code: def _request_state(prediction: str, options: List[_Option]):
      references = [
          Reference(
              output=Output(text=option.text),
              tags=[CORRECT_TAG] if option.is_correct else [],
          )
          for option in options
      ]
      return RequestState(
          instance=Instance(
              input=Input(text=""), references=references
          ),
          reference_index=None,
          request_mode=None,
          train_trial_index=0,
          output_mapping=None,
          request=Request(),
          result=RequestResult(
              success=True,
              embedding=[],
              completions=[
                  Sequence(text=prediction, logprob=0.0, tokens=[])
              ],
              cached=False,
          ),
          num_train_instances=0,
          prompt_truncated=False,
      )
  
file_path: H2O/h2o_hf/helm/src/helm/benchmark/metrics/test_classification_metrics.py
imports: from collections import defaultdict
  from typing import Dict, List, NamedTuple
  from pytest import approx
  from helm.benchmark.adaptation.request_state import RequestState
  from helm.benchmark.metrics.classification_metrics import ClassificationMetric
  from helm.benchmark.metrics.statistic import Stat
  from helm.benchmark.scenarios.scenario import Input, Instance, Output, Reference, CORRECT_TAG
  from helm.common.request import Request, RequestResult, Sequence
label_desc: Use image node_id 1 for calling a global function with example usage: _request_state(prediction, options) and returns: RequestState