class_docstr: A step that can sends the expected_outputs to the wrapped step
  so that it can transform the expected outputs.
code: def _set_expected_outputs(
      self,
      data_container: DACT,
      new_expected_outputs_data_container: DACT,
      context: CX,
  ) -> DACT:
      self._assert(
          len(data_container)
          == len(new_expected_outputs_data_container),
          "OutputTransformerWrapper: Found different len for old data inputs, and expected outputs "
          "to reinsert. Please return the same the same amount of data inputs, and expected outputs, "
          "or otherwise create your own handler methods to do more funky things.",
          context,
      )
  
      data_container.set_expected_outputs(
          new_expected_outputs_data_container.data_inputs
      )
      data_container.set_ids(new_expected_outputs_data_container._ids)
  
      return data_container
  
imports: import copy
  from typing import Tuple
  from neuraxle.base import BaseStep
  from neuraxle.base import ExecutionContext
  from neuraxle.base import ForceHandleOnlyMixin, MetaStep, MixinForBaseTransformer
  from neuraxle.data_container import DataContainer
label_desc: Use image node_id 6 for calling the OutputTransformerWrapper obj's underlying member method code with example usage: obj._set_expected_outputs(data_container, new_expected_outputs_data_container, context) and returns: data_container