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[mob][photos] Rename to MLIndexingIsolate

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This commit is contained in:
laurenspriem 2024-07-25 21:50:56 +02:00
parent d30c04cc55
commit 00beadbc01
2 changed files with 20 additions and 20 deletions
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30
mobile/lib/services/machine_learning/ml_isolate.dart → mobile/lib/services/machine_learning/ml_indexing_isolate.dart
View File

@ -14,10 +14,10 @@ import "package:photos/services/machine_learning/semantic_search/clip/clip_image
import "package:photos/utils/ml_util.dart";
import "package:synchronized/synchronized.dart";
enum MLOperation { analyzeImage, loadModels, releaseModels }
enum MLIndexingOperation { analyzeImage, loadModels, releaseModels }
class MLIsolate {
static final _logger = Logger("MLIsolate");
class MLIndexingIsolate {
static final _logger = Logger("MLIndexingIsolate");
Timer? _inactivityTimer;
final Duration _inactivityDuration = const Duration(seconds: 120);
@ -35,9 +35,9 @@ class MLIsolate {
bool shouldPauseIndexingAndClustering = false;
// Singleton pattern
MLIsolate._privateConstructor();
static final instance = MLIsolate._privateConstructor();
factory MLIsolate() => instance;
MLIndexingIsolate._privateConstructor();
static final instance = MLIndexingIsolate._privateConstructor();
factory MLIndexingIsolate() => instance;
Future<void> _initIsolate() async {
return _initIsolateLock.synchronized(() async {
@ -74,13 +74,13 @@ class MLIsolate {
mainSendPort.send(receivePort.sendPort);
receivePort.listen((message) async {
final functionIndex = message[0] as int;
final function = MLOperation.values[functionIndex];
final function = MLIndexingOperation.values[functionIndex];
final args = message[1] as Map<String, dynamic>;
final sendPort = message[2] as SendPort;
try {
switch (function) {
case MLOperation.analyzeImage:
case MLIndexingOperation.analyzeImage:
final time = DateTime.now();
final MLResult result = await analyzeImageStatic(args);
_logger.info(
@ -88,7 +88,7 @@ class MLIsolate {
);
sendPort.send(result.toJsonString());
break;
case MLOperation.loadModels:
case MLIndexingOperation.loadModels:
final modelNames = args['modelNames'] as List<String>;
final modelPaths = args['modelPaths'] as List<String>;
final addresses = <int>[];
@ -101,7 +101,7 @@ class MLIsolate {
}
sendPort.send(List.from(addresses, growable: false));
break;
case MLOperation.releaseModels:
case MLIndexingOperation.releaseModels:
final modelNames = args['modelNames'] as List<String>;
final modelAddresses = args['modelAddresses'] as List<int>;
for (int i = 0; i < modelNames.length; i++) {
@ -122,13 +122,13 @@ class MLIsolate {
/// The common method to run any operation in the isolate. It sends the [message] to [_isolateMain] and waits for the result.
Future<dynamic> _runInIsolate(
(MLOperation, Map<String, dynamic>) message,
(MLIndexingOperation, Map<String, dynamic>) message,
) async {
await _initIsolate();
return _functionLock.synchronized(() async {
_resetInactivityTimer();
if (message.$1 == MLOperation.analyzeImage &&
if (message.$1 == MLIndexingOperation.analyzeImage &&
shouldPauseIndexingAndClustering) {
return null;
}
@ -198,7 +198,7 @@ class MLIsolate {
try {
final resultJsonString = await _runInIsolate(
(
MLOperation.analyzeImage,
MLIndexingOperation.analyzeImage,
{
"enteFileID": instruction.enteFile.uploadedFileID ?? -1,
"filePath": filePath,
@ -271,7 +271,7 @@ class MLIsolate {
try {
final addresses = await _runInIsolate(
(
MLOperation.loadModels,
MLIndexingOperation.loadModels,
{
"modelNames": modelNames,
"modelPaths": modelPaths,
@ -306,7 +306,7 @@ class MLIsolate {
try {
await _runInIsolate(
(
MLOperation.releaseModels,
MLIndexingOperation.releaseModels,
{
"modelNames": modelNames,
"modelAddresses": modelAddresses,

10
mobile/lib/services/machine_learning/ml_service.dart
View File

@ -26,7 +26,7 @@ import "package:photos/services/machine_learning/face_ml/person/person_service.d
import 'package:photos/services/machine_learning/file_ml/file_ml.dart';
import 'package:photos/services/machine_learning/file_ml/remote_fileml_service.dart';
import 'package:photos/services/machine_learning/ml_exceptions.dart';
import "package:photos/services/machine_learning/ml_isolate.dart";
import "package:photos/services/machine_learning/ml_indexing_isolate.dart";
import 'package:photos/services/machine_learning/ml_result.dart';
import "package:photos/services/machine_learning/semantic_search/clip/clip_image_encoder.dart";
import "package:photos/services/machine_learning/semantic_search/semantic_search_service.dart";
@ -138,13 +138,13 @@ class MLService {
void pauseIndexingAndClustering() {
if (_isIndexingOrClusteringRunning) {
_shouldPauseIndexingAndClustering = true;
MLIsolate.instance.shouldPauseIndexingAndClustering = true;
MLIndexingIsolate.instance.shouldPauseIndexingAndClustering = true;
}
}
void _cancelPauseIndexingAndClustering() {
_shouldPauseIndexingAndClustering = false;
MLIsolate.instance.shouldPauseIndexingAndClustering = false;
MLIndexingIsolate.instance.shouldPauseIndexingAndClustering = false;
}
/// Analyzes all the images in the database with the latest ml version and stores the results in the database.
@ -380,7 +380,7 @@ class MLService {
bool actuallyRanML = false;
try {
final MLResult? result = await MLIsolate.instance.analyzeImage(
final MLResult? result = await MLIndexingIsolate.instance.analyzeImage(
instruction,
);
if (result == null) {
@ -518,7 +518,7 @@ class MLService {
_logger.info(
'Loading models. faces: $shouldLoadFaces, clip: $shouldLoadClip',
);
await MLIsolate.instance
await MLIndexingIsolate.instance
.loadModels(loadFaces: shouldLoadFaces, loadClip: shouldLoadClip);
_logger.info('Models loaded');
_logStatus();