PLearn 0.1
Public Member Functions | Static Public Member Functions | Public Attributes | Static Public Attributes | Static Protected Member Functions | Private Types | Private Member Functions | Static Private Member Functions
PLearn::MultiMaxVariable Class Reference

This variables computes a max functions (softmax, log-softmax, hardmax, etc., determined by the field computation_type) on subvectors of the input, which lenght is defined by the field groupsizes. More...

#include <MultiMaxVariable.h>

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List of all members.

Public Member Functions

 MultiMaxVariable ()
 Default constructor, usually does nothing.
 MultiMaxVariable (Variable *input, TVec< int > groupsizes, char computation_type='S')
 Constructor.
 MultiMaxVariable (Variable *input, int groupsizes, char computation_type='S')
virtual void recomputeSize (int &l, int &w) const
 Recomputes the length l and width w that this variable should have, according to its parent variables.
virtual void fprop ()
 Nothing to do by default.
virtual void bprop ()
 Nothing to do by default.
virtual string classname () const
virtual OptionListgetOptionList () const
virtual OptionMapgetOptionMap () const
virtual RemoteMethodMapgetRemoteMethodMap () const
virtual MultiMaxVariabledeepCopy (CopiesMap &copies) const
virtual void build ()
 Post-constructor.
virtual void makeDeepCopyFromShallowCopy (CopiesMap &copies)
 Transforms a shallow copy into a deep copy.

Static Public Member Functions

static string _classname_ ()
 MultiMaxVariable.
static OptionList_getOptionList_ ()
static RemoteMethodMap_getRemoteMethodMap_ ()
static Object_new_instance_for_typemap_ ()
static bool _isa_ (const Object *o)
static void _static_initialize_ ()
static const PPathdeclaringFile ()

Public Attributes

TVec< intgroupsizes
 ### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //!
char computation_type
int groupsize

Static Public Attributes

static StaticInitializer _static_initializer_

Static Protected Member Functions

static void declareOptions (OptionList &ol)
 Declares the class options.

Private Types

typedef UnaryVariable inherited

Private Member Functions

void build_ ()
 This does the actual building.

Static Private Member Functions

static void softmax_range (Vec &x, Vec &y, int start, int length)
static void logSoftmax_range (Vec &x, Vec &y, int start, int length)
static void hardMax_range (Vec &x, Vec &y, int start, int length, bool value=false)
static void bpropSoftMax (Vec &gradientInput, Vec &gradient, Vec &variableValue, int start, int length)
static void bpropLogSoftMax (Vec &gradientInput, Vec &gradient, Vec &variableValue, int start, int length)
static void bpropHardMaxValue (Vec &gradientInput, Vec &gradient, Vec &variableValue, int start, int length)

Detailed Description

This variables computes a max functions (softmax, log-softmax, hardmax, etc., determined by the field computation_type) on subvectors of the input, which lenght is defined by the field groupsizes.

* MultiMaxVariable *

ex : if groupsizes = [1,2,3], and computation_type = 'S' (for softmax), and the input vector [1,2,3,4,5,6], the result will be [softmax([1]), softmax([2,3]), softmax([4,5,6])]

note : in that example matValue.width() of the variable must be 1+2+3=6

Todo:
Write class to-do's here if there are any.
Deprecated:
Write deprecated stuff here if there is any. Indicate what else should be used instead.

Definition at line 65 of file MultiMaxVariable.h.


Member Typedef Documentation

Reimplemented from PLearn::UnaryVariable.

Definition at line 67 of file MultiMaxVariable.h.


Constructor & Destructor Documentation

PLearn::MultiMaxVariable::MultiMaxVariable ( ) [inline]

Default constructor, usually does nothing.

Definition at line 87 of file MultiMaxVariable.h.

        :computation_type('S'),
         groupsize(-1)
    {}
PLearn::MultiMaxVariable::MultiMaxVariable ( Variable input,
TVec< int groupsizes,
char  computation_type = 'S' 
)

Constructor.

