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import argparse
import subprocess
import torch
def process_checkpoint(in_file, out_file):
checkpoint = torch.load(in_file, map_location="cpu")
# only keep `epoch` and `state_dict`/`state_dict_ema`` for smaller file size
ckpt_keys = list(checkpoint.keys())
save_keys = ["meta", "epoch"]
if "state_dict_ema" in ckpt_keys:
save_keys.append("state_dict_ema")
else:
save_keys.append("state_dict")
for k in ckpt_keys:
if k not in save_keys:
print(f"Key `{k}` will be removed because it is not in save_keys.")
checkpoint.pop(k, None)
# if it is necessary to remove some sensitive data in checkpoint['meta'],
# add the code here.
torch.save(checkpoint, out_file)
sha = subprocess.check_output(["sha256sum", out_file]).decode()
if out_file.endswith(".pth"):
out_file_name = out_file[:-4]
else:
out_file_name = out_file
final_file = out_file_name + f"_{sha[:8]}.pth"
subprocess.Popen(["mv", out_file, final_file])
print(f"The published model is saved at {final_file}.")
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Process a checkpoint to be published")
parser.add_argument("in_file", help="input checkpoint filename")
parser.add_argument("out_file", help="output checkpoint filename")
args = parser.parse_args()
process_checkpoint(args.in_file, args.out_file)
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