code: def test_update_all_0deg(idtype):
      # test#1
      g = dgl.graph(
          ([1, 2, 3, 4], [0, 0, 0, 0]), idtype=idtype, device=F.ctx()
      )
  
      def _message(edges):
          return {"m": edges.src["h"]}
  
      def _reduce(nodes):
          return {"x": nodes.data["h"] + F.sum(nodes.mailbox["m"], 1)}
  
      def _apply(nodes):
          return {"x": nodes.data["x"] * 2}
  
      def _init2(shape, dtype, ctx, ids):
          return 2 + F.zeros(shape, dtype, ctx)
  
      g.set_n_initializer(_init2, "x")
      old_repr = F.randn((5, 5))
      g.ndata["h"] = old_repr
      g.update_all(_message, _reduce, _apply)
      new_repr = g.ndata["x"]
      # the first row of the new_repr should be the sum of all the node
      # features; while the 0-deg nodes should be initialized by the
      # initializer and applied with UDF.
      assert F.allclose(new_repr[1:], 2 * (2 + F.zeros((4, 5))))
      assert F.allclose(new_repr[0], 2 * F.sum(old_repr, 0))
  
      # test#2: graph with no edge
      g = dgl.graph(
          ([], []), num_nodes=5, idtype=idtype, device=F.ctx()
      )
      g.ndata["h"] = old_repr
      # Intercepting the warning: The input graph for the user-defined edge
      # function does not contain valid edges.
      with warnings.catch_warnings():
          warnings.simplefilter("ignore", category=UserWarning)
          g.update_all(
              _message,
              _reduce,
              lambda nodes: {"h": nodes.data["h"] * 2},
          )
  
      new_repr = g.ndata["h"]
      # should fallback to apply
      assert F.allclose(new_repr, 2 * old_repr)
  
imports: import warnings
  from collections import defaultdict
  import backend
  import dgl
  import networkx
  import numpy
  from utils import parametrize_idtype
label_desc: Use image node_id 13 for calling a global function with example usage: test_update_all_0deg(idtype) and returns: dict, dict, dict, unknown