code: def create_and_check_for_image_segmentation(
      self, config, pixel_values, labels, pixel_labels
  ):
      config.num_labels = self.num_labels
      model = TFData2VecVisionForSemanticSegmentation(config)
      result = model(pixel_values, training=False)
      self.parent.assertEqual(
          result.logits.shape,
          (
              self.batch_size,
              self.num_labels,
              self.image_size * 2,
              self.image_size * 2,
          ),
      )
      result = model(pixel_values, labels=pixel_labels)
      self.parent.assertEqual(
          result.logits.shape,
          (
              self.batch_size,
              self.num_labels,
              self.image_size * 2,
              self.image_size * 2,
          ),
      )
  
imports: import collections.abc
  import inspect
  import unittest
  import numpy
  from transformers import Data2VecVisionConfig
  from transformers.file_utils import cached_property, is_tf_available, is_vision_available
  from transformers.testing_utils import require_tf, require_vision, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 6 for calling the TFData2VecVisionModelTester obj's underlying member method code with example usage: obj.create_and_check_for_image_segmentation(config, pixel_values, labels, pixel_labels) without return types