semvec/pypi-packages huggingface dataset:
TorchSUL 0.3.1
Simple but useful layers for Pytorch

# TorchSUL

This package is created for a better experience with Pytorch. 


## Quick start

[Quick start](https://github.com/ddddwee1/TorchSUL/blob/master/QuickStart.md)


## References

[Quantization](https://github.com/ddddwee1/TorchSUL/blob/master/QuantInstruction.md)

[Model Flags](https://github.com/ddddwee1/TorchSUL/blob/master/FlagList.md)


## Why making this

- I dont want to write in_channels when building models. It's wired that I should care about input when I only want to write *forward* flows.

- It inlines with my [TF wrap-ups](https://github.com/ddddwee1/sul) so I can easily move my old code and model structures to the current package.


## Installation

You need to install pytorch>=1.10, and python>=3.7

Good, then just 

```
pip install --upgrade torchsul
```


## Patch Notes


#### 2023-xx-xx:  Upgrade to 0.3.0

1. Refactor the codes. Now the structure becomes clearer and more extendable

2. Almost supports type hinting 

3. (Base) build_forward is removed 

4. (Tools) Add more tools


## Projects 

You can find some examples in the "example" folder. It's almost like a trash bin, and some of the functions & modules may be no longer supported in the current version.

- ArcFace (Deng, Jiankang, et al. "Arcface: Additive angular margin loss for deep face recognition." arXiv preprint arXiv:1801.07698 (2018))

- HR Net (Sun, Ke, et al. "Deep High-Resolution Representation Learning for Human Pose Estimation." arXiv preprint arXiv:1902.09212 (2019))

- AutoDeepLab (Liu, Chenxi, et al. "Auto-deeplab: Hierarchical neural architecture search for semantic image segmentation." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019)

- Knowledge distillation (Hinton, Geoffrey, Oriol Vinyals, and Jeff Dean. "Distilling the knowledge in a neural network." arXiv preprint arXiv:1503.02531 (2015))

- 3DCNN (Ji, Shuiwang, et al. "3D convolutional neural networks for human action recognition." IEEE transactions on pattern analysis and machine intelligence 35.1 (2012): 221-231)

- Temporal Convolutional Network (Not the same) (Pavllo, Dario, et al. "3D human pose estimation in video with temporal convolutions and semi-supervised training." Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019)

- RetinaFace for face detection (Deng, Jiankang, et al. "Retinaface: Single-stage dense face localisation in the wild." arXiv preprint arXiv:1905.00641 (2019))

- Fractal Net (Larsson, Gustav, Michael Maire, and Gregory Shakhnarovich. "Fractalnet: Ultra-deep neural networks without residuals." arXiv preprint arXiv:1605.07648 (2016))

- Polarized Self Attention (Liu, Huajun, et al. "Polarized self-attention: Towards high-quality pixel-wise regression." arXiv preprint arXiv:2107.00782 (2021))

- Some 2D/3D pose estimation works

- Some network structures

- Some cuda kernels
make-package-selector 1.0.post1
A tool to select directories and run make clean all command on those selected directory/src
Requires Python: >=3.6

# Make Package Selector

make_package_selector is a utility written in Python to `make` clean and build multiple directories. It does it by allowing you to select one or multiple directory in a visual table through CLI. 

You can also customize the start path (default is current directory) and source path (default is src) and other parameter. 


## Pre-requisite
* Python >= 3.6
* simple-term-menu >= 1.6.4

### Usage

```
$ make_package_selector.py [-h] [-d DIR] [-s SOURCE] [-y] [-w WAIT] 

Clean and build selected directories.

options:
  -h, --help                    Show this help message and exit
  -d DIR, --dir DIR             Absolute or relative path to start directory scanning. Default is current directory.
  -s SOURCE, --source SOURCE    The source directory inside the selected directory. Default is src 
  -y, --yes                     Suppress confirmation. Default is do not suppress. 
  -w WAIT, --wait WAIT          Time to wait in seconds before executing the command. Default is 15 seconds.

```


## Installation

### Using Pip
```
pip install make-package-selector
``` 

### Using Git
#### Clone the repo
```
git clone https://github.com/animeshdas/make_package_selector.git
```
#### Install
```
cd make_package_selector/dist
python -m pip install make_package_selector-<version>-py3-none-any.whl
```
OR
```
cd make_package_selector/dist
python -m pip install make_package_selector-<version>.tar.gz
```