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73 lines
2.7 KiB
73 lines
2.7 KiB
4 months ago
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/*
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* Copyright (C) 2018 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_ACTIONS_NGRAM_MODEL_H_
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#define LIBTEXTCLASSIFIER_ACTIONS_NGRAM_MODEL_H_
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#include <memory>
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#include "actions/actions_model_generated.h"
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#include "actions/sensitive-classifier-base.h"
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#include "actions/types.h"
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#include "utils/tokenizer.h"
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#include "utils/utf8/unicodetext.h"
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#include "utils/utf8/unilib.h"
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namespace libtextclassifier3 {
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class NGramSensitiveModel : public SensitiveTopicModelBase {
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public:
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static std::unique_ptr<NGramSensitiveModel> Create(
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const UniLib* unilib, const NGramLinearRegressionModel* model,
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const Tokenizer* tokenizer);
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// Evaluates an n-gram linear regression model, and tests against the
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// threshold. Returns true in case of a positive classification. The caller
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// may also optionally query the score.
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std::pair<bool, float> Eval(const UnicodeText& text) const override;
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// Evaluates an n-gram linear regression model against all messages in a
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// conversation and returns true in case of any positive classification.
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std::pair<bool, float> EvalConversation(const Conversation& conversation,
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int num_messages) const override;
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// Exposed for testing only.
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static uint64 GetNumSkipGrams(int num_tokens, int max_ngram_length,
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int max_skips);
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private:
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explicit NGramSensitiveModel(const UniLib* unilib,
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const NGramLinearRegressionModel* model,
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const Tokenizer* tokenizer);
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// Returns the (begin,end] range of n-grams where the first hashed token
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// matches the given value.
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std::pair<int, int> GetFirstTokenMatches(uint32 token_hash) const;
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// Returns whether a given n-gram matches the token stream.
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bool IsNGramMatch(const uint32* tokens, size_t num_tokens,
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const uint32* ngram_tokens, size_t num_ngram_tokens,
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int max_skips) const;
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const NGramLinearRegressionModel* model_;
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const Tokenizer* tokenizer_;
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std::unique_ptr<Tokenizer> owned_tokenizer_;
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};
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} // namespace libtextclassifier3
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#endif // LIBTEXTCLASSIFIER_ACTIONS_NGRAM_MODEL_H_
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