Functions, losses, and module blocks to share between experiments.
Project description
Pugh Torch
Functions, losses, and module blocks to share between experiments.
Features
- Additional methods to TensorBoard summary writer for adding normalized images and semantic segmentation images.
- hetero_cross_entropy for cross_entropy loss across heterogeneous datasets
Installation
Stable Release: pip install pugh_torch
Development Head: pip install git+https://github.com/BrianPugh/pugh_torch.git
Documentation
For full package documentation please visit BrianPugh.github.io/pugh_torch.
Free software: MIT license
#HISTORY
Changelog
All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
[0.1.0] - 2020-09-13
Added
- Initial Release
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pugh_torch-0.1.0.tar.gz
(17.7 kB
view hashes)
Built Distribution
Close
Hashes for pugh_torch-0.1.0-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 50910b84b63f2b8d34b9c00e14e58bfe7209e7318af1d0b1e7403e4fcfdb55ca |
|
MD5 | 2692eb10a7b53226315d633f8407ab36 |
|
BLAKE2b-256 | 4da63426ca342906f5d9a68121821674d711b484b6149bae2094a7bf0d865ee3 |