asserts added for null imputs

python_binding/operator/pybind_Resize.cpp

@@ -24,6 +24,6 @@ void init_Resize(py::module& m) {
 
     declare_registrable<Resize_Op>(m, "ResizeOp");
 
-    m.def("Resize", &Resize, py::arg("nb_input_dims"), py::arg("no_roi"), py::arg("no_scales"), py::arg("no_sizes"), py::arg("name") = "");
+    m.def("Resize", &Resize, py::arg("name") = "");
 }
 }  // namespace Aidge

src/operator/Resize.cpp

@@ -53,26 +53,23 @@ bool Aidge::Resize_Op::forwardDims(bool allowDataDependency) {
         return false;
     }
 
-    if (getInput(1) && !getInput(1)->empty()) {
-        AIDGE_THROW_OR_ABORT(std::runtime_error, "ROI input is not supported");
-        return false;
-    }
+    bool input1ROIPresent           = getInput(1) && !getInput(1)->empty();
+    bool input2ScalesPresent        = getInput(2) && !getInput(2)->empty();
+    bool input3SizesPresent         = getInput(3) && !getInput(3)->empty();
 
-    if (getInput(2) && !getInput(2)->empty())  {
+    if (input1ROIPresent) {
 
-        /*
-         fmt::print("Condition scales: Input#0 and Input#2 must be provided and must have the same dimension,\
-          while Inputs#1 and #3 must not be provided.\n"); 
-        */
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "Input #1 (ROI) is given and it is not supported.");
+
+    } else if (input2ScalesPresent)  {
 
         if (!allowDataDependency) {
-            Log::warn("Resize_Op: unable to forwardDims() because output dims are data dependent\
-             on input#0 and input#2");
+            Log::warn("Resize_Op: cannot execute forwardDims() as the output dimensions depend on the input #2");
             return false;
         }
 
         AIDGE_ASSERT(getInput(0)->nbDims() ==  getInput(2)->size(),\
-             "input tensor and Scales must have the same dimensions.");
+             "input #0 and input #2 (Scales) must have the same dimensions.");
     
         std::vector<DimSize_t>      outDims = getInput(0)->dims();
         const std::vector<DimSize_t> inDims = getInput(0)->dims();
@@ -83,26 +80,20 @@ bool Aidge::Resize_Op::forwardDims(bool allowDataDependency) {
         for (std::size_t dim=0; dim < getInput(2)->size(); ++dim) {
             outDims[dim] = inDims[dim]*static_cast<int64_t*>(scales.getImpl()->hostPtr())[dim];
         }
+
         mOutputs[0]->resize(outDims);
 
         return true;
-    }
-
-    if (getInput(3) && !getInput(3)->empty())  {
 
-        /*
-         fmt::print("Condition sizes: Input#0 and Input#3 must be provided and must have the same dimension,\
-          while Inputs#1 and #2 must not be provided.\n"); 
-        */
+    } else if (input3SizesPresent) {
 
         if (!allowDataDependency) {
-            Log::warn("Resize_Op: unable to forwardDims() because output dims are data dependent\
-             on input#0 and input#3)");
+            Log::warn("Resize_Op: cannot execute forwardDims() as the output dimensions depend on the input #3");
             return false;
         }
 
         AIDGE_ASSERT(getInput(0)->nbDims() ==  getInput(3)->size(),\
-             "input tensor and Sizes must have the same dimensions.");       
+             "input #0 and input #3 (Sizes) must have the same dimensions.");
         
         std::vector<DimSize_t> outDims = getInput(0)->dims();
 
@@ -112,12 +103,15 @@ bool Aidge::Resize_Op::forwardDims(bool allowDataDependency) {
         for (std::size_t dim=0; dim < getInput(3)->size(); ++dim) {            
             outDims[dim] = static_cast<int64_t*>(sizes.getImpl()->hostPtr())[dim];
         }
+        
         mOutputs[0]->resize(outDims);
         
         return true;
+    } else {
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "Error: Either Input #2 or Input #3 must be present.");
     }
 
-    return false;
+    return false; 
 }
 
 void Aidge::Resize_Op::setBackend(const std::string& name, Aidge::DeviceIdx_t device) {