ShareBoostOptimizer.cpp

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/*
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3 of the License, or
 * (at your option) any later version.
 *
 * Written (W) 2012 Chiyuan Zhang
 * Copyright (C) 2012 Chiyuan Zhang
 */

#include <algorithm>

#include <shogun/mathematics/Math.h>
#include <shogun/optimization/lbfgs/lbfgs.h>
#include <shogun/multiclass/ShareBoostOptimizer.h>

using namespace shogun;

void ShareBoostOptimizer::optimize()
{
    int32_t N = m_sb->m_multiclass_strategy->get_num_classes() * m_sb->m_activeset.vlen;
    float64_t *W = SG_CALLOC(float64_t, N); // should use this function, if sse is enabled for liblbfgs
    float64_t objval;
    lbfgs_parameter_t param;
    lbfgs_parameter_init(&param);

    std::fill(W, W+N, 0);

    lbfgs_progress_t progress = m_verbose ? &ShareBoostOptimizer::lbfgs_progress : NULL;

    lbfgs(N, W, &objval, &ShareBoostOptimizer::lbfgs_evaluate, progress, this, &param);

    int32_t w_len = m_sb->m_activeset.vlen;
    for (int32_t i=0; i < m_sb->m_multiclass_strategy->get_num_classes(); ++i)
    {
        CLinearMachine *machine = dynamic_cast<CLinearMachine *>(m_sb->m_machines->get_element(i));
        SGVector<float64_t> w(w_len);
        std::copy(W + i*w_len, W + (i+1)*w_len, w.vector);
        machine->set_w(w);
        SG_UNREF(machine);
    }

    SG_FREE(W);
}

float64_t ShareBoostOptimizer::lbfgs_evaluate(void *userdata, const float64_t *W, 
        float64_t *grad, const int32_t n, const float64_t step)
{
    ShareBoostOptimizer *optimizer = static_cast<ShareBoostOptimizer *>(userdata);

    optimizer->m_sb->compute_pred(W);
    optimizer->m_sb->compute_rho();

    int32_t m = optimizer->m_sb->m_activeset.vlen;
    int32_t k = optimizer->m_sb->m_multiclass_strategy->get_num_classes();

    SGMatrix<float64_t> fea = optimizer->m_sb->m_fea;
    CMulticlassLabels *lab = dynamic_cast<CMulticlassLabels *>(optimizer->m_sb->m_labels);

    // compute gradient
    for (int32_t i=0; i < m; ++i)
    {
        for (int32_t j=0; j < k; ++j)
        {
            int32_t idx = j*m + i;
            float64_t g=0;
            for (int32_t ii=0; ii < fea.num_cols; ++ii)
                g += fea(optimizer->m_sb->m_activeset[i], ii) *
                    (optimizer->m_sb->m_rho(j,ii)/optimizer->m_sb->m_rho_norm[ii] - 
                     (j == lab->get_int_label(ii)));
            g /= fea.num_cols;
            grad[idx] = g;
        }
    }

    // compute objective function
    float64_t objval = 0;
    for (int32_t ii=0; ii < fea.num_cols; ++ii)
    {
        objval += CMath::log(optimizer->m_sb->m_rho_norm[ii]);
    }
    objval /= fea.num_cols;

    return objval;
}

int ShareBoostOptimizer::lbfgs_progress(
        void *instance,
        const float64_t *x,
        const float64_t *g,
        const float64_t fx,
        const float64_t xnorm,
        const float64_t gnorm,
        const float64_t step,
        int n,
        int k,
        int ls
        )
{
    if (k != 1 && k % 100 != 0)
        return 0;

    SG_SPRINT("Iteration %d:\n", k);
    SG_SPRINT("  fx = %f, x[0] = %f, x[1] = %f\n", fx, x[0], x[1]);
    SG_SPRINT("  xnorm = %f, gnorm = %f, step = %f\n", xnorm, gnorm, step);
    SG_SPRINT("\n");
    return 0;
}