trainer.cpp

Gaussian Mixture Algorithm

/***************************************************************************
 *   Copyright (C) 2008 by Yann LeCun and Pierre Sermanet  *
 *   [e-mail], [e-mail]   *
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 *        Institute of Mathematical Sciences (http://cims.nyu.edu).
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#include "Trainer.h"
#include "IdxIO.h"

using namespace std;

namespace ebl {

eb_trainer::eb_trainer(idx3_supervised_module *m, parameter *p,
		state_idx *e, state_idx *in) {
  machine = m;
  param = p;
  age = 0;
  energy_owned = false;
  input_owned = false;
  if (e != NULL)
  	energy = e;
  else {
    // set energy slot to default idx0-ddstate
    energy = new state_idx();
    energy_owned = true;
    energy->dx.set(1.0);
    energy->ddx.set(0.0);
  }
  if (in != NULL)
  	input = in;
  else {
  	input = new state_idx(1, 1, 1);
  	input_owned = true;
  }
}

eb_trainer::~eb_trainer() {
	if (energy_owned) delete energy;
	if (input_owned) delete input;
}

////////////////////////////////////////////////////////////////

supervised::supervised(idx3_supervised_module *m, parameter *p,
		state_idx *e, state_idx *in,
		class_state *out, Idx<ubyte> *des)
: eb_trainer(m, p, e, in) {
  output_owned = true;
  desired_owned = true;
  if (out != NULL)
  	output = out;
  else {
    output = new class_state(2);
    output_owned = true;
  }
  if (des != NULL)
    desired = des;
  else {
    desired = new Idx<ubyte>();
    desired_owned = true;
  }
}

supervised::~supervised() {
	if (output_owned) delete output;
	if (desired_owned) delete desired;
}



////////////////////////////////////////////////////////////////

supervised_gradient::supervised_gradient(idx3_supervised_module *m, parameter *p,
		state_idx *e, state_idx *in,
		class_state *out, Idx<ubyte> *des)
: supervised(m, p, e, in, out, des) {
}

supervised_gradient::~supervised_gradient() {
}


} // end namespace ebl