am ee5d8441: Merge "Introduce SuggestionResults and use it for predictions."
* commit 'ee5d8441d175dd32e4b2088f2ac04ded912fa981': Introduce SuggestionResults and use it for predictions.main
commit
d37cf57a2d
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@ -87,6 +87,7 @@ public final class BinaryDictionary extends Dictionary {
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private final String mDictFilePath;
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private final boolean mIsUpdatable;
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private final int[] mInputCodePoints = new int[MAX_WORD_LENGTH];
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private final int[] mOutputSuggestionCount = new int[1];
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private final int[] mOutputCodePoints = new int[MAX_WORD_LENGTH * MAX_RESULTS];
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private final int[] mSpaceIndices = new int[MAX_RESULTS];
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private final int[] mOutputScores = new int[MAX_RESULTS];
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@ -158,10 +159,10 @@ public final class BinaryDictionary extends Dictionary {
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ArrayList<int[]> outBigramTargets, ArrayList<int[]> outBigramProbabilityInfo,
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ArrayList<int[]> outShortcutTargets, ArrayList<Integer> outShortcutProbabilities);
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private static native int getNextWordNative(long dict, int token, int[] outCodePoints);
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private static native int getSuggestionsNative(long dict, long proximityInfo,
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private static native void 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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int[] suggestOptions, int[] prevWordCodePointArray,
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int[] suggestOptions, int[] prevWordCodePointArray, int[] outputSuggestionCount,
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int[] outputCodePoints, int[] outputScores, int[] outputIndices, int[] outputTypes,
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int[] outputAutoCommitFirstWordConfidence);
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private static native void addUnigramWordNative(long dict, int[] word, int probability,
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@ -258,12 +259,13 @@ public final class BinaryDictionary extends Dictionary {
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mNativeSuggestOptions.setIsGesture(isGesture);
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mNativeSuggestOptions.setAdditionalFeaturesOptions(additionalFeaturesOptions);
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// proximityInfo and/or prevWordForBigrams may not be null.
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final int count = getSuggestionsNative(mNativeDict, proximityInfo.getNativeProximityInfo(),
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getSuggestionsNative(mNativeDict, proximityInfo.getNativeProximityInfo(),
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getTraverseSession(sessionId).getSession(), ips.getXCoordinates(),
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ips.getYCoordinates(), ips.getTimes(), ips.getPointerIds(), mInputCodePoints,
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inputSize, 0 /* commitPoint */, mNativeSuggestOptions.getOptions(),
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prevWordCodePointArray, mOutputCodePoints, mOutputScores, mSpaceIndices,
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mOutputTypes, mOutputAutoCommitFirstWordConfidence);
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prevWordCodePointArray, mOutputSuggestionCount, mOutputCodePoints, mOutputScores,
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mSpaceIndices, mOutputTypes, mOutputAutoCommitFirstWordConfidence);
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final int count = mOutputSuggestionCount[0];
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final ArrayList<SuggestedWordInfo> suggestions = CollectionUtils.newArrayList();
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for (int j = 0; j < count; ++j) {
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final int start = j * MAX_WORD_LENGTH;
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@ -40,8 +40,10 @@ LATIN_IME_CORE_SRC_FILES := \
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proximity_info_state.cpp \
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proximity_info_state_utils.cpp) \
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suggest/core/policy/weighting.cpp \
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suggest/core/result/suggestions_output_utils.cpp \
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suggest/core/session/dic_traverse_session.cpp \
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$(addprefix suggest/core/result/, \
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suggestion_results.cpp \
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suggestions_output_utils.cpp) \
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$(addprefix suggest/policyimpl/dictionary/, \
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header/header_policy.cpp \
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header/header_read_write_utils.cpp \
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@ -25,6 +25,7 @@
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#include "jni_common.h"
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#include "suggest/core/dictionary/dictionary.h"
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#include "suggest/core/dictionary/word_property.h"
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#include "suggest/core/result/suggestion_results.h"
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#include "suggest/core/suggest_options.h"
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#include "suggest/policyimpl/dictionary/structure/dictionary_structure_with_buffer_policy_factory.h"
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#include "utils/char_utils.h"
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@ -139,15 +140,20 @@ static int latinime_BinaryDictionary_getFormatVersion(JNIEnv *env, jclass clazz,
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return headerPolicy->getFormatVersionNumber();
