docstr: 10 flod
docstr_tok: ["10","flod"]
code: def _split_fold10(self, labels, fold_idx=0, seed=0, shuffle=True):
      """10 flod"""
      assert 0 <= fold_idx and fold_idx < 10, print(
          "fold_idx must be from 0 to 9."
      )
  
      skf = StratifiedKFold(
          n_splits=10, shuffle=shuffle, random_state=seed
      )
      idx_list = []
      for idx in skf.split(
          np.zeros(len(labels)), [label.asnumpy() for label in labels]
      ):  # split(x, y)
          idx_list.append(idx)
      train_idx, valid_idx = idx_list[fold_idx]
  
      print(
          "train_set : test_set = %d : %d",
          len(train_idx),
          len(valid_idx),
      )
  
      return train_idx, valid_idx
  
file_path: dgl/examples/mxnet/gin/dataloader.py
imports: import math
  import dgl
  import numpy
  from mxnet import nd
  from mxnet.gluon.data import DataLoader, Sampler
  from sklearn.model_selection import StratifiedKFold
label_desc: Use image node_id 3 for calling the GraphDataLoader obj's underlying member method code with example usage: obj._split_fold10(labels, fold_idx, seed, shuffle) and returns: train_idx,  valid_idx