Torch Library API

The Torch Library API provides capabilities for extending PyTorch's core library of operators with user-defined operators and data types. This is the primary mechanism for registering custom C++ operators that can be called from both Python and C++.

When to use the Library API:

• When creating custom operators for PyTorch
• When implementing backend-specific kernels (CPU, CUDA, etc.)
• When registering custom classes for use in TorchScript
• When extending PyTorch with new functionality

Basic usage:

#include <torch/library.h>

// Define a custom operator
torch::Tensor my_add(const torch::Tensor& a, const torch::Tensor& b) {
    return a + b;
}

// Register the operator
TORCH_LIBRARY(myops, m) {
    m.def("add(Tensor a, Tensor b) -> Tensor", &my_add);
}

// Use from C++
auto result = torch::dispatcher::call("myops::add", tensor_a, tensor_b);

For a tutorial-style introduction to the library API, check out the Extending TorchScript with Custom C++ Operators tutorial.

Header Files

• torch/library.h - Main library API header
• torch/custom_class.h - Custom class registration

Library API Categories

:maxdepth: 1

registration
custom_classes
versioning

See Also

• {doc}../stable/index - For stable ABI operator registration