mcw-rcc/tensorflow:1.14-gpu
$ singularity pull shub://mcw-rcc/tensorflow:1.14-gpu
Singularity Recipe
Bootstrap: docker
From: ubuntu:16.04
%labels
Maintainer Matthew Flister
Version 1.14-gpu
%help
This container runs TensorFlow-GPU 1.14.
%environment
# nvidia driver libs specific cuda version libs are mounted by --bind command at run
# required for GPU enabled container
SHELL=/bin/bash
CPATH="/cuda/include:$CPATH"
PATH="/cuda/bin:/nvidia:$PATH"
LD_LIBRARY_PATH="/cuda/lib64:/nvidia:$LD_LIBRARY_PATH"
CUDA_HOME="/cuda"
LC_ALL="C"
export PATH LD_LIBRARY_PATH CPATH CUDA_HOME LC_ALL
%post
# default mount points
mkdir -p /scratch/global /scratch/local /rcc/stor1/refdata /rcc/stor1/projects /rcc/stor1/depts
# NVIDIA driver mount points
mkdir /nvidia /cuda
touch /usr/bin/nvidia-smi
# Install necessary packages
apt-get update && apt-get install -y --no-install-recommends \
build-essential \
gcc-multilib \
libatlas-base-dev \
libboost-all-dev \
libhdf5-serial-dev \
libprotobuf-dev \
protobuf-compiler \
libopenblas-dev \
liblapack-dev \
gfortran \
libcurl4-openssl-dev \
python-pip \
python3-pip \
pkg-config \
python-dev \
python3-dev \
python-setuptools \
python3-setuptools \
python-tk \
python3-tk
apt-get clean
# Update pip
pip install --no-cache-dir --upgrade pip==9.0.3
pip3 install --no-cache-dir --upgrade pip==9.0.3
# Install TensorFlow-GPU
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.14.0-cp27-none-linux_x86_64.whl
pip install --no-cache-dir --ignore-installed --upgrade $TF_BINARY_URL
# Install python packages
pip install --no-binary --upgrade \
keras \
tflearn \
numpy \
nibabel \
h5py \
scikit-learn \
pandas \
scipy \
matplotlib \
ipykernel \
jupyter \
jupyterlab \
pydicom \
opencv-python \
tables \
tqdm \
scikit-image \
SimpleITK
# Install TensorFlow-GPU
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.14.0-cp35-cp35m-linux_x86_64.whl
pip3 install --no-cache-dir --ignore-installed --upgrade $TF_BINARY_URL
# Install python packages
pip3 install --no-binary --upgrade \
keras \
tflearn \
numpy \
nibabel \
h5py \
scikit-learn \
pandas \
scipy \
matplotlib \
ipykernel \
jupyter \
jupyterlab \
pydicom \
opencv-python \
tables \
tqdm \
scikit-image \
SimpleITK
Collection
- Name: mcw-rcc/tensorflow
- License: MIT License
View on Datalad
Metrics
key | value |
---|---|
id | /containers/mcw-rcc-tensorflow-1.14-gpu |
collection name | mcw-rcc/tensorflow |
branch | 1.14-gpu |
tag | 1.14-gpu |
commit | 22684bd06c715bbd445c3a732dbaf3206bb2ebaf |
version (container hash) | f0f3ec92284cb15b1c80137b315f8ed8 |
build date | 2020-08-31T12:06:55.780Z |
size (MB) | 5776 |
size (bytes) | 1855782943 |
SIF | Download URL (please use pull with shub://) |
Datalad URL | View on Datalad |
Singularity Recipe | Singularity Recipe on Datalad |
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