This repository provides PyTorch implementations of numerous deep learning architectures for image classification tasks. It includes models such as ResNet, DenseNet, PyramidNet, SENet, and various augmentation techniques like CutMix, Mixup, and Random Erasing. The code supports training on standard benchmark datasets including CIFAR-10, CIFAR-100, MNIST, FashionMNIST, and ImageNet with configurable settings via YAML files.