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PLearn 0.1
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Deep Belief Net, possibly supervised, trained only with CD. More...
#include <SemiSupervisedDBN.h>


Public Member Functions | |
| SemiSupervisedDBN () | |
| ### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //! | |
| virtual int | outputsize () const |
| Returns the size of this learner's output, (which typically may depend on its inputsize(), targetsize() and set options). | |
| virtual void | forget () |
| (Re-)initializes the PLearner in its fresh state (that state may depend on the 'seed' option) and sets 'stage' back to 0 (this is the stage of a fresh learner!). | |
| virtual void | train () |
| The role of the train method is to bring the learner up to stage==nstages, updating the train_stats collector with training costs measured on-line in the process. | |
| virtual void | computeOutput (const Vec &input, Vec &output) const |
| Computes the output from the input. | |
| virtual void | computeCostsFromOutputs (const Vec &input, const Vec &output, const Vec &target, Vec &costs) const |
| Computes the costs from already computed output. | |
| virtual TVec< std::string > | getTestCostNames () const |
| Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method). | |
| virtual TVec< std::string > | getTrainCostNames () const |
| Returns the names of the objective costs that the train method computes and for which it updates the VecStatsCollector train_stats. | |
| virtual string | classname () const |
| virtual OptionList & | getOptionList () const |
| virtual OptionMap & | getOptionMap () const |
| virtual RemoteMethodMap & | getRemoteMethodMap () const |
| virtual SemiSupervisedDBN * | deepCopy (CopiesMap &copies) const |
| virtual void | build () |
| Finish building the object; just call inherited::build followed by build_() | |
| virtual void | makeDeepCopyFromShallowCopy (CopiesMap &copies) |
| Transforms a shallow copy into a deep copy. | |
Static Public Member Functions | |
| static string | _classname_ () |
| static OptionList & | _getOptionList_ () |
| static RemoteMethodMap & | _getRemoteMethodMap_ () |
| static Object * | _new_instance_for_typemap_ () |
| static bool | _isa_ (const Object *o) |
| static void | _static_initialize_ () |
| static const PPath & | declaringFile () |
Static Public Attributes | |
| static StaticInitializer | _static_initializer_ |
Static Protected Member Functions | |
| static void | declareOptions (OptionList &ol) |
| Declares the class options. | |
Private Types | |
| typedef PLearner | inherited |
Private Member Functions | |
| void | build_ () |
| This does the actual building. | |
Deep Belief Net, possibly supervised, trained only with CD.
Definition at line 55 of file SemiSupervisedDBN.h.
typedef PLearner PLearn::SemiSupervisedDBN::inherited [private] |
Reimplemented from PLearn::PLearner.
Definition at line 57 of file SemiSupervisedDBN.h.
| PLearn::SemiSupervisedDBN::SemiSupervisedDBN | ( | ) |
### declare public option fields (such as build options) here Start your comments with Doxygen-compatible comments such as //!
Default constructor
Definition at line 50 of file SemiSupervisedDBN.cc.
References PLearn::PLearner::random_gen.
:
learning_rate(0),
n_classes(0),
share_layers(false),
n_layers(0)
{
random_gen = new PRandom();
}
| string PLearn::SemiSupervisedDBN::_classname_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 48 of file SemiSupervisedDBN.cc.
| OptionList & PLearn::SemiSupervisedDBN::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 48 of file SemiSupervisedDBN.cc.
| RemoteMethodMap & PLearn::SemiSupervisedDBN::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 48 of file SemiSupervisedDBN.cc.
Reimplemented from PLearn::PLearner.
Definition at line 48 of file SemiSupervisedDBN.cc.
| Object * PLearn::SemiSupervisedDBN::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 48 of file SemiSupervisedDBN.cc.
| StaticInitializer SemiSupervisedDBN::_static_initializer_ & PLearn::SemiSupervisedDBN::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::PLearner.
Definition at line 48 of file SemiSupervisedDBN.cc.
| void PLearn::SemiSupervisedDBN::build | ( | ) | [virtual] |
Finish building the object; just call inherited::build followed by build_()
Reimplemented from PLearn::PLearner.
Definition at line 140 of file SemiSupervisedDBN.cc.
References PLearn::PLearner::build(), and build_().
{
inherited::build();
build_();
}

| void PLearn::SemiSupervisedDBN::build_ | ( | ) | [private] |
This does the actual building.
Reimplemented from PLearn::PLearner.
Definition at line 73 of file SemiSupervisedDBN.cc.
References i.
Referenced by build().
{
bool rbms_need_build = false;
if (layer_sizes.length() != rbms.size()+1)
rbms_need_build = true;
else
{
n_rbms = rbms.size();
for (int i=0; i<n_rbms; i++)
{
if (layer_sizes[i] != rbms[i]->input_size)
{
rbms_need_build = true;
break;
}
if (layer_is_supervised[i] && (rbms[i]->target_size != n_target))
{
rbms_need_build = true;
break;
}
if (!layer_is_supervised[i] && (rbms[i]->target_size != 0))
{
rbms_need_build = true;
break;
}
if (layer_sizes[i+1] != rbms[i]->hidden_size)
{
rbms_need_build = true;
break;
}
}
}
if (rbms_need_build)
build_rbms();
}

