Improved error messages

Improved error messages in TensorImpl.

include/aidge/backend/opencv/data/TensorImpl.hpp

@@ -88,8 +88,8 @@ public:
         const T* srcT = static_cast<const T *>(src);
         T* dstT = static_cast<T *>(rawPtr(offset));
 
-        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
-        AIDGE_ASSERT(dstT < srcT || dstT >= srcT + length, "overlapping copy is not supported");
+        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "TensorImpl_opencv<{}>::copy(): copy length ({}) is above capacity ({})", typeid(T).name(), length, mNbElts);
+        AIDGE_ASSERT(dstT < srcT || dstT >= srcT + length, "TensorImpl_opencv<{}>::copy(): overlapping copy is not supported", typeid(T).name());
         std::copy(srcT, srcT + length, dstT);
 
     }
@@ -100,7 +100,7 @@ public:
         }
         
         T* dstT = static_cast<T *>(rawPtr(offset));
-        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
+        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "TensorImpl_opencv<{}>::copyCast(): copy length ({}) is above capacity ({})", typeid(T).name(), length, mNbElts);
         switch (srcDt)
         {
             case DataType::Float64:
@@ -148,15 +148,15 @@ public:
                         dstT);
                 break;
             default:
-                AIDGE_THROW_OR_ABORT(std::runtime_error, "Unsupported data type.");
+                AIDGE_THROW_OR_ABORT(std::runtime_error, "TensorImpl_opencv<{}>::copyCast(): unsupported data type {}.", typeid(T).name(), srcDt);
                 break;
         }
     }
 
 
     void copyFromDevice(const void *src, const std::pair<std::string, DeviceIdx_t>& device, NbElts_t length, NbElts_t offset = 0) override final {
-        AIDGE_ASSERT(device.first == Backend, "backend must match");
-        AIDGE_ASSERT(device.second == 0, "device cannot be != 0 for CPU backend");
+        AIDGE_ASSERT(device.first == Backend, "TensorImpl_opencv<{}>::copyFromDevice(): backend must match", typeid(T).name());
+        AIDGE_ASSERT(device.second == 0, "TensorImpl_opencv<{}>::copyFromDevice(): device ({}) cannot be != 0 for CPU backend", typeid(T).name(), device.second);
         copy(src, length, offset);
     }
 
@@ -166,7 +166,7 @@ public:
 
     void copyToHost(void *dst, NbElts_t length, NbElts_t offset = 0) const override final {
         const T* src = static_cast<const T*>(rawPtr(offset));
-        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "copy length is above capacity");
+        AIDGE_ASSERT(length <= (mData.total() * mData.channels()) || length <= mNbElts, "TensorImpl_opencv<{}>::copyToHost(): copy length ({}) is above capacity ({})", typeid(T).name(), length, mNbElts);
         std::copy(src, src + length, static_cast<T *>(dst));
     }
 
@@ -176,7 +176,7 @@ public:
     };
 
     const void *rawPtr(NbElts_t offset = 0) const override final {
-        AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "accessing uninitialized const rawPtr");
+        AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "TensorImpl_opencv<{}>::rawPtr(): accessing uninitialized const rawPtr", typeid(T).name());
         return (mData.ptr<T>() + offset);
     };
 
@@ -186,8 +186,8 @@ public:
     };
 
     const void *hostPtr(NbElts_t offset = 0) const override {
-        AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "accessing uninitialized const hostPtr");
-        AIDGE_ASSERT(mData.isContinuous(), "CV Matrix not continuous");
+        AIDGE_ASSERT((mData.total() * mData.channels()) >= mNbElts, "TensorImpl_opencv<{}>::hostPtr(): accessing uninitialized const hostPtr", typeid(T).name());
+        AIDGE_ASSERT(mData.isContinuous(), "TensorImpl_opencv<{}>::hostPtr(): CV Matrix not continuous", typeid(T).name());
         return (mData.ptr<T>() + offset);
     };
 
@@ -201,7 +201,7 @@ private:
   void lazyInit() {
     if ((mData.total() * mData.channels()) < mNbElts) {
         // Need more data, a re-allocation will occur
-        AIDGE_ASSERT(mData.empty() , "trying to enlarge non-owned data");
+        AIDGE_ASSERT(mData.empty(), "TensorImpl_opencv<{}>: trying to enlarge non-owned data", typeid(T).name());
 
         if (mDims.size() < 3) {
             mData = cv::Mat(((mDims.size() > 1) ? static_cast<int>(mDims[0])