code: def testDistribution(self, dist_name, data):
      if dist_name in STATISTIC_CONSISTENT_SHAPES_TEST_BLOCK_LIST:
          self.skipTest("{} is blocked".format(dist_name))
  
      def eligibility_filter(name):
          return name not in STATISTIC_CONSISTENT_SHAPES_TEST_BLOCK_LIST
  
      dist = data.draw(
          dhps.distributions(
              dist_name=dist_name,
              eligibility_filter=eligibility_filter,
              enable_vars=False,
              validate_args=False,
          )
      )
      hp.note(
          "Trying distribution {}".format(
              self.evaluate_dict(dist.parameters)
          )
      )
  
      for statistic in ["mean", "mode", "stddev", "variance"]:
          hp.note("Testing {}.{}".format(dist_name, statistic))
          self.check_statistic(
              dist,
              statistic,
              dist.batch_shape + dist.event_shape,
              tf.concat(
                  [
                      dist.batch_shape_tensor(),
                      dist.event_shape_tensor(),
                  ],
                  axis=0,
              ),
          )
      hp.note("Testing {}.covariance".format(dist_name))
      self.check_statistic(
          dist,
          "covariance",
          dist.batch_shape + dist.event_shape + dist.event_shape,
          tf.concat(
              [
                  dist.batch_shape_tensor(),
                  dist.event_shape_tensor(),
                  dist.event_shape_tensor(),
              ],
              axis=0,
          ),
      )
      hp.note("Testing {}.entropy".format(dist_name))
      self.check_statistic(
          dist, "entropy", dist.batch_shape, dist.batch_shape_tensor()
      )
  
imports: import collections
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python import distributions
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import expm1
  from tensorflow_probability.python.bijectors import normal_cdf
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensor_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.math.psd_kernels import hypothesis_testlib
label_desc: Use image node_id 1 for calling the StatisticConsistentShapesTest obj's underlying member method code with example usage: obj.testDistribution(dist_name, data) and returns: unknown