From: Marcin Kaminski <marcin.ka@partner.samsung.com>
Date: Wed, 2 Mar 2022 18:52:04 +0000 (+0100)
Subject: [ML] TODO resolving/removal
X-Git-Tag: submit/tizen/20220325.070959~5^2
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=9ba1466075957d0aea0432fd7b8cd935072a8adb;p=platform%2Fcore%2Fapi%2Fwebapi-plugins.git

[ML] TODO resolving/removal

Changes:
- constants sorted in ml_instance.cc
- stubs for createGeneratorDataset() removed from all levels
- obsolete try-catch removed

Change-Id: Ie50592ae1c6af6c9e3a8cfddc1c93dd61bc26da2
---

diff --git a/src/ml/js/ml_trainer.js b/src/ml/js/ml_trainer.js
index e874baf9..e31a2414 100755
--- a/src/ml/js/ml_trainer.js
+++ b/src/ml/js/ml_trainer.js
@@ -766,35 +766,6 @@ MachineLearningTrainer.prototype.createFileDataset = function() {
     return new Dataset(result.id, 'DATASET_FILE');
 };
 
-MachineLearningTrainer.prototype.createGeneratorDataset = function() {
-    var args = validator_.validateArgs(arguments, [
-        {
-            name: 'train',
-            type: types_.FUNCTION
-        },
-        {
-            name: 'validate',
-            type: types_.FUNCTION,
-            optional: true,
-            nullable: true
-        },
-        {
-            name: 'test',
-            type: types_.FUNCTION,
-            optional: true,
-            nullable: true
-        }
-    ]);
-    ValidateDatasetPaths(
-        args.train,
-        args.has.validate ? args.validate : undefined,
-        args.has.test ? args.test : undefined
-    );
-
-    // TODO
-    return new Dataset(result.id, 'DATASET_GENERATOR');
-};
-
 var ValidCreateOptimizerExceptions = [
     'NotSupportedError',
     'TypeMismatchError',
diff --git a/src/ml/ml_instance.cc b/src/ml/ml_instance.cc
index 6e256d79..9d924408 100644
--- a/src/ml/ml_instance.cc
+++ b/src/ml/ml_instance.cc
@@ -32,11 +32,15 @@ namespace ml {
 namespace {
 const int kCustomFilterSuccess = 0;
 const int kNoId = -1;
+
 const std::string kAsync = "async";
 const std::string kBOOLEAN = "BOOLEAN";
 const std::string kBuffer = "buffer";
 const std::string kCallbackId = "callbackId";
+const std::string kConfigPath = "configPath";
+const std::string kCustomRequirement = "customRequirement";
 const std::string kDataId = "dataId";
+const std::string kDatasetId = "datasetId";
 const std::string kDefinition = "definition";
 const std::string kDimensions = "dimensions";
 const std::string kFwType = "fwType";
@@ -44,49 +48,45 @@ const std::string kGetInputMode = "getInputMode";
 const std::string kHw = "hw";
 const std::string kHwType = "hwType";
 const std::string kId = "id";
+const std::string kInTensorsInfo = "inTensorsInfo";
 const std::string kIndex = "index";
 const std::string kInputTensorsInfoId = "inputTensorsInfoId";
-const std::string kInTensorsInfo = "inTensorsInfo";
 const std::string kIsDynamicMode = "isDynamicMode";
+const std::string kLayerId = "layerId";
+const std::string kLevel = "level";
 const std::string kListenerName = "listenerName";
 const std::string kLocation = "location";
+const std::string kMode = "mode";
 const std::string kModelPath = "modelPath";
-const std::string kConfigPath = "configPath";
 const std::string kName = "name";
 const std::string kNnfw = "nnfw";
-const std::string kCustomRequirement = "customRequirement";
 const std::string kNodeName = "nodeName";
 const std::string kOpen = "open";
+const std::string kOptimizerId = "optimizerId";
+const std::string kOptions = "options";
 const std::string kOtherId = "otherId";
-const std::string kOutputTensorsInfoId = "outputTensorsInfoId";
 const std::string kOutTensorsInfo = "outTensorsInfo";
+const std::string kOutputTensorsInfoId = "outputTensorsInfoId";
 const std::string kPadName = "padName";
 const std::string kPipelineStateChangeListenerName = "listenerName";
 const std::string kProperty = "property";
 const std::string kRequestId = "requestId";
+const std::string kSTRING = "STRING";
+const std::string kSaveFormat = "saveFormat";
+const std::string kSavePath = "savePath";
 const std::string kShape = "shape";
 const std::string kSize = "size";
 const std::string kStatus = "status";
-const std::string kSTRING = "STRING";
+const std::string kSummary = "summary";
 const std::string kTensorsDataId = "tensorsDataId";
 const std::string kTensorsInfoId = "tensorsInfoId";
+const std::string kTest = "test";
 const std::string kTimeout = "timeout";
+const std::string kTrain = "train";
 const std::string kType = "type";
+const std::string kValid = "valid";
 const std::string kValue = "value";
 
