code: def testInferredBatchShapeMatchesTrueBatchShape(
      self, dist_name, data
  ):
      with tfp_hps.no_cholesky_decomposition_errors():
  
          def eligibility_filter(name):
              return name not in TF1_GRAPH_MODE_BROKEN
  
          dist = data.draw(
              dhps.distributions(
                  dist_name=dist_name,
                  eligibility_filter=eligibility_filter,
                  validate_args=False,
              )
          )
          with tfp_hps.no_tf_rank_errors():
              lp = dist.log_prob(
                  dist.sample(seed=test_util.test_seed())
              )
  
      self.assertAllEqual(dist.batch_shape_tensor(), tf.shape(lp))
      self.assertAllEqual(dist.batch_shape, tf.shape(lp))
  
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 2 for calling the ParameterPropertiesTest obj's underlying member method code with example usage: obj.testInferredBatchShapeMatchesTrueBatchShape(dist_name, data) and returns: unknown