Merge "Implement LanguageModelDictContent.getWordProbability()."
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commit
38085ee7ae
8 changed files with 95 additions and 40 deletions
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@ -354,7 +354,7 @@ bool Ver4PatriciaTriePolicy::addNgramEntry(const PrevWordsInfo *const prevWordsI
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}
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bool addedNewBigram = false;
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const int prevWordPtNodePos = getTerminalPtNodePosFromWordId(prevWordIds[0]);
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if (mUpdatingHelper.addNgramEntry(PtNodePosArrayView::fromObject(&prevWordPtNodePos),
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if (mUpdatingHelper.addNgramEntry(PtNodePosArrayView::singleElementView(&prevWordPtNodePos),
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wordPos, bigramProperty, &addedNewBigram)) {
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if (addedNewBigram) {
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mBigramCount++;
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@ -396,7 +396,7 @@ bool Ver4PatriciaTriePolicy::removeNgramEntry(const PrevWordsInfo *const prevWor
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}
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const int prevWordPtNodePos = getTerminalPtNodePosFromWordId(prevWordIds[0]);
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if (mUpdatingHelper.removeNgramEntry(
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PtNodePosArrayView::fromObject(&prevWordPtNodePos), wordPos)) {
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PtNodePosArrayView::singleElementView(&prevWordPtNodePos), wordPos)) {
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mBigramCount--;
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return true;
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} else {
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@ -38,6 +38,40 @@ bool LanguageModelDictContent::runGC(
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0 /* nextLevelBitmapEntryIndex */, outNgramCount);
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}
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int LanguageModelDictContent::getWordProbability(const WordIdArrayView prevWordIds,
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const int wordId) const {
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int bitmapEntryIndices[MAX_PREV_WORD_COUNT_FOR_N_GRAM + 1];
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bitmapEntryIndices[0] = mTrieMap.getRootBitmapEntryIndex();
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int maxLevel = 0;
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for (size_t i = 0; i < prevWordIds.size(); ++i) {
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const int nextBitmapEntryIndex =
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mTrieMap.get(prevWordIds[i], bitmapEntryIndices[i]).mNextLevelBitmapEntryIndex;
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if (nextBitmapEntryIndex == TrieMap::INVALID_INDEX) {
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break;
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}
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maxLevel = i + 1;
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bitmapEntryIndices[i + 1] = nextBitmapEntryIndex;
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}
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for (int i = maxLevel; i >= 0; --i) {
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const TrieMap::Result result = mTrieMap.get(wordId, bitmapEntryIndices[i]);
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if (!result.mIsValid) {
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continue;
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}
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const int probability =
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ProbabilityEntry::decode(result.mValue, mHasHistoricalInfo).getProbability();
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if (mHasHistoricalInfo) {
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return std::min(
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probability + ForgettingCurveUtils::getProbabilityBiasForNgram(i + 1 /* n */),
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MAX_PROBABILITY);
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} else {
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return probability;
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}
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}
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// Cannot find the word.
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return NOT_A_PROBABILITY;
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}
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ProbabilityEntry LanguageModelDictContent::getNgramProbabilityEntry(
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const WordIdArrayView prevWordIds, const int wordId) const {
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const int bitmapEntryIndex = getBitmapEntryIndex(prevWordIds);
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@ -128,6 +128,8 @@ class LanguageModelDictContent {
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const LanguageModelDictContent *const originalContent,
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int *const outNgramCount);
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int getWordProbability(const WordIdArrayView prevWordIds, const int wordId) const;
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ProbabilityEntry getProbabilityEntry(const int wordId) const {
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return getNgramProbabilityEntry(WordIdArrayView(), wordId);
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}
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@ -115,24 +115,12 @@ int Ver4PatriciaTriePolicy::getWordId(const CodePointArrayView wordCodePoints,
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int Ver4PatriciaTriePolicy::getProbabilityOfWordInContext(const int *const prevWordIds,
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const int wordId, MultiBigramMap *const multiBigramMap) const {
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// TODO: Quit using MultiBigramMap.
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if (wordId == NOT_A_WORD_ID) {
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return NOT_A_PROBABILITY;
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}
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const int ptNodePos =
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mBuffers->getTerminalPositionLookupTable()->getTerminalPtNodePosition(wordId);
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const PtNodeParams ptNodeParams(mNodeReader.fetchPtNodeParamsInBufferFromPtNodePos(ptNodePos));
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if (multiBigramMap) {
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return multiBigramMap->getBigramProbability(this /* structurePolicy */, prevWordIds,
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wordId, ptNodeParams.getProbability());
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}
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if (prevWordIds) {
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const int probability = getProbabilityOfWord(prevWordIds, wordId);
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if (probability != NOT_A_PROBABILITY) {
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return probability;
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}
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}
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return getProbability(ptNodeParams.getProbability(), NOT_A_PROBABILITY);
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// TODO: Support n-gram.
