code: def disabled_testFailureCase(self):  # pylint: disable=invalid-name
      # TODO(b/140229057): This test should pass.
      dist = tfd.Chi(
          df=np.float32(27.744131) * np.ones((4,)).astype(np.float32)
      )
      dist = tfd.TransformedDistribution(
          bijector=normal_cdf.NormalCDF(), distribution=dist
      )
      dist = expm1.Expm1()(dist)
      samps = 1.7182817 + tf.zeros_like(
          dist.sample(seed=test_util.test_seed())
      )
      self.assertAllClose(
          dist.log_prob(samps)[0], dist[0].log_prob(samps[0])
      )
  
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 3 for calling the DistributionSlicingTest obj's underlying member method code with example usage: obj.disabled_testFailureCase() without return types