code: def LabelList(ratio=1, root="~/.mxnet/datasets", name="market1501"):
      """Load the Label List for Market 1501 dataset.
  
      Parameters
      ----------
      ratio : float, default 1
          Split label into train and test.
      root : str, default '~/.mxnet/datasets'
          Path to the folder stored the dataset.
      name : str, default 'market1501'
          Which dataset is used. Only support market 1501 now.
      """
      root = osp.expanduser(root)
  
      if name == "market1501":
          path = osp.join(root, "Market-1501-v15.09.15")
          train_txt = osp.join(path, "train.txt")
          image_path = osp.join(path, "bounding_box_train")
  
          item_list = [
              (
                  osp.join(image_path, line.split()[0]),
                  int(line.split()[1]),
              )
              for line in open(train_txt).readlines()
          ]
          random.shuffle(item_list)
          count = len(item_list)
          train_count = int(count * ratio)
  
          train_set = item_list[:train_count]
          valid_set = item_list[train_count:]
  
          return train_set, valid_set
      return None, None
  
label_desc: Use image node_id 1 for calling a global function with example usage: LabelList(ratio, root, name) and returns: None,  None, train_set,  valid_set