neural prototyping framework
Project description
![[protoNN logo]](https://pypi-camo.freetls.fastly.net/8d59517442f149b51095ac983b2ed928c77fdfca/68747470733a2f2f757365722d696d616765732e67697468756275736572636f6e74656e742e636f6d2f313633353930372f33343337343837322d62633030343135322d656232362d313165372d396537322d3966303233346666353635382e706e67)
A framework for code-agnostic, interactive prototyping of DNNs.
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 3.4 or later is required
Contributors
Aleksandr Drozd
Mohamed Wahib
Mateusz Bysiek
Maxim Shpakovich
For licensing information, please see LICENSE
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