1#pragma once
2
3// @generated by torchgen/gen.py from Function.h
4
5#include <ATen/Context.h>
6#include <ATen/DeviceGuard.h>
7#include <ATen/TensorUtils.h>
8#include <ATen/TracerMode.h>
9#include <ATen/core/Generator.h>
10#include <ATen/core/Reduction.h>
11#include <ATen/core/Tensor.h>
12#include <c10/core/Scalar.h>
13#include <c10/core/Storage.h>
14#include <c10/core/TensorOptions.h>
15#include <c10/util/Deprecated.h>
16#include <c10/util/Optional.h>
17
18
19
20#include <ATen/ops/binary_cross_entropy_backward_ops.h>
21
22namespace at {
23
24
25// aten::binary_cross_entropy_backward(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean) -> Tensor
26inline at::Tensor binary_cross_entropy_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean) {
27 return at::_ops::binary_cross_entropy_backward::call(grad_output, self, target, weight, reduction);
28}
29
30// aten::binary_cross_entropy_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!)
31inline at::Tensor & binary_cross_entropy_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight={}, int64_t reduction=at::Reduction::Mean) {
32 return at::_ops::binary_cross_entropy_backward_grad_input::call(grad_output, self, target, weight, reduction, grad_input);
33}
34// aten::binary_cross_entropy_backward.grad_input(Tensor grad_output, Tensor self, Tensor target, Tensor? weight=None, int reduction=Mean, *, Tensor(a!) grad_input) -> Tensor(a!)
35inline at::Tensor & binary_cross_entropy_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Tensor & target, const c10::optional<at::Tensor> & weight, int64_t reduction, at::Tensor & grad_input) {
36 return at::_ops::binary_cross_entropy_backward_grad_input::call(grad_output, self, target, weight, reduction, grad_input);
37}
38
39}
40