code: def load_data_stats(self, path_data_stats):
      stats = pickle.load(open(path_data_stats, "rb"))
      self.path_data_stats = path_data_stats
  
      self.set_data_stats(
          np.asarray(stats["Xmn"]),
          stats["sv1"],
          stats["Xsd"],
          stats["ymn"],
          stats["ysd"],
      )
  
      if self.storage_level == constants.StorageLevel.DISK and hasattr(
          self, "path_mappings"
      ):
          if "ix_statistics" in stats:
              self.ix_statistics = stats["ix_statistics"]
          else:
              self.ix_statistics = range(self.N)
  
      self.set_return_raw(False)
  
imports: import os
  import pickle
  import sys
  import time
  import numpy
  import scipy.sparse
  from sklearn.datasets import load_svmlight_file
  import torch
  from torch.utils.data import DataLoader, Dataset
  from torch.utils.data.dataloader import _SingleProcessDataLoaderIter, _MultiProcessingDataLoaderIter, _utils
  from .None import constants
  from .None import syssettings
label_desc: Use image node_id 7 for calling the PrepareData obj's underlying member method code with example usage: obj.load_data_stats(path_data_stats) without return types