Dockerfile

ARG IMAGE_NAME
FROM ${IMAGE_NAME}:11.8.0-runtime-ubuntu20.04 as base

ENV NV_CUDA_LIB_VERSION "11.8.0-1"

FROM base as base-amd64

ENV NV_CUDA_CUDART_DEV_VERSION 11.8.89-1
ENV NV_NVML_DEV_VERSION 11.8.86-1
ENV NV_LIBCUSPARSE_DEV_VERSION 11.7.5.86-1
ENV NV_LIBNPP_DEV_VERSION 11.8.0.86-1
ENV NV_LIBNPP_DEV_PACKAGE libnpp-dev-11-8=${NV_LIBNPP_DEV_VERSION}

ENV NV_LIBCUBLAS_DEV_VERSION 11.11.3.6-1
ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME libcublas-dev-11-8
ENV NV_LIBCUBLAS_DEV_PACKAGE ${NV_LIBCUBLAS_DEV_PACKAGE_NAME}=${NV_LIBCUBLAS_DEV_VERSION}

ENV NV_NVPROF_VERSION 11.8.87-1
ENV NV_NVPROF_DEV_PACKAGE cuda-nvprof-11-8=${NV_NVPROF_VERSION}

ENV NV_LIBNCCL_DEV_PACKAGE_NAME libnccl-dev
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION 2.16.2-1
ENV NCCL_VERSION 2.16.2-1
ENV NV_LIBNCCL_DEV_PACKAGE ${NV_LIBNCCL_DEV_PACKAGE_NAME}=${NV_LIBNCCL_DEV_PACKAGE_VERSION}+cuda11.8
FROM base as base-arm64

ENV NV_CUDA_CUDART_DEV_VERSION 11.8.89-1
ENV NV_NVML_DEV_VERSION 11.8.86-1
ENV NV_LIBCUSPARSE_DEV_VERSION 11.7.5.86-1
ENV NV_LIBNPP_DEV_VERSION 11.8.0.86-1
ENV NV_LIBNPP_DEV_PACKAGE libnpp-dev-11-8=${NV_LIBNPP_DEV_VERSION}

ENV NV_LIBCUBLAS_DEV_PACKAGE_NAME libcublas-dev-11-8
ENV NV_LIBCUBLAS_DEV_VERSION 11.11.3.6-1
ENV NV_LIBCUBLAS_DEV_PACKAGE ${NV_LIBCUBLAS_DEV_PACKAGE_NAME}=${NV_LIBCUBLAS_DEV_VERSION}

ENV NV_LIBNCCL_DEV_PACKAGE_NAME libnccl-dev
ENV NV_LIBNCCL_DEV_PACKAGE_VERSION 2.16.2-1
ENV NCCL_VERSION 2.16.2-1
ENV NV_LIBNCCL_DEV_PACKAGE ${NV_LIBNCCL_DEV_PACKAGE_NAME}=${NV_LIBNCCL_DEV_PACKAGE_VERSION}+cuda11.8


FROM base-${TARGETARCH}

ARG TARGETARCH

LABEL maintainer "NVIDIA CORPORATION <cudatools@nvidia.com>"

RUN apt-get update && apt-get install -y --no-install-recommends \
    libtinfo5 libncursesw5 \
    cuda-cudart-dev-11-8=${NV_CUDA_CUDART_DEV_VERSION} \
    cuda-command-line-tools-11-8=${NV_CUDA_LIB_VERSION} \
    cuda-minimal-build-11-8=${NV_CUDA_LIB_VERSION} \
    cuda-libraries-dev-11-8=${NV_CUDA_LIB_VERSION} \
    cuda-nvml-dev-11-8=${NV_NVML_DEV_VERSION} \
    ${NV_NVPROF_DEV_PACKAGE} \
    ${NV_LIBNPP_DEV_PACKAGE} \
    libcusparse-dev-11-8=${NV_LIBCUSPARSE_DEV_VERSION} \
    ${NV_LIBCUBLAS_DEV_PACKAGE} \
    ${NV_LIBNCCL_DEV_PACKAGE} \
    && rm -rf /var/lib/apt/lists/*

# Keep apt from auto upgrading the cublas and nccl packages. See https://gitlab.com/nvidia/container-images/cuda/-/issues/88
RUN apt-mark hold ${NV_LIBCUBLAS_DEV_PACKAGE_NAME} ${NV_LIBNCCL_DEV_PACKAGE_NAME}
ENV LIBRARY_PATH /usr/local/cuda/lib64/stubs


WORKDIR /app

COPY ./requirements.txt /app/requirements.txt
COPY ./packages.txt /app/packages.txt
RUN pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
RUN apt-get update && xargs -r -a /app/packages.txt apt-get install -y && rm -rf /var/lib/apt/lists/*
RUN pip3 install --no-cache-dir -r /app/requirements.txt


# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user

# Switch to the "user" user
USER user

# Set home to the user's home directory
ENV HOME=/home/user \
	PATH=/home/user/.local/bin:$PATH

# Set the working directory to the user's home directory
WORKDIR $HOME/app

# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/app


EXPOSE 8501
CMD nvidia-smi -l
CMD streamlit run app.py --server.maxUploadSize 1024 --server.enableWebsocketCompression=false --server.enableXsrfProtection=false