1. 使用yml文件打包
bash
conda activate your_env
conda env export > environment.yml
编写cond.def
文件
bash
Bootstrap: docker
From: continuumio/miniconda3
%files
environment.yml
%post
/opt/conda/bin/conda env create -f environment.yml
%runscript
exec /opt/conda/envs/$(head -n 1 environment.yml | cut -f 2 -d ' ')/bin/"$@"
生成镜像:
bash
singularity build conda.sif conda.def
2. 利用tar包
2.1 安装conda-pack
bash
pip install conda-pack
版本需要0.7
以上。
2.2 导出tar包
bash
conda-pack -n <MY_ENV> -o packed_environment.tar.gz
编写conda.def
文件:
bash
Bootstrap: docker
From: continuumio/miniconda3
%files
packed_environment.tar.gz /packed_environment.tar.gz
%post
tar xvzf /packed_environment.tar.gz -C /opt/conda
conda-unpack
rm /packed_environment.tar.gz
生成镜像:
bash
singularity build --fakeroot <OUTPUT_CONTAINER.sif> conda.def
3. 在已有基础上构建
def
:
bash
Bootstrap: localimage
From: local_image.sif
%environment
# set up environment for when using the container
. /opt/conda/etc/profile.d/conda.sh
conda activate
%post
apt-get update -y
apt-get install -y \
build-essential \
wget \
cmake \
g++ \
r-base-dev \
make
R -e "install.packages('cowsay', dependencies=TRUE, repos='http://cran.rstudio.com/')"
# install miniconda
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh -b -f -p /opt/conda
rm Miniconda3-latest-Linux-x86_64.sh
# install conda components - add the packages you need here
. /opt/conda/etc/profile.d/conda.sh
conda activate
conda install -y -c conda-forge numpy cowpy
conda update --all
4. 沙盒模式
4.1 构建沙河目录
bash
singularity build --sandbox lolcow/ library://sylabs-jms/testing/lolcow
4.2 进入沙盒
bash
singularity shell --writable lolcow/
4.3 将沙盒打包成sif
bash
singularity build lolcow.sif lolcow/
5. 设置环境变量
pytorch
cmake未设置cuda
环境变量
bash
SET(CMAKE_INCLUDE_PATH ${CMAKE_INCLUDE_PATH} "path\\boost_1_80_0")
SET(CMAKE_LIBRARY_PATH ${CMAKE_LIBRARY_PATH} "path\\boost_1_80_0\\libs")
可以通过如下设置:
bash
%environment
export CUDA_INCLUDE_DIRS=/opt/conda/cuda/include
export CUDA_CUDART_LIBRARY=/opt/conda/cuda/lib
export LIBRARY_PATH=/opt/conda/cuda/lib:$LIBRARY_PATH
export CPATH=/opt/conda/cuda/include:$CPATH
export PATH=/opt/conda/cuda:$PATH
%post
mkdir -p /opt/conda/cuda
conda install cuda -c nvidia -p /opt/conda/cuda
mkdir -p /opt/conda/cudnn
conda install -c anaconda cudnn -p /opt/conda/cudnn
export PATH=/opt/conda/cuda:$PATH