[doc] Add doxygen commnet on getNumLoadedTensors

Add doxygen comment on getNumLoadedTensors **Self evaluation:** 1. Build test: [X]Passed [ ]Failed [ ]Skipped 2. Run test: [X]Passed [ ]Failed [ ]Skipped Signed-off-by: Donghak PARK <[email protected]>
nnstreamer · Feb 11, 2025 · 97a7dcd · 97a7dcd
1 parent 1da9b80
commit 97a7dcd
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Showing 8 changed files with 48 additions and 5 deletions.
diff --git a/Applications/SimpleFC/jni/main.cpp b/Applications/SimpleFC/jni/main.cpp
@@ -131,8 +131,8 @@ void createAndRun(unsigned int epochs, unsigned int batch_size,
 
   float input[1 * 1024];
 
-  for (uint j = 0; j < feature_size; ++j)
-    input[j] = (j / feature_size);
+  for (unsigned int j = 0; j < feature_size; ++j)
+    input[j] = (j / (float)feature_size);
 
   std::vector<float *> in;
   std::vector<float *> answer;
@@ -183,8 +183,8 @@ int main(int argc, char *argv[]) {
   std::cout << "swap_on : " << swap_on << std::endl;
   std::cout << "look_ahead : " << look_ahead << std::endl;
 
-  uint batch_size = 1;
-  uint epoch = 1;
+  unsigned int batch_size = 1;
+  unsigned int epoch = 1;
 
   try {
     createAndRun(epoch, batch_size, swap_on, look_ahead);

diff --git a/nntrainer/graph/network_graph.h b/nntrainer/graph/network_graph.h
@@ -502,7 +502,18 @@ class NetworkGraph {
    */
   bool isMixedPrecision() { return (!istrequal(tensor_dtype[1], "FP32")); }
 
+  /**
+   * @brief Get Number of Loaded WeightPool Tensor
+   *
+   * @return Number of Loaded WeightPool Tensor
+   */
   unsigned int getNumLoadedWeightPoolTensors();
+
+  /**
+   * @brief Get Number of Loaded TensorPool Tensor
+   *
+   * @return Number of Loaded TensorPool Tensor
+   */
   unsigned int getNumLoadedTensorPoolTensors();
 
 private:

diff --git a/nntrainer/layers/layer_node.h b/nntrainer/layers/layer_node.h
@@ -750,7 +750,9 @@ class LayerNode final : public ml::train::Layer, public GraphNode {
   /**
    * @brief     read layer Weight & Bias data from file
    * @param file input file stream
-   * @param bool read optimizer variables
+   * @param swap swap type
+   * @param mode Execution mode
+   * @param opt_var read optimizer variables
    */
   void read(std::ifstream &file, bool opt_var = false,
             ml::train::ExecutionMode mode = ml::train::ExecutionMode::TRAIN,

diff --git a/nntrainer/tensor/cache_loader.h b/nntrainer/tensor/cache_loader.h
@@ -115,6 +115,11 @@ class CacheLoader {
    */
   virtual int cancelAsync(int id);
 
+  /**
+   * @brief Get number of loaded tensors
+   *
+   * @return number of loaded tensors
+   */
   virtual unsigned int getNumLoadedTensors();
 
 private:

diff --git a/nntrainer/tensor/cache_pool.h b/nntrainer/tensor/cache_pool.h
@@ -188,6 +188,11 @@ class CachePool : public MemoryPool {
    */
   virtual std::string getName() { return name; }
 
+  /**
+   * @brief Get number of loaded tensors
+   *
+   * @return number of loaded tensors
+   */
   virtual unsigned int getNumLoadedTensors();
 
 protected:

diff --git a/nntrainer/tensor/manager.h b/nntrainer/tensor/manager.h
@@ -540,8 +540,18 @@ class Manager {
    */
   bool isMixedPrecision() { return !istrequal(tensor_dtype[0], "FP32"); }
 
+  /**
+   * @brief Get Number of Loaded WeightPool Tensor
+   *
+   * @return Number of Loaded WeightPool Tensor
+   */
   unsigned int getNumLoadedWeightPoolTensors();
 
+  /**
+   * @brief Get Number of Loaded TensorPool Tensor
+   *
+   * @return Number of Loaded TensorPool Tensor
+   */
   unsigned int getNumLoadedTensorPoolTensors();
 
 private:

diff --git a/nntrainer/tensor/swap_device.h b/nntrainer/tensor/swap_device.h
@@ -119,6 +119,11 @@ class SwapDevice {
    */
   const std::string getDevicePath() const { return dev_path; }
 
+  /**
+   * @brief Get number of loaded tensors
+   *
+   * @return number of loaded tensors
+   */
   unsigned int getNumLoadedTensors();
 
 private:

diff --git a/nntrainer/tensor/tensor_pool.h b/nntrainer/tensor/tensor_pool.h
@@ -304,6 +304,11 @@ class TensorPool {
    */
   void loadCacheCancel(int id);
 
+  /**
+   * @brief Get number of loaded tensors
+   *
+   * @return number of loaded tensors
+   */
   unsigned int getNumLoadedTensors();
 
 private: