code: def test_empty_dataset(self):
      opt = Options()
      opt.dataset_name = os.path.join(os.getcwd(), "test")
      opt.dataroot = os.path.join(os.getcwd(), "test")
      opt.pre_transform = [DictConfig({"transform": "RandomNoise"})]
      opt.test_transform = [DictConfig({"transform": "AddOnes"})]
      opt.val_transform = [DictConfig({"transform": "Jitter"})]
      opt.train_transform = [
          DictConfig({"transform": "RandomSymmetry"})
      ]
      dataset = BaseDataset(opt)
  
      self.assertEqual(
          str(dataset.pre_transform),
          str(T.Compose([T3d.RandomNoise()])),
      )
      self.assertEqual(
          str(dataset.test_transform), str(T.Compose([T3d.AddOnes()]))
      )
      self.assertEqual(
          str(dataset.train_transform),
          str(T.Compose([T3d.RandomSymmetry()])),
      )
      self.assertEqual(
          str(dataset.val_transform), str(T.Compose([T3d.Jitter()]))
      )
      self.assertEqual(
          str(dataset.inference_transform),
          str(T.Compose([T3d.RandomNoise(), T3d.AddOnes()])),
      )
      self.assertEqual(dataset.train_dataset, None)
      self.assertEqual(dataset.test_dataset, None)
      self.assertEqual(dataset.val_dataset, None)
  
imports: import unittest
  from omegaconf import DictConfig, OmegaConf
  import os
  import sys
  from glob import glob
  import torch
  import numpy
  from torch_geometric.data.data import Data
  import torch_geometric.transforms
  from test.mockdatasets import MockDataset, MockDatasetConfig
  from test.mock_models import MockModel, MockModelConfig
  from torch_points3d.datasets.base_dataset import BaseDataset
  from torch_points3d.models.model_factory import instantiate_model
  from torch_points3d.utils.model_building_utils.model_definition_resolver import resolve_model
  from torch_points3d.utils.enums import ConvolutionFormat
  import torch_points3d.core.data_transform
label_desc: Use image node_id 1 for calling the TestDataset obj's underlying member method code with example usage: obj.test_empty_dataset() without return types