code: def test_on_real_audio():
      """Test that metric works as expected on real audio signals."""
      rate, ref = wavfile.read(_SAMPLE_AUDIO_SPEECH)
      rate, deg = wavfile.read(_SAMPLE_AUDIO_SPEECH_BAB_DB)
      ref = torch.tensor(ref, dtype=torch.float32)
      deg = torch.tensor(deg, dtype=torch.float32)
      ref_stft = torch.stft(
          ref, n_fft=256, hop_length=128, return_complex=True
      )
      deg_stft = torch.stft(
          deg, n_fft=256, hop_length=128, return_complex=True
      )
  
      v = complex_scale_invariant_signal_noise_ratio(
          deg_stft, ref_stft, zero_mean=False
      )
      assert torch.allclose(
          v, torch.tensor(0.03019072115421295, dtype=v.dtype), atol=1e-4
      ), v
      v = complex_scale_invariant_signal_noise_ratio(
          deg_stft, ref_stft, zero_mean=True
      )
      assert torch.allclose(
          v,
          torch.tensor(0.030391741544008255, dtype=v.dtype),
          atol=1e-4,
      ), v
  
file_path: torchmetrics/tests/unittests/audio/test_c_si_snr.py
imports: import pytest
  import torch
  from scipy.io import wavfile
  from torchmetrics.audio import ComplexScaleInvariantSignalNoiseRatio
  from torchmetrics.functional.audio import complex_scale_invariant_signal_noise_ratio
  from unittests import BATCH_SIZE, NUM_BATCHES, _Input
  from unittests.audio import _SAMPLE_AUDIO_SPEECH, _SAMPLE_AUDIO_SPEECH_BAB_DB
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 1 for calling a global function with example usage: test_on_real_audio() without return types