47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
# -*- coding: UTF-8 -*-
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# Copyright (c) 2019 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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Define the function to create lexical analysis model and model's data reader
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"""
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import sys
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import os
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import math
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import paddle
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import paddle.fluid as fluid
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from paddle.fluid.initializer import NormalInitializer
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import jieba.lac_small.nets as nets
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def create_model(vocab_size, num_labels, mode='train'):
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"""create lac model"""
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# model's input data
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words = fluid.data(name='words', shape=[-1, 1], dtype='int64', lod_level=1)
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targets = fluid.data(
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name='targets', shape=[-1, 1], dtype='int64', lod_level=1)
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# for inference process
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if mode == 'infer':
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crf_decode = nets.lex_net(
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words, vocab_size, num_labels, for_infer=True, target=None)
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return {
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"feed_list": [words],
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"words": words,
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"crf_decode": crf_decode,
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}
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return ret
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