code: def test_unbatched_inputs_outputs(self):
      (
          config,
          inputs,
      ) = self.model_tester.prepare_config_and_inputs_for_common()
  
      for model_class in self.all_model_classes:
          model = model_class(config)
          model.to(torch_device)
          model.eval()
  
          with torch.no_grad():
              outputs = model(
                  inputs["input_features"].to(torch_device),
                  inputs["noise_sequence"].to(torch_device),
              )[0]
          self.assertTrue(
              outputs.shape[0] == 1,
              msg="Unbatched input should create batched output with bsz = 1",
          )
  
imports: import gc
  import inspect
  import random
  import unittest
  from datasets import Audio, load_dataset
  from transformers import UnivNetConfig, UnivNetFeatureExtractor
  from transformers.testing_utils import is_torch_available, require_torch, require_torch_gpu, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, floats_tensor
label_desc: Use image node_id 12 for calling the UnivNetModelTest obj's underlying member method code with example usage: obj.test_unbatched_inputs_outputs() without return types