code: def test_predict_array_with_preprocessor(use_gpu):
      preprocessor = DummyPreprocessor()
      predictor = TensorflowPredictor(
          model=build_model(),
          preprocessor=preprocessor,
          use_gpu=use_gpu,
      )
  
      data_batch = np.array([1, 2, 3])
      predictions = predictor.predict(data_batch)
  
      assert len(predictions) == 1
      # [1 2 3] returns [[2],[4],[6]] with shape: (3,1) from Tensorflow model
      np.testing.assert_array_equal(
          predictions["predictions"], np.asarray([[2], [4], [6]])
      )
      assert predictor.get_preprocessor().has_preprocessed
  
imports: import re
  from typing import Tuple
  import numpy
  import pandas
  import pytest
  import tensorflow
  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.data.preprocessor import Preprocessor
  from ray.train.predictor import TYPE_TO_ENUM
  from ray.train.tensorflow import TensorflowCheckpoint, TensorflowPredictor
  from ray.train.tests.dummy_preprocessor import DummyPreprocessor
label_desc: Use image node_id 11 for calling a global function with example usage: test_predict_array_with_preprocessor(use_gpu) without return types