Add LanguageModel class

java/res/raw/.gitignore

@@ -0,0 +1,2 @@
+*.gguf
+*tokenizer.model

java/src/org/futo/inputmethod/latin/Dictionary.java

@@ -63,6 +63,8 @@ public abstract class Dictionary {
     public static final String TYPE_USER = "user";
     // User history dictionary internal to LatinIME.
     public static final String TYPE_USER_HISTORY = "history";
+
+    public static final String TYPE_GGML = "ggml";
     public final String mDictType;
     // The locale for this dictionary. May be null if unknown (phony dictionary for example).
     public final Locale mLocale;

java/src/org/futo/inputmethod/latin/DictionaryFacilitator.java

@@ -45,10 +45,12 @@ import javax.annotation.Nullable;
 public interface DictionaryFacilitator {
 
     public static final String[] ALL_DICTIONARY_TYPES = new String[] {
-            Dictionary.TYPE_MAIN,
-            Dictionary.TYPE_CONTACTS,
-            Dictionary.TYPE_USER_HISTORY,
-            Dictionary.TYPE_USER};
+            Dictionary.TYPE_GGML,
+            //Dictionary.TYPE_MAIN,
+            //Dictionary.TYPE_CONTACTS,
+            //Dictionary.TYPE_USER_HISTORY,
+            //Dictionary.TYPE_USER
+    };
 
     public static final String[] DYNAMIC_DICTIONARY_TYPES = new String[] {
             Dictionary.TYPE_CONTACTS,

java/src/org/futo/inputmethod/latin/DictionaryFacilitatorImpl.java

@@ -34,6 +34,7 @@ import org.futo.inputmethod.latin.personalization.UserHistoryDictionary;
 import org.futo.inputmethod.latin.settings.SettingsValuesForSuggestion;
 import org.futo.inputmethod.latin.utils.ExecutorUtils;
 import org.futo.inputmethod.latin.utils.SuggestionResults;
+import org.futo.inputmethod.latin.xlm.LanguageModel;
 
 import java.io.File;
 import java.lang.reflect.InvocationTargetException;
@@ -135,6 +136,8 @@ public class DictionaryFacilitatorImpl implements DictionaryFacilitator {
         @Nullable public final String mAccount;
 
         @Nullable private Dictionary mMainDict;
+
+        @Nullable private LanguageModel mGGMLDict = null;
         // Confidence that the most probable language is actually the language the user is
         // typing in. For now, this is simply the number of times a word from this language
         // has been committed in a row.
@@ -182,6 +185,9 @@ public class DictionaryFacilitatorImpl implements DictionaryFacilitator {
             if (Dictionary.TYPE_MAIN.equals(dictType)) {
                 return mMainDict;
             }
+            if (Dictionary.TYPE_GGML.equals(dictType)) {
+                return mGGMLDict;
+            }
             return getSubDict(dictType);
         }
 
@@ -193,6 +199,9 @@ public class DictionaryFacilitatorImpl implements DictionaryFacilitator {
             if (Dictionary.TYPE_MAIN.equals(dictType)) {
                 return mMainDict != null;
             }
+            if (Dictionary.TYPE_GGML.equals(dictType)) {
+                return mGGMLDict != null;
+            }
             if (Dictionary.TYPE_USER_HISTORY.equals(dictType) &&
                     !TextUtils.equals(account, mAccount)) {
                 // If the dictionary type is user history, & if the account doesn't match,
@@ -349,6 +358,7 @@ public class DictionaryFacilitatorImpl implements DictionaryFacilitator {
         DictionaryGroup newDictionaryGroup =
                 new DictionaryGroup(newLocale, mainDict, account, subDicts);
 
