diff --git a/unit_tests/operator/Test_EqualImpl.cpp b/unit_tests/operator/Test_EqualImpl.cpp
index a229b8ce3ebcd7672323f2585e3a48343f544c3d..013e16ebbf467e6111adaba90900b6cacc06ba67 100644
--- a/unit_tests/operator/Test_EqualImpl.cpp
+++ b/unit_tests/operator/Test_EqualImpl.cpp
@@ -19,86 +19,85 @@
using namespace Aidge;
-TEST_CASE("[cpu/operator] Equal(forward)", "[Equal][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("Same dimensions") {
- 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> myInput1 = std::make_shared<Tensor>(dims);
- myInput1->setBackend("cpu");
- myInput1->setDataType(DataType::Float32);
- myInput1->zeros();
- std::shared_ptr<Tensor> myInput2 = std::make_shared<Tensor>(dims);
- myInput2->setBackend("cpu");
- myInput2->setDataType(DataType::Float32);
- myInput2->zeros();
- std::shared_ptr<Node> myEqual = Equal();
- auto op = std::static_pointer_cast<OperatorTensor>(myEqual -> getOperator());
- op->associateInput(0,myInput1);
- op->associateInput(1,myInput2);
- op->setDataType(DataType::Float32);
- op->setBackend("cpu");
- op->forwardDims();
-
- const auto outputDims = op->getOutput(0)->dims();
- REQUIRE(outputDims == dims);
+TEST_CASE("[cpu/operator] Equal(forwardDims)", "[Equal][CPU]") {
+ 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("Same dimensions") {
+ 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> myInput1 = std::make_shared<Tensor>(dims);
+ myInput1->setBackend("cpu");
+ myInput1->setDataType(DataType::Float32);
+ myInput1->zeros();
+ std::shared_ptr<Tensor> myInput2 = std::make_shared<Tensor>(dims);
+ myInput2->setBackend("cpu");
+ myInput2->setDataType(DataType::Float32);
+ myInput2->zeros();
+ std::shared_ptr<Node> myEqual = Equal();
+ auto op = std::static_pointer_cast<OperatorTensor>(myEqual -> getOperator());
+ op->associateInput(0,myInput1);
+ op->associateInput(1,myInput2);
+ op->setDataType(DataType::Float32);
+ op->setBackend("cpu");
+ op->forwardDims();
+
+ const auto outputDims = op->getOutput(0)->dims();
+ REQUIRE(outputDims == dims);
}
- SECTION("Broadcasting") {
- for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
- DimSize_t nbDims = nbDimsDist(gen);
- std::vector<DimSize_t> dims1(nbDims, 1);
- std::vector<DimSize_t> dims2(nbDims, 1);
- std::vector<DimSize_t> expectedOutDims;
- for (std::size_t i = 0; i < nbDims; i++) {
- DimSize_t dim = dimSizeDist(gen);
- if (boolDist(gen)) {
- dims1[i] = dim;
- }
- if (boolDist(gen)) {
- dims2[i] = dim;
- }
- expectedOutDims.push_back(std::max(dims1[i],dims2[i]));
+ }
+ SECTION("Broadcasting") {
+ for (std::uint16_t trial = 0; trial < NBTRIALS; ++trial) {
+ DimSize_t nbDims = nbDimsDist(gen);
+ std::vector<DimSize_t> dims1(nbDims, 1);
+ std::vector<DimSize_t> dims2(nbDims, 1);
+ std::vector<DimSize_t> expectedOutDims;
+ for (std::size_t i = 0; i < nbDims; i++) {
+ DimSize_t dim = dimSizeDist(gen);
+ if (boolDist(gen)) {
+ dims1[i] = dim;
+ }
+ if (boolDist(gen)) {
+ dims2[i] = dim;
}
+ expectedOutDims.push_back(std::max(dims1[i],dims2[i]));
+ }
- std::shared_ptr<Tensor> myInput1 = std::make_shared<Tensor>(dims1);
- myInput1->setBackend("cpu");
- myInput1->setDataType(DataType::Float32);
- myInput1->zeros();
- std::shared_ptr<Tensor> myInput2 = std::make_shared<Tensor>(dims2);
- myInput2->setBackend("cpu");
- myInput2->setDataType(DataType::Float32);
- myInput2->zeros();
- std::shared_ptr<Node> myEqual = Equal();
- auto op = std::static_pointer_cast<OperatorTensor>(myEqual -> getOperator());
- op->associateInput(0,myInput1);
- op->associateInput(1,myInput2);
- op->setDataType(DataType::Float32);
- op->setBackend("cpu");
-
- op->forwardDims();
-
- const auto outputDims = op->getOutput(0)->dims();
- REQUIRE(outputDims == expectedOutDims);
- }
+ std::shared_ptr<Tensor> myInput1 = std::make_shared<Tensor>(dims1);
+ myInput1->setBackend("cpu");
+ myInput1->setDataType(DataType::Float32);
+ myInput1->zeros();
+ std::shared_ptr<Tensor> myInput2 = std::make_shared<Tensor>(dims2);
+ myInput2->setBackend("cpu");
+ myInput2->setDataType(DataType::Float32);
+ myInput2->zeros();
+ std::shared_ptr<Node> myEqual = Equal();
+ auto op = std::static_pointer_cast<OperatorTensor>(myEqual -> getOperator());
+ op->associateInput(0,myInput1);
+ op->associateInput(1,myInput2);
+ op->setDataType(DataType::Float32);
+ op->setBackend("cpu");
+
+ op->forwardDims();
+
+ const auto outputDims = op->getOutput(0)->dims();
+ REQUIRE(outputDims == expectedOutDims);
}
}
+}
+TEST_CASE("[cpu/operator] Equal(forward)", "[Equal][CPU]") {
SECTION("Same size inputs") {
std::shared_ptr<Tensor> input1 = std::make_shared<Tensor>(Array4D<int,3,3,3,2> {
{ //