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Description
ive been struggling some with a Cuda dockerfile sinze the devel image was so large the build ended up at almost 8gb, i came up with this. just wanted to share it:
FROM nvidia/cuda:12.1.1-devel-ubuntu22.04 AS builder
RUN apt-get update && apt-get upgrade -y \
&& apt-get install -y git build-essential \
python3 python3-pip gcc wget \
ocl-icd-opencl-dev opencl-headers clinfo \
libclblast-dev libopenblas-dev \
&& mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd
# setting build related env vars
ENV CUDA_DOCKER_ARCH=all
ENV LLAMA_CUBLAS=1
# Install depencencies
RUN python3 -m pip install --user --upgrade pip pytest cmake scikit-build setuptools fastapi uvicorn sse-starlette pydantic-settings starlette-context
# Install llama-cpp-python (build with cuda)
RUN CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install --user llama-cpp-python
FROM nvidia/cuda:12.1.1-runtime-ubuntu22.04
RUN apt-get update && apt-get upgrade -y \
&& apt-get install -y git build-essential \
python3 python3-pip gcc wget \
ocl-icd-opencl-dev opencl-headers clinfo \
libclblast-dev libopenblas-dev \
&& mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd
# Copy libraries from build local path
COPY --from=builder /root/.local /root/.local
COPY --from=builder /tmp/*.txt /tmp/
ENV PATH=/root/.local:$PATH
the final image ended up att aroung 2gb and GPU support is working as expected..