[Add] broadcasting for Arithmetic Operators

This merge request is dedicated to enabling broadcasting on binary operators (Add, Mul, Div, Sub, Pow). The expected behaviour is the same as numpy

Here are examples of supported broadcasting

Tensor_A shape	3	2	1	3
Tensor_B shape	1	2	4	3
Output shape	3	2	4	3

Tensor_A shape	3	2	1	3
Tensor_C shape				3
Output shape	3	2	1	3

src/operator/ArithmeticOperator.cpp

@@ -21,7 +21,7 @@
 
 void Aidge::ArithmeticOperator::associateInput(const Aidge::IOIndex_t inputIdx, const std::shared_ptr<Aidge::Data>& data) {
     if (inputIdx >= 2) {
-        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has %hu inputs", type().c_str(),2);
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has 2 inputs", type().c_str());
     }
     if (strcmp((data)->type(), Tensor::Type) != 0) {
         AIDGE_THROW_OR_ABORT(std::runtime_error, "Input data must be of Tensor type");
@@ -55,7 +55,7 @@ void Aidge::ArithmeticOperator::setInput(const Aidge::IOIndex_t inputIdx, std::s
 
 const std::shared_ptr<Aidge::Tensor>& Aidge::ArithmeticOperator::getInput(const Aidge::IOIndex_t inputIdx) const {
     if (inputIdx >= nbInputs()) {
-        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has %hu inputs", type().c_str(), nbInputs());
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has 2 inputs", type().c_str());
     }
     return mInputs[inputIdx];
 }
@@ -65,7 +65,7 @@ void Aidge::ArithmeticOperator::setOutput(const Aidge::IOIndex_t outputIdx, cons
         AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator only accepts Tensors as inputs", type().c_str());
     }
     if (outputIdx >= nbOutputs()) {
-        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has %hu outputs", type().c_str(), nbOutputs());
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has 1 outputs", type().c_str());
     }
     *mOutputs[outputIdx] = *std::dynamic_pointer_cast<Tensor>(data);
 }
@@ -75,14 +75,14 @@ void Aidge::ArithmeticOperator::setOutput(const Aidge::IOIndex_t outputIdx, std:
         AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator only accepts Tensors as inputs", type().c_str());
     }
     if (outputIdx >= nbOutputs()) {
-        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has %hu outputs", type().c_str(), nbOutputs());
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has 1 output", type().c_str());
     }
     *mOutputs[outputIdx] = std::move(*std::dynamic_pointer_cast<Tensor>(data));
 }
 
 const std::shared_ptr<Aidge::Tensor>& Aidge::ArithmeticOperator::getOutput(const Aidge::IOIndex_t outputIdx) const {
     if (outputIdx >= nbOutputs()) {
-        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has %hu outputs", type().c_str(), nbOutputs());
+        AIDGE_THROW_OR_ABORT(std::runtime_error, "%s Operator has 1 output", type().c_str());
     }
     return mOutputs[outputIdx];
 }