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BinaryMiscOpsKernels.cu
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BinaryMiscOpsKernels.cu
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#include <ATen/Dispatch.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/cuda/Loops.cuh>
#include <ATen/native/cuda/Math.cuh>
#include <ATen/native/TensorIterator.h>
#include <ATen/native/BinaryOps.h>
// NOTE: CUDA on Windows requires that the enclosing function
// of a __device__ lambda not have internal linkage.
namespace at { namespace native {
void atan2_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES_AND_HALF(iter.common_dtype(), "atan2_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
return ::atan2(a, b);
});
});
}
void smooth_l1_kernel_cuda(TensorIterator& iter, double beta) {
AT_DISPATCH_FLOATING_TYPES_AND_HALF(iter.dtype(), "smooth_l1_cuda", [&iter, beta]() {
scalar_t beta_val(beta);
gpu_kernel(iter, [beta_val] GPU_LAMBDA (scalar_t a, scalar_t b) -> scalar_t {
auto z = ::abs(a - b);
return z < beta_val ? scalar_t(0.5) * z * z / beta_val : z - scalar_t(0.5) * beta_val;
});
});
}
void mse_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES_AND2(at::ScalarType::Half, at::ScalarType::BFloat16, iter.dtype(), "mse_cuda", [&]() {
gpu_kernel(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
auto diff = a - b;
return diff * diff;
});
});
}
void logaddexp_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES(iter.dtype(), "logaddexp_cuda", [&]() {
gpu_kernel(iter, [] GPU_LAMBDA (scalar_t a, scalar_t b) -> scalar_t {
if (::isinf(a) && a == b) {
return a;
}
else {
scalar_t m = ::max(a, b);
return m + ::log((scalar_t)(1.0) + ::exp(-::abs(a - b)));
}
});
});
}
void logaddexp2_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES(iter.dtype(), "logaddexp2_cuda", [&]() {
gpu_kernel(iter, [] GPU_LAMBDA (scalar_t a, scalar_t b) -> scalar_t {
if (::isinf(a) && a == b) {
return a;
}
else {
scalar_t m = ::max(a, b);
return m + ::log2((scalar_t)(1.0) + ::pow((scalar_t)(2.0), -::abs(a - b)));
}
});
});
}
void gcd_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_INTEGRAL_TYPES(iter.dtype(), "gcd_cuda", [&]() {
gpu_kernel(iter, [] GPU_LAMBDA (scalar_t a, scalar_t b) -> scalar_t {
return calc_gcd(a, b);
});
});
}
void lcm_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_INTEGRAL_TYPES(iter.dtype(), "lcm_cuda", [&]() {
gpu_kernel(iter, [] GPU_LAMBDA (scalar_t a, scalar_t b) -> scalar_t {
scalar_t g = calc_gcd(a, b);
return (g == 0) ? 0 : ::abs(a / g * b);
});
});
}
void hypot_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES_AND_HALF(iter.common_dtype(), "hypot_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
return ::hypot(a, b);
});
});
}
void nextafter_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_FLOATING_TYPES(iter.common_dtype(), "nextafter_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
return ::nextafter(a, b);
});
});
}
void heaviside_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_ALL_TYPES_AND3(kHalf, kBool, kBFloat16, iter.dtype(), "heaviside_cuda", [&]() {
gpu_kernel(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
return a == 0 ? b : static_cast<scalar_t>(a > 0);
});
});
}
void copysign_kernel_cuda(TensorIterator& iter) {
AT_DISPATCH_ALL_TYPES_AND3(kHalf, kBool, kBFloat16, iter.dtype(), "copysign_cuda", [&]() {
gpu_kernel(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> scalar_t {
return ::copysign(a, b);
});
});
}
REGISTER_DISPATCH(atan2_stub, &atan2_kernel_cuda);
REGISTER_DISPATCH(smooth_l1_stub, &smooth_l1_kernel_cuda);
REGISTER_DISPATCH(mse_stub, &mse_kernel_cuda);
REGISTER_DISPATCH(logaddexp_stub, &logaddexp_kernel_cuda);
REGISTER_DISPATCH(logaddexp2_stub, &logaddexp2_kernel_cuda);
REGISTER_DISPATCH(gcd_stub, &gcd_kernel_cuda);
REGISTER_DISPATCH(lcm_stub, &lcm_kernel_cuda);
REGISTER_DISPATCH(hypot_stub, &hypot_kernel_cuda);
REGISTER_DISPATCH(nextafter_stub, &nextafter_kernel_cuda);
REGISTER_DISPATCH(heaviside_stub, &heaviside_kernel_cuda);
REGISTER_DISPATCH(copysign_stub, ©sign_kernel_cuda);
}} // namespace at::native