+        newDictionaryGroup.mGGMLDict = new LanguageModel(context, Dictionary.TYPE_GGML, newLocale);
         // Replace Dictionaries.
         final DictionaryGroup oldDictionaryGroup;
         synchronized (mLock) {
@@ -406,6 +416,7 @@ public class DictionaryFacilitatorImpl implements DictionaryFacilitator {
         synchronized (mLock) {
             if (locale.equals(dictionaryGroup.mLocale)) {
                 dictionaryGroup.setMainDict(mainDict);
+                dictionaryGroup.mGGMLDict = new LanguageModel(context, Dictionary.TYPE_GGML, locale);
             } else {
                 // Dictionary facilitator has been reset for another locale.
                 mainDict.close();

java/src/org/futo/inputmethod/latin/LatinIME.kt

@@ -185,7 +185,7 @@ class LatinIME : InputMethodService(), LifecycleOwner, ViewModelStoreOwner, Save
 
         deferGetSetting(THEME_KEY) { key ->
             if(key != activeThemeOption?.key) {
-                ThemeOptions[key]?.let { updateTheme(it) }
+                ThemeOptions[key]?.let { if(it.available(this)) updateTheme(it) }
             }
         }
     }

java/src/org/futo/inputmethod/latin/NgramContext.java

@@ -43,6 +43,8 @@ public class NgramContext {
 
     public static final String CONTEXT_SEPARATOR = " ";
 
+    public String fullContext = "";
+
     public static NgramContext getEmptyPrevWordsContext(int maxPrevWordCount) {
         return new NgramContext(maxPrevWordCount, WordInfo.EMPTY_WORD_INFO);
     }

java/src/org/futo/inputmethod/latin/RichInputConnection.java

@@ -683,8 +683,18 @@ public final class RichInputConnection implements PrivateCommandPerformer {
                 }
             }
         }
-        return NgramContextUtils.getNgramContextFromNthPreviousWord(
+        NgramContext ngramContext = NgramContextUtils.getNgramContextFromNthPreviousWord(
                 prev, spacingAndPunctuations, n);
+
+        ngramContext.fullContext = getTextBeforeCursor(4096, 0).toString();
+
+        if(ngramContext.fullContext.length() == 4096) {
+            ngramContext.fullContext = String.join(" ",ngramContext.fullContext.split(" ")).substring(ngramContext.fullContext.split(" ")[0].length()+1);
+
+        }
+
+        return ngramContext;
+
     }
 
