/media/e/eblearn-trunk/libeblearn/include/EblBasic.h

/***************************************************************************
 *   Copyright (C) 2008 by Yann LeCun and Pierre Sermanet *
 *   yann@cs.nyu.edu, pierre.sermanet@gmail.com *
 *
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 *     * Redistributions of source code must retain the above copyright
 *       notice, this list of conditions and the following disclaimer.
 *     * Redistributions in binary form must reproduce the above copyright
 *       notice, this list of conditions and the following disclaimer in the
 *       documentation and/or other materials provided with the distribution.
 *     * Redistribution under a license not approved by the Open Source
 *       Initiative (http://www.opensource.org) must display the
 *       following acknowledgement in all advertising material:
 *        This product includes software developed at the Courant
 *        Institute of Mathematical Sciences (http://cims.nyu.edu).
 *     * The names of the authors may not be used to endorse or promote products
 *       derived from this software without specific prior written permission.
 *
 * THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESS OR IMPLIED
 * WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
 * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
 * DISCLAIMED. IN NO EVENT SHALL ThE AUTHORS BE LIABLE FOR ANY
 * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
 * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
 * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
 * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
 * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 ***************************************************************************/

#ifndef EBLBASIC_H_
#define EBLBASIC_H_

#include "Defines.h"
#include "Idx.h"
#include "Blas.h"
#include "EblArch.h"
#include "EblStates.h"

namespace ebl {

  // linear_module
  class linear_module: public module_1_1<state_idx, state_idx> {
  public:
    state_idx w;

    linear_module(parameter &p, intg in, intg out);
    virtual ~linear_module();
    virtual void fprop(state_idx &in, state_idx &out);
    virtual void bprop(state_idx &in, state_idx &out);
    virtual void bbprop(state_idx &in, state_idx &out);
    virtual int replicable_order() { return 1; }
    virtual void forget(forget_param_linear &fp);
    virtual void normalize();
    virtual void resize_output(state_idx &in, state_idx &out);
  };

  DECLARE_REPLICABLE_MODULE_1_1(linear_module_replicable, 
                                linear_module,
                                (parameter &p, intg in, intg out),
                                (p, in, out));

  // convolution_module_2D
  class convolution_module_2D: public module_1_1<state_idx, state_idx> {
  public:
    state_idx    kernel;
    intg         thickness;
    intg         stridei;
    intg         stridej;
    Idx<intg>   &table; 
    
    convolution_module_2D(parameter &p, intg kerneli, intg kernelj, 
                          intg  stridei, intg stridej, 
                          Idx<intg> &table, intg thick);
    virtual ~convolution_module_2D();
    virtual void fprop(state_idx &in, state_idx &out);
    virtual void bprop(state_idx &in, state_idx &out);
    virtual void bbprop(state_idx &in, state_idx &out);
    virtual void forget(forget_param_linear &fp);
    virtual int replicable_order() { return 3; }
    virtual void resize_output(state_idx &in, state_idx &out);
  };

  DECLARE_REPLICABLE_MODULE_1_1(convolution_module_2D_replicable, 
                                convolution_module_2D,
                                (parameter &p, intg ki, intg kj, intg si, 
                                 intg sj, Idx<intg> &table, intg thick),
                                (p, ki, kj, si, sj, table, thick));

  // subsampling_module_2D
  class subsampling_module_2D: public module_1_1<state_idx, state_idx> {
  public:
    state_idx    coeff;
    state_idx    sub;
    intg         thickness;
    intg         stridei;
    intg         stridej;
    
    subsampling_module_2D(parameter &p, intg stridei_, intg stridej_,
                          intg subi, intg subj, intg thick);
    virtual ~subsampling_module_2D();
    virtual void fprop(state_idx &in, state_idx &out);
    virtual void bprop(state_idx &in, state_idx &out);
    virtual void bbprop(state_idx &in, state_idx &out);
    virtual void forget(forget_param_linear &fp);
    virtual int replicable_order() { return 3; }
    virtual void resize_output(state_idx &in, state_idx &out);
  };

  DECLARE_REPLICABLE_MODULE_1_1(subsampling_module_2D_replicable, 
                                subsampling_module_2D,
                                (parameter &p, intg sti, intg stj, intg subi, 
                                 intg subj, intg thick),
                                (p, sti, stj, subi, subj, thick));

  // addc_module
  class addc_module: public module_1_1<state_idx, state_idx> {
  public:
    state_idx  bias; 

    addc_module(parameter &p, intg size);
    virtual ~addc_module();
    virtual void fprop(state_idx &in, state_idx &out);
    virtual void bprop(state_idx &in, state_idx &out);
    virtual void bbprop(state_idx &in, state_idx &out);
    virtual void forget(forget_param_linear &fp);
    virtual void normalize();
  };

} // namespace ebl {

#endif /* EBLBASIC_H_ */

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