code: def generate_mixture(waveform_clean, waveform_noise, target_snr):
      power_clean_signal = waveform_clean.pow(2).mean()
      power_noise_signal = waveform_noise.pow(2).mean()
      current_snr = 10 * torch.log10(
          power_clean_signal / power_noise_signal
      )
      waveform_noise *= 10 ** (-(target_snr - current_snr) / 20)
      return waveform_clean + waveform_noise
  
file_path: audio/examples/tutorials/mvdr_tutorial.py
imports: import torch
  import torchaudio
  import torchaudio.functional
  import matplotlib.pyplot
  import mir_eval
  from IPython.display import Audio
  from pesq import pesq
  from pystoi import stoi
  from torchaudio.utils import download_asset
label_desc: Use image node_id 4 for calling a global function with example usage: generate_mixture(waveform_clean, waveform_noise, target_snr) and returns: unknown