class_docstr: Tests the correctness of the Y = Invert(bij) transformation.
code: def testDocstringExample(self):
      exp_gamma_distribution = (
          transformed_distribution.TransformedDistribution(
              distribution=gamma.Gamma(concentration=1.0, rate=2.0),
              bijector=invert.Invert(exp.Exp()),
          )
      )
      self.assertAllEqual(
          [],
          self.evaluate(
              tf.shape(
                  exp_gamma_distribution.sample(
                      seed=test_util.test_seed()
                  )
              )
          ),
      )
  
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 4 for calling the InvertBijectorTest obj's underlying member method code with example usage: obj.testDocstringExample() without return types