ai-content-maker/.venv/Lib/site-packages/torch/include/ATen/cuda/DeviceUtils.cuh

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#pragma once
#include <cuda.h>
#include <c10/util/complex.h>
#include <c10/util/Half.h>
__device__ __forceinline__ unsigned int ACTIVE_MASK()
{
#if !defined(USE_ROCM)
return __activemask();
#else
// will be ignored anyway
return 0xffffffff;
#endif
}
__device__ __forceinline__ void WARP_SYNC(unsigned mask = 0xffffffff) {
#if !defined(USE_ROCM)
return __syncwarp(mask);
#endif
}
#if defined(USE_ROCM)
__device__ __forceinline__ unsigned long long int WARP_BALLOT(int predicate)
{
return __ballot(predicate);
}
#else
__device__ __forceinline__ unsigned int WARP_BALLOT(int predicate, unsigned int mask = 0xffffffff)
{
#if !defined(USE_ROCM)
return __ballot_sync(mask, predicate);
#else
return __ballot(predicate);
#endif
}
#endif
template <typename T>
__device__ __forceinline__ T WARP_SHFL_XOR(T value, int laneMask, int width = warpSize, unsigned int mask = 0xffffffff)
{
#if !defined(USE_ROCM)
return __shfl_xor_sync(mask, value, laneMask, width);
#else
return __shfl_xor(value, laneMask, width);
#endif
}
template <typename T>
__device__ __forceinline__ T WARP_SHFL(T value, int srcLane, int width = warpSize, unsigned int mask = 0xffffffff)
{
#if !defined(USE_ROCM)
return __shfl_sync(mask, value, srcLane, width);
#else
return __shfl(value, srcLane, width);
#endif
}
template <typename T>
__device__ __forceinline__ T WARP_SHFL_UP(T value, unsigned int delta, int width = warpSize, unsigned int mask = 0xffffffff)
{
#if !defined(USE_ROCM)
return __shfl_up_sync(mask, value, delta, width);
#else
return __shfl_up(value, delta, width);
#endif
}
template <typename T>
__device__ __forceinline__ T WARP_SHFL_DOWN(T value, unsigned int delta, int width = warpSize, unsigned int mask = 0xffffffff)
{
#if !defined(USE_ROCM)
return __shfl_down_sync(mask, value, delta, width);
#else
return __shfl_down(value, delta, width);
#endif
}
#if defined(USE_ROCM)
template<>
__device__ __forceinline__ int64_t WARP_SHFL_DOWN<int64_t>(int64_t value, unsigned int delta, int width , unsigned int mask)
{
//(HIP doesn't support int64_t). Trick from https://devblogs.nvidia.com/faster-parallel-reductions-kepler/
int2 a = *reinterpret_cast<int2*>(&value);
a.x = __shfl_down(a.x, delta);
a.y = __shfl_down(a.y, delta);
return *reinterpret_cast<int64_t*>(&a);
}
#endif
template<>
__device__ __forceinline__ c10::Half WARP_SHFL_DOWN<c10::Half>(c10::Half value, unsigned int delta, int width, unsigned int mask)
{
return c10::Half(WARP_SHFL_DOWN<unsigned short>(value.x, delta, width, mask), c10::Half::from_bits_t{});
}
template <typename T>
__device__ __forceinline__ c10::complex<T> WARP_SHFL_DOWN(c10::complex<T> value, unsigned int delta, int width = warpSize, unsigned int mask = 0xffffffff)
{
#if !defined(USE_ROCM)
return c10::complex<T>(
__shfl_down_sync(mask, value.real_, delta, width),
__shfl_down_sync(mask, value.imag_, delta, width));
#else
return c10::complex<T>(
__shfl_down(value.real_, delta, width),
__shfl_down(value.imag_, delta, width));
#endif
}
/**
* For CC 3.5+, perform a load using __ldg
*/
template <typename T>
__device__ __forceinline__ T doLdg(const T* p) {
#if __CUDA_ARCH__ >= 350 && !defined(USE_ROCM)
return __ldg(p);
#else
return *p;
#endif
}