code: def test_hypersparse_query():
      g = dgl.graph([])
      g = g.to(F.ctx())
      g.add_nodes(1000001)
      g.add_edges([0], [1])
      for i in range(10):
          assert g.has_nodes(i)
      assert not g.has_nodes(1000002)
      assert g.edge_ids(0, 1) == 0
      src, dst = g.find_edges([0])
      src, dst, eid = g.in_edges(1, form="all")
      src, dst, eid = g.out_edges(0, form="all")
      src, dst = g.edges()
      assert g.in_degrees(0) == 0
      assert g.in_degrees(1) == 1
      assert g.out_degrees(0) == 1
      assert g.out_degrees(1) == 0
  
imports: import math
  import numbers
  import backend
  import dgl
  import networkx
  import numpy
  import pytest
  import scipy.sparse
  from dgl import DGLError
label_desc: Use image node_id 13 for calling a global function with example usage: test_hypersparse_query() without return types