code: def test_from_unet2d(self):
      torch.manual_seed(0)
      unet2d = UNet2DConditionModel()
  
      torch.manual_seed(1)
      model = self.model_class.from_unet2d(unet2d)
      model_state_dict = model.state_dict()
  
      for param_name, param_value in unet2d.named_parameters():
          self.assertTrue(
              torch.equal(model_state_dict[param_name], param_value)
          )
  
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 5 for calling the UNetMotionModelTests obj's underlying member method code with example usage: obj.test_from_unet2d() without return types