|
|
|
import argparse |
|
import subprocess |
|
|
|
import torch |
|
|
|
|
|
def parse_args(): |
|
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() |
|
return args |
|
|
|
|
|
def process_checkpoint(in_file, out_file): |
|
checkpoint = torch.load(in_file, map_location='cpu') |
|
|
|
|
|
if 'optimizer' in checkpoint: |
|
del checkpoint['optimizer'] |
|
if 'message_hub' in checkpoint: |
|
del checkpoint['message_hub'] |
|
if 'ema_state_dict' in checkpoint: |
|
del checkpoint['ema_state_dict'] |
|
|
|
for key in list(checkpoint['state_dict']): |
|
if key.startswith('data_preprocessor'): |
|
checkpoint['state_dict'].pop(key) |
|
elif 'priors_base_sizes' in key: |
|
checkpoint['state_dict'].pop(key) |
|
elif 'grid_offset' in key: |
|
checkpoint['state_dict'].pop(key) |
|
elif 'prior_inds' in key: |
|
checkpoint['state_dict'].pop(key) |
|
|
|
if torch.__version__ >= '1.6': |
|
torch.save(checkpoint, out_file, _use_new_zipfile_serialization=False) |
|
else: |
|
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]) |
|
|
|
|
|
def main(): |
|
args = parse_args() |
|
process_checkpoint(args.in_file, args.out_file) |
|
|
|
|
|
if __name__ == '__main__': |
|
main() |
|
|
