code: def _affine_normal_params_model_fn(out_units, in_units, dtype):
      yield Root(
          sample.Sample(
              normal.Normal(tf.zeros([], dtype), 1.0),
              [out_units, in_units],
              name="weights",
          )
      )
      yield Root(
          sample.Sample(
              normal.Normal(tf.zeros([], dtype), 1.0),
              out_units,
              name="bias",
          )
      )
  
imports: import collections
  import functools
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import deterministic
  from tensorflow_probability.python.distributions import joint_distribution_coroutine
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import sample
  from tensorflow_probability.python.internal import vectorization_util
label_desc: Use image node_id 1 for calling a global function with example usage: _affine_normal_params_model_fn(out_units, in_units, dtype) without return types