class_docstr: The :class:`LayerNorm` class is for layer normalization, see `tf.contrib.layers.layer_norm <https://www.tensorflow.org/api_docs/python/tf/contrib/layers/layer_norm>`__.
  
  Parameters
  ----------
  prev_layer : :class:`Layer`
      The previous layer.
  act : activation function
      The activation function of this layer.
  others : _
      `tf.contrib.layers.layer_norm <https://www.tensorflow.org/api_docs/python/tf/contrib/layers/layer_norm>`__.
class_docstr_tok: ["The",":","class",":","`","LayerNorm","`","class","is","for","layer","normalization",",","see","`","tf.contrib.layers.layer_norm","<","https",":","\/\/www.tensorflow.org\/api_docs\/python\/tf\/contrib\/layers\/layer_norm",">","`","__",".","Parameters","--","--","--","--","--","prev_layer",":",":","class",":","`","Layer","`","The","previous","layer",".","act",":","activation","function","The","activation","function","of","this","layer",".","others",":","_","`","tf.contrib.layers.layer_norm","<","https",":","\/\/www.tensorflow.org\/api_docs\/python\/tf\/contrib\/layers\/layer_norm",">","`","__","."]
code: def build(self, inputs_shape):
      params_shape = inputs_shape[self.begin_params_axis :]
      self.beta, self.gamma = None, None
      if self.center:
          self.beta = self._get_weights(
              "beta", shape=params_shape, init=self.beta_init
          )
      if self.scale:
          self.gamma = self._get_weights(
              "gamma", shape=params_shape, init=self.gamma_init
          )
  
      self.norm_axes = range(self.begin_norm_axis, len(inputs_shape))
  
imports: import tensorflow
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.training import moving_averages
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 2 for calling the LayerNorm obj's underlying member method code with example usage: obj.build(inputs_shape) without return types