code: def test_pipeline_fit_transform_should_load_all_pipeline_steps(
      tmpdir: LocalPath,
  ):
      p = given_saved_pipeline(tmpdir)
  
      p, outputs = p.fit_transform(
          np.array(range(10)), np.array(range(10))
      )
  
      assert np.array_equal(outputs, EXPECTED_OUTPUTS)
  
imports: import os
  import numpy
  from joblib import dump
  from py._path.local import LocalPath
  from pprint import pprint
  from neuraxle.hyperparams.space import RecursiveDict
  from neuraxle.base import CX, StepWithContext, TruncableJoblibStepSaver
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.numpy import MultiplyByN
label_desc: Use image node_id 7 for calling a global function with example usage: test_pipeline_fit_transform_should_load_all_pipeline_steps(tmpdir) without return types