[CAPI/acr] Update tizen capi

**Changes proposed in this PR:**
- Setting void *user_data
- Update layer type enum

**Self evaluation:**
1. Build test: [X]Passed [ ]Failed [ ]Skipped
2. Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: Jihoon Lee <jhoon.it.lee@samsung.com>

diff --git a/api/ccapi/include/layer.h b/api/ccapi/include/layer.h
index 80efd18ccc1aaf34cf0e4eac68215bcd503cf8b9..ecddbf5a0005356e2b0d6a4aac969e416aa8fad0 100644 (file)
--- a/api/ccapi/include/layer.h
+++ b/api/ccapi/include/layer.h
@@ -33,17 +33,18 @@ namespace train {
 enum LayerType {
   LAYER_IN = ML_TRAIN_LAYER_TYPE_INPUT, /** Input Layer type */
   LAYER_FC = ML_TRAIN_LAYER_TYPE_FC,    /** Fully Connected Layer type */
-  LAYER_BN,                             /** Batch Normalization Layer type */
-  LAYER_CONV2D,                         /** Convolution 2D Layer type */
-  LAYER_POOLING2D,                      /** Pooling 2D Layer type */
-  LAYER_FLATTEN,                        /** Flatten Layer type */
-  LAYER_ACTIVATION,                     /** Activation Layer type */
-  LAYER_ADDITION,                       /** Addition Layer type */
-  LAYER_CONCAT,                         /** Concat Layer type */
-  LAYER_OUT,                            /** Multi Output Layer type */
-  LAYER_LOSS,                           /** Loss Layer type */
-  LAYER_BACKBONE_NNSTREAMER,            /** Backbone using NNStreamer */
-  LAYER_BACKBONE_TFLITE,                /** Backbone using TFLite */
+  LAYER_BN = ML_TRAIN_LAYER_TYPE_BN,    /** Batch Normalization Layer type */
+  LAYER_CONV2D = ML_TRAIN_LAYER_TYPE_CONV2D, /** Convolution 2D Layer type */
+  LAYER_POOLING2D = ML_TRAIN_LAYER_TYPE_POOLING2D, /** Pooling 2D Layer type */
+  LAYER_FLATTEN = ML_TRAIN_LAYER_TYPE_FLATTEN,     /** Flatten Layer type */
+  LAYER_ACTIVATION =
+    ML_TRAIN_LAYER_TYPE_ACTIVATION,              /** Activation Layer type */
+  LAYER_ADDITION = ML_TRAIN_LAYER_TYPE_ADDITION, /** Addition Layer type */
+  LAYER_CONCAT = ML_TRAIN_LAYER_TYPE_CONCAT,     /** Concat Layer type */
+  LAYER_MULTIOUT = ML_TRAIN_LAYER_TYPE_MULTIOUT, /** Multi Output Layer type */
+  LAYER_LOSS,                                    /** Loss Layer type */
+  LAYER_BACKBONE_NNSTREAMER,                  /** Backbone using NNStreamer */
+  LAYER_BACKBONE_TFLITE,                      /** Backbone using TFLite */
   LAYER_UNKNOWN = ML_TRAIN_LAYER_TYPE_UNKNOWN /** Unknown */
 };
 
@@ -289,7 +290,7 @@ Concat(const std::vector<std::string> &properties = {}) {
  */
 inline std::unique_ptr<Layer>
 MultiOut(const std::vector<std::string> &properties = {}) {
-  return createLayer(LayerType::LAYER_OUT, properties);
+  return createLayer(LayerType::LAYER_MULTIOUT, properties);
 }
 
 /**

diff --git a/api/nntrainer-api-common.h b/api/nntrainer-api-common.h
index 5f91954120699a05e352274fca1fb4d5d7ee74d7..58e99a71a6076bea160e05669b79a758d855583c 100644 (file)
--- a/api/nntrainer-api-common.h
+++ b/api/nntrainer-api-common.h
@@ -27,8 +27,16 @@ extern "C" {
  * @since_tizen 6.0
  */
 typedef enum {
-  ML_TRAIN_LAYER_TYPE_INPUT = 0,    /**< Input Layer */
-  ML_TRAIN_LAYER_TYPE_FC,           /**< Fully Connected Layer */
+  ML_TRAIN_LAYER_TYPE_INPUT = 0,  /**< Input Layer */
+  ML_TRAIN_LAYER_TYPE_FC,         /**< Fully Connected Layer */
+  ML_TRAIN_LAYER_TYPE_BN,         /**< Batch Normalization Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_CONV2D,     /**< Convolution 2D Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_POOLING2D,  /**< Pooling 2D Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_FLATTEN,    /**< Flatten Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_ACTIVATION, /**< Activation Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_ADDITION,   /**< Addition Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_CONCAT,     /**< Concat Layer (since 6.5) */
+  ML_TRAIN_LAYER_TYPE_MULTIOUT,   /**< MultiOut Layer (since 6.5) */
   ML_TRAIN_LAYER_TYPE_UNKNOWN = 999 /**< Unknown Layer */
 } ml_train_layer_type_e;
 

diff --git a/nntrainer/app_context.cpp b/nntrainer/app_context.cpp
index 270d6612026099f98ee717b56ac6491b2072e709..9fddb97993e37cd790a914cdbc78de6b84747851 100644 (file)
--- a/nntrainer/app_context.cpp
+++ b/nntrainer/app_context.cpp
@@ -89,10 +89,10 @@ static void init_global_context_nntrainer(void) {
                      ActivationLayer::type, LayerType::LAYER_ACTIVATION);
   ac.registerFactory(ml::train::createLayer<AdditionLayer>, AdditionLayer::type,
                      LayerType::LAYER_ADDITION);
+  ac.registerFactory(ml::train::createLayer<OutputLayer>, OutputLayer::type,
+                     LayerType::LAYER_MULTIOUT);
   ac.registerFactory(ml::train::createLayer<ConcatLayer>, ConcatLayer::type,
                      LayerType::LAYER_CONCAT);
-  ac.registerFactory(ml::train::createLayer<OutputLayer>, OutputLayer::type,
-                     LayerType::LAYER_OUT);
   ac.registerFactory(ml::train::createLayer<LossLayer>, LossLayer::type,
                      LayerType::LAYER_LOSS);
 #ifdef ENABLE_NNSTREAMER_BACKBONE

diff --git a/nntrainer/layers/layer_factory.cpp b/nntrainer/layers/layer_factory.cpp
index b72b6e6a18ad4149d6ab872f166042a6d2800f1a..3b90690de3002e3ffad43deed67bb0d71ffe0445 100644 (file)
--- a/nntrainer/layers/layer_factory.cpp
+++ b/nntrainer/layers/layer_factory.cpp
@@ -40,7 +40,7 @@ const std::string layerGetStrType(const LayerType &type) {
   switch (type) {
   case LayerType::LAYER_IN:
     return InputLayer::type;
-  case LayerType::LAYER_OUT:
+  case LayerType::LAYER_MULTIOUT:
     return OutputLayer::type;
   case LayerType::LAYER_FC:
     return FullyConnectedLayer::type;