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To create a conda environment that contains pytorch and tensorflow it is we first needed need to determine what is the driver used by cuda.
Login to "ssh -X psana -l psrel"
and run "nvidia-smi"

The driver is v11.4 (top right)
Allow the proxy to see the external internet:
export HTTP_PROXY=http://psproxy:3128
export HTTPS_PROXY=http://psproxy:3128

Allow conda and deactivate the loaded environemtenvironmet:

source /cds/sw/ds/ana/conda1/manage/bin/psconda.sh

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conda deactivate

proceed in creating the new environment:

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PS: Since we start without an environment (conda deactivate) the --experimental-solver does not work in the creation of the environment. This is the reason of the split up in two commands.

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To import the new environment into Jupyter notebook we need to change the user.:

Exit from this ssh and re-login as ssh -X psbuild-rhel7-01 -l psreldev

make a new copy of a prexisting kernel folder:

cp /reg/g/psdm/sw/conda/jhub_config/prod-rhel7/kernels/deeplearning5/ /reg/g/psdm/sw/conda/jhub_config/prod-rhel7/kernels/deeplearning8/

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