Definition at line 61 of file MultiMaxVariable.cc.

References build_().

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PLearn::MultiMaxVariable::MultiMaxVariable ( Variable input,
int  groupsizes,
char  computation_type = 'S' 
)

Definition at line 70 of file MultiMaxVariable.cc.

References build_().

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Member Function Documentation

string PLearn::MultiMaxVariable::_classname_ ( ) [static]

MultiMaxVariable.

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
OptionList & PLearn::MultiMaxVariable::_getOptionList_ ( ) [static]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
RemoteMethodMap & PLearn::MultiMaxVariable::_getRemoteMethodMap_ ( ) [static]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
bool PLearn::MultiMaxVariable::_isa_ ( const Object o) [static]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
Object * PLearn::MultiMaxVariable::_new_instance_for_typemap_ ( ) [static]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
StaticInitializer MultiMaxVariable::_static_initializer_ & PLearn::MultiMaxVariable::_static_initialize_ ( ) [static]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
void PLearn::MultiMaxVariable::bprop ( ) [virtual]

Nothing to do by default.

Reimplemented from PLearn::UnaryVariable.

Definition at line 145 of file MultiMaxVariable.cc.

References bpropHardMaxValue(), bpropLogSoftMax(), bpropSoftMax(), computation_type, groupsizes, i, PLearn::UnaryVariable::input, PLearn::TVec< T >::length(), PLearn::TMat< T >::length(), PLearn::Variable::matGradient, PLearn::Variable::matValue, n, and PLERROR.

{
    int k;
    Mat inputGradient = input->matGradient;
    int l = inputGradient.length();
    Vec inputGradient_n;
    Vec value_n;
    Vec gradient_n;
    for(int n=0; n<l; n++)
    {
        inputGradient_n = inputGradient(n);
        value_n = matValue(n);
        gradient_n = matGradient(n);
        k=0;
        for(int i=0; i<groupsizes.length(); i++)
        {
            switch(computation_type)
            {
//softmax
            case 'S':
                bpropSoftMax(inputGradient_n, gradient_n, value_n, k, groupsizes[i]);
                break;
//log_softmax
            case 'L':
                //ici aussi j'ai tout copié, en changeant seulement les "bornes" de la sommation
                bpropLogSoftMax(inputGradient_n, gradient_n, value_n, k, groupsizes[i]); 
                break;
//hardmax_value
            case 'H':
                bpropHardMaxValue(inputGradient_n, gradient_n, value_n, k, groupsizes[i]);
                break;
//hardmax
            case 'h':
                PLERROR("computation_type 'h' not implemented yet");
                break;
//random_softmax_value
            case 'R':
                PLERROR("computation_type 'R' not implemented yet");
                break;
//random_softmax
            case 'r':
                PLERROR("computation_type 'r' not implemented yet");
                break;
            default :
                PLERROR("unable to bprop because of invalid computation_type");
            }
            k+=groupsizes[i];
        }
    }
}    

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void PLearn::MultiMaxVariable::bpropHardMaxValue ( Vec gradientInput,
Vec gradient,
Vec variableValue,
int  start,
int  length 
) [static, private]

Definition at line 356 of file MultiMaxVariable.cc.

References i, PLearn::Variable::length(), and PLearn::sum().

Referenced by bprop().

{
    real sum=0.;
    for(int i=start; i<start+length; i++)
        sum += gradient[i];

    for(int i=start; i<start+length; i++)
        if(variableValue[i] != 0)
            gradientInput[i] += sum;
}

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void PLearn::MultiMaxVariable::bpropLogSoftMax ( Vec gradientInput,
Vec gradient,
Vec variableValue,
int  start,
int  length 
) [static, private]

Definition at line 346 of file MultiMaxVariable.cc.

References i, PLearn::Variable::length(), PLearn::safeexp(), and PLearn::sum().

Referenced by bprop().

