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https://gitlab.futo.org/keyboard/latinime.git
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am 9465819c
: Merge "Add BinaryDictionary.getBigramProbabilityNative()."
* commit '9465819cf6f2e6c2074daaae60c5efc0c170185e': Add BinaryDictionary.getBigramProbabilityNative().
This commit is contained in:
commit
bb11d26649
@ -109,7 +109,7 @@ public final class BinaryDictionary extends Dictionary {
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private static native void flushWithGCNative(long dict, String filePath);
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private static native void closeNative(long dict);
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private static native int getProbabilityNative(long dict, int[] word);
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private static native boolean isValidBigramNative(long dict, int[] word0, int[] word1);
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private static native int getBigramProbabilityNative(long dict, int[] word0, int[] word1);
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private static native int getSuggestionsNative(long dict, long proximityInfo,
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long traverseSession, int[] xCoordinates, int[] yCoordinates, int[] times,
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int[] pointerIds, int[] inputCodePoints, int inputSize, int commitPoint,
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@ -122,6 +122,8 @@ public final class BinaryDictionary extends Dictionary {
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private static native void addBigramWordsNative(long dict, int[] word0, int[] word1,
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int probability);
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private static native void removeBigramWordsNative(long dict, int[] word0, int[] word1);
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private static native int calculateProbabilityNative(long dict, int unigramProbability,
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int bigramProbability);
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// TODO: Move native dict into session
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private final void loadDictionary(final String path, final long startOffset,
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@ -219,12 +221,12 @@ public final class BinaryDictionary extends Dictionary {
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@Override
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public boolean isValidWord(final String word) {
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return getFrequency(word) >= 0;
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return getFrequency(word) != NOT_A_PROBABILITY;
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}
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@Override
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public int getFrequency(final String word) {
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if (word == null) return -1;
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if (word == null) return NOT_A_PROBABILITY;
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int[] codePoints = StringUtils.toCodePointArray(word);
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return getProbabilityNative(mNativeDict, codePoints);
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}
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@ -232,10 +234,14 @@ public final class BinaryDictionary extends Dictionary {
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// TODO: Add a batch process version (isValidBigramMultiple?) to avoid excessive numbers of jni
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// calls when checking for changes in an entire dictionary.
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public boolean isValidBigram(final String word0, final String word1) {
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if (TextUtils.isEmpty(word0) || TextUtils.isEmpty(word1)) return false;
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return getBigramProbability(word0, word1) != NOT_A_PROBABILITY;
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}
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public int getBigramProbability(final String word0, final String word1) {
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if (TextUtils.isEmpty(word0) || TextUtils.isEmpty(word1)) return NOT_A_PROBABILITY;
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final int[] codePoints0 = StringUtils.toCodePointArray(word0);
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final int[] codePoints1 = StringUtils.toCodePointArray(word1);
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return isValidBigramNative(mNativeDict, codePoints0, codePoints1);
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return getBigramProbabilityNative(mNativeDict, codePoints0, codePoints1);
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}
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// Add a unigram entry to binary dictionary in native code.
