c10/macros/Export.h - platform/external/pytorch - Git at Google

 #ifndef C10_MACROS_EXPORT_H_
 #define C10_MACROS_EXPORT_H_

 /* Header file to define the common scaffolding for exported symbols.
  *
  * Export is by itself a quite tricky situation to deal with, and if you are
  * hitting this file, make sure you start with the background here:
  * - Linux: https://gcc.gnu.org/wiki/Visibility
  * - Windows:
  * https://docs.microsoft.com/en-us/cpp/cpp/dllexport-dllimport?view=vs-2017
  *
  * Do NOT include this file directly. Instead, use c10/macros/Macros.h
  */

 // You do not need to edit this part of file unless you are changing the core
 // pytorch export abstractions.
 //
 // This part defines the C10 core export and import macros. This is controlled
 // by whether we are building shared libraries or not, which is determined
 // during build time and codified in c10/core/cmake_macros.h.
 // When the library is built as a shared lib, EXPORT and IMPORT will contain
 // visibility attributes. If it is being built as a static lib, then EXPORT
 // and IMPORT basically have no effect.

 // As a rule of thumb, you should almost NEVER mix static and shared builds for
 // libraries that depend on c10. AKA, if c10 is built as a static library, we
 // recommend everything dependent on c10 to be built statically. If c10 is built
 // as a shared library, everything dependent on it should be built as shared. In
 // the PyTorch project, all native libraries shall use the macro
 // C10_BUILD_SHARED_LIB to check whether pytorch is building shared or static
 // libraries.

 // For build systems that do not directly depend on CMake and directly build
 // from the source directory (such as Buck), one may not have a cmake_macros.h
 // file at all. In this case, the build system is responsible for providing
 // correct macro definitions corresponding to the cmake_macros.h.in file.
 //
 // In such scenarios, one should define the macro
 //     C10_USING_CUSTOM_GENERATED_MACROS
 // to inform this header that it does not need to include the cmake_macros.h
 // file.

 #ifndef C10_USING_CUSTOM_GENERATED_MACROS
 #include <c10/macros/cmake_macros.h>
 #endif // C10_USING_CUSTOM_GENERATED_MACROS

 #ifdef _WIN32
 #define C10_HIDDEN
 #if defined(C10_BUILD_SHARED_LIBS)
 #define C10_EXPORT __declspec(dllexport)
 #define C10_IMPORT __declspec(dllimport)
 #else
 #define C10_EXPORT
 #define C10_IMPORT
 #endif
 #else // _WIN32
 #if defined(__GNUC__)
 #define C10_EXPORT __attribute__((__visibility__("default")))
 #define C10_HIDDEN __attribute__((__visibility__("hidden")))
 #else // defined(__GNUC__)
 #define C10_EXPORT
 #define C10_HIDDEN
 #endif // defined(__GNUC__)
 #define C10_IMPORT C10_EXPORT
 #endif // _WIN32

 #ifdef NO_EXPORT
 #undef C10_EXPORT
 #define C10_EXPORT
 #endif

 // Definition of an adaptive XX_API macro, that depends on whether you are
 // building the library itself or not, routes to XX_EXPORT and XX_IMPORT.
 // Basically, you will need to do this for each shared library that you are
 // building, and the instruction is as follows: assuming that you are building
 // a library called libawesome.so. You should:
 // (1) for your cmake target (usually done by "add_library(awesome, ...)"),
 //     define a macro called AWESOME_BUILD_MAIN_LIB using
 //     target_compile_options.
 // (2) define the AWESOME_API macro similar to the one below.
 // And in the source file of your awesome library, use AWESOME_API to
 // annotate public symbols.

 // Here, for the C10 library, we will define the macro C10_API for both import
 // and export.

 // This one is being used by libc10.so
 #ifdef C10_BUILD_MAIN_LIB
 #define C10_API C10_EXPORT
 #else
 #define C10_API C10_IMPORT
 #endif

 // This one is being used by libtorch.so
 #ifdef CAFFE2_BUILD_MAIN_LIB
 #define TORCH_API C10_EXPORT
 #else
 #define TORCH_API C10_IMPORT
 #endif

 // You may be wondering: Whose brilliant idea was it to split torch_cuda into
 // two pieces with confusing names?
 // Once upon a time, there _was_ only TORCH_CUDA_API. All was happy until we
 // tried to compile PyTorch for CUDA 11.1, which ran into relocation marker
 // issues when linking big binaries.
 // (https://github.com/pytorch/pytorch/issues/39968) We had two choices:
 //    (1) Stop supporting so many GPU architectures
 //    (2) Do something else
 // We chose #2 and decided to split the behemoth that was torch_cuda into two
 // smaller libraries, one with most of the core kernel functions (torch_cuda_cu)
 // and the other that had..well..everything else (torch_cuda_cpp). The idea was
 // this: instead of linking our static libraries (like the hefty
 // libcudnn_static.a) with another huge library, torch_cuda, and run into pesky
 // relocation marker issues, we could link our static libraries to a smaller
 // part of torch_cuda (torch_cuda_cpp) and avoid the issues.

