67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
import argparse
|
|
import os.path as osp
|
|
from collections import OrderedDict
|
|
|
|
import mmengine
|
|
import torch
|
|
from mmengine.runner import CheckpointLoader
|
|
|
|
|
|
def convert_van(ckpt):
|
|
|
|
new_ckpt = OrderedDict()
|
|
|
|
for k, v in list(ckpt.items()):
|
|
new_v = v
|
|
if k.startswith('head'):
|
|
new_k = k.replace('head.', 'head.fc.')
|
|
new_ckpt[new_k] = new_v
|
|
continue
|
|
elif k.startswith('patch_embed'):
|
|
if 'proj.' in k:
|
|
new_k = k.replace('proj.', 'projection.')
|
|
else:
|
|
new_k = k
|
|
elif k.startswith('block'):
|
|
new_k = k.replace('block', 'blocks')
|
|
if 'attn.spatial_gating_unit' in new_k:
|
|
new_k = new_k.replace('conv0', 'DW_conv')
|
|
new_k = new_k.replace('conv_spatial', 'DW_D_conv')
|
|
if 'dwconv.dwconv' in new_k:
|
|
new_k = new_k.replace('dwconv.dwconv', 'dwconv')
|
|
else:
|
|
new_k = k
|
|
|
|
if not new_k.startswith('head'):
|
|
new_k = 'backbone.' + new_k
|
|
new_ckpt[new_k] = new_v
|
|
return new_ckpt
|
|
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description='Convert keys in pretrained van '
|
|
'models to mmpretrain style.')
|
|
parser.add_argument('src', help='src model path or url')
|
|
# The dst path must be a full path of the new checkpoint.
|
|
parser.add_argument('dst', help='save path')
|
|
args = parser.parse_args()
|
|
|
|
checkpoint = CheckpointLoader.load_checkpoint(args.src, map_location='cpu')
|
|
|
|
if 'state_dict' in checkpoint:
|
|
state_dict = checkpoint['state_dict']
|
|
else:
|
|
state_dict = checkpoint
|
|
|
|
weight = convert_van(state_dict)
|
|
mmengine.mkdir_or_exist(osp.dirname(args.dst))
|
|
torch.save(weight, args.dst)
|
|
|
|
print('Done!!')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|