class_docstr: The :class:`PTRelu6` class is Parametric Rectified Linear layer integrating ReLU6 behaviour.
  
  This Layer is a modified version of the :class:`PRelu`.
  
  This activation layer use a modified version :func:`tl.act.leaky_relu` introduced by the following paper:
  `Rectifier Nonlinearities Improve Neural Network Acoustic Models [A. L. Maas et al., 2013] <https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf>`__
  
  This activation function also use a modified version of the activation function :func:`tf.nn.relu6` introduced by the following paper:
  `Convolutional Deep Belief Networks on CIFAR-10 [A. Krizhevsky, 2010] <http://www.cs.utoronto.ca/~kriz/conv-cifar10-aug2010.pdf>`__
  
  This activation layer push further the logic by adding `leaky` behaviour both below zero and above six.
  
  The function return the following results:
    - When x < 0: ``f(x) = alpha_low * x``.
    - When x in [0, 6]: ``f(x) = x``.
    - When x > 6: ``f(x) = 6 + (alpha_high * (x-6))``.
  
  This version goes one step beyond :class:`PRelu6` by introducing leaky behaviour on the positive side when x > 6.
  
  Parameters
  ----------
  channel_shared : boolean
      If True, single weight is shared by all channels.
  in_channels: int
      The number of channels of the previous layer.
      If None, it will be automatically detected when the layer is forwarded for the first time.
  a_init : initializer
      The initializer for initializing the alpha(s).
  name : None or str
      A unique layer name.
  
  References
  -----------
  - `Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification <http://arxiv.org/abs/1502.01852>`__
  - `Convolutional Deep Belief Networks on CIFAR-10 [A. Krizhevsky, 2010] <http://www.cs.utoronto.ca/~kriz/conv-cifar10-aug2010.pdf>`__
  - `Rectifier Nonlinearities Improve Neural Network Acoustic Models [A. L. Maas et al., 2013] <https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf>`__
class_docstr_tok: ["The",":","class",":","`","PTRelu6","`","class","is","Parametric","Rectified","Linear","layer","integrating","ReLU6","behaviour",".","This","Layer","is","a","modified","version","of","the",":","class",":","`","PRelu","`",".","This","activation","layer","use","a","modified","version",":","func",":","`","tl.act.leaky_relu","`","introduced","by","the","following","paper",":","`","Rectifier","Nonlinearities","Improve","Neural","Network","Acoustic","Models","[","A.","L.","Maas","et","al.",",","2013","]","<","https",":","\/\/ai.stanford.edu\/~amaas\/papers\/relu_hybrid_icml2013_final.pdf",">","`","__","This","activation","function","also","use","a","modified","version","of","the","activation","function",":","func",":","`","tf.nn.relu6","`","introduced","by","the","following","paper",":","`","Convolutional","Deep","Belief","Networks","on","CIFAR-10","[","A.","Krizhevsky",",","2010","]","<","http",":","\/\/www.cs.utoronto.ca\/~kriz\/conv-cifar10-aug2010.pdf",">","`","__","This","activation","layer","push","further","the","logic","by","adding","`","leaky","`","behaviour","both","below","zero","and","above","six",".","The","function","return","the","following","results",":","-","When","x","<","0",":","``","f","(","x",")","=","alpha_low","*","x","``",".","-","When","x","in","[","0",",","6","]",":","``","f","(","x",")","=","x","``",".","-","When","x",">","6",":","``","f","(","x",")","=","6","+","(","alpha_high","*","(","x-6",")",")","``",".","This","version","goes","one","step","beyond",":","class",":","`","PRelu6","`","by","introducing","leaky","behaviour","on","the","positive","side","when","x",">","6",".","Parameters","--","--","--","--","--","channel_shared",":","boolean","If","True",",","single","weight","is","shared","by","all","channels",".","in_channels",":","int","The","number","of","channels","of","the","previous","layer",".","If","None",",","it","will","be","automatically","detected","when","the","layer","is","forwarded","for","the","first","time",".","a_init",":","initializer","The","initializer","for","initializing","the","alpha","(","s",")",".","name",":","None","or","str","A","unique","layer","name",".","References","--","--","--","--","--","-","-","`","Delving","Deep","into","Rectifiers",":","Surpassing","Human-Level","Performance","on","ImageNet","Classification","<","http",":","\/\/arxiv.org\/abs\/1502.01852",">","`","__","-","`","Convolutional","Deep","Belief","Networks","on","CIFAR-10","[","A.","Krizhevsky",",","2010","]","<","http",":","\/\/www.cs.utoronto.ca\/~kriz\/conv-cifar10-aug2010.pdf",">","`","__","-","`","Rectifier","Nonlinearities","Improve","Neural","Network","Acoustic","Models","[","A.","L.","Maas","et","al.",",","2013","]","<","https",":","\/\/ai.stanford.edu\/~amaas\/papers\/relu_hybrid_icml2013_final.pdf",">","`","__"]
code: def __repr__(self):
      s = "{classname}("
      s += "channel_shared={channel_shared},"
      s += "in_channels={in_channels},"
      s += "name={name}"
      s += ")"
      return s.format(
          classname=self.__class__.__name__, **self.__dict__
      )
  
imports: import tensorflow
  from tensorlayer import logging
  from tensorlayer.activation import leaky_relu6, leaky_twice_relu6
  from tensorlayer.decorators import deprecated_alias
  from tensorlayer.initializers import truncated_normal
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 2 for calling the PTRelu6 obj's underlying member method code with example usage: obj.__repr__() and returns: s