ai-content-maker/.venv/Lib/site-packages/torch/include/c10/cuda/CUDAException.h

101 lines
4.4 KiB
C++

#pragma once
#include <c10/cuda/CUDADeviceAssertionHost.h>
#include <c10/cuda/CUDAMacros.h>
#include <c10/cuda/CUDAMiscFunctions.h>
#include <c10/macros/Macros.h>
#include <c10/util/Exception.h>
#include <c10/util/irange.h>
#include <cuda.h>
// Note [CHECK macro]
// ~~~~~~~~~~~~~~~~~~
// This is a macro so that AT_ERROR can get accurate __LINE__
// and __FILE__ information. We could split this into a short
// macro and a function implementation if we pass along __LINE__
// and __FILE__, but no one has found this worth doing.
// Used to denote errors from CUDA framework.
// This needs to be declared here instead util/Exception.h for proper conversion
// during hipify.
namespace c10 {
class C10_CUDA_API CUDAError : public c10::Error {
using Error::Error;
};
} // namespace c10
#define C10_CUDA_CHECK(EXPR) \
do { \
const cudaError_t __err = EXPR; \
c10::cuda::c10_cuda_check_implementation( \
static_cast<int32_t>(__err), \
__FILE__, \
__func__, /* Line number data type not well-defined between \
compilers, so we perform an explicit cast */ \
static_cast<uint32_t>(__LINE__), \
true); \
} while (0)
#define C10_CUDA_CHECK_WARN(EXPR) \
do { \
const cudaError_t __err = EXPR; \
if (C10_UNLIKELY(__err != cudaSuccess)) { \
auto error_unused C10_UNUSED = cudaGetLastError(); \
(void)error_unused; \
TORCH_WARN("CUDA warning: ", cudaGetErrorString(__err)); \
} \
} while (0)
// Indicates that a CUDA error is handled in a non-standard way
#define C10_CUDA_ERROR_HANDLED(EXPR) EXPR
// Intentionally ignore a CUDA error
#define C10_CUDA_IGNORE_ERROR(EXPR) \
do { \
const cudaError_t __err = EXPR; \
if (C10_UNLIKELY(__err != cudaSuccess)) { \
cudaError_t error_unused C10_UNUSED = cudaGetLastError(); \
(void)error_unused; \
} \
} while (0)
// Clear the last CUDA error
#define C10_CUDA_CLEAR_ERROR() \
do { \
cudaError_t error_unused C10_UNUSED = cudaGetLastError(); \
(void)error_unused; \
} while (0)
// This should be used directly after every kernel launch to ensure
// the launch happened correctly and provide an early, close-to-source
// diagnostic if it didn't.
#define C10_CUDA_KERNEL_LAUNCH_CHECK() C10_CUDA_CHECK(cudaGetLastError())
/// Launches a CUDA kernel appending to it all the information need to handle
/// device-side assertion failures. Checks that the launch was successful.
#define TORCH_DSA_KERNEL_LAUNCH( \
kernel, blocks, threads, shared_mem, stream, ...) \
do { \
auto& launch_registry = \
c10::cuda::CUDAKernelLaunchRegistry::get_singleton_ref(); \
kernel<<<blocks, threads, shared_mem, stream>>>( \
__VA_ARGS__, \
launch_registry.get_uvm_assertions_ptr_for_current_device(), \
launch_registry.insert( \
__FILE__, __FUNCTION__, __LINE__, #kernel, stream.id())); \
C10_CUDA_KERNEL_LAUNCH_CHECK(); \
} while (0)
namespace c10::cuda {
/// In the event of a CUDA failure, formats a nice error message about that
/// failure and also checks for device-side assertion failures
C10_CUDA_API void c10_cuda_check_implementation(
const int32_t err,
const char* filename,
const char* function_name,
const int line_number,
const bool include_device_assertions);
} // namespace c10::cuda