forked from pytorch/pytorch
-
Notifications
You must be signed in to change notification settings - Fork 0
/
BinaryInternal.h
44 lines (39 loc) · 1.16 KB
/
BinaryInternal.h
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
// DON'T include this except from Binary*.cu files. It should not leak into
// headers.
#pragma once
#define TORCH_ASSERT_NO_OPERATORS
#include <ATen/AccumulateType.h>
#include <ATen/Dispatch.h>
#include <ATen/native/BinaryOps.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/TensorIterator.h>
#include <c10/cuda/CUDAGuard.h>
#include <c10/cuda/CUDAMathCompat.h>
#include <c10/util/TypeSafeSignMath.h>
#include <ATen/native/cuda/JitLoops.cuh>
#include <ATen/native/cuda/Loops.cuh>
#include <type_traits>
namespace at::native::binary_internal {
template <typename scalar_t>
struct DivFunctor {
__device__ scalar_t operator()(scalar_t a, scalar_t b) const {
return a / b;
}
};
template <typename T>
struct MulFunctor {
__device__ T operator()(T a, T b) const {
return a * b;
}
};
// Workaround for the error: '*' in boolean context, suggest '&&' instead
// [-Werror=int-in-bool-context]
template <>
struct MulFunctor<bool> {
__device__ bool operator()(bool a, bool b) const {
return a && b;
}
};
void div_true_kernel_cuda(TensorIteratorBase& iter);
void div_trunc_kernel_cuda(TensorIteratorBase& iter);
} // namespace at::native::binary_internal