code: def __init__(
      self, se_filters: int, output_filters: int, name: str = None
  ):
      super(SE, self).__init__(name=name)
  
      self.se_reduce = layers.Conv2D(
          filters=se_filters,
          kernel_size=1,
          strides=1,
          padding="same",
          activation="swish",
          use_bias=True,
          kernel_initializer=CONV_KERNEL_INITIALIZER,
          name="conv2d",
      )
  
      self.se_expand = layers.Conv2D(
          filters=output_filters,
          kernel_size=1,
          strides=1,
          padding="same",
          activation="sigmoid",
          use_bias=True,
          kernel_initializer=CONV_KERNEL_INITIALIZER,
          name="conv2d_1",
      )
  
imports: import itertools
  import tensorflow
  from tensorflow.keras import layers, Model, Input
label_desc: Use image node_id 1 to create a new SE object from inherited base classes: layers with example: obj = SE(se_filters, output_filters, name)