code: def test_get_and_set_preprocessor():
      """Test preprocessor can be set and get."""
  
      preprocessor = DummyPreprocessor(1)
      with create_dict_checkpoint(
          {"factor": 2.0}, checkpoint_cls=FrameworkCheckpoint
      ) as checkpoint:
          checkpoint.set_preprocessor(preprocessor)
          predictor = DummyPredictor.from_checkpoint(checkpoint)
  
      assert predictor.get_preprocessor().id == preprocessor.id
  
      test_dataset = pd.DataFrame(range(4))
      output_df = predictor.predict(test_dataset)
      assert output_df.to_numpy().squeeze().tolist() == [
          0.0,
          2.0,
          4.0,
          6.0,
      ]
  
      preprocessor2 = DummyPreprocessor(2)
      predictor.set_preprocessor(preprocessor2)
      assert predictor.get_preprocessor().id == preprocessor2.id
  
      output_df = predictor.predict(test_dataset)
      assert output_df.to_numpy().squeeze().tolist() == [
          0.0,
          4.0,
          8.0,
          12.0,
      ]
  
imports: import uuid
  from typing import Dict, Optional, Union
  from unittest import mock
  import numpy
  import pandas
  import pytest
  import ray
  from ray.air.constants import TENSOR_COLUMN_NAME
  from ray.air.util.data_batch_conversion import BatchFormat
  from ray.data import Preprocessor
  from ray.train._internal.framework_checkpoint import FrameworkCheckpoint
  from ray.train.predictor import Predictor, PredictorNotSerializableException
  from ray.train.tests.util import create_dict_checkpoint, load_dict_checkpoint
label_desc: Use image node_id 8 for calling a global function with example usage: test_get_and_set_preprocessor() without return types