code: def test_relaxed_binomial():
      total_count = torch.arange(1, 33)
      probs = torch.linspace(0.1, 0.9, 16).unsqueeze(-1)
  
      d1 = binomial_dist(total_count, probs)
      assert isinstance(d1, dist.ExtendedBinomial)
  
      with set_relaxed_distributions():
          d2 = binomial_dist(total_count, probs)
      assert isinstance(d2, dist.Normal)
      assert_close(d2.mean, d1.mean)
      assert_close(
          d2.variance, d1.variance.clamp(min=_RELAX_MIN_VARIANCE)
      )
  
imports: import math
  import pytest
  import torch
  from torch.distributions.transforms import SigmoidTransform
  import pyro.distributions
  from pyro.contrib.epidemiology import beta_binomial_dist, binomial_dist, infection_dist
  from pyro.contrib.epidemiology.distributions import _RELAX_MIN_VARIANCE, set_relaxed_distributions
  from tests.common import assert_close
label_desc: Use image node_id 10 for calling a global function with example usage: test_relaxed_binomial() without return types