Fixed wrong offsets

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

@@ -210,8 +210,8 @@ void ConvDepthWiseImpl2D_cpu_forward_kernel(const std::array<DimSize_t, 2>& stri
                 const std::size_t wIndex = ch;
 
                 if (strideDims[0] == 1 && strideDims[1] == 1) {
-                    for (std::size_t i = iIndex; i < iIndex + oxSize*oySize; ++i) {
-                        output[oIndex + i] = biasVal + weights[wIndex] * input[i];
+                    for (std::size_t i = 0; i < oxSize*oySize; ++i) {
+                        output[oIndex + i] = biasVal + weights[wIndex] * input[iIndex + i];
                     }
                 } else  {
                     for (std::size_t ox = 0; ox < oxSize; ++ox, oIndex+=oySize, iIndex+=strideDims[0]*inputDims[3]) {

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

@@ -486,13 +486,13 @@ void ConvImpl2D_cpu_forward_kernel(const array<DimSize_t, 2> &strideDims,
 #endif
         for (int batch = 0; batch < static_cast<int>(inputDims[0]); ++batch) {
             for (int outCh = 0; outCh < static_cast<int>(outChannels); ++outCh) {
-                std::size_t oIndex = (outCh + batch*inputDims[1]) * outChannels_s;
+                std::size_t oIndex = (outCh + batch*outChannels) * outChannels_s;
 
                 // If bias = nullptr, set B(0)
                 B biasVal = (biases != nullptr) ? biases[outCh] : B(0);
                 std::fill(output + oIndex, output + oIndex + outChannels_s, biasVal);
                 for (std::size_t inCh = 0; inCh < inputDims[1]; ++inCh) {
-                    oIndex = (outCh + batch*inputDims[1]) * outChannels_s;
+                    oIndex = (outCh + batch*outChannels) * outChannels_s;
                     std::size_t iIndex = (inCh + batch * inputDims[1]) *
                                          inputDims[2] * inputDims[3];
                     const std::size_t wIndex =
@@ -575,13 +575,13 @@ void ConvImpl2D_cpu_forward_kernel(const array<DimSize_t, 2> &strideDims,
 #endif
         for (int batch = 0; batch < static_cast<int>(inputDims[0]); ++batch) {
             for (int outCh = 0; outCh < static_cast<int>(outChannels); ++outCh) {
-                std::size_t oIndex = (outCh + batch*inputDims[1]) * outChannels_s;
+                std::size_t oIndex = (outCh + batch*outChannels) * outChannels_s;
 
                 // If bias = nullptr, set B(0)
                 B biasVal = (biases != nullptr) ? biases[outCh] : B(0);
                 std::fill(output + oIndex, output + oIndex + outChannels_s, biasVal);
                 for (std::size_t inCh = 0; inCh < inputDims[1]; ++inCh) {
-                    oIndex = (outCh + batch*inputDims[1]) * outChannels_s;
+                    oIndex = (outCh + batch*outChannels) * outChannels_s;
                     std::size_t iIndex = (inCh + batch * inputDims[1]) *
                                          inputDims[2] * inputDims[3];
                     const std::size_t wIndex = (inCh + outCh * inputDims[1]);
@@ -611,13 +611,13 @@ void ConvImpl2D_cpu_forward_kernel(const array<DimSize_t, 2> &strideDims,
 #endif
         for (int batch = 0; batch < static_cast<int>(inputDims[0]); ++batch) {
             for (int outCh = 0; outCh < static_cast<int>(outChannels); ++outCh) {
-                std::size_t oIndex = (outCh + batch*inputDims[1]) * outChannels_s;
+                std::size_t oIndex = (outCh + batch*outChannels) * outChannels_s;
 
                 // If bias = nullptr, set B(0)
                 B biasVal = (biases != nullptr) ? biases[outCh] : B(0);
                 std::fill(output + oIndex, output + oIndex + outChannels_s, biasVal);
                 for (std::size_t inCh = 0; inCh < inputDims[1]; ++inCh) {
-                    oIndex = (outCh + batch*inputDims[1]) * outChannels_s;
+                    oIndex = (outCh + batch*outChannels) * outChannels_s;
                     std::size_t iIndex_channel =
                         (inCh + batch * inputDims[1]) * inputDims[2] *
                         inputDims[3];