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@ -285,6 +291,12 @@ public final class BinaryDictionary extends Dictionary {
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return needsToRunGCNative(mNativeDict);
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}
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@UsedForTesting
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public int calculateProbability(final int unigramProbability, final int bigramProbability) {
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if (!isValidDictionary()) return NOT_A_PROBABILITY;
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return calculateProbabilityNative(mNativeDict, unigramProbability, bigramProbability);
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}
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@Override
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public boolean shouldAutoCommit(final SuggestedWordInfo candidate) {
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// TODO: actually use the confidence rather than use this completely broken heuristic
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@ -188,8 +188,8 @@ static jint latinime_BinaryDictionary_getProbability(JNIEnv *env, jclass clazz,
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return dictionary->getProbability(codePoints, wordLength);
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}
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static jboolean latinime_BinaryDictionary_isValidBigram(JNIEnv *env, jclass clazz, jlong dict,
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jintArray word0, jintArray word1) {
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static jint latinime_BinaryDictionary_getBigramProbability(JNIEnv *env, jclass clazz,
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jlong dict, jintArray word0, jintArray word1) {
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Dictionary *dictionary = reinterpret_cast<Dictionary *>(dict);
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if (!dictionary) return JNI_FALSE;
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const jsize word0Length = env->GetArrayLength(word0);
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@ -198,7 +198,8 @@ static jboolean latinime_BinaryDictionary_isValidBigram(JNIEnv *env, jclass claz
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int word1CodePoints[word1Length];
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env->GetIntArrayRegion(word0, 0, word0Length, word0CodePoints);
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env->GetIntArrayRegion(word1, 0, word1Length, word1CodePoints);
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return dictionary->isValidBigram(word0CodePoints, word0Length, word1CodePoints, word1Length);
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return dictionary->getBigramProbability(word0CodePoints, word0Length, word1CodePoints,
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word1Length);
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}
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static jfloat latinime_BinaryDictionary_calcNormalizedScore(JNIEnv *env, jclass clazz,
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@ -269,6 +270,16 @@ static void latinime_BinaryDictionary_removeBigramWords(JNIEnv *env, jclass claz
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word1Length);
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}
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static int latinime_BinaryDictionary_calculateProbabilityNative(JNIEnv *env, jclass clazz,
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jlong dict, jint unigramProbability, jint bigramProbability) {
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Dictionary *dictionary = reinterpret_cast<Dictionary *>(dict);
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if (!dictionary) {
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return NOT_A_PROBABILITY;
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}
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return dictionary->getDictionaryStructurePolicy()->getProbability(unigramProbability,
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bigramProbability);
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}
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static const JNINativeMethod sMethods[] = {
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{
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const_cast<char *>("openNative"),
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@ -306,9 +317,9 @@ static const JNINativeMethod sMethods[] = {
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reinterpret_cast<void *>(latinime_BinaryDictionary_getProbability)
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},
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{
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const_cast<char *>("isValidBigramNative"),
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const_cast<char *>("(J[I[I)Z"),
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reinterpret_cast<void *>(latinime_BinaryDictionary_isValidBigram)
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const_cast<char *>("getBigramProbabilityNative"),
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const_cast<char *>("(J[I[I)I"),
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reinterpret_cast<void *>(latinime_BinaryDictionary_getBigramProbability)
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},
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{
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const_cast<char *>("calcNormalizedScoreNative"),
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@ -334,6 +345,11 @@ static const JNINativeMethod sMethods[] = {
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const_cast<char *>("removeBigramWordsNative"),
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const_cast<char *>("(J[I[I)V"),
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reinterpret_cast<void *>(latinime_BinaryDictionary_removeBigramWords)
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},
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{
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const_cast<char *>("calculateProbabilityNative"),
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const_cast<char *>("(JII)I"),
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reinterpret_cast<void *>(latinime_BinaryDictionary_calculateProbabilityNative)
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}
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};
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@ -150,24 +150,26 @@ int BigramDictionary::getBigramListPositionForWord(const int *prevWord, const in
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return mDictionaryStructurePolicy->getBigramsPositionOfNode(pos);
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}
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bool BigramDictionary::isValidBigram(const int *word0, int length0, const int *word1,
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int BigramDictionary::getBigramProbability(const int *word0, int length0, const int *word1,
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int length1) const {
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int pos = getBigramListPositionForWord(word0, length0, false /* forceLowerCaseSearch */);
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// getBigramListPositionForWord returns 0 if this word isn't in the dictionary or has no bigrams
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if (NOT_A_DICT_POS == pos) return false;
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if (NOT_A_DICT_POS == pos) return NOT_A_PROBABILITY;
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int nextWordPos = mDictionaryStructurePolicy->getTerminalNodePositionOfWord(word1, length1,
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false /* forceLowerCaseSearch */);
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if (NOT_A_DICT_POS == nextWordPos) return false;
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if (NOT_A_DICT_POS == nextWordPos) return NOT_A_PROBABILITY;
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BinaryDictionaryBigramsIterator bigramsIt(
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mDictionaryStructurePolicy->getBigramsStructurePolicy(), pos);
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while (bigramsIt.hasNext()) {
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bigramsIt.next();
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if (bigramsIt.getBigramPos() == nextWordPos) {
