Corrected additionnal errors

include/aidge/operator/AvgPooling.hpp

@@ -63,8 +63,9 @@ public:
         setDatatype(DataType::Float32);
     }
 
-    constexpr void associateInput(const IOIndex_t /*inputIdx*/, std::shared_ptr<Data> data) override final {
+    constexpr void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
         assert(inputIdx < 1 && "operators supports only 3 inputs");
+        (void) inputIdx; // avoid unused warning
         assert(strcmp(data->type(), Tensor::Type) == 0 && "input data must be of Tensor type");
 
         mInput = std::dynamic_pointer_cast<Tensor>(data);
@@ -91,8 +92,9 @@ public:
     bool outputDimsForwarded() const override final { return !(mOutput->empty()); }
 
 
-    inline Tensor& input(const IOIndex_t /*inputIdx*/) const override final {
+    inline Tensor& input(const IOIndex_t inputIdx) const override final {
         assert(inputIdx == 0 && "operators supports only 1 inputs");
+        (void) inputIdx; // avoid unused warning
         return *(mInput.get());
     }
     inline Tensor& output(const IOIndex_t /*outputIdx*/) const override final { return *(mOutput.get()); }

include/aidge/operator/BatchNorm.hpp

@@ -65,7 +65,7 @@ public:
     //     return *in;
     // }
 
-    constexpr void associateInput(const IOIndex_t /*inputIdx*/, std::shared_ptr<Data> data) override final {
+    constexpr void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
         assert(inputIdx < 5 && "operators supports only 5 inputs");
         assert(strcmp(data->type(), Tensor::Type) == 0 && "input data must be of Tensor type");
 

include/aidge/operator/Conv.hpp

@@ -79,7 +79,7 @@ public:
 
     // }
 
-    constexpr void associateInput(const IOIndex_t /*inputIdx*/, std::shared_ptr<Data> data) override final {
+    constexpr void associateInput(const IOIndex_t inputIdx, std::shared_ptr<Data> data) override final {
         assert(inputIdx < 3 && "operators supports only 3 inputs");
         assert(strcmp(data->type(), Tensor::Type) == 0 && "input data must be of Tensor type");