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experimental softsoftmax
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‎plearn/var/EXPERIMENTAL/AdditiveGaussianNoiseVariable.cc

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// -*- C++ -*-
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// AdditiveGaussianNoiseVariable.cc
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//
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// Copyright (C) 2010 Pascal Vincent
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// 1. Redistributions of source code must retain the above copyright
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// notice, this list of conditions and the following disclaimer.
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//
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// 2. Redistributions in binary form must reproduce the above copyright
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// notice, this list of conditions and the following disclaimer in the
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// documentation and/or other materials provided with the distribution.
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//
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// 3. The name of the authors may not be used to endorse or promote
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// products derived from this software without specific prior written
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// permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
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// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
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// NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
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// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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//
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// This file is part of the PLearn library. For more information on the PLearn
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// library, go to the PLearn Web site at www.plearn.org
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// Authors: Pascal Vincent
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/*! \file AdditiveGaussianNoiseVariable.cc */
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#include "AdditiveGaussianNoiseVariable.h"
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namespace PLearn {
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using namespace std;
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/** AdditiveGaussianNoiseVariable **/
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PLEARN_IMPLEMENT_OBJECT(
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AdditiveGaussianNoiseVariable,
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"Adds an isotropic Gaussian noise of given standard deviation",
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""
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);
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AdditiveGaussianNoiseVariable::AdditiveGaussianNoiseVariable()
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:sigma(1)
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{
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// ### You may (or not) want to call build_() to finish building the object
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// ### (doing so assumes the parent classes' build_() have been called too
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// ### in the parent classes' constructors, something that you must ensure)
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}
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// constructor from input variable and parameters
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// AdditiveGaussianNoiseVariable::AdditiveGaussianNoiseVariable(Variable* input, param_type the_parameter,...)
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// ### replace with actual parameters
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// : inherited(input, this_variable_length, this_variable_width),
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// parameter(the_parameter),
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// ...
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//{
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// // ### You may (or not) want to call build_() to finish building the
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// // ### object
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//}
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void AdditiveGaussianNoiseVariable::recomputeSize(int& l, int& w) const
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{
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if (input)
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{
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l = input.length();
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w = input.width(); // the computed width
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}
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else
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l = w = 0;
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}
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// ### computes value from input's value
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void AdditiveGaussianNoiseVariable::fprop()
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{
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checkContiguity();
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if(random_gen.isNull())
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random_gen = PRandom::common(false);
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int n = value.length();
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for(int i=0; i<n; i++)
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{
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valuedata[i] = random_gen->gaussian_mu_sigma(input->valuedata[i], sigma);
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}
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}
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// ### computes input's gradient from gradient
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void AdditiveGaussianNoiseVariable::bprop()
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{
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}
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// ### You can implement these methods:
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// void AdditiveGaussianNoiseVariable::bbprop() {}
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// void AdditiveGaussianNoiseVariable::symbolicBprop() {}
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// void AdditiveGaussianNoiseVariable::rfprop() {}
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// ### Nothing to add here, simply calls build_
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void AdditiveGaussianNoiseVariable::build()
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{
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inherited::build();
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build_();
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}
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void AdditiveGaussianNoiseVariable::makeDeepCopyFromShallowCopy(CopiesMap& copies)
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{
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inherited::makeDeepCopyFromShallowCopy(copies);
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// ### Call deepCopyField on all "pointer-like" fields
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// ### that you wish to be deepCopied rather than
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// ### shallow-copied.
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// ### ex:
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deepCopyField(random_gen, copies);
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// ### If you want to deepCopy a Var field:
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// varDeepCopyField(somevariable, copies);
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}
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void AdditiveGaussianNoiseVariable::declareOptions(OptionList& ol)
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{
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// ### Declare all of this object's options here.
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// ### For the "flags" of each option, you should typically specify
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// ### one of OptionBase::buildoption, OptionBase::learntoption or
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// ### OptionBase::tuningoption. If you don't provide one of these three,
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// ### this option will be ignored when loading values from a script.
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// ### You can also combine flags, for example with OptionBase::nosave:
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// ### (OptionBase::buildoption | OptionBase::nosave)
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declareOption(ol, "sigma", &AdditiveGaussianNoiseVariable::sigma,
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OptionBase::buildoption,
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"The standard deviation of the isotropic Gaussian noise to be added to the input");
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declareOption(ol, "random_gen", &AdditiveGaussianNoiseVariable::random_gen,
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OptionBase::buildoption,
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"Random number generator. If null, the PRandom::common(false) generator will be used.");
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// Now call the parent class' declareOptions
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inherited::declareOptions(ol);
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}
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void AdditiveGaussianNoiseVariable::build_()
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{
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// ### This method should do the real building of the object,
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// ### according to set 'options', in *any* situation.
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// ### Typical situations include:
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// ### - Initial building of an object from a few user-specified options
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// ### - Building of a "reloaded" object: i.e. from the complete set of
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// ### all serialised options.
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// ### - Updating or "re-building" of an object after a few "tuning"
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// ### options have been modified.
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// ### You should assume that the parent class' build_() has already been
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// ### called.
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}
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} // end of namespace PLearn
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/*
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Local Variables:
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mode:c++
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c-basic-offset:4
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c-file-style:"stroustrup"
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c-file-offsets:((innamespace . 0)(inline-open . 0))
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indent-tabs-mode:nil
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fill-column:79
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End:
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*/
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// vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :

‎plearn/var/EXPERIMENTAL/AdditiveGaussianNoiseVariable.h

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// -*- C++ -*-
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// AdditiveGaussianNoiseVariable.h
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//
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// Copyright (C) 2010 Pascal Vincent
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// 1. Redistributions of source code must retain the above copyright
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// notice, this list of conditions and the following disclaimer.
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//
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// 2. Redistributions in binary form must reproduce the above copyright
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// notice, this list of conditions and the following disclaimer in the
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// documentation and/or other materials provided with the distribution.
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//
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// 3. The name of the authors may not be used to endorse or promote
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// products derived from this software without specific prior written
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// permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND ANY EXPRESS OR
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// IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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// OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN
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// NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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// SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED
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// TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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// PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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// LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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// NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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//
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// This file is part of the PLearn library. For more information on the PLearn
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// library, go to the PLearn Web site at www.plearn.org
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// Authors: Pascal Vincent
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/*! \file AdditiveGaussianNoiseVariable.h */
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#ifndef AdditiveGaussianNoiseVariable_INC
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#define AdditiveGaussianNoiseVariable_INC
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#include <plearn/var/UnaryVariable.h>
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#include <plearn/math/PRandom.h>
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namespace PLearn {
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using namespace std;
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/*! * AdditiveGaussianNoiseVariable * */
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/**
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* The first sentence should be a BRIEF DESCRIPTION of what the class does.
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* Place the rest of the class programmer documentation here. Doxygen supports
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* Javadoc-style comments. See http://www.doxygen.org/manual.html
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*
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* @todo Write class to-do's here if there are any.
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*
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* @deprecated Write deprecated stuff here if there is any. Indicate what else
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* should be used instead.
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*/
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class AdditiveGaussianNoiseVariable : public UnaryVariable
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{
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typedef UnaryVariable inherited;
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public:
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//##### Public Build Options ############################################
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//! ### declare public option fields (such as build options) here
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//! Start your comments with Doxygen-compatible comments such as //!
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PP<PRandom> random_gen;
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real sigma;
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public:
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//##### Public Member Functions #########################################
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//! Default constructor, usually does nothing
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AdditiveGaussianNoiseVariable();
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// ### If your class has parameters, you probably want a constructor that
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// ### initializes them
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// AdditiveGaussianNoiseVariable(Variable* input, param_type the_parameter, ...);
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// Your other public member functions go here
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//##### PLearn::Variable methods #########################################
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// (PLEASE IMPLEMENT IN .cc)
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virtual void recomputeSize(int& l, int& w) const;
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virtual void fprop();
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virtual void bprop();
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// ### These ones are not always implemented
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// virtual void bbprop();
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// virtual void symbolicBprop();
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// virtual void rfprop();
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//##### PLearn::Object Protocol #########################################
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// Declares other standard object methods.
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// ### If your class is not instantiatable (it has pure virtual methods)
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// ### you should replace this by PLEARN_DECLARE_ABSTRACT_OBJECT
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PLEARN_DECLARE_OBJECT(AdditiveGaussianNoiseVariable);
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// Simply calls inherited::build() then build_()
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virtual void build();
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//! Transforms a shallow copy into a deep copy
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// (PLEASE IMPLEMENT IN .cc)
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virtual void makeDeepCopyFromShallowCopy(CopiesMap& copies);
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protected:
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//##### Protected Options ###############################################
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// ### Declare protected option fields (such as learned parameters) here
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// ...
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// will contain true where features have been corrupted
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TVec<bool> corrupted;
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protected:
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//##### Protected Member Functions ######################################
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//! Declares the class options.
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// (PLEASE IMPLEMENT IN .cc)
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static void declareOptions(OptionList& ol);
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private:
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//##### Private Member Functions ########################################
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//! This does the actual building.
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// (PLEASE IMPLEMENT IN .cc)
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void build_();
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private:
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//##### Private Data Members ############################################
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// The rest of the private stuff goes here
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};
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// Declares a few other classes and functions related to this class
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DECLARE_OBJECT_PTR(AdditiveGaussianNoiseVariable);
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// ### Put here a convenient method for building your variable.
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// ### e.g., if your class is TotoVariable, with two parameters foo_type foo
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// ### and bar_type bar, you could write:
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// inline Var toto(Var v, foo_type foo=default_foo, bar_type bar=default_bar)
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// { return new TotoVariable(v, foo, bar); }
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} // end of namespace PLearn
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#endif
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/*
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Local Variables:
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mode:c++
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c-basic-offset:4
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c-file-style:"stroustrup"
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c-file-offsets:((innamespace . 0)(inline-open . 0))
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indent-tabs-mode:nil
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fill-column:79
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End:
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*/
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// vim: filetype=cpp:expandtab:shiftwidth=4:tabstop=8:softtabstop=4:encoding=utf-8:textwidth=79 :

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