     private static boolean isPartOfCompositionForScript(final int codePoint,

java/src/org/futo/inputmethod/latin/xlm/LanguageModel.java

@@ -0,0 +1,227 @@
+package org.futo.inputmethod.latin.xlm;
+
+import android.content.Context;
+import android.util.Log;
+
+import org.futo.inputmethod.latin.Dictionary;
+import org.futo.inputmethod.latin.NgramContext;
+import org.futo.inputmethod.latin.R;
+import org.futo.inputmethod.latin.SuggestedWords;
+import org.futo.inputmethod.latin.common.ComposedData;
+import org.futo.inputmethod.latin.common.InputPointers;
+import org.futo.inputmethod.latin.settings.SettingsValuesForSuggestion;
+
+import java.io.File;
+import java.io.FileOutputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.OutputStream;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.Locale;
+
+
+public class LanguageModel extends Dictionary {
+    static long mNativeState = 0;
+
+    private String getPathToModelResource(Context context, int modelResource, int tokenizerResource, boolean forceDelete) {
+        File outputDir = context.getCacheDir();
+        File outputFile = new File(outputDir, "ggml-model-" + String.valueOf(modelResource) + ".gguf");
+        File outputFileTokenizer = new File(outputDir, "tokenizer-" + String.valueOf(tokenizerResource) + ".tokenizer");
+
+        if(forceDelete && outputFile.exists()) {
+            outputFile.delete();
+            outputFileTokenizer.delete();
+        }
+
+        if((!outputFile.exists()) || forceDelete){
+            // FIXME: We save this to a random temporary file so that we can have a path instead of an InputStream
+            InputStream is = context.getResources().openRawResource(modelResource);
+            InputStream is_t = context.getResources().openRawResource(tokenizerResource);
+
+            try {
+                OutputStream os = new FileOutputStream(outputFile);
+
+                int read = 0;
+                byte[] bytes = new byte[1024];
+
+                while ((read = is.read(bytes)) != -1) {
+                    os.write(bytes, 0, read);
+                }
+
+                os.flush();
+                os.close();
+                is.close();
+
+
+                OutputStream os_t = new FileOutputStream(outputFileTokenizer);
+
+                read = 0;
+                while ((read = is_t.read(bytes)) != -1) {
+                    os_t.write(bytes, 0, read);
+                }
+
+                os_t.flush();
+                os_t.close();
+                is_t.close();
+
+            } catch(IOException e) {
+                e.printStackTrace();
+                throw new RuntimeException("Failed to write model asset to file");
+            }
+        }
+
+        return outputFile.getAbsolutePath() + ":" + outputFileTokenizer.getAbsolutePath();
+    }
+
+    Thread initThread = null;
+    public LanguageModel(Context context, String dictType, Locale locale) {
+        super(dictType, locale);
+
+        initThread = new Thread() {
+            @Override public void run() {
+                if(mNativeState != 0) return;
+
+                String modelPath = getPathToModelResource(context, R.raw.l2_steps_12k_w1_s1_1k, R.raw.l2_steps_12k_w1_s1_1k_tokenizer, false);
+                mNativeState = openNative(modelPath);
+
+                if(mNativeState == 0){
+                    modelPath = getPathToModelResource(context, R.raw.l2_steps_12k_w1_s1_1k, R.raw.l2_steps_12k_w1_s1_1k_tokenizer, true);
+                    mNativeState = openNative(modelPath);
+                }
+
+                if(mNativeState == 0){
+                    throw new RuntimeException("Failed to load R.raw.l2_steps_12k_w1_s1_1k, R.raw.l2_steps_12k_w1_s1_1k_tokenizer model");
+                }
+            }
+        };
+
+        initThread.start();
+    }
+
+    @Override
+    public ArrayList<SuggestedWords.SuggestedWordInfo> getSuggestions(
+            ComposedData composedData,
+            NgramContext ngramContext,
+            long proximityInfoHandle,
+            SettingsValuesForSuggestion settingsValuesForSuggestion,
+            int sessionId,
+            float weightForLocale,
+            float[] inOutWeightOfLangModelVsSpatialModel
+    ) {
+        if (mNativeState == 0) return null;
