add forwardDims unit tests for ArgMax

unit_tests/operator/Test_ArgMaxImpl.cpp

@@ -11,6 +11,8 @@
 
 #include <catch2/catch_test_macros.hpp>
 #include <memory>
+#include <numeric>   // std::accumulate
+#include <random>    // std::random_device, std::mt19937, std::uniform_real_distribution
 
 #include "aidge/data/Tensor.hpp"
 #include "aidge/operator/ArgMax.hpp"
@@ -22,6 +24,82 @@
 using namespace Aidge;
 
 TEST_CASE("[cpu/operator] ArgMax(forward)", "[ArgMax][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::uniform_int_distribution<std::int32_t> axisDist(std::int32_t(0), std::int32_t(nbDims-1));
+                std::int32_t axis = axisDist(gen);
+                for (std::size_t i = 0; i < nbDims; i++) {
+                    dims[i] = dimSizeDist(gen);
+                    if (i == axis) {
+                        expectedOutDims[i] = 1;
+                    }
+                    else {
+                        expectedOutDims[i] = dims[i];
+                    }
+                }
+
+                std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(dims);
+                myInput->setBackend("cpu");
+                myInput->setDataType(DataType::Float32);
+                myInput->zeros();
+                std::shared_ptr<Node> myArgMax = ArgMax(axis);
+                auto op = std::static_pointer_cast<OperatorTensor>(myArgMax -> 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::uniform_int_distribution<std::int32_t> axisDist(std::int32_t(0), std::int32_t(nbDims-1));
+                std::int32_t axis = axisDist(gen);
+                for (std::size_t i = 0; i < nbDims; i++) {
+                    dims[i] = dimSizeDist(gen);
+                    if(i != axis) {
+                        expectedOutDims.push_back(dims[i]);
+                    }
+                }
+                if(expectedOutDims.empty()) {
+                    expectedOutDims.push_back(1);
+                }
+
+                std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(dims);
+                myInput->setBackend("cpu");
+                myInput->setDataType(DataType::Float32);
+                std::shared_ptr<Node> myArgMax = ArgMax(axis, false);
+                auto op = std::static_pointer_cast<OperatorTensor>(myArgMax -> 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("3D Tensor") {
             std::shared_ptr<Tensor> myInput = std::make_shared<Tensor>(Array3D<float,2,3,4> {
                 {

unit_tests/operator/Test_ReduceMeanImpl.cpp

@@ -310,8 +310,7 @@ TEST_CASE("[cpu/operator] ReduceMean(forward)", "[ReduceMean][CPU]") {
             op->setDataType(DataType::Float32);
             op->setBackend("cpu");
             myReduceMean->forward();
-            op->getOutput(0)->print();
-            // approxEq<float>(*(op->getOutput(0)), *myOutput);
+
             REQUIRE(approxEq<float>(*(op->getOutput(0)), *myOutput));
         }
         SECTION("noop_with_empty_axes") {

unit_tests/operator/Test_ReduceSumImpl.cpp

@@ -11,6 +11,8 @@
 
 #include <catch2/catch_test_macros.hpp>
 #include <memory>
+#include <numeric>   // std::accumulate
+#include <random>    // std::random_device, std::mt19937, std::uniform_real_distribution
 
 #include "aidge/data/Tensor.hpp"
 #include "aidge/operator/ReduceSum.hpp"