class_docstr: This container identifies which methods need to be overridden in addition to
  the base container to enable use in the RLHF pipeline. These methods are not
  necessary for inference alone.
  
  NOTE: If you are using this feature with a container that
  also inherits from `MetaTensorContainer`, ensure that `MetaTensorContainer`
  is inherited before `HybridEngineContainer` in the class definition.
class_docstr_tok: ["This","container","identifies","which","methods","need","to","be","overridden","in","addition","to","the","base","container","to","enable","use","in","the","RLHF","pipeline",".","These","methods","are","not","necessary","for","inference","alone",".","NOTE",":","If","you","are","using","this","feature","with","a","container","that","also","inherits","from","`","MetaTensorContainer","`",",","ensure","that","`","MetaTensorContainer","`","is","inherited","before","`","HybridEngineContainer","`","in","the","class","definition","."]
docstr: If the views on certain parameters are largely incompatible, it may be necessary to do
  more substantial transformations to the parameters. This method should be overridden to
  transform the training format to what is necessary for inference.
docstr_tok: ["If","the","views","on","certain","parameters","are","largely","incompatible",",","it","may","be","necessary","to","do","more","substantial","transformations","to","the","parameters",".","This","method","should","be","overridden","to","transform","the","training","format","to","what","is","necessary","for","inference","."]
code: def transform_for_inference(self):
      """
      If the views on certain parameters are largely incompatible, it may be necessary to do
      more substantial transformations to the parameters. This method should be overridden to
      transform the training format to what is necessary for inference.
      """
      pass
  
imports: from abc import ABC, abstractmethod
  from typing import List, Tuple
  import torch
label_desc: Use image node_id 3 for calling the HybridEngineContainer obj's underlying member method code with example usage: obj.transform_for_inference() without return types