code: def greedy_cover(
      task_id: str, tests: Dict[str, List[Any]], exclude_model: str
  ) -> Tuple[str, List[str]]:
      q, U = [], set()
      for test_name, test_cover in tests.items():
          cover_set = set()
          for model_path, i_code in test_cover:
              if exclude_model not in model_path:
                  cover_set.add((model_path, i_code))
          q.append((test_name, cover_set))
          U = U.union(cover_set)
      # Greedy algorithm for min set cover
      min_cover = []
      while len(U) > 0:
          max_uncover_set, max_test_name = {}, ""
          for test_name, cover_set in q:
              if len(cover_set) > len(max_uncover_set):
                  max_uncover_set = cover_set
                  max_test_name = test_name
          min_cover.append(max_test_name)
          U = U - max_uncover_set
          qq = []
          for test_name, cover_set in q:
              new_cover_set = U.intersection(cover_set)
              if len(new_cover_set) != 0:
                  qq.append((test_name, new_cover_set))
          q = qq
      return task_id, min_cover
  
imports: import argparse
  import json
  import os
  import pickle
  from concurrent.futures import ProcessPoolExecutor, as_completed
  from copy import deepcopy
  from typing import Any, Dict, List, Optional, Tuple
  from rich.progress import track
  from evalplus.data import write_jsonl
  from tools.tsr.coverage_init import collect_coverage_info
  from tools.tsr.mutation_init import collect_mutation_info
  from tools.tsr.sample_init import collect_sample_info
  from tools.tsr.utils import get_problems, get_task_ids, to_path
label_desc: Use image node_id 3 for calling a global function with example usage: greedy_cover(task_id, tests, exclude_model) and returns: task_id,  min_cover