[LINUX] Creating a graphtool Python environment, installing packages, and using the environment on IPEA's Linux SBSB server - jamiefogel/Networks GitHub Wiki
INSTALLATION OF MINICONDA
- Log into the linux server
- Go to root with sudo privileges
sudo su
- Enable proxy connection (temporarily)
export http_proxy="http://cache.ipea.gov.br:3128/"
export https_proxy="http://cache.ipea.gov.br:3128/"
- Or enable proxy connection (permanently) by adding the two lines above to the ~/.bashrc by doing
nano ~/.bashrc
(paste the two lines at the end of the file, CRTL+O to save it, enter, and CRTL+X to exit)
- On your browser, get the link to the latest miniconda from https://docs.anaconda.com/miniconda/
- Download the file with the link e.g.:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
- Run the bash file
bash Miniconda3-latest-Linux-x86_64.sh
- When asked for where to install it, install it somewhere in the user file system, e.g.
/home/DLIPEA/p13861161/miniconda3
- After installed, re-initiate the terminal with
source ~/.bashrc
- Run
conda init
CREATING A GRAPHTOOL ENVIRONMENT
- After steps above, still as a sudo user, run
conda create --name labor_gt -c conda-forge graph-tool
- Give user permissions to the new folder
sudo chown -R p13861161: /home/DLIPEA/p13861161/miniconda3
- In order to make conda accessible to our user, we need to return to the user profile
su p13861161
- Add the miniconda to the path, so we can execute the function conda from our user
echo 'export PATH="/home/DLIPEA/p13861161/miniconda3/bin:$PATH"' >> ~/.bashrc
- Test the function conda with
conda init
conda --version
INSTALLING PACKAGES
- First we want to make sure we are using the internet proxy by running
export http_proxy="http://cache.ipea.gov.br:3128/"
export https_proxy="http://cache.ipea.gov.br:3128/"
- Or enable proxy connection (permanently) by adding the two lines above to the ~/.bashrc by doing
nano ~/.bashrc
(paste the two lines at the end of the file, CRTL+O to save it, enter, and CRTL+X to exit)
- Enter in our environment
conda activate labor_gt
- Install any package with pip3, e.g.:
pip3 install pyarrow
- Notice that installing pytorch is less trivial, as we need to specify GPU options
(labor_gt) p13861161@graphtool-prod:~$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2017 NVIDIA Corporation
Built on Fri_Nov__3_21:07:56_CDT_2017
Cuda compilation tools, release 9.1, V9.1.85
- Install torch
conda install pytorch torchvision torchaudio cudatoolkit=9.2 -c pytorch
UTILIZING THE NEW PYTHON AND NEW ENVIRONMENT
- After logging in at our regular user in linux, enter in our environment
conda activate labor_gt
- Run python
python