Deep Learning Algorithm Implementations 1.0.0
C++ implementations of fundamental deep learning algorithms
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matrix.cpp File Reference
#include "../include/utils/matrix.hpp"
#include <xtensor-blas/xlinalg.hpp>
#include <xtensor/containers/xadapt.hpp>
Include dependency graph for matrix.cpp:

Go to the source code of this file.

Namespaces

namespace  utils
 

Functions

template std::ostream & utils::operator<<< float > (std::ostream &, const Matrix< float > &)
 
template std::ostream & utils::operator<<< double > (std::ostream &, const Matrix< double > &)
 
template Matrix< float > utils::dot< float > (const Matrix< float > &, const Matrix< float > &)
 
template Matrix< double > utils::dot< double > (const Matrix< double > &, const Matrix< double > &)
 
template float utils::sum< float > (const Matrix< float > &)
 
template double utils::sum< double > (const Matrix< double > &)
 
template float utils::mean< float > (const Matrix< float > &)
 
template double utils::mean< double > (const Matrix< double > &)
 
Non-member Functions
template<typename T >
std::ostream & utils::operator<< (std::ostream &os, const Matrix< T > &matrix)
 Output stream operator for matrix visualization.
 
template<typename T >
Matrix< T > utils::dot (const Matrix< T > &a, const Matrix< T > &b)
 Compute dot product of two matrices.
 
template<typename T >
utils::sum (const Matrix< T > &matrix)
 Calculate sum of all matrix elements.
 
template<typename T >
utils::mean (const Matrix< T > &matrix)
 Calculate mean of all matrix elements.