add noop_with_empty_axes attr

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

@@ -38,7 +38,10 @@ void ReduceMeanImpl_cpu_forward_kernel(const std::vector<std::int32_t>& axes,
     const std::size_t nb_dims = inputDims.size();
     const std::size_t totalElements = std::accumulate(inputDims.cbegin(), inputDims.cend(), 1, std::multiplies<std::size_t>());
 
-    if (axes.size() == 1) {
+    if (axes.empty()){
+        std::copy_n(input,totalElements, output);
+    }
+    else if (axes.size() == 1) {
         const std::size_t stride_pre = std::accumulate(inputDims.cbegin(), inputDims.cbegin() + axes[0], 1, std::multiplies<std::size_t>());
         const std::size_t stride_post = std::accumulate(inputDims.crbegin(), inputDims.crbegin() + nb_dims -1 - axes[0], 1, std::multiplies<std::size_t>());
 

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

@@ -38,7 +38,10 @@ void ReduceSumImpl_cpu_forward_kernel(const std::vector<std::int32_t>& axes,
     const std::size_t nb_dims = inputDims.size();
     const std::size_t totalElements = std::accumulate(inputDims.cbegin(), inputDims.cend(), 1, std::multiplies<std::size_t>());
 
-    if (axes.size() == 1) {
+    if (axes.empty()){
+        std::copy_n(input,totalElements, output);
+    }
+    else if (axes.size() == 1) {
         const std::size_t stride_pre = std::accumulate(inputDims.cbegin(), inputDims.cbegin() + axes[0], 1, std::multiplies<std::size_t>());
         const std::size_t stride_post = std::accumulate(inputDims.crbegin(), inputDims.crbegin() + nb_dims -1 - axes[0], 1, std::multiplies<std::size_t>());
 

unit_tests/operator/Test_ReduceMeanImpl.cpp

@@ -157,7 +157,7 @@ TEST_CASE("[cpu/operator] ReduceMean(forward)", "[ReduceMean][CPU]") {
                 {18.25}
             });
 
-            std::shared_ptr<Node> myReduceMean = ReduceMean({0, 1, 2}, 0);
+            std::shared_ptr<Node> myReduceMean = ReduceMean({}, 0);
             auto op = std::static_pointer_cast<OperatorTensor>(myReduceMean -> getOperator());
             op->associateInput(0,myInput);
             op->setDataType(DataType::Float32);
@@ -179,7 +179,7 @@ TEST_CASE("[cpu/operator] ReduceMean(forward)", "[ReduceMean][CPU]") {
                 {0.1293547f}
             });
 
-            std::shared_ptr<Node> myReduceMean = ReduceMean({0, 1}, 0);
+            std::shared_ptr<Node> myReduceMean = ReduceMean({}, 0);
             auto op = std::static_pointer_cast<OperatorTensor>(myReduceMean -> getOperator());
             op->associateInput(0,myInput);
             op->setDataType(DataType::Float32);
@@ -189,5 +189,33 @@ TEST_CASE("[cpu/operator] ReduceMean(forward)", "[ReduceMean][CPU]") {
             // approxEq<float>(*(op->getOutput(0)), *myOutput);
             REQUIRE(approxEq<float>(*(op->getOutput(0)), *myOutput));
         }
+        SECTION("noop_with_empty_axes") {
+            std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array3D<float,3,2,2> {
+                {
+                    {
+                        { 5.0, 1.0 },
+                        { 20.0, 2.0 }
+                    },
+                    {
+                        { 30.0, 1.0 },
+                        { 40.0, 2.0 }
+                    },
+                    {
+                        { 55.0, 1.0 },
+                        { 60.0, 2.0 }
+                    }
+                }
+            });
+
+            std::shared_ptr<Node> myReduceSum = ReduceSum({}, 0, 1);
+            auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
+            op->associateInput(0,myInput);
+            op->setDataType(DataType::Float32);
+            op->setBackend("cpu");
+            myReduceSum->forward();
+            op->getOutput(0)->print();
+
+            REQUIRE(*(op->getOutput(0)) == *myInput);
+        }
     }
 }
\ No newline at end of file

unit_tests/operator/Test_ReduceSumImpl.cpp

@@ -157,7 +157,7 @@ TEST_CASE("[cpu/operator] ReduceSum(forward)", "[ReduceSum][CPU]") {
                 {219.0}
             });
 
-            std::shared_ptr<Node> myReduceSum = ReduceSum({0, 1, 2}, 0);
+            std::shared_ptr<Node> myReduceSum = ReduceSum({}, 0);
             auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
             op->associateInput(0,myInput);
             op->setDataType(DataType::Float32);
@@ -189,5 +189,33 @@ TEST_CASE("[cpu/operator] ReduceSum(forward)", "[ReduceSum][CPU]") {
             // approxEq<float>(*(op->getOutput(0)), *myOutput);
             REQUIRE(approxEq<float>(*(op->getOutput(0)), *myOutput));
         }
+        SECTION("noop_with_empty_axes") {
+            std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array3D<float,3,2,2> {
+                {
+                    {
+                        { 5.0, 1.0 },
+                        { 20.0, 2.0 }
+                    },
+                    {
+                        { 30.0, 1.0 },
+                        { 40.0, 2.0 }
+                    },
+                    {
+                        { 55.0, 1.0 },
+                        { 60.0, 2.0 }
+                    }
+                }
+            });
+
+            std::shared_ptr<Node> myReduceSum = ReduceSum({}, 0, 1);
+            auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
+            op->associateInput(0,myInput);
+            op->setDataType(DataType::Float32);
+            op->setBackend("cpu");
+            myReduceSum->forward();
+            op->getOutput(0)->print();
+
+            REQUIRE(*(op->getOutput(0)) == *myInput);
+        }
     }
 }
\ No newline at end of file