code: def write_summary(self):
      def _format_value(v):
          if isinstance(v, float):
              return "{:.4f}".format(v)
          elif isinstance(v, int):
              return "{:d}".format(v)
          else:
              return "{}".format(v)
  
      statistics = {
          "num_samples": self.num_samples_examined,
          "v_min": self.v_min,
          "v_max": self.v_max,
          "average_size": self.average_size,
          "valid_size_ratio": self.valid_size_ratio,
          "cycle_ratio": self.cycle_ratio,
          "valid_ratio": self.valid_ratio,
      }
  
      model_eval_path = os.path.join(self.dir, "model_eval.txt")
  
      with open(model_eval_path, "w") as f:
          for key, value in statistics.items():
              msg = "{}\t{}\n".format(key, _format_value(value))
              f.write(msg)
  
      print(
          "Saved model evaluation statistics to {}".format(
              model_eval_path
          )
      )
  
imports: import os
  import pickle
  import random
  import matplotlib.pyplot
  import networkx
  from torch.utils.data import Dataset
label_desc: Use image node_id 3 for calling the CycleModelEvaluation obj's underlying member method code with example usage: obj.write_summary() and returns: str, str, str