diff --git a/include/aidge/backend/TensorImpl.hpp b/include/aidge/backend/TensorImpl.hpp
index 8be15d1d8259ce606e410eb16bcd189ec0ff7b0e..d66f12dd02678d091b01d4fd41e50d8cb58ed17d 100644
--- a/include/aidge/backend/TensorImpl.hpp
+++ b/include/aidge/backend/TensorImpl.hpp
@@ -36,8 +36,8 @@ public:
/// @param length Nb of element to copy from the buffer
virtual void copy(Byte_t const *const src, NbElts_t length) = 0;
/// @deprecated see API V2
- /// @todo This function returns the address of a data allocated on the spot if it does
- /// not exists, which is undocumented. Is it a valid design. reconsider.
+ /// @todo This function returns the address of a data allocated on the spot if it
+ /// does not exists, which is undocumented. Is it a valid design. reconsider.
virtual Byte_t *rawPtr() = 0;
/// @brief Size of one scalar (in bytes)
inline std::size_t scalarSize() const noexcept
@@ -82,7 +82,8 @@ public:
/// @brief Returns a vector of the tensor in-memory dimensions.
/// @return Reference to a const vector of D sizes expressed in number of elements
/// along a dimension.<br>
- /// D is the number of dimensions of the tensor (thus equals getDimensions().size())
+ /// D is the number of dimensions of the tensor (thus equals
+ /// getDimensions().size())
inline std::vector<DimSize_t> const &getDimensions() const noexcept
{
return mvDimensions;
@@ -147,8 +148,8 @@ public:
std::size_t In = flatIdx;
// trick for reverse loop without index underflow
// when i is 1, (i--)>0 is true but i contains 0 on ouput
- // when i is 0, (i--)>0 is false leaving the loop, i has underflow but its value
- // is not used anymore
+ // when i is 0, (i--)>0 is false leaving the loop, i has underflow but its
+ // value is not used anymore
/// @todo implement it with synchronized reverse iterators
for (std::size_t i = mvDimensions.size(); (i--) > 0;)
{
@@ -160,7 +161,8 @@ public:
}
};
- /// @brief Get the linear index of the first Byte_t of the data at given coordinates
+ /// @brief Get the linear index of the first Byte_t of the data at given
+ /// coordinates
/// @param coordIdx coordinates of the desired data
/// @note The index is expressed in number of elements
/// @return Linear index of the first Byte_t of the data at given coordinates
@@ -172,7 +174,8 @@ public:
assert(
((coordIdx[i] - mvFirstDataCoordinates[i]) < mvDimensions[i])
&& (coordIdx[i] >= mvFirstDataCoordinates[i])
- && "Coordinates dimensions does not fit the dimensions of the tensor");
+ && "Coordinates dimensions does not fit the dimensions of the "
+ "tensor");
flatIdx += (coordIdx[i] * mvLayout[i]);
}
return flatIdx / mScalarSize;
@@ -181,8 +184,8 @@ public:
/// @brief Change TensorImpl dimensions
/// @note Current API does not change first data coordinates
/// @note Preexisting data are lost whatever dims value
- /// @note If new dimensions are not large enough to hold the Tensors that referenced
- /// this implementation is undefined behavior
+ /// @note If new dimensions are not large enough to hold the Tensors that
+ /// referenced this implementation is undefined behavior
/// @param dims New dimensions
/// @todo first data coordinates should be redefined also
virtual void resize(const std::vector<DimSize_t> &dims) = 0;
@@ -193,8 +196,8 @@ private:
/// @brief Tensor whose the TensorImpl manage the memory
/// @deprecated Future version may be referenced by several Tensors
/// @todo edesign must be
- /// considered so that a TensorImpl either does not know of its user or it has a list
- /// of all of them
+ /// considered so that a TensorImpl either does not know of its user or it has a
+ /// list of all of them
Tensor const &mTensor;
/// @brief Number of stored data
/// @details mNbElts == prod(mDimensions)/mScalarSize
@@ -205,8 +208,8 @@ private:
/// @todo Implement overflow protection as mNbElts*mScalarSize must fit into a
/// std::size_t
std::size_t mScalarSize = 0;
- /// @brief Actual in-memory tensor dimensions expressed as number of elements along
- /// each dimension
+ /// @brief Actual in-memory tensor dimensions expressed as number of elements
+ /// along each dimension
std::vector<DimSize_t> mvDimensions;
/// @brief memory tensor layout
/// @details Let ptr be the memory address of a data of logical coordinates
@@ -223,7 +226,8 @@ private:
/// the actual data pointer type, all the data can be traversed by simple
/// pointer arithmetic.
/// @deprecated Such storage is meaningless for most backend except CPU.
- /// @todo If needed, replace by a _any storing a backend-dependant handle on storage.
+ /// @todo If needed, replace by a _any storing a backend-dependant handle on
+ /// storage.
Byte_t *mStorage = nullptr;
/// @brief Logical coordinates of the data stored at mStorage.
std::vector<Coord_t> mvFirstDataCoordinates;
@@ -305,8 +309,9 @@ protected:
// supposedly more efficient reverse_iterator based solution but much less
// readable auto pLayout = std::rbegin(mvLayout); auto pFinish =
- // std::rend(mvLayout); auto pDimension = std::rbegin(mvDimensions); *pLayout =
- // mScalarSize; auto pPrevLayout = pLayout; for (++pLayout; pLayout != pFinish;
+ // std::rend(mvLayout); auto pDimension = std::rbegin(mvDimensions); *pLayout
+ // = mScalarSize; auto pPrevLayout = pLayout; for (++pLayout; pLayout !=
+ // pFinish;
// ++pLayout, ++pDimension, ++pPrevLayout)
// {
// *pLayout = (*pPrevLayout) * (*pDimension);
diff --git a/include/aidge/data/Tensor.hpp b/include/aidge/data/Tensor.hpp
index 13cd605290a2f83e309b93e0686af3493ae201d0..de02654d863a28fe933aff9fb194a01321861db5 100644
--- a/include/aidge/data/Tensor.hpp
+++ b/include/aidge/data/Tensor.hpp
@@ -112,10 +112,9 @@ public:
/**
* @brief Construct a new Tensor object copied from another one.
* @param otherTensor Tensor to copy
- * @details Copy only the active area, without existing context and using the same
- * backend as the input tensor.
+ * @details Performs a deep copy of all the data in the source tensor, using the same
+ * backend.
*/
-
Tensor(const Tensor &otherTensor);
/**