57 lines
1.7 KiB
Python
57 lines
1.7 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_beit(ckpt):
|
|
new_ckpt = OrderedDict()
|
|
|
|
for k, v in ckpt.items():
|
|
if k.startswith('patch_embed'):
|
|
new_key = k.replace('patch_embed.proj', 'patch_embed.projection')
|
|
new_ckpt[new_key] = v
|
|
if k.startswith('blocks'):
|
|
new_key = k.replace('blocks', 'layers')
|
|
if 'norm' in new_key:
|
|
new_key = new_key.replace('norm', 'ln')
|
|
elif 'mlp.fc1' in new_key:
|
|
new_key = new_key.replace('mlp.fc1', 'ffn.layers.0.0')
|
|
elif 'mlp.fc2' in new_key:
|
|
new_key = new_key.replace('mlp.fc2', 'ffn.layers.1')
|
|
new_ckpt[new_key] = v
|
|
else:
|
|
new_key = k
|
|
new_ckpt[new_key] = v
|
|
|
|
return new_ckpt
|
|
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description='Convert keys in official pretrained beit models to'
|
|
'MMSegmentation 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']
|
|
elif 'model' in checkpoint:
|
|
state_dict = checkpoint['model']
|
|
else:
|
|
state_dict = checkpoint
|
|
weight = convert_beit(state_dict)
|
|
mmengine.mkdir_or_exist(osp.dirname(args.dst))
|
|
torch.save(weight, args.dst)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|