code: def test_repr(model):
      predictor = TorchPredictor(model=model)
  
      representation = repr(predictor)
  
      assert len(representation) < MAX_REPR_LENGTH
      pattern = re.compile("^TorchPredictor\\((.*)\\)$")
      assert pattern.match(representation)
  
imports: import re
  import numpy
  import pandas
  import pytest
  import torch
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.air.util.data_batch_conversion import _convert_batch_type_to_pandas, _convert_pandas_to_batch_type
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
  from ray.train.torch import TorchCheckpoint, TorchPredictor
label_desc: Use image node_id 3 for calling a global function with example usage: test_repr(model) without return types