class_docstr: Re-ranker object which uses a predictor model to rerank candidates given.
  
  This AbstractReranker can be subclassed to use any classifier or ranking model as
  the predictor.
class_docstr_tok: ["Re-ranker","object","which","uses","a","predictor","model","to","rerank","candidates","given",".","This","AbstractReranker","can","be","subclassed","to","use","any","classifier","or","ranking","model","as","the","predictor","."]
docstr: The class from the predictor (classifier) that we will rerank to favor.
  
  This must correspond to an output from the predictor.
docstr_tok: ["The","class","from","the","predictor","(","classifier",")","that","we","will","rerank","to","favor",".","This","must","correspond","to","an","output","from","the","predictor","."]
code: def get_class_to_rerank_for(
      self, observation: Message, full_context: str
  ) -> str:
      """
      The class from the predictor (classifier) that we will rerank to favor.
  
      This must correspond to an output from the predictor.
      """
  
imports: import logging
  import torch
  from abc import ABC, abstractmethod, abstractclassmethod
  from typing import List, Optional, Tuple
  from parlai.agents.transformer.transformer import TransformerGeneratorAgent
  from parlai.core.agents import create_agent_from_model_file, Agent
  from parlai.core.build_data import modelzoo_path
  from parlai.core.message import Message
  from parlai.core.opt import Opt
  from parlai.core.params import ParlaiParser
  from parlai.core.torch_agent import TorchAgent
  from parlai.utils.strings import normalize_reply
  from parlai.utils.torch import argsort
  from parlai.agents.hugging_face.gpt2 import Gpt2Agent
  from projects.msc.agents.long_tga import TransformerVariantAgent
label_desc: Use image node_id 13 for calling the AbstractReranker obj's underlying member method code with example usage: obj.get_class_to_rerank_for(observation, full_context) without return types