add forwardDims test for ReduceSum

unit_tests/operator/Test_ReduceSumImpl.cpp

@@ -22,6 +22,129 @@
 using namespace Aidge;
 
 TEST_CASE("[cpu/operator] ReduceSum(forward)", "[ReduceSum][CPU]") {
+    SECTION("ForwardDims")
+    {
+        constexpr std::uint16_t NBTRIALS = 10;
+        // Create a random number generator
+        std::random_device rd;
+        std::mt19937 gen(rd());
+        std::uniform_real_distribution<float> valueDist(0.1f, 1.1f); // Random float distribution between 0 and 1
+        std::uniform_int_distribution<std::size_t> dimSizeDist(std::size_t(2), std::size_t(10));
+        std::uniform_int_distribution<std::size_t> nbDimsDist(std::size_t(1), std::size_t(5));
+        std::uniform_int_distribution<int> boolDist(0,1);
+
+        SECTION("KeepDims") {
+            for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
+                DimSize_t nbDims = nbDimsDist(gen);
+                std::vector<DimSize_t> dims(nbDims);
+                std::vector<DimSize_t> expectedOutDims(nbDims);
+                std::vector<std::int32_t> axes;
+                for (std::size_t i = 0; i < nbDims; i++) {
+                    dims[i] = dimSizeDist(gen);
+                    expectedOutDims[i] = dims[i];
+                    if(boolDist(gen)) {
+                        axes.push_back(i);
+                        expectedOutDims[i] = 1;
+                    }
+                }
+                if (axes.empty()) { // Default behaviour if no axes are provided is to reduce all dimensions
+                   std::fill(expectedOutDims.begin(), expectedOutDims.end(), 1);
+                }
+
+                std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(dims);
+                myInput->setBackend("cpu");
+                myInput->setDataType(DataType::Float32);
+                myInput->zeros();
+                std::shared_ptr<Node> myReduceSum = ReduceSum(axes, true);
+                auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
+                op->associateInput(0,myInput);
+                op->setDataType(DataType::Float32);
+                op->setBackend("cpu");
+                op->forwardDims();
+
+                const auto outputDims = op->getOutput(0)->dims();
+                REQUIRE(outputDims == expectedOutDims);
+            }
+        }
+        SECTION("Not KeepDims") {
+            for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
+                DimSize_t nbDims = nbDimsDist(gen);
+                std::vector<DimSize_t> dims(nbDims);
+                std::vector<DimSize_t> expectedOutDims;
+                std::vector<std::int32_t> axes;
+                for (std::size_t i = 0; i < nbDims; i++) {
+                    dims[i] = dimSizeDist(gen);
+                    if(boolDist(gen)) {
+                        axes.push_back(i);
+                    }
+                    else {
+                        expectedOutDims.push_back(dims[i]);
+                    }
+                }
+                if (axes.empty() || expectedOutDims.empty()) { // Default behaviour if no axes are provided is to reduce all dimensions
+                   expectedOutDims = std::vector<DimSize_t>{1};
+                }
+
+                std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(dims);
+                myInput->setBackend("cpu");
+                myInput->setDataType(DataType::Float32);
+                std::shared_ptr<Node> myReduceSum = ReduceSum(axes, false);
+                auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
+                op->associateInput(0,myInput);
+                op->setDataType(DataType::Float32);
+                op->setBackend("cpu");
+
+                op->forwardDims();
+
+                const auto outputDims = op->getOutput(0)->dims();
+                REQUIRE(outputDims == expectedOutDims);
+            }
+        }
+        SECTION("NoopWithEmptyAxes") {
+            for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
+                DimSize_t nbDims = nbDimsDist(gen);
+                std::vector<DimSize_t> dims(nbDims);
+                for (std::size_t i = 0; i < nbDims; i++) {
+                    dims[i] = dimSizeDist(gen);
+                }
+                std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(dims);
+                myInput->setBackend("cpu");
+                myInput->setDataType(DataType::Float32);
+                std::shared_ptr<Node> myReduceSum = ReduceSum(std::vector<int32_t>{}, false, true);
+                auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
+                op->associateInput(0,myInput);
+                op->setDataType(DataType::Float32);
+                op->setBackend("cpu");
+
+                op->forwardDims();
+
+                const auto outputDims = op->getOutput(0)->dims();
+                REQUIRE(outputDims == dims);
+            }
+        }
+        SECTION("Not NoopWithEmptyAxes") {
+            for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
+                DimSize_t nbDims = nbDimsDist(gen);
+                std::vector<DimSize_t> dims(nbDims);
+                for (std::size_t i = 0; i < nbDims; i++) {
+                    dims[i] = dimSizeDist(gen);
+                }
+                std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(dims);
+                myInput->setBackend("cpu");
+                myInput->setDataType(DataType::Float32);
+                std::shared_ptr<Node> myReduceSum = ReduceSum({}, false, false);
+                auto op = std::static_pointer_cast<OperatorTensor>(myReduceSum -> getOperator());
+                op->associateInput(0,myInput);
+                op->setDataType(DataType::Float32);
+                op->setBackend("cpu");
+
+                op->forwardDims();
+
+                REQUIRE(op->getOutput(0)->nbDims() == 1);
+                REQUIRE(op->getOutput(0)->size() == 1);
+            }
+        }
+    }
     SECTION("KeepDims") {
         SECTION("test 1") {
             std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array3D<float,3,2,2> {