This repository provides a clean implementation of Graph Attention Networks in PyTorch. GATs apply self-attention mechanisms to graph-structured data, enabling nodes to weight their neighbors’ features adaptively. The implementation includes transductive learning on the Cora dataset and inductive learning on the PPI dataset, along with visualization tools for t-SNE embeddings, attention patterns, and entropy histograms.