code: def forward(self, x):
      if self.filter_size > 0:
          return self.layers(x)  # image, conv, batchnorm, relu
      else:
          y = torch.add(x.unsqueeze(2), self.noise * self.level)
          # (10, 3, 1, 32, 32) + (1, 3, 128, 32, 32) --> (10, 3, 128, 32, 32)
  
          y = y.view(
              -1,
              self.in_channels * self.nmasks,
              self.input_size,
              self.input_size,
          )
          y = self.layers(y)
  
          if self.mix_maps:
              y = self.mix_layers(y)
  
          return y
  
imports: import torch
  import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the PerturbLayerFirst obj's underlying member method code with example usage: obj.forward(x) and returns: self, y