code: def testEventNdimsIsStaticWhenPossible(self):
      ind = independent.Independent(
          distribution=normal.Normal(
              loc=tf1.placeholder_with_default([2.0], shape=None),
              scale=tf1.placeholder_with_default(1.0, shape=None),
          ),
          reinterpreted_batch_ndims=1,
          validate_args=True,
      )
      # Even though `event_shape` is not static, event_ndims must equal
      # `reinterpreted_batch_ndims + rank(distribution.event_shape)`.
      self.assertEqual(tensorshape_util.rank(ind.event_shape), 1)
  
imports: import functools
  import os
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import exponential
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import log_prob_ratio
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 6 for calling the IndependentDistributionTest obj's underlying member method code with example usage: obj.testEventNdimsIsStaticWhenPossible() without return types