code: def extract_stats(self):
      path_to_checkpoint = os.path.join(self._run_path, self.model_name)
      stats = torch.load(path_to_checkpoint)["stats"]
      self._stats = stats
      num_epoch = len(stats["train"])
      stats_dict = defaultdict(dict)
      for split_name in stats.keys():
          if len(stats[split_name]) > 0:
              latest_epoch = stats[split_name][-1]
              for metric_name in latest_epoch.keys():
                  if "best" in metric_name:
                      stats_dict[metric_name][
                          split_name
                      ] = latest_epoch[metric_name]
      return num_epoch, stats_dict
  
imports: import os
  from glob import glob
  from collections import defaultdict
  import torch
  from plyfile import PlyData, PlyElement
  from numpy.lib import recfunctions
  from torch_points3d.utils.colors import COLORS
  import numpy
label_desc: Use image node_id 12 for calling the ExperimentFolder obj's underlying member method code with example usage: obj.extract_stats() and returns: num_epoch,  stats_dict