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       "name": "Torch Library API",
       "headline": "Torch Library API",
       "description": "PyTorch Library API in C++ \u2014 operator registration, custom classes, and versioning.",
       "url": "/api/library/index.html",
       "articleBody": "Torch Library API# The Torch Library API provides capabilities for extending PyTorch\u2019s 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 \u003ctorch/library.h\u003e // Define a custom operator torch::Tensor my_add(const torch::Tensor\u0026 a, const torch::Tensor\u0026 b) { return a + b; } // Register the operator TORCH_LIBRARY(myops, m) { m.def(\"add(Tensor a, Tensor b) -\u003e Tensor\", \u0026my_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# Operator Registration Custom Classes Library Versioning See Also# Torch Stable API - For stable ABI operator registration",
       "author": {
         "@type": "Organization",
         "name": "PyTorch Contributors",
         "url": "https://pytorch.org"
       },
       "image": "https://pytorch.org/docs/stable/_static/img/pytorch_seo.png",
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         "@id": "/api/library/index.html"
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       "datePublished": "2023-01-01T00:00:00Z",
       "dateModified": "2023-01-01T00:00:00Z"
     }