Fix problem where wrong autocorrection is used during stress

java/src/org/futo/inputmethod/latin/inputlogic/InputLogic.java

@@ -1502,12 +1502,12 @@ public final class InputLogic {
         }
     }
 
-    private void ensureSuggestionStripCompleted(final SettingsValues settingsValues,
+    private boolean ensureSuggestionStripCompleted(final SettingsValues settingsValues,
             final String separator, final LatinIMELegacy.UIHandler handler) {
         LanguageModelFacilitator facilitator = handler.getLanguageModelFacilitator();
         if(!facilitator.shouldPassThroughToLegacy()) {
             if(facilitator.hasPendingUpdate()) {
-                facilitator.blockUntilComplete();
+                return facilitator.blockUntilComplete();
             }
         } else {
             if (handler.hasPendingUpdateSuggestions()) {
@@ -1523,6 +1523,8 @@ public final class InputLogic {
                 performUpdateSuggestionStripSync(settingsValues, SuggestedWords.INPUT_STYLE_TYPING);
             }
         }
+
+        return true;
     }
 
     public void performUpdateSuggestionStripSync(final SettingsValues settingsValues,
@@ -2177,7 +2179,8 @@ public final class InputLogic {
     private void commitCurrentAutoCorrection(final SettingsValues settingsValues,
             final String separator, final LatinIMELegacy.UIHandler handler) {
         // Complete any pending suggestions query first
-        ensureSuggestionStripCompleted(settingsValues, separator, handler);
+        if(!ensureSuggestionStripCompleted(settingsValues, separator, handler)) return;
+
         final SuggestedWordInfo autoCorrectionOrNull = mWordComposer.getAutoCorrectionOrNull();
         final String typedWord = mWordComposer.getTypedWord();
         final String stringToCommit = (autoCorrectionOrNull != null)

java/src/org/futo/inputmethod/latin/xlm/LanguageModelFacilitator.kt

@@ -136,10 +136,10 @@ public class LanguageModelFacilitator(
 
     private var numConsecutiveTimeouts = 0
     private var transformerDisabled = false
-    public fun blockUntilComplete() {
+    public fun blockUntilComplete(): Boolean {
         runBlocking {
             try {
-                withTimeout(1000L) {
+                withTimeout(700L) {
                     computationSemaphore.acquire()
                     computationSemaphore.release()
                     try {
@@ -150,14 +150,16 @@ public class LanguageModelFacilitator(
                 }
                 numConsecutiveTimeouts = 0
             } catch(e: TimeoutCancellationException) {
-                Log.d("LanguageModelFacilitator", "Failed to complete prediction within 1000ms!")
+                Log.d("LanguageModelFacilitator", "Failed to complete prediction within the time!")
                 numConsecutiveTimeouts += 1
                 if(numConsecutiveTimeouts > 5) {
                     transformerDisabled = true
                     Log.w("LanguageModelFacilitator", "Temporarily disabling transformer due to continuous timeouts")
                 }
+                return@runBlocking false
             }
         }
+        return true
     }
 
     private fun getEmojiCandidate(word: String): SuggestedWordInfo? {
@@ -232,6 +234,8 @@ public class LanguageModelFacilitator(
 
         computationSemaphore.acquire()
 
+        inputLogic.mWordComposer.setAutoCorrection(null)
+
         try {
             var transformerWeight = context.getSetting(BinaryDictTransformerWeightSetting)