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return true;
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return mDictionaryStructurePolicy->getProbability(
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mDictionaryStructurePolicy->getUnigramProbabilityOfPtNode(nextWordPos),
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bigramsIt.getProbability());
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}
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}
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return false;
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return NOT_A_PROBABILITY;
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}
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// TODO: Move functions related to bigram to here
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@ -29,7 +29,7 @@ class BigramDictionary {
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int getPredictions(const int *word, int length, int *outBigramCodePoints,
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int *outBigramProbability, int *outputTypes) const;
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bool isValidBigram(const int *word1, int length1, const int *word2, int length2) const;
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int getBigramProbability(const int *word1, int length1, const int *word2, int length2) const;
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~BigramDictionary();
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private:
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@ -93,8 +93,9 @@ int Dictionary::getProbability(const int *word, int length) const {
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return getDictionaryStructurePolicy()->getUnigramProbabilityOfPtNode(pos);
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}
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bool Dictionary::isValidBigram(const int *word0, int length0, const int *word1, int length1) const {
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return mBigramDictionary->isValidBigram(word0, length0, word1, length1);
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int Dictionary::getBigramProbability(const int *word0, int length0, const int *word1,
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int length1) const {
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return mBigramDictionary->getBigramProbability(word0, length0, word1, length1);
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}
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void Dictionary::addUnigramWord(const int *const word, const int length, const int probability) {
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@ -67,7 +67,7 @@ class Dictionary {
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int getProbability(const int *word, int length) const;
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bool isValidBigram(const int *word0, int length0, const int *word1, int length1) const;
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int getBigramProbability(const int *word0, int length0, const int *word1, int length1) const;
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void addUnigramWord(const int *const word, const int length, const int probability);
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@ -151,7 +151,7 @@ public class BinaryDictionaryTests extends AndroidTestCase {
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final int[] codePointSet = CodePointUtils.generateCodePointSet(codePointSetSize, random);
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for (int i = 0; i < wordCount; ++i) {
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final String word = CodePointUtils.generateWord(random, codePointSet);
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probabilityMap.put(word, random.nextInt() & 0xFF);
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probabilityMap.put(word, random.nextInt(0xFF));
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}
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for (String word : probabilityMap.keySet()) {
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binaryDictionary.addUnigramWord(word, probabilityMap.get(word));
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@ -163,8 +163,6 @@ public class BinaryDictionaryTests extends AndroidTestCase {
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}
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public void testAddBigramWords() {
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// TODO: Add a test to check the frequency of the bigram score which uses current value
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// calculated in the native code
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File dictFile = null;
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try {
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dictFile = createEmptyDictionaryAndGetFile("TestBinaryDictionary");
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@ -179,6 +177,7 @@ public class BinaryDictionaryTests extends AndroidTestCase {
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final int unigramProbability = 100;
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final int bigramProbability = 10;
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final int updatedBigramProbability = 15;
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binaryDictionary.addUnigramWord("aaa", unigramProbability);
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binaryDictionary.addUnigramWord("abb", unigramProbability);
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binaryDictionary.addUnigramWord("bcc", unigramProbability);
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@ -187,21 +186,49 @@ public class BinaryDictionaryTests extends AndroidTestCase {
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binaryDictionary.addBigramWords("abb", "aaa", bigramProbability);
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binaryDictionary.addBigramWords("abb", "bcc", bigramProbability);
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final int probability = binaryDictionary.calculateProbability(unigramProbability,
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bigramProbability);
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assertEquals(true, binaryDictionary.isValidBigram("aaa", "abb"));
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assertEquals(true, binaryDictionary.isValidBigram("aaa", "bcc"));
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assertEquals(true, binaryDictionary.isValidBigram("abb", "aaa"));
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assertEquals(true, binaryDictionary.isValidBigram("abb", "bcc"));
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assertEquals(probability, binaryDictionary.getBigramProbability("aaa", "abb"));
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assertEquals(probability, binaryDictionary.getBigramProbability("aaa", "bcc"));
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assertEquals(probability, binaryDictionary.getBigramProbability("abb", "aaa"));
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assertEquals(probability, binaryDictionary.getBigramProbability("abb", "bcc"));
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binaryDictionary.addBigramWords("aaa", "abb", updatedBigramProbability);
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final int updatedProbability = binaryDictionary.calculateProbability(unigramProbability,
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updatedBigramProbability);
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assertEquals(updatedProbability, binaryDictionary.getBigramProbability("aaa", "abb"));
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assertEquals(false, binaryDictionary.isValidBigram("bcc", "aaa"));
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assertEquals(false, binaryDictionary.isValidBigram("bcc", "bbc"));
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assertEquals(false, binaryDictionary.isValidBigram("aaa", "aaa"));
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assertEquals(Dictionary.NOT_A_PROBABILITY,
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binaryDictionary.getBigramProbability("bcc", "aaa"));
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assertEquals(Dictionary.NOT_A_PROBABILITY,
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binaryDictionary.getBigramProbability("bcc", "bbc"));
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assertEquals(Dictionary.NOT_A_PROBABILITY,
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binaryDictionary.getBigramProbability("aaa", "aaa"));
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// Testing bigram link.
