Catalyst helps you write compact but full-featured DL & RL pipelines in a few lines of code. You get a training loop with metrics, early-stopping, model checkpointing and other features without the boilerplate.
Features:
- Universal train/inference loop.
- Configuration files for model/data hyperparameters.
- Reproducibility – all source code and environment variables will be saved.
- Callbacks – reusable train/inference pipeline parts.
- Training stages support.
- Easy customization.
- PyTorch best practices (SWA, AdamW, 1Cycle, Ranger optimizer, FP16 and more).
https://github.com/catalyst-team/catalyst
#python #data
Features:
- Universal train/inference loop.
- Configuration files for model/data hyperparameters.
- Reproducibility – all source code and environment variables will be saved.
- Callbacks – reusable train/inference pipeline parts.
- Training stages support.
- Easy customization.
- PyTorch best practices (SWA, AdamW, 1Cycle, Ranger optimizer, FP16 and more).
https://github.com/catalyst-team/catalyst
#python #data
GitHub
GitHub - catalyst-team/catalyst: Accelerated deep learning R&D
Accelerated deep learning R&D. Contribute to catalyst-team/catalyst development by creating an account on GitHub.