code: def linear_cx(cx, in_units, out_units, *, bias=False, trainable=True):
      """Accumulates complexity of linear into cx = (h, w, flops, params, acts)."""
      c = cx["c"]
      assert c == in_units
      cx["c"] = out_units
      cx["flops"] += in_units * out_units + (out_units if bias else 0)
      cx["params"] += in_units * out_units + (out_units if bias else 0)
      cx["acts"] += out_units
      if trainable is False:
          cx["freeze"] += in_units * out_units + (
              out_units if bias else 0
          )
      return cx
  
label_desc: Use image node_id 5 for calling a global function with example usage: linear_cx(cx, in_units, out_units) and returns: cx