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Running
on
Zero
| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # | |
| # This source code is licensed under the license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| import argparse | |
| import subprocess | |
| from collections import OrderedDict | |
| import torch | |
| from mmengine.runner import CheckpointLoader | |
| def swin_converter(ckpt): | |
| new_ckpt = OrderedDict() | |
| def correct_unfold_reduction_order(x): | |
| out_channel, in_channel = x.shape | |
| x = x.reshape(out_channel, 4, in_channel // 4) | |
| x = x[:, [0, 2, 1, 3], :].transpose(1, | |
| 2).reshape(out_channel, in_channel) | |
| return x | |
| def correct_unfold_norm_order(x): | |
| in_channel = x.shape[0] | |
| x = x.reshape(4, in_channel // 4) | |
| x = x[[0, 2, 1, 3], :].transpose(0, 1).reshape(in_channel) | |
| return x | |
| for k, v in ckpt.items(): | |
| if k.startswith('backbone.layers'): | |
| new_v = v | |
| if 'attn.' in k: | |
| new_k = k.replace('attn.', 'attn.w_msa.') | |
| elif 'mlp.' in k: | |
| if '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.') | |
| else: | |
| new_k = k.replace('mlp.', 'ffn.') | |
| elif 'downsample' in k: | |
| new_k = k | |
| if 'reduction.' in k: | |
| new_v = correct_unfold_reduction_order(v) | |
| elif 'norm.' in k: | |
| new_v = correct_unfold_norm_order(v) | |
| else: | |
| new_k = k | |
| new_k = new_k.replace('layers', 'stages', 1) | |
| elif k.startswith('backbone.patch_embed'): | |
| new_v = v | |
| if 'proj' in k: | |
| new_k = k.replace('proj', 'projection') | |
| else: | |
| new_k = k | |
| else: | |
| new_v = v | |
| new_k = k | |
| new_ckpt[new_k] = new_v | |
| return new_ckpt | |
| def main(): | |
| parser = argparse.ArgumentParser( | |
| description='Convert keys to mmdet 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 | |
| torch.save(swin_converter(state_dict), args.dst) | |
| sha = subprocess.check_output(['sha256sum', args.dst]).decode() | |
| final_file = args.dst.replace('.pth', '') + '-{}.pth'.format(sha[:8]) | |
| subprocess.Popen(['mv', args.dst, final_file]) | |
| print(f'Done!!, save to {final_file}') | |
| if __name__ == '__main__': | |
| main() | |