return x.sin() + y.sin();
   }
   """



module = load_inline(name='inline_extension',
   ...                      cpp_sources=[source],
   ...                      functions=['sin_add'])



Note:
 By default, the Ninja backend uses #CPUS + 2 workers to build the
 extension. This may use up too many resources on some systems.
 One can control the number of workers by setting the *MAX_JOBS*
 environment variable to a non-negative number.

torch.utils.cpp_extension.include_paths(cuda=False)
Get the include paths required to build a C++ or CUDA extension.
Parameters:
      cuda (bool) -- If True, includes CUDA-specific include
      paths.
Returns:
      A list of include path strings.
Return type:
      List[str]
torch.utils.cpp_extension.get_compiler_abi_compatibility_and_version(compiler)
Determine if the given compiler is ABI-compatible with PyTorch
   alongside its version.
Parameters: