\(\newcommand{\W}[1]{ \; #1 \; }\) \(\newcommand{\R}[1]{ {\rm #1} }\) \(\newcommand{\B}[1]{ {\bf #1} }\) \(\newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} }\) \(\newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} }\) \(\newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} }\) \(\newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }\)
fadbad_mat_mul.cpp¶
View page sourceFadbad Speed: Matrix Multiplication¶
Specifications¶
See link_mat_mul .
Implementation¶
// suppress conversion warnings before other includes
# include <cppad/wno_conversion.hpp>
//
# include <FADBAD++/badiff.h>
# include <cppad/speed/mat_sum_sq.hpp>
# include <cppad/speed/uniform_01.hpp>
# include <cppad/utility/vector.hpp>
// list of possible options
# include <map>
extern std::map<std::string, bool> global_option;
bool link_mat_mul(
size_t size ,
size_t repeat ,
CppAD::vector<double>& x ,
CppAD::vector<double>& z ,
CppAD::vector<double>& dz )
{
// speed test global option values
if( global_option["memory"] || global_option["onetape"] || global_option["atomic"] || global_option["optimize"] )
return false;
// The correctness check for this test is failing, so abort (for now).
return false;
// -----------------------------------------------------
// setup
// object for computing determinant
typedef fadbad::B<double> ADScalar;
typedef CppAD::vector<ADScalar> ADVector;
size_t j; // temporary index
size_t m = 1; // number of dependent variables
size_t n = size * size; // number of independent variables
ADVector X(n); // AD domain space vector
ADVector Y(n); // Store product matrix
ADVector Z(m); // AD range space vector
// ------------------------------------------------------
while(repeat--)
{ // get the next matrix
CppAD::uniform_01(n, x);
// set independent variable values
for(j = 0; j < n; j++)
X[j] = x[j];
// do the computation
mat_sum_sq(size, X, Y, Z);
// create function object f : X -> Z
Z[0].diff(0, m); // index 0 of m dependent variables
// evaluate and return gradient using reverse mode
for(j = 0; j < n; j++)
dz[j] = X[j].d(0); // partial Z[0] w.r.t X[j]
}
// return function value
z[0] = Z[0].x();
// ---------------------------------------------------------
return true;
}