code: def _fetch_human_evaluation_results(
      eval_cache_path: str, file_name: str
  ) -> Dict:
      """Downloads the human evaluation results from CodaLab."""
      target_path: str = os.path.join(eval_cache_path, file_name)
      ensure_file_downloaded(
          source_url=HUMAN_EVAL_CODALAB_LINK.format(
              file_name=file_name
          ),
          target_path=target_path,
      )
      with open(target_path) as f:
          return json.load(f)
  
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 3 for calling a global function with example usage: _fetch_human_evaluation_results(eval_cache_path, file_name) and returns: json