import torch, sys, os
spec=sys.argv[1]  # path:weight,path:weight,...
out_path=sys.argv[2]
parts=[(p,float(w)) for p,w in (x.rsplit(":",1) for x in spec.split(","))]
ck=[torch.load(p,map_location="cpu") for p,_ in parts]
ws=[w for _,w in parts]; s=sum(ws); ws=[w/s for w in ws]
def merge(vals):
    a=vals[0]
    if isinstance(a,dict): return {k:merge([v[k] for v in vals]) for k in a}
    if torch.is_tensor(a):
        return sum(w*v.float() for w,v in zip(ws,vals))
    return a
out={"args":ck[0].get("args")}
for sec in ["backbone","heads","aux"]:
    if sec in ck[0]: out[sec]=merge([c[sec] for c in ck])
os.makedirs(os.path.dirname(out_path),exist_ok=True)
torch.save(out,out_path); print("saved",out_path,ws)