DeepLearnPhysics/larcv3-singularity:centos7-cuda-tf-larcv
$ singularity pull shub://DeepLearnPhysics/larcv3-singularity:centos7-cuda-tf-larcv
Singularity Recipe
Bootstrap: shub
From: DeepLearnPhysics/larcv3-singularity:centos7-cuda-tf
%help
Centos7 with cuda9.0 cudnn7
ML/DL packages : torchnightly sc-learn
Sci. packages : numpy pandas sc-image matplotlib opencv-python
Basic python : ipython jupyter yaml pygments six zmq wheel h5py tqdm
Development kit : g++/gcc cython nvcc libqt4-dev python-dev
Utility kit : git wget emacs vim openssh-client swig larrcv
To start your container simply try
singularity exec THIS_CONTAINER.simg bash
To use GPUs, try
singularity exec --nv THIS_CONTAINER.simg bash
%labels
Maintainer coreyjadams
Version centos7-cuda-tf-larcv
#------------
# Global installation
#------------
%environment
%post
# Using the app area to store software:
mkdir /app
cd /app
scl enable devtoolset-4 bash
scl enable rh-python36 bash
pip3 install ninja
#Install the latest larcv3:
git clone https://github.com/DeepLearnPhysics/larcv3.git
cd larcv3/
python setup.py install --cmake-executable cmake3
cd -
Collection
View on Datalad
Metrics
key | value |
---|---|
id | /containers/DeepLearnPhysics-larcv3-singularity-centos7-cuda-tf-larcv |
collection name | DeepLearnPhysics/larcv3-singularity |
branch | master |
tag | centos7-cuda-tf-larcv |
commit | 8c86bd90e0225b2db3d9e92246ab612e9dcd1433 |
version (container hash) | 1934a05e8313713cbc4cf514e1cd5865 |
build date | 2020-05-08T10:08:57.381Z |
size (MB) | 6269 |
size (bytes) | 2900660255 |
SIF | Download URL (please use pull with shub://) |
Datalad URL | View on Datalad |
Singularity Recipe | Singularity Recipe on Datalad |
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