code: def test_diff_group_norm():
      x = torch.randn(6, 16)
  
      norm = DiffGroupNorm(16, groups=4, lamda=0)
      assert str(norm) == "DiffGroupNorm(16, groups=4)"
  
      assert torch.allclose(norm(x), x)
  
      if is_full_test():
          jit = torch.jit.script(norm)
          assert torch.allclose(jit(x), x)
  
      norm = DiffGroupNorm(16, groups=4, lamda=0.01)
      assert str(norm) == "DiffGroupNorm(16, groups=4)"
  
      out = norm(x)
      assert out.size() == x.size()
  
      if is_full_test():
          jit = torch.jit.script(norm)
          assert torch.allclose(jit(x), out)
  
imports: import torch
  from torch_geometric.nn import DiffGroupNorm
  from torch_geometric.testing import is_full_test
label_desc: Use image node_id 1 for calling a global function with example usage: test_diff_group_norm() without return types