code: def __init__(self, dataset_opt):
      super().__init__(dataset_opt)
  
      number = dataset_opt.number
      if str(number) not in self.AVAILABLE_NUMBERS:
          raise Exception(
              "Only ModelNet10 and ModelNet40 are available"
          )
      self.train_dataset = SampledModelNet(
          self._data_path,
          name=str(number),
          train=True,
          transform=self.train_transform,
          pre_transform=self.pre_transform,
      )
      self.test_dataset = SampledModelNet(
          self._data_path,
          name=str(number),
          train=False,
          transform=self.test_transform,
          pre_transform=self.pre_transform,
      )
  
imports: import os.path
  import os
  import shutil
  import torch
  from torch_geometric.datasets import ModelNet
  from torch_geometric.data import DataLoader, InMemoryDataset, extract_zip, Data
  import torch_geometric.transforms
  from torch_geometric.io import read_txt_array
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.metrics.classification_tracker import ClassificationTracker
  from torch_points3d.utils.download import download_url
label_desc: Use image node_id 1 to create a new ModelNetDataset object from inherited base classes: BaseDataset with example: obj = ModelNetDataset(dataset_opt)