A C++ implementation of density forests.
A template for extending PyTorch using C/CUDA operations.
Basic and advanced torch examples, template for implementing custom C/CUDA modules and implementations of variational auto-encoders.
PyTorch, alongside TensorFlow, has become standard among deep learning researchers and practitioners. While PyTorch provides a large variety in terms of tensor operations or deep learning layers, some specialized operations still need to be implemented manually. In cases where runtime is crucial, this should be done in C or CUDA for supporting both CPU and GPU computation. In this article, I want to provide a simple example and framework for extending PyTorch with custom C and CUDA operations using CFFI for Python and CuPy.