code: def wh_aware(self):
      data_line_new = []
      wh_ratio = []
      for lins in self.data_lines:
          data_line_new.append(lins)
          lins = lins.decode("utf-8")
          name, label, w, h = lins.strip("\n").split(self.delimiter)
          wh_ratio.append(float(w) / float(h))
  
      self.data_lines = data_line_new
      self.wh_ratio = np.array(wh_ratio)
      self.wh_ratio_sort = np.argsort(self.wh_ratio)
      self.data_idx_order_list = list(range(len(self.data_lines)))
  
imports: import numpy
  import cv2
  import math
  import os
  import json
  import random
  import traceback
  from paddle.io import Dataset
  from .imaug import transform, create_operators
label_desc: Use image node_id 2 for calling the MultiScaleDataSet obj's underlying member method code with example usage: obj.wh_aware() without return types