docstr: Test analysis and synthesis transform result in a perfect reconstruction.
          
code: def test_audio_to_spectrogram_reconstruction(
      self, fft_length: int, num_channels: int
  ):
      """Test analysis and synthesis transform result in a perfect reconstruction."""
      batch_size = 4
      num_samples = fft_length * 50
      num_examples = 25
      random_seed = 42
      atol = 1e-6
  
      _rng = np.random.default_rng(seed=random_seed)
  
      hop_lengths = [fft_length // 2, fft_length // 4]
  
      for hop_length in hop_lengths:
          audio2spec = AudioToSpectrogram(
              fft_length=fft_length, hop_length=hop_length
          )
          spec2audio = SpectrogramToAudio(
              fft_length=fft_length, hop_length=hop_length
          )
  
          for n in range(num_examples):
              x = _rng.normal(
                  size=(batch_size, num_channels, num_samples)
              )
  
              x_spec, x_spec_length = audio2spec(input=torch.Tensor(x))
              x_hat, x_hat_length = spec2audio(
                  input=x_spec, input_length=x_spec_length
              )
  
              assert np.allclose(
                  x_hat.cpu().detach().numpy(), x, atol=atol
              ), f"Reconstructed not matching for example {n} (hop length {hop_length})"
  
file_path: NeMo/tests/collections/asr/test_audio_preprocessing.py
imports: import importlib
  import numpy
  import pytest
  import torch
  from nemo.collections.asr.modules.audio_preprocessing import AudioToSpectrogram, SpectrogramToAudio
label_desc: Use image node_id 3 for calling the TestAudioSpectrogram obj's underlying member method code with example usage: obj.test_audio_to_spectrogram_reconstruction(fft_length, num_channels) without return types