code: def test_pipeline_fit_should_load_all_pipeline_steps(
      tmpdir: LocalPath,
  ):
      p = given_saved_pipeline(tmpdir)
  
      p = p.fit(np.array(range(10)), np.array(range(10)))
  
      assert p.wrapped[SOME_STEPS[0]].hyperparams["multiply_by"] == 2
      assert (
          p.wrapped[PIPELINE_2][SOME_STEPS[1]].hyperparams[
              "multiply_by"
          ]
          == 4
      )
      assert (
          p.wrapped[PIPELINE_2][SOME_STEPS[2]].hyperparams[
              "multiply_by"
          ]
          == 6
      )
  
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 9 for calling a global function with example usage: test_pipeline_fit_should_load_all_pipeline_steps(tmpdir) without return types