code: def test_melgan_feature_loss():
      feats_real = []
      feats_fake = []
  
      # if all the features are different.
      for _ in range(5):  # different scales
          scale_feats_real = []
          scale_feats_fake = []
          for _ in range(4):  # different layers
              scale_feats_real.append(torch.rand([3, 5, 7]))
              scale_feats_fake.append(torch.rand([3, 5, 7]))
          feats_real.append(scale_feats_real)
          feats_fake.append(scale_feats_fake)
  
      loss_func = MelganFeatureLoss()
      loss = loss_func(feats_fake, feats_real)
      assert loss.item() <= 1.0
  
      feats_real = []
      feats_fake = []
  
      # if all the features are the same
      for _ in range(5):  # different scales
          scale_feats_real = []
          scale_feats_fake = []
          for _ in range(4):  # different layers
              tensor = torch.rand([3, 5, 7])
              scale_feats_real.append(tensor)
              scale_feats_fake.append(tensor)
          feats_real.append(scale_feats_real)
          feats_fake.append(scale_feats_fake)
  
      loss_func = MelganFeatureLoss()
      loss = loss_func(feats_fake, feats_real)
      assert loss.item() == 0
  
file_path: TTS/tests/vocoder_tests/test_vocoder_losses.py
imports: import os
  import torch
  from tests import get_tests_input_path, get_tests_output_path, get_tests_path
  from TTS.config import BaseAudioConfig
  from TTS.utils.audio import AudioProcessor
  from TTS.utils.audio.numpy_transforms import stft
  from TTS.vocoder.layers.losses import MelganFeatureLoss, MultiScaleSTFTLoss, STFTLoss, TorchSTFT
label_desc: Use image node_id 4 for calling a global function with example usage: test_melgan_feature_loss() without return types