code: def test_column_transformer_transform_should_support_multiple_tuples():
      # Given
      test_case = ColumnChooserTestCase(
          data_inputs=np.array(
              [[[1, 1, 2, 3]], [[10, 11, 12, 13]], [[20, 21, 22, 23]]]
          ),
          expected_outputs=np.array(
              [[[0, 1, 2, 3]], [[10, 11, 12, 13]], [[20, 21, 22, 23]]]
          ),
          expected_processed_outputs=np.array(
              [[[2, 2, 4]], [[20, 22, 24]], [[40, 42, 44]]]
          ),
          column_transformer_tuple_list=[
              (slice(0, 2), MultiplyBy2()),
              (2, MultiplyBy2()),
          ],
          n_dimension=3,
      )
      data_inputs = test_case.data_inputs
      p = ColumnTransformer(
          test_case.column_transformer_tuple_list, test_case.n_dimension
      )
  
      # When
      outputs = p.transform(data_inputs)
  
      # Then
      assert np.array_equal(
          test_case.expected_processed_outputs, outputs
      )
  
imports: import copy
  from typing import Any, Tuple
  import numpy
  import pytest
  from neuraxle.base import BaseStep
  from neuraxle.steps.column_transformer import ColumnTransformer
label_desc: Use image node_id 6 for calling a global function with example usage: test_column_transformer_transform_should_support_multiple_tuples() without return types