This repository provides examples of writing custom CUDA operators and integrating them with popular neural network toolkits. It demonstrates three compilation methods (JIT, setuptools, CMake) for building CUDA kernels and their C++ wrappers. The repository includes Python code for timing comparisons between custom CUDA kernels and framework operations, as well as model training examples using custom kernels. It covers both PyTorch and TensorFlow integration patterns.