code: def testCompositeTensor(self):
      e = exp.Exp()
      sp = softplus.Softplus()
      aff = scale.Scale(scale=2.0)
      bijector = blockwise.Blockwise(bijectors=[e, sp, aff])
      self.assertIsInstance(bijector, tf.__internal__.CompositeTensor)
  
      # Bijector may be flattened into `Tensor` components and rebuilt.
      flat = tf.nest.flatten(bijector, expand_composites=True)
      unflat = tf.nest.pack_sequence_as(
          bijector, flat, expand_composites=True
      )
      self.assertIsInstance(unflat, blockwise.Blockwise)
  
      # Bijector may be input to a `tf.function`-decorated callable.
      @tf.function
      def call_forward(bij, x):
          return bij.forward(x)
  
      x = tf.ones([2, 3], dtype=tf.float32)
      self.assertAllClose(call_forward(unflat, x), bijector.forward(x))
  
      # Type spec can be encoded/decoded.
      enc = tf.__internal__.saved_model.encode_structure(
          bijector._type_spec
      )
      dec = tf.__internal__.saved_model.decode_proto(enc)
      self.assertEqual(bijector._type_spec, dec)
  
imports: from absl.testing import parameterized
  import mock
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import blockwise
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import inline
  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.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 11 for calling the BlockwiseBijectorTest obj's underlying member method code with example usage: obj.testCompositeTensor() and returns: bij