daverblair/singularity_vlpi:latest
$ singularity pull shub://daverblair/singularity_vlpi:latest
Singularity Recipe
Bootstrap: docker
From: marcchpc/pytorch_cuda9
%environment
# use bash as default shell
SHELL=/bin/bash
export SHELL
# add CUDA paths
CPATH="/usr/local/cuda/include:$CPATH"
PATH="/usr/local/cuda/bin:$PATH"
LD_LIBRARY_PATH="/usr/local/cuda/lib64:$LD_LIBRARY_PATH"
CUDA_HOME="/usr/local/cuda"
export CPATH PATH LD_LIBRARY_PATH CUDA_HOME
# make conda accessible
PATH=/opt/conda/envs/pytorch-py3.6/bin:$PATH
export PATH
%setup
# runs on host - the path to the image is $SINGULARITY_ROOTFS
%post
# post-setup script
# load environment variables
. /environment
# make environment file executable
chmod +x /environment
# default mount paths, files
mkdir /scratch /data /work-zfs
touch /usr/bin/nvidia-smi
#conda installs
/opt/conda/bin/conda install libgcc opencv
#pip installs
#pytorch fixed to 1.5.1
/opt/conda/bin/pip install scikit-learn==0.22.1
/opt/conda/bin/pip install vlpi==0.1.5
/opt/conda/bin/pip install QRankGWAS
/opt/conda/bin/pip install CrypticPhenoImpute
%runscript
# executes with the singularity run command
# delete this section to use existing docker ENTRYPOINT command
%test
# test that script is a success
Collection
- Name: daverblair/singularity_vlpi
- License: None
View on Datalad
Metrics
key | value |
---|---|
id | /containers/daverblair-singularity_vlpi-latest |
collection name | daverblair/singularity_vlpi |
branch | master |
tag | latest |
commit | 80861c6261378e595db9f5a1df6bf250f207906d |
version (container hash) | cd8dc7f6c459a092a02575de504788d6 |
build date | 2021-03-05T21:51:53.806Z |
size (MB) | 8435.0 |
size (bytes) | 4636631071 |
SIF | Download URL (please use pull with shub://) |
Datalad URL | View on Datalad |
Singularity Recipe | Singularity Recipe on Datalad |
Feedback
Was this page helpful?
Glad to hear it! Please tell us how we can improve.
Sorry to hear that. Please tell us how we can improve.