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https://github.com/ggerganov/llama.cpp.git
synced 2024-11-11 13:30:35 +00:00
docker : update CUDA images (#9213)
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20f1789dfb
commit
66b039a501
@ -1,18 +1,16 @@
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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=11.7.1
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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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FROM ${BASE_CUDA_DEV_CONTAINER} AS build
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# Unless otherwise specified, we make a fat build.
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ARG CUDA_DOCKER_ARCH=all
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# CUDA architecture to build for (defaults to all supported archs)
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ARG CUDA_DOCKER_ARCH=default
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RUN apt-get update && \
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apt-get install -y build-essential python3 python3-pip git libcurl4-openssl-dev libgomp1
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apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
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COPY requirements.txt requirements.txt
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COPY requirements requirements
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@ -24,13 +22,12 @@ WORKDIR /app
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COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV GGML_CUDA=1
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# Enable cURL
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ENV LLAMA_CURL=1
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RUN make -j$(nproc)
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# Use the default CUDA archs if not specified
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RUN if [ "${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 -DLLAMA_CURL=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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cp build/bin/* .
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ENTRYPOINT ["/app/.devops/tools.sh"]
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@ -1,6 +1,6 @@
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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=11.7.1
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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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@ -8,28 +8,30 @@ ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_V
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FROM ${BASE_CUDA_DEV_CONTAINER} AS build
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# Unless otherwise specified, we make a fat build.
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ARG CUDA_DOCKER_ARCH=all
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# CUDA architecture to build for (defaults to all supported archs)
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ARG CUDA_DOCKER_ARCH=default
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RUN apt-get update && \
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apt-get install -y build-essential git
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apt-get install -y build-essential git cmake
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WORKDIR /app
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COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV GGML_CUDA=1
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RUN make -j$(nproc) llama-cli
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# Use the default CUDA archs if not specified
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RUN if [ "${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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FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
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RUN apt-get update && \
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apt-get install -y libgomp1
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COPY --from=build /app/llama-cli /llama-cli
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COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
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COPY --from=build /app/build/src/libllama.so /libllama.so
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COPY --from=build /app/build/bin/llama-cli /llama-cli
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ENTRYPOINT [ "/llama-cli" ]
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@ -1,6 +1,6 @@
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ARG UBUNTU_VERSION=22.04
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# This needs to generally match the container host's environment.
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ARG CUDA_VERSION=11.7.1
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ARG CUDA_VERSION=12.6.0
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# Target the CUDA build image
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ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
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# Target the CUDA runtime image
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@ -8,33 +8,34 @@ ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_V
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FROM ${BASE_CUDA_DEV_CONTAINER} AS build
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# Unless otherwise specified, we make a fat build.
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ARG CUDA_DOCKER_ARCH=all
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# CUDA architecture to build for (defaults to all supported archs)
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ARG CUDA_DOCKER_ARCH=default
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RUN apt-get update && \
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apt-get install -y build-essential git libcurl4-openssl-dev
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apt-get install -y build-essential git cmake libcurl4-openssl-dev
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WORKDIR /app
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COPY . .
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# Set nvcc architecture
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ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH}
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# Enable CUDA
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ENV GGML_CUDA=1
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# Enable cURL
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ENV LLAMA_CURL=1
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# Must be set to 0.0.0.0 so it can listen to requests from host machine
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ENV LLAMA_ARG_HOST=0.0.0.0
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RUN make -j$(nproc) llama-server
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# Use the default CUDA archs if not specified
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RUN if [ "${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 -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
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cmake --build build --config Release --target llama-server -j$(nproc)
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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 libcurl4-openssl-dev libgomp1 curl
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COPY --from=build /app/llama-server /llama-server
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COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
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COPY --from=build /app/build/src/libllama.so /libllama.so
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COPY --from=build /app/build/bin/llama-server /llama-server
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# Must be set to 0.0.0.0 so it can listen to requests from host machine
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ENV LLAMA_ARG_HOST=0.0.0.0
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HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]
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@ -66,8 +66,8 @@ You may want to pass in some different `ARGS`, depending on the CUDA environment
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The defaults are:
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- `CUDA_VERSION` set to `11.7.1`
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- `CUDA_DOCKER_ARCH` set to `all`
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- `CUDA_VERSION` set to `12.6.0`
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- `CUDA_DOCKER_ARCH` set to the cmake build default, which includes all the supported architectures
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The resulting images, are essentially the same as the non-CUDA images:
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