BootStrap: docker From: nvidia/cuda:9.2-devel-ubuntu18.04 # NOTE: This container will have both the Python and the R API's enabled %environment # ----------------------------------------------------------------------------------- export PYTHON_VERSION=3.6 export CUDA_HOME=/usr/local/cuda export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64/:$CUDA_HOME/lib/:$CUDA_HOME/extras/CUPTI/lib64 export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH export LC_ALL=C %post # ----------------------------------------------------------------------------------- # this will install all necessary packages and prepare the contianer export PYTHON_VERSION=3.6 export CUDA_HOME=/usr/local/cuda export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$CUDA_HOME/lib64/:$CUDA_HOME/lib/:$CUDA_HOME/extras/CUPTI/lib64 echo "deb http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64 /" > /etc/apt/sources.list.d/nvidia-ml.list apt-get -y update && apt-get install -y --no-install-recommends \ build-essential \ git \ curl \ vim \ wget \ ca-certificates \ libjpeg-dev \ libpng-dev \ libpython3.6-dev \ libopenblas-dev pbzip2 \ libcurl4-openssl-dev libssl-dev libxml2-dev ln -s /usr/bin/python${PYTHON_VERSION} /usr/bin/python curl -O https://bootstrap.pypa.io/get-pip.py && \ python get-pip.py && \ rm get-pip.py wget https://s3.amazonaws.com/h2o-release/h2o4gpu/releases/stable/ai/h2o/h2o4gpu/0.3-nccl-cuda92/h2o4gpu-0.3.0-cp36-cp36m-linux_x86_64.whl pip install h2o4gpu-0.3.0-cp36-cp36m-linux_x86_64.whl export DEBIAN_FRONTEND=noninteractive export DEBCONF_NONINTERACTIVE_SEEN=true apt-get install -y r-base r-base-dev apt-get install -y libcurl4-gnutls-dev dpkg-reconfigure -f noninteractive tzdata R -e ' install.packages(c("devtools","curl","Metrics")) ' R -e ' devtools::install_github("h2oai/h2o4gpu", subdir = "src/interface_r") '