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[protoNN logo]

A framework for code-agnostic, interactive prototyping of DNNs.

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Features

  • Transparent and elastic scheduling of DNN training jobs on modern HPC systems.

  • Monitoring and visualizing model parameters and computational performance statistics.

  • Perform semi-automatic hyperparameter tuning/optimization and architecture search using evolutionary algorithms.

  • A user-defined interactive interface to drive the framework/ design process, not bound to any particular framework.

  • Scaling the functionality and performance of the model as the resources increase.

How do I get set up?

  • pip3 install protonn for latest stable release

  • pip3 install git+https://github.com/undertherain/protoNN.git for recent development version

  • Python 3.6 or later is required

Contributors

Aleksandr Drozd

Mohamed Wahib

Mateusz Bysiek

Maxim Shpakovich

For licensing information, please see LICENSE

Release files for protonn 0.3.2

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Table of built distributions (wheels) for protonn 0.3.2
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