class_docstr: Wrapper step to transform both ids, data inputs, and expected output at the same time using classical fit and transform methods.
  It sends the data_inputs, and the expected_outputs to the wrapped step so that it can transform them.
  
  .. seealso::
      :class:`~neuraxle.base.BaseStep`,
      :class:`~neuraxle.base.ForceHandleOnlyMixin`
code: def __init__(self, wrapped):
      MetaStep.__init__(self, wrapped)
      ForceHandleOnlyMixin.__init__(self)
      _DidProcessIdsInputOutputHandlerMixin.__init__(self)
  
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 1 to create a new IdsInputAndOutputTransformerWrapper object from inherited base classes: _DidProcessIdsInputOutputHandlerMixin, ForceHandleOnlyMixin, MetaStep with example: obj = IdsInputAndOutputTransformerWrapper(wrapped)