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53 lines
1.8 KiB
53 lines
1.8 KiB
9 years ago
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# Copyright (c) 2016 Baidu, Inc. 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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from paddle.trainer.PyDataProvider2 import *
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UNK_IDX = 0
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def initializer(settings, dictionary, **kwargs):
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settings.word_dict = dictionary
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settings.input_types = [
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# Define the type of the first input as sequence of integer.
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# The value of the integers range from 0 to len(dictrionary)-1
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integer_value_sequence(len(dictionary)),
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# Define the second input for label id
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integer_value(2)]
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@provider(init_hook=initializer, cache=CacheType.CACHE_PASS_IN_MEM)
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def process(settings, file_name):
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with open(file_name, 'r') as f:
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for line in f:
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label, comment = line.strip().split('\t')
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words = comment.split()
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word_slot = [settings.word_dict.get(w, UNK_IDX) for w in words]
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yield word_slot, int(label)
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def predict_initializer(settings, dictionary, **kwargs):
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settings.word_dict = dictionary
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settings.input_types = [
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integer_value(len(dictionary), seq_type=SequenceType.SEQUENCE)
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]
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@provider(init_hook=predict_initializer)
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def process_predict(settings, file_name):
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with open(file_name, 'r') as f:
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for line in f:
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comment = line.strip()
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word_slot = [settings.word_dict.get(w, UNK_IDX) for w in comment]
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yield word_slot
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