code: def test_sample_tree_mcmc_smoke(num_edges, backend):
      pyro.set_rng_seed(num_edges)
      E = num_edges
      V = 1 + E
      K = V * (V - 1) // 2
      edge_logits = torch.rand(K)
      edges = torch.tensor(
          [(v, v + 1) for v in range(V - 1)], dtype=torch.long
      )
      for _ in range(10 if backend == "cpp" or num_edges <= 30 else 1):
          edges = sample_tree(edge_logits, edges, backend=backend)
  
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 2 for calling a global function with example usage: test_sample_tree_mcmc_smoke(num_edges, backend) without return types