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