PyTorch-SVGRender provides differentiable rendering methods for SVG generation using neural networks. It supports text-to-SVG and image-to-SVG conversion through techniques including score distillation sampling (SDS) and diffusion models. The library integrates differentiable vector graphics rasterization (DiffVG) and enables editing and synthesis of vector sketches and graphics.