|
import argparse |
|
import torch |
|
from safetensors.torch import load_file, save_file |
|
|
|
if __name__ == "__main__": |
|
parser = argparse.ArgumentParser() |
|
parser.add_argument("--src", default=None, type=str, required=True, help="Path to the model to convert.") |
|
parser.add_argument("--dst", default=None, type=str, required=True, help="Path to the output model.") |
|
parser.add_argument("--fp16", action="store_true", help="Whether to convert the model to fp16.") |
|
args = parser.parse_args() |
|
|
|
assert args.src is not None, "Must provide a model path!" |
|
assert args.dst is not None, "Must provide a checkpoint path!" |
|
|
|
if args.src.endswith(".safetensors"): |
|
state_dict = load_file(args.src, map_location="cpu") |
|
else: |
|
state_dict = torch.load(args.src, map_location="cpu") |
|
|
|
try: |
|
state_dict = state_dict['state_dict']["state_dict"] |
|
except: |
|
try: |
|
state_dict = state_dict['state_dict'] |
|
except: |
|
pass |
|
|
|
if args.fp16: |
|
if any([k.startswith("control_model.") for k, v in state_dict.items()]): |
|
state_dict = {k.replace("control_model.", ""): v.half() for k, v in state_dict.items() if k.startswith("control_model.")} |
|
else: |
|
if any([k.startswith("control_model.") for k, v in state_dict.items()]): |
|
state_dict = {k.replace("control_model.", ""): v for k, v in state_dict.items() if k.startswith("control_model.")} |
|
|
|
|
|
if args.dst.endswith(".safetensors"): |
|
save_file(state_dict, args.dst) |
|
else: |
|
torch.save({"state_dict": state_dict}, args.dst) |
|
|