code: def test_input_and_output_transformer_wrapper_should_not_return_a_different_amount_of_data_inputs_and_expected_outputs():
      with pytest.raises(AssertionError):
          p = IdsInputAndOutputTransformerWrapper(ChangeLenDataInputs())
          ids, data_inputs, expected_outputs = _create_data_source(
              (10, 10), with_ids=True
          )
  
          p.handle_transform(
              DACT(
                  ids=ids,
                  data_inputs=data_inputs,
                  expected_outputs=expected_outputs,
              ),
              CX(),
          )
  
imports: import numpy
  import pytest
  from neuraxle.base import BaseTransformer
  from neuraxle.base import ExecutionContext
  from neuraxle.base import ForceHandleMixin
  from neuraxle.data_container import EOT
  from neuraxle.data_container import DataContainer
  from neuraxle.hyperparams.space import HyperparameterSamples
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.misc import FitCallbackStep, TapeCallbackFunction
  from neuraxle.steps.numpy import MultiplyByN
  from neuraxle.steps.output_handlers import IdsInputAndOutputTransformerWrapper, OutputTransformerWrapper
label_desc: Use image node_id 7 for calling a global function with example usage: test_input_and_output_transformer_wrapper_should_not_return_a_different_amount_of_data_inputs_and_expected_outputs() without return types