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}
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static int latinime_BinaryDictionary_getSuggestions(JNIEnv *env, jclass clazz, jlong dict,
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static void latinime_BinaryDictionary_getSuggestions(JNIEnv *env, jclass clazz, jlong dict,
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jlong proximityInfo, jlong dicTraverseSession, jintArray xCoordinatesArray,
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jintArray yCoordinatesArray, jintArray timesArray, jintArray pointerIdsArray,
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jintArray inputCodePointsArray, jint inputSize, jint commitPoint, jintArray suggestOptions,
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jintArray prevWordCodePointsForBigrams, jintArray outputCodePointsArray,
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jintArray scoresArray, jintArray spaceIndicesArray, jintArray outputTypesArray,
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jintArray outputAutoCommitFirstWordConfidenceArray) {
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jintArray prevWordCodePointsForBigrams, jintArray outSuggestionCount,
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jintArray outCodePointsArray, jintArray outScoresArray, jintArray outSpaceIndicesArray,
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jintArray outTypesArray, jintArray outAutoCommitFirstWordConfidenceArray) {
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Dictionary *dictionary = reinterpret_cast<Dictionary *>(dict);
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if (!dictionary) return 0;
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// Assign 0 to outSuggestionCount here in case of returning earlier in this method.
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int count = 0;
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env->SetIntArrayRegion(outSuggestionCount, 0, 1 /* len */, &count);
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if (!dictionary) {
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return;
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}
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ProximityInfo *pInfo = reinterpret_cast<ProximityInfo *>(proximityInfo);
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DicTraverseSession *traverseSession =
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reinterpret_cast<DicTraverseSession *>(dicTraverseSession);
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@ -181,26 +187,26 @@ static int latinime_BinaryDictionary_getSuggestions(JNIEnv *env, jclass clazz, j
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// Output values
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/* By the way, let's check the output array length here to make sure */
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const jsize outputCodePointsLength = env->GetArrayLength(outputCodePointsArray);
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const jsize outputCodePointsLength = env->GetArrayLength(outCodePointsArray);
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if (outputCodePointsLength != (MAX_WORD_LENGTH * MAX_RESULTS)) {
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AKLOGE("Invalid outputCodePointsLength: %d", outputCodePointsLength);
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ASSERT(false);
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return 0;
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return;
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}
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const jsize scoresLength = env->GetArrayLength(scoresArray);
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const jsize scoresLength = env->GetArrayLength(outScoresArray);
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if (scoresLength != MAX_RESULTS) {
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AKLOGE("Invalid scoresLength: %d", scoresLength);
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ASSERT(false);
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return 0;
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return;
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}
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int outputCodePoints[outputCodePointsLength];
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int scores[scoresLength];
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const jsize spaceIndicesLength = env->GetArrayLength(spaceIndicesArray);
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const jsize spaceIndicesLength = env->GetArrayLength(outSpaceIndicesArray);
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int spaceIndices[spaceIndicesLength];
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const jsize outputTypesLength = env->GetArrayLength(outputTypesArray);
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const jsize outputTypesLength = env->GetArrayLength(outTypesArray);
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int outputTypes[outputTypesLength];
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const jsize outputAutoCommitFirstWordConfidenceLength =
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env->GetArrayLength(outputAutoCommitFirstWordConfidenceArray);
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env->GetArrayLength(outAutoCommitFirstWordConfidenceArray);
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// We only use the first result, as obviously we will only ever autocommit the first one
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ASSERT(outputAutoCommitFirstWordConfidenceLength == 1);
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int outputAutoCommitFirstWordConfidence[outputAutoCommitFirstWordConfidenceLength];
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@ -210,26 +216,30 @@ static int latinime_BinaryDictionary_getSuggestions(JNIEnv *env, jclass clazz, j
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memset(outputTypes, 0, sizeof(outputTypes));
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memset(outputAutoCommitFirstWordConfidence, 0, sizeof(outputAutoCommitFirstWordConfidence));
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int count;
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if (givenSuggestOptions.isGesture() || inputSize > 0) {
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// TODO: Use SuggestionResults to return suggestions.
