code: def shuffle_data(data):
      num_points = data.pos.shape[0]
      shuffle_idx = torch.randperm(num_points)
      for key in set(data.keys):
          item = data[key]
          if torch.is_tensor(item) and num_points == item.shape[0]:
              data[key] = item[shuffle_idx]
      return data
  
imports: from typing import *
  import numpy
  import numpy
  import random
  import scipy
  import re
  import torch
  import logging
  import torch.nn.functional
  from torch_scatter import scatter_mean, scatter_add
  from torch_geometric.nn.pool.consecutive import consecutive_cluster
  from torch_geometric.nn import voxel_grid
  from torch_geometric.data import Data
  from torch_cluster import grid_cluster
label_desc: Use image node_id 1 for calling a global function with example usage: shuffle_data(data) and returns: data