I recently watched a video which inspired me to write my own neural network system, and I wanted to have the amount of nodes in the network be adjustable.
At first I achieved this at runtime by parsing an array of the numbers of nodes but I was wondering if I could do this at compile time instead. Here's an example of the kind of thing I was hoping to accomplish.
template<int FirstNodes, int SecondNodes, int... OtherNodes>
class Net
{
tuple<Eigen::Matrix<float, FirstNodes, SecondNodes>, ...> m_weights;
// More matricies with the values from the OtherNodes
};
As a more detailed example, Net<784, 16, 16, 10> n;
n.m_weight should have type
tuple<Eigen::Matrix<float, 784, 16>,
Eigen::Matrix<float, 16, 16>,
Eigen::Matrix<float, 16, 10>>
From what I know about C++ and constexpr, this should be possible.
I should add that I was able to do
template<int FirstNodes, int SecondNodes, int... OtherNodes>
class Net
{
public:
Net()
{
auto nodes = {FirstNodes, SecondNodes, OtherNodes...};
auto i = nodes.begin();
do
{
// Eigen::Matrix<float, Dynamic, Dynamic>
Eigen::MatrixXf m(*(i++), *i);
} while (i+1 != nodes.end());
}
};
But then I'm just using dynamic matricies again and that isn't what I was hoping for.
Any advice or working examples would be greatly appreciated.
m(*(i++), *i)
invokes undefined behavior up to c++14, unspecified in c++17 – Wench