code: def test_frontend_forward(normalize, window_fn, log, train):
      frontend = MelSpectrogramTorch(
          preemp=True,
          n_fft=512,
          log=log,
          win_length=400,
          hop_length=160,
          f_min=20,
          f_max=7600,
          n_mels=20,
          window_fn=window_fn,
          mel_scale="htk",
          normalize=normalize,
      )
      if train:
          frontend.train()
      else:
          frontend.eval()
      set_all_random_seed(14)
      x = torch.randn(2, 1000, requires_grad=True)
      x_lengths = torch.LongTensor([1000, 980])
      y, y_lengths = frontend(x, x_lengths)
  
imports: import pytest
  import torch
  from espnet2.asr.frontend.melspec_torch import MelSpectrogramTorch
  from espnet2.torch_utils.set_all_random_seed import set_all_random_seed
label_desc: Use image node_id 3 for calling a global function with example usage: test_frontend_forward(normalize, window_fn, log, train) without return types