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| # 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_twins(args, ckpt): | |
| new_ckpt = OrderedDict() | |
| for k, v in list(ckpt.items()): | |
| new_v = v | |
| if k.startswith('head'): | |
| continue | |
| elif k.startswith('patch_embeds'): | |
| if 'proj.' in k: | |
| new_k = k.replace('proj.', 'projection.') | |
| else: | |
| new_k = k | |
| elif k.startswith('blocks'): | |
| # Union | |
| if 'attn.q.' in k: | |
| new_k = k.replace('q.', 'attn.in_proj_') | |
| new_v = torch.cat([v, ckpt[k.replace('attn.q.', 'attn.kv.')]], | |
| dim=0) | |
| elif 'mlp.fc1' in k: | |
| new_k = k.replace('mlp.fc1', 'ffn.layers.0.0') | |
| elif 'mlp.fc2' in k: | |
| new_k = k.replace('mlp.fc2', 'ffn.layers.1') | |
| # Only pcpvt | |
| elif args.model == 'pcpvt': | |
| if 'attn.proj.' in k: | |
| new_k = k.replace('proj.', 'attn.out_proj.') | |
| else: | |
| new_k = k | |
| # Only svt | |
| else: | |
| if 'attn.proj.' in k: | |
| k_lst = k.split('.') | |
| if int(k_lst[2]) % 2 == 1: | |
| new_k = k.replace('proj.', 'attn.out_proj.') | |
| else: | |
| new_k = k | |
| else: | |
| new_k = k | |
| new_k = new_k.replace('blocks.', 'layers.') | |
| elif k.startswith('pos_block'): | |
| new_k = k.replace('pos_block', 'position_encodings') | |
| if 'proj.0.' in new_k: | |
| new_k = new_k.replace('proj.0.', 'proj.') | |
| else: | |
| new_k = k | |
| if 'attn.kv.' not in k: | |
| new_ckpt[new_k] = new_v | |
| return new_ckpt | |
| def main(): | |
| parser = argparse.ArgumentParser( | |
| description='Convert keys in timm pretrained vit 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') | |
| parser.add_argument('model', help='model: pcpvt or svt') | |
| args = parser.parse_args() | |
| checkpoint = CheckpointLoader.load_checkpoint(args.src, map_location='cpu') | |
| if 'state_dict' in checkpoint: | |
| # timm checkpoint | |
| state_dict = checkpoint['state_dict'] | |
| else: | |
| state_dict = checkpoint | |
| weight = convert_twins(args, state_dict) | |
| mmengine.mkdir_or_exist(osp.dirname(args.dst)) | |
| torch.save(weight, args.dst) | |
| if __name__ == '__main__': | |
| main() | |