code: def test_dnn_bayes(self):
      self.num_samples = 3
      self.num_components = None
      inputs = tf.zeros([4, 5])
      affine = tfn.Affine(
          5, 10, make_kernel_bias_fn=self.make_bayesian_kernel_bias
      )
      output = affine(inputs[:, tf.newaxis, :])
      self.assertShapeEqual(np.zeros([4, 3, 10]), output)
  
imports: import functools
  from absl.testing import parameterized
  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 prefer_static
  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 3 for calling the AffineTest obj's underlying member method code with example usage: obj.test_dnn_bayes() without return types