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import torch
from pathlib import Path

Path("./converted").mkdir(exist_ok=True)

ori = torch.load("consolidated.00.pth", map_location="cpu")
ori = {"llma." + key: val for key, val in ori.items()}


def func(rank=0):
    shard_split_to = 8
    split_ckpt = {}
    for key, ori_param in ori.items():
        if key in weight_parallel_dim:
            split_ckpt[key] = torch.chunk(ori_param, shard_split_to, weight_parallel_dim[key])[
                rank % shard_split_to].clone()
            if rank == 0:
                print(f"chunk {key}")
        else:
            if "experts." in key and int(key.split("experts.")[1].split(".")[0]) != rank:
                continue
            else:
                split_ckpt[key] = ori_param
                if rank == 0:
                    print(f"inherit {key}")
    torch.save({"model": split_ckpt}, f"converted/consolidated.{rank:02d}-of-08.model.pth")


for r in range(8):
    func(r)