code: def test_inference_ctc_robust_batched(self):
      model = TFHubertForCTC.from_pretrained(
          "facebook/hubert-large-ls960-ft"
      )
      processor = Wav2Vec2Processor.from_pretrained(
          "facebook/hubert-large-ls960-ft", do_lower_case=True
      )
  
      input_speech = self._load_datasamples(4)
  
      inputs = processor(
          input_speech,
          return_tensors="tf",
          padding=True,
          sampling_rate=16000,
      )
  
      input_values = inputs.input_values
      attention_mask = inputs.attention_mask
  
      logits = model(input_values, attention_mask=attention_mask).logits
  
      predicted_ids = tf.argmax(logits, axis=-1)
      predicted_trans = processor.batch_decode(predicted_ids)
  
      EXPECTED_TRANSCRIPTIONS = [
          "a man said to the universe sir i exist",
          "sweat covered brion's body trickling into the tight loin cloth that was the only garment he wore",
          "the cut on his chest still dripping blood the ache of his overstrained eyes even the soaring arena around"
          " him with the thousands of spectators were trivialities not worth thinking about",
          "his instant of panic was followed by a small sharp blow high on his chest",
      ]
      self.assertListEqual(predicted_trans, EXPECTED_TRANSCRIPTIONS)
  
imports: import copy
  import inspect
  import math
  import unittest
  import numpy
  import pytest
  from transformers import is_tf_available
  from transformers.testing_utils import require_soundfile, require_tf, slow
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
label_desc: Use image node_id 4 for calling the TFHubertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_ctc_robust_batched() without return types