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-rw-r--r--native/jni/src/correction.cpp10
-rw-r--r--native/jni/src/correction.h2
-rw-r--r--native/jni/src/defines.h10
-rw-r--r--native/jni/src/unigram_dictionary.cpp13
-rw-r--r--native/jni/src/words_priority_queue.h79
5 files changed, 75 insertions, 39 deletions
diff --git a/native/jni/src/correction.cpp b/native/jni/src/correction.cpp
index a1f812909..5ae34cd02 100644
--- a/native/jni/src/correction.cpp
+++ b/native/jni/src/correction.cpp
@@ -1113,7 +1113,7 @@ int Correction::RankingAlgorithm::editDistance(const unsigned short* before,
// So, we can normalize original score by dividing pow(2, min(b.l(),a.l())) * 255 * 2.
/* static */
-double Correction::RankingAlgorithm::calcNormalizedScore(const unsigned short* before,
+float Correction::RankingAlgorithm::calcNormalizedScore(const unsigned short* before,
const int beforeLength, const unsigned short* after, const int afterLength,
const int score) {
if (0 == beforeLength || 0 == afterLength) {
@@ -1131,14 +1131,14 @@ double Correction::RankingAlgorithm::calcNormalizedScore(const unsigned short* b
return 0;
}
- const double maxScore = score >= S_INT_MAX ? S_INT_MAX : MAX_INITIAL_SCORE
- * pow((double)TYPED_LETTER_MULTIPLIER,
- (double)min(beforeLength, afterLength - spaceCount)) * FULL_WORD_MULTIPLIER;
+ const float maxScore = score >= S_INT_MAX ? S_INT_MAX : MAX_INITIAL_SCORE
+ * pow((float)TYPED_LETTER_MULTIPLIER,
+ (float)min(beforeLength, afterLength - spaceCount)) * FULL_WORD_MULTIPLIER;
// add a weight based on edit distance.
// distance <= max(afterLength, beforeLength) == afterLength,
// so, 0 <= distance / afterLength <= 1
- const double weight = 1.0 - (double) distance / afterLength;
+ const float weight = 1.0 - (float) distance / afterLength;
return (score / maxScore) * weight;
}
diff --git a/native/jni/src/correction.h b/native/jni/src/correction.h
index 1b4e4bf4e..1ac4b8782 100644
--- a/native/jni/src/correction.h
+++ b/native/jni/src/correction.h
@@ -162,7 +162,7 @@ class Correction {
static int calcFreqForSplitMultipleWords(const int *freqArray, const int *wordLengthArray,
const int wordCount, const Correction* correction, const bool isSpaceProximity,
const unsigned short *word);
- static double calcNormalizedScore(const unsigned short* before, const int beforeLength,
+ static float calcNormalizedScore(const unsigned short* before, const int beforeLength,
const unsigned short* after, const int afterLength, const int score);
static int editDistance(const unsigned short* before,
const int beforeLength, const unsigned short* after, const int afterLength);
diff --git a/native/jni/src/defines.h b/native/jni/src/defines.h
index cb3dbb115..c6ad66abe 100644
--- a/native/jni/src/defines.h
+++ b/native/jni/src/defines.h
@@ -46,8 +46,8 @@ static inline void dumpWord(const unsigned short* word, const int length) {
#include <time.h>
#define PROF_BUF_SIZE 100
-static double profile_buf[PROF_BUF_SIZE];
-static double profile_old[PROF_BUF_SIZE];
+static float profile_buf[PROF_BUF_SIZE];
+static float profile_old[PROF_BUF_SIZE];
static unsigned int profile_counter[PROF_BUF_SIZE];
#define PROF_RESET prof_reset()
@@ -74,8 +74,8 @@ static inline void prof_out(void) {
AKLOGI("Error: You must call PROF_OPEN before PROF_CLOSE.");
}
AKLOGI("Total time is %6.3f ms.",
- profile_buf[PROF_BUF_SIZE - 1] * 1000 / (double)CLOCKS_PER_SEC);
