code: def test_invalid_transform_raises_value_error(self):
      dataset = ray.data.from_items(
          [
              {"image": np.zeros((32, 32, 3)), "label": 0},
              {"image": np.zeros((32, 32, 3)), "label": 1},
          ]
      )
      transform = transforms.Lambda(lambda tensor: "BLAH BLAH INVALID")
      preprocessor = TorchVisionPreprocessor(
          columns=["image"], transform=transform
      )
  
      with pytest.raises(ValueError):
          preprocessor.transform(dataset).materialize()
  
file_path: ray/python/ray/data/tests/preprocessors/test_torch.py
imports: import numpy
  import pytest
  import torch
  from torchvision import transforms
  import ray
  from ray.data.preprocessors import TorchVisionPreprocessor
label_desc: Use image node_id 5 for calling the TestTorchVisionPreprocessor obj's underlying member method code with example usage: obj.test_invalid_transform_raises_value_error() without return types