code: def test_predict(batch_type):
      preprocessor = DummyPreprocessor()
      predictor = SklearnPredictor(
          estimator=model, preprocessor=preprocessor
      )
  
      raw_batch = pd.DataFrame([[1, 2], [3, 4], [5, 6]])
      data_batch = _convert_pandas_to_batch_type(
          raw_batch, type=TYPE_TO_ENUM[batch_type]
      )
      predictions = predictor.predict(data_batch)
  
      assert len(predictions) == 3
      assert predictor.get_preprocessor().has_preprocessed
  
file_path: ray/python/ray/train/tests/test_sklearn_predictor.py
imports: import re
  import numpy
  import pandas
  import pytest
  from sklearn.ensemble import RandomForestClassifier
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.air.util.data_batch_conversion import _convert_pandas_to_batch_type
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.sklearn import SklearnCheckpoint, SklearnPredictor
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
label_desc: Use image node_id 3 for calling a global function with example usage: test_predict(batch_type) without return types