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An Introduction to Writing Modulefiles: Module files are scripted using Lua and define core environment elements required to setup and use something.
Example:
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[salexan5@mblog2 ~]$ cd /project/arcc<project-name>/software [salexan5@mblog2 software] mkdir -p modules/tensorflow [salexan5@mblog2 software] cd modules/tensorflow [salexan5@mblog2 tensorflow] vim 2.16.lua |
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# 2.16.lua
whatis(" Name: TensorFlow ")
whatis(" Version : 2.16 ")
whatis(" Short Description: An end-to-end platform for machine learning.")
prepend_path("PATH","/project/arcc<project-name>/software/tensorflow/2.16/bin/") |
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To expose your module files you need to tell the module system where to look using the |
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[salexan5@mblog1 ~]$ module avail
-------------- /apps/s/lmod/mf/opt/linux-rhel9-x86_64/containers ---------------
stress-ng/0.17.08
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# Expose your module files. [salexan5@mblog1 ~]$ module use /project/arcc<project-name>/software/modules/ |
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[salexan5@mblog1 ~]$ module avail ------------------------ /project/arcc<project-name>/software/modules ------------------------ tensorflow/2.16 -------------- /apps/s/lmod/mf/opt/linux-rhel9-x86_64/containers --------------- stress-ng/0.17.08 ... |
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[salexan5@mblog2 ~]$ module spider tensorflow
----------------------------------------------------------------------------
tensorflow: tensorflow/2.16
----------------------------------------------------------------------------
This module can be loaded directly: module load tensorflow/2.16 |
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Loading a local module has the same effect as using a System module. Your environment will be updated by setting appropriate environment variables. |
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[salexan5@mblog1 ~@mblog1]$ salloc -A arcc<project-name> -t 10:00 salloc: Granted job allocation 845851 salloc: Nodes mbcpu-001 are ready for job [salexan5@mbcpu@mbcpu-001 ~]$ module use /project/arcc<project-name>/software/modules/ [salexan5@mbcpu@mbcpu-001 ~]$ module load tensorflow/2.16 [salexan5@mbcpu@mbcpu-001 ~]$ python --version Python 3.11.9 [salexan5@mblog2 tensorflow@mbcpu-001]$ which python /project/arcc<project-name>/software/tensorflow/2.16/bin/python |
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After loading our module and exposing the conda environment, notice how the |
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[salexan5@mblog2 tensorflow@mbcpu-001]$ python -m sysconfig Platform: "linux-x86_64" Python version: "3.11" Current installation scheme: "posix_prefix" Paths: data = "/project/arcc<project-name>/software/tensorflow/2.16" ... stdlib = "/project/arcc<project-name>/software/tensorflow/2.16/lib/python3.11" Variables: ... userbase = "/cluster/medbow/project/arcc<project-name>/software/tensorflow/2.16" |
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All the conda and pip package installs within this conda environment are available. |
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[salexan5@mbcpu@mbcpu-001 ~]$ python -c "import tensorflow as tf; print(\"TensorFlow Version: \" + str( tf.__version__))" ... TensorFlow Version: 2.16.1 [salexan5@mbcpu@mbcpu-001 ~]$ exit exit salloc: Relinquishing job allocation 845851 |
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