
TorchDynamo captures PyTorch programs safely using Python Frame Evaluation Hooks and is a significant innovation that was a result of 5 years of our R&D into safe graph capture. 
AOTAutograd overloads PyTorch’s autograd engine as a tracing autodiff for generating ahead-of-time backward traces. 
PrimTorch canonicalizes ~2000+ PyTorch operators down to a closed set of ~250 primitive operators that developers can target to build a complete PyTorch backend. This substantially lowers the barrier of writing a PyTorch feature or backend. 
TorchInductor is a deep learning compiler that generates fast code for multiple accelerators and backends. For NVIDIA and AMD GPUs, it uses OpenAI Triton as a key building block. For intel CPUs, we generate C++ code using multithreading, vectorized instructions and offloading appropriate operations to mkldnn when possible.
