old_contents: import torchaudio
  import librosa
  
  # resampling reference https://core.ac.uk/download/pdf/228298313.pdf
  # resampling input transformation defense for audio
  
  T = torchaudio.transforms
  audio_data = librosa.load(files, sr=16000)[0][-19456:]  # Read audio file
  audio_data = torch.tensor(audio_data).float().to(device)
  sample = T.Resample(
      16000, 8000, resampling_method="sinc_interpolation"
  )  # resample the audio files to 8kHz from 16kHz
  audio_resample_1 = sample(audio_data)
  sample = T.Resample(
      8000, 16000, resampling_method="sinc_interpolation"
  )  # resample the audio back to 16kHz
  audio_resample_2 = sample(audio_resample_1)
  # Give audio_resample_2 as input to the asr model
  
new_contents: import torchaudio
  import librosa
  
  
  # resampling reference https://core.ac.uk/download/pdf/228298313.pdf
  # resampling input transformation defense for audio
  
  T = torchaudio.transforms
  
  # Read audio file
  audio_data = librosa.load(files, sr=16000)[0][-19456:]
  
  audio_data = torch.tensor(audio_data).float().to(device)
  
  # Discarding samples from a waveform during downsampling could remove a significant portion of the adversarial perturbation,
  # thereby prevents an adversarial attack.
  
  # resample the audio files to 8kHz from 16kHz
  sample = T.Resample(16000, 8000, resampling_method="sinc_interpolation")
  
  audio_resample_1 = sample(audio_data)
  
  # resample the audio back to 16kHz
  sample = T.Resample(8000, 16000, resampling_method="sinc_interpolation")
  
  # Give audio_resample_2 as input to the asr model
  audio_resample_2 = sample(audio_resample_1)
  
subject: Update resampling.py