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
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.
[0.3.1] - 2020-09-21
Added
- Aliased
ResizeShortest
toShortestMaxSize
to be consistent withalbumentations.augmentations.transforms.LongestMaxSize
Fixed
- Add missing interpolation attribute in ResizeShortest transform.
- Fixed
ResizeShortest
producing erroenous results when both sides are the same length.
[0.3.0] - 2020-09-21
Added
- Text label adding to TensorBoard Images
- ResizeShortest augmentation transform
- Unit Testing utilities
- basic Datasets API
- A bunch of useful dependencies added.
[0.2.0] - 2020-09-15
Added
- Additional extra_requires in preparation for docker release.
[0.1.0] - 2020-09-13
Added
- Initial Release
Project details
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