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count = dictionary->getSuggestions(pInfo, traverseSession, xCoordinates, yCoordinates,
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times, pointerIds, inputCodePoints, inputSize, prevWordCodePoints,
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prevWordCodePointsLength, commitPoint, &givenSuggestOptions, outputCodePoints,
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scores, spaceIndices, outputTypes, outputAutoCommitFirstWordConfidence);
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} else {
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count = dictionary->getBigrams(prevWordCodePoints, prevWordCodePointsLength,
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outputCodePoints, scores, outputTypes);
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SuggestionResults suggestionResults(MAX_RESULTS);
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dictionary->getPredictions(prevWordCodePoints, prevWordCodePointsLength,
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&suggestionResults);
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suggestionResults.outputSuggestions(env, outSuggestionCount, outCodePointsArray,
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outScoresArray, outSpaceIndicesArray, outTypesArray,
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outAutoCommitFirstWordConfidenceArray);
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return;
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}
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// Copy back the output values
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env->SetIntArrayRegion(outputCodePointsArray, 0, outputCodePointsLength, outputCodePoints);
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env->SetIntArrayRegion(scoresArray, 0, scoresLength, scores);
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env->SetIntArrayRegion(spaceIndicesArray, 0, spaceIndicesLength, spaceIndices);
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env->SetIntArrayRegion(outputTypesArray, 0, outputTypesLength, outputTypes);
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env->SetIntArrayRegion(outputAutoCommitFirstWordConfidenceArray, 0,
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env->SetIntArrayRegion(outSuggestionCount, 0, 1 /* len */, &count);
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env->SetIntArrayRegion(outCodePointsArray, 0, outputCodePointsLength, outputCodePoints);
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env->SetIntArrayRegion(outScoresArray, 0, scoresLength, scores);
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env->SetIntArrayRegion(outSpaceIndicesArray, 0, spaceIndicesLength, spaceIndices);
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env->SetIntArrayRegion(outTypesArray, 0, outputTypesLength, outputTypes);
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env->SetIntArrayRegion(outAutoCommitFirstWordConfidenceArray, 0,
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outputAutoCommitFirstWordConfidenceLength, outputAutoCommitFirstWordConfidence);
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return count;
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}
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static jint latinime_BinaryDictionary_getProbability(JNIEnv *env, jclass clazz, jlong dict,
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@ -496,7 +506,7 @@ static const JNINativeMethod sMethods[] = {
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},
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{
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const_cast<char *>("getSuggestionsNative"),
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const_cast<char *>("(JJJ[I[I[I[I[III[I[I[I[I[I[I[I)I"),
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const_cast<char *>("(JJJ[I[I[I[I[III[I[I[I[I[I[I[I[I)V"),
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reinterpret_cast<void *>(latinime_BinaryDictionary_getSuggestions)
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},
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{
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@ -25,6 +25,7 @@
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#include "suggest/core/dictionary/binary_dictionary_bigrams_iterator.h"
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#include "suggest/core/dictionary/dictionary.h"
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#include "suggest/core/policy/dictionary_structure_with_buffer_policy.h"
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#include "suggest/core/result/suggestion_results.h"
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#include "utils/char_utils.h"
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namespace latinime {
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@ -40,71 +41,13 @@ BigramDictionary::BigramDictionary(
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BigramDictionary::~BigramDictionary() {
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}
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void BigramDictionary::addWordBigram(int *word, int length, int probability, int *bigramProbability,
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int *bigramCodePoints, int *outputTypes) const {
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if (length >= MAX_WORD_LENGTH) {
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length = MAX_WORD_LENGTH - 1;
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}
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word[length] = 0;
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if (DEBUG_DICT_FULL) {
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#ifdef FLAG_DBG
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char s[length + 1];
