ARG CUDA_VERSION_ARG
FROM nvidia/cuda:$CUDA_VERSION_ARG-devel-ubuntu18.04
ARG CUDA_VERSION_ARG

# Environment
ENV DEBIAN_FRONTEND noninteractive
SHELL ["/bin/bash", "-c"]   # Use Bash as shell

# Install all basic requirements
RUN \
    apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub && \
    apt-get update && \
    apt-get install -y wget unzip bzip2 libgomp1 build-essential ninja-build git && \
    # Python
    wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
    bash Miniconda3.sh -b -p /opt/python

# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
RUN \
    export CUDA_SHORT=`echo $CUDA_VERSION_ARG | grep -o -E '[0-9]+\.[0-9]'` && \
    export NCCL_VERSION=2.13.4-1 && \
    apt-get update && \
    apt-get install -y --allow-downgrades --allow-change-held-packages libnccl2=${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-dev=${NCCL_VERSION}+cuda${CUDA_SHORT}

ENV PATH=/opt/python/bin:$PATH

# Create new Conda environment with RMM
RUN \
    conda create -n gpu_test -c rapidsai-nightly -c rapidsai -c nvidia -c conda-forge -c defaults \
        python=3.9 rmm=22.04* cudatoolkit=$CUDA_VERSION_ARG cmake

ENV GOSU_VERSION 1.10

# Install lightweight sudo (not bound to TTY)
RUN set -ex; \
    wget -O /usr/local/bin/gosu "https://github.com/tianon/gosu/releases/download/$GOSU_VERSION/gosu-amd64" && \
    chmod +x /usr/local/bin/gosu && \
    gosu nobody true

# Default entry-point to use if running locally
# It will preserve attributes of created files
COPY entrypoint.sh /scripts/

WORKDIR /workspace
ENTRYPOINT ["/scripts/entrypoint.sh"]