code: def get_alpha(self):
      return torch.stack(
          (
              self.diffuse0.alpha.data,
              self.diffuse1.alpha.data,
              self.diffuse2.alpha.data,
              self.diffuse3.alpha.data,
              self.diffuse4.alpha.data,
          )
      ).t()
  
imports: import math
  import torch
  import torch.nn
  from torch.nn.parameter import Parameter
  import torch.nn.functional
label_desc: Use image node_id 2 for calling the DifNet obj's underlying member method code with example usage: obj.get_alpha() and returns: torch