class_docstr: Implement ChannelNorm.
  
  Based on this paper and keras' InstanceNorm layer:
    Ba, Jimmy Lei, Jamie Ryan Kiros, and Geoffrey E. Hinton.
    "Layer normalization."
    arXiv preprint arXiv:1607.06450 (2016).
class_docstr_tok: ["Implement","ChannelNorm",".","Based","on","this","paper","and","keras","'","InstanceNorm","layer",":","Ba",",","Jimmy","Lei",",","Jamie","Ryan","Kiros",",","and","Geoffrey","E.","Hinton",".","``","Layer","normalization",".","''","arXiv","preprint","arXiv:1607.06450","(","2016",")","."]
code: def _add_gamma_weight(self, input_shape):
      dim = input_shape[self.axis]
      shape = (dim,)
  
      if self.scale:
          self.gamma = self.add_weight(
              shape=shape,
              name="gamma",
              initializer=self.gamma_initializer,
          )
      else:
          self.gamma = None
  
imports: import collections
  from compare_gan.architectures import abstract_arch
  from compare_gan.architectures import arch_ops
  import numpy
  import tensorflow.compat.v1
  import tensorflow_compression
  from hific.helpers import ModelMode
label_desc: Use image node_id 5 for calling the ChannelNorm obj's underlying member method code with example usage: obj._add_gamma_weight(input_shape) without return types