class_docstr: Tests the correctness of the Y = Chain(bij1, bij2, bij3) transformation.
code: def testNonCompositeTensor(self):
      e = exp.Exp()
      s = bijector_test_util.NonCompositeTensorScale(
          scale=tf.constant(3.0)
      )
      bijector = chain.Chain(bijectors=[e, s])
      self.assertNotIsInstance(
          bijector, tf.__internal__.CompositeTensor
      )
      self.assertAllClose(
          bijector.forward([1.0]), e.forward(s.forward([1.0]))
      )
  
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 21 for calling the ChainBijectorTest obj's underlying member method code with example usage: obj.testNonCompositeTensor() without return types