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Install the ipykernel package

Code Block
[salexan5@mblog1 ~]$ module purge
[]$ module load miniconda3/24.3.0
[salexan5@mblog1 ~]$ conda activate /cluster/medbow/project/arcc<project-name>/software/tensorflow/2.16
(/cluster/medbow/project/arcc<project-name>/software/tensorflow/2.16) [salexan5@mblog1 ~]$ export PYTHONUSERBASE=$CONDA_PREFIX
(/cluster/medbow/project/arcc<project-name>/software/tensorflow/2.16) [salexan5@mblog1 ~]$ conda install ipykernel
...
(/cluster/medbow/project/arcc<project-name>/software/tensorflow/2.16) [salexan5@mblog1 ~]$ conda deactivate

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Created kernel related folder

Info

Installing the ipykernel package will create a kernel spec related folder that we can use.

This can be found under the Conda environment location, under: share/jupyter/kernels/ named python3

Code Block
[salexan5@mblog1 ~]$ ls /project/arcc/software/tensorflow/2.16/share/jupyter/kernels/python3/

[salexan5@mblog1 ~]$ cd /project/arcc<project-name>/software/tensorflow/2.16
[salexan5@mblog1 2.16]$ cd share/jupyter/kernels/
[salexan5@mblog1 kernels]$ ls
python3

[salexan5@mblog1 kernels]$ ls python3
kernel.json  logo-32x32.png  logo-64x64.png  logo-svg.svg
Info

Rename the folder to something more appropriate:

Code Block
[salexan5@mblog1 kernels]$ mv python3 TF2.16

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Configure Your Jupyter Environment

Note

If you haven’t used the Jupyter service, then you might not have, and thus will need to create the following folders:

~/.local/share/jupyter/kernels/

Info

Copy the created TF2.16 folder into your home:

Code Block
[salexan5@mblog1 kernels]$ cp -r TF2.16/ ~/.local/share/jupyter/kernels/
Info

Update the kernel.json file to:

  • give this kernel a unique display name.

Code Block
[salexan5@mblog1 kernels]$ ~/.local/share/jupyter/kernels/TF2.16/
[salexan5@mblog1 tf2.16]$ cat kernel.json
{
 "argv": [
  "/cluster/medbow/project/arcc<project-name>/software/tensorflow/2.16/bin/python",
  "-m",
  "ipykernel_launcher",
  "-f",
  "{connection_file}"
 ],
 "display_name": "TF2.16 (local)",
 "language": "python",
 "metadata": {
  "debugger": true
 }
}

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Within a Notebook

Within a Jupyter notebook cell try:

Code Block
import tensorflow as tf; 
print("TensorFlow Version: " + str( tf.__version__))

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