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#include <RcppArmadillo.h> | |
#include <omp.h> | |
using namespace Rcpp; | |
using namespace arma; | |
// [[Rcpp::depends(RcppArmadillo)]] | |
// [[Rcpp::plugins(openmp)]] | |
// [[Rcpp::export]] | |
void updateImplicitX_p(arma::mat & X, const arma::mat & Y, const arma::mat & P, const arma::mat & C, double lambda, int cores = 1) { | |
int num_users = C.n_rows; | |
int num_prods = C.n_cols; | |
int num_factors = Y.n_cols; // or X.n_cols | |
Rprintf("."); | |
arma::mat YTY = Y.t() * Y; | |
arma::mat fact_eye = eye(num_prods, num_prods); | |
arma::mat lambda_eye = lambda * eye(num_factors, num_factors); | |
#pragma omp parallel for num_threads(cores) | |
for (int u = 0; u < C.n_rows; u++) { | |
arma::mat Cu = diagmat(C.row(u)); | |
arma::mat YTCuIY = Y.t() * (Cu) * Y; | |
arma::mat YTCupu = Y.t() * (Cu + fact_eye) * P.row(u).t(); | |
arma::mat WuT = YTY + YTCuIY + lambda_eye; | |
arma::mat xu = solve(WuT, YTCupu); | |
// Update gradient -- maybe a slow operation in parallel? | |
X.row(u) = xu.t(); | |
} | |
} | |
/*** R | |
test = matrix(rnorm(10000), ncol=100, nrow=100) | |
install.packages(microbenchmark | |
library(microbenchmark) | |
microbenchmark(updateImplicitX(test,test,test,test,5), | |
updateImplicitX_p(test,test,test,test,5,1), | |
updateImplicitX_p(test,test,test,test,5,2), | |
updateImplicitX_p(test,test,test,test,5,3), | |
updateImplicitX_p(test,test,test,test,5,4), | |
updateImplicitX_p(test,test,test,test,5,5)) | |
*/ |
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