⚡️Flexible interface for solving computer vision tasks leveraging Pytorch Lightning, PyTorch Image Models , and Hydra. ⚡️
Requirements
Linux or macOS with Python ≥ 3.6
PyTorch ≥ 1.7.0 and torchvision that matches the PyTorch installation. Install them together at pytorch.org to make sure of this.
Introduction
PyTorch Gale tasks allow you to train models using PyTorch Image Models models, use Hydra to hotswap models, optimizers or schedulers and leverage all the advances features that Lightning has to offer, including custom Callbacks, Loggers, Accelerators and high performance scaling with minimal changes.
This project was started as a way to collect interesting techniques dotted throughout Kaggle competitions and varous deep learning forums which have been usefull in training accuracte deep learning models for Computer Vision Tasks.
Currently PyTorch Gale only supports Image Classification. The final goal is to be able to support both Object Detection and Image Segmentation hopefully.
PyTorch Gale is beta software. The project is under active development and our APIs are subject to change in future releases. The current API of PyTorch Gale is highly inspired from Detectron 2.
PyTorch Gale comes with all the goodness that comes in PyTorch Lightning. Using the training script train.py [WIP] you can override any config parameter from command line. The same code can be trained on CPU, GPU even TPUs. Hydra configuration makes it easy to keep track of training hyperparameters enabling you to interate over different parameters without changing the code, just make minor changes to the config. Some examples configs are given in references [WIP].
PyTorch Gale also comes with a few usefull tricks to streamline you trainings and also has extensive callbacks for PyTorch Lightning.
How To Learn
The best way to learn PyTorch Gale is to go through the documentation. You should probably get familiar with PyTorch and PyTorch Lightning. Next, go through Hydra docs and PyTorch Image Models
Contributions
Have a question? Found a bug? Missing a specific feature? Ran into a problem? Feel free to file a new issue or PR with respective title and description. If you already found a solution to your problem, don't hesitate to share it. Suggestions for new best practices and tricks are always welcome!
After you clone this repository, please run nbdev_install_git_hooks in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks (e.g. which cells you ran) which causes unnecessary merge conflicts.