This repository provides a PyTorch implementation of DropBlock, a regularization technique specifically designed for convolutional layers. Unlike standard dropout which is less effective on spatially correlated activation units in conv layers, DropBlock drops contiguous regions of feature maps together, improving regularization. The implementation supports configurable block sizes and includes integration options for skip connections. It targets computer vision models where convolutional networks dominate.