- double all = 0;
+ profile_buf[PROF_BUF_SIZE - 1] * 1000 / (float)CLOCKS_PER_SEC);
+ float all = 0;
for (int i = 0; i < PROF_BUF_SIZE - 1; ++i) {
all += profile_buf[i];
}
@@ -84,7 +84,7 @@ static inline void prof_out(void) {
if (profile_buf[i] != 0) {
AKLOGI("(%d): Used %4.2f%%, %8.4f ms. Called %d times.",
i, (profile_buf[i] * 100 / all),
- profile_buf[i] * 1000 / (double)CLOCKS_PER_SEC, profile_counter[i]);
+ profile_buf[i] * 1000 / (float)CLOCKS_PER_SEC, profile_counter[i]);
}
}
}
diff --git a/native/jni/src/unigram_dictionary.cpp b/native/jni/src/unigram_dictionary.cpp
index 9234b1b52..ee8c49703 100644
--- a/native/jni/src/unigram_dictionary.cpp
+++ b/native/jni/src/unigram_dictionary.cpp
@@ -202,16 +202,17 @@ int UnigramDictionary::getSuggestions(ProximityInfo *proximityInfo,
PROF_START(20);
if (DEBUG_DICT) {
- double ns = queuePool->getMasterQueue()->getHighestNormalizedScore(
+ float ns = queuePool->getMasterQueue()->getHighestNormalizedScore(
proximityInfo->getPrimaryInputWord(), codesSize, 0, 0, 0);
ns += 0;
AKLOGI("Max normalized score = %f", ns);
}
const int suggestedWordsCount =
- queuePool->getMasterQueue()->outputSuggestions(frequencies, outWords);
+ queuePool->getMasterQueue()->outputSuggestions(
+ proximityInfo->getPrimaryInputWord(), codesSize, frequencies, outWords);
if (DEBUG_DICT) {
- double ns = queuePool->getMasterQueue()->getHighestNormalizedScore(
+ float ns = queuePool->getMasterQueue()->getHighestNormalizedScore(
proximityInfo->getPrimaryInputWord(), codesSize, 0, 0, 0);
ns += 0;
AKLOGI("Returning %d words", suggestedWordsCount);
@@ -254,7 +255,7 @@ void UnigramDictionary::getWordSuggestions(ProximityInfo *proximityInfo,
bool hasAutoCorrectionCandidate = false;
WordsPriorityQueue* masterQueue = queuePool->getMasterQueue();
if (masterQueue->size() > 0) {
- double nsForMaster = masterQueue->getHighestNormalizedScore(
+ float nsForMaster = masterQueue->getHighestNormalizedScore(
proximityInfo->getPrimaryInputWord(), inputLength, 0, 0, 0);
hasAutoCorrectionCandidate = (nsForMaster > START_TWO_WORDS_CORRECTION_THRESHOLD);
}
@@ -283,7 +284,7 @@ void UnigramDictionary::getWordSuggestions(ProximityInfo *proximityInfo,
const int score = sw->mScore;
const unsigned short* word = sw->mWord;
const int wordLength = sw->mWordLength;
- double ns = Correction::RankingAlgorithm::calcNormalizedScore(
+ float ns = Correction::RankingAlgorithm::calcNormalizedScore(
proximityInfo->getPrimaryInputWord(), i, word, wordLength, score);
ns += 0;
AKLOGI("--- TOP SUB WORDS for %d --- %d %f [%d]", i, score, ns,
@@ -451,7 +452,7 @@ bool UnigramDictionary::getSubStringSuggestion(
return false;
}
int score = 0;
- const double ns = queue->getHighestNormalizedScore(
+ const float ns = queue->getHighestNormalizedScore(
proximityInfo->getPrimaryInputWord(), inputWordLength,
&tempOutputWord, &score, &nextWordLength);
if (DEBUG_DICT) {
diff --git a/native/jni/src/words_priority_queue.h b/native/jni/src/words_priority_queue.h
index 249962eec..7629251d6 100644
--- a/native/jni/src/words_priority_queue.h
+++ b/native/jni/src/words_priority_queue.h
@@ -92,10 +92,12 @@ class WordsPriorityQueue {
return sw;
}
- int outputSuggestions(int *frequencies, unsigned short *outputChars) {
+ int outputSuggestions(const unsigned short* before, const int beforeLength,