-// TODO: sort const
-const std::string kTrain = "train";
-const std::string kValid = "valid";
-const std::string kTest = "test";
-const std::string kOptions = "options";
-const std::string kLayerId = "layerId";
-const std::string kDatasetId = "datasetId";
-const std::string kOptimizerId = "optimizerId";
-const std::string kLevel = "level";
-const std::string kSummary = "summary";
-const std::string kSavePath = "savePath";
-const std::string kSaveFormat = "saveFormat";
-const std::string kMode = "mode";
 }  //  namespace
 
 using namespace common;
@@ -201,7 +201,6 @@ MlInstance::MlInstance()
   REGISTER_METHOD(MLTrainerModelSetDataset);
   REGISTER_METHOD(MLTrainerModelSetOptimizer);
   REGISTER_METHOD(MLTrainerModelDispose);
-  REGISTER_METHOD(MLTrainerDatasetCreateGenerator);
   REGISTER_METHOD(MLTrainerDatasetCreateFromFile);
   REGISTER_METHOD(MLTrainerDatasetSetProperty);
   REGISTER_METHOD(MLTrainerDatasetDispose);
@@ -1920,12 +1919,7 @@ void MlInstance::MLTrainerModelRun(const picojson::value& args, picojson::object
   auto async_logic = [this, id, options](decltype(out) out) {
     PlatformResult result;
 
-    try {
-      result = trainer_manager_.ModelRun(id, options);
-    } catch (...) {  // MK-TODO verify why this exception occurs
-      LoggerE("Unhandled and unexpected exception!!");
-      ReportError(result, &out);
-    }
+    result = trainer_manager_.ModelRun(id, options);
 
     if (!result) {
       ReportError(result, &out);
@@ -2102,11 +2096,6 @@ void MlInstance::MLTrainerModelDispose(const picojson::value& args,
   ReportSuccess(out);
 }
 
-void MlInstance::MLTrainerDatasetCreateGenerator(const picojson::value& args,
-                                                 picojson::object& out) {
-  ScopeLogger("args: %s", args.serialize().c_str());
-}
-
 void MlInstance::MLTrainerDatasetCreateFromFile(const picojson::value& args,
                                                 picojson::object& out) {
   ScopeLogger("args: %s", args.serialize().c_str());
diff --git a/src/ml/ml_instance.h b/src/ml/ml_instance.h
index 5fed8fa8..6269a6ef 100644
--- a/src/ml/ml_instance.h
+++ b/src/ml/ml_instance.h
@@ -177,7 +177,6 @@ class MlInstance : public common::ParsedInstance {
   void MLTrainerModelDispose(const picojson::value& args,
                              picojson::object& out);
 
-  void MLTrainerDatasetCreateGenerator(const picojson::value& args, picojson::object& out);
   void MLTrainerDatasetCreateFromFile(const picojson::value& args, picojson::object& out);
   void MLTrainerDatasetSetProperty(const picojson::value& args, picojson::object& out);
   void MLTrainerDatasetDispose(const picojson::value& args,