class_docstr: Squeeze-and-Excitation (SE) block: AvgPool, FC, Act, FC, Sigmoid.
code: def complexity(cx, w_in, w_se):
      h, w = cx["h"], cx["w"]
      cx = gap2d_cx(cx, w_in)
      cx = conv2d_cx(cx, w_in, w_se, 1, bias=True)
      cx = conv2d_cx(cx, w_se, w_in, 1, bias=True)
      cx["h"], cx["w"] = h, w
      return cx
  
imports: import numpy
  import torch
  import torch.nn
  from pycls.core.config import cfg
  from torch.nn import Module
label_desc: Use image node_id 3 for calling the SE obj's underlying member method code with example usage: obj.complexity(cx, w_in, w_se) and returns: cx