code: def test_output_transformer_wrapper_should_fit_with_data_inputs_and_expected_outputs_as_data_inputs():
      tape = TapeCallbackFunction()
      p = OutputTransformerWrapper(FitCallbackStep(tape))
      data_inputs, expected_outputs = _create_data_source((10, 10))
  
      p.fit(data_inputs, expected_outputs)
  
      assert np.array_equal(tape.data[0][0], expected_outputs)
      for i in range(10):
          _first_eot_seen: EOT = tape.data[0][1]
          assert _first_eot_seen is None
  
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 1 for calling a global function with example usage: test_output_transformer_wrapper_should_fit_with_data_inputs_and_expected_outputs_as_data_inputs() without return types