code: def test_sample_shape_smoke(
      num_destins, sample_shape, dtype, bp_iters
  ):
      num_sources = 2 * num_destins
      logits = torch.randn(num_sources, num_destins, dtype=dtype)
      d = dist.OneTwoMatching(logits, bp_iters=bp_iters)
      with xfail_if_not_implemented():
          values = d.sample(sample_shape)
      assert values.shape == sample_shape + (num_sources,)
      assert d.support.check(values).all()
  
imports: import logging
  import math
  import pytest
  import torch
  import pyro.distributions
  from tests.common import assert_close, assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 4 for calling a global function with example usage: test_sample_shape_smoke(num_destins, sample_shape, dtype, bp_iters) without return types