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return mBuffers->getLanguageModelDictContent()->getWordProbability(
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WordIdArrayView::singleElementView(prevWordIds), wordId);
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}
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int Ver4PatriciaTriePolicy::getProbability(const int unigramProbability,
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@ -166,7 +154,7 @@ int Ver4PatriciaTriePolicy::getProbabilityOfWord(const int *const prevWordIds,
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// TODO: Support n-gram.
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const ProbabilityEntry probabilityEntry =
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mBuffers->getLanguageModelDictContent()->getNgramProbabilityEntry(
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IntArrayView::fromObject(prevWordIds), wordId);
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IntArrayView::singleElementView(prevWordIds), wordId);
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if (!probabilityEntry.isValid()) {
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return NOT_A_PROBABILITY;
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}
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@ -194,7 +182,7 @@ void Ver4PatriciaTriePolicy::iterateNgramEntries(const int *const prevWordIds,
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// TODO: Support n-gram.
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const auto languageModelDictContent = mBuffers->getLanguageModelDictContent();
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for (const auto entry : languageModelDictContent->getProbabilityEntries(
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WordIdArrayView::fromObject(prevWordIds))) {
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WordIdArrayView::singleElementView(prevWordIds))) {
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const ProbabilityEntry &probabilityEntry = entry.getProbabilityEntry();
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const int probability = probabilityEntry.hasHistoricalInfo() ?
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ForgettingCurveUtils::decodeProbability(
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@ -511,7 +499,7 @@ const WordProperty Ver4PatriciaTriePolicy::getWordProperty(
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// Fetch bigram information.
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// TODO: Support n-gram.
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std::vector<BigramProperty> bigrams;
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const WordIdArrayView prevWordIds = WordIdArrayView::fromObject(&wordId);
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const WordIdArrayView prevWordIds = WordIdArrayView::singleElementView(&wordId);
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int bigramWord1CodePoints[MAX_WORD_LENGTH];
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for (const auto entry : mBuffers->getLanguageModelDictContent()->getProbabilityEntries(
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prevWordIds)) {
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@ -48,6 +48,11 @@ class ForgettingCurveUtils {
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static bool needsToDecay(const bool mindsBlockByDecay, const int unigramCount,
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const int bigramCount, const HeaderPolicy *const headerPolicy);
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// TODO: Improve probability computation method and remove this.
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static int getProbabilityBiasForNgram(const int n) {
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return (n - 1) * MULTIPLIER_TWO_IN_PROBABILITY_SCALE;
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}
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AK_FORCE_INLINE static int getUnigramCountHardLimit(const int maxUnigramCount) {
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return static_cast<int>(static_cast<float>(maxUnigramCount)
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* UNIGRAM_COUNT_HARD_LIMIT_WEIGHT);
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@ -61,9 +61,9 @@ class IntArrayView {
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return IntArrayView(array, N);
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}
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// Returns a view that points one int object. Does not take ownership of the given object.
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AK_FORCE_INLINE static IntArrayView fromObject(const int *const object) {
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return IntArrayView(object, 1);
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// Returns a view that points one int object.
