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: Given context and candidate, augment the context with the new candidate.
  
  This is generally the input for the predictor model.
  
  :param full_context:
      dialogue context:
  :param candidate:
      candidate response
  :param include_context:
      Whether to include the context utterances (as defined by self.is_context())
  
  :return augmented_context:
      return the augmented context.
docstr_tok: ["Given","context","and","candidate",",","augment","the","context","with","the","new","candidate",".","This","is","generally","the","input","for","the","predictor","model",".",":","param","full_context",":","dialogue","context",":",":","param","candidate",":","candidate","response",":","param","include_context",":","Whether","to","include","the","context","utterances","(","as","defined","by","self.is_context","(",")",")",":","return","augmented_context",":","return","the","augmented","context","."]
code: def augment_context(
      self, full_context: str, candidate: str, include_context: bool
  ) -> List[str]:
      """
      Given context and candidate, augment the context with the new candidate.
  
      This is generally the input for the predictor model.
  
      :param full_context:
          dialogue context:
      :param candidate:
          candidate response
      :param include_context:
          Whether to include the context utterances (as defined by self.is_context())
  
      :return augmented_context:
          return the augmented context.
      """
      utterances = self.get_utterances_from_full_context(
          full_context, include_context=include_context
      )
  
      utterances.append(candidate)
      return utterances
  
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 6 for calling the AbstractReranker obj's underlying member method code with example usage: obj.augment_context(full_context, candidate, include_context) and returns: utterances