/
theano.def
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/
theano.def
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Bootstrap: docker
From: nvidia/cuda:8.0-cudnn5-devel-ubuntu16.04
%setup
#Runs on host
#The path to the image is $SINGULARITY_ROOTFS
%post
#Post setup script
#Use bash as default shell
echo "\n #Using bash as default shell \n" >> /environment
echo 'SHELL=/bin/bash' >> /environment
#Make environment file executable
chmod +x /environment
#Default mount paths
mkdir /scratch /data /shared /fastdata
#Nvidia Library mount paths
mkdir /nvlib /nvbin
#Add nvidia driver paths
echo "\n #Nvidia driver paths \n" >> /environment
echo 'export PATH="/nvbin:$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
#Run every time image starts
%test
#Test that script is a success