code: def test_numpy_pandas_support_transform_batch_tensor(
      create_dummy_preprocessors,
  ):
      # Case 4: tensor dataset created by from numpy data directly
      (
          with_nothing,
          with_pandas,
          with_numpy,
          with_pandas_and_numpy,
          with_pandas_and_numpy_preferred,
      ) = create_dummy_preprocessors
      np_data = np.arange(12).reshape(3, 2, 2)
      np_single_column = {"A": np.arange(12).reshape(3, 2, 2)}
      np_multi_column = {
          "A": np.arange(12).reshape(3, 2, 2),
          "B": np.arange(12, 24).reshape(3, 2, 2),
      }
  
      with pytest.raises(NotImplementedError):
          with_nothing.transform_batch(np_data)
      with pytest.raises(NotImplementedError):
          with_nothing.transform_batch(np_single_column)
      with pytest.raises(NotImplementedError):
          with_nothing.transform_batch(np_multi_column)
  
      assert isinstance(
          with_pandas.transform_batch(np_data), pd.DataFrame
      )
      assert isinstance(
          with_pandas.transform_batch(np_single_column), pd.DataFrame
      )
      assert isinstance(
          with_pandas.transform_batch(np_multi_column), pd.DataFrame
      )
  
      assert isinstance(with_numpy.transform_batch(np_data), np.ndarray)
      assert isinstance(
          with_numpy.transform_batch(np_single_column), dict
      )
      assert isinstance(
          with_numpy.transform_batch(np_multi_column), dict
      )
  
      assert isinstance(
          with_pandas_and_numpy.transform_batch(np_data), pd.DataFrame
      )
      assert isinstance(
          with_pandas_and_numpy.transform_batch(np_single_column),
          pd.DataFrame,
      )
      assert isinstance(
          with_pandas_and_numpy.transform_batch(np_multi_column),
          pd.DataFrame,
      )
  
      assert isinstance(
          with_pandas_and_numpy_preferred.transform_batch(np_data),
          np.ndarray,
      )
      assert isinstance(
          with_pandas_and_numpy_preferred.transform_batch(
              np_single_column
          ),
          dict,
      )
      assert isinstance(
          with_pandas_and_numpy_preferred.transform_batch(
              np_multi_column
          ),
          dict,
      )
  
imports: import re
  import warnings
  from typing import Dict, Union
  from unittest.mock import patch
  import numpy
  import pandas
  import pyarrow
  import pytest
  import ray
  from ray.air.constants import MAX_REPR_LENGTH
  from ray.air.util.data_batch_conversion import BatchFormat
  from ray.data.preprocessor import Preprocessor
  from ray.data.preprocessors import BatchMapper, Categorizer, Chain, Concatenator, CountVectorizer, FeatureHasher, HashingVectorizer, LabelEncoder, MaxAbsScaler, MinMaxScaler, MultiHotEncoder, Normalizer, OneHotEncoder, OrdinalEncoder, PowerTransformer, RobustScaler, SimpleImputer, StandardScaler, Tokenizer
label_desc: Use image node_id 11 for calling a global function with example usage: test_numpy_pandas_support_transform_batch_tensor(create_dummy_preprocessors) without return types