code: def inverse_transform(self, processed_outputs):
      ids, processed_outputs, expected_outputs = processed_outputs
  
      if not isinstance(processed_outputs, np.ndarray):
          processed_outputs = np.array(processed_outputs)
  
      if not isinstance(expected_outputs, np.ndarray):
          expected_outputs = np.array(expected_outputs)
  
      return (
          ids,
          processed_outputs / self.hyperparams["multiply_by"],
          expected_outputs / self.hyperparams["multiply_by"],
      )
  
imports: import numpy
  import pytest
  from neuraxle.base import BaseTransformer
  from neuraxle.base import ExecutionContext
  from neuraxle.base import ForceHandleMixin
  from neuraxle.data_container import EOT
  from neuraxle.data_container import DataContainer
  from neuraxle.hyperparams.space import HyperparameterSamples
  from neuraxle.pipeline import Pipeline
  from neuraxle.steps.misc import FitCallbackStep, TapeCallbackFunction
  from neuraxle.steps.numpy import MultiplyByN
  from neuraxle.steps.output_handlers import IdsInputAndOutputTransformerWrapper, OutputTransformerWrapper
label_desc: Use image node_id 3 for calling the MultiplyByNInputAndOutput obj's underlying member method code with example usage: obj.inverse_transform(processed_outputs) and returns: ids,  unknown,  unknown