code: def evaluate_generation(
      self,
      adapter_spec: AdapterSpec,
      request_state: RequestState,
      metric_service: MetricService,
      eval_cache_path: str,
  ) -> List[Stat]:
      metrics = []
      request_result: Optional[RequestResult] = request_state.result
      if request_result is not None:
          result = self._metric_fn(
              completions=request_result.completions,
              references=request_state.instance.references,
          )
          metrics.append(Stat(MetricName(self._name)).add(result))
      return metrics
  
imports: import json
  import os
  from typing import Dict, List, Optional
  import numpy
  from sacrebleu.metrics import BLEU
  from helm.common.general import ensure_file_downloaded
  from helm.common.request import RequestResult, Sequence
  from helm.benchmark.adaptation.request_state import RequestState
  from helm.benchmark.adaptation.adapter_spec import AdapterSpec
  from .metric import Metric
  from .metric_name import MetricName
  from .metric_service import MetricService
  from .statistic import Stat
label_desc: Use image node_id 2 for calling the DisinformationMetric obj's underlying member method code with example usage: obj.evaluate_generation(adapter_spec, request_state, metric_service, eval_cache_path) and returns: metrics