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60 lines
2.0 KiB
Python
60 lines
2.0 KiB
Python
"""
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# Copyright (c) 2024 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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import paddle
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import paddle.distributed as dist
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from glob import glob
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import os
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument("--model_dir", type=str, required=True)
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args = parser.parse_args()
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rank = dist.get_rank()
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ep_num = dist.get_world_size()
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print("rank: ", rank)
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# merge tpn -> tp1
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model_dir = args.model_dir
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save_merged_pp_dir = os.path.join(model_dir, "merged_tp1_state_split")
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os.makedirs(save_merged_pp_dir, exist_ok=True)
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model_path_pp = glob(os.path.join(model_dir, "shangxianv1_ep_hadamard_quantmodel_to_eval_pp*"))
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for p in model_path_pp:
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model_path_ep = os.path.join(p, f"model_state.ep0{rank}.pdparams")
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print(p, model_path_ep)
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state_dicts = paddle.load(model_path_ep, return_numpy=True)
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print("merge ep")
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print("p: ", p)
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for k, v in state_dicts.items():
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v = paddle.to_tensor(v)
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if "mlp.experts" in k:
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k_list = k.split(".")
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export_id = rank * ep_num + int(k_list[5])
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k_list[5] = str(export_id)
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k = ".".join(k_list)
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print(f"key: {k}")
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save_split_path = os.path.join(save_merged_pp_dir, k)
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paddle.save(v, save_split_path)
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elif rank == 0:
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save_split_path = os.path.join(save_merged_pp_dir, k)
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paddle.save(paddle.to_tensor(v), save_split_path)
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print(f"merge {p} end")
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print("merge end")
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