class_docstr: Tests the correctness of the Y = Chain(bij1, bij2, bij3) transformation.
code: def testDofValidationDoesNoHarm(self):
      # Chain with no change in degrees-of-freedom.
      bij = chain.Chain(
          [exp.Exp()], validate_args=True, validate_event_size=True
      )
      self.evaluate(bij.forward_log_det_jacobian([1.0, 2.0, 3.0], 1))
  
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 19 for calling the ChainBijectorTest obj's underlying member method code with example usage: obj.testDofValidationDoesNoHarm() without return types