code: def test_ConvEncoder_backward(channel, kernel_size, stride):
      encoder = ConvEncoder(
          channel=channel,
          kernel_size=kernel_size,
          stride=stride,
      )
  
      x = torch.rand(2, 32000)
      x_lens = torch.tensor([32000, 30000], dtype=torch.long)
      y, flens = encoder(x, x_lens)
      y.sum().backward()
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_ConvEncoder_backward(channel, kernel_size, stride) without return types