class_docstr: Tests the correctness of the Y = Chain(bij1, bij2, bij3) transformation.
code: def testChainIldjWithPlaceholder(self):
      bijector = chain.Chain((exp.Exp(), exp.Exp()))
      samples = tf1.placeholder_with_default(
          np.zeros([2, 10], np.float32), shape=None
      )
      ildj = bijector.inverse_log_det_jacobian(samples, event_ndims=0)
      self.assertIsNotNone(ildj)
      self.evaluate(ildj)
  
imports: import mock
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import inline
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import joint_map
  from tensorflow_probability.python.bijectors import restructure
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import scale_matvec_diag
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.bijectors import split
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 16 for calling the ChainBijectorTest obj's underlying member method code with example usage: obj.testChainIldjWithPlaceholder() without return types