code: def test_init(model, preprocessor):
      predictor = TorchPredictor(model=model, preprocessor=preprocessor)
  
      checkpoint_predictor = TorchPredictor.from_checkpoint(
          TorchCheckpoint.from_model(model, preprocessor=preprocessor)
      )
  
      data_batch = np.array([1, 2, 3])
      np.testing.assert_array_equal(
          predictor.predict(data_batch)["predictions"],
          checkpoint_predictor.predict(data_batch)["predictions"],
      )
      assert (
          checkpoint_predictor.get_preprocessor()
          == predictor.get_preprocessor()
      )
  
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 4 for calling a global function with example usage: test_init(model, preprocessor) without return types