code: def create_and_check_for_semantic_segmentation(
      self, config, pixel_values, labels, pixel_labels
  ):
      config.num_labels = self.num_labels
      model = TFMobileViTForSemanticSegmentation(config)
      expected_height = expected_width = (
          self.image_size // self.output_stride
      )
  
      result = model(pixel_values, training=False)
      self.parent.assertEqual(
          result.logits.shape,
          (
              self.batch_size,
              self.num_labels,
              expected_height,
              expected_width,
          ),
      )
  
      result = model(pixel_values, labels=pixel_labels, training=False)
      self.parent.assertEqual(
          result.logits.shape,
          (
              self.batch_size,
              self.num_labels,
              expected_height,
              expected_width,
          ),
      )
  
imports: from __future__ import annotations
  import inspect
  import unittest
  from transformers import MobileViTConfig
  from transformers.file_utils import is_tf_available, is_vision_available
  from transformers.testing_utils import require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 6 for calling the TFMobileViTModelTester obj's underlying member method code with example usage: obj.create_and_check_for_semantic_segmentation(config, pixel_values, labels, pixel_labels) without return types