code: def lrn(self, depth_radius, bias, alpha, beta):
          
          name = "lrn" + str(self.counts["lrn"])
          self.counts["lrn"] += 1
          self.top_layer = tf.nn.lrn(
              self.top_layer, depth_radius, bias, alpha, beta, name=name)
          return self.top_layer
docs: Adds a local response normalization layer.