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AK_FORCE_INLINE static IntArrayView singleElementView(const int *const ptr) {
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return IntArrayView(ptr, 1);
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}
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AK_FORCE_INLINE int operator[](const size_t index) const {
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@ -26,28 +26,28 @@ namespace latinime {
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namespace {
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TEST(LanguageModelDictContentTest, TestUnigramProbability) {
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LanguageModelDictContent LanguageModelDictContent(false /* useHistoricalInfo */);
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LanguageModelDictContent languageModelDictContent(false /* useHistoricalInfo */);
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const int flag = 0xFF;
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const int probability = 10;
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const int wordId = 100;
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const ProbabilityEntry probabilityEntry(flag, probability);
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LanguageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry);
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languageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry);
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const ProbabilityEntry entry =
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LanguageModelDictContent.getProbabilityEntry(wordId);
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languageModelDictContent.getProbabilityEntry(wordId);
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EXPECT_EQ(flag, entry.getFlags());
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EXPECT_EQ(probability, entry.getProbability());
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// Remove
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EXPECT_TRUE(LanguageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_FALSE(LanguageModelDictContent.getProbabilityEntry(wordId).isValid());
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EXPECT_FALSE(LanguageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_TRUE(LanguageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry));
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EXPECT_TRUE(LanguageModelDictContent.getProbabilityEntry(wordId).isValid());
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EXPECT_TRUE(languageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_FALSE(languageModelDictContent.getProbabilityEntry(wordId).isValid());
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EXPECT_FALSE(languageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_TRUE(languageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry));
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EXPECT_TRUE(languageModelDictContent.getProbabilityEntry(wordId).isValid());
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}
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TEST(LanguageModelDictContentTest, TestUnigramProbabilityWithHistoricalInfo) {
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LanguageModelDictContent LanguageModelDictContent(true /* useHistoricalInfo */);
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LanguageModelDictContent languageModelDictContent(true /* useHistoricalInfo */);
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const int flag = 0xF0;
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const int timestamp = 0x3FFFFFFF;
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@ -56,19 +56,19 @@ TEST(LanguageModelDictContentTest, TestUnigramProbabilityWithHistoricalInfo) {
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const int wordId = 100;
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const HistoricalInfo historicalInfo(timestamp, level, count);
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const ProbabilityEntry probabilityEntry(flag, &historicalInfo);
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LanguageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry);
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const ProbabilityEntry entry = LanguageModelDictContent.getProbabilityEntry(wordId);
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languageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry);
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const ProbabilityEntry entry = languageModelDictContent.getProbabilityEntry(wordId);
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EXPECT_EQ(flag, entry.getFlags());
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EXPECT_EQ(timestamp, entry.getHistoricalInfo()->getTimeStamp());
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EXPECT_EQ(level, entry.getHistoricalInfo()->getLevel());
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EXPECT_EQ(count, entry.getHistoricalInfo()->getCount());
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// Remove
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EXPECT_TRUE(LanguageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_FALSE(LanguageModelDictContent.getProbabilityEntry(wordId).isValid());
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EXPECT_FALSE(LanguageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_TRUE(LanguageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry));
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EXPECT_TRUE(LanguageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_TRUE(languageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_FALSE(languageModelDictContent.getProbabilityEntry(wordId).isValid());
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EXPECT_FALSE(languageModelDictContent.removeProbabilityEntry(wordId));
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EXPECT_TRUE(languageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry));
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EXPECT_TRUE(languageModelDictContent.removeProbabilityEntry(wordId));
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}
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TEST(LanguageModelDictContentTest, TestIterateProbabilityEntry) {
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@ -89,5 +89,31 @@ TEST(LanguageModelDictContentTest, TestIterateProbabilityEntry) {
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EXPECT_TRUE(wordIdSet.empty());
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}
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TEST(LanguageModelDictContentTest, TestGetWordProbability) {
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LanguageModelDictContent languageModelDictContent(false /* useHistoricalInfo */);
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const int flag = 0xFF;
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const int probability = 10;
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const int bigramProbability = 20;
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const int trigramProbability = 30;
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const int wordId = 100;
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const int prevWordIdArray[] = { 1, 2 };
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const WordIdArrayView prevWordIds = WordIdArrayView::fromFixedSizeArray(prevWordIdArray);
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const ProbabilityEntry probabilityEntry(flag, probability);
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languageModelDictContent.setProbabilityEntry(wordId, &probabilityEntry);
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const ProbabilityEntry bigramProbabilityEntry(flag, bigramProbability);
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languageModelDictContent.setProbabilityEntry(prevWordIds[0], &probabilityEntry);
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languageModelDictContent.setNgramProbabilityEntry(prevWordIds.limit(1), wordId,
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&bigramProbabilityEntry);
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EXPECT_EQ(bigramProbability, languageModelDictContent.getWordProbability(prevWordIds, wordId));
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const ProbabilityEntry trigramProbabilityEntry(flag, trigramProbability);
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languageModelDictContent.setNgramProbabilityEntry(prevWordIds.limit(1),
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prevWordIds[1], &probabilityEntry);
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languageModelDictContent.setNgramProbabilityEntry(prevWordIds.limit(2), wordId,
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&trigramProbabilityEntry);
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EXPECT_EQ(trigramProbability, languageModelDictContent.getWordProbability(prevWordIds, wordId));
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}
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} // namespace
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} // namespace latinime
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@ -52,7 +52,7 @@ TEST(IntArrayViewTest, TestConstructFromArray) {
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TEST(IntArrayViewTest, TestConstructFromObject) {
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const int object = 10;
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const auto intArrayView = IntArrayView::fromObject(&object);
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const auto intArrayView = IntArrayView::singleElementView(&object);
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EXPECT_EQ(1u, intArrayView.size());
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EXPECT_EQ(object, intArrayView[0]);
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}
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