 // libtorch_cuda_cu.so
 #ifdef TORCH_CUDA_CU_BUILD_MAIN_LIB
 #define TORCH_CUDA_CU_API C10_EXPORT
 #elif defined(BUILD_SPLIT_CUDA)
 #define TORCH_CUDA_CU_API C10_IMPORT
 #endif

 // libtorch_cuda_cpp.so
 #ifdef TORCH_CUDA_CPP_BUILD_MAIN_LIB
 #define TORCH_CUDA_CPP_API C10_EXPORT
 #elif defined(BUILD_SPLIT_CUDA)
 #define TORCH_CUDA_CPP_API C10_IMPORT
 #endif

 // libtorch_cuda.so (where torch_cuda_cu and torch_cuda_cpp are a part of the
 // same api)
 #ifdef TORCH_CUDA_BUILD_MAIN_LIB
 #define TORCH_CUDA_CPP_API C10_EXPORT
 #define TORCH_CUDA_CU_API C10_EXPORT
 #elif !defined(BUILD_SPLIT_CUDA)
 #define TORCH_CUDA_CPP_API C10_IMPORT
 #define TORCH_CUDA_CU_API C10_IMPORT
 #endif

 #if defined(TORCH_HIP_BUILD_MAIN_LIB)
 #define TORCH_HIP_API C10_EXPORT
 #else
 #define TORCH_HIP_API C10_IMPORT
 #endif

 #if defined(TORCH_XPU_BUILD_MAIN_LIB)
 #define TORCH_XPU_API C10_EXPORT
 #else
 #define TORCH_XPU_API C10_IMPORT
 #endif

 // Enums only need to be exported on windows for non-CUDA files
 #if defined(_WIN32) && defined(__CUDACC__)
 #define C10_API_ENUM C10_API
 #else
 #define C10_API_ENUM
 #endif

 #endif // C10_MACROS_MACROS_H_
	#ifndef C10_MACROS_EXPORT_H_
	#define C10_MACROS_EXPORT_H_

	/* Header file to define the common scaffolding for exported symbols.
	*
	* Export is by itself a quite tricky situation to deal with, and if you are
	* hitting this file, make sure you start with the background here:
	* - Linux: https://gcc.gnu.org/wiki/Visibility
	* - Windows:
	* https://docs.microsoft.com/en-us/cpp/cpp/dllexport-dllimport?view=vs-2017
	*
	* Do NOT include this file directly. Instead, use c10/macros/Macros.h
	*/

	// You do not need to edit this part of file unless you are changing the core
	// pytorch export abstractions.
	//
	// This part defines the C10 core export and import macros. This is controlled
	// by whether we are building shared libraries or not, which is determined
	// during build time and codified in c10/core/cmake_macros.h.
	// When the library is built as a shared lib, EXPORT and IMPORT will contain
	// visibility attributes. If it is being built as a static lib, then EXPORT
	// and IMPORT basically have no effect.

	// As a rule of thumb, you should almost NEVER mix static and shared builds for
	// libraries that depend on c10. AKA, if c10 is built as a static library, we
	// recommend everything dependent on c10 to be built statically. If c10 is built
	// as a shared library, everything dependent on it should be built as shared. In
	// the PyTorch project, all native libraries shall use the macro
	// C10_BUILD_SHARED_LIB to check whether pytorch is building shared or static
	// libraries.

	// For build systems that do not directly depend on CMake and directly build
	// from the source directory (such as Buck), one may not have a cmake_macros.h
	// file at all. In this case, the build system is responsible for providing
	// correct macro definitions corresponding to the cmake_macros.h.in file.
	//
	// In such scenarios, one should define the macro
	// C10_USING_CUSTOM_GENERATED_MACROS
	// to inform this header that it does not need to include the cmake_macros.h
	// file.