{
    real sum=0.;
    for (int i = start; i < start+length; i++)
        sum += gradient[i];

    for (int i = start; i < start+length; ++i)
        gradientInput[i] += gradient[i] - sum * safeexp(variableValue[i]);    
}

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void PLearn::MultiMaxVariable::bpropSoftMax ( Vec gradientInput,
Vec gradient,
Vec variableValue,
int  start,
int  length 
) [static, private]

Definition at line 327 of file MultiMaxVariable.cc.

References i, j, and PLearn::Variable::length().

Referenced by bprop().

{
    //on parcout le gradient de notre vecteur
    for(int i=start; i<start+length; i++)
    {
        //et on rajoute un petit qqch pour chacun du gradient de l'input
        for(int j=start; j<start+length; j++)
        {
            //note ici jai juste copié ce quil y avait avant dans le bprob de softmaxVariable...
            if(i==j)
                gradientInput[i] += gradient[j]*variableValue[i]*(1.-variableValue[i]);
            else
                gradientInput[i] -= gradient[j]*variableValue[i]*variableValue[j];
        }
    }           
}

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void PLearn::MultiMaxVariable::build ( ) [virtual]

Post-constructor.

The normal implementation should call simply inherited::build(), then this class's build_(). This method should be callable again at later times, after modifying some option fields to change the "architecture" of the object.

Reimplemented from PLearn::UnaryVariable.

Definition at line 202 of file MultiMaxVariable.cc.

References PLearn::UnaryVariable::build(), and build_().

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void PLearn::MultiMaxVariable::build_ ( ) [private]

This does the actual building.

Reimplemented from PLearn::UnaryVariable.

Definition at line 248 of file MultiMaxVariable.cc.

References groupsize, groupsizes, i, PLearn::UnaryVariable::input, PLearn::PP< T >::isNotNull(), PLearn::TVec< T >::length(), PLERROR, PLearn::sum(), and PLearn::Var::width().

Referenced by build(), and MultiMaxVariable().

{
    // ### This method should do the real building of the object,
    // ### according to set 'options', in *any* situation.
    // ### Typical situations include:
    // ###  - Initial building of an object from a few user-specified options
    // ###  - Building of a "reloaded" object: i.e. from the complete set of
    // ###    all serialised options.
    // ###  - Updating or "re-building" of an object after a few "tuning"
    // ###    options have been modified.
    // ### You should assume that the parent class' build_() has already been
    // ### called.
    
    if (input.isNotNull() ) // otherwise postpone building until we have an input!
    {
        if (groupsizes.length() <= 0)
        {
            if (groupsize <= 0)
                PLERROR("Groupsize(s) not specified or invalid in MultiMaxVariable");    
            if (input->width() % groupsize != 0)
                PLERROR("Invalid groupsize in MultiMaxVariable");

            TVec<int> vec(input->width()/groupsize, groupsize);
            groupsizes = vec;
        }
        else
        {
            int sum = 0;
            for(int i=0; i<groupsizes.length(); i++)
                sum += groupsizes[i];       
            if(sum != input->width())
                PLERROR("Invalid groupsizes in MultiMaxVariable");    
        }
    }
}

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string PLearn::MultiMaxVariable::classname ( ) const [virtual]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
void PLearn::MultiMaxVariable::declareOptions ( OptionList ol) [static, protected]

Declares the class options.

Reimplemented from PLearn::UnaryVariable.

Definition at line 221 of file MultiMaxVariable.cc.

References PLearn::OptionBase::buildoption, computation_type, PLearn::declareOption(), PLearn::UnaryVariable::declareOptions(), groupsize, and groupsizes.

