Removed mSizeM1 which is not that usefull

include/aidge/data/Tensor.hpp

@@ -40,8 +40,7 @@ class Tensor : public Data,
     std::shared_ptr<Tensor> mGrad; /** Pointer to the associated gradient Tensor instance. */
 
     // Cached data
-    std::size_t mSize;    /** Number of elements in the Tensor. */
-    std::size_t mSizeM1;  /** Number of elements in the N-1 first dimensions */
+    std::size_t mSize = 0;    /** Number of elements in the Tensor. */
 
    public:
     static constexpr const char *Type = "Tensor";
@@ -52,10 +51,7 @@ class Tensor : public Data,
      */
     Tensor(DataType dataType = DataType::Float32)
         : Data(Type),
-          mDataType(dataType),
-          mDims({}),
-          mSize(0),
-          mSizeM1(0)
+          mDataType(dataType)
     {
         // ctor
     }
@@ -68,8 +64,7 @@ class Tensor : public Data,
         : Data(Type),
           mDataType(otherTensor.mDataType),
           mDims(otherTensor.mDims),
-          mSize(otherTensor.mSize),
-          mSizeM1(otherTensor.mSizeM1)
+          mSize(otherTensor.mSize)
     {
         if (otherTensor.hasImpl()) {
             mImpl = Registrar<Tensor>::create({otherTensor.mImpl->backend(), dataType()})(*this);
@@ -90,8 +85,7 @@ class Tensor : public Data,
           mDataType(NativeType<T>::type),
           mDims({SIZE_0}),
           mImpl(Registrar<Tensor>::create({"cpu", NativeType<T>::type})(*this)),
-          mSize(SIZE_0),
-          mSizeM1(SIZE_0) {
+          mSize(SIZE_0) {
         mImpl->copyFromHost(&arr.data[0], SIZE_0);
     }
 
@@ -117,8 +111,7 @@ class Tensor : public Data,
           mDataType(NativeType<T>::type),
           mDims({SIZE_0, SIZE_1}),
           mImpl(Registrar<Tensor>::create({"cpu", NativeType<T>::type})(*this)),
-          mSize(SIZE_0 * SIZE_1),
-          mSizeM1(SIZE_1) {
+          mSize(SIZE_0 * SIZE_1) {
         mImpl->copyFromHost(&arr.data[0][0], SIZE_0 * SIZE_1);
     }
 
@@ -145,8 +138,7 @@ class Tensor : public Data,
           mDataType(NativeType<T>::type),
           mDims({SIZE_0, SIZE_1, SIZE_2}),
           mImpl(Registrar<Tensor>::create({"cpu", NativeType<T>::type})(*this)),
-          mSize(SIZE_0 * SIZE_1 * SIZE_2),
-          mSizeM1(SIZE_1 * SIZE_2) {
+          mSize(SIZE_0 * SIZE_1 * SIZE_2) {
         mImpl->copyFromHost(&arr.data[0][0][0], SIZE_0 * SIZE_1 * SIZE_2);
     }
 
@@ -174,8 +166,7 @@ class Tensor : public Data,
           mDataType(NativeType<T>::type),
           mDims({SIZE_0, SIZE_1, SIZE_2, SIZE_3}),
           mImpl(Registrar<Tensor>::create({"cpu", NativeType<T>::type})(*this)),
-          mSize(SIZE_0 * SIZE_1 * SIZE_2 * SIZE_3),
-          mSizeM1(SIZE_1 * SIZE_2 * SIZE_3) {
+          mSize(SIZE_0 * SIZE_1 * SIZE_2 * SIZE_3) {
         mImpl->copyFromHost(&arr.data[0][0][0][0], SIZE_0 * SIZE_1 * SIZE_2 * SIZE_3);
     }
 
@@ -334,12 +325,6 @@ class Tensor : public Data,
      */
     constexpr std::size_t size() const { return mSize; }
 
-    /**
-     * @brief Get the number of elements in the N-1 dimensions of the Tensor object.
-     * @return constexpr std::size_t
-     */
-    constexpr std::size_t sizeM1() const { return mSizeM1; }
-
     /**
      * @brief Change the dimensions of the Tensor object according to the given argument.
      * If the overall size is not changed (meaning we actually only performed a 
@@ -673,17 +658,10 @@ private:
     ///\bug not protected against overflow
     std::size_t computeSize() {
         if (mDims.empty()) {
-            mSizeM1 = DimSize_t(0);
             mSize = DimSize_t(0);
         }
-        else if (mDims.size() == 1)
-        {
-            mSizeM1 = mDims[0];
-            mSize = mDims[0];
-        }
         else {
-            mSizeM1 = std::accumulate(++mDims.begin(),mDims.end(), DimSize_t(1), std::multiplies<DimSize_t>());
-            mSize = static_cast<std::size_t>(mSizeM1 * mDims[0]);
+            mSize = std::accumulate(mDims.begin(), mDims.end(), DimSize_t(1), std::multiplies<DimSize_t>());
         }
 
         return mSize;