#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::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!) inline at::Tensor & hardtanh_backward_out(at::Tensor & grad_input, const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val) { return at::_ops::hardtanh_backward_grad_input::call(grad_output, self, min_val, max_val, grad_input); } // aten::hardtanh_backward.grad_input(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val, *, Tensor(a!) grad_input) -> Tensor(a!) inline at::Tensor & hardtanh_backward_outf(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val, at::Tensor & grad_input) { return at::_ops::hardtanh_backward_grad_input::call(grad_output, self, min_val, max_val, grad_input); } // aten::hardtanh_backward(Tensor grad_output, Tensor self, Scalar min_val, Scalar max_val) -> Tensor inline at::Tensor hardtanh_backward(const at::Tensor & grad_output, const at::Tensor & self, const at::Scalar & min_val, const at::Scalar & max_val) { return at::_ops::hardtanh_backward::call(grad_output, self, min_val, max_val); } }