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for (int i = 0; i <= length; i++) s[i] = static_cast<char>(word[i]);
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AKLOGI("Bigram: Found word = %s, freq = %d :", s, probability);
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#endif
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}
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// Find the right insertion point
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int insertAt = 0;
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while (insertAt < MAX_RESULTS) {
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if (probability > bigramProbability[insertAt] || (bigramProbability[insertAt] == probability
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&& length < CharUtils::getCodePointCount(MAX_WORD_LENGTH,
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bigramCodePoints + insertAt * MAX_WORD_LENGTH))) {
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break;
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}
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insertAt++;
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}
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if (DEBUG_DICT_FULL) {
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AKLOGI("Bigram: InsertAt -> %d MAX_RESULTS: %d", insertAt, MAX_RESULTS);
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}
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if (insertAt >= MAX_RESULTS) {
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return;
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}
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// Shift result buffers to insert the new entry.
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memmove(bigramProbability + (insertAt + 1), bigramProbability + insertAt,
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(MAX_RESULTS - insertAt - 1) * sizeof(bigramProbability[0]));
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memmove(outputTypes + (insertAt + 1), outputTypes + insertAt,
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(MAX_RESULTS - insertAt - 1) * sizeof(outputTypes[0]));
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memmove(bigramCodePoints + (insertAt + 1) * MAX_WORD_LENGTH,
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bigramCodePoints + insertAt * MAX_WORD_LENGTH,
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(MAX_RESULTS - insertAt - 1) * sizeof(bigramCodePoints[0]) * MAX_WORD_LENGTH);
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// Put the result.
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bigramProbability[insertAt] = probability;
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outputTypes[insertAt] = Dictionary::KIND_PREDICTION;
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int *dest = bigramCodePoints + insertAt * MAX_WORD_LENGTH;
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while (length--) {
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*dest++ = *word++;
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}
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*dest = 0; // NULL terminate
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if (DEBUG_DICT_FULL) {
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AKLOGI("Bigram: Added word at %d", insertAt);
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}
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}
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/* Parameters :
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* prevWord: the word before, the one for which we need to look up bigrams.
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* prevWordLength: its length.
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* outBigramCodePoints: an array for output, at the same format as outwords for getSuggestions.
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* outBigramProbability: an array to output frequencies.
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* outputTypes: an array to output types.
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* This method returns the number of bigrams this word has, for backward compatibility.
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* outSuggestionResults: SuggestionResults to put the predictions.
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*/
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int BigramDictionary::getPredictions(const int *prevWord, const int prevWordLength,
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int *const outBigramCodePoints, int *const outBigramProbability,
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int *const outputTypes) const {
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// TODO: remove unused arguments, and refrain from storing stuff in members of this class
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// TODO: have "in" arguments before "out" ones, and make out args explicit in the name
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void BigramDictionary::getPredictions(const int *prevWord, const int prevWordLength,
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SuggestionResults *const outSuggestionResults) const {
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int pos = getBigramListPositionForWord(prevWord, prevWordLength,
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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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@ -114,11 +57,10 @@ int BigramDictionary::getPredictions(const int *prevWord, const int prevWordLeng
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true /* forceLowerCaseSearch */);
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}
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// If still no bigrams, we really don't have them!
