mirror of
https://github.com/zebrajr/pytorch.git
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1249d490de
Summary: Introduces additional ways of handling CUDA errors that allow automated linters to detect if errors are being handled. Pull Request resolved: https://github.com/pytorch/pytorch/pull/74865 Test Plan: Sandcastle Reviewed By: ngimel Differential Revision: D35194530 fbshipit-source-id: f4fe61594edbfd81e97a4b605935961b893df167 (cherry picked from commit 919ddf677c5b9b46c5e493ed64346a5f2527bf08)
90 lines
4.1 KiB
C++
90 lines
4.1 KiB
C++
#pragma once
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#include <c10/cuda/CUDAMacros.h>
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#include <c10/cuda/CUDAMiscFunctions.h>
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#include <c10/macros/Macros.h>
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#include <c10/util/Exception.h>
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#include <cuda.h>
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// Note [CHECK macro]
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// ~~~~~~~~~~~~~~~~~~
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// This is a macro so that AT_ERROR can get accurate __LINE__
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// and __FILE__ information. We could split this into a short
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// macro and a function implementation if we pass along __LINE__
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// and __FILE__, but no one has found this worth doing.
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// Used to denote errors from CUDA framework.
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// This needs to be declared here instead util/Exception.h for proper conversion
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// during hipify.
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namespace c10 {
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class C10_CUDA_API CUDAError : public c10::Error {
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using Error::Error;
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};
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} // namespace c10
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// For CUDA Runtime API
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#ifdef STRIP_ERROR_MESSAGES
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#define C10_CUDA_CHECK(EXPR) \
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do { \
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cudaError_t __err = EXPR; \
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if (__err != cudaSuccess) { \
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throw c10::CUDAError( \
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{__func__, __FILE__, static_cast<uint32_t>(__LINE__)}, \
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TORCH_CHECK_MSG(false, "")); \
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} \
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} while (0)
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#else
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#define C10_CUDA_CHECK(EXPR) \
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do { \
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cudaError_t __err = EXPR; \
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if (__err != cudaSuccess) { \
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auto error_unused C10_UNUSED = cudaGetLastError(); \
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(void)error_unused; \
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auto _cuda_check_suffix = c10::cuda::get_cuda_check_suffix(); \
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throw c10::CUDAError( \
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{__func__, __FILE__, static_cast<uint32_t>(__LINE__)}, \
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TORCH_CHECK_MSG( \
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false, \
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"", \
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"CUDA error: ", \
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cudaGetErrorString(__err), \
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_cuda_check_suffix)); \
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} \
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} while (0)
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#endif
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#define C10_CUDA_CHECK_WARN(EXPR) \
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do { \
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cudaError_t __err = EXPR; \
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if (__err != cudaSuccess) { \
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auto error_unused C10_UNUSED = cudaGetLastError(); \
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(void)error_unused; \
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TORCH_WARN("CUDA warning: ", cudaGetErrorString(__err)); \
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} \
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} while (0)
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// Indicates that a CUDA error is handled in a non-standard way
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#define C10_CUDA_ERROR_HANDLED(EXPR) EXPR
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// Intentionally ignore a CUDA error
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#define C10_CUDA_IGNORE_ERROR(EXPR) \
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do { \
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cudaError_t __err = EXPR; \
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if (__err != cudaSuccess) { \
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cudaError_t error_unused C10_UNUSED = cudaGetLastError(); \
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(void)error_unused; \
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} \
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} while (0)
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// Clear the last CUDA error
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#define C10_CUDA_CLEAR_ERROR() \
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do { \
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cudaError_t error_unused C10_UNUSED = cudaGetLastError(); \
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(void)error_unused; \
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} while (0)
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// This should be used directly after every kernel launch to ensure
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// the launch happened correctly and provide an early, close-to-source
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// diagnostic if it didn't.
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#define C10_CUDA_KERNEL_LAUNCH_CHECK() C10_CUDA_CHECK(cudaGetLastError())
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