/** empty the buffer */
ssize_t Swipl_IO::_write_f(void *handle, char* buf, size_t bufsize) {
auto e = pq_cast<Swipl_IO>(handle);
if (e->target) {
emit e->user_output(QString::fromUtf8(buf, bufsize));
e->flush();
}
return bufsize;
}
void output_svdpp_result(std::string filename) {
MMOutputter_mat<vertex_data> user_output(filename + "_U.mm", 0, M, "This file contains SVD++ output matrix U. In each row D factors of a single user node. Then additional D weight factors.", latent_factors_inmem, 2*D);
MMOutputter_mat<vertex_data> item_output(filename + "_V.mm", M ,M+N, "This file contains SVD++ output matrix V. In each row D factors of a single item node.", latent_factors_inmem);
MMOutputter_vec<vertex_data> bias_user_vec(filename + "_U_bias.mm", 0, M, BIAS_POS, "This file contains SVD++ output bias vector. In each row a single user bias.", latent_factors_inmem);
MMOutputter_vec<vertex_data> bias_mov_vec(filename + "_V_bias.mm", M, M+N, BIAS_POS, "This file contains SVD++ output bias vector. In each row a single item bias.", latent_factors_inmem);
MMOutputter_scalar gmean(filename + "_global_mean.mm", "This file contains SVD++ global mean which is required for computing predictions.", globalMean);
logstream(LOG_INFO) << "SVDPP output files (in matrix market format): " << filename << "_U.mm" <<
", " << filename + "_V.mm, " << filename << "_U_bias.mm, " << filename << "_V_bias.mm, " << filename << "_global_mean.mm" << std::endl;
}
