code: def test_inference(self):
      model_name = "openai/clip-vit-base-patch32"
      model = TFCLIPModel.from_pretrained(model_name)
      processor = CLIPProcessor.from_pretrained(model_name)
  
      image = prepare_img()
      inputs = processor(
          text=["a photo of a cat", "a photo of a dog"],
          images=image,
          padding=True,
          return_tensors="tf",
      )
  
      outputs = model(**inputs, training=False)
  
      # verify the logits
      self.assertEqual(
          outputs.logits_per_image.shape,
          tf.TensorShape(
              (inputs.pixel_values.shape[0], inputs.input_ids.shape[0])
          ),
      )
      self.assertEqual(
          outputs.logits_per_text.shape,
          tf.TensorShape(
              (inputs.input_ids.shape[0], inputs.pixel_values.shape[0])
          ),
      )
  
      expected_logits = tf.constant([[24.5701, 19.3049]])
  
      tf.debugging.assert_near(
          outputs.logits_per_image, expected_logits, atol=1e-3
      )
  
imports: import inspect
  import os
  import tempfile
  import unittest
  from importlib import import_module
  import requests
  from transformers import CLIPConfig, CLIPTextConfig, CLIPVisionConfig
  from transformers.testing_utils import require_tf, require_vision, slow
  from transformers.utils import is_tf_available, is_vision_available
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
label_desc: Use image node_id 1 for calling the TFCLIPModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference() without return types