mark-e-deyoung/afit_mlperf_training:translation
$ singularity pull shub://mark-e-deyoung/afit_mlperf_training:translation
Singularity Recipe
Bootstrap: docker
# https://hub.docker.com/r/nvidia/cuda
From: nvidia/cuda:9.0-cudnn7-devel
%environment
PATH="/usr/local/anaconda/bin:$PATH"
MLPERF_DATA_DIR="/data"
%post
# install debian packages
apt-get update
apt-get install -y eatmydata
eatmydata apt-get install -y wget bzip2 \
ca-certificates libglib2.0-0 libxext6 libsm6 libxrender1 \
git git-annex uuid-runtime
apt-get clean
# install anaconda
if [ ! -d /usr/local/anaconda ]; then
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh \
-O ~/anaconda.sh && \
bash ~/anaconda.sh -b -p /usr/local/anaconda && \
rm ~/anaconda.sh
fi
# set anaconda path
export PATH="/usr/local/anaconda/bin:$PATH"
# install required packages
conda install python=3.6
conda install pip
pip install --ignore-installed \
--upgrade https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.9.0-cp36-cp36m-linux_x86_64.whl
pip install mlperf-compliance
conda clean --tarballs
# make /data and /code for mounts to external directories
if [ ! -d /data ]; then mkdir /data; fi
if [ ! -d /code ]; then mkdir /code; fi
% runscript
echo "Singularity: TensorFlow 1.9.0"
exec /bin/bash
Collection
- Name: mark-e-deyoung/afit_mlperf_training
- License: Apache License 2.0
View on Datalad
Metrics
key | value |
---|---|
id | /containers/mark-e-deyoung-afit_mlperf_training-translation |
collection name | mark-e-deyoung/afit_mlperf_training |
branch | master |
tag | translation |
commit | eaf1758ac31a8b96c233869fbd6ae755d34b5d18 |
version (container hash) | 0b4c4b1e430cb22b8a5e5bb011a644f8 |
build date | 2020-05-06T17:54:26.367Z |
size (MB) | 4406 |
size (bytes) | 2308608031 |
SIF | Download URL (please use pull with shub://) |
Datalad URL | View on Datalad |
Singularity Recipe | Singularity Recipe on Datalad |
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