code: def CSPDarknet53WithSPP(self):
      def feed(x):
          x = self.darknetConv(32, 3, activation="mish")(x)
          x = self.darknetResidualBlock(32, initial=True)(x)
          x = self.darknetResidualBlock(64, repeats=2)(x)
          x = route_1 = self.darknetResidualBlock(128, repeats=8)(x)
          x = route_2 = self.darknetResidualBlock(256, repeats=8)(x)
          x = self.darknetResidualBlock(512, repeats=4)(x)
          x = self.darknetConv(512, 1)(x)
          x = self.darknetConv(1024, 3)(x)
          x = self.darknetConv(512, 1)(x)
  
          # SPP
          spp1 = tf.keras.layers.MaxPooling2D(
              pool_size=13, strides=1, padding="same"
          )(x)
          spp2 = tf.keras.layers.MaxPooling2D(
              pool_size=9, strides=1, padding="same"
          )(x)
          spp3 = tf.keras.layers.MaxPooling2D(
              pool_size=5, strides=1, padding="same"
          )(x)
  
          x = tf.keras.layers.Concatenate()([spp1, spp2, spp3, x])
  
          x = self.darknetConv(512, 1)(x)
          x = self.darknetConv(1024, 3)(x)
          x = self.darknetConv(512, 1)(x)
          return route_1, route_2, x
  
      return feed
  
imports: import tensorflow
  import numpy
  from layers import Mish, ScaledRandomUniform
  import utils
label_desc: Use image node_id 10 for calling the YOLOv4Model obj's underlying member method code with example usage: obj.CSPDarknet53WithSPP() and returns: feed, route_1,  route_2,  x