code: def test_mode(num_edges, backend):
      pyro.set_rng_seed(2**32 - num_edges)
      E = num_edges
      V = 1 + E
      K = V * (V - 1) // 2
      edge_logits = torch.randn(K)
      d = SpanningTree(
          edge_logits, sampler_options={"backend": backend}
      )
      with xfail_if_not_implemented():
          support = d.enumerate_support()
      v1 = support[..., 0]
      v2 = support[..., 1]
      k = v1 + v2 * (v2 - 1) // 2
      expected = support[edge_logits[k].sum(-1).argmax(0)]
      actual = d.mode
      assert (actual == expected).all()
  
file_path: pyro/tests/distributions/test_spanning_tree.py
imports: import logging
  import os
  from collections import Counter
  import pytest
  import torch
  import pyro
  from pyro.distributions.spanning_tree import NUM_SPANNING_TREES, SpanningTree, find_best_tree, make_complete_graph, sample_tree
  from tests.common import assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 9 for calling a global function with example usage: test_mode(num_edges, backend) without return types