I'm currently writing a typesafe compiletime-enabled tensor class, which boils down to
template<typename T, int... Sizes> struct tensor { T elements[(Sizes * ...)]; auto ptr() {return elements;} auto size() {return (Sizes * ...);} using value_type = T; }; I wanted to write a method that allows to create a tensor with arrays as an expression, like that:
make_tensor({1,2,3,4}) or make_tensor({{1,2},{3,4}}), giving a vector and a matrix. my make_tensor function currently looks like this:
template<template<typename, int...> class Fill, typename Type, int... Sizes> struct array_to_index { using type = Fill<Type, Sizes...>; }; template<template<typename, int...> class Fill, typename Type, int Size, int... Sizes> struct array_to_index<Fill, Type[Size], Sizes...> { using type = typename array_to_index<Fill, Type, Sizes..., Size>::type; }; template<template<typename, int...> class Fill, typename Type> using array_to_index_t = typename array_to_index<Fill, Type>::type; template<typename Type, int Size> auto make_tensor(const Type (&arr)[Size]) { using tensor_t = array_to_index_t<tensor, Type[Size]>; tensor_t tensor; using ptr_t = const typename tensor_t::value_type *; for(int i = 0; i < tensor.size(); ++i) tensor.elements[i] = reinterpret_cast<ptr_t>(arr)[i]; return tensor; } I can call this with a multidimensional array if I assign it first, but the nice syntax doesn't work:
int main() { //auto matrix = make_tensor({{0,1},{2,3},{4,5}}); // doesn't work int arr[][2] = {{0,1},{2,3},{4,5}}; auto other = make_tensor(arr); // works assert(other.elements[3] == 3); } With what I gather from this Failed to deduce bounds from initializer for multi-dimensional arrays question, my approach won't work. Is there any other way this deduction is possible (e.g with initializer lists)?
