code: def _build_random_data(device, num_feat):
      node_nums = 3000
      edge_nums = 10000
  
      class Data:
          pass
  
      data = Data()
      data.x = torch.randn((node_nums, num_feat)).to(device)
      data.edge_index = torch.randint(0, node_nums, (2, edge_nums)).to(
          device
      )
      data.num_features = num_feat
      return data
  
imports: import logging
  from collections import OrderedDict
  import time
  import numpy
  import torch
  import nni.retiarii.nn.pytorch
  from nni.nas.pytorch.mutables import Mutable, InputChoice, LayerChoice
label_desc: Use image node_id 4 for calling a global function with example usage: _build_random_data(device, num_feat) and returns: data