class_docstr: Sonnet module for adding clipped Gaussian noise to each output.
code: def __init__(self, stddev: float, name: str = "clipped_gaussian"):
      super().__init__(name=name)
      self._noise = tfd.Normal(loc=0.0, scale=stddev)
  
file_path: acme/acme/tf/networks/noise.py
imports: from acme import types
  import sonnet
  import tensorflow
  import tensorflow_probability
  import tree
label_desc: Use image node_id 1 to create a new ClippedGaussian object from inherited base classes: snt with example: obj = ClippedGaussian(stddev, name)