code: def test_inference_ctc_normal_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(2)
  
      input_values = processor(
          input_speech,
          return_tensors="tf",
          padding=True,
          sampling_rate=16000,
      ).input_values
  
      logits = model(input_values).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",
      ]
      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 3 for calling the TFHubertModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_ctc_normal_batched() without return types