Improved error messages

python_binding/scheduler/pybind_Scheduler.cpp

@@ -25,6 +25,7 @@ void init_Scheduler(py::module& m){
     .def(py::init<std::shared_ptr<GraphView>&>(), py::arg("graph_view"))
     .def("graph_view", &Scheduler::graphView)
     .def("save_scheduling_diagram", &Scheduler::saveSchedulingDiagram, py::arg("file_name"))
+    .def("save_static_scheduling_diagram", &Scheduler::saveStaticSchedulingDiagram, py::arg("file_name"))
     .def("resetScheduling", &Scheduler::resetScheduling)
     .def("generate_scheduling", &Scheduler::generateScheduling)
     .def("get_static_scheduling", &Scheduler::getStaticScheduling, py::arg("step") = 0)

src/operator/Conv.cpp

@@ -43,16 +43,17 @@ bool Aidge::Conv_Op<DIM>::forwardDims(bool /*allowDataDependency*/) {
     if (inputsAssociated()) {
         // first check weight since it defines inChannels and outChannels
         AIDGE_ASSERT((getInput(1)->nbDims() == (DIM+2)),
-                    "Wrong weight Tensor dimension: {} for Conv{}D operator.", getInput(1)->nbDims(), DIM);
+                    "Wrong weight Tensor dimension: {} for Conv{}D operator. Expected number of dimensions is {}.", getInput(1)->nbDims(), DIM, DIM+2);
         // check data
         AIDGE_ASSERT((getInput(0)->nbDims() == (DIM+2)) &&
                     (getInput(0)->template dims<DIM+2>()[1] == inChannels()),
-                    "Wrong input size for Conv operator.");
+                    "Wrong input size ({}) for Conv operator. Expected dims are [x, {}, {}].", getInput(0)->dims(), inChannels(), fmt::join(std::vector<std::string>(DIM, "x"), ", "));
         // check optional bias
         if(getInput(2))
             AIDGE_ASSERT((getInput(2)->nbDims() == (1)) &&
                     (getInput(2)->template dims<1>()[0] == outChannels()),
-                    "Wrong bias size for Conv operator.");
+                    "Wrong bias size ({}) for Conv operator. Expected dims are [{}].", getInput(2)->dims(), outChannels());
+
         std::array<DimSize_t, DIM + 2> outputDims{};
         const std::array<DimSize_t, DIM + 2> inputDims(getInput(0)->template dims<DIM+2>());
 

src/operator/ConvDepthWise.cpp

@@ -44,16 +44,17 @@ bool Aidge::ConvDepthWise_Op<DIM>::forwardDims(bool /*allowDataDependency*/) {
     if (inputsAssociated()) {
         // first check weight since it defines nbChannels
         AIDGE_ASSERT((getInput(1)->nbDims() == (DIM+2)),
-                    "Wrong weight Tensor dimension: {} for Conv{}D operator.", getInput(1)->nbDims(), DIM);
+                    "Wrong weight Tensor dimension: {} for ConvDepthWise{}D operator. Expected number of dimensions is {}.", getInput(1)->nbDims(), DIM, DIM+2);
         // check data
         AIDGE_ASSERT((getInput(0)->nbDims() == (DIM+2)) &&
                     (getInput(0)->template dims<DIM+2>()[1] == nbChannels()),
-                    "Wrong input size for Conv operator.");
+                    "Wrong input size ({}) for ConvDepthWise operator. Expected dims are [x, {}, {}].", getInput(0)->dims(), nbChannels(), fmt::join(std::vector<std::string>(DIM, "x"), ", "));
         // check optional bias
         if(getInput(2))
             AIDGE_ASSERT((getInput(2)->nbDims() == (1)) &&
                     (getInput(2)->template dims<1>()[0] == nbChannels()),
-                    "Wrong bias size for Conv operator.");
+                    "Wrong bias size ({}) for ConvDepthWise operator. Expected dims are [{}].", getInput(2)->dims(), nbChannels());
+
         std::array<DimSize_t, DIM + 2> outputDims = {};
         const std::array<DimSize_t, DIM + 2> inputDims(getInput(0)->template dims<DIM+2>());