* [CI] Use Vault repository to re-gain access to devtoolset-4 * Use manylinux2010 tag * Update Dockerfile.jvm * Fix rename_whl.py * Upgrade Pip, to handle manylinux2010 tag * Update insert_vcomp140.py * Update test_python.sh
59 lines
2.5 KiB
Docker
59 lines
2.5 KiB
Docker
ARG CUDA_VERSION
|
|
FROM nvidia/cuda:$CUDA_VERSION-devel-centos6
|
|
|
|
# Environment
|
|
ENV DEBIAN_FRONTEND noninteractive
|
|
ENV DEVTOOLSET_URL_ROOT http://vault.centos.org/6.9/sclo/x86_64/rh/devtoolset-4/
|
|
|
|
# Install all basic requirements
|
|
RUN \
|
|
yum -y update && \
|
|
yum install -y tar unzip wget xz git centos-release-scl yum-utils && \
|
|
yum-config-manager --enable centos-sclo-rh-testing && \
|
|
yum -y update && \
|
|
yum install -y $DEVTOOLSET_URL_ROOT/devtoolset-4-gcc-5.3.1-6.1.el6.x86_64.rpm \
|
|
$DEVTOOLSET_URL_ROOT/devtoolset-4-gcc-c++-5.3.1-6.1.el6.x86_64.rpm \
|
|
$DEVTOOLSET_URL_ROOT/devtoolset-4-binutils-2.25.1-8.el6.x86_64.rpm \
|
|
$DEVTOOLSET_URL_ROOT/devtoolset-4-runtime-4.1-3.sc1.el6.x86_64.rpm \
|
|
$DEVTOOLSET_URL_ROOT/devtoolset-4-libstdc++-devel-5.3.1-6.1.el6.x86_64.rpm && \
|
|
# Python
|
|
wget -O Miniconda3.sh https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
|
|
bash Miniconda3.sh -b -p /opt/python && \
|
|
# CMake
|
|
wget -nv -nc https://cmake.org/files/v3.13/cmake-3.13.0-Linux-x86_64.sh --no-check-certificate && \
|
|
bash cmake-3.13.0-Linux-x86_64.sh --skip-license --prefix=/usr
|
|
|
|
# NCCL2 (License: https://docs.nvidia.com/deeplearning/sdk/nccl-sla/index.html)
|
|
RUN \
|
|
export CUDA_SHORT=`echo $CUDA_VERSION | egrep -o '[0-9]+\.[0-9]'` && \
|
|
export NCCL_VERSION=2.4.8-1 && \
|
|
wget https://developer.download.nvidia.com/compute/machine-learning/repos/rhel7/x86_64/nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
|
|
rpm -i nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm && \
|
|
yum -y update && \
|
|
yum install -y libnccl-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-devel-${NCCL_VERSION}+cuda${CUDA_SHORT} libnccl-static-${NCCL_VERSION}+cuda${CUDA_SHORT} && \
|
|
rm -f nvidia-machine-learning-repo-rhel7-1.0.0-1.x86_64.rpm;
|
|
|
|
ENV PATH=/opt/python/bin:$PATH
|
|
ENV CC=/opt/rh/devtoolset-4/root/usr/bin/gcc
|
|
ENV CXX=/opt/rh/devtoolset-4/root/usr/bin/c++
|
|
ENV CPP=/opt/rh/devtoolset-4/root/usr/bin/cpp
|
|
|
|
# Install Python packages
|
|
RUN \
|
|
pip install numpy pytest scipy scikit-learn wheel kubernetes urllib3==1.22
|
|
|
|
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"]
|