Tensorflow
SDSC Expanse Notebook: Tensorflow
This README file provides instructions for Expanse users on how to run TensorFlow on Expanse, both on CPU and GPU.
TensorFlow is a free and open-source software library for machine learning. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. Tensorflow is a symbolic math library based on dataflow and differentiable programming.
This chapter will show you how to implement an image classifaction NN as well as how to train an NN. Enjoy!\
Listof Content
Import Module:
- matplotlib
- numpy
- PIL
- tensorflow
- pathlib
- csv
Launch Galyleo
For specific information about launching Galyleo, please refer to this GitHub repository.
Command-line options
In Expanse, we have command-line options for building software environments like modules and Singularity, as well as managing memory, among other capabilities. To run the ML_Tensorflow_CPU notebook, we can utilize a Singularity container to execute the TensorFlow package.
- CPU:
galyleo launch --account abc123 --partition shared --cpus 2 --memory 4 --time-limit 00:30:00 --env-modules singularitypro --sif /cm/shared/apps/containers/singularity/tensorflow/tensorflow_24.03-tf2-py3.sif
Install Modules
We do not need to install any additional packages.
Location
Tensorflow
├── Image Classification.ipynb
├── SimpleTraining.ipynb
├── README.md
Submit Ticket
If you find anything that needs to be changed, edited, or if you would like to provide feedback or contribute to the notebook, please submit a ticket by contacting us at:
Email: consult@sdsc.edu
We appreciate your input and will review your suggestions promptly!
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