class_docstr: implementation of get_fragment and get_name to avoid repetitions
docstr: get the name of the scene and the name of the fragments.
docstr_tok: ["get","the","name","of","the","scene","and","the","name","of","the","fragments","."]
code: def get_name(self, idx):
      """
      get the name of the scene and the name of the fragments.
      """
  
      match = np.load(
          osp.join(self.path_match, "matches{:06d}.npy".format(idx)),
          allow_pickle=True,
      ).item()
      source = match["name_source"]
      target = match["name_target"]
      scene = match["scene"]
      return scene, source, target
  
imports: import numpy
  import os.path
  import random
  import torch
  import logging
  from torch_geometric.data import Data
  from torch_points_kernels.points_cpu import ball_query
  from functools import partial
  from torch_points3d.core.data_transform import MultiScaleTransform
  from torch_points3d.core.data_transform import PairTransform
  from torch_points3d.datasets.registration.pair import DensePairBatch
  from torch_points3d.utils.enums import ConvolutionFormat
  from torch_points3d.utils.config import ConvolutionFormatFactory
  from torch_points3d.datasets.registration.pair import PairMultiScaleBatch, PairBatch
  from torch_points3d.datasets.registration.pair import Pair, MultiScalePair
  from torch_points3d.datasets.registration.utils import tracked_matches
  from torch_points3d.datasets.registration.utils import compute_overlap_and_matches
  from torch_points3d.datasets.registration.utils import fps_sampling
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.metrics.registration_tracker import PatchRegistrationTracker
  from torch_points3d.metrics.registration_tracker import FragmentRegistrationTracker
label_desc: Use image node_id 4 for calling the GeneralFragment obj's underlying member method code with example usage: obj.get_name(idx) and returns: scene,  source,  target