code: def test_shap_e(self):
      device = "cpu"
  
      components = self.get_dummy_components()
  
      pipe = self.pipeline_class(**components)
      pipe = pipe.to(device)
  
      pipe.set_progress_bar_config(disable=None)
  
      output = pipe(**self.get_dummy_inputs(device))
      image = output.images[0]
      image = image.cpu().numpy()
      image_slice = image[-3:, -3:]
  
      assert image.shape == (32, 16)
  
      expected_slice = np.array(
          [
              -1.0000,
              -0.6241,
              1.0000,
              -0.8978,
              -0.6866,
              0.7876,
              -0.7473,
              -0.2874,
              0.6103,
          ]
      )
      assert np.abs(image_slice.flatten() - expected_slice).max() < 1e-2
  
imports: import gc
  import unittest
  import numpy
  import torch
  from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
  from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
  from diffusers.pipelines.shap_e import ShapERenderer
  from diffusers.utils.testing_utils import load_numpy, nightly, require_torch_gpu, torch_device
  from ..test_pipelines_common import PipelineTesterMixin, assert_mean_pixel_difference
label_desc: Use image node_id 11 for calling the ShapEPipelineFastTests obj's underlying member method code with example usage: obj.test_shap_e() without return types