code: def test_inference_classification_head(self):
      model = TFRobertaForSequenceClassification.from_pretrained(
          "roberta-large-mnli"
      )
  
      input_ids = tf.constant(
          [[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]]
      )
      output = model(input_ids)[0]
      expected_shape = [1, 3]
      self.assertEqual(list(output.numpy().shape), expected_shape)
      expected_tensor = tf.constant([[-0.9469, 0.3913, 0.5118]])
      self.assertTrue(
          numpy.allclose(
              output.numpy(), expected_tensor.numpy(), atol=1e-4
          )
      )
  
imports: import unittest
  from transformers import RobertaConfig, is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
  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 3 for calling the TFRobertaModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_classification_head() without return types