code: def __init__(self, inplane, pdcs, dil=None, sa=False, convert=False):
      super(PiDiNet, self).__init__()
      self.sa = sa
      if dil is not None:
          assert isinstance(dil, int), "dil should be an int"
      self.dil = dil
  
      self.fuseplanes = []
  
      self.inplane = inplane
      if convert:
          if pdcs[0] == "rd":
              init_kernel_size = 5
              init_padding = 2
          else:
              init_kernel_size = 3
              init_padding = 1
          self.init_block = nn.Conv2d(
              3,
              self.inplane,
              kernel_size=init_kernel_size,
              padding=init_padding,
              bias=False,
          )
          block_class = PDCBlock_converted
      else:
          self.init_block = Conv2d(
              pdcs[0], 3, self.inplane, kernel_size=3, padding=1
          )
          block_class = PDCBlock
  
      self.block1_1 = block_class(pdcs[1], self.inplane, self.inplane)
      self.block1_2 = block_class(pdcs[2], self.inplane, self.inplane)
      self.block1_3 = block_class(pdcs[3], self.inplane, self.inplane)
      self.fuseplanes.append(self.inplane)  # C
  
      inplane = self.inplane
      self.inplane = self.inplane * 2
      self.block2_1 = block_class(
          pdcs[4], inplane, self.inplane, stride=2
      )
      self.block2_2 = block_class(pdcs[5], self.inplane, self.inplane)
      self.block2_3 = block_class(pdcs[6], self.inplane, self.inplane)
      self.block2_4 = block_class(pdcs[7], self.inplane, self.inplane)
      self.fuseplanes.append(self.inplane)  # 2C
  
      inplane = self.inplane
      self.inplane = self.inplane * 2
      self.block3_1 = block_class(
          pdcs[8], inplane, self.inplane, stride=2
      )
      self.block3_2 = block_class(pdcs[9], self.inplane, self.inplane)
      self.block3_3 = block_class(pdcs[10], self.inplane, self.inplane)
      self.block3_4 = block_class(pdcs[11], self.inplane, self.inplane)
      self.fuseplanes.append(self.inplane)  # 4C
  
      self.block4_1 = block_class(
          pdcs[12], self.inplane, self.inplane, stride=2
      )
      self.block4_2 = block_class(pdcs[13], self.inplane, self.inplane)
      self.block4_3 = block_class(pdcs[14], self.inplane, self.inplane)
      self.block4_4 = block_class(pdcs[15], self.inplane, self.inplane)
      self.fuseplanes.append(self.inplane)  # 4C
  
      self.conv_reduces = nn.ModuleList()
      if self.sa and self.dil is not None:
          self.attentions = nn.ModuleList()
          self.dilations = nn.ModuleList()
          for i in range(4):
              self.dilations.append(CDCM(self.fuseplanes[i], self.dil))
              self.attentions.append(CSAM(self.dil))
              self.conv_reduces.append(MapReduce(self.dil))
      elif self.sa:
          self.attentions = nn.ModuleList()
          for i in range(4):
              self.attentions.append(CSAM(self.fuseplanes[i]))
              self.conv_reduces.append(MapReduce(self.fuseplanes[i]))
      elif self.dil is not None:
          self.dilations = nn.ModuleList()
          for i in range(4):
              self.dilations.append(CDCM(self.fuseplanes[i], self.dil))
              self.conv_reduces.append(MapReduce(self.dil))
      else:
          for i in range(4):
              self.conv_reduces.append(MapReduce(self.fuseplanes[i]))
  
      self.classifier = nn.Conv2d(4, 1, kernel_size=1)  # has bias
      nn.init.constant_(self.classifier.weight, 0.25)
      nn.init.constant_(self.classifier.bias, 0)
  
imports: import os
  import math
  import torch
  import numpy
  import torch.nn
  import torch.nn.functional
  from typing import Optional
  from cftool.cv import to_uint8
  from ....parameters import OPT
label_desc: Use image node_id 1 to create a new PiDiNet object from inherited base classes: nn with example: obj = PiDiNet(inplane, pdcs, dil, sa, convert)