58 lines
2.3 KiB
C++
58 lines
2.3 KiB
C++
/*
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* Copyright (C) 2017 The Android Open Source Project
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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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#ifndef LIBTEXTCLASSIFIER_LANG_ID_RELEVANT_SCRIPT_FEATURE_H_
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#define LIBTEXTCLASSIFIER_LANG_ID_RELEVANT_SCRIPT_FEATURE_H_
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#include "common/feature-extractor.h"
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#include "common/task-context.h"
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#include "common/workspace.h"
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#include "lang_id/light-sentence-features.h"
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#include "lang_id/light-sentence.h"
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namespace libtextclassifier {
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namespace nlp_core {
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namespace lang_id {
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// Given a sentence, generates one FloatFeatureValue for each "relevant" Unicode
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// script (see below): each such feature indicates the script and the ratio of
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// UTF8 characters in that script, in the given sentence.
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//
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// What is a relevant script? Recognizing all 100+ Unicode scripts would
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// require too much code size and runtime. Instead, we focus only on a few
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// scripts that communicate a lot of language information: e.g., the use of
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// Hiragana characters almost always indicates Japanese, so Hiragana is a
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// "relevant" script for us. The Latin script is used by dozens of language, so
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// Latin is not relevant in this context.
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class RelevantScriptFeature : public LightSentenceFeature {
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public:
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// Idiomatic SAFT Setup() and Init().
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bool Setup(TaskContext *context) override;
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bool Init(TaskContext *context) override;
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// Appends the features computed from the sentence to the feature vector.
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void Evaluate(const WorkspaceSet &workspaces, const LightSentence &sentence,
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FeatureVector *result) const override;
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TC_DEFINE_REGISTRATION_METHOD("continuous-bag-of-relevant-scripts",
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RelevantScriptFeature);
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};
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} // namespace lang_id
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} // namespace nlp_core
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} // namespace libtextclassifier
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#endif // LIBTEXTCLASSIFIER_LANG_ID_RELEVANT_SCRIPT_FEATURE_H_
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