我一直在使用Eigen的AutoDiffScalar取得了很大的成功,现在我想转到AutoDiffJacobian,而不是自己一个人做。因此,在研究了AutoDiffJacobian.h之后,我创建了一个学习示例,但是出了点问题。
函子:
template <typename Scalar>
struct adFunctor
{
typedef Eigen::Matrix<Scalar, 3, 1> InputType;
typedef Eigen::Matrix<Scalar, 2, 1> ValueType;
typedef Eigen::Matrix<Scalar,
ValueType::RowsAtCompileTime,
InputType::RowsAtCompileTime> JacobianType;
enum {
InputsAtCompileTime = InputType::RowsAtCompileTime,
ValuesAtCompileTime = ValueType::RowsAtCompileTime
};
adFunctor() {}
size_t inputs() const { return InputsAtCompileTime; }
void operator() (const InputType &input,
ValueType *output) const
{
Scalar s1 = Scalar(0), s2 = Scalar(0);
/* Some operations to test the AD. */
for (int i = 0; i < 3; i++)
{
s1 += log(input(i));
s2 += sqrt(input(i));
}
(*output)(0) = s1;
(*output)(1) = s2;
}
};
用法:
Eigen::Matrix<double, 3, 1> in;
in << 1,2,3;
Eigen::Matrix<double, 2, 1> out;
Eigen::AutoDiffJacobian< adFunctor<double> > adjac;
adjac(in, &out);
从此收到的错误如下:
/usr/include/eigen3/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h: In instantiation of ‘void Eigen::AutoDiffJacobian<Functor>::operator()(const InputType&, Eigen::AutoDiffJacobian<Functor>::ValueType*, Eigen::AutoDiffJacobian<Functor>::JacobianType*) const [with Functor = adFunctor<double>; Eigen::AutoDiffJacobian<Functor>::InputType = Eigen::Matrix<double, 3, 1>; Eigen::AutoDiffJacobian<Functor>::ValueType = Eigen::Matrix<double, 2, 1>; Eigen::AutoDiffJacobian<Functor>::JacobianType = Eigen::Matrix<double, 2, 3, 0, 2, 3>]’:
/home/emifre/Git/autodiff-test/src/autodiff_test.cpp:55:17: required from here
/usr/include/eigen3/unsupported/Eigen/src/AutoDiff/AutoDiffJacobian.h:69:24: error: no matching function for call to ‘Eigen::AutoDiffJacobian<adFunctor<double> >::operator()(Eigen::AutoDiffJacobian<adFunctor<double> >::ActiveInput&, Eigen::AutoDiffJacobian<adFunctor<double> >::ActiveValue*) const’
Functor::operator()(ax, &av);
~~~~~~~~~~~~~~~~~~~^~~~~~~~~
/home/emifre/Git/autodiff-test/src/autodiff_test.cpp:27:8: note: candidate: void adFunctor<Scalar>::operator()(const InputType&, adFunctor<Scalar>::ValueType*) const [with Scalar = double; adFunctor<Scalar>::InputType = Eigen::Matrix<double, 3, 1>; adFunctor<Scalar>::ValueType = Eigen::Matrix<double, 2, 1>]
void operator() (const InputType &input,
^~~~~~~~
/home/emifre/Git/autodiff-test/src/autodiff_test.cpp:27:8: note: no known conversion for argument 2 from ‘Eigen::AutoDiffJacobian<adFunctor<double> >::ActiveValue* {aka Eigen::Matrix<Eigen::AutoDiffScalar<Eigen::Matrix<double, 3, 1> >, 2, 1, 0, 2, 1>*}’ to ‘adFunctor<double>::ValueType* {aka Eigen::Matrix<double, 2, 1>*}’
从该错误看来,在AutoDiffJacobian.h中第二次调用函子时,我似乎不知道函子的类型正确,但是第一次调用了。
我希望这里的人知道为什么并且可以提供帮助,也许我只是误解了用法。
编辑:一个显示问题的可编译示例:
#include <Eigen/Dense>
#include <unsupported/Eigen/AutoDiff>
/*
* Testing differentiation that will produce a Jacobian, using functors and the
* AutoDiffJacobian helper.
*/
template <typename Scalar>
struct adFunctor
{
typedef Eigen::Matrix<Scalar, 3, 1> InputType;
typedef Eigen::Matrix<Scalar, 2, 1> ValueType;
typedef Eigen::Matrix<Scalar,
ValueType::RowsAtCompileTime,
InputType::RowsAtCompileTime> JacobianType;
enum {
InputsAtCompileTime = InputType::RowsAtCompileTime,
ValuesAtCompileTime = ValueType::RowsAtCompileTime
};
adFunctor() {}
size_t inputs() const { return InputsAtCompileTime; }
void operator() (const InputType &input,
ValueType *output) const
{
Scalar s1 = Scalar(0), s2 = Scalar(0);
/* Some operations to test the AD. */
for (int i = 0; i < 3; i++)
{
s1 += log(input(i));
s2 += sqrt(input(i));
}
(*output)(0) = s1;
(*output)(1) = s2;
}
};
int main(int argc, char *argv[])
{
Eigen::Matrix<double, 3, 1> in;
in << 1,2,3;
Eigen::Matrix<double, 2, 1> out;
Eigen::AutoDiffJacobian< adFunctor<double> > adjac;
adjac(in, &out);
return 0;
}
最佳答案
Okey,经过大量测试后,我开始使用它。
只是我误解了编译器的错误,直截了当地说,我缺少运算符本身的模板。
只需将其更改为:
template <typename T1, typename T2>
void operator() (const T1 &input, T2 *output) const
现在,它就像一种享受!我希望比我更多的人可以使用此功能。