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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.
#include "LogMixer.h"
#include "log_add.h"
namespace Torch {
LogMixer::LogMixer(int n_experts_, int n_outputs_per_expert) : GradientMachine(n_experts_*(n_outputs_per_expert+1), n_outputs_per_expert)
{
n_experts = n_experts_;
}
void LogMixer::frameForward(int t, real *f_inputs, real *f_outputs)
{
for(int i = 0; i < n_outputs; i++)
f_outputs[i] = LOG_ZERO;
real *log_weight_ = f_inputs;
real *log_src_ = f_inputs+n_experts;
for(int i = 0; i < n_experts; i++)
{
real z = log_weight_[i];
for(int j = 0; j < n_outputs; j++)
f_outputs[j] = logAdd(f_outputs[j], z + *log_src_++);
}
}
void LogMixer::frameBackward(int t, real *f_inputs, real *beta_, real *f_outputs, real *alpha_)
{
if(partial_backprop)
return;
real *beta__ = beta_+n_experts;
real *log_weight_ = f_inputs;
real *log_src_ = f_inputs+n_experts;
for(int i = 0; i < n_experts; i++)
{
real z = log_weight_[i];
for(int j = 0; j < n_outputs; j++)
*beta__++ = alpha_[j] * exp(z + *log_src_++ - f_outputs[j]);
}
beta__ = beta_+n_experts;
for(int i = 0; i < n_experts; i++)
{
real sum = 0;
for(int j = 0; j < n_outputs; j++)
sum += *beta__++;
beta_[i] = sum;
}
}
LogMixer::~LogMixer()
{
}
}
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