code: def get_batch(self):
      if self.match is not None:
          batch = self.input.C[:, 0]
          batch_target = self.input_target.C[:, 0]
          return batch, batch_target
      else:
          return None, None
  
imports: import logging
  import torch
  from torch_geometric.data import Data
  from torch_points3d.modules.MinkowskiEngine import *
  from torch_points3d.models.base_architectures import UnwrappedUnetBasedModel
  from torch_points3d.models.registration.base import FragmentBaseModel
  from torch.nn import Sequential, Linear, LeakyReLU, Dropout
  from torch_points3d.core.common_modules import FastBatchNorm1d, Seq
label_desc: Use image node_id 3 for calling the BaseMinkowski obj's underlying member method code with example usage: obj.get_batch() and returns: batch,  batch_target, None,  None