class_docstr: Combine Instance Norm and Batch Norm into One Layer
class_docstr_tok: ["Combine","Instance","Norm","and","Batch","Norm","into","One","Layer"]
code: def __init__(self, in_channels):
      super().__init__()
      self.bnorm_channels = in_channels // 2
      self.inorm_channels = in_channels - self.bnorm_channels
  
      self.bnorm = nn.BatchNorm2D(self.bnorm_channels)
      self.inorm = nn.InstanceNorm2D(self.inorm_channels)
  
imports: from collections import defaultdict
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
  import scipy
  import paddleseg
  from paddleseg.models import layers, losses
  from paddleseg import utils
  from paddleseg.cvlibs import manager, param_init
label_desc: Use image node_id 1 to create a new IBNorm object from inherited base classes: nn with example: obj = IBNorm(in_channels)