class_docstr: Tests the correctness of the Y = Invert(bij) transformation.
code: def testNonCompositeTensorBijectorTfFunction(self):
      scale = tf.Variable(5.0)
      b = bijector_test_util.NonCompositeTensorScale(scale)
      inv_b = invert.Invert(b)
      x = tf.constant([3.0])
  
      @tf.function
      def f(bij, x):
          return bij.forward(x)
  
      self.evaluate(scale.initializer)
      self.assertAllClose(self.evaluate(f(inv_b, x)), [0.6])
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import bijector_test_util
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import scale_matvec_diag
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 8 for calling the InvertBijectorTest obj's underlying member method code with example usage: obj.testNonCompositeTensorBijectorTfFunction() and returns: bij