code: def __init__(
      self,
      feature_size=0,
      transform=None,
      num_points=100,
      is_pair_ind=True,
      batch_size=2,
  ):
      super(PairMockDataset, self).__init__(
          feature_size, transform, num_points, batch_size=batch_size
      )
      if is_pair_ind:
          self._pair_ind = torch.tensor([[0, 1], [1, 0]])
      else:
          self._pair_ind = None
  
imports: import numpy
  import torch
  from torch_geometric.data import Data, Batch
  from torch_points3d.datasets.batch import SimpleBatch
  from torch_points3d.core.data_transform import MultiScaleTransform
  from torch_points3d.datasets.multiscale_data import MultiScaleBatch
  from torch_points3d.datasets.registration.pair import Pair, PairBatch, PairMultiScaleBatch, DensePairBatch
label_desc: Use image node_id 1 to create a new PairMockDataset object from inherited base classes: MockDataset with example: obj = PairMockDataset(feature_size, transform, num_points, is_pair_ind, batch_size)