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# It's generally advisable to perform installations in an interactive session (https://confluence.columbia.edu/confluence/display/zmbbi/Interactive+Sessions)
# on one of the nodes, since there are memory limitations on the login node that can occasionally 
# lead to out-of-memory errors during the installation process.
# In this case I am requesting 2 CPUs on node ax08, 1 GPU, for 1 hour, and to use a bash interactive shell
srun --pty -c 2 --nodelist=ax08 --gres=gpu:1 -t 0-01:00 /bin/bash

# Next I activate conda by loading the module for it
ml load anaconda3-2019.03

# next I create an environment. Note that I specify a version of python that I want
conda create -n demo-env python=3.6

# once the environment finishes building I need to activate it
conda activate demo-env

# then I can install software that is available in the conda repos
# N.B. the -c flag will specify a "channel" or specific repo
conda install pytorch torchvision torchaudio cudatoolkit=10.2 -c pytorch
conda install -c conda-forge tensorboard

# you can also do pip installs for python requirements which will be local to this environment
pip install gym