Sylvia-Liang/torch37:latest
$ singularity pull shub://Sylvia-Liang/torch37: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:$LD_LIBRARY_PATH"
CUDA_HOME="/usr/local/cuda"
export CPATH PATH LD_LIBRARY_PATH CUDA_HOME
# make conda accessible
PATH=/opt/conda/envs/pytorch-py3.7/bin:$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
# user requests (contact marcc-help@marcc.jhu.edu)
/opt/conda/bin/conda install opencv scikit-learn scikit-image scipy pandas
/opt/conda/bin/conda install -c anaconda numpy pytest flake8 tensorflow-tensorboard
/opt/conda/bin/conda install -c conda-forge tensorboardx tqdm protobuf onnx spectrum nibabel
# try a pip install
/opt/conda/bin/pip install torchtext
%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: Sylvia-Liang/torch37
- License: None
View on Datalad
Metrics
key | value |
---|---|
id | /containers/Sylvia-Liang-torch37-latest |
collection name | Sylvia-Liang/torch37 |
branch | master |
tag | latest |
commit | 3492c23464151d76e48f83997cd947c127634c6a |
version (container hash) | d7d530723f8f90ee46e44332336f4142 |
build date | 2019-04-22T21:53:08.860Z |
size (MB) | 9012 |
size (bytes) | 4232753183 |
SIF | Download URL (please use pull with shub://) |
Datalad URL | View on Datalad |
Singularity Recipe | Singularity Recipe on Datalad |
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