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.