code: def forward(self, input_):
      output = self.conv3x3(input_)
  
      if self.nIn < self.nOut:
          max_pool = self.max_pool(input_)
          output = torch.cat([output, max_pool], 1)
  
      output = self.bn_prelu(output)
  
      return output
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the DownSamplingBlock obj's underlying member method code with example usage: obj.forward(input_) and returns: output