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if (NOT_A_DICT_POS == pos) return 0;
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if (NOT_A_DICT_POS == pos) return;
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int bigramCount = 0;
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int unigramProbability = 0;
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int bigramBuffer[MAX_WORD_LENGTH];
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int bigramCodePoints[MAX_WORD_LENGTH];
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BinaryDictionaryBigramsIterator bigramsIt(
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mDictionaryStructurePolicy->getBigramsStructurePolicy(), pos);
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while (bigramsIt.hasNext()) {
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@ -128,7 +70,7 @@ int BigramDictionary::getPredictions(const int *prevWord, const int prevWordLeng
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}
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const int codePointCount = mDictionaryStructurePolicy->
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getCodePointsAndProbabilityAndReturnCodePointCount(bigramsIt.getBigramPos(),
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MAX_WORD_LENGTH, bigramBuffer, &unigramProbability);
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MAX_WORD_LENGTH, bigramCodePoints, &unigramProbability);
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if (codePointCount <= 0) {
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continue;
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}
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@ -139,11 +81,8 @@ int BigramDictionary::getPredictions(const int *prevWord, const int prevWordLeng
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// here, but it can't get too bad.
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const int probability = mDictionaryStructurePolicy->getProbability(
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unigramProbability, bigramsIt.getProbability());
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addWordBigram(bigramBuffer, codePointCount, probability, outBigramProbability,
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outBigramCodePoints, outputTypes);
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++bigramCount;
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outSuggestionResults->addPrediction(bigramCodePoints, codePointCount, probability);
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}
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return std::min(bigramCount, MAX_RESULTS);
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}
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// Returns a pointer to the start of the bigram list.
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|
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@ -22,21 +22,20 @@
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namespace latinime {
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class DictionaryStructureWithBufferPolicy;
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class SuggestionResults;
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class BigramDictionary {
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public:
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BigramDictionary(const DictionaryStructureWithBufferPolicy *const dictionaryStructurePolicy);
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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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void getPredictions(const int *word, int length,
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SuggestionResults *const outSuggestionResults) 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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DISALLOW_IMPLICIT_CONSTRUCTORS(BigramDictionary);
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void addWordBigram(int *word, int length, int probability, int *bigramProbability,
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int *bigramCodePoints, int *outputTypes) const;
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int getBigramListPositionForWord(const int *prevWord, const int prevWordLength,
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const bool forceLowerCaseSearch) const;
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|
|
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@ -74,12 +74,11 @@ int Dictionary::getSuggestions(ProximityInfo *proximityInfo, DicTraverseSession
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}
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}
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int Dictionary::getBigrams(const int *word, int length, int *outWords, int *outputScores,
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int *outputTypes) const {
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void Dictionary::getPredictions(const int *word, int length,
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SuggestionResults *const outSuggestionResults) const {
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TimeKeeper::setCurrentTime();
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if (length <= 0) return 0;
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return mBigramDictionary->getPredictions(word, length, outWords, outputScores,
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outputTypes);
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if (length <= 0) return;
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mBigramDictionary->getPredictions(word, length, outSuggestionResults);
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}
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int Dictionary::getProbability(const int *word, int length) const {
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|
|
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@ -33,6 +33,7 @@ namespace latinime {
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class DictionaryStructureWithBufferPolicy;
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class DicTraverseSession;
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class ProximityInfo;
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class SuggestionResults;
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class SuggestOptions;
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class WordProperty;
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@ -67,8 +68,8 @@ class Dictionary {
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const SuggestOptions *const suggestOptions, int *outWords, int *outputScores,
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int *spaceIndices, int *outputTypes, int *outputAutoCommitFirstWordConfidence) const;
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int getBigrams(const int *word, int length, int *outWords, int *outputScores,
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int *outputTypes) const;
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void getPredictions(const int *word, int length,
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SuggestionResults *const outSuggestionResults) const;
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int getProbability(const int *word, int length) const;
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|
|
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@ -0,0 +1,83 @@
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/*
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* Copyright (C) 2014 The Android Open Source Project
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*
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* 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
|
||||
*
|
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* 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.
