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docker : update CUDA images (#9213)

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slaren
2024-08-28 13:20:36 +02:00
committed by GitHub
parent 20f1789dfb
commit 66b039a501
4 changed files with 42 additions and 42 deletions
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25
.devops/full-cuda.Dockerfile
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@@ -1,18 +1,16 @@
ARG UBUNTU_VERSION=22.04 ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment. # This needs to generally match the container host's environment.
ARG CUDA_VERSION=11.7.1 ARG CUDA_VERSION=12.6.0
# Target the CUDA build image # Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION} ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
FROM ${BASE_CUDA_DEV_CONTAINER} AS build FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build. # CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=all ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y build-essential python3 python3-pip git libcurl4-openssl-dev libgomp1 apt-get install -y build-essential cmake python3 python3-pip git libcurl4-openssl-dev libgomp1
COPY requirements.txt requirements.txt COPY requirements.txt requirements.txt
COPY requirements requirements COPY requirements requirements
@@ -24,13 +22,12 @@ WORKDIR /app
COPY . . COPY . .
# Set nvcc architecture # Use the default CUDA archs if not specified
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
# Enable CUDA export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
ENV GGML_CUDA=1 fi && \
# Enable cURL cmake -B build -DGGML_CUDA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
ENV LLAMA_CURL=1 cmake --build build --config Release --target llama-cli -j$(nproc) && \
cp build/bin/* .
RUN make -j$(nproc)
ENTRYPOINT ["/app/.devops/tools.sh"] ENTRYPOINT ["/app/.devops/tools.sh"]

24
.devops/llama-cli-cuda.Dockerfile
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@@ -1,6 +1,6 @@
ARG UBUNTU_VERSION=22.04 ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment. # This needs to generally match the container host's environment.
ARG CUDA_VERSION=11.7.1 ARG CUDA_VERSION=12.6.0
# Target the CUDA build image # Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION} ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image # Target the CUDA runtime image
@@ -8,28 +8,30 @@ ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_V
FROM ${BASE_CUDA_DEV_CONTAINER} AS build FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build. # CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=all ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y build-essential git apt-get install -y build-essential git cmake
WORKDIR /app WORKDIR /app
COPY . . COPY . .
# Set nvcc architecture # Use the default CUDA archs if not specified
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
# Enable CUDA export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
ENV GGML_CUDA=1 fi && \
cmake -B build -DGGML_CUDA=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
RUN make -j$(nproc) llama-cli cmake --build build --config Release --target llama-cli -j$(nproc)
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y libgomp1 apt-get install -y libgomp1
COPY --from=build /app/llama-cli /llama-cli COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
COPY --from=build /app/build/src/libllama.so /libllama.so
COPY --from=build /app/build/bin/llama-cli /llama-cli
ENTRYPOINT [ "/llama-cli" ] ENTRYPOINT [ "/llama-cli" ]

31
.devops/llama-server-cuda.Dockerfile
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@@ -1,6 +1,6 @@
ARG UBUNTU_VERSION=22.04 ARG UBUNTU_VERSION=22.04
# This needs to generally match the container host's environment. # This needs to generally match the container host's environment.
ARG CUDA_VERSION=11.7.1 ARG CUDA_VERSION=12.6.0
# Target the CUDA build image # Target the CUDA build image
ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION} ARG BASE_CUDA_DEV_CONTAINER=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu${UBUNTU_VERSION}
# Target the CUDA runtime image # Target the CUDA runtime image
@@ -8,33 +8,34 @@ ARG BASE_CUDA_RUN_CONTAINER=nvidia/cuda:${CUDA_VERSION}-runtime-ubuntu${UBUNTU_V
FROM ${BASE_CUDA_DEV_CONTAINER} AS build FROM ${BASE_CUDA_DEV_CONTAINER} AS build
# Unless otherwise specified, we make a fat build. # CUDA architecture to build for (defaults to all supported archs)
ARG CUDA_DOCKER_ARCH=all ARG CUDA_DOCKER_ARCH=default
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y build-essential git libcurl4-openssl-dev apt-get install -y build-essential git cmake libcurl4-openssl-dev
WORKDIR /app WORKDIR /app
COPY . . COPY . .
# Set nvcc architecture # Use the default CUDA archs if not specified
ENV CUDA_DOCKER_ARCH=${CUDA_DOCKER_ARCH} RUN if [ "${CUDA_DOCKER_ARCH}" != "default" ]; then \
# Enable CUDA export CMAKE_ARGS="-DCMAKE_CUDA_ARCHITECTURES=${CUDA_DOCKER_ARCH}"; \
ENV GGML_CUDA=1 fi && \
# Enable cURL cmake -B build -DGGML_CUDA=ON -DLLAMA_CURL=ON ${CMAKE_ARGS} -DCMAKE_EXE_LINKER_FLAGS=-Wl,--allow-shlib-undefined . && \
ENV LLAMA_CURL=1 cmake --build build --config Release --target llama-server -j$(nproc)
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
RUN make -j$(nproc) llama-server
FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime FROM ${BASE_CUDA_RUN_CONTAINER} AS runtime
RUN apt-get update && \ RUN apt-get update && \
apt-get install -y libcurl4-openssl-dev libgomp1 curl apt-get install -y libcurl4-openssl-dev libgomp1 curl
COPY --from=build /app/llama-server /llama-server COPY --from=build /app/build/ggml/src/libggml.so /libggml.so
COPY --from=build /app/build/src/libllama.so /libllama.so
COPY --from=build /app/build/bin/llama-server /llama-server
# Must be set to 0.0.0.0 so it can listen to requests from host machine
ENV LLAMA_ARG_HOST=0.0.0.0
HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ] HEALTHCHECK CMD [ "curl", "-f", "http://localhost:8080/health" ]

4
docs/docker.md
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@@ -66,8 +66,8 @@ You may want to pass in some different `ARGS`, depending on the CUDA environment
The defaults are: The defaults are:
- `CUDA_VERSION` set to `11.7.1` - `CUDA_VERSION` set to `12.6.0`
- `CUDA_DOCKER_ARCH` set to `all` - `CUDA_DOCKER_ARCH` set to the cmake build default, which includes all the supported architectures
The resulting images, are essentially the same as the non-CUDA images: The resulting images, are essentially the same as the non-CUDA images: