class_docstr: Rounded `DeepFactorized` + uniform noise.
class_docstr_tok: ["Rounded","`","DeepFactorized","`","+","uniform","noise","."]
code: def __init__(self, name="NoisyRoundedDeepFactorized", **kwargs):
      prior = deep_factorized.DeepFactorized(**kwargs)
      super().__init__(base=prior, name=name)
  
imports: import tensorflow
  import tensorflow_probability
  from tensorflow_compression.python.distributions import deep_factorized
  from tensorflow_compression.python.distributions import helpers
  from tensorflow_compression.python.distributions import uniform_noise
  from tensorflow_compression.python.ops import round_ops
label_desc: Use image node_id 1 to create a new NoisyRoundedDeepFactorized object from inherited base classes: NoisyRoundAdapter with example: obj = NoisyRoundedDeepFactorized(name)