class_docstr: Residual connection with learnable scalar multipliers on the main branch.
  
  scalar: Single scalar multiplier, or one per dimension
  scale, power: Initialize to scale * layer_num**(-power)
code: def forward(self, x, y, transposed):
      c = self.affine
      if transposed:
          c = c.unsqueeze(-1)
      return self.alpha * x + c * y
  
imports: import torch
  from torch import nn
label_desc: Use image node_id 2 for calling the Affine obj's underlying member method code with example usage: obj.forward(x, y, transposed) and returns: unknown