code: def evaluate_generation(
      self,
      adapter_spec: AdapterSpec,
      request_state: RequestState,
      metric_service: MetricService,
      eval_cache_path: str,
  ) -> List[Stat]:
      reference = request_state.instance.references[0]
      reference = cast(CodeReference, reference)
      assert request_state.result is not None
      request_result: RequestResult = request_state.result
      metadata = reference.test_cases
      assert metadata is not None
      root = metadata.get("root")
  
      metrics = []
      for name in self.names:
          metric_fn = METRICS[name]
  
          best_score = 0.0
          for completion_sequence in request_result.completions:
              completion = completion_sequence.text.strip()
  
              # Similar to the logic in https://github.com/hendrycks/apps/blob/main/eval/test_one_solution.py
              # Running the testing code in a forked process prevents against annoying memory issues.
              shared_list = (
                  multiprocessing.Manager().list()
              )  # Create shared object to hold results.
              p = multiprocessing.Process(
                  target=_run_test_wrapper,
                  args=(root, completion, self.timeout, shared_list),
              )
              p.start()
              p.join(
                  timeout=11
              )  # Same 'global' timeout used in original APPS codebase.
              if p.is_alive():
                  hlog(
                      f"Before kill thread count: {threading.active_count()} exitcode: {p.exitcode}"
                  )
                  p.kill()
                  p.join(timeout=60)
                  hlog(
                      f"After second join thread count: {threading.active_count()}. exitcode: {p.exitcode}"
                  )
                  assert (
                      not p.is_alive()
                  ), "The code process was still alive even after calling kill."
  
              if len(shared_list) == 0:
                  # Remark: ideally should consider all tests that failed;
                  # use the average number of tests here for simplicity
                  avg_number_tests = 21
                  shared_list = [[-1] * avg_number_tests]  # type: ignore
              scores = shared_list[0]
  
              scores = _convert_scores(
                  scores
              )  # Convert list of bool/int to list of ints.
              this_score = metric_fn(scores)
              if this_score > best_score:
                  best_score = this_score
          metrics.append(Stat(MetricName(name)).add(best_score))
      return metrics
  
imports: import threading
  import multiprocessing
  from typing import List, Union, Sequence, cast
  from helm.common.hierarchical_logger import hlog
  from helm.common.request import RequestResult
  from helm.benchmark.adaptation.scenario_state import ScenarioState
  from helm.benchmark.adaptation.request_state import RequestState
  from helm.benchmark.adaptation.adapter_spec import AdapterSpec
  from helm.benchmark.scenarios.code_scenario import CodeReference
  from .None import code_metrics_helper
  from .metric import Metric, MetricResult
  from .metric_service import MetricService
  from .metric_name import MetricName
  from .statistic import Stat
label_desc: Use image node_id 3 for calling the APPSMetric obj's underlying member method code with example usage: obj.evaluate_generation(adapter_spec, request_state, metric_service, eval_cache_path) and returns: metrics