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77 lines
2.5 KiB
Python
77 lines
2.5 KiB
Python
"""
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# Copyright (c) 2025 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 argparse
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import os
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import paddle
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parser = argparse.ArgumentParser()
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parser.add_argument(
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"--model_path",
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default="./",
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type=str,
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required=True,
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help="The directory of model.",
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)
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parser.add_argument(
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"--output_path",
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default="./",
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type=str,
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help="The directory of splited model",
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)
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parser.add_argument("--model_degree", default=4, type=int, help="Input model mp degree.")
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args = parser.parse_args()
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hidden_size = 1280
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kv_num_heads = 16
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head_dim = 80
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input_model_state_dict = paddle.load(os.path.join(args.model_path, "model_state.pdparams"))
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for i in range(args.model_degree):
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static_dict = {}
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for k, v in input_model_state_dict.items():
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if "qkv.weight" in k:
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static_dict[k] = (
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input_model_state_dict[k]
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.reshape([hidden_size, 3, kv_num_heads, head_dim])
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.split(args.model_degree, axis=-2)[i]
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.reshape([hidden_size, -1])
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)
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elif "qkv.bias" in k:
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static_dict[k] = (
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input_model_state_dict[k]
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.reshape([3, kv_num_heads, head_dim])
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.split(args.model_degree, axis=-2)[i]
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.reshape([-1])
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)
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elif "attn.proj.weight" in k:
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static_dict[k] = input_model_state_dict[k].split(args.model_degree, axis=-2)[i]
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elif "fc1.weight" in k:
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static_dict[k] = input_model_state_dict[k].split(args.model_degree, axis=-1)[i]
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elif "fc1.bias" in k:
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static_dict[k] = input_model_state_dict[k].split(args.model_degree, axis=-1)[i]
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elif "fc2.weight" in k:
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static_dict[k] = input_model_state_dict[k].split(args.model_degree, axis=-2)[i]
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else:
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static_dict[k] = v
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paddle.save(
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static_dict,
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os.path.join(args.model_path, f"model_state_tp0{i}.pdparams"),
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)
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