code: def dummy_renderer(self):
      torch.manual_seed(0)
  
      model_kwargs = {
          "param_shapes": (
              (self.renderer_dim, 93),
              (self.renderer_dim, 8),
              (self.renderer_dim, 8),
              (self.renderer_dim, 8),
          ),
          "d_latent": self.time_input_dim,
          "d_hidden": self.renderer_dim,
          "n_output": 12,
          "background": (
              0.1,
              0.1,
              0.1,
          ),
      }
      model = ShapERenderer(**model_kwargs)
      return model
  
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 8 for calling the ShapEPipelineFastTests obj's underlying member method code with example usage: obj.dummy_renderer() and returns: model