class_docstr: The :class:`GaussianNoise` class is noise layer that adding noise with
  gaussian distribution to the activation.
  
  Parameters
  ------------
  mean : float
      The mean. Default is 0.0.
  stddev : float
      The standard deviation. Default is 1.0.
  is_always : boolean
      Is True, add noise for train and eval mode. If False, skip this layer in eval mode.
  seed : int or None
      The seed for random noise.
  name : str
      A unique layer name.
  
  Examples
  --------
  With TensorLayer
  
  >>> net = tl.layers.Input([64, 200], name='input')
  >>> net = tl.layers.Dense(n_units=100, act=tf.nn.relu, name='dense')(net)
  >>> gaussianlayer = tl.layers.GaussianNoise(name='gaussian')(net)
  >>> print(gaussianlayer)
  >>> output shape : (64, 100)
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code: def __repr__(self):
      s = "{classname}(mean={mean}, stddev={stddev}"
      if self.name is not None:
          s += ", name='{name}'"
      s += ")"
      return s.format(
          classname=self.__class__.__name__, **self.__dict__
      )
  
file_path: TensorLayer/tensorlayer/layers/noise.py
imports: import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated_alias
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 2 for calling the GaussianNoise obj's underlying member method code with example usage: obj.__repr__() and returns: s