code: def test_inference_image_classification_head(self):
      model = TFSwinForImageClassification.from_pretrained(
          "microsoft/swin-tiny-patch4-window7-224"
      )
      feature_extractor = self.default_feature_extractor
  
      image = Image.open(
          "./tests/fixtures/tests_samples/COCO/000000039769.png"
      )
      inputs = feature_extractor(images=image, return_tensors="tf")
  
      # forward pass
      outputs = model(inputs)
  
      # verify the logits
      expected_shape = tf.TensorShape((1, 1000))
      self.assertEqual(outputs.logits.shape, expected_shape)
      expected_slice = tf.constant([-0.0948, -0.6454, -0.0921])
      self.assertTrue(
          np.allclose(outputs.logits[0, :3], expected_slice, atol=1e-4)
      )
  
imports: import inspect
  import unittest
  import numpy
  from transformers import SwinConfig
  from transformers.testing_utils import require_tf, require_vision, slow, to_2tuple, tooslow
  from transformers.utils import cached_property, is_tf_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor
label_desc: Use image node_id 2 for calling the TFSwinModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_image_classification_head() without return types