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