101 lines
3.0 KiB
Python
101 lines
3.0 KiB
Python
# 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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The file_reader converts raw corpus to input.
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"""
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import os
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import __future__
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import io
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import paddle
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import paddle.fluid as fluid
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def load_kv_dict(dict_path,
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reverse=False,
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delimiter="\t",
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key_func=None,
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value_func=None):
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"""
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Load key-value dict from file
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"""
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result_dict = {}
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for line in io.open(dict_path, "r", encoding='utf8'):
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terms = line.strip("\n").split(delimiter)
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if len(terms) != 2:
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continue
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if reverse:
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value, key = terms
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else:
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key, value = terms
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if key in result_dict:
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raise KeyError("key duplicated with [%s]" % (key))
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if key_func:
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key = key_func(key)
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if value_func:
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value = value_func(value)
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result_dict[key] = value
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return result_dict
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class Dataset(object):
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"""data reader"""
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def __init__(self):
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# read dict
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basepath = os.path.abspath(__file__)
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folder = os.path.dirname(basepath)
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word_dict_path = os.path.join(folder, "word.dic")
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label_dict_path = os.path.join(folder, "tag.dic")
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self.word2id_dict = load_kv_dict(
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word_dict_path, reverse=True, value_func=int)
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self.id2word_dict = load_kv_dict(word_dict_path)
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self.label2id_dict = load_kv_dict(
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label_dict_path, reverse=True, value_func=int)
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self.id2label_dict = load_kv_dict(label_dict_path)
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@property
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def vocab_size(self):
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"""vocabulary size"""
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return max(self.word2id_dict.values()) + 1
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@property
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def num_labels(self):
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"""num_labels"""
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return max(self.label2id_dict.values()) + 1
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def word_to_ids(self, words):
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"""convert word to word index"""
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word_ids = []
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for word in words:
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if word not in self.word2id_dict:
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word = "OOV"
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word_id = self.word2id_dict[word]
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word_ids.append(word_id)
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return word_ids
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def label_to_ids(self, labels):
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"""convert label to label index"""
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label_ids = []
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for label in labels:
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if label not in self.label2id_dict:
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label = "O"
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label_id = self.label2id_dict[label]
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label_ids.append(label_id)
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return label_ids
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def get_vars(self,str1):
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words = str1.strip()
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word_ids = self.word_to_ids(words)
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return word_ids
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