* commit 'e398d09a50486d1b91ce109f4bd1a7529560c634': Implement the heuristic for auto-commit.
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commit
e8c011679a
6 changed files with 90 additions and 21 deletions
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@ -44,9 +44,9 @@ public final class BinaryDictionary extends Dictionary {
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private static final int MAX_WORD_LENGTH = Constants.DICTIONARY_MAX_WORD_LENGTH;
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// Must be equal to MAX_RESULTS in native/jni/src/defines.h
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private static final int MAX_RESULTS = 18;
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// Required space count for auto commit.
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// TODO: Remove this heuristic.
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private static final int SPACE_COUNT_FOR_AUTO_COMMIT = 3;
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// The cutoff returned by native for auto-commit confidence.
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// Must be equal to CONFIDENCE_TO_AUTO_COMMIT in native/jni/src/defines.h
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private static final int CONFIDENCE_TO_AUTO_COMMIT = 1000000;
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@UsedForTesting
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public static final String UNIGRAM_COUNT_QUERY = "UNIGRAM_COUNT";
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@ -343,18 +343,7 @@ public final class BinaryDictionary extends Dictionary {
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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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final String word = candidate.mWord;
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final int length = word.length();
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int remainingSpaces = SPACE_COUNT_FOR_AUTO_COMMIT;
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for (int i = 0; i < length; ++i) {
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// This is okay because no low-surrogate and no high-surrogate can ever match the
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// space character, so we don't need to take care of iterating on code points.
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if (Constants.CODE_SPACE == word.charAt(i)) {
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if (0 >= --remainingSpaces) return true;
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}
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}
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return false;
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return candidate.mAutoCommitFirstWordConfidence > CONFIDENCE_TO_AUTO_COMMIT;
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}
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@Override
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@ -298,9 +298,19 @@ static inline void prof_out(void) {
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#define NOT_AN_INDEX (-1)
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#define NOT_A_PROBABILITY (-1)
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#define NOT_A_DICT_POS (S_INT_MIN)
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// A special value to mean the first word confidence makes no sense in this case,
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// e.g. this is not a multi-word suggestion.
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#define NOT_A_FIRST_WORD_CONFIDENCE (S_INT_MIN)
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#define NOT_A_FIRST_WORD_CONFIDENCE (S_INT_MAX)
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// How high the confidence needs to be for us to auto-commit. Arbitrary.
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// This needs to be the same as CONFIDENCE_FOR_AUTO_COMMIT in BinaryDictionary.java
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#define CONFIDENCE_FOR_AUTO_COMMIT (1000000)
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// 80% of the full confidence
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#define DISTANCE_WEIGHT_FOR_AUTO_COMMIT (80 * CONFIDENCE_FOR_AUTO_COMMIT / 100)
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// 100% of the full confidence
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#define LENGTH_WEIGHT_FOR_AUTO_COMMIT (CONFIDENCE_FOR_AUTO_COMMIT)
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// 80% of the full confidence
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#define SPACE_COUNT_WEIGHT_FOR_AUTO_COMMIT (80 * CONFIDENCE_FOR_AUTO_COMMIT / 100)
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#define KEYCODE_SPACE ' '
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#define KEYCODE_SINGLE_QUOTE '\''
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@ -321,6 +321,16 @@ class DicNode {
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DUMP_WORD_AND_SCORE("OUTPUT");
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}
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// "Total" in this context (and other methods in this class) means the whole suggestion. When
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// this represents a multi-word suggestion, the referenced PtNode (in mDicNodeState) is only
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// the one that corresponds to the last word of the suggestion, and all the previous words
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// are concatenated together in mPrevWord - which contains a space at the end.
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int getTotalNodeSpaceCount() const {
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if (isFirstWord()) return 0;
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return CharUtils::getSpaceCount(mDicNodeState.mDicNodeStatePrevWord.mPrevWord,
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mDicNodeState.mDicNodeStatePrevWord.getPrevWordLength());
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}
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int getSecondWordFirstInputIndex(const ProximityInfoState *const pInfoState) const {
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const int inputIndex = mDicNodeState.mDicNodeStatePrevWord.getSecondWordFirstInputIndex();
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if (inputIndex == NOT_AN_INDEX) {
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@ -166,7 +166,11 @@ int Suggest::outputSuggestions(DicTraverseSession *traverseSession, int *frequen
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// TODO: have partial commit work even with multiple pointers.
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const bool outputSecondWordFirstLetterInputIndex =
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traverseSession->isOnlyOnePointerUsed(0 /* pointerId */);
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outputAutoCommitFirstWordConfidence[0] = computeFirstWordConfidence();
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if (terminalSize > 0) {
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// If we have no suggestions, don't write this
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outputAutoCommitFirstWordConfidence[0] =
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computeFirstWordConfidence(&terminals[0]);
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}
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// Output suggestion results here
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for (int terminalIndex = 0; terminalIndex < terminalSize && outputWordIndex < MAX_RESULTS;
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@ -255,9 +259,55 @@ int Suggest::outputSuggestions(DicTraverseSession *traverseSession, int *frequen
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return outputWordIndex;
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}
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int Suggest::computeFirstWordConfidence() const {
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// TODO: implement this.
