Interdisciplinary Deep Learning Platform
Project description
Introduction
DeepMuon is a easy-using deep learning platform initially built for dark matter searching experiments. Up to now it has been a interdisciplinary deep learning platform. We are eager to provide advanced model training framework and excellent project management assistance.
Here we list out some available features of DeepMuon:
- Single GPU training, Distributed Data Parallel training and Fully Sharded Distributed Parallel training.
- Neural Network Hyperparameter Searching (NNHS)
- Gradient accumulation
- Gradient clipping
- Mixed precision training
- Double precision training
- Customize models
- Customize datasets
- Customize loss functions
- Tidy logging system
- Model interpretation
- Simple and direct tutorials
More details please refer to the home page of DeepMuon.
Installation (From source recommended)
git clone https://github.com/Airscker/DeepMuon.git
cd DeepMuon
pip install -v -e ./ --user
CopyRight
GNU AFFERO GENERAL PUBLIC LICENSE
Project: DeepMuon
Interdisciplinary Deep Learning Platform
Author: Airscker/Yufeng Wang
Contributors: Yufeng Wang, Shendong Su
University of Science of Technology of China
If you want to publish thesis using DeepMuon, please add bibliography:
@misc{deepmuon, author = {Yufeng Wang}, title = {DeepMuon: Interdisciplinary deep-learning platform}, year = {2022}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://airscker.github.io/DeepMuon}}, }Copyright (C) 2023 by Airscker(Yufeng), All Rights Reserved.
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