code: def test_TimeWarp(x_lens, requires_grad):
      time_warp = TimeWarp(window=10)
      x = torch.randn(2, 100, 80, requires_grad=requires_grad)
      y, y_lens = time_warp(x, x_lens)
      if x_lens is not None:
          assert all(l1 == l2 for l1, l2 in zip(x_lens, y_lens))
      if requires_grad:
          y.sum().backward()
  
imports: import pytest
  import torch
  from espnet2.layers.time_warp import TimeWarp
label_desc: Use image node_id 1 for calling a global function with example usage: test_TimeWarp(x_lens, requires_grad) without return types