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 3.6 or later is required

Aleksandr Drozd

Mohamed Wahib

Mateusz Bysiek

Maxim Shpakovich

For licensing information, please see LICENSE

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Table of built distributions (wheels) for protonn 0.2.2
File	Interpreter	ABI	Platform	Reset
protonn-0.2.2-py3-none-any.whl 17.6 kB Dec 1, 2020	Python 3	none	any	Details

Download URL	protonn-0.2.2-py3-none-any.whl
Size	17.6 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`263c9948087009580257d4612b5ec4656763539366d2f391847eedbcafd6a41e`
BLAKE2b-256 checksum How to use checksums	`3b691af87ab1924eaf09964b93e1a935d94ae1162d60f773b1afe542ea03cf98`
Upload date	Dec 1, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.1.1 pkginfo/1.5.0.1 requests/2.23.0 setuptools/50.3.0 requests-toolbelt/0.9.1 tqdm/4.45.0 CPython/3.8.6`