code: def pool2d_cx(cx, w_in, k, *, stride=1):
      """Accumulates complexity of pool2d into cx = (h, w, flops, params, acts)."""
      assert (
          k % 2 == 1
      ), "Only odd size kernels supported to avoid padding issues."
      h, w, flops, params, acts = (
          cx["h"],
          cx["w"],
          cx["flops"],
          cx["params"],
          cx["acts"],
      )
      h, w = (h - 1) // stride + 1, (w - 1) // stride + 1
      acts += w_in * h * w
      return {
          "h": h,
          "w": w,
          "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 12 for calling a global function with example usage: pool2d_cx(cx, w_in, k) and returns: dict