|
||||
*/
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#ifndef LATINIME_SUGGESTED_WORD_H
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#define LATINIME_SUGGESTED_WORD_H
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#include <vector>
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#include "defines.h"
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#include "suggest/core/dictionary/dictionary.h"
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namespace latinime {
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class SuggestedWord {
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public:
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class Comparator {
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public:
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bool operator()(const SuggestedWord &left, const SuggestedWord &right) {
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if (left.getScore() != right.getScore()) {
|
||||
return left.getScore() < right.getScore();
|
||||
}
|
||||
return left.getCodePointCount() > right.getCodePointCount();
|
||||
}
|
||||
|
||||
private:
|
||||
DISALLOW_ASSIGNMENT_OPERATOR(Comparator);
|
||||
};
|
||||
|
||||
SuggestedWord(const int *const codePoints, const int codePointCount,
|
||||
const int score, const int type, const int indexToPartialCommit,
|
||||
const int autoCommitFirstWordConfidence)
|
||||
: mCodePoints(codePoints, codePoints + codePointCount), mScore(score),
|
||||
mType(type), mIndexToPartialCommit(indexToPartialCommit),
|
||||
mAutoCommitFirstWordConfidence(autoCommitFirstWordConfidence) {}
|
||||
|
||||
const int *getCodePoint() const {
|
||||
return &mCodePoints.at(0);
|
||||
}
|
||||
|
||||
int getCodePointCount() const {
|
||||
return mCodePoints.size();
|
||||
}
|
||||
|
||||
int getScore() const {
|
||||
return mScore;
|
||||
}
|
||||
|
||||
int getType() const {
|
||||
return mType;
|
||||
}
|
||||
|
||||
int getIndexToPartialCommit() const {
|
||||
return mIndexToPartialCommit;
|
||||
}
|
||||
|
||||
int getAutoCommitFirstWordConfidence() const {
|
||||
return mAutoCommitFirstWordConfidence;
|
||||
}
|
||||
|
||||
private:
|
||||
DISALLOW_DEFAULT_CONSTRUCTOR(SuggestedWord);
|
||||
|
||||
std::vector<int> mCodePoints;
|
||||
int mScore;
|
||||
int mType;
|
||||
int mIndexToPartialCommit;
|
||||
int mAutoCommitFirstWordConfidence;
|
||||
};
|
||||
} // namespace latinime
|
||||
#endif /* LATINIME_SUGGESTED_WORD_H */
|
|
@ -0,0 +1,77 @@
|
|||
/*
|
||||
* Copyright (C) 2014 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 "suggest/core/result/suggestion_results.h"
|
||||
|
||||
namespace latinime {
|
||||
|
||||
void SuggestionResults::outputSuggestions(JNIEnv *env, jintArray outSuggestionCount,
|
||||
jintArray outputCodePointsArray, jintArray outScoresArray, jintArray outSpaceIndicesArray,
|
||||
jintArray outTypesArray, jintArray outAutoCommitFirstWordConfidenceArray) {
|
||||
int outputIndex = 0;
|
||||
while (!mSuggestedWords.empty()) {
|
||||
const SuggestedWord &suggestedWord = mSuggestedWords.top();
|
||||
suggestedWord.getCodePointCount();
|
||||
const int start = outputIndex * MAX_WORD_LENGTH;
|
||||
env->SetIntArrayRegion(outputCodePointsArray, start, suggestedWord.getCodePointCount(),
|
||||
suggestedWord.getCodePoint());
|
||||
if (suggestedWord.getCodePointCount() < MAX_WORD_LENGTH) {
|
||||
const int terminal = 0;
|
||||
env->SetIntArrayRegion(outputCodePointsArray, start + suggestedWord.getCodePointCount(),
|
||||
1 /* len */, &terminal);
|
||||
}
|
||||
const int score = suggestedWord.getScore();
|
||||
env->SetIntArrayRegion(outScoresArray, outputIndex, 1 /* len */, &score);
|
||||
const int indexToPartialCommit = suggestedWord.getIndexToPartialCommit();
|
||||
env->SetIntArrayRegion(outSpaceIndicesArray, outputIndex, 1 /* len */,
|
||||
&indexToPartialCommit);
|
||||
const int type = suggestedWord.getType();
|
||||
env->SetIntArrayRegion(outTypesArray, outputIndex, 1 /* len */, &type);
|
||||
if (mSuggestedWords.size() == 1) {
|
||||
const int autoCommitFirstWordConfidence =
|
||||
suggestedWord.getAutoCommitFirstWordConfidence();
|
||||
env->SetIntArrayRegion(outAutoCommitFirstWordConfidenceArray, 0 /* start */,
|
||||
1 /* len */, &autoCommitFirstWordConfidence);
|
||||
}
|
||||
++outputIndex;
|
||||
mSuggestedWords.pop();
|
||||
}
|
||||
env->SetIntArrayRegion(outSuggestionCount, 0 /* start */, 1 /* len */, &outputIndex);
|
||||
}
|
||||
|
||||
void SuggestionResults::addPrediction(const int *const codePoints, const int codePointCount,
|
||||
const int probability) {
|
||||
if (codePointCount <= 0 || codePointCount > MAX_WORD_LENGTH
|
||||
|| probability == NOT_A_PROBABILITY) {
|
||||
// Invalid word.
