code: def test_appnp_conv():
      g = dgl.from_networkx(nx.erdos_renyi_graph(20, 0.3)).to(F.ctx())
      ctx = F.ctx()
  
      appnp_conv = nn.APPNPConv(3, 0.1, 0)
      appnp_conv.initialize(ctx=ctx)
      print(appnp_conv)
  
      # test#1: basic
      h0 = F.randn((20, 10))
      h1 = appnp_conv(g, h0)
      assert h1.shape == (20, 10)
  
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 17 for calling a global function with example usage: test_appnp_conv() without return types