+ int *frequencies, unsigned short *outputChars) {
mHighestSuggestedWord = 0;
const unsigned int size = min(
MAX_WORDS, static_cast<unsigned int>(mSuggestions.size()));
+ SuggestedWord* swBuffer[size];
int index = size - 1;
while (!mSuggestions.empty() && index >= 0) {
SuggestedWord* sw = mSuggestions.top();
@@ -103,17 +105,45 @@ class WordsPriorityQueue {
AKLOGI("dump word. %d", sw->mScore);
DUMP_WORD(sw->mWord, sw->mWordLength);
}
+ swBuffer[index] = sw;
+ mSuggestions.pop();
+ --index;
+ }
+ if (size >= 2) {
+ SuggestedWord* nsMaxSw = 0;
+ unsigned int maxIndex = 0;
+ float maxNs = 0;
+ for (unsigned int i = 0; i < size; ++i) {
+ SuggestedWord* tempSw = swBuffer[i];
+ if (!tempSw) {
+ continue;
+ }
+ const float tempNs = getNormalizedScore(tempSw, before, beforeLength, 0, 0, 0);
+ if (tempNs >= maxNs) {
+ maxNs = tempNs;
+ maxIndex = i;
+ nsMaxSw = tempSw;
+ }
+ }
+ if (maxIndex > 0 && nsMaxSw) {
+ memmove(&swBuffer[1], &swBuffer[0], maxIndex * sizeof(SuggestedWord*));
+ swBuffer[0] = nsMaxSw;
+ }
+ }
+ for (unsigned int i = 0; i < size; ++i) {
+ SuggestedWord* sw = swBuffer[i];
+ if (!sw) {
+ AKLOGE("SuggestedWord is null %d", i);
+ continue;
+ }
const unsigned int wordLength = sw->mWordLength;
- char* targetAdr = (char*) outputChars
- + (index) * MAX_WORD_LENGTH * sizeof(short);
- frequencies[index] = sw->mScore;
+ char* targetAdr = (char*) outputChars + i * MAX_WORD_LENGTH * sizeof(short);
+ frequencies[i] = sw->mScore;
memcpy(targetAdr, sw->mWord, (wordLength) * sizeof(short));
if (wordLength < MAX_WORD_LENGTH) {
((unsigned short*) targetAdr)[wordLength] = 0;
}
sw->mUsed = false;
- mSuggestions.pop();
- --index;
}
return size;
}
@@ -142,26 +172,13 @@ class WordsPriorityQueue {
DUMP_WORD(mHighestSuggestedWord->mWord, mHighestSuggestedWord->mWordLength);
}
- double getHighestNormalizedScore(const unsigned short* before, const int beforeLength,
+ float getHighestNormalizedScore(const unsigned short* before, const int beforeLength,
unsigned short** outWord, int *outScore, int *outLength) {
if (!mHighestSuggestedWord) {
return 0.0;
}
- SuggestedWord* sw = mHighestSuggestedWord;
- const int score = sw->mScore;
- unsigned short* word = sw->mWord;
- const int wordLength = sw->mWordLength;
- if (outScore) {
- *outScore = score;
- }
- if (outWord) {
- *outWord = word;
- }
- if (outLength) {
- *outLength = wordLength;
- }
- return Correction::RankingAlgorithm::calcNormalizedScore(
- before, beforeLength, word, wordLength, score);
+ return getNormalizedScore(
+ mHighestSuggestedWord, before, beforeLength, outWord, outScore, outLength);
}
private:
@@ -182,6 +199,24 @@ class WordsPriorityQueue {
return 0;
}
+ static float getNormalizedScore(SuggestedWord* sw, const unsigned short* before,
+ const int beforeLength, unsigned short** outWord, int *outScore, int *outLength) {
+ const int score = sw->mScore;
+ unsigned short* word = sw->mWord;
+ const int wordLength = sw->mWordLength;
+ if (outScore) {
+ *outScore = score;
+ }
+ if (outWord) {
+ *outWord = word;
+ }
+ if (outLength) {
+ *outLength = wordLength;
+ }
+ return Correction::RankingAlgorithm::calcNormalizedScore(
+ before, beforeLength, word, wordLength, score);
+ }
+
typedef std::priority_queue<SuggestedWord*, std::vector<SuggestedWord*>,
wordComparator> Suggestions;
Suggestions mSuggestions;
generated by cgit v1.2.3-83-g751a (git 2.47.1) at 2025-05-20 18:26:56 +0000