code: def cv_split2(data, labels, nfold, valid_id):
      assert (nfold > 1) and (valid_id >= 0) and (valid_id < nfold)
      train_x = [x for i, x in enumerate(data) if i % nfold != valid_id]
      train_y = [
          y for i, y in enumerate(labels) if i % nfold != valid_id
      ]
      valid_x = [x for i, x in enumerate(data) if i % nfold == valid_id]
      valid_y = [
          y for i, y in enumerate(labels) if i % nfold == valid_id
      ]
      return train_x, train_y, valid_x, valid_y
  
imports: import gzip
  import os
  import sys
  import re
  import random
  import numpy
  import torch
label_desc: Use image node_id 10 for calling a global function with example usage: cv_split2(data, labels, nfold, valid_id) and returns: train_x,  train_y,  valid_x,  valid_y