code: def test_pipeline_fit_should_save_all_fitted_pipeline_steps(
      tmpdir: LocalPath,
  ):
      p: StepWithContext = create_pipeline(tmpdir)
  
      p = p.fit(np.array(range(10)), np.array(range(10)))
      p.save()
  
      saved_paths = [
          create_root_path(tmpdir),
          create_pipeline2_path(tmpdir),
          create_some_step_path(tmpdir, step_no=0),
          create_some_step_path(tmpdir, step_no=1),
          create_some_step_path(tmpdir, step_no=2),
      ]
      for path in saved_paths:
          assert os.path.exists(path), path
  
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 6 for calling a global function with example usage: test_pipeline_fit_should_save_all_fitted_pipeline_steps(tmpdir) without return types