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- # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
-
- import argparse
- from collections import OrderedDict
-
- dont_transpose = [
- ".w.weight",
- "layernorm1.weight",
- "layernorm2.weight",
- "layernorm.weight",
- ]
-
-
- def convert_pytorch_checkpoint_to_paddle(pytorch_checkpoint_path, paddle_dump_path):
- import paddle
- import torch
-
- pytorch_state_dict = torch.load(pytorch_checkpoint_path, map_location="cpu")
- paddle_state_dict = OrderedDict()
- for k, v in pytorch_state_dict.items():
- if k == "lm_head.weight":
- continue
-
- transpose = False
- if k[-7:] == ".weight":
- if not any([w in k for w in dont_transpose]):
- if v.ndim == 2:
- v = v.transpose(0, 1)
- transpose = True
- if k == "lm_head.bias":
- k = "lm_head_bias"
- print(f"Converting: {k} | is_transpose {transpose}")
-
- paddle_state_dict[k] = v.data.numpy()
-
- paddle.save(paddle_state_dict, paddle_dump_path)
-
-
- if __name__ == "__main__":
- parser = argparse.ArgumentParser()
- parser.add_argument(
- "--pytorch_checkpoint_path",
- default="hg/ctrl/pytorch_model.bin",
- type=str,
- required=False,
- help="Path to the Pytorch checkpoint path.",
- )
- parser.add_argument(
- "--paddle_dump_path",
- default="pd/ctrl/model_state.pdparams",
- type=str,
- required=False,
- help="Path to the output Paddle model.",
- )
- args = parser.parse_args()
- convert_pytorch_checkpoint_to_paddle(
- args.pytorch_checkpoint_path, args.paddle_dump_path
- )
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