code: def pytorch_shufflenetv2(request: Any) -> ModelAndData:
      if request.config.option.skipslow:
          pytest.skip()
  
      import torchvision.models as models
  
      model = models.shufflenet_v2_x0_5(pretrained=True).eval()
      preprocessing = dict(
          mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225], axis=-3
      )
      fmodel = fbn.PyTorchModel(
          model, bounds=(0, 1), preprocessing=preprocessing
      )
  
      x, y = fbn.samples(fmodel, dataset="imagenet", batchsize=8)
      x = ep.astensor(x)
      y = ep.astensor(y)
      return fmodel, x, y
  
imports: from typing import Optional, Callable, Tuple, Dict, Any, List, NamedTuple
  import functools
  import pytest
  import eagerpy
  import foolbox
  import foolbox
label_desc: Use image node_id 12 for calling a global function with example usage: pytorch_shufflenetv2(request) and returns: fmodel,  x,  y