{
    // ### Declare all of this object's options here.
    // ### For the "flags" of each option, you should typically specify
    // ### one of OptionBase::buildoption, OptionBase::learntoption or
    // ### OptionBase::tuningoption. If you don't provide one of these three,
    // ### this option will be ignored when loading values from a script.
    // ### You can also combine flags, for example with OptionBase::nosave:
    // ### (OptionBase::buildoption | OptionBase::nosave)

    // ### ex:
    declareOption(ol, "groupsizes", &MultiMaxVariable::groupsizes,
                  OptionBase::buildoption,
                  "this tells how to \"divide\" our diffrents inputs\nex: groupsizes = [1,2,3] says we divide our output like this :\n[x1],[x2,x3],[x4,x5,x6] and apply a maximum algorithm on each group separately");

    declareOption(ol, "groupsize", &MultiMaxVariable::groupsize,
                  OptionBase::buildoption,
                  "shortcut if you want all groupsizes to be equals, for example if you set the value of this option to be 3, it will make groupsizes = [3,3,...,3]");

    declareOption(ol, "computation_type", &MultiMaxVariable::computation_type,
                  OptionBase::buildoption,
                  "specifies what maximum algorithm should be used on our groups\n\'S\' = Softmax\n\'L\' = Log(Softmax)\n\'H\' = Hardmax*value\n\'h\' = hardmax\n\'R\' = random_Softmax*value\n\'r\' = random_Softmax");
            
    // Now call the parent class' declareOptions
    inherited::declareOptions(ol);
}

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static const PPath& PLearn::MultiMaxVariable::declaringFile ( ) [inline, static]

Reimplemented from PLearn::UnaryVariable.

Definition at line 116 of file MultiMaxVariable.h.

:
    //#####  Protected Options  ###############################################
MultiMaxVariable * PLearn::MultiMaxVariable::deepCopy ( CopiesMap copies) const [virtual]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
void PLearn::MultiMaxVariable::fprop ( ) [virtual]

Nothing to do by default.

Reimplemented from PLearn::UnaryVariable.

Definition at line 88 of file MultiMaxVariable.cc.

References computation_type, groupsizes, hardMax_range(), i, PLearn::UnaryVariable::input, PLearn::TVec< T >::length(), PLearn::TMat< T >::length(), logSoftmax_range(), PLearn::Variable::matValue, n, PLERROR, and softmax_range().

{
    int k;
    Mat inputValue = input->matValue;

    Vec inputValue_n;
    Vec value_n;

    for(int n=0; n<inputValue.length(); n++)
    {
        k=0;
        inputValue_n = inputValue(n);
        value_n = matValue(n);
        
        for(int i=0; i<groupsizes.length(); i++)
        {
            switch(computation_type)
            {
//softmax
            case 'S':
//          softmax(v.subVec(k,k+groupsizes[i]), value.subVec(k,k+groupsizes[i]));
                softmax_range(inputValue_n, value_n, k, groupsizes[i]);                   
                break;
//log_softmax
            case 'L':
//          log_softmax(v.subVec(k,k+groupsizes[i]), value.subVec(k,k+groupsizes[i]));
                logSoftmax_range(inputValue_n, value_n, k, groupsizes[i]);
                break;
//hardmax_value
            case 'H':
                hardMax_range(inputValue_n, value_n, k, groupsizes[i], true);
                break;
//hardmax
            case 'h':
                hardMax_range(inputValue_n, value_n, k, groupsizes[i], false);
                break;
//random_softmax_value
            case 'R':
                softmax_range(inputValue_n, value_n, k, groupsizes[i]);
                //TODO : RANDOM
                PLERROR("computation_type 'R' not fully implemented yet");
                break;
//random_softmax
            case 'r':
                softmax_range(inputValue_n, value_n, k, groupsizes[i]);
                //TODO : RANDOM
                PLERROR("computation_type 'r' not fully implemented yet");
                break;
            default :
                PLERROR("invalid computation_type in MultiMaxVariable");
            }
            k+=groupsizes[i];
        }
    }
}

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OptionList & PLearn::MultiMaxVariable::getOptionList ( ) const [virtual]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
OptionMap & PLearn::MultiMaxVariable::getOptionMap ( ) const [virtual]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
RemoteMethodMap & PLearn::MultiMaxVariable::getRemoteMethodMap ( ) const [virtual]

Reimplemented from PLearn::UnaryVariable.

