chore : added documentation + cleaned up prints

include/aidge/graphRegex/GraphRegex.hpp

@@ -12,13 +12,12 @@
 namespace Aidge{
 
 /**
- * type for recipes function use in query and resolve  
-*/
+ * @brief type for recipes function use in query and resolve  
+ */
 using RecipesFunctionType = std::function<void(std::shared_ptr<MatchSolution>)>;
 
 /**
- * @brief class which is the hight level interface for graph matching, used to simplify match definition  
- * 
+ * @brief high level interface for graph matching, used to simplify match definition 
  */
 class GraphRegex{
 

include/aidge/operator/OperatorTensor.hpp

@@ -40,6 +40,14 @@ protected:
 public:
     OperatorTensor() = delete;
 
+    /**
+     * @brief Operator tensor constructor. This function is not meant to be called directly but by a derived class constructor
+     * every operator class derive from this class.
+     * 
+	 * @param[in] type     : type of operator (i.e. "Add", "AveragePool",...)
+	 * @param[in] inputsCategory : describes the type of each input.
+	 * @param[in] nbOut    : Number of tensors this operator will output
+     */
     OperatorTensor(const std::string& type, const std::vector<InputCategory>& inputsCategory,
                    const IOIndex_t nbOut);
 
@@ -79,6 +87,15 @@ public:
      * For each dataInput Tensor of the Operator, the first index and dimensions of the feature area.
      */
     virtual std::vector<std::pair<std::vector<Aidge::DimSize_t>, std::vector<DimSize_t>>> computeReceptiveField(const std::vector<DimSize_t>& firstEltDims, const std::vector<DimSize_t>& outputDims, const IOIndex_t outputIdx = 0) const;
+
+	/**
+	 * @brief Will compute the dimensions of operator's output tensor given the input sizes
+ 	 *        If the output dimensions cannot be computed because it depends on some undefined inputs then forwardDims will return false and enter in TOKEN mode for subsequent tensors.
+ 	 *        - TOKEN mode means that forwarddims will only ensure that all inputs and outputs of the graph the node is within are connected.
+ 	 * @param[in] allowDataDependency if set to true, this means that this operator output dimensions depends on the dimensions of optionnal parameter tensors.
+ 	 * @return true if dims have been properly forwarded. false otherwise. If set to false, then forwardDims will enter in token mode.
+ 	 *      
+     */
     virtual bool forwardDims(bool allowDataDependency = false);
     virtual bool dimsForwarded() const;
     ///////////////////////////////////////////////////

include/aidge/operator/Producer.hpp

@@ -103,7 +103,7 @@ public:
     void forward() override final;
 
     void backward() override final {
-        // fmt::print("Basic Producer backward() function.\n");
+        Log::debug("Basic Producer backward() function.");
     }
 
     void setOutput(const IOIndex_t outputIdx, const std::shared_ptr<Data>& data) const override;

python_binding/utils/pybind_Log.cpp

@@ -78,6 +78,13 @@ void init_Log(py::module& m){
     .def_static("set_console_level", &Log::setConsoleLevel, py::arg("level"),
           R"mydelimiter(
           Set the minimum log level displayed in the console.
+          Available `Level`s in ascending order : 
+            - Level.Debug
+            - Level.Info
+            - Level.Notice
+            - Level.Warn
+            - Level.Error
+            - Level.Fatal          
 
           :param level: Log level.
           :type level: Level
@@ -93,6 +100,13 @@ void init_Log(py::module& m){
     .def_static("set_file_level", &Log::setFileLevel, py::arg("level"),
           R"mydelimiter(
           Set the minimum log level saved in the log file.
+          Available `Level`s in ascending order : 
+            - Level.Debug
+            - Level.Info
+            - Level.Notice
+            - Level.Warn
+            - Level.Error
+            - Level.Fatal          
 
           :param level: Log level.
           :type level: Level

src/graph/Node.cpp

@@ -211,7 +211,7 @@ void Aidge::Node::setInputId(const IOIndex_t inId, const IOIndex_t newNodeoutId)
         "Input index ({}) is out of bound ({}) for node {} (of type {})",
         inId, nbInputs(), name(), type());
     if (mIdOutParents[inId] != gk_IODefaultIndex) {
-        Log::notice("Notice: filling a Tensor already attributed");
+        Log::notice("Filling a Tensor already attributed.");
         auto originalParent = input(inId);
         // remove original parent reference to child
         // find the output ID for original Parent
@@ -279,7 +279,7 @@ void Aidge::Node::addChild(std::shared_ptr<GraphView> otherView, const IOIndex_t
 
 void Aidge::Node::addParent(const std::shared_ptr<Node> other_node, const IOIndex_t inId) {
     if (getParent(inId) != nullptr) {
-        Log::notice("Notice: you are replacing an existing parent for node {} (of type {})", name(), type());
+        Log::notice("You are replacing an existing parent for node {} (of type {}).", name(), type());
     }
     AIDGE_ASSERT(inId != gk_IODefaultIndex && inId < nbInputs(),
         "Input index ({}) is out of bound ({}) for node {} (of type {})",

src/scheduler/Scheduler.cpp

@@ -33,6 +33,7 @@
 #include "aidge/operator/MetaOperator.hpp"
 #include "aidge/operator/OperatorTensor.hpp"
 #include "aidge/operator/Producer.hpp"
+#include "aidge/utils/Log.hpp"
 #include "aidge/utils/Types.h"
 
 
@@ -665,7 +666,7 @@ Aidge::Elts_t Aidge::Scheduler::getNbAvailableData(const std::shared_ptr<Node>&
         // => This means data was fed manually to the input, without a Producer
         // In this case, we assume a single-use data (unlike a Producer, which
         // keep producing the data each time it is needed).
-        fmt::print("No producer node attached to input#{} for node {} ({})\n", inputIdx, node->name(), node->type());
+        Log::warn("No producer node attached to input#{} for node {} ({})\n", inputIdx, node->name(), node->type());
         return Elts_t::DataElts(std::static_pointer_cast<Tensor>(node->getOperator()->getRawInput(inputIdx))->size());
     }