code: def test_x_conv():
      x = torch.randn(8, 16)
      pos = torch.rand(8, 3)
      batch = torch.tensor([0, 0, 0, 0, 1, 1, 1, 1])
  
      conv = XConv(16, 32, dim=3, kernel_size=2, dilation=2)
      assert str(conv) == "XConv(16, 32)"
  
      torch.manual_seed(12345)
      out1 = conv(x, pos)
      assert out1.size() == (8, 32)
  
      torch.manual_seed(12345)
      out2 = conv(x, pos, batch)
      assert out2.size() == (8, 32)
  
      if is_full_test():
          jit = torch.jit.script(conv)
  
          torch.manual_seed(12345)
          assert torch.allclose(jit(x, pos), out1, atol=1e-6)
  
          torch.manual_seed(12345)
          assert torch.allclose(jit(x, pos, batch), out2, atol=1e-6)
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_x_conv() without return types