Welcome to tensor’s documentation!¶
tensor¶
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build/tests |
coverage |
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C++ |
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Python |
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This library provides a two main features:
A class for interacting with multidimensional arrays (For backend library uses BLAS/LAPACK libraries with fallback to own naive implementations).
Deep neural networks.
The design goal is to create a numpy/pytorch alike interface for interacting with multidimensional arrays packaged in a simple, relatively lightweight, library with limited external dependencies that could be used on platforms like android phones and microcontrollers.
How to use in your project¶
If you’re using cmake see tensor-example for example usage.
Usage of tensor/nn module¶
For example usage jump to nn-planar-data example
Usage of tensor module in embedded application¶
See this repository
Example usages of tensor module¶
Create multidimensional tensor:
// Create an array for storing bitmaps with variadic constructor
int constexpr width = 1024;
int constexpr height = 720;
int constexpr channels = 3;
ts::Tensor<int, 3> image(width, height, channels);
image.shape(); // std::array{1024, 720, 3});
image.data_size(); // 1024 * 720 * 3 = 2211840
Multiply matrices:
// Construct 2D arrays via std::initializer_list
using Matrix = ts::Tensor<float, 2>;
Matrix A = {
{3, 1, 3},
{1, 5, 9},
};
Matrix B = {
{3, 1},
{1, 5},
{2, 6}
};
// Multiply via free function
Matrix C = ts::dot(A, B);
// C =
// / 16 26 \
// 26 80 /
Contents:
The Basics