|
||||
return;
|
||||
}
|
||||
// Use probability as a score of the word.
|
||||
const int score = probability;
|
||||
if (getSuggestionCount() >= mMaxSuggestionCount) {
|
||||
const SuggestedWord &mWorstSuggestion = mSuggestedWords.top();
|
||||
if (score > mWorstSuggestion.getScore() || (score == mWorstSuggestion.getScore()
|
||||
&& codePointCount < mWorstSuggestion.getCodePointCount())) {
|
||||
mSuggestedWords.pop();
|
||||
} else {
|
||||
return;
|
||||
}
|
||||
}
|
||||
mSuggestedWords.push(SuggestedWord(codePoints, codePointCount, score,
|
||||
Dictionary::KIND_PREDICTION, NOT_AN_INDEX, NOT_A_FIRST_WORD_CONFIDENCE));
|
||||
}
|
||||
|
||||
} // namespace latinime
|
|
@ -0,0 +1,53 @@
|
|||
/*
|
||||
* 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.
|
||||
*/
|
||||
|
||||
#ifndef LATINIME_SUGGESTION_RESULTS_H
|
||||
#define LATINIME_SUGGESTION_RESULTS_H
|
||||
|
||||
#include <queue>
|
||||
#include <vector>
|
||||
|
||||
#include "defines.h"
|
||||
#include "jni.h"
|
||||
#include "suggest/core/result/suggested_word.h"
|
||||
|
||||
namespace latinime {
|
||||
|
||||
class SuggestionResults {
|
||||
public:
|
||||
explicit SuggestionResults(const int maxSuggestionCount)
|
||||
: mMaxSuggestionCount(maxSuggestionCount), mSuggestedWords() {}
|
||||
|
||||
// Returns suggestion count.
|
||||
void outputSuggestions(JNIEnv *env, jintArray outSuggestionCount, jintArray outCodePointsArray,
|
||||
jintArray outScoresArray, jintArray outSpaceIndicesArray, jintArray outTypesArray,
|
||||
jintArray outAutoCommitFirstWordConfidenceArray);
|
||||
|
||||
void addPrediction(const int *const codePoints, const int codePointCount, const int score);
|
||||
|
||||
int getSuggestionCount() const {
|
||||
return mSuggestedWords.size();
|
||||
}
|
||||
|
||||
private:
|
||||
DISALLOW_IMPLICIT_CONSTRUCTORS(SuggestionResults);
|
||||
|
||||
const int mMaxSuggestionCount;
|
||||
std::priority_queue<
|
||||
SuggestedWord, std::vector<SuggestedWord>, SuggestedWord::Comparator> mSuggestedWords;
|
||||
};
|
||||
} // namespace latinime
|
||||
#endif // LATINIME_SUGGESTION_RESULTS_H
|
Loading…
Reference in New Issue