code: def test_from_pretrained_hub(self):
      model, loading_info = UNet2DModel.from_pretrained(
          "fusing/unet-ldm-dummy-update", output_loading_info=True
      )
  
      self.assertIsNotNone(model)
      self.assertEqual(len(loading_info["missing_keys"]), 0)
  
      model.to(torch_device)
      image = model(**self.dummy_input).sample
  
      assert image is not None, "Make sure output is not None"
  
imports: import gc
  import math
  import unittest
  import torch
  from diffusers import UNet2DModel
  from diffusers.utils import logging
  from diffusers.utils.testing_utils import enable_full_determinism, floats_tensor, require_torch_accelerator, slow, torch_all_close, torch_device
  from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
label_desc: Use image node_id 5 for calling the UNetLDMModelTests obj's underlying member method code with example usage: obj.test_from_pretrained_hub() without return types