content: import argparse
  
  import numpy as np
  
  from evalplus.data import get_human_eval_plus, get_mbpp_plus
  
  if __name__ == "__main__":
      parser = argparse.ArgumentParser()
      parser.add_argument("--dataset", default="humaneval", choices=["mbpp", "humaneval"])
      parser.add_argument("--mini", action="store_true")
      args = parser.parse_args()
  
      print(f"Reporting stats for {args.dataset} dataset [ mini = {args.mini} ]")
      if args.dataset == "humaneval":
          data = get_human_eval_plus(mini=args.mini)
      elif args.dataset == "mbpp":
          data = get_mbpp_plus(mini=args.mini)
  
      sizes = np.array(
          [[len(inp["base_input"]), len(inp["plus_input"])] for inp in data.values()]
      )
      size_base = sizes[:, 0]
      print(f"{size_base.min() = }", f"{size_base.argmin() = }")
      print(f"{size_base.max() = }", f"{size_base.argmax() = }")
      print(f"{np.percentile(size_base, 50) = :.1f}")
      print(f"{size_base.mean() = :.1f}")
  
      size_plus = sizes[:, 1]
      size_plus += size_base
      print(f"{size_plus.min() = }", f"{size_plus.argmin() = }")
      print(f"{size_plus.max() = }", f"{size_plus.argmax() = }")
      print(f"{np.percentile(size_plus, 50) = :.1f}")
      print(f"{size_plus.mean() = :.1f}")
  