code: def __init__(
      self,
      root,
      radius_patch=0.3,
      pre_transform=None,
      pre_filter=None,
      transform=None,
      verbose=False,
      debug=False,
      num_random_pt=5000,
      max_dist_overlap=0.01,
  ):
      super(Test3DMatch, self).__init__(
          root,
          transform,
          pre_transform,
          pre_filter,
          verbose,
          debug,
          max_dist_overlap,
      )
      self.num_random_pt = num_random_pt
      self.radius_patch = radius_patch
      self.patch_extractor = PatchExtractor(self.radius_patch)
      self.path_table = osp.join(self.processed_dir, "fragment")
      with open(osp.join(self.path_table, "table.json"), "r") as f:
          self.table = json.load(f)
  
imports: import numpy
  import os
  import os.path
  import torch
  import json
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.datasets.registration.basetest import Base3DMatchTest
  from torch_points3d.datasets.registration.basetest import SimplePatch
  from torch_points3d.datasets.registration.utils import PatchExtractor
  from torch_points3d.datasets.registration.detector import RandomDetector
  from torch_points3d.datasets.registration.pair import Pair, MultiScalePair
  from torch_points3d.datasets.registration.utils import tracked_matches
  from torch_points3d.datasets.registration.base_siamese_dataset import GeneralFragment
  from torch_points3d.datasets.registration.base_siamese_dataset import BaseSiameseDataset
label_desc: Use image node_id 1 to create a new Test3DMatch object from inherited base classes: Base3DMatchTest with example: obj = Test3DMatch(root, radius_patch, pre_transform, pre_filter, transform, verbose, debug, num_random_pt, max_dist_overlap)