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: Return utterances to consider from context string.
  
  :param full_context:
      full context (or dialog history) to consider
  :param include_context:
      whether or not to include the context utterances (like "your persona:...")
  
  :return utterances:
      return list of utterances
docstr_tok: ["Return","utterances","to","consider","from","context","string",".",":","param","full_context",":","full","context","(","or","dialog","history",")","to","consider",":","param","include_context",":","whether","or","not","to","include","the","context","utterances","(","like","``","your","persona",":","...","''",")",":","return","utterances",":","return","list","of","utterances"]
code: def get_utterances_from_full_context(
      self, full_context: str, include_context: Optional[bool] = True
  ) -> List[str]:
      """
      Return utterances to consider from context string.
  
      :param full_context:
          full context (or dialog history) to consider
      :param include_context:
          whether or not to include the context utterances (like "your persona:...")
  
      :return utterances:
          return list of utterances
      """
      split_context = full_context.split(self.delimiter)
      context = [l for l in split_context if self.is_context(l)]
      dialogue = [l for l in split_context if not self.is_context(l)]
  
      if include_context:
          utterances = context + dialogue
      else:
          utterances = dialogue
      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 5 for calling the AbstractReranker obj's underlying member method code with example usage: obj.get_utterances_from_full_context(full_context, include_context) and returns: utterances