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BinaryRemainderKernel.cu
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BinaryRemainderKernel.cu
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#include <ATen/Dispatch.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/cuda/Loops.cuh>
#include <ATen/native/BinaryOps.h>
#include <ATen/native/TensorIterator.h>
#include <type_traits>
// NOTE: CUDA on Windows requires that the enclosing function
// of a __device__ lambda not have internal linkage.
namespace at { namespace native {
void remainder_kernel_cuda(TensorIterator& iter) {
if (isIntegralType(iter.dtype(), /*includeBool*/ false)) {
AT_DISPATCH_INTEGRAL_TYPES(iter.dtype(), "remainder_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
scalar_t r = a % b;
if (!std::is_unsigned<scalar_t>::value && (r != 0) && ((r < 0) != (b < 0))) {
r += b;
}
return r;
});
});
} else {
AT_DISPATCH_FLOATING_TYPES_AND2(kHalf, kBFloat16, iter.dtype(), "remainder_cuda", [&]() {
gpu_kernel_with_scalars(iter,
[]GPU_LAMBDA(scalar_t a, scalar_t b) __ubsan_ignore_float_divide_by_zero__ -> scalar_t {
auto mod = ::fmod(a, b);
if (!std::is_unsigned<scalar_t>::value && (mod != 0) && ((b < 0) != (mod < 0))) {
mod += b;
}
return mod;
});
});
}
}
void fmod_kernel_cuda(TensorIterator& iter) {
// Use the dtype of the first argument to retain BC,
// change to common_dtype for type promotion in the future
// Issue #47779: https://github.com/pytorch/pytorch/issues/47779
if (isIntegralType(iter.dtype(), /*includeBool*/ false)) {
AT_DISPATCH_INTEGRAL_TYPES(iter.dtype(), "fmod_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
return a % b;
});
});
} else {
AT_DISPATCH_FLOATING_TYPES_AND(kHalf, iter.dtype(), "fmod_cuda", [&]() {
gpu_kernel_with_scalars(iter,
[]GPU_LAMBDA(scalar_t a, scalar_t b) __ubsan_ignore_float_divide_by_zero__ -> scalar_t {
return ::fmod(a, b);
});
});
}
}
REGISTER_DISPATCH(remainder_stub, &remainder_kernel_cuda);
REGISTER_DISPATCH(fmod_stub, &fmod_kernel_cuda);
}} // namespace at::native