code: def test_inference_ctc_normal(self):
      model = Data2VecAudioForCTC.from_pretrained(
          "facebook/data2vec-audio-base-960h"
      )
      model.to(torch_device)
      processor = Wav2Vec2Processor.from_pretrained(
          "hf-internal-testing/tiny-random-wav2vec2", do_lower_case=True
      )
      input_speech = self._load_datasamples(1)
  
      input_values = processor(
          input_speech, return_tensors="pt"
      ).input_values.to(torch_device)
  
      with torch.no_grad():
          logits = model(input_values).logits
  
      predicted_ids = torch.argmax(logits, dim=-1)
      predicted_trans = processor.batch_decode(predicted_ids)
  
      EXPECTED_TRANSCRIPTIONS = [
          "a man said to the universe sir i exist"
      ]
      self.assertListEqual(predicted_trans, EXPECTED_TRANSCRIPTIONS)
  
imports: import math
  import unittest
  import numpy
  from datasets import load_dataset
  from tests.test_modeling_common import floats_tensor, ids_tensor, random_attention_mask
  from transformers import Data2VecAudioConfig, is_torch_available
  from transformers.testing_utils import is_pt_flax_cross_test, require_soundfile, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 3 for calling the Data2VecAudioModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_ctc_normal() without return types