code: def generate_graph(idtype, grad=False):
      """
      s, d, eid
      0, 1, 0
      1, 9, 1
      0, 2, 2
      2, 9, 3
      0, 3, 4
      3, 9, 5
      0, 4, 6
      4, 9, 7
      0, 5, 8
      5, 9, 9
      0, 6, 10
      6, 9, 11
      0, 7, 12
      7, 9, 13
      0, 8, 14
      8, 9, 15
      9, 0, 16
      """
      u = F.tensor([0, 1, 0, 2, 0, 3, 0, 4, 0, 5, 0, 6, 0, 7, 0, 8, 9])
      v = F.tensor([1, 9, 2, 9, 3, 9, 4, 9, 5, 9, 6, 9, 7, 9, 8, 9, 0])
      g = dgl.graph((u, v), idtype=idtype)
      assert g.device == F.ctx()
      ncol = F.randn((10, D))
      ecol = F.randn((17, D))
      if grad:
          ncol = F.attach_grad(ncol)
          ecol = F.attach_grad(ecol)
  
      g.ndata["h"] = ncol
      g.edata["w"] = ecol
      g.set_n_initializer(dgl.init.zero_initializer)
      g.set_e_initializer(dgl.init.zero_initializer)
      return g
  
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 5 for calling a global function with example usage: generate_graph(idtype, grad) and returns: g