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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)
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