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return NOT_A_FIRST_WORD_CONFIDENCE;
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int Suggest::computeFirstWordConfidence(const DicNode *const terminalDicNode) const {
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// Get the number of spaces in the first suggestion
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const int spaceCount = terminalDicNode->getTotalNodeSpaceCount();
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// Get the number of characters in the first suggestion
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const int length = terminalDicNode->getTotalNodeCodePointCount();
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// Get the distance for the first word of the suggestion
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const float distance = terminalDicNode->getNormalizedCompoundDistanceAfterFirstWord();
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// Arbitrarily, we give a score whose useful values range from 0 to 1,000,000.
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// 1,000,000 will be the cutoff to auto-commit. It's fine if the number is under 0 or
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// above 1,000,000 : under 0 just means it's very bad to commit, and above 1,000,000 means
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// we are very confident.
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// Expected space count is 1 ~ 5
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static const int MIN_EXPECTED_SPACE_COUNT = 1;
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static const int MAX_EXPECTED_SPACE_COUNT = 5;
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// Expected length is about 4 ~ 30
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static const int MIN_EXPECTED_LENGTH = 4;
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static const int MAX_EXPECTED_LENGTH = 30;
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// Expected distance is about 0.2 ~ 2.0, but consider 0.0 ~ 2.0
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static const float MIN_EXPECTED_DISTANCE = 0.0;
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static const float MAX_EXPECTED_DISTANCE = 2.0;
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// This is not strict: it's where most stuff will be falling, but it's still fine if it's
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// outside these values. We want to output a value that reflects all of these. Each factor
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// contributes a bit.
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// We need at least a space.
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if (spaceCount < 1) return NOT_A_FIRST_WORD_CONFIDENCE;
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// The smaller the edit distance, the higher the contribution. MIN_EXPECTED_DISTANCE means 0
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// contribution, while MAX_EXPECTED_DISTANCE means full contribution according to the
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// weight of the distance. Clamp to avoid overflows.
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const float clampedDistance = distance < MIN_EXPECTED_DISTANCE ? MIN_EXPECTED_DISTANCE
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: distance > MAX_EXPECTED_DISTANCE ? MAX_EXPECTED_DISTANCE : distance;
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const int distanceContribution = DISTANCE_WEIGHT_FOR_AUTO_COMMIT
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* (MAX_EXPECTED_DISTANCE - clampedDistance)
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/ (MAX_EXPECTED_DISTANCE - MIN_EXPECTED_DISTANCE);
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// The larger the suggestion length, the larger the contribution. MIN_EXPECTED_LENGTH is no
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// contribution, MAX_EXPECTED_LENGTH is full contribution according to the weight of the
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// length. Length is guaranteed to be between 1 and 48, so we don't need to clamp.
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const int lengthContribution = LENGTH_WEIGHT_FOR_AUTO_COMMIT
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* (length - MIN_EXPECTED_LENGTH) / (MAX_EXPECTED_LENGTH - MIN_EXPECTED_LENGTH);
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// The more spaces, the larger the contribution. MIN_EXPECTED_SPACE_COUNT space is no
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// contribution, MAX_EXPECTED_SPACE_COUNT spaces is full contribution according to the
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// weight of the space count.
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const int spaceContribution = SPACE_COUNT_WEIGHT_FOR_AUTO_COMMIT
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* (spaceCount - MIN_EXPECTED_SPACE_COUNT)
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/ (MAX_EXPECTED_SPACE_COUNT - MIN_EXPECTED_SPACE_COUNT);
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return distanceContribution + lengthContribution + spaceContribution;
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}
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/**
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@ -58,7 +58,7 @@ class Suggest : public SuggestInterface {
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int outputSuggestions(DicTraverseSession *traverseSession, int *frequencies,
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int *outputCodePoints, int *outputIndicesToPartialCommit, int *outputTypes,
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int *outputAutoCommitFirstWordConfidence) const;
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int computeFirstWordConfidence() const;
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int computeFirstWordConfidence(const DicNode *const terminalDicNode) const;
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void initializeSearch(DicTraverseSession *traverseSession, int commitPoint) const;
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void expandCurrentDicNodes(DicTraverseSession *traverseSession) const;
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void processTerminalDicNode(DicTraverseSession *traverseSession, DicNode *dicNode) const;
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@ -75,6 +75,16 @@ class CharUtils {
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return c;
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}
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static AK_FORCE_INLINE int getSpaceCount(const int *const codePointBuffer, const int length) {
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int spaceCount = 0;
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for (int i = 0; i < length; ++i) {
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if (codePointBuffer[i] == KEYCODE_SPACE) {
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++spaceCount;
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}
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}
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return spaceCount;
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}
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static unsigned short latin_tolower(const unsigned short c);
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private:
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