# Container to test XGBoost against dev versions of dependencies ARG CUDA_VERSION_ARG FROM nvidia/cuda:$CUDA_VERSION_ARG-runtime-ubuntu22.04 ARG CUDA_VERSION_ARG ARG RAPIDS_VERSION_ARG # Should be first 4 digits of the dev version (e.g. 24.06) ARG NCCL_VERSION_ARG # Environment ENV DEBIAN_FRONTEND noninteractive SHELL ["/bin/bash", "-c"] # Use Bash as shell # Install all basic requirements RUN \ apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub && \ apt-get update && \ apt-get install -y wget unzip bzip2 libgomp1 build-essential openjdk-8-jdk-headless && \ # Python wget -nv -O conda.sh https://github.com/conda-forge/miniforge/releases/download/24.3.0-0/Miniforge3-24.3.0-0-Linux-x86_64.sh && \ bash conda.sh -b -p /opt/miniforge ENV PATH=/opt/miniforge/bin:$PATH # Create new Conda environment with dev versions of cuDF, Dask, and cuPy RUN \ export NCCL_SHORT_VER=$(echo "$NCCL_VERSION_ARG" | cut -d "-" -f 1) && \ mamba create -y -n gpu_test -c rapidsai-nightly -c conda-forge -c nvidia \ python=3.10 "cudf=$RAPIDS_VERSION_ARG.*" "rmm=$RAPIDS_VERSION_ARG.*" cudatoolkit=$CUDA_VERSION_ARG \ "nccl>=${NCCL_SHORT_VER}" \ dask \ "dask-cuda=$RAPIDS_VERSION_ARG.*" "dask-cudf=$RAPIDS_VERSION_ARG.*" cupy \ numpy pytest pytest-timeout scipy scikit-learn pandas matplotlib wheel python-kubernetes urllib3 graphviz hypothesis \ "pyspark>=3.4.0" cloudpickle cuda-python && \ mamba clean --all --yes && \ conda run --no-capture-output -n gpu_test pip install buildkite-test-collector ENV GOSU_VERSION 1.10 ENV JAVA_HOME /usr/lib/jvm/java-8-openjdk-amd64/ # Install lightweight sudo (not bound to TTY) RUN set -ex; \ wget -nv -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"]