code: def _kldiv(self, p_counter, q_counter) -> float:
      ptotal = sum(p_counter.values())
      qtotal = sum(q_counter.values())
      kldiv = 0.0
      for word, _ in p_counter.items():
          prob_p = p_counter[word] / ptotal
          prob_q = q_counter[word] / qtotal
          kldiv += prob_p * math.log(1e-20 + (prob_q / prob_p))
      return -kldiv
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  import json
  import math
  import os
  import torch
  import torch.nn.functional
  from collections import defaultdict, Counter
  from nltk import ngrams
  from parlai.core.torch_generator_agent import PPLMetric
  from parlai.agents.image_seq2seq.image_seq2seq import ImageSeq2seqAgent
  from parlai.agents.transformer.transformer import TransformerGeneratorAgent
  from parlai.core.metrics import AverageMetric, SumMetric, GlobalAverageMetric
  from parlai.utils.misc import round_sigfigs
  from parlai.utils.io import PathManager
label_desc: Use image node_id 2 for calling the _VocabUnlikelihoodTrait obj's underlying member method code with example usage: obj._kldiv(p_counter, q_counter) and returns: unknown