code: def __init__(self, groups, eps=1e-5):
      if not isinstance(groups, int):
          raise TypeError("Argument: 'groups' type must be (int).")
  
      self.groups = groups
      self.eps = eps
      self.mean = None
      self.inv_std = None
      self.dummy_gamma = None
  
imports: import numpy
  import chainer
  from chainer import backend
  from chainer.backends import cuda
  from chainer import configuration
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 1 to create a new GroupNormalization object from inherited base classes: function_node with example: obj = GroupNormalization(groups, eps)