code: def __init__(self, filters):
      super().__init__()
      self.conv1 = Conv2D(
          filters // 2, kernel_size=1, strides=2, use_bias=False
      )
      self.conv2 = Conv2D(
          filters // 2, kernel_size=1, strides=2, use_bias=False
      )
      self.bn = BatchNormalization(trainable=False)
  
imports: import tensorflow
  from tensorflow.keras import Model, Sequential
  from tensorflow.keras.layers import AveragePooling2D, BatchNormalization, Conv2D, Dense, Dropout, GlobalAveragePooling2D, MaxPool2D, ReLU, SeparableConv2D
  from nni.nas.tensorflow.mutables import InputChoice, LayerChoice, MutableScope
label_desc: Use image node_id 1 to create a new FactorizedReduce object from inherited base classes: Model with example: obj = FactorizedReduce(filters)