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",")","."]
docstr: Instantiate layer.
  
  Args:
    epsilon: For stability when normalizing.
    center: Whether to create and use a {beta}.
    scale: Whether to create and use a {gamma}.
    beta_initializer: Initializer for beta.
    gamma_initializer: Initializer for gamma.
    **kwargs: Passed to keras.
docstr_tok: ["Instantiate","layer",".","Args",":","epsilon",":","For","stability","when","normalizing",".","center",":","Whether","to","create","and","use","a","{","beta","}",".","scale",":","Whether","to","create","and","use","a","{","gamma","}",".","beta_initializer",":","Initializer","for","beta",".","gamma_initializer",":","Initializer","for","gamma",".","*","*","kwargs",":","Passed","to","keras","."]
code: def __init__(
      self,
      epsilon: float = 1e-3,
      center: bool = True,
      scale: bool = True,
      beta_initializer="zeros",
      gamma_initializer="ones",
      **kwargs,
  ):
      """Instantiate layer.
  
      Args:
        epsilon: For stability when normalizing.
        center: Whether to create and use a {beta}.
        scale: Whether to create and use a {gamma}.
        beta_initializer: Initializer for beta.
        gamma_initializer: Initializer for gamma.
        **kwargs: Passed to keras.
      """
      super(ChannelNorm, self).__init__(**kwargs)
  
      self.axis = -1
      self.epsilon = epsilon
      self.center = center
      self.scale = scale
      self.beta_initializer = tf.keras.initializers.get(
          beta_initializer
      )
      self.gamma_initializer = tf.keras.initializers.get(
          gamma_initializer
      )
  
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 1 to create a new ChannelNorm object from inherited base classes: tf.keras.layers with example: obj = ChannelNorm(epsilon, center, scale, beta_initializer, gamma_initializer)