ai-content-maker/.venv/Lib/site-packages/torch/include/ATen/native/ReduceOps.h

57 lines
1.8 KiB
C++

#pragma once
#include <ATen/native/DispatchStub.h>
#include <c10/util/ArrayRef.h>
#include <c10/util/Optional.h>
namespace c10 {
class Scalar;
}
namespace at {
struct TensorIterator;
class Tensor;
}
namespace at::native {
using reduce_fn = void(*)(TensorIterator &);
DECLARE_DISPATCH(reduce_fn, sum_stub);
DECLARE_DISPATCH(reduce_fn, nansum_stub);
DECLARE_DISPATCH(reduce_fn, prod_stub);
DECLARE_DISPATCH(reduce_fn, mean_stub);
DECLARE_DISPATCH(reduce_fn, and_stub);
DECLARE_DISPATCH(reduce_fn, or_stub);
DECLARE_DISPATCH(reduce_fn, min_values_stub);
DECLARE_DISPATCH(reduce_fn, max_values_stub);
DECLARE_DISPATCH(reduce_fn, argmax_stub);
DECLARE_DISPATCH(reduce_fn, argmin_stub);
using reduce_std_var_function =
void (*)(TensorIterator&, double correction, bool take_sqrt);
DECLARE_DISPATCH(reduce_std_var_function, std_var_stub);
using reduce_norm_fn =
void (*)(Tensor&, const Tensor&, const c10::Scalar&, c10::optional<int64_t>);
DECLARE_DISPATCH(reduce_norm_fn, norm_kernel);
using reduce_fn_flag = void(*)(TensorIterator &, const c10::Scalar&);
DECLARE_DISPATCH(reduce_fn_flag, norm_stub);
using structured_cum_fn = void (*)(const Tensor&, const Tensor&, int64_t);
using cum_fn = void (*)(Tensor&, const Tensor&, int64_t);
DECLARE_DISPATCH(structured_cum_fn, cumsum_stub);
DECLARE_DISPATCH(structured_cum_fn, cumprod_stub);
DECLARE_DISPATCH(cum_fn, logcumsumexp_stub);
DECLARE_DISPATCH(void (*)(const Tensor&, int64_t, bool, Tensor&, Tensor&), aminmax_stub);
DECLARE_DISPATCH(void (*)(const Tensor&, Tensor&, Tensor&), aminmax_allreduce_stub);
// Used in cuda/Normalization.cu
TORCH_API std::tuple<Tensor&,Tensor&> var_mean_out(
Tensor &result1, Tensor &result2, const Tensor &self, IntArrayRef dim,
int64_t correction, bool keepdim);
} // namespace at::native