From 94a27dd6b59657935771b3fa3fb3ad0fb2b4a901 Mon Sep 17 00:00:00 2001
From: Jihoon Lee <jhoon.it.lee@samsung.com>
Date: Tue, 23 Nov 2021 20:28:49 +0900
Subject: [PATCH] [nn] InputLayer->InputConnection

This patch substitue input layer to input connection while removing
props::InputLayer

**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>
---
 nntrainer/compiler/recurrent_realizer.h |  1 -
 nntrainer/layers/common_properties.cpp  |  3 ---
 nntrainer/layers/common_properties.h    | 41 +++++++++++++++------------------
 nntrainer/models/neuralnet.cpp          |  6 +++--
 nntrainer/models/neuralnet.h            |  2 +-
 5 files changed, 23 insertions(+), 30 deletions(-)

diff --git a/nntrainer/compiler/recurrent_realizer.h b/nntrainer/compiler/recurrent_realizer.h
index 997c266..eae0fe3 100644
--- a/nntrainer/compiler/recurrent_realizer.h
+++ b/nntrainer/compiler/recurrent_realizer.h
@@ -26,7 +26,6 @@ namespace nntrainer {
 namespace props {
 class UnrollFor;
 class ReturnSequences;
-class InputLayer;
 class OutputLayer;
 class RecurrentInput;
 class RecurrentOutput;
diff --git a/nntrainer/layers/common_properties.cpp b/nntrainer/layers/common_properties.cpp
index 27b5431..a17021c 100644
--- a/nntrainer/layers/common_properties.cpp
+++ b/nntrainer/layers/common_properties.cpp
@@ -238,9 +238,6 @@ bool WeightRegularizerConstant::isValid(const float &value) const {
   return value >= 0.0f;
 }
 
-InputLayer::InputLayer() : Name() {}
-InputLayer::InputLayer(const std::string &name) : Name(name) {}
-
 OutputLayer::OutputLayer() : Name() {}
 OutputLayer::OutputLayer(const std::string &name) : Name(name) {}
 
diff --git a/nntrainer/layers/common_properties.h b/nntrainer/layers/common_properties.h
index 1f84257..aa5c6ce 100644
--- a/nntrainer/layers/common_properties.h
+++ b/nntrainer/layers/common_properties.h
@@ -165,6 +165,24 @@ public:
   static constexpr const char *key =
     "input_layers";                     /**< unique key to access */
   using prop_tag = connection_prop_tag; /**< property type */
+
+  /**
+   * @brief cast operator for property
+   * @todo deprecate this, this is needed to bridge input_layers(name) <-> input
+   * connections temporarily
+   *
+   * @return std::string value
+   */
+  operator const std::string &() const { return get().getName(); }
+
+  /**
+   * @brief cast operator for property
+   * @todo deprecate this, this is needed to bridge input_layers(name) <-> input
+   * connections temporarily
+   *
+   * @return std::string value
+   */
+  operator std::string &() { return get().getName(); }
 };
 
 /**
@@ -584,29 +602,6 @@ public:
 };
 
 /**
- * @brief Input Layer name property which saves a single connection
- * (practically, std::vector<InputLayers> is used)
- *
- */
-class InputLayer : public Name {
-public:
-  /**
-   * @brief Construct InputLayer object
-   *
-   */
-  InputLayer();
-
-  /**
-   * @brief Construct InputLayer with the given name
-   *
-   * @param name Name for the input_layers
-   */
-  InputLayer(const std::string &name);
-  static constexpr const char *key = "input_layers";
-  using prop_tag = str_prop_tag;
-};
-
-/**
  * @brief Output Layer name property which saves a single connection
  * (practically, std::vector<InputLayers> is used)
  *
diff --git a/nntrainer/models/neuralnet.cpp b/nntrainer/models/neuralnet.cpp
index bb5dc6a..e049d57 100644
--- a/nntrainer/models/neuralnet.cpp
+++ b/nntrainer/models/neuralnet.cpp
@@ -28,6 +28,7 @@
 #include <sstream>
 
 #include <activation_realizer.h>
+#include <common_properties.h>
 #include <databuffer.h>
 #include <flatten_realizer.h>
 #include <ini_interpreter.h>
@@ -108,9 +109,10 @@ int NeuralNetwork::compile() {
                             : std::get<props::LossType>(model_props);
 
   auto &input_layer_prop =
-    std::get<std::vector<props::InputLayer>>(model_props);
+    std::get<std::vector<props::InputConnection>>(model_props);
   /// @note label layer might need to be treated in the similar way as well
 
+  /// @todo deprecate this instead directly pass connection to the realizer
   std::vector<std::string> input_layers = {};
   if (!input_layer_prop.empty()) {
     input_layers = std::vector<std::string>(input_layer_prop.begin(),
@@ -179,7 +181,7 @@ int NeuralNetwork::initialize() {
     std::get<props::TrainingBatchSize>(model_flex_props));
 
   auto &input_layer_prop =
-    std::get<std::vector<props::InputLayer>>(model_props);
+    std::get<std::vector<props::InputConnection>>(model_props);
   auto &label_layer_prop =
     std::get<std::vector<props::LabelLayer>>(model_props);
 
diff --git a/nntrainer/models/neuralnet.h b/nntrainer/models/neuralnet.h
index 02ea6bc..2a1f4f0 100644
--- a/nntrainer/models/neuralnet.h
+++ b/nntrainer/models/neuralnet.h
@@ -489,7 +489,7 @@ private:
                props::ContinueTrain, props::SaveBestPath,
                props::MemoryOptimization>;
   using RigidPropTypes =
-    std::tuple<props::LossType, std::vector<props::InputLayer>,
+    std::tuple<props::LossType, std::vector<props::InputConnection>,
                std::vector<props::LabelLayer>>;
 
   RigidPropTypes model_props;         /**< model props */
-- 
2.7.4