code: def forward(self, x):
      aspp3 = self.aspp_3(x)
      x = torch.cat([aspp3, x], dim=1)
  
      aspp6 = self.aspp_6(x)
      x = torch.cat([aspp6, x], dim=1)
  
      aspp12 = self.aspp_12(x)
      x = torch.cat([aspp12, x], dim=1)
  
      aspp18 = self.aspp_18(x)
      x = torch.cat([aspp18, x], dim=1)
  
      aspp24 = self.aspp_24(x)
      x = torch.cat([aspp24, x], dim=1)
  
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from pywick.models.segmentation.da_basenets.densenet import *
  from pywick.models.segmentation.da_basenets.fcn import _FCNHead
label_desc: Use image node_id 2 for calling the _DenseASPPBlock obj's underlying member method code with example usage: obj.forward(x) and returns: x