I have already define my own evaluateError function, but the compiler always says error: invalid cast to abstract class type ‘gtsamexamples::GPSPose2Factor’

[LeoX0808]

I have already define my own evaluateError function, but the compiler always says
error: invalid cast to abstract class type ‘gtsamexamples::GPSPose2Factor’
57 | graph.add(GPSPose2Factor(Symbol('x', 2), Point2(5, 0), gpsModel));

this is my GPSPose2Factor.h

#pragma once

#include <gtsam/nonlinear/NonlinearFactor.h>
#include <gtsam/base/Matrix.h>
#include <gtsam/base/Vector.h>
#include <gtsam/geometry/Pose2.h>

// you can custom namespace (if needed for your project)
namespace gtsamexamples {

class GPSPose2Factor: public gtsam::NoiseModelFactor1gtsam::Pose2 {
private:
// measurement information
double mx_, my_;

public:
GPSPose2Factor(gtsam::Key poseKey, const gtsam::Point2 m, gtsam::SharedNoiseModel model);
gtsam::Vector evaluateError(const gtsam::Pose2& p, boost::optionalgtsam::Matrix& H = boost::none) const;
};

} // namespace gtsamexamples

this is GPSPose2Factor.cpp
#include "GPSPose2Factor.h"

namespace gtsamexamples {
GPSPose2Factor::GPSPose2Factor(gtsam::Key poseKey, const gtsam::Point2 m, gtsam::SharedNoiseModel model) :gtsam::NoiseModelFactor1gtsam::Pose2(model, poseKey)
{
mx_ = m.x();
my_ = m.y();
}
gtsam::Vector GPSPose2Factor::evaluateError(const gtsam::Pose2& p, boost::optionalgtsam::Matrix& H) const {

if (H) *H = (gtsam::Matrix23() << 1.0, 0.0, 0.0, 
                                  0.0, 1.0, 0.0).finished();
return (gtsam::Vector2() << p.x() - mx_, p.y() - my_).finished();

}
}

[ 25%] Building CXX object cpp/CMakeFiles/GPSPose2Factor.dir/GPSPose2Factor.cpp.o
[ 50%] Linking CXX shared library libGPSPose2Factor.so
[ 50%] Built target GPSPose2Factor

building GPSPose2Factor is already done but Pose2GPSExample.cpp cannot correctly use the GPSPose2Factor class

this is Pose2GPSExample.cpp

#include "/home/xyx/codeAndDemo/gtsam-examples-master/cpp/GPSPose2Factor.h"

#include <gtsam/geometry/Pose2.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
#include <gtsam/nonlinear/Values.h>
#include <gtsam/inference/Symbol.h>
#include <gtsam/slam/BetweenFactor.h>
#include <gtsam/nonlinear/GaussNewtonOptimizer.h>
#include <gtsam/nonlinear/Marginals.h>

using namespace std;
using namespace gtsam;
using namespace gtsamexamples;

int main(int argc, char** argv) {

// Create a factor graph container
NonlinearFactorGraph graph;

// odometry measurement noise model (covariance matrix)
noiseModel::Diagonal::shared_ptr odomModel = noiseModel::Diagonal::Sigmas(Vector3(0.5, 0.5, 0.1));

// Add odometry factors
// Create odometry (Between) factors between consecutive poses
// robot makes 90 deg right turns at x3 - x5
graph.add(BetweenFactor(Symbol('x', 1), Symbol('x', 2), Pose2(5, 0, 0), odomModel));
graph.add(BetweenFactor(Symbol('x', 2), Symbol('x', 3), Pose2(5, 0, 0), odomModel));

// 2D 'GPS' measurement noise model, 2-dim
noiseModel::Diagonal::shared_ptr gpsModel = noiseModel::Diagonal::Sigmas(Vector2(1.0, 1.0));

