code: def test_MaskAlongAxis(dim, replace_with_zero, requires_grad):
      freq_mask = MaskAlongAxis(
          dim=dim,
          mask_width_range=30,
          num_mask=2,
          replace_with_zero=replace_with_zero,
      )
      x = torch.randn(2, 100, 80, requires_grad=requires_grad)
      x_lens = torch.tensor([80, 78])
      y, y_lens = freq_mask(x, x_lens)
      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.mask_along_axis import MaskAlongAxis
label_desc: Use image node_id 1 for calling a global function with example usage: test_MaskAlongAxis(dim, replace_with_zero, requires_grad) without return types