code: def test_predict_should_predict_in_test_mode():
      tape_fit = TapeCallbackFunction()
      tape_transform = TapeCallbackFunction()
      p = Pipeline(
          [
              TestOnlyWrapper(
                  CallbackWrapper(
                      MultiplyByN(2), tape_transform, tape_fit
                  )
              ),
              TrainOnlyWrapper(
                  CallbackWrapper(
                      MultiplyByN(4), tape_transform, tape_fit
                  )
              ),
          ]
      )
  
      outputs = p.predict(np.array([1, 1]))
  
      assert np.array_equal(outputs, np.array([2, 2]))
  
file_path: Neuraxle/testing_neuraxle/test_basestep.py
imports: import numpy
  from neuraxle.base import ExecutionContext
  from neuraxle.data_container import DataContainer
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.flow import TestOnlyWrapper, TrainOnlyWrapper
  from neuraxle.steps.misc import TapeCallbackFunction, CallbackWrapper
  from neuraxle.steps.numpy import MultiplyByN
  from testing_neuraxle.mocks.step_mocks import SomeStepWithHyperparams
label_desc: Use image node_id 5 for calling a global function with example usage: test_predict_should_predict_in_test_mode() without return types