+        if (initThread != null && initThread.isAlive()) return null;
+
+        final InputPointers inputPointers = composedData.mInputPointers;
+        final boolean isGesture = composedData.mIsBatchMode;
+        final int inputSize;
+        inputSize = inputPointers.getPointerSize();
+
+        String context = ngramContext.extractPrevWordsContext().replace(NgramContext.BEGINNING_OF_SENTENCE_TAG, " ").trim();
+        if(!ngramContext.fullContext.isEmpty()) {
+            context = ngramContext.fullContext.trim();
+        }
+
+        String partialWord = composedData.mTypedWord;
+
+        if(!partialWord.isEmpty() && context.endsWith(partialWord)) {
+            context = context.substring(0, context.length() - partialWord.length()).trim();
+        }
+
+        if(!partialWord.isEmpty()) {
+            partialWord = partialWord.trim();
+        }
+
+        // TODO: We may want to pass times too, and adjust autocorrect confidence
+        // based on time (taking a long time to type a char = trust the typed character
+        // more, speed typing = trust it less)
+        int[] xCoordsI = composedData.mInputPointers.getXCoordinates();
+        int[] yCoordsI = composedData.mInputPointers.getYCoordinates();
+
+        float[] xCoords = new float[composedData.mInputPointers.getPointerSize()];
+        float[] yCoords = new float[composedData.mInputPointers.getPointerSize()];
+
+        for(int i=0; i<composedData.mInputPointers.getPointerSize(); i++) xCoords[i] = (float)xCoordsI[i];
+        for(int i=0; i<composedData.mInputPointers.getPointerSize(); i++) yCoords[i] = (float)yCoordsI[i];
+
+        int maxResults = 128;
+        float[] outProbabilities = new float[maxResults];
+        String[] outStrings = new String[maxResults];
+
+        // TOOD: Pass multiple previous words information for n-gram.
+        getSuggestionsNative(mNativeState, proximityInfoHandle, context, partialWord, xCoords, yCoords, outStrings, outProbabilities);
+
+        final ArrayList<SuggestedWords.SuggestedWordInfo> suggestions = new ArrayList<>();
+
+        int kind = SuggestedWords.SuggestedWordInfo.KIND_PREDICTION;
+        for(int i=0; i<maxResults; i++) {
+            if(outStrings[i] == null) continue;
+
+            String word = outStrings[i].trim();
+
+            if(outProbabilities[i] > 150.0f) {
+                kind = SuggestedWords.SuggestedWordInfo.KIND_WHITELIST | SuggestedWords.SuggestedWordInfo.KIND_FLAG_APPROPRIATE_FOR_AUTO_CORRECTION;
+            }
+
+            suggestions.add(new SuggestedWords.SuggestedWordInfo( word, context, (int)(outProbabilities[i] * 100.0f), kind, this, 0, 0 ));
+        }
+
+        if(kind == SuggestedWords.SuggestedWordInfo.KIND_PREDICTION) {
+            // TODO: Forcing the thing to appear
+            for (int i = suggestions.size(); i < 3; i++) {
+                String word = " ";
+                for (int j = 0; j < i; j++) word += " ";
+
+                suggestions.add(new SuggestedWords.SuggestedWordInfo(word, context, 1, kind, this, 0, 0));
+            }
+        }
+
+        return suggestions;
+    }
+
+
+    private synchronized void closeInternalLocked() {
+        try {
+            if (initThread != null) initThread.join();
+        } catch (InterruptedException e) {
+            e.printStackTrace();
+        }
+
+        /*if (mNativeState != 0) {
+            closeNative(mNativeState);
+            mNativeState = 0;
+        }*/
+    }
+
+
+    @Override
+    protected void finalize() throws Throwable {
+        try {
+            closeInternalLocked();
+        } finally {
+            super.finalize();
+        }
+    }
+
+    @Override
+    public boolean isInDictionary(String word) {
+        return false;
+    }
+
+
+    private static native long openNative(String sourceDir);
+    private static native void closeNative(long state);
+    private static native void getSuggestionsNative(
+            // inputs
+            long state,
+            long proximityInfoHandle,
+            String context,
+            String partialWord,
+            float[] inComposeX,
+            float[] inComposeY,
+
+            // outputs
+            String[] outStrings,
+            float[] outProbs
+    );
+}

