neural prototyping framework
Project description
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/protoNN-ai/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
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