code: def test_apply_on_pipeline_with_meta_step_and_positional_argument():
      pipeline = Pipeline(
          [OutputTransformerWrapper(MultiplyByN(1)), MultiplyByN(1)]
      )
  
      pipeline.apply(
          "_set_hyperparams",
          hyperparams=HyperparameterSamples(
              {
                  "multiply_by": 2,
                  "OutputTransformerWrapper__multiply_by": 3,
                  "OutputTransformerWrapper__MultiplyByN__multiply_by": 4,
                  "MultiplyByN__multiply_by": 5,
              }
          ),
      )
  
      assert pipeline.get_hyperparams()["multiply_by"] == 2
      assert (
          pipeline["OutputTransformerWrapper"].get_hyperparams()[
              "multiply_by"
          ]
          == 3
      )
      assert (
          pipeline[
              "OutputTransformerWrapper"
          ].wrapped.get_hyperparams()["multiply_by"]
          == 4
      )
      assert (
          pipeline["MultiplyByN"].get_hyperparams()["multiply_by"] == 5
      )
  
imports: import pytest
  from neuraxle.base import BaseStep
  from neuraxle.base import ExecutionContext
  from neuraxle.base import Identity, NonFittableMixin
  from neuraxle.data_container import DataContainer
  from neuraxle.hyperparams.space import HyperparameterSamples
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.flow import OptionalStep
  from neuraxle.steps.numpy import MultiplyByN
  from neuraxle.steps.output_handlers import OutputTransformerWrapper
label_desc: Use image node_id 3 for calling a global function with example usage: test_apply_on_pipeline_with_meta_step_and_positional_argument() without return types