ZhugeKongan/torch-template-for-deep-learning
A PyTorch deep learning template offering implementations of backbone CNNs, augmentation strategies, losses, attention modules, and visualization tools.
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This repository provides PyTorch implementations of numerous classical backbone CNN architectures along with common deep learning utilities. It includes data augmentation techniques like Cutout, Mixup, CutMix, and ShakeDrop, various loss functions, attention mechanisms, and visualization tools. The template comes with dataset loaders for multiple domains and a training script to facilitate model development.
Frequently asked
- What is ZhugeKongan/torch-template-for-deep-learning?
- A PyTorch deep learning template offering implementations of backbone CNNs, augmentation strategies, losses, attention modules, and visualization tools.
- Is torch-template-for-deep-learning open source?
- Yes — ZhugeKongan/torch-template-for-deep-learning is open source, released under the Apache-2.0 license.
- What language is torch-template-for-deep-learning written in?
- ZhugeKongan/torch-template-for-deep-learning is primarily written in Python.
- How popular is torch-template-for-deep-learning?
- ZhugeKongan/torch-template-for-deep-learning has 1.3k stars on GitHub.
- Where can I find torch-template-for-deep-learning?
- ZhugeKongan/torch-template-for-deep-learning is on GitHub at https://github.com/ZhugeKongan/torch-template-for-deep-learning.