update recipes header file with 'foldConstantOfShape'

include/aidge/recipes/Recipes.hpp

@@ -51,11 +51,14 @@ void matMulToFC(std::shared_ptr<GraphView> graphView);
 size_t removeNode(std::shared_ptr<GraphView> graphView, const std::string& type, bool incProducers = false);
 
 /**
- * @brief Fuses constant => Generic | constantOfShape and transforms it into a Producer
- * @param graph Graph to manipulate
- * @return size_t Number of replacement
+ * @brief Compute the output of any ConstantOfShape with a constant input and
+ * replaces it with a Producer.
+ * @details Replace "constant->GenericOperator|ConstantOfShape" with "Producer".
+ * @note Currently, this function only matches the query "Producer->ConstantOfShape".
+ * @param graph GraphView to transform.
+ * @return std::size_t Number of replacements.
  */
-size_t removeConstantOfShape(std::shared_ptr<GraphView> graph_view);
+std::size_t foldConstantOfShape(std::shared_ptr<GraphView> view);
 
 /**
  * @brief Remove ``Dropout`` Node.
@@ -139,16 +142,16 @@ void expandMetaOps(std::shared_ptr<GraphView> graph, bool recursive = false);
 
 /**
  * @brief Tile any :cpp:function:`Aidge::MatMul` operator to several fixed size matrix multiplications.
- * For instance, for a MatMul of size 80x80 and a tiling of 16x16, this will tile 
+ * For instance, for a MatMul of size 80x80 and a tiling of 16x16, this will tile
  * the MatMul operator to 25 (5 by 5) MatMul operators of size 16x16, with Slice
  * operators inserted at the inputs and Concat operators inserted at the outputs.
- * 
- * This is especially useful when matrix multiplication must be mapped to fixed 
- * maximum size hardware TPU (Tensor Processing Unit) or MMA (Matrix Multiplication 
- * Accelerator). This recipe can be combined with the :cpp:function:`Aidge::convToMatMul` recipe in 
- * order to convert convolutions to matrix multiplication beforehand, and 
+ *
+ * This is especially useful when matrix multiplication must be mapped to fixed
+ * maximum size hardware TPU (Tensor Processing Unit) or MMA (Matrix Multiplication
+ * Accelerator). This recipe can be combined with the :cpp:function:`Aidge::convToMatMul` recipe in
+ * order to convert convolutions to matrix multiplication beforehand, and
  * :cpp:function:`Aidge::constantFolding` recipe to fold sliced constant tensors.
- * 
+ *
  * @param matMul MatMul operator to be tiled.
  * @param maxDims Maximum output dimensions of the tiled MatMul operators.
  */
@@ -181,7 +184,7 @@ size_t convToMatMul(std::shared_ptr<GraphView> graph);
 
 /**
  * @brief Adapt a graph to the available kernels of a backend.
- * 
+ *
  * @param graph Graph to manipulate
  */
 void adaptToBackend(std::shared_ptr<GraphView> graph);
@@ -189,18 +192,18 @@ void adaptToBackend(std::shared_ptr<GraphView> graph);
 
 /**
  * @brief Create a GenericOp from an Operator and replace it
- * 
+ *
  * @param node Node which Operator will be changed into a generic Operator
  */
 void toGenericOp(std::shared_ptr<Node> node);
 
 /**
  * @brief The node passed contains an operator which input of index 1 is supposed be be weights of type Int4, Int3, Int2, binary.
- *        This recipie only operates memory transformations on the weight tensor. 
+ *        This recipie only operates memory transformations on the weight tensor.
  *        First, permutes the dimensions to match the dataformat NHWC
- *        Second, compact the last dimension of the weights (Channel dimension) into 8bits 
- * 
- * @param node Node 
+ *        Second, compact the last dimension of the weights (Channel dimension) into 8bits
+ *
+ * @param node Node
  */
 void applyWeightInterleaving(std::shared_ptr<Node> node);