PLearn 0.1
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#include <MinusRowVariable.h>
Public Member Functions | |
MinusRowVariable () | |
Default constructor for persistence. | |
MinusRowVariable (Variable *input1, Variable *input2) | |
virtual string | classname () const |
virtual OptionList & | getOptionList () const |
virtual OptionMap & | getOptionMap () const |
virtual RemoteMethodMap & | getRemoteMethodMap () const |
virtual MinusRowVariable * | 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 () |
virtual void | bbprop () |
compute an approximation to diag(d^2/dinput^2) given diag(d^2/doutput^2), with diag(d^2/dinput^2) ~=~ (doutput/dinput)' diag(d^2/doutput^2) (doutput/dinput) In particular: if 'C' depends on 'y' and 'y' depends on x ... | |
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_ () |
MinusRowVariable. | |
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 MinusRowVariable.h.
typedef BinaryVariable PLearn::MinusRowVariable::inherited [private] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 54 of file MinusRowVariable.h.
PLearn::MinusRowVariable::MinusRowVariable | ( | ) | [inline] |
string PLearn::MinusRowVariable::_classname_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 56 of file MinusRowVariable.cc.
OptionList & PLearn::MinusRowVariable::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 56 of file MinusRowVariable.cc.
RemoteMethodMap & PLearn::MinusRowVariable::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 56 of file MinusRowVariable.cc.
Reimplemented from PLearn::BinaryVariable.
Definition at line 56 of file MinusRowVariable.cc.
Object * PLearn::MinusRowVariable::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 56 of file MinusRowVariable.cc.
StaticInitializer MinusRowVariable::_static_initializer_ & PLearn::MinusRowVariable::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 56 of file MinusRowVariable.cc.
void PLearn::MinusRowVariable::bbprop | ( | ) | [virtual] |
compute an approximation to diag(d^2/dinput^2) given diag(d^2/doutput^2), with diag(d^2/dinput^2) ~=~ (doutput/dinput)' diag(d^2/doutput^2) (doutput/dinput) In particular: if 'C' depends on 'y' and 'y' depends on x ...
d^2C/dx^2 = d^2C/dy^2 * (dy/dx)^2 + dC/dy * d^2y/dx^2 (diaghessian) (gradient)
Reimplemented from PLearn::Variable.
Definition at line 113 of file MinusRowVariable.cc.
References PLearn::Variable::diaghessiandata, i, PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, j, PLearn::Var::length(), PLearn::Variable::length(), and PLearn::Variable::width().
{ if (input1->diaghessian.length()==0) input1->resizeDiagHessian(); if (input2->diaghessian.length()==0) input2->resizeDiagHessian(); int k=0; for(int i=0; i<length(); i++) for(int j=0; j<width(); j++, k++) { input1->diaghessiandata[k] += diaghessiandata[k]; input2->diaghessiandata[j] -= diaghessiandata[k]; } }
void PLearn::MinusRowVariable::bprop | ( | ) | [virtual] |
Implements PLearn::Variable.
Definition at line 101 of file MinusRowVariable.cc.
References PLearn::Variable::gradientdata, i, PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, j, PLearn::Variable::length(), and PLearn::Variable::width().
{ int k=0; for(int i=0; i<length(); i++) for(int j=0; j<width(); j++, k++) { input1->gradientdata[k] += gradientdata[k]; input2->gradientdata[j] -= gradientdata[k]; } }
void PLearn::MinusRowVariable::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 65 of file MinusRowVariable.cc.
References PLearn::BinaryVariable::build(), and build_().
{ inherited::build(); build_(); }
void PLearn::MinusRowVariable::build_ | ( | ) | [protected] |
This does the actual building.
Reimplemented from PLearn::BinaryVariable.
Definition at line 72 of file MinusRowVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLERROR, and PLearn::Var::width().
Referenced by build(), and MinusRowVariable().
{ if (input1 && input2) { if(!input2->isRowVec()) PLERROR("IN MinusRowVariable: input2 is not a row"); if(input2->width() != input1->width()) PLERROR("IN MinusRowVariable: input1 and input2 have a different width()"); } }
string PLearn::MinusRowVariable::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 56 of file MinusRowVariable.cc.
static const PPath& PLearn::MinusRowVariable::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 61 of file MinusRowVariable.h.
: void build_();
MinusRowVariable * PLearn::MinusRowVariable::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 56 of file MinusRowVariable.cc.
void PLearn::MinusRowVariable::fprop | ( | ) | [virtual] |
compute output given input
Implements PLearn::Variable.
Definition at line 92 of file MinusRowVariable.cc.
References i, PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, j, PLearn::Variable::length(), PLearn::Variable::valuedata, and PLearn::Variable::width().
{ int k=0; for(int i=0; i<length(); i++) for(int j=0; j<width(); j++, k++) valuedata[k] = input1->valuedata[k] - input2->valuedata[j]; }
OptionList & PLearn::MinusRowVariable::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 56 of file MinusRowVariable.cc.
OptionMap & PLearn::MinusRowVariable::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 56 of file MinusRowVariable.cc.
RemoteMethodMap & PLearn::MinusRowVariable::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 56 of file MinusRowVariable.cc.
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 83 of file MinusRowVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::Var::length(), and PLearn::Var::width().
void PLearn::MinusRowVariable::symbolicBprop | ( | ) | [virtual] |
compute a piece of new Var graph that represents the symbolic derivative of this Var
Reimplemented from PLearn::Variable.
Definition at line 129 of file MinusRowVariable.cc.
References PLearn::columnSum(), PLearn::Variable::g, PLearn::BinaryVariable::input1, and PLearn::BinaryVariable::input2.
Reimplemented from PLearn::BinaryVariable.
Definition at line 61 of file MinusRowVariable.h.