Remove the outChannels attribute from FC_Op as it is only used for Weight and Bias creation

include/aidge/operator/FC.hpp

@@ -24,26 +24,24 @@
 #include "aidge/utils/Registrar.hpp"
 
 namespace Aidge {
-enum class FCAttr { OutChannels, NoBias };
+enum class FCAttr { NoBias };
 
 class FC_Op : public OperatorTensor,
               public Registrable<FC_Op,
                                  std::string,
                                  std::shared_ptr<OperatorImpl>(const FC_Op &)>,
-              public StaticAttributes<FCAttr, DimSize_t, bool> {
+              public StaticAttributes<FCAttr, bool> {
 public:
     static const std::string Type;
 
     FC_Op() = delete;
 
-    using Attributes_ = StaticAttributes<FCAttr, DimSize_t, bool>;
+    using Attributes_ = StaticAttributes<FCAttr, bool>;
     template <FCAttr e> using attr = typename Attributes_::template attr<e>;
 
-    FC_Op(DimSize_t out_channels, bool noBias)
+    FC_Op(bool noBias)
     : OperatorTensor(Type, 1, 2, 1),
-      Attributes_(
-        attr<FCAttr::OutChannels>(out_channels),
-        attr<FCAttr::NoBias>(noBias))
+      Attributes_(attr<FCAttr::NoBias>(noBias))
     {}
 
     /**
@@ -83,9 +81,9 @@ public:
     }
 };
 
-inline std::shared_ptr<Node> FC(DimSize_t inChannels, DimSize_t outChannels, bool noBias = false, const std::string& name = "") {
+inline std::shared_ptr<Node> FC(const DimSize_t inChannels, const DimSize_t outChannels, bool noBias = false, const std::string& name = "") {
     // FIXME: properly handle default w&b initialization in every cases
-    auto fc = std::make_shared<Node>(std::make_shared<FC_Op>(outChannels, noBias), name);
+    auto fc = std::make_shared<Node>(std::make_shared<FC_Op>(noBias), name);
     addProducer(fc, 1, {outChannels, inChannels}, "w");
     addProducer(fc, 2, {(noBias ? 0 : outChannels)}, "b"); // already sets bias dims
     return fc;
@@ -94,8 +92,7 @@ inline std::shared_ptr<Node> FC(DimSize_t inChannels, DimSize_t outChannels, boo
 
 namespace {
 template <>
-const char *const EnumStrings<Aidge::FCAttr>::data[] = {"OutChannels",
-                                                        "NoBias"};
+const char *const EnumStrings<Aidge::FCAttr>::data[] = {"NoBias"};
 }
 
 #endif /* AIDGE_CORE_OPERATOR_FC_H_ */

src/operator/FC.cpp

@@ -45,8 +45,31 @@ bool Aidge::FC_Op::forwardDims(bool /*allowDataDependency*/) {
         associated &= !(getInput(i)->empty());
     }
     if (associated) {
+        // first check weight since it defines inChannels and outChannels
+        AIDGE_ASSERT((getInput(1)->nbDims() == 2),
+                    "Wrong weight Tensor dimension: {} for FC operator (should have 2 dimensions).", getInput(1)->nbDims());
+        const DimSize_t outChannels = getInput(1)->template dims<2>()[0];
+        const DimSize_t inChannels = getInput(1)->template dims<2>()[1];
+        // check data
+        const std::vector<DimSize_t>& inputDims = getInput(0)->dims();
+        if (getInput(0)->nbDims() == 1) {
+            AIDGE_ASSERT(inputDims[0] == inChannels,
+                "Wrong number of input features for input data ({}), expected {}",
+                inputDims[0], inChannels);
+        } else {
+            AIDGE_ASSERT(getInput(0)->nbDims() > 1, "FC input data must have at least one dimension");
+            const DimSize_t nbInputFeatures = std::accumulate(inputDims.cbegin() + 1, inputDims.cend(), DimSize_t(1), std::multiplies<DimSize_t>());
+            AIDGE_ASSERT(nbInputFeatures == inChannels,
+                    "Wrong number of input features for input data ({}), expected {}",
+                    nbInputFeatures, inChannels);
+        }
+        // check optional bias
+        if(!this->template getAttr<FCAttr::NoBias>())
+            AIDGE_ASSERT((getInput(2)->nbDims() == 1) &&
+                    (getInput(2)->template dims<1>()[0] == outChannels),
+                    "Wrong bias size for FC operator.");
         // <batch, OutChannels>
-        mOutputs[0]->resize({getInput(0)->dims()[0], this->template getAttr<FCAttr::OutChannels>()});
+        mOutputs[0]->resize({getInput(0)->dims()[0], outChannels});
     }
 
     return associated;