code: def loglikelihood(self, requests):
      res = []
  
      for ctx, cont in requests:
          res.append((-random.random(), False))
          self.tokencost += len(self.tokenizer.tokenize(ctx + cont))
  
      return res
  
file_path: lm-evaluation-harness/scripts/cost_estimate.py
imports: import random
  import transformers
  from lm_eval import tasks, evaluator
  from lm_eval.base import LM
label_desc: Use image node_id 3 for calling the DryrunLM obj's underlying member method code with example usage: obj.loglikelihood(requests) and returns: res