native/jni/jni_common.cpp

@@ -22,6 +22,7 @@
 #include "org_futo_inputmethod_latin_BinaryDictionary.h"
 #include "org_futo_inputmethod_latin_BinaryDictionaryUtils.h"
 #include "org_futo_inputmethod_latin_DicTraverseSession.h"
+#include "org_futo_inputmethod_latin_xlm_LanguageModel.h"
 #include "defines.h"
 
 /*
@@ -55,6 +56,10 @@ jint JNI_OnLoad(JavaVM *vm, void *reserved) {
         AKLOGE("ERROR: ProximityInfo native registration failed");
         return -1;
     }
+    if (!latinime::register_LanguageModel(env)) {
+        AKLOGE("ERROR: LanguageModel native registration failed");
+        return -1;
+    }
     /* success -- return valid version number */
     return JNI_VERSION_1_6;
 }

native/jni/org_futo_inputmethod_latin_xlm_LanguageModel.cpp

@@ -0,0 +1,259 @@
+#define LOG_TAG "LatinIME: jni: LanguageModel"
+
+#include "org_futo_inputmethod_latin_xlm_LanguageModel.h"
+
+#include <cstring> // for memset()
+#include <vector>
+
+#include "jni.h"
+#include "jni_common.h"
+#include "ggml/LanguageModel.h"
+#include "defines.h"
+
+static std::string trim(const std::string &s) {
+    auto start = s.begin();
+    while (start != s.end() && std::isspace(*start)) {
+        start++;
+    }
+
+    auto end = s.end();
+    do {
+        end--;
+    } while (std::distance(start, end) > 0 && std::isspace(*end));
+
+    return {start, end + 1};
+}
+
+template<typename T>
+bool sortProbabilityPairDescending(const std::pair<float, T>& a, const std::pair<float, T>& b) {
+    return a.first > b.first;
+}
+
+template<typename T>
+static inline void sortProbabilityPairVectorDescending(std::vector<std::pair<float, T>> &vec) {
+    std::sort(vec.begin(), vec.end(), sortProbabilityPairDescending<T>);
+}
+
+template<typename T>
+static inline void sortProbabilityPairVectorDescending(std::vector<std::pair<float, T>> &vec, int partial) {
+    std::partial_sort(vec.begin(), vec.begin() + partial, vec.end(), sortProbabilityPairDescending<T>);
+}
+
+struct LanguageModelState {
+    LanguageModel *model;
+
+    struct {
+        int XBU;
+        int XBC;
+        int XEC;
+
+        int LETTERS_TO_IDS[26];
+    } specialTokens;
+
+    bool Initialize(const std::string &paths){
+        model = LlamaAdapter::createLanguageModel(paths);
+        if(!model) {
+            AKLOGE("GGMLDict: Could not load model");
+            return false;
+        }
+
+        specialTokens.XBU = 104; //model->tokenToId("_XBU_");
+        specialTokens.XBC = 105; //model->tokenToId("_XBC_");
+        specialTokens.XEC = 106; //model->tokenToId("_XEC_");
+        specialTokens.LETTERS_TO_IDS[0] = 124; //model->tokenToId("_XU_LETTER_A_");
+
+        ASSERT(specialTokens.XBU != 0);
+        ASSERT(specialTokens.XBC != 0);
+        ASSERT(specialTokens.XEC != 0);
+        ASSERT(specialTokens.LETTERS_TO_IDS[0] != 0);
+
+        for(int i = 1; i < 26; i++) {
+            specialTokens.LETTERS_TO_IDS[i] = specialTokens.LETTERS_TO_IDS[0] + i;
+        }
+
+        return true;
+    }
+
+    std::pair<float, token_sequence> Sample(){
+        float probability = 0.0f;
+        token_sequence sampled_sequence;
+
+        std::vector<std::pair<float, int>> index_value;
+
+        while(sampled_sequence.size() < 8) {
+            std::vector<float> logits = model->infer();
+            logits[specialTokens.XBU] = -999.0f;
+
+            index_value.clear();
+            for (size_t i = 0; i < logits.size(); i++) {
+                index_value.emplace_back(logits[i], i);
+            }
+
+            sortProbabilityPairVectorDescending(index_value, 1);
+
+            int next_token = index_value[0].second;
+            model->pushToContext(next_token);
+
+            // Check if this is the end of correction
+            if(next_token == specialTokens.XEC) {
+                break;
+            }
+
+            probability += index_value[0].first;
+            sampled_sequence.push_back(next_token);
+
+
+            // Check if this is the end of a word
+            std::string token = model->getToken(next_token);
+            if(token.size() >= 3 && (token[token.size() - 1] == '\x81') && (token[token.size() - 2] == '\x96') && token[token.size() - 3] == '\xe2') {
+                break;
+            }
+        }
+
+        return {probability, std::move(sampled_sequence)};
+    }
+
+    std::string PredictNextWord(const std::string &context) {
+        token_sequence next_context = model->tokenize(trim(context) + " ");
+        model->updateContext(next_context);
+
+        auto result = Sample();
+
+        return model->decode(result.second);
+    }
+
+    std::string PredictCorrection(const std::string &context, std::string &word) {
+        token_sequence next_context = model->tokenize(trim(context) + " ");
+        next_context.push_back(specialTokens.XBU);
+
+        for(char c : trim(word)) {
+            if(c >= 'a' && c <= 'z') {
+                next_context.push_back(specialTokens.LETTERS_TO_IDS[c - 'a']);
+            }else if(c >= 'A' && c <= 'Z') {
