code: def test_serialization(self):
      unet, ema_unet = self.get_models()
      (
          noisy_latents,
          timesteps,
          encoder_hidden_states,
      ) = self.get_dummy_inputs()
  
      with tempfile.TemporaryDirectory() as tmpdir:
          ema_unet.save_pretrained(tmpdir)
          loaded_unet = UNet2DConditionModel.from_pretrained(
              tmpdir, model_cls=UNet2DConditionModel
          )
          loaded_unet = loaded_unet.to(unet.device)
  
      # Since no EMA step has been performed the outputs should match.
      output = unet(
          noisy_latents, timesteps, encoder_hidden_states
      ).sample
      output_loaded = loaded_unet(
          noisy_latents, timesteps, encoder_hidden_states
      ).sample
  
      assert torch.allclose(output, output_loaded, atol=1e-4)
  
file_path: llmga/llmga/diffusers/tests/others/test_ema.py
imports: import tempfile
  import unittest
  import torch
  from diffusers import UNet2DConditionModel
  from diffusers.training_utils import EMAModel
  from diffusers.utils.testing_utils import enable_full_determinism, skip_mps, torch_device
label_desc: Use image node_id 9 for calling the EMAModelTests obj's underlying member method code with example usage: obj.test_serialization() without return types