code: def test_sg_conv(out_dim):
      g = dgl.from_networkx(nx.erdos_renyi_graph(20, 0.3)).to(F.ctx())
      g = dgl.add_self_loop(g)
      ctx = F.ctx()
  
      sgc = nn.SGConv(5, out_dim, 2)
      sgc.initialize(ctx=ctx)
      print(sgc)
  
      # test #1: basic
      h0 = F.randn((g.num_nodes(), 5))
      h1 = sgc(g, h0)
      assert h1.shape == (g.num_nodes(), out_dim)
  
imports: import backend
  import dgl
  import dgl.function
  import dgl.nn.mxnet
  import mxnet
  import networkx
  import numpy
  import pytest
  import scipy
  from mxnet import autograd, gluon, nd
  from utils import parametrize_idtype
  from utils.graph_cases import get_cases, random_bipartite, random_dglgraph, random_graph
label_desc: Use image node_id 29 for calling a global function with example usage: test_sg_conv(out_dim) without return types