code: def test_with_segmentation_maps_and_loss(self):
      dummy_model = OneFormerForUniversalSegmentation.from_pretrained(
          self.model_checkpoints
      )
      processor = self.default_processor
      processor.image_processor.num_text = (
          dummy_model.config.num_queries
          - dummy_model.config.text_encoder_n_ctx
      )
      dummy_model.config.is_training = True
      model = (
          OneFormerForUniversalSegmentation(dummy_model.config)
          .to(torch_device)
          .eval()
      )
      del dummy_model
  
      inputs = processor(
          [np.zeros((3, 512, 640)), np.zeros((3, 512, 640))],
          ["semantic", "semantic"],
          segmentation_maps=[
              np.zeros((384, 384)).astype(np.float32),
              np.zeros((384, 384)).astype(np.float32),
          ],
          return_tensors="pt",
      )
  
      inputs["pixel_values"] = inputs["pixel_values"].to(torch_device)
      inputs["task_inputs"] = inputs["task_inputs"].to(torch_device)
      inputs["text_inputs"] = inputs["text_inputs"].to(torch_device)
      inputs["mask_labels"] = [
          el.to(torch_device) for el in inputs["mask_labels"]
      ]
      inputs["class_labels"] = [
          el.to(torch_device) for el in inputs["class_labels"]
      ]
  
      with torch.no_grad():
          outputs = model(**inputs)
  
      self.assertTrue(outputs.loss is not None)
  
imports: import copy
  import inspect
  import unittest
  import numpy
  from tests.test_modeling_common import floats_tensor
  from transformers import OneFormerConfig, is_torch_available, is_vision_available
  from transformers.testing_utils import require_torch, require_torch_accelerator, require_torch_fp16, require_torch_multi_gpu, require_vision, slow, torch_device
  from transformers.utils import cached_property
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 6 for calling the OneFormerModelIntegrationTest obj's underlying member method code with example usage: obj.test_with_segmentation_maps_and_loss() without return types