attorch reimplements PyTorch’s nn module using OpenAI’s Triton language for GPU acceleration. It provides optimized implementations of common neural network layers including attention mechanisms, convolutions, and normalization operations. The library supports both training and inference by implementing both forward and backward passes. It targets developers who need custom deep learning operations but lack expertise to write CUDA kernels directly.