code: def __init__(self, in_channels, out_channels):
      super().__init__()
      self.process = None
      if in_channels != out_channels:
          self.process = StdConv(in_channels, out_channels)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from nni.nas.pytorch import mutables
  from ops import FactorizedReduce, StdConv, SepConvBN, Pool
label_desc: Use image node_id 1 to create a new Calibration object from inherited base classes: nn with example: obj = Calibration(in_channels, out_channels)