code: def test_multi_column_batch_raises_value_error(predictor):
      data = {
          "image": np.zeros((2, 3, 32, 32), dtype=np.float32),
          "boxes": np.zeros((2, 0, 4), dtype=np.float32),
          "labels": np.zeros((2, 0), dtype=np.int64),
      }
      with pytest.raises(ValueError):
          # `data` should only contain one key. Otherwise, `TorchDetectionPredictor`
          # doesn't know which column contains the input images.
          predictor.predict(data)
  
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 3 for calling a global function with example usage: test_multi_column_batch_raises_value_error(predictor) without return types