My objective is to use the following class and script, derived from this excellent work: https://github.com/timesler/facenet-pytorch 7 :
from facenet_pytorch import MTCNN, InceptionResnetV1
import torch
from torch.utils.data import DataLoader
from torchvision import datasets
import numpy as np
import pandas as pd
import os

workers = 0 if os.name == 'nt' else 4

def collate_fn(x):
    return x[0]

def describe(x):
    print("Type: {}".format(x.type()))
    print("Shape/size: {}".format(x.shape))
    print("Values: \n{}".format(x))

class GetFaceEmbedding(torch.nn.Module):
    def __init__(self):
        super(GetFaceEmbedding, self).__init__()

    @classmethod
    def getFaceEmbedding(self, imagePath):

        device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
        print('Running on device: {}'.format(device))

        mtcnn = MTCNN(
            image_size=160, margin=0, min_face_size=20,
            thresholds=[0.6, 0.7, 0.7], factor=0.709, post_process=True,
            device=device
        )
        resnet = InceptionResnetV1(pretrained='vggface2').eval().to(device)
        dataset = datasets.ImageFolder(imagePath)
        dataset.idx_to_class = {i:c for c, i in dataset.class_to_idx.items()}
        loader = DataLoader(dataset, collate_fn=collate_fn, num_workers=workers)
        aligned = []
        names = []
        for x, y in loader:
            x_aligned, prob = mtcnn(x, return_prob=True)
            if x_aligned is not None:
                print('Face detected with probability: {:8f}'.format(prob))
                aligned.append(x_aligned)
                names.append(dataset.idx_to_class[y])
        aligned = torch.stack(aligned).to(device)
        embeddings = resnet(aligned).detach().cpu()
        return embeddings

With python it works fine:
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples$ python3 .  
/getFaceEmbedding-01.py 
Running on device: cpu
Face detected with probability: 0.999430
Type: torch.FloatTensor
Shape/size: torch.Size([1, 512])
Values: 
tensor([[ 3.6307e-02, -8.8092e-02, -3.5002e-02, -8.2932e-02,  1.9032e-02,
          2.3228e-02,  2.4253e-02, -3.7844e-02, -6.8906e-02,  2.0351e-02,
         -6.7093e-02,  3.6181e-02, -2.5933e-02, -6.0015e-02,  2.6653e-02,
          9.4335e-02, -2.9241e-02, -2.8357e-02,  7.2207e-02, -3.7747e-02,
          6.3515e-03, -3.0220e-02, -2.4530e-02,  1.0004e-01,  6.6520e-02,
          ....
          3.2497e-02,  2.3421e-02, -5.3921e-02,  1.9589e-02, -2.8655e-03,
          1.3474e-02, -2.2743e-02,  3.2976e-02, -5.6658e-02,  2.0837e-02,
         -4.7152e-02, -6.5534e-02]])

Following the indications found here: https://pytorch.org/tutorials/advanced/cpp_export.html
I added to getFaceEmbedding.py these lines:
my_module = GetFaceEmbedding()
sm = torch.jit.script(my_module)
sm.save("annotated_get_face_embedding.pt")

I then saved the serialized file:
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples$ python3 
./getFaceEmbedding.py

-rw-r--r-- 1 marco marco 1,4K mar 19 18:52 annotated_get_face_embedding.pt

And created this cpp file:
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples$ nano 

faceEmbedding.cpp  :
#include <torch/script.h>
#include <iostream>
#include <memory>
#include <filesystem>

int main(int argc, const char* argv[]) {
    //if(argc != 3) {
    //    std::cerr << "usage:usage: faceEmbedding <path-to-exported-script-module> <path-to-image-f 
ile> \n";
    //    return -1;
    //}

  torch::jit::script::Module module;
  try {
      // Deserialize the ScriptModule from a file using torch::jit::load().
      module = torch::jit::load(argv[1]);
      std::filesystem::path imgPath = argv[2];

      // Execute the model and turn its output into a tensor
      at::Tensor output = module.getFaceEmbedding(imgPath).ToTensor();
  }
  catch (const c10::Error& e) {
      std::cerr << "error loading the model\n";
      return -1;
  }
  std::cout << "ok\n";
} // end of main() function

But during the compilation phase I get this error :
"struct torch::jit::script::Module’ has no member named ‘getFaceEmbedding’ "
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples$ mkdir build
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples$ cd build
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples/build$ cmake 
-DCMAKE_PREFIX_PATH=/home/marco/PyTorchMatters/libtorch ..
-- The C compiler identification is GNU 9.2.1
-- The CXX compiler identification is GNU 9.2.1
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Failed
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE  
-- Found torch: /home/marco/PyTorchMatters/libtorch/lib/libtorch.so  
-- Configuring done
-- Generating done
-- Build files have been written to: /home/marco/PyTorchMatters/facenet_pytorch/examples/build
(venv373) (base) marco@pc01:~/PyTorchMatters/facenet_pytorch/examples/build$ cmake --build . 
--config Release
Scanning dependencies of target faceEmbedding
[ 50%] Building CXX object CMakeFiles/faceEmbedding.dir/faceEmbedding.cpp.o
/home/marco/PyTorchMatters/facenet_pytorch/examples/faceEmbedding.cpp: In function ‘int 
main(int, const char**)’:
/home/marco/PyTorchMatters/facenet_pytorch/examples/faceEmbedding.cpp:20:34: error: ‘struct 
torch::jit::script::Module’ has no member named ‘getFaceEmbedding’
   20 |       at::Tensor output = module.getFaceEmbedding(imgPath).ToTensor();
      |                                  ^~~~~~~~~~~~~~~~
CMakeFiles/faceEmbedding.dir/build.make:62: recipe for target 'CMakeFiles/faceEmbedding.dir
/faceEmbedding.cpp.o' failed
make[2]: *** [CMakeFiles/faceEmbedding.dir/faceEmbedding.cpp.o] Error 1
CMakeFiles/Makefile2:75: recipe for target 'CMakeFiles/faceEmbedding.dir/all' failed
make[1]: *** [CMakeFiles/faceEmbedding.dir/all] Error 2
Makefile:83: recipe for target 'all' failed
make: *** [all] Error 2

How to solve the problem?
Looking forward to your kind help.
Marco