This library provides a pure PyTorch implementation of SSIM, a widely used image quality metric. It offers both functional (ssim) and module (SSIM class) interfaces for computing structural similarity between images. The implementation supports GPU acceleration via CUDA and integrates with PyTorch’s autograd system, enabling its use as a differentiable loss function in training loops for image generation, super-resolution, and enhancement models.