class_docstr: This interesting layer produces an MVNDiag via affine transformation.
class_docstr_tok: ["This","interesting","layer","produces","an","MVNDiag","via","affine","transformation","."]
code: def __init__(
      self, output_size, input_size, dtype=tf.float32, name=None
  ):
      super(AffineMeanFieldNormal, self).__init__(name=name)
      self._kernel = tf.Variable(
          tfn.initializers.glorot_normal()(
              [input_size, output_size], dtype
          ),
          name="kernel",
      )
      self._bias = tf.Variable(
          tfn.initializers.glorot_normal()([output_size], dtype),
          name="bias",
      )
  
imports: import tensorflow.compat.v2
  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
label_desc: Use image node_id 1 to create a new AffineMeanFieldNormal object from inherited base classes: tfn with example: obj = AffineMeanFieldNormal(output_size, input_size, dtype, name)