code: def forward(self, x):
      c2, c3, c4, c5 = x
  
      in5 = self.in5_conv(c5)
      in4 = self.in4_conv(c4)
      in3 = self.in3_conv(c3)
      in2 = self.in2_conv(c2)
  
      out4 = in4 + F.upsample(
          in5, scale_factor=2, mode="nearest", align_mode=1
      )  # 1/16
      out3 = in3 + F.upsample(
          out4, scale_factor=2, mode="nearest", align_mode=1
      )  # 1/8
      out2 = in2 + F.upsample(
          out3, scale_factor=2, mode="nearest", align_mode=1
      )  # 1/4
  
      p5 = self.p5_conv(in5)
      p4 = self.p4_conv(out4)
      p3 = self.p3_conv(out3)
      p2 = self.p2_conv(out2)
      p5 = F.upsample(p5, scale_factor=8, mode="nearest", align_mode=1)
      p4 = F.upsample(p4, scale_factor=4, mode="nearest", align_mode=1)
      p3 = F.upsample(p3, scale_factor=2, mode="nearest", align_mode=1)
  
      fuse = paddle.concat([p5, p4, p3, p2], axis=1)
  
      if self.use_asf is True:
          fuse = self.asf(fuse, [p5, p4, p3, p2])
  
      return fuse
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from paddle import nn
  import paddle.nn.functional
  from paddle import ParamAttr
  import os
  import sys
  from ppocr.modeling.necks.intracl import IntraCLBlock
  from ppocr.modeling.backbones.det_mobilenet_v3 import SEModule
label_desc: Use image node_id 2 for calling the DBFPN obj's underlying member method code with example usage: obj.forward(x) and returns: fuse