class_docstr: Tests the correctness of the Y = Chain(bij1, bij2, bij3) transformation.
code: def testNestedDtype(self):
      bijector = chain.Chain(
          [
              identity.Identity(),
              scale.Scale(tf.constant(2.0, tf.float64)),
              identity.Identity(),
          ]
      )
  
      self.assertAllClose(
          tf.constant([2, 4, 6], tf.float64),
          self.evaluate(bijector.forward([1, 2, 3])),
      )
  
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 3 for calling the ChainBijectorTest obj's underlying member method code with example usage: obj.testNestedDtype() without return types