Fixed merge issues

include/aidge/backend/cpu/operator/FoldImpl.hpp

@@ -27,8 +27,13 @@ namespace Aidge {
 class FoldImpl2DForward_cpu
     : public Registrable<FoldImpl2DForward_cpu,
                          std::tuple<DataType, DataType>,
-                         void(const Fold_Op<2>::Attrs &, const std::vector<DimSize_t> &, const void *,
-                              void *)> {};
+                         void(const std::array<DimSize_t, 2>&,
+                            const std::array<DimSize_t, 2>&,
+                            const std::array<DimSize_t, 2>&,
+                            const std::array<DimSize_t, 2>&,
+                            const std::vector<DimSize_t> &,
+                            const void *,
+                            void *)> {};
 
 class FoldImpl2D_cpu : public OperatorImpl {
 public:

include/aidge/backend/cpu/operator/FoldImpl_forward_kernels.hpp

@@ -23,17 +23,18 @@
 
 namespace Aidge {
 template <class I, class O>
-void FoldImpl2D_cpu_forward_kernel(const Fold_Op<2>::Attrs &attrs, const std::vector<DimSize_t> &dims,
-                                       const void *input_, void *output_)
+void FoldImpl2D_cpu_forward_kernel(const std::array<DimSize_t, 2>& outputDims,
+                                    const std::array<DimSize_t, 2>& strideDims,
+                                    const std::array<DimSize_t, 2>& dilationDims,
+                                    const std::array<DimSize_t, 2>& kernelDims,
+                                    const std::vector<DimSize_t> &dims,
+                                    const void *input_, void *output_)
 {
     const I *input = static_cast<const I *>(input_);
     O *output = static_cast<O *>(output_);
 
-    const auto kernelDims = std::get<3>(attrs);
-    const auto dilationDims = std::get<2>(attrs);
-    const auto strideDims = std::get<1>(attrs);
-    const DimSize_t inHeight = std::get<0>(attrs)[0];
-    const DimSize_t inWidth = std::get<0>(attrs)[1];
+    const DimSize_t inHeight = outputDims[0];
+    const DimSize_t inWidth = outputDims[1];
 
     const DimSize_t kernelExtentHeight = dilationDims[0] *
                                             (kernelDims[0] - 1) + 1;

src/operator/FoldImpl.cpp

@@ -30,8 +30,12 @@ void Aidge::FoldImpl2D_cpu::forward() {
             Registrar<FoldImpl2DForward_cpu>::create({std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dataType(), std::static_pointer_cast<Tensor>(mOp.getRawOutput(0))->dataType()});
 
     // Call kernel
-    kernelFunc(dynamic_cast<const Fold_Op<2>&>(mOp).getStaticAttributes(),
-                        std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dims(),
-                        getCPUPtr(mOp.getRawInput(0)),
-                        getCPUPtr(mOp.getRawOutput(0)));
+    const auto& op_ = static_cast<const Fold_Op<2>&>(mOp);
+    kernelFunc(op_.outputDims(),
+                op_.strideDims(),
+                op_.dilationDims(),
+                op_.kernelDims(),
+                std::static_pointer_cast<Tensor>(mOp.getRawInput(0))->dims(),
+                getCPUPtr(mOp.getRawInput(0)),
+                getCPUPtr(mOp.getRawOutput(0)));
 }

unit_tests/recipies/Test_ConvToMatMul.cpp

@@ -67,7 +67,7 @@ TEST_CASE("[ConvToMatMul] conv") {
     // Simplify the graph: freeze parameters to allow reshaping of the Producers
     for (auto node : g2->getNodes()) {
         if (node->type() == Producer_Op::Type && node->name() != "dataProvider") {
-            std::static_pointer_cast<Producer_Op>(node->getOperator())->getAttr<bool>("Constant") = true;
+            std::static_pointer_cast<Producer_Op>(node->getOperator())->constant() = true;
         }
     }