code: def test_inference_masked_lm_long(self):
      model = TFLongformerForMaskedLM.from_pretrained(
          "allenai/longformer-base-4096"
      )
  
      # 'Hello world! ' repeated 1000 times
      input_ids = tf.convert_to_tensor(
          [[0] + [20920, 232, 328, 1437] * 1000 + [2]], dtype=tf.int64
      )
  
      output = model(input_ids, labels=input_ids)
      loss = output.loss
      prediction_scores = output.logits
  
      expected_loss = tf.constant(0.0073798)
      expected_prediction_scores_sum = tf.constant(-610476600.0)
      expected_prediction_scores_mean = tf.constant(-3.03477)
  
      # assert close
      tf.debugging.assert_near(
          tf.reduce_mean(loss), expected_loss, rtol=1e-4, atol=1e-4
      )
      tf.debugging.assert_near(
          tf.reduce_sum(prediction_scores),
          expected_prediction_scores_sum,
          rtol=1e-4,
          atol=1e-4,
      )
      tf.debugging.assert_near(
          tf.reduce_mean(prediction_scores),
          expected_prediction_scores_mean,
          rtol=1e-4,
          atol=1e-4,
      )
  
imports: import unittest
  from transformers import is_tf_available
  from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow, tooslow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
label_desc: Use image node_id 11 for calling the TFLongformerModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_masked_lm_long() without return types