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// Copyright (C) 2003--2004 Ronan Collobert (collober@idiap.ch)
//                
// This file is part of Torch 3.1.
//
// All rights reserved.
// 
// Redistribution and use in source and binary forms, with or without
// modification, are permitted provided that the following conditions
// are met:
// 1. Redistributions of source code must retain the above copyright
//    notice, this list of conditions and the following disclaimer.
// 2. 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.
// 3. The name of the author may not be used to endorse or promote products
//    derived from this software without specific prior written permission.
// 
// THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``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 AUTHOR 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 LOG_MIXER_INC
#define LOG_MIXER_INC

#include "GradientMachine.h"

namespace Torch {

/** LogMixer useful for experts mixtures.
    Formally speaking, it computes:
    $outputs[i] = log(\sum_j exp(log_{a_j}) + log(LogInputs_j[i]))$
    
    where
    \begin{itemize}
      \item ${log_{a_1},...,log_{a_n}}$ are the first #n_experts# inputs
      of the machine.
      
      \item $LogInputs_j$ are the outputs of the j-th expert.
      Therefore, the inputs given to the machine have the following structure:
      ${log_a, LogOutputsExpert_1, LogOutputsExpert_2, ...}$.
    \end{itemize}

    @author Ronan Collobert (collober@idiap.ch)
*/
class LogMixer : public GradientMachine
{
  public:
    int n_experts;

    //-----

    ///
    LogMixer(int n_inputs_, int n_outputs_per_expert);

    //-----

    virtual void frameForward(int t, real *f_inputs, real *f_outputs);
    virtual void frameBackward(int t, real *f_inputs, real *beta_, real *f_outputs, real *alpha_);

    virtual ~LogMixer();
};

}

#endif