#pragma once // @generated by torchgen/gen.py from Function.h #include #include #include #include #include #include #include #include #include #include #include #include #include namespace at { // aten::linear_backward(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask) -> (Tensor, Tensor, Tensor) inline ::std::tuple linear_backward(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { return at::_ops::linear_backward::call(self, grad_output, weight, output_mask); } // aten::linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) inline ::std::tuple linear_backward_out(at::Tensor & out0, at::Tensor & out1, at::Tensor & out2, const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask) { return at::_ops::linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); } // aten::linear_backward.out(Tensor self, Tensor grad_output, Tensor weight, bool[3] output_mask, *, Tensor(a!) out0, Tensor(b!) out1, Tensor(c!) out2) -> (Tensor(a!), Tensor(b!), Tensor(c!)) inline ::std::tuple linear_backward_outf(const at::Tensor & self, const at::Tensor & grad_output, const at::Tensor & weight, ::std::array output_mask, at::Tensor & out0, at::Tensor & out1, at::Tensor & out2) { return at::_ops::linear_backward_out::call(self, grad_output, weight, output_mask, out0, out1, out2); } }