39baaf55a1
* feat: add Dockerfiles for each platform that user ./server instead of ./main * feat: update .github/workflows/docker.yml to build server-first docker containers * doc: add information about running the server with Docker to README.md * doc: add information about running with docker to the server README * doc: update n-gpu-layers to show correct GPU usage * fix(doc): update container tag from `server` to `server-cuda` for README example on running server container with CUDA
46 lines
1,010 B
Docker
46 lines
1,010 B
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 ROCM_VERSION=5.6
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# Target the CUDA build image
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ARG BASE_ROCM_DEV_CONTAINER=rocm/dev-ubuntu-${UBUNTU_VERSION}:${ROCM_VERSION}-complete
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FROM ${BASE_ROCM_DEV_CONTAINER} as build
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# Unless otherwise specified, we make a fat build.
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# List from https://github.com/ggerganov/llama.cpp/pull/1087#issuecomment-1682807878
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# This is mostly tied to rocBLAS supported archs.
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ARG ROCM_DOCKER_ARCH=\
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gfx803 \
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gfx900 \
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gfx906 \
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gfx908 \
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gfx90a \
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gfx1010 \
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gfx1030 \
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gfx1100 \
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gfx1101 \
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gfx1102
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COPY requirements.txt requirements.txt
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COPY requirements requirements
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RUN pip install --upgrade pip setuptools wheel \
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&& pip install -r requirements.txt
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WORKDIR /app
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COPY . .
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# Set nvcc architecture
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ENV GPU_TARGETS=${ROCM_DOCKER_ARCH}
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# Enable ROCm
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ENV LLAMA_HIPBLAS=1
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ENV CC=/opt/rocm/llvm/bin/clang
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ENV CXX=/opt/rocm/llvm/bin/clang++
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RUN make
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ENTRYPOINT [ "/app/server" ]
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