PLearn 0.1
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#include <MiniBatchClassificationLossVariable.h>
Public Member Functions | |
MiniBatchClassificationLossVariable () | |
Default constructor for persistence. | |
MiniBatchClassificationLossVariable (Variable *netout, Variable *classnum) | |
virtual string | classname () const |
virtual OptionList & | getOptionList () const |
virtual OptionMap & | getOptionMap () const |
virtual RemoteMethodMap & | getRemoteMethodMap () const |
virtual MiniBatchClassificationLossVariable * | deepCopy (CopiesMap &copies) const |
virtual void | build () |
Post-constructor. | |
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 () |
compute output given input | |
virtual void | bprop () |
can't bprop through a hard classification error... | |
virtual void | symbolicBprop () |
compute a piece of new Var graph that represents the symbolic derivative of this Var | |
Static Public Member Functions | |
static string | _classname_ () |
MiniBatchClassificationLossVariable. | |
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_ |
Protected Member Functions | |
void | build_ () |
This does the actual building. | |
Private Types | |
typedef BinaryVariable | inherited |
Definition at line 52 of file MiniBatchClassificationLossVariable.h.
typedef BinaryVariable PLearn::MiniBatchClassificationLossVariable::inherited [private] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 54 of file MiniBatchClassificationLossVariable.h.
PLearn::MiniBatchClassificationLossVariable::MiniBatchClassificationLossVariable | ( | ) | [inline] |
Default constructor for persistence.
Definition at line 58 of file MiniBatchClassificationLossVariable.h.
{}
PLearn::MiniBatchClassificationLossVariable::MiniBatchClassificationLossVariable | ( | Variable * | netout, |
Variable * | classnum | ||
) |
Definition at line 55 of file MiniBatchClassificationLossVariable.cc.
References build_().
string PLearn::MiniBatchClassificationLossVariable::_classname_ | ( | ) | [static] |
MiniBatchClassificationLossVariable.
Reimplemented from PLearn::BinaryVariable.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
OptionList & PLearn::MiniBatchClassificationLossVariable::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
RemoteMethodMap & PLearn::MiniBatchClassificationLossVariable::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
Reimplemented from PLearn::BinaryVariable.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
Object * PLearn::MiniBatchClassificationLossVariable::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
StaticInitializer MiniBatchClassificationLossVariable::_static_initializer_ & PLearn::MiniBatchClassificationLossVariable::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
virtual void PLearn::MiniBatchClassificationLossVariable::bprop | ( | ) | [inline, virtual] |
can't bprop through a hard classification error...
Implements PLearn::Variable.
Definition at line 68 of file MiniBatchClassificationLossVariable.h.
{}
void PLearn::MiniBatchClassificationLossVariable::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::BinaryVariable.
Definition at line 62 of file MiniBatchClassificationLossVariable.cc.
References PLearn::BinaryVariable::build(), and build_().
{ inherited::build(); build_(); }
void PLearn::MiniBatchClassificationLossVariable::build_ | ( | ) | [protected] |
This does the actual building.
Reimplemented from PLearn::BinaryVariable.
Definition at line 69 of file MiniBatchClassificationLossVariable.cc.
References PLearn::BinaryVariable::input2, and PLERROR.
Referenced by build(), and MiniBatchClassificationLossVariable().
{ // input2 is classnum from constructor if(input2 && !input2->isVec()) PLERROR("In MiniBatchClassificationLossVariable: classnum must be a vector variable representing the indexs of netout (typically class numbers)"); }
string PLearn::MiniBatchClassificationLossVariable::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
static const PPath& PLearn::MiniBatchClassificationLossVariable::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 61 of file MiniBatchClassificationLossVariable.h.
{}
MiniBatchClassificationLossVariable * PLearn::MiniBatchClassificationLossVariable::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
void PLearn::MiniBatchClassificationLossVariable::fprop | ( | ) | [virtual] |
compute output given input
Implements PLearn::Variable.
Definition at line 86 of file MiniBatchClassificationLossVariable.cc.
References PLearn::argmax(), PLearn::Var::column(), i, PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::Var::length(), n, PLERROR, PLearn::Var::row(), PLearn::Variable::valuedata, and PLearn::Var::width().
{ int n = input2->size(); if(input1->length()==n) for (int i=0; i<n; i++) { int topscorepos = argmax(input1->matValue.row(i)); int num = int(input2->valuedata[i]); valuedata[i] = (topscorepos==num ?0 :1); } else if(input1->width()==n) for (int i=0; i<n; i++) { int topscorepos = argmax(input1->matValue.column(i)); int num = int(input2->valuedata[i]); valuedata[i] = (topscorepos==num ?0 :1); } else PLERROR("In MiniBatchClassificationLossVariable: The length or width of netout doesn't equal to the size of classnum"); }
OptionList & PLearn::MiniBatchClassificationLossVariable::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
OptionMap & PLearn::MiniBatchClassificationLossVariable::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
RemoteMethodMap & PLearn::MiniBatchClassificationLossVariable::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 53 of file MiniBatchClassificationLossVariable.cc.
void PLearn::MiniBatchClassificationLossVariable::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 77 of file MiniBatchClassificationLossVariable.cc.
References PLearn::BinaryVariable::input2, PLearn::Var::length(), and PLearn::Var::width().
void PLearn::MiniBatchClassificationLossVariable::symbolicBprop | ( | ) | [virtual] |
compute a piece of new Var graph that represents the symbolic derivative of this Var
Reimplemented from PLearn::Variable.
Definition at line 107 of file MiniBatchClassificationLossVariable.cc.
References PLERROR.
{ PLERROR("MiniBatchClassificationLossVariable::symbolicBprop not implemented."); }
Reimplemented from PLearn::BinaryVariable.
Definition at line 61 of file MiniBatchClassificationLossVariable.h.