code: def gap2d_cx(cx, _w_in):
      """Accumulates complexity of gap2d into cx = (h, w, flops, params, acts)."""
      flops, params, acts = cx["flops"], cx["params"], cx["acts"]
      return {
          "h": 1,
          "w": 1,
          "flops": flops,
          "params": params,
          "acts": acts,
      }
  
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 13 for calling a global function with example usage: gap2d_cx(cx, _w_in) and returns: dict