code: def get_batch(self):
      if self.match is not None:
          return self.input.batch, self.input_target.batch
      else:
          return self.input.batch, None
  
imports: import torch
  import torch.nn
  from torch.nn import LeakyReLU, Linear, Sequential
  from torch_geometric.nn.pool.consecutive import consecutive_cluster
  from torch_geometric.nn import voxel_grid
  from torch_geometric.data import Batch
  from torch_scatter import scatter_max, scatter_mean
  from torch_points3d.applications.sparseconv3d import SparseConv3d
  from torch_points3d.core.common_modules import FastBatchNorm1d, Seq
  from torch_points3d.core.common_modules import MLP
  from torch_points3d.models.registration.base import FragmentBaseModel
label_desc: Use image node_id 3 for calling the BaseMS_SparseConv3d obj's underlying member method code with example usage: obj.get_batch() and returns: self,  self, self,  None