code: def test_sinc_filters():
      filters = SincConv(
          in_channels=1,
          out_channels=128,
          kernel_size=101,
          stride=1,
          fs=16000,
      )
      x = torch.randn([50, 1, 400], requires_grad=True)
      y = filters(x)
      assert y.shape == torch.Size([50, 128, 300])
      # now test multichannel
      filters = SincConv(
          in_channels=2,
          out_channels=128,
          kernel_size=101,
          stride=1,
          fs=16000,
      )
      x = torch.randn([50, 2, 400], requires_grad=True)
      y = filters(x)
      assert y.shape == torch.Size([50, 128, 300])
  
imports: import torch
  from espnet2.layers.sinc_conv import BarkScale, LogCompression, MelScale, SincConv
label_desc: Use image node_id 2 for calling a global function with example usage: test_sinc_filters() without return types