code: def forward(self, x: Tensor) -> Tensor:
      scale = F.adaptive_avg_pool2d(x, output_size=(1, 1))
      scale = self.fc1(scale)
      scale = self.ac1(scale)
      scale = self.fc2(scale)
      scale = self.ac2(scale)
      return scale * x
  
imports: import math
  import copy
  from functools import partial
  from collections import OrderedDict
  from typing import Optional, Callable
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import functional
label_desc: Use image node_id 2 for calling the SqueezeExcitation obj's underlying member method code with example usage: obj.forward(x) and returns: unknown