code: def datalist(self):
      torch.manual_seed(0)
      torch.randn((self.num_points, 3))
      datalist = [
          Data(
              pos=torch.randn((self.num_points, 3)),
              x=self._feature,
              y=self._y,
              category=self._category,
          )
          for i in range(self.batch_size)
      ]
      if self._transform:
          datalist = [self._transform(d.clone()) for d in datalist]
      if self._ms_transform:
          datalist = [self._ms_transform(d.clone()) for d in datalist]
      return datalist
  
imports: 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
label_desc: Use image node_id 4 for calling the MockDataset obj's underlying member method code with example usage: obj.datalist() and returns: datalist