	#ifndef C10_USING_CUSTOM_GENERATED_MACROS
	#include <c10/macros/cmake_macros.h>
	#endif // C10_USING_CUSTOM_GENERATED_MACROS

	#ifdef _WIN32
	#define C10_HIDDEN
	#if defined(C10_BUILD_SHARED_LIBS)
	#define C10_EXPORT __declspec(dllexport)
	#define C10_IMPORT __declspec(dllimport)
	#else
	#define C10_EXPORT
	#define C10_IMPORT
	#endif
	#else // _WIN32
	#if defined(__GNUC__)
	#define C10_EXPORT __attribute__((__visibility__("default")))
	#define C10_HIDDEN __attribute__((__visibility__("hidden")))
	#else // defined(__GNUC__)
	#define C10_EXPORT
	#define C10_HIDDEN
	#endif // defined(__GNUC__)
	#define C10_IMPORT C10_EXPORT
	#endif // _WIN32

	#ifdef NO_EXPORT
	#undef C10_EXPORT
	#define C10_EXPORT
	#endif

	// Definition of an adaptive XX_API macro, that depends on whether you are
	// building the library itself or not, routes to XX_EXPORT and XX_IMPORT.
	// Basically, you will need to do this for each shared library that you are
	// building, and the instruction is as follows: assuming that you are building
	// a library called libawesome.so. You should:
	// (1) for your cmake target (usually done by "add_library(awesome, ...)"),
	// define a macro called AWESOME_BUILD_MAIN_LIB using
	// target_compile_options.
	// (2) define the AWESOME_API macro similar to the one below.
	// And in the source file of your awesome library, use AWESOME_API to
	// annotate public symbols.

	// Here, for the C10 library, we will define the macro C10_API for both import
	// and export.

	// This one is being used by libc10.so
	#ifdef C10_BUILD_MAIN_LIB
	#define C10_API C10_EXPORT
	#else
	#define C10_API C10_IMPORT
	#endif

	// This one is being used by libtorch.so
	#ifdef CAFFE2_BUILD_MAIN_LIB
	#define TORCH_API C10_EXPORT
	#else
	#define TORCH_API C10_IMPORT
	#endif

	// You may be wondering: Whose brilliant idea was it to split torch_cuda into
	// two pieces with confusing names?
	// Once upon a time, there _was_ only TORCH_CUDA_API. All was happy until we
	// tried to compile PyTorch for CUDA 11.1, which ran into relocation marker
	// issues when linking big binaries.
	// (https://github.com/pytorch/pytorch/issues/39968) We had two choices:
	// (1) Stop supporting so many GPU architectures
	// (2) Do something else
	// We chose #2 and decided to split the behemoth that was torch_cuda into two
	// smaller libraries, one with most of the core kernel functions (torch_cuda_cu)
	// and the other that had..well..everything else (torch_cuda_cpp). The idea was
	// this: instead of linking our static libraries (like the hefty
	// libcudnn_static.a) with another huge library, torch_cuda, and run into pesky
	// relocation marker issues, we could link our static libraries to a smaller
	// part of torch_cuda (torch_cuda_cpp) and avoid the issues.

	// libtorch_cuda_cu.so
	#ifdef TORCH_CUDA_CU_BUILD_MAIN_LIB
	#define TORCH_CUDA_CU_API C10_EXPORT
	#elif defined(BUILD_SPLIT_CUDA)
	#define TORCH_CUDA_CU_API C10_IMPORT
	#endif

	// libtorch_cuda_cpp.so
	#ifdef TORCH_CUDA_CPP_BUILD_MAIN_LIB
	#define TORCH_CUDA_CPP_API C10_EXPORT
	#elif defined(BUILD_SPLIT_CUDA)
	#define TORCH_CUDA_CPP_API C10_IMPORT
	#endif

	// libtorch_cuda.so (where torch_cuda_cu and torch_cuda_cpp are a part of the
	// same api)
	#ifdef TORCH_CUDA_BUILD_MAIN_LIB
	#define TORCH_CUDA_CPP_API C10_EXPORT
	#define TORCH_CUDA_CU_API C10_EXPORT
	#elif !defined(BUILD_SPLIT_CUDA)
	#define TORCH_CUDA_CPP_API C10_IMPORT
	#define TORCH_CUDA_CU_API C10_IMPORT
	#endif

	#if defined(TORCH_HIP_BUILD_MAIN_LIB)
	#define TORCH_HIP_API C10_EXPORT
	#else
	#define TORCH_HIP_API C10_IMPORT
	#endif

	#if defined(TORCH_XPU_BUILD_MAIN_LIB)
	#define TORCH_XPU_API C10_EXPORT
	#else
	#define TORCH_XPU_API C10_IMPORT
	#endif

	// Enums only need to be exported on windows for non-CUDA files
	#if defined(_WIN32) && defined(__CUDACC__)
	#define C10_API_ENUM C10_API
	#else
	#define C10_API_ENUM
	#endif

	#endif // C10_MACROS_MACROS_H_