Definition at line 57 of file MultiMaxVariable.cc.

: in that example matValue.width() of the variable must be 1+2+3=6" );
void PLearn::MultiMaxVariable::hardMax_range ( Vec x,
Vec y,
int  start,
int  length,
bool  value = false 
) [static, private]

Definition at line 310 of file MultiMaxVariable.cc.

References i, and PLearn::Variable::length().

Referenced by fprop().

{
    int indMax=start;
    for(int i=start+1; i<start+length; i++)
        if(x[i] > x[indMax])
            indMax = i;

    for(int i=start; i<start+length; i++)
        y[i] = 0;

    if(value)
        y[indMax] = x[indMax];
    else
        y[indMax]=1;
}

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void PLearn::MultiMaxVariable::logSoftmax_range ( Vec x,
Vec y,
int  start,
int  length 
) [static, private]

Definition at line 300 of file MultiMaxVariable.cc.

References i, PLearn::Variable::length(), PLearn::safeexp(), and PLearn::safelog().

Referenced by fprop().

{
    real somme=0;
    for(int i=start; i<start+length; i++)    
        somme += safeexp(x[i]);
    
    for(int i=start; i<start+length; i++)
        y[i] = x[i] - safelog(somme);
}

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void PLearn::MultiMaxVariable::makeDeepCopyFromShallowCopy ( CopiesMap copies) [virtual]

Transforms a shallow copy into a deep copy.

Reimplemented from PLearn::UnaryVariable.

Definition at line 208 of file MultiMaxVariable.cc.

References PLearn::deepCopyField(), groupsizes, and PLearn::UnaryVariable::makeDeepCopyFromShallowCopy().

{
    inherited::makeDeepCopyFromShallowCopy(copies);

    // ### Call deepCopyField on all "pointer-like" fields
    // ### that you wish to be deepCopied rather than
    // ### shallow-copied.
    // ### ex:
    deepCopyField(groupsizes, copies);
    // ### If you want to deepCopy a Var field:
    // varDeepCopyField(somevariable, copies);   
}

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void PLearn::MultiMaxVariable::recomputeSize ( int l,
int w 
) const [virtual]

Recomputes the length l and width w that this variable should have, according to its parent variables.

This is used for ex. by sizeprop() The default version stupidly returns the current dimensions, so make sure to overload it in subclasses if this is not appropriate.

Reimplemented from PLearn::Variable.

Definition at line 78 of file MultiMaxVariable.cc.

References PLearn::UnaryVariable::input, PLearn::Var::length(), and PLearn::Var::width().

{
        if (input) {
            l = input->length();
            w = input->width() ;
        } else
            l = w = 0;
}

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void PLearn::MultiMaxVariable::softmax_range ( Vec x,
Vec y,
int  start,
int  length 
) [static, private]

Definition at line 289 of file MultiMaxVariable.cc.

References i, PLearn::Variable::length(), PLERROR, and PLearn::safeexp().

Referenced by fprop().

{
    real somme=0;
    for(int i=start; i<start+length; i++)    
        somme +=safeexp(x[i]);
    if (somme == 0) PLERROR("trying to divide by 0 in softmax");

    for(int i=start; i<start+length; i++)
        y[i] = safeexp(x[i])/somme;
}

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Member Data Documentation

Reimplemented from PLearn::UnaryVariable.

Definition at line 116 of file MultiMaxVariable.h.

Definition at line 80 of file MultiMaxVariable.h.

Referenced by bprop(), declareOptions(), and fprop().

Definition at line 81 of file MultiMaxVariable.h.

Referenced by build_(), and declareOptions().

### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //!

group sizes, ex: [2,3,4] = ([x1,x2],[x3,x4,x5],[x6,x7,x8,x9])

Definition at line 79 of file MultiMaxVariable.h.

Referenced by bprop(), build_(), declareOptions(), fprop(), and makeDeepCopyFromShallowCopy().


The documentation for this class was generated from the following files:
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