code: def test_batch_entropy_shape(dist):
      for idx in range(dist.get_num_test_data()):
          dist_params = dist.get_dist_params(idx)
          d = dist.pyro_dist(**dist_params)
          with xfail_if_not_implemented():
              # Get entropy shape after broadcasting.
              expected_shape = _log_prob_shape(d)
              entropy_obj = d.entropy()
              assert entropy_obj.size() == expected_shape
  
imports: import numpy
  import pytest
  import torch
  import pyro
  import pyro.distributions
  from pyro.distributions import TorchDistribution
  from pyro.distributions.testing.gof import auto_goodness_of_fit
  from pyro.distributions.util import broadcast_shape
  from tests.common import TEST_FAILURE_RATE, assert_close, assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 6 for calling a global function with example usage: test_batch_entropy_shape(dist) without return types