+                next_context.push_back(specialTokens.LETTERS_TO_IDS[c - 'A']);
+            } else {
+                AKLOGI("ignoring character in partial word [%c]", c);
+            }
+        }
+        next_context.push_back(specialTokens.XBC);
+
+        model->updateContext(next_context);
+
+        auto result = Sample();
+
+        return model->decode(result.second);
+    }
+};
+
+namespace latinime {
+    class ProximityInfo;
+
+    static jlong xlm_LanguageModel_open(JNIEnv *env, jclass clazz, jstring modelDir) {
+        AKLOGI("open LM");
+        const jsize sourceDirUtf8Length = env->GetStringUTFLength(modelDir);
+        if (sourceDirUtf8Length <= 0) {
+            AKLOGE("DICT: Can't get sourceDir string");
+            return 0;
+        }
+        char sourceDirChars[sourceDirUtf8Length + 1];
+        env->GetStringUTFRegion(modelDir, 0, env->GetStringLength(modelDir), sourceDirChars);
+        sourceDirChars[sourceDirUtf8Length] = '\0';
+
+        LanguageModelState *state = new LanguageModelState();
+
+        if(!state->Initialize(sourceDirChars)) {
+            free(state);
+            return 0;
+        }
+
+        return reinterpret_cast<jlong>(state);
+    }
+
+    static void xlm_LanguageModel_close(JNIEnv *env, jclass clazz, jlong statePtr) {
+        LanguageModelState *state = reinterpret_cast<LanguageModelState *>(statePtr);
+        if(state == nullptr) return;
+        delete state;
+    }
+
+    static void xlm_LanguageModel_getSuggestions(JNIEnv *env, jclass clazz,
+         // inputs
+         jlong dict,
+         jlong proximityInfo,
+         jstring context,
+         jstring partialWord,
+         jfloatArray inComposeX,
+         jfloatArray inComposeY,
+
+         // outputs
+         jobjectArray outPredictions,
+         jfloatArray outProbabilities
+    ) {
+        LanguageModelState *state = reinterpret_cast<LanguageModelState *>(dict);
+
+        const char* cstr = env->GetStringUTFChars(context, nullptr);
+        std::string contextString(cstr);
+        env->ReleaseStringUTFChars(context, cstr);
+
+        std::string partialWordString;
+        if(partialWord != nullptr){
+            const char* pwstr = env->GetStringUTFChars(partialWord, nullptr);
+            partialWordString = std::string(pwstr);
+            env->ReleaseStringUTFChars(partialWord, pwstr);
+        }
+
+        AKLOGI("LanguageModel context [%s]", contextString.c_str());
+
+        bool isAutoCorrect = false;
+        std::string result;
+        if(partialWordString.empty()) {
+            result = state->PredictNextWord(contextString);
+
+            AKLOGI("LanguageModel suggestion [%s]", result.c_str());
+        } else {
+            isAutoCorrect = true;
+            result = state->PredictCorrection(contextString, partialWordString);
+
+            AKLOGI("LanguageModel correction [%s] -> [%s]", partialWordString.c_str(), result.c_str());
+        }
+
+        // Output
+        size_t size = env->GetArrayLength(outPredictions);
+
+        jfloat *probsArray = env->GetFloatArrayElements(outProbabilities, nullptr);
+
+        // Output predictions for next word
+        for (int i = 0; i < 1; i++) {
+            jstring jstr = env->NewStringUTF(result.c_str());
+            env->SetObjectArrayElement(outPredictions, i, jstr);
+            probsArray[i] = isAutoCorrect ? 200.0f : 100.0f;
+            env->DeleteLocalRef(jstr);
+        }
+
+        env->ReleaseFloatArrayElements(outProbabilities, probsArray, 0);
+    }
+
+    static const JNINativeMethod sMethods[] = {
+            {
+                    const_cast<char *>("openNative"),
+                    const_cast<char *>("(Ljava/lang/String;)J"),
+                    reinterpret_cast<void *>(xlm_LanguageModel_open)
+            },
+            {
+                    const_cast<char *>("closeNative"),
+                    const_cast<char *>("(J)V"),
+                    reinterpret_cast<void *>(xlm_LanguageModel_close)
+            },
+            {
+                    const_cast<char *>("getSuggestionsNative"),
+                    const_cast<char *>("(JJLjava/lang/String;Ljava/lang/String;[F[F[Ljava/lang/String;[F)V"),
+                    reinterpret_cast<void *>(xlm_LanguageModel_getSuggestions)
+            }
+    };
+
+    int register_LanguageModel(JNIEnv *env) {
+        llama_backend_init(true /* numa??? */);
+
+        const char *const kClassPathName = "org/futo/inputmethod/latin/xlm/LanguageModel";
+        return registerNativeMethods(env, kClassPathName, sMethods, NELEMS(sMethods));
+    }
+} // namespace latinime

native/jni/org_futo_inputmethod_latin_xlm_LanguageModel.h

@@ -0,0 +1,14 @@
+//
+// Created by alex on 9/27/23.
+//
+
+#ifndef LATINIME_ORG_FUTO_INPUTMETHOD_LATIN_XLM_LANGUAGEMODEL_H
+#define LATINIME_ORG_FUTO_INPUTMETHOD_LATIN_XLM_LANGUAGEMODEL_H
+
+#include "jni.h"
+
+namespace latinime {
+    int register_LanguageModel(JNIEnv *env);
+} // namespace latinime
+
+#endif //LATINIME_ORG_FUTO_INPUTMETHOD_LATIN_XLM_LANGUAGEMODEL_H