/***************************************************************************
 *   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:
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 *       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
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 * DISCLAIMED. IN NO EVENT SHALL ThE AUTHORS BE LIABLE FOR ANY
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#ifndef NET_CSCSCFE_H_
#define NET_CSCSCFE_H_

#include "Ebm.h"
#include "Net.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.
class e_layer :
	public module_1_1<state_idx, state_idx>
{
public:
	//! weight matrix
	state_idx *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 *out);
	//! bprop
	void bprop(state_idx *in, state_idx *out);
	//! bbprop
	void bbprop(state_idx *in, state_idx *out);
	//! initialize the weights to random values
	void forget(forget_param_linear &fp);
};



//! Standard LeNet5-type architecture with the "RBF" layer on top
class net_cscscfe : public module_1_1<state_idx, state_idx>
{
public:
	net_cscscf		*net;
	state_idx		*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 *in, state_idx *out);
	//! bprop
	virtual void bprop(state_idx *in, state_idx *out);
	//! bbprop
	virtual void bbprop(state_idx *in, state_idx *out);
};

} // end namespace ebl

#endif /* NET_CSCSCFE_H_ */