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
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distribution
File details
Details for the file protonn-0.1.5-py3-none-any.whl.
File metadata
- Download URL: protonn-0.1.5-py3-none-any.whl
- Upload date:
- Size: 14.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/44.0.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.5
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 636afa4bfb81ea5b27d9ce22de5147b8a0a9f2524c7a2cbc8573b62c1caa2338 |
|
| MD5 | 315221ed414250a1366c0e1b3fdb0efb |
|
| BLAKE2b-256 | 8d1cadcd89c89af534d44613343112e8aa9688d290718bac1a8d28b4aabc7a21 |
