code: def test_invalid_dtype_raises_value_error(predictor):
      data = np.zeros((1, 3, 32, 32), dtype=np.float32)
      with pytest.raises(ValueError):
          # `dtype` should be a single `torch.dtype`.
          predictor.predict(data, dtype=np.float32)
  
file_path: ray/python/ray/train/tests/test_torch_detection_predictor.py
imports: import numpy
  import pytest
  from torchvision import models
  from ray.air.util.tensor_extensions.utils import create_ragged_ndarray
  from ray.train.torch import TorchDetectionPredictor
label_desc: Use image node_id 4 for calling a global function with example usage: test_invalid_dtype_raises_value_error(predictor) without return types