Custom Operators

Created On: Jul 28, 2025 | Last Updated On: Jul 28, 2025

Summary:

• Use custom operators to have torch.compile treat a function as opaque. torch.compile will never trace into the function and Inductor (the backend) will run the function as-is.

You may wish to use a custom operator in any of the following situations:

• Your code calls some C/C++/CUDA code. Dynamo is a Python bytecode interpreter and generally does not know how to handle calls to C/C++/CUDA functions that are bound to Python.

• Dynamo and non-strict tracing have trouble tracing through a function and you want it to be ignored by torch.compile.

Please see the Python custom ops tutorialfor more details on how to wrap a Python function into a torch.compile-understood custom operator.

For more advanced use cases, you may wish to use our C++ Custom Operator API; please see here for more information.