Bootstrap: docker From: nvidia/cuda:8.0-cudnn5-devel-ubuntu16.04 %setup #Runs on host #The path to the image is $APPTAINER_ROOTFS %post #Post setup script #Use bash as default shell echo "\n #Using bash as default shell \n" >> /environment echo 'SHELL=/bin/bash' >> /environment #Make environment file executable chmod +x /environment #Default mount paths mkdir /scratch /data /shared /fastdata #Nvidia Library mount paths mkdir /nvlib /nvbin #Add nvidia driver paths echo "\n #Nvidia driver paths \n" >> /environment echo 'export PATH="/nvbin:$PATH"' >> /environment echo 'export LD_LIBRARY_PATH="/nvlib:$LD_LIBRARY_PATH"' >> /environment #Add CUDA paths echo "\n #Cuda paths \n" >> /environment echo 'export CPATH="/usr/local/cuda/include:$CPATH"' >> /environment echo 'export PATH="/usr/local/cuda/bin:$PATH"' >> /environment echo 'export LD_LIBRARY_PATH="/usr/local/cuda/lib64:$LD_LIBRARY_PATH"' >> /environment echo 'export CUDA_HOME="/usr/local/cuda"' >> /environment #Updating and getting required packages apt-get update apt-get install -y wget git vim #Creates a build directory mkdir build cd build #Download and install Anaconda CONDA_INSTALL_PATH="/usr/local/anaconda3-4.2.0" wget https://repo.continuum.io/archive/Anaconda3-4.2.0-Linux-x86_64.sh chmod +x Anaconda3-4.2.0-Linux-x86_64.sh ./Anaconda3-4.2.0-Linux-x86_64.sh -b -p $CONDA_INSTALL_PATH #Add Anaconda path echo "\n #Anaconda paths \n" >> /environment echo 'export PATH="'$CONDA_INSTALL_PATH'/bin:$PATH"' >> /environment #Loads the environment file . /environment #Install Theano conda install -y scipy nose pydot-ng theano pygpu #Install Keras pip install keras %runscript #Executes with the apptainer run command #delete this section to use existing docker ENTRYPOINT command %test #Test that script is a success