// Add the GPS factors
// note that there is NO prior factor needed at first pose, since GPS provides
// the global positions (and rotations given more than 1 GPS measurements)
graph.add(GPSPose2Factor(Symbol('x', 1), Point2(0, 0), gpsModel));
graph.add(GPSPose2Factor(Symbol('x', 2), Point2(5, 0), gpsModel));
graph.add(GPSPose2Factor(Symbol('x', 3), Point2(10, 0), gpsModel));

// print factor graph
graph.print("\nFactor Graph:\n");

// initial varible values for the optimization
// add random noise from ground truth values
Values initials;
initials.insert(Symbol('x', 1), Pose2(0.2, -0.3, 0.2));
initials.insert(Symbol('x', 2), Pose2(5.1, 0.3, -0.1));
initials.insert(Symbol('x', 3), Pose2(9.9, -0.1, -0.2));

// print initial values
initials.print("\nInitial Values:\n");

// Use Gauss-Newton method optimizes the initial values
GaussNewtonParams parameters;

// print per iteration
parameters.setVerbosity("ERROR");

// optimize!
GaussNewtonOptimizer optimizer(graph, initials, parameters);
Values results = optimizer.optimize();

// print final values
results.print("Final Result:\n");

// Calculate marginal covariances for all poses
Marginals marginals(graph, results);

// print marginal covariances
cout << "x1 covariance:\n" << marginals.marginalCovariance(Symbol('x', 1)) << endl;
cout << "x2 covariance:\n" << marginals.marginalCovariance(Symbol('x', 2)) << endl;
cout << "x3 covariance:\n" << marginals.marginalCovariance(Symbol('x', 3)) << endl;

return 0;
}

but the compiler says
Scanning dependencies of target Pose2GPSExample
[ 75%] Building CXX object cpp/CMakeFiles/Pose2GPSExample.dir/examples/Pose2GPSExample.cpp.o
/home/xyx/codeAndDemo/gtsam-examples-master/cpp/examples/Pose2GPSExample.cpp: In function ‘int main(int, char**)’:
/home/xyx/codeAndDemo/gtsam-examples-master/cpp/examples/Pose2GPSExample.cpp:56:66: error: invalid cast to abstract class type ‘gtsamexamples::GPSPose2Factor’
56 | graph.add(GPSPose2Factor(Symbol('x', 1), Point2(0, 0), gpsModel));
| ^
In file included from /home/xyx/codeAndDemo/gtsam-examples-master/cpp/examples/Pose2GPSExample.cpp:20:
/home/xyx/codeAndDemo/gtsam-examples-master/cpp/GPSPose2Factor.h:26:7: note: because the following virtual functions are pure within ‘gtsamexamples::GPSPose2Factor’:
26 | class GPSPose2Factor: public gtsam::NoiseModelFactor1gtsam::Pose2 {
| ^~~~~~~~~~~~~~
In file included from /home/xyx/codeAndDemo/gtsam-examples-master/cpp/GPSPose2Factor.h:16,
from /home/xyx/codeAndDemo/gtsam-examples-master/cpp/examples/Pose2GPSExample.cpp:20:
/usr/local/include/gtsam/nonlinear/NonlinearFactor.h:640:18: note: ‘gtsam::Vector gtsam::NoiseModelFactorN::evaluateError(const ValueTypes& ..., gtsam::NoiseModelFactorN::OptionalMatrixTypeT...) const [with ValueTypes = {gtsam::Pose2}; gtsam::Vector = Eigen::Matrix<double, -1, 1>]’
640 | virtual Vector evaluateError(const ValueTypes&... x,
| ^~~~~~~~~~~~~

at last my cmakelists is:
.....
add_library(GPSPose2Factor SHARED GPSPose2Factor.cpp)

include_directories(/home/xyx/codeAndDemo/gtsam-examples-master/cpp)

add_executable(Pose2GPSExample ./examples/Pose2GPSExample.cpp)

target_link_libraries(Pose2GPSExample ${Boost_LIBRARIES} gtsam GPSPose2Factor)

.....

I have no idea what the problem is, and I would greatly appreciate it if you could provide me with some reliable solutions.