code: def find_edges_test(g, orig_nid_map):
      etypes = g.canonical_etypes
  
      etype_eids_uv_map = dict()
      for u_type, etype, v_type in etypes:
          orig_u = g.edges[etype].data["edge_u"]
          orig_v = g.edges[etype].data["edge_v"]
          eids = F.tensor(
              np.random.randint(g.num_edges(etype), size=100)
          )
          u, v = g.find_edges(eids, etype=etype)
          assert F.allclose(orig_nid_map[u_type][u], orig_u[eids])
          assert F.allclose(orig_nid_map[v_type][v], orig_v[eids])
          etype_eids_uv_map[etype] = (eids, F.cat([u, v], dim=0))
      return etype_eids_uv_map
  
imports: import json
  import os
  from itertools import product
  import dgl
  import dgl.backend
  import numpy
  from dgl.distributed import edge_split, load_partition_book, node_split
label_desc: Use image node_id 8 for calling a global function with example usage: find_edges_test(g, orig_nid_map) and returns: etype_eids_uv_map