chore : conv forward 1/2D formatting

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

@@ -20,6 +20,7 @@
 #include "aidge/utils/Types.h"
 
 namespace Aidge {
+
 // Operator implementation entry point for the backend
 using Conv1D_Op = Conv_Op<1>;
 using ConvImpl1D_cpu = OperatorImpl_cpu<Conv_Op<1>,

src/operator/ConvImpl.cpp

@@ -40,16 +40,17 @@ void Aidge::ConvImpl1D_cpu::forward() {
     const auto& input2 = (op_.getInput(2)) ? op_.getInput(2)->refCastFrom(input2Fallback, *op_.getOutput(0)) : Tensor();
 
     // Call kernel
-    impl.forward(op_.strideDims(),
-            op_.dilationDims(),
-            op_.kernelDims(),
-            op_.getInput(0)->template dims<3>(), // input dimensions
-            dynamic_cast<const Conv_Op<1>&>(mOp).outChannels(), // outChannels
-            input0.getImpl()->rawPtr(), // input
-            input1.getImpl()->rawPtr(), // weight
-            op_.getInput(2) ? input2.getImpl()->rawPtr() : nullptr, // bias
-            getCPUPtr(mOp.getRawOutput(0)) // output
-            );
+    impl.forward(
+        op_.strideDims(),
+        op_.dilationDims(),
+        op_.kernelDims(),
+        op_.getInput(0)->template dims<3>(), // input dimensions
+        dynamic_cast<const Conv_Op<1> &>(mOp).outChannels(),    // outChannels
+        input0.getImpl()->rawPtr(),                             // input
+        input1.getImpl()->rawPtr(),                             // weight
+        op_.getInput(2) ? input2.getImpl()->rawPtr() : nullptr, // bias
+        getCPUPtr(mOp.getRawOutput(0))                          // output
+    );
 }
 
 template <> void ConvImpl1D_cpu::backward() {