| string PLearn::SemiSupervisedDBN::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 48 of file SemiSupervisedDBN.cc.
| void PLearn::SemiSupervisedDBN::computeCostsFromOutputs | ( | const Vec & | input, |
| const Vec & | output, | ||
| const Vec & | target, | ||
| Vec & | costs | ||
| ) | const [virtual] |
Computes the costs from already computed output.
Implements PLearn::PLearner.
Definition at line 227 of file SemiSupervisedDBN.cc.
{
// Compute the costs from *already* computed output.
// ...
}
Computes the output from the input.
Reimplemented from PLearn::PLearner.
Definition at line 219 of file SemiSupervisedDBN.cc.
{
// Compute the output from the input.
// int nout = outputsize();
// output.resize(nout);
// ...
}
| void PLearn::SemiSupervisedDBN::declareOptions | ( | OptionList & | ol | ) | [static, protected] |
Declares the class options.
Reimplemented from PLearn::PLearner.
Definition at line 59 of file SemiSupervisedDBN.cc.
References PLearn::OptionBase::buildoption, PLearn::declareOption(), and PLearn::PLearner::declareOptions().
{
// declareOption(ol, "myoption", &SemiSupervisedDBN::myoption,
// OptionBase::buildoption,
// "Help text describing this option");
declareOption(ol, "", &SemiSupervisedDBN::,
OptionBase::buildoption,
"");
// Now call the parent class' declareOptions
inherited::declareOptions(ol);
}

| static const PPath& PLearn::SemiSupervisedDBN::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::PLearner.
Definition at line 134 of file SemiSupervisedDBN.h.
:
//##### Protected Options ###############################################
| SemiSupervisedDBN * PLearn::SemiSupervisedDBN::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::PLearner.
Definition at line 48 of file SemiSupervisedDBN.cc.
| void PLearn::SemiSupervisedDBN::forget | ( | ) | [virtual] |
(Re-)initializes the PLearner in its fresh state (that state may depend on the 'seed' option) and sets 'stage' back to 0 (this is the stage of a fresh learner!).
(Re-)initialize the PLearner in its fresh state (that state may depend on the 'seed' option) and sets 'stage' back to 0 (this is the stage of a fresh learner!)
A typical forget() method should do the following:
Reimplemented from PLearn::PLearner.
Definition at line 168 of file SemiSupervisedDBN.cc.
References PLearn::PLearner::forget().
{
inherited::forget();
}

| OptionList & PLearn::SemiSupervisedDBN::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 48 of file SemiSupervisedDBN.cc.
| OptionMap & PLearn::SemiSupervisedDBN::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 48 of file SemiSupervisedDBN.cc.
| RemoteMethodMap & PLearn::SemiSupervisedDBN::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 48 of file SemiSupervisedDBN.cc.
| TVec< string > PLearn::SemiSupervisedDBN::getTestCostNames | ( | ) | const [virtual] |
Returns the names of the costs computed by computeCostsFromOutpus (and thus the test method).
Implements PLearn::PLearner.
Definition at line 234 of file SemiSupervisedDBN.cc.
{
// Return the names of the costs computed by computeCostsFromOutputs
// (these may or may not be exactly the same as what's returned by
// getTrainCostNames).
// ...
}
| TVec< string > PLearn::SemiSupervisedDBN::getTrainCostNames | ( | ) | const [virtual] |
Returns the names of the objective costs that the train method computes and for which it updates the VecStatsCollector train_stats.
Implements PLearn::PLearner.
Definition at line 242 of file SemiSupervisedDBN.cc.
{
// Return the names of the objective costs that the train method computes
// and for which it updates the VecStatsCollector train_stats
// (these may or may not be exactly the same as what's returned by
// getTestCostNames).
// ...
}
| void PLearn::SemiSupervisedDBN::makeDeepCopyFromShallowCopy | ( | CopiesMap & | copies | ) | [virtual] |
Transforms a shallow copy into a deep copy.
Reimplemented from PLearn::PLearner.
Definition at line 147 of file SemiSupervisedDBN.cc.
References PLearn::PLearner::makeDeepCopyFromShallowCopy(), and PLERROR.
{
inherited::makeDeepCopyFromShallowCopy(copies);
// ### Call deepCopyField on all "pointer-like" fields
// ### that you wish to be deepCopied rather than
// ### shallow-copied.
// ### ex:
// deepCopyField(trainvec, copies);
// ### Remove this line when you have fully implemented this method.
PLERROR("SemiSupervisedDBN::makeDeepCopyFromShallowCopy not fully (correctly) implemented yet!");
}

| int PLearn::SemiSupervisedDBN::outputsize | ( | ) | const [virtual] |
Returns the size of this learner's output, (which typically may depend on its inputsize(), targetsize() and set options).
Implements PLearn::PLearner.
Definition at line 162 of file SemiSupervisedDBN.cc.
{
// Compute and return the size of this learner's output (which typically
// may depend on its inputsize(), targetsize() and set options).
}
| void PLearn::SemiSupervisedDBN::train | ( | ) | [virtual] |
The role of the train method is to bring the learner up to stage==nstages, updating the train_stats collector with training costs measured on-line in the process.
Implements PLearn::PLearner.
Definition at line 183 of file SemiSupervisedDBN.cc.
{
// The role of the train method is to bring the learner up to
// stage==nstages, updating train_stats with training costs measured
// on-line in the process.
/* TYPICAL CODE:
static Vec input; // static so we don't reallocate memory each time...
static Vec target; // (but be careful that static means shared!)
input.resize(inputsize()); // the train_set's inputsize()
target.resize(targetsize()); // the train_set's targetsize()
real weight;
// This generic PLearner method does a number of standard stuff useful for
// (almost) any learner, and return 'false' if no training should take
// place. See PLearner.h for more details.
if (!initTrain())
return;
while(stage<nstages)
{
// clear statistics of previous epoch
train_stats->forget();
//... train for 1 stage, and update train_stats,
// using train_set->getExample(input, target, weight)
// and train_stats->update(train_costs)
++stage;
train_stats->finalize(); // finalize statistics for this epoch
}
*/
}
Reimplemented from PLearn::PLearner.
Definition at line 134 of file SemiSupervisedDBN.h.
1.7.4