mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-27 06:39:25 +01:00
ae8de6d50a
* ggml : build backends as libraries --------- Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com> Co-authored-by: Georgi Gerganov <ggerganov@gmail.com> Co-authored-by: R0CKSTAR <xiaodong.ye@mthreads.com>
39 lines
1.2 KiB
Docker
39 lines
1.2 KiB
Docker
ARG UBUNTU_VERSION=22.04
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# This needs to generally match the container host's environment.
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ARG CUDA_VERSION=12.6.0
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# Target the CUDA build image
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ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
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# Target the CUDA runtime image
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ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_VERSION}
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FROM ${BASE_CUDA_DEV_CONTAINER} AS build
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# CUDA architecture to build for (defaults to all supported archs)
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ARG CUDA_DOCKER_ARCH=default
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RUN apt-get update && \
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apt-get install -y build-essential git cmake
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WORKDIR /app
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COPY . .
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# Use the default CUDA archs if not specified
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RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
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export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
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fi && \
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cmake -B build -DGGML_CUDA=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
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cmake --build build --config Release --target llama-cli -j$(nproc) && \
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mkdir -p /app/lib && \
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find build -name "*.so" -exec cp {} /app/lib \;
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FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
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RUN apt-get update && \
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apt-get install -y libgomp1
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COPY --from=build /app/lib/ /
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COPY --from=build /app/build/bin/llama-cli /
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ENTRYPOINT [ "/llama-cli" ]
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