bash -lc '\ bash -lc '\
export CMAKE_PREFIX_PATH="$(python3 -c "import torch; print(torch.utils.cmake_prefix_path)")" && \ export CMAKE_PREFIX_PATH="$(python3 -c "import torch; print(torch.utils.cmake_prefix_path)")" && \
# 这些卡就够了：A100(80), 3090(86), 4090(89)。别碰 90a。
export TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9" && \ export TORCH_CUDA_ARCH_LIST="8.0;8.6;8.9" && \
export CUDAARCHS="80;86;89" && \ export CUDAARCHS="80;86;89" && \
export CMAKE_CUDA_ARCHITECTURES="$CUDAARCHS" && \ export CMAKE_CUDA_ARCHITECTURES="$CUDAARCHS" && \
# 同时把它塞进 CMAKE_ARGS；不认识的开关会被忽略，不会报错 # 这里保留常规参数；如果项目支持，也把内核编译线程设为 1（未知项将被忽略，不会报错）
export CMAKE_ARGS="-DCMAKE_POLICY_VERSION_MINIMUM=3.5 -DCMAKE_CUDA_ARCHITECTURES=$CUDAARCHS -DFA3_WITH_SM90A=OFF -DSGLK_DISABLE_SM90A=ON" && \ export CMAKE_ARGS="-DCMAKE_POLICY_VERSION_MINIMUM=3.5 -DCMAKE_CUDA_ARCHITECTURES=$CUDAARCHS -Ccmake.define.SGL_KERNEL_COMPILE_THREADS=1" && \
python3 -m pip wheel . --no-deps --no-build-isolation -w /tmp/sgl_kernel_wheels' python3 -m pip wheel . --no-deps --no-build-isolation -w /tmp/sgl_kernel_wheels \
'
# ── 收集所有 wheel 到 /wheels ────────────────────────────────────────────── # ── 收集所有 wheel 到 /wheels ──────────────────────────────────────────────