trunk/8027bc9387f8f06e13bbc50219df868b26d38aef: Add docs for higher order ops (#173896)
This changes how developers build complex AI models and control flows.
Deep Dive
PyTorch has officially documented four new higher-order operators—`scan`, `map`, `while_loop`, and `cond`—in a recent commit to its main development branch. These operators, now grouped under a dedicated directory, provide more functional and declarative ways to handle complex control flow, sequences, and transformations directly within PyTorch graphs. This move signals a maturation of PyTorch's capabilities beyond basic tensor operations, enabling more sophisticated and potentially more efficient model architectures.
Why It Matters
It enables developers to write cleaner, more efficient code for complex AI models like RNNs and stateful systems.