mirror of
https://github.com/kvcache-ai/ktransformers.git
synced 2026-10-25 11:26:07 +08:00
Peilin LiandZiWei Yuan
171578a7ec
* Change named 'KT-SFT' to 'kt-sft' * [docs]: update kt-sft name --------- Co-authored-by: ZiWei Yuan <yzwliam@126.com>
64 lines
1.4 KiB
Docker
64 lines
1.4 KiB
Docker
FROM pytorch/pytorch:2.5.1-cuda12.1-cudnn9-devel as compile_server
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ARG CPU_INSTRUCT=NATIVE
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# 设置工作目录和 CUDA 路径
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WORKDIR /workspace
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ENV CUDA_HOME=/usr/local/cuda
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# 安装依赖
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RUN apt update -y
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RUN apt install -y --no-install-recommends \
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libtbb-dev \
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libssl-dev \
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libcurl4-openssl-dev \
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libaio1 \
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libaio-dev \
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libfmt-dev \
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libgflags-dev \
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zlib1g-dev \
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patchelf \
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git \
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wget \
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vim \
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gcc \
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g++ \
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cmake
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# 拷贝代码
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RUN git clone https://github.com/kvcache-ai/ktransformers.git
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# 清理 apt 缓存
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RUN rm -rf /var/lib/apt/lists/*
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# 进入项目目录
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WORKDIR /workspace/ktransformers
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# 初始化子模块
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RUN git submodule update --init --recursive
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# 升级 pip
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RUN pip install --upgrade pip
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# 安装构建依赖
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RUN pip install ninja pyproject numpy cpufeature aiohttp zmq openai
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# 安装 flash-attn（提前装可以避免后续某些编译依赖出错）
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RUN pip install flash-attn
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# 安装 ktransformers 本体（含编译）
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RUN CPU_INSTRUCT=${CPU_INSTRUCT} \
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USE_BALANCE_SERVE=1 \
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KTRANSFORMERS_FORCE_BUILD=TRUE \
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TORCH_CUDA_ARCH_LIST="8.0;8.6;8.7;8.9;9.0+PTX" \
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pip install . --no-build-isolation --verbose
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RUN pip install third_party/custom_flashinfer/
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# 清理 pip 缓存
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RUN pip cache purge
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# 拷贝 C++ 运行时库
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RUN cp /usr/lib/x86_64-linux-gnu/libstdc++.so.6 /opt/conda/lib/
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# 保持容器运行（调试用）
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ENTRYPOINT ["tail", "-f", "/dev/null"] |