Required Support and Test for Multibroadcasting added.

Author: Neel-Shah-29

tmva/sofie/inc/TMVA/ROperator_BasicBinary.hxx

@@ -83,11 +83,17 @@ public:
       auto shapeX2 = model.GetTensorShape(fNX2);
       // assume same shape X1 and X2
       if (shapeX1 != shapeX2) {
-         std::string msg = "TMVA SOFIE Binary Op: Support only inputs with same shape, shape 1 is " +
-                           ConvertShapeToString(shapeX1) + "shape 2 is " + ConvertShapeToString(shapeX2);
-         throw std::runtime_error(msg);
+         fShape = UTILITY::Multidirectional_broadcast(shapeX1,shapeX2);
+         size_t length1 = ConvertShapeToLength(shapeX1);
+         size_t length2 = ConvertShapeToLength(shapeX2);
+         size_t output_length = ConvertShapeToLength(fShape);
+         if(length1 != length2 || length1 != output_length){
+            throw std::runtime_error(std::string("TMVA SOFIE Binary Op does not support input tensors with different lengths. The output tensor should also have the same length as the input tensors."));
+         }
       }
-      fShape = shapeX1;
+      else if(shapeX1 == shapeX2){
+         fShape = shapeX1;
+      }   
       model.AddIntermediateTensor(fNY, model.GetTensorType(fNX1), fShape);
    }
 

tmva/sofie/test/TestCustomModelsFromONNX.cxx

@@ -18,6 +18,9 @@
 #include "Add_FromONNX.hxx"
 #include "input_models/references/Add.ref.hxx"
 
+#include "Add_broadcast_FromONNX.hxx"
+#include "input_models/references/Add_broadcast.ref.hxx"
+
 #include "Mul_FromONNX.hxx"
 #include "input_models/references/Mul.ref.hxx"
 
@@ -172,6 +175,33 @@ TEST(ONNX, Sub)
       }
    }
 
+TEST(ONNX, Add_broadcast)
+   {
+      constexpr float TOLERANCE = DEFAULT_TOLERANCE;
+
+      // Preparing the standard input
+      std::vector<float> input1({
+         1, 2, 3,
+         3, 4, 5
+      });
+      std::vector<float> input2({
+         5, 6, 7,
+         8, 9, 10
+      });
+      TMVA_SOFIE_Add_broadcast::Session s("Add_broadcast_FromONNX.dat");
+
+      std::vector<float> output = s.infer(input2.data(),input1.data());
+
+      // Checking output size
+      EXPECT_EQ(output.size(), sizeof(Add_broadcast_ExpectedOutput::outputs) / sizeof(float));
+
+      float *correct = Add_broadcast_ExpectedOutput::outputs;
+
+      // Checking every output value, one by one
+      for (size_t i = 0; i < output.size(); ++i) {
+         EXPECT_LE(std::abs(output[i] - correct[i]), TOLERANCE);
+      }
+   }
 
 TEST(ONNX, Add)
    {

tmva/sofie/test/input_models/Add_broadcast.onnx

@@ -0,0 +1,18 @@
+pytorch1.11.0:�

+)
+onnx::Add_0
+onnx::Add_1
2Add_0"Addtorch-jit-exportZ!
+onnx::Add_0
+

+

+
+Z
+onnx::Add_1
+

+
+b
+
2
+

+

+
+B	

tmva/sofie/test/input_models/references/Add_broadcast.ref.hxx

@@ -0,0 +1,6 @@
+namespace Add_broadcast_ExpectedOutput{
+	float outputs[] = {
+            6,  8, 10,
+            11, 13, 15
+	};
+} // namespace Add_ExpectedOutput