/home/rex/ebltrunk/core/libeblearn/include/net_cscscfe.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 NET_CSCSCFE_H_
#define NET_CSCSCFE_H_

#include "libidx.h"
#include "ebl_machines.h"

namespace ebl {

/*   //! full connection with Euclidean distance between replicable  */
/*   //! 3D layers. This is like a layer of RBF WITHOUT NON-LINEAR FUNCTIONS. */
/*   //! the output is the square Euclidean distance between the input */
/*   //! and the weight */
/*   //! the full connection is only across the first dimension  */
/*   //! of the input and output layer. */
/*   //! the other two dimensions are spatial dimensions accross which the  */
/*   //! weight matrix is shared. */
/*   template <class T> class e_layer : */
/*   public module_1_1<state_idx<T>, state_idx<T> > */
/*     { */
/*     public: */
/*       //! weight matrix */
/*       state_idx<T> weight; */

/*       virtual ~e_layer(void); */
/*       //! new e-layer (Eucliden distance RBF). <tin> is the */
/*       //! thickness of the input layer, <tout> is the thickness  */
/*       //! of the output layer, <prm> is the parameter. */
/*       e_layer(parameter &prm, intg tin, intg tout);   */
/*       //! fprop from in to out */
/*       void fprop(state_idx &in, state_idx<T> &out); */
/*       //! bprop */
/*       void bprop(state_idx<T> &in, state_idx<T> &out); */
/*       //! bbprop */
/*       void bbprop(state_idx<T> &in, state_idx<T> &out); */
/*       //! initialize the weights to random values */
/*       void forget(forget_param_linear &fp); */
/*     }; */

/*   //! Standard LeNet5-type architecture with the "RBF" layer on top */
/*   template <class T> */
/*     class net_cscscfe : public module_1_1<state_idx<T>, state_idx<T> > */
/*     { */
/*     public: */
/*       net_cscscf     &net; */
/*       state_idx<T>   netout; */
/*       e_layer                &rbf; */

/*       //! makes a new net_cscscfe module. */
/*       //! <n> is a net-cscscf, <e> is an e-dist layer, */
/*       //! <thick> is the number of outputs. */
/*       //! <si>,<sj> are the initial replication factors. */
/*       net_cscscfe(net_cscscf &n, e_layer &e, int thick, int si, int sj); */
/*       virtual ~net_cscscfe(); */

/*       //! initialize the weights to random values */
/*       void forget(forget_param_linear &fp); */
/*       //! fprop from in to out */
/*       virtual void fprop(state_idx<T> &in, state_idx<T> &out); */
/*       //! bprop */
/*       virtual void bprop(state_idx<T> &in, state_idx<T> &out); */
/*       //! bbprop */
/*       virtual void bbprop(state_idx<T> &in, state_idx<T> &out); */
/*     }; */

} // end namespace ebl

#endif /* NET_CSCSCFE_H_ */