code: def test_inference_ctc_batched(self):
      model = SEWDForCTC.from_pretrained(
          "asapp/sew-d-tiny-100k-ft-ls100h"
      ).to(torch_device)
      processor = Wav2Vec2Processor.from_pretrained(
          "asapp/sew-d-tiny-100k-ft-ls100h", do_lower_case=True
      )
  
      input_speech = self._load_datasamples(2)
  
      inputs = processor(
          input_speech, return_tensors="pt", padding=True
      )
  
      input_values = inputs.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",
          "swet covered breon's body trickling into the titlowing closs that was the only garmened he war",
      ]
      self.assertListEqual(predicted_trans, EXPECTED_TRANSCRIPTIONS)
  
imports: import math
  import unittest
  import pytest
  from transformers import SEWDConfig, is_torch_available
  from transformers.testing_utils import require_soundfile, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_tensor, ids_tensor, random_attention_mask
  from ...test_pipeline_mixin import PipelineTesterMixin
label_desc: Use image node_id 3 for calling the SEWDModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_ctc_batched() without return types