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binaryDictionary.addUnigramWord("abcde", unigramProbability);
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binaryDictionary.addUnigramWord("fghij", unigramProbability);
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binaryDictionary.addBigramWords("abcde", "fghij", bigramProbability);
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binaryDictionary.addUnigramWord("fgh", unigramProbability);
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binaryDictionary.addUnigramWord("abc", unigramProbability);
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binaryDictionary.addUnigramWord("f", unigramProbability);
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assertEquals(probability, binaryDictionary.getBigramProbability("abcde", "fghij"));
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assertEquals(Dictionary.NOT_A_PROBABILITY,
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binaryDictionary.getBigramProbability("abcde", "fgh"));
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binaryDictionary.addBigramWords("abcde", "fghij", updatedBigramProbability);
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assertEquals(updatedProbability, binaryDictionary.getBigramProbability("abcde", "fghij"));
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dictFile.delete();
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}
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public void testRandomlyAddBigramWords() {
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// TODO: Add a test to check the frequency of the bigram score which uses current value
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// calculated in the native code
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final int wordCount = 100;
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final int bigramCount = 1000;
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final int codePointSetSize = 50;
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@ -222,29 +249,38 @@ public class BinaryDictionaryTests extends AndroidTestCase {
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// Test a word that isn't contained within the dictionary.
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final Random random = new Random(seed);
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final int[] codePointSet = CodePointUtils.generateCodePointSet(codePointSetSize, random);
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final int unigramProbability = 100;
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final int bigramProbability = 10;
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final int[] unigramProbabilities = new int[wordCount];
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for (int i = 0; i < wordCount; ++i) {
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final String word = CodePointUtils.generateWord(random, codePointSet);
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words.add(word);
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final int unigramProbability = random.nextInt(0xFF);
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unigramProbabilities[i] = unigramProbability;
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binaryDictionary.addUnigramWord(word, unigramProbability);
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}
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final boolean[][] bigramRelations = new boolean[wordCount][wordCount];
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final int[][] probabilities = new int[wordCount][wordCount];
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for (int i = 0; i < wordCount; ++i) {
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for (int j = 0; j < wordCount; ++j) {
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probabilities[i][j] = Dictionary.NOT_A_PROBABILITY;
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}
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}
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for (int i = 0; i < bigramCount; i++) {
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final int word0Index = random.nextInt(wordCount);
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final int word1Index = random.nextInt(wordCount);
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final String word0 = words.get(word0Index);
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final String word1 = words.get(word1Index);
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bigramRelations[word0Index][word1Index] = true;
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final int bigramProbability = random.nextInt(0xF);
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probabilities[word0Index][word1Index] = binaryDictionary.calculateProbability(
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unigramProbabilities[word1Index], bigramProbability);
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binaryDictionary.addBigramWords(word0, word1, bigramProbability);
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}
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for (int i = 0; i < words.size(); i++) {
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for (int j = 0; j < words.size(); j++) {
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assertEquals(bigramRelations[i][j],
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binaryDictionary.isValidBigram(words.get(i), words.get(j)));
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assertEquals(probabilities[i][j],
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binaryDictionary.getBigramProbability(words.get(i), words.get(j)));
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}
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}
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