code: def shuffle(*arrays, **kwargs):
      require_indices = kwargs.get("indices", False)
  
      if len(set(len(x) for x in arrays)) != 1:
          raise ValueError(
              "All inputs to shuffle must have " "the same length."
          )
  
      shuffle_indices = np.arange(len(arrays[0]))
      np.random.shuffle(shuffle_indices)
  
      if len(arrays) == 1:
          result = arrays[0][shuffle_indices]
      else:
          result = tuple(x[shuffle_indices] for x in arrays)
  
      if require_indices:
          return result, shuffle_indices
      else:
          return result
  
imports: import paddle
  from paddle import nn, optimizer
  import numpy
  from paddle import log
  from dataloader import BasicDataset
  from paddle.io import Dataset
  from time import time
  from sklearn.metrics import roc_auc_score
  import random
  import os
  from tqdm import tqdm
label_desc: Use image node_id 2 for calling a global function with example usage: shuffle() and returns: result,  shuffle_indices, result