#pragma once

// @generated by torchgen/gen.py from Function.h

#include <ATen/Context.h>
#include <ATen/DeviceGuard.h>
#include <ATen/TensorUtils.h>
#include <ATen/TracerMode.h>
#include <ATen/core/Generator.h>
#include <ATen/core/Reduction.h>
#include <ATen/core/Tensor.h>
#include <c10/core/Scalar.h>
#include <c10/core/Storage.h>
#include <c10/core/TensorOptions.h>
#include <c10/util/Deprecated.h>
#include <c10/util/Optional.h>



#include <ATen/ops/ormqr_ops.h>

namespace at {


// aten::ormqr.out(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False, *, Tensor(a!) out) -> Tensor(a!)
TORCH_API inline at::Tensor & ormqr_out(at::Tensor & out, const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false) {
    return at::_ops::ormqr_out::call(self, input2, input3, left, transpose, out);
}

// aten::ormqr.out(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False, *, Tensor(a!) out) -> Tensor(a!)
TORCH_API inline at::Tensor & ormqr_outf(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left, bool transpose, at::Tensor & out) {
    return at::_ops::ormqr_out::call(self, input2, input3, left, transpose, out);
}

// aten::ormqr(Tensor self, Tensor input2, Tensor input3, bool left=True, bool transpose=False) -> Tensor
TORCH_API inline at::Tensor ormqr(const at::Tensor & self, const at::Tensor & input2, const at::Tensor & input3, bool left=true, bool transpose=false) {
    return at::_ops::ormqr::call(self, input2, input3, left, transpose);
}

}
