A C++ Tensor library that can be used to work with machine learning or deep learning project.
Build your own neural network models with this library.
You need to clone repository by using Git
You need to install Tensor-Array with CMake
git clone https://github.com/Tensor-Array/Tensor-Array.git cd Tensor-Array mkdir build cd build cmake .. cmake --build . cmake --install . cd ..
We created a template struct that named TensorArray. That struct is a multi-dimensional array wrapper.
#include <tensor-array/core/tensorbase.hh> using namespace tensor_array::value; int main() { TensorArray<float, 4, 4> example_tensor_array = {{ {{ 1, 2, 3, 4 }}, {{ 5, 6, 7, 8 }}, {{ 9, 10, 11, 12 }}, {{ 13, 14, 15, 16 }}, }}; return 0; }
That code is wrapping for:
int main() { float example_tensor_array[4][4] = { { 1, 2, 3, 4 }, { 5, 6, 7, 8 }, { 9, 10, 11, 12 }, { 13, 14, 15, 16 }, }; return 0; }
The Tensor class is a storage that store value and calculate the tensor.
The Tensor::calc_grad() method can do automatic differentiation.
The Tensor::get_grad() method can get the gradient after call Tensor::calc_grad().
#include <iostream> #include <tensor-array/core/tensor.hh> using namespace std; using namespace tensor_array::value; int main() { TensorArray<float, 4, 4> example_tensor_array = {{ {{ 1, 2, 3, 4 }}, {{ 5, 6, 7, 8 }}, {{ 9, 10, 11, 12 }}, {{ 13, 14, 15, 16 }}, }}; TensorArray<float> example_tensor_array_scalar = {100}; Tensor example_tensor_1(example_tensor_array); Tensor example_tensor_2(example_tensor_array_scalar); Tensor example_tensor_sum = example_tensor_1 + example_tensor_2; cout << example_tensor_sum << endl; example_tensor_sum.calc_grad(); cout << example_tensor_1.get_grad() << endl; cout << example_tensor_2.get_grad() << endl; return 0; }