/* * Copyright (C) 2013, 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. */ #include "dictionary/utils/multi_bigram_map.h" #include #include namespace latinime { // Max number of bigram maps (previous word contexts) to be cached. Increasing this number // could improve bigram lookup speed for multi-word suggestions, but at the cost of more memory // usage. Also, there are diminishing returns since the most frequently used bigrams are // typically near the beginning of the input and are thus the first ones to be cached. Note // that these bigrams are reset for each new composing word. const size_t MultiBigramMap::MAX_CACHED_PREV_WORDS_IN_BIGRAM_MAP = 25; // Most common previous word contexts currently have 100 bigrams const int MultiBigramMap::BigramMap::DEFAULT_HASH_MAP_SIZE_FOR_EACH_BIGRAM_MAP = 100; // Look up the bigram probability for the given word pair from the cached bigram maps. // Also caches the bigrams if there is space remaining and they have not been cached already. int MultiBigramMap::getBigramProbability( const DictionaryStructureWithBufferPolicy *const structurePolicy, const WordIdArrayView prevWordIds, const int nextWordId, const int unigramProbability) { if (prevWordIds.empty() || prevWordIds[0] == NOT_A_WORD_ID) { return structurePolicy->getProbability(unigramProbability, NOT_A_PROBABILITY); } const auto mapPosition = mBigramMaps.find(prevWordIds[0]); if (mapPosition != mBigramMaps.end()) { return mapPosition->second.getBigramProbability(structurePolicy, nextWordId, unigramProbability); } if (mBigramMaps.size() < MAX_CACHED_PREV_WORDS_IN_BIGRAM_MAP) { addBigramsForWord(structurePolicy, prevWordIds); return mBigramMaps[prevWordIds[0]].getBigramProbability(structurePolicy, nextWordId, unigramProbability); } return readBigramProbabilityFromBinaryDictionary(structurePolicy, prevWordIds, nextWordId, unigramProbability); } void MultiBigramMap::BigramMap::init( const DictionaryStructureWithBufferPolicy *const structurePolicy, const WordIdArrayView prevWordIds) { structurePolicy->iterateNgramEntries(prevWordIds, this /* listener */); } int MultiBigramMap::BigramMap::getBigramProbability( const DictionaryStructureWithBufferPolicy *const structurePolicy, const int nextWordId, const int unigramProbability) const { int bigramProbability = NOT_A_PROBABILITY; if (mBloomFilter.isInFilter(nextWordId)) { const auto bigramProbabilityIt = mBigramMap.find(nextWordId); if (bigramProbabilityIt != mBigramMap.end()) { bigramProbability = bigramProbabilityIt->second; } } return structurePolicy->getProbability(unigramProbability, bigramProbability); } void MultiBigramMap::BigramMap::onVisitEntry(const int ngramProbability, const int targetWordId) { if (targetWordId == NOT_A_WORD_ID) { return; } mBigramMap[targetWordId] = ngramProbability; mBloomFilter.setInFilter(targetWordId); } void MultiBigramMap::addBigramsForWord( const DictionaryStructureWithBufferPolicy *const structurePolicy, const WordIdArrayView prevWordIds) { mBigramMaps[prevWordIds[0]].init(structurePolicy, prevWordIds); } int MultiBigramMap::readBigramProbabilityFromBinaryDictionary( const DictionaryStructureWithBufferPolicy *const structurePolicy, const WordIdArrayView prevWordIds, const int nextWordId, const int unigramProbability) { const int bigramProbability = structurePolicy->getProbabilityOfWord(prevWordIds, nextWordId); if (bigramProbability != NOT_A_PROBABILITY) { return bigramProbability; } return structurePolicy->getProbability(unigramProbability, NOT_A_PROBABILITY); } } // namespace latinime