code: def _build_query_representation(
      cls, query: str, dictionary: DictionaryAgent
  ) -> Dict[str, Any]:
      rep = {}
      rep["words"] = {}
      words = [w for w in dictionary.tokenize(query.lower())]
      rw = rep["words"]
      used = {}
      for w in words:
          rw[w] = 1.0 / (1.0 + math.log(1.0 + dictionary.freq[w]))
          used[w] = True
      rep["norm"] = math.sqrt(len(words))
      return rep
  
imports: import aiohttp
  import asyncio
  from enum import Enum
  import json
  import math
  from nltk.corpus import stopwords
  from nltk.tokenize import word_tokenize
  from nltk.stem import PorterStemmer
  import os
  import random
  import string
  import time
  from typing import List, Tuple, Optional, Dict, Any, Set, Union
  from parlai.agents.ir_baseline.ir_baseline import score_match, MaxPriorityQueue
  from parlai.core.dict import DictionaryAgent
  from parlai.core.message import Message
  from parlai.core.metrics import F1Metric
  from parlai.core.torch_generator_agent import PPLMetric
  import parlai.utils.logging
  import projects.bb3.constants
  import projects.bb3.prompts
  from projects.bb3.agents.module import Module
label_desc: Use image node_id 10 for calling the MemoryUtils obj's underlying member method code with example usage: obj._build_query_representation(cls, query, dictionary) and returns: rep