[ccapi] rename LearningRateType enum name to LearningRateSchedulerType
authorhyeonseok lee <hs89.lee@samsung.com>
Thu, 13 Apr 2023 02:56:31 +0000 (11:56 +0900)
committerJijoong Moon <jijoong.moon@samsung.com>
Tue, 18 Apr 2023 04:49:44 +0000 (13:49 +0900)
 - rename enum name LearningRateType to LearningRateSchedulerType for more detailed info

Signed-off-by: hyeonseok lee <hs89.lee@samsung.com>
api/ccapi/include/optimizer.h
api/ccapi/src/factory.cpp
nntrainer/app_context.cpp
nntrainer/optimizers/lr_scheduler.h

index 2a89f40..da1f943 100644 (file)
@@ -138,9 +138,9 @@ SGD(const std::vector<std::string> &properties = {}) {
 } // namespace optimizer
 
 /**
- * @brief     Enumeration of learning type
+ * @brief     Enumeration of learning rate scheduler type
  */
-enum LearningRateType {
+enum LearningRateSchedulerType {
   CONSTANT = 0, /**< constant */
   EXPONENTIAL,  /**< exponentially decay */
   STEP          /**< step wise decay */
@@ -194,7 +194,7 @@ public:
  * @brief Factory creator with constructor for learning rate scheduler type
  */
 std::unique_ptr<ml::train::LearningRateScheduler>
-createLearningRateScheduler(const LearningRateType &type,
+createLearningRateScheduler(const LearningRateSchedulerType &type,
                             const std::vector<std::string> &properties = {});
 
 /**
@@ -228,7 +228,8 @@ namespace learning_rate {
  */
 inline std::unique_ptr<LearningRateScheduler>
 Constant(const std::vector<std::string> &properties = {}) {
-  return createLearningRateScheduler(LearningRateType::CONSTANT, properties);
+  return createLearningRateScheduler(LearningRateSchedulerType::CONSTANT,
+                                     properties);
 }
 
 /**
@@ -236,7 +237,8 @@ Constant(const std::vector<std::string> &properties = {}) {
  */
 inline std::unique_ptr<LearningRateScheduler>
 Exponential(const std::vector<std::string> &properties = {}) {
-  return createLearningRateScheduler(LearningRateType::EXPONENTIAL, properties);
+  return createLearningRateScheduler(LearningRateSchedulerType::EXPONENTIAL,
+                                     properties);
 }
 
 /**
@@ -244,7 +246,8 @@ Exponential(const std::vector<std::string> &properties = {}) {
  */
 inline std::unique_ptr<LearningRateScheduler>
 Step(const std::vector<std::string> &properties = {}) {
-  return createLearningRateScheduler(LearningRateType::STEP, properties);
+  return createLearningRateScheduler(LearningRateSchedulerType::STEP,
+                                     properties);
 }
 
 } // namespace learning_rate
index 944fd1f..6aa384a 100644 (file)
@@ -122,7 +122,7 @@ createDataset(DatasetType type, datagen_cb cb, void *user_data,
  * @brief Factory creator with constructor for learning rate scheduler type
  */
 std::unique_ptr<ml::train::LearningRateScheduler>
-createLearningRateScheduler(const LearningRateType &type,
+createLearningRateScheduler(const LearningRateSchedulerType &type,
                             const std::vector<std::string> &properties) {
   auto &ac = nntrainer::AppContext::Global();
   return ac.createObject<ml::train::LearningRateScheduler>(type, properties);
index fbf560f..a66bc66 100644 (file)
@@ -230,7 +230,7 @@ static void add_default_object(AppContext &ac) {
   ac.registerFactory(AppContext::unknownFactory<nntrainer::Optimizer>,
                      "unknown", OptType::UNKNOWN);
 
-  using LRType = LearningRateType;
+  using LRType = LearningRateSchedulerType;
   ac.registerFactory(
     ml::train::createLearningRateScheduler<ConstantLearningRateScheduler>,
     ConstantLearningRateScheduler::type, LRType::CONSTANT);
index 482acca..e6448d5 100644 (file)
@@ -26,7 +26,7 @@ class Exporter;
 /**
  * @brief     Enumeration of optimizer type
  */
-enum LearningRateType {
+enum LearningRateSchedulerType {
   CONSTANT = 0, /**< constant */
   EXPONENTIAL,  /**< exponentially decay */
   STEP          /**< step wise decay */