code: def test_lightweight_sinc_convolutions_output_size():
      frontend = LightweightSincConvs()
      idim = 400
      # Get output dimension by making one inference.
      # The test vector that is used has dimensions (1, T, 1, idim).
      # T was set to idim without any special reason,
      in_test = torch.zeros((1, idim, 1, idim))
      out, _ = frontend.forward(in_test, [idim])
      odim = out.size(2)
      assert frontend.output_size() == odim
  
imports: import torch
  from espnet2.asr.preencoder.sinc import LightweightSincConvs, SpatialDropout
label_desc: Use image node_id 2 for calling a global function with example usage: test_lightweight_sinc_convolutions_output_size() without return types