code: def test_works_correctly(self):
      if not tf.executing_eagerly():
          self.skipTest(
              "Skipping graph mode test since we simulate user behavior."
          )
      make_conv = functools.partial(
          tfn.ConvolutionVariationalFlipout,
          rank=2,
          padding="same",
          kernel_initializer=tfn.initializers.he_uniform(),
          activation_fn=tf.nn.elu,
      )
      self.run_bnn_test(make_conv)
  
imports: import functools
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import softmax_centered
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental import nn
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import tf_keras
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 1 for calling the ConvolutionVariationalFlipoutTest obj's underlying member method code with example usage: obj.test_works_correctly() without return types