code: def cifar_like_data():
      return torch.rand(3, 3, 32, 32).to(device)
  
imports: import numpy
  import pytest
  import torch
  from pythae.models import AEConfig, VAEConfig
  from pythae.models.nn.benchmarks.celeba import *
  from pythae.models.nn.benchmarks.cifar import *
  from pythae.models.nn.benchmarks.mnist import *
  from pythae.models.nn.default_architectures import *
label_desc: Use image node_id 4 for calling a global function with example usage: cifar_like_data() and returns: torch