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BinaryLogicalOpsKernels.cu
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BinaryLogicalOpsKernels.cu
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#define TORCH_ASSERT_NO_OPERATORS
#include <ATen/Dispatch.h>
#include <ATen/native/DispatchStub.h>
#include <ATen/native/cuda/Loops.cuh>
#include <ATen/native/cuda/JitLoops.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::native {
CONSTEXPR_EXCEPT_WIN_CUDA char logical_and_name[] = "logical_and_kernel";
void logical_and_kernel_cuda(TensorIterator& iter) {
auto dtype = iter.common_dtype();
if (at::isComplexType(dtype)) {
#if AT_USE_JITERATOR()
static const auto logical_and_string = jiterator_stringify(
template <typename T>
bool logical_and_kernel(T a, T b) {
return a && b;
}
); // logical_and_string
AT_DISPATCH_COMPLEX_TYPES(dtype, "logical_and_cuda", [&]() {
jitted_gpu_kernel<
/*name=*/ logical_and_name,
/*return_dtype=*/ scalar_t,
/*common_dtype=*/ scalar_t,
/*arity=*/ 2>(iter, logical_and_string);
}); // logical_and_string
#else
AT_DISPATCH_COMPLEX_TYPES(dtype, "logical_and_cuda", [&]() {
opmath_symmetric_gpu_kernel_with_scalars<scalar_t, bool>(
iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> bool {
return a && b;
});
});
#endif
} else {
AT_DISPATCH_ALL_TYPES_AND3(kHalf, kBool, ScalarType::BFloat16,
dtype, "logical_and_cuda", [&]() {
opmath_symmetric_gpu_kernel_with_scalars<scalar_t, bool>(
iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> bool {
return a && b;
});
});
}
}
CONSTEXPR_EXCEPT_WIN_CUDA char logical_or_name[] = "logical_or_kernel";
void logical_or_kernel_cuda(TensorIterator& iter) {
auto dtype = iter.common_dtype();
if (at::isComplexType(dtype)) {
#if AT_USE_JITERATOR()
static const auto logical_or_string = jiterator_stringify(
template <typename T>
bool logical_or_kernel(T a, T b) {
return a || b;
}
); // logical_or_string
AT_DISPATCH_COMPLEX_TYPES(dtype, "logical_or_cuda", [&]() {
jitted_gpu_kernel<
/*name=*/ logical_or_name,
/*return_dtype=*/ scalar_t,
/*common_dtype=*/ scalar_t,
/*arity=*/ 2>(iter, logical_or_string);
});
#else
AT_DISPATCH_COMPLEX_TYPES(dtype, "logical_or_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> bool {
return a || b;
});
});
#endif
} else {
AT_DISPATCH_ALL_TYPES_AND3(kHalf, kBool, ScalarType::BFloat16,
dtype, "logical_or_cuda", [&]() {
opmath_symmetric_gpu_kernel_with_scalars<scalar_t, bool>(
iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> bool {
return a || b;
});
});
}
}
CONSTEXPR_EXCEPT_WIN_CUDA char logical_xor_name[] = "logical_xor_kernel";
void logical_xor_kernel_cuda(TensorIterator& iter) {
auto dtype = iter.common_dtype();
if (at::isComplexType(dtype)) {
#if AT_USE_JITERATOR()
static const auto logical_xor_string = jiterator_stringify(
template <typename T>
bool logical_xor_kernel(T a, T b) {
return bool(a) != bool(b);
}
);
AT_DISPATCH_COMPLEX_TYPES(dtype, "logical_xor_cuda", [&]() {
jitted_gpu_kernel<
/*name=*/ logical_xor_name,
/*return_dtype=*/ scalar_t,
/*common_dtype=*/ scalar_t,
/*arity=*/ 2>(iter, logical_xor_string);
}); // logical_xor_string
#else
AT_DISPATCH_COMPLEX_TYPES(dtype, "logical_xor_cuda", [&]() {
gpu_kernel_with_scalars(iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> bool {
return bool(a) != bool(b);
});
});
#endif
} else {
AT_DISPATCH_ALL_TYPES_AND3(kHalf, kBool, ScalarType::BFloat16,
dtype, "logical_xor_cuda", [&]() {
opmath_symmetric_gpu_kernel_with_scalars<scalar_t, bool>(
iter, []GPU_LAMBDA(scalar_t a, scalar_t b) -> bool {
return bool(a) != bool(b);
});
});
}
}
REGISTER_DISPATCH(logical_and_stub, &logical_and_kernel_cuda);
REGISTER_DISPATCH(logical_or_stub, &logical_or_kernel_cuda);
REGISTER_DISPATCH(logical_xor_stub, &logical_xor_kernel_cuda);
} // namespace at::native