code: def get_batch(self):
      if self.match is not None:
          batch = self.input.batch
          batch_target = self.input_target.batch
          return batch, batch_target
      else:
          return None, None
  
file_path: torch-points3d/torch_points3d/models/registration/spconv3d.py
imports: import torch
  from torch_points3d.models.registration.base import FragmentBaseModel
  from torch.nn import Sequential, Linear, LeakyReLU, Dropout
  from torch_geometric.data import Data, Batch
  from torch_points3d.core.common_modules import FastBatchNorm1d, Seq
  from torch_points3d.applications.sparseconv3d import SparseConv3d
label_desc: Use image node_id 3 for calling the SparseConv3D obj's underlying member method code with example usage: obj.get_batch() and returns: batch,  batch_target, None,  None