// 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 valuesif( global_option["memory"] || global_option["onetape"] || global_option["atomic"] || global_option["optimize"] )
returnfalse;
// The correctness check for this test is failing, so abort (for now).returnfalse;
// -----------------------------------------------------// setup// object for computing determinanttypedef 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 valuesfor(j = 0; j < n; j++)
X[j] = x[j];
// do the computationmat_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 modefor(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();
// ---------------------------------------------------------returntrue;
}