code: def test_feed_forward_chunking(self):
      (
          init_dict,
          inputs_dict,
      ) = self.prepare_init_args_and_inputs_for_common()
      init_dict["norm_num_groups"] = 32
  
      model = self.model_class(**init_dict)
      model.to(torch_device)
      model.eval()
  
      with torch.no_grad():
          output = model(**inputs_dict)[0]
  
      model.enable_forward_chunking()
      with torch.no_grad():
          output_2 = model(**inputs_dict)[0]
  
      self.assertEqual(
          output.shape, output_2.shape, "Shape doesn't match"
      )
      assert np.abs(output.cpu() - output_2.cpu()).max() < 1e-2
  
imports: import copy
  import os
  import tempfile
  import unittest
  import numpy
  import torch
  from diffusers import MotionAdapter, UNet2DConditionModel, UNetMotionModel
  from diffusers.utils import logging
  from diffusers.utils.import_utils import is_xformers_available
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, torch_device
  from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
label_desc: Use image node_id 11 for calling the UNetMotionModelTests obj's underlying member method code with example usage: obj.test_feed_forward_chunking() without return types