class_docstr: :param kernel_size: (int) Must be an ODD number!!
class_docstr_tok: [":","param","kernel_size",":","(","int",")","Must","be","an","ODD","number","!","!"]
code: def forward(self, x):
      # suppose input = x , if x 512
      f0 = self.layer0(x)  # 256
      f1 = self.layer1(f0)  # 128
      # print (f1.size())
      f2 = self.layer2(f1)  # 64
      # print (f2.size())
      f3 = self.layer3(f2)  # 32
      # print (f3.size())
      f4 = self.layer4(f3)  # 16
      # print (f4.size())
      x = self.gcm1(f4)
      out1 = self.ecre(x)
      seb1 = self.seb1([f3, f4])
      gcn1 = self.gcm2(seb1)
  
      seb2 = self.seb2([f2, torch.cat([f3, self.upsample2(f4)], dim=1)])
      gcn2 = self.gcm3(seb2)
  
      seb3 = self.seb3(
          [
              f1,
              torch.cat(
                  [f2, self.upsample2(f3), self.upsample4(f4)], dim=1
              ),
          ]
      )
      gcn3 = self.gcm4(seb3)
  
      y = self.deconv2(gcn1 + out1)
      y = self.deconv3(gcn2 + y)
      y = self.deconv4(gcn3 + y)
      y = self.deconv5(y)
      y = self.DAP(y)
      return y
  
file_path: pywick/pywick/models/segmentation/testnets/lg_kernel_exfuse/large_kernel_exfuse.py
imports: import torch
  from torch import nn
  from .deeplab_resnet import ModelBuilder
  from .large_kernel import _GlobalConvModule
label_desc: Use image node_id 2 for calling the GCNFuse obj's underlying member method code with example usage: obj.forward(x) and returns: y