PLearn 0.1
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Matrix product between matrix1 and transpose of matrix2. More...
#include <ProductTransposeVariable.h>
Public Member Functions | |
ProductTransposeVariable () | |
Default constructor for persistence. | |
ProductTransposeVariable (Variable *matrix1, Variable *matrix2) | |
virtual string | classname () const |
virtual OptionList & | getOptionList () const |
virtual OptionMap & | getOptionMap () const |
virtual RemoteMethodMap & | getRemoteMethodMap () const |
virtual ProductTransposeVariable * | 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 | |
virtual void | rfprop () |
Static Public Member Functions | |
static string | _classname_ () |
ProductTransposeVariable. | |
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 |
Matrix product between matrix1 and transpose of matrix2.
Definition at line 53 of file ProductTransposeVariable.h.
typedef BinaryVariable PLearn::ProductTransposeVariable::inherited [private] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 55 of file ProductTransposeVariable.h.
PLearn::ProductTransposeVariable::ProductTransposeVariable | ( | ) | [inline] |
PLearn::ProductTransposeVariable::ProductTransposeVariable | ( | Variable * | matrix1, |
Variable * | matrix2 | ||
) |
Definition at line 60 of file ProductTransposeVariable.cc.
References build_().
string PLearn::ProductTransposeVariable::_classname_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 58 of file ProductTransposeVariable.cc.
OptionList & PLearn::ProductTransposeVariable::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 58 of file ProductTransposeVariable.cc.
RemoteMethodMap & PLearn::ProductTransposeVariable::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 58 of file ProductTransposeVariable.cc.
Reimplemented from PLearn::BinaryVariable.
Definition at line 58 of file ProductTransposeVariable.cc.
Object * PLearn::ProductTransposeVariable::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ProductTransposeVariable.cc.
StaticInitializer ProductTransposeVariable::_static_initializer_ & PLearn::ProductTransposeVariable::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 58 of file ProductTransposeVariable.cc.
void PLearn::ProductTransposeVariable::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 111 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::Var::length(), PLearn::Variable::matGradient, PLearn::product2Acc(), and PLearn::transposeProduct2Acc().
{ if (input1->diaghessian.length()==0) input1->resizeDiagHessian(); if (input2->diaghessian.length()==0) input2->resizeDiagHessian(); // d^2C/dinput1[i,k]^2 += sum_j d^2C/dm[i,j]^2 input2[j,k]^2 product2Acc(input1->matGradient, matGradient,input2->matValue); // d^2C/dinput2[j,k]^2 += sum_i d^C/dm[i,j]^2 input1[i,k]^2 transposeProduct2Acc(input2->matGradient, matGradient,input1->matValue); }
void PLearn::ProductTransposeVariable::bprop | ( | ) | [virtual] |
Implements PLearn::Variable.
Definition at line 102 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::Variable::matGradient, PLearn::productAcc(), and PLearn::transposeProductAcc().
{ // dC/dinput1[i,k] += sum_j dC/dm[i,j] input2[j,k] productAcc(input1->matGradient, matGradient,input2->matValue); // dC/dinput2[j,k] += sum_i dC/dm[i,j] itnput1[i,k] transposeProductAcc(input2->matGradient, matGradient,input1->matValue); }
void PLearn::ProductTransposeVariable::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 67 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::build(), and build_().
{ inherited::build(); build_(); }
void PLearn::ProductTransposeVariable::build_ | ( | ) | [protected] |
This does the actual building.
Reimplemented from PLearn::BinaryVariable.
Definition at line 74 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLERROR, and PLearn::Var::width().
Referenced by build(), and ProductTransposeVariable().
{ if (input1 && input2) { // input1 and input2 are (respectively) m1 and m2 from constructor if (input1->width() != input2->width()) PLERROR("In ProductVariable: the size of m1 and m2 are not compatible for a matrix product"); } }
string PLearn::ProductTransposeVariable::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ProductTransposeVariable.cc.
static const PPath& PLearn::ProductTransposeVariable::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 62 of file ProductTransposeVariable.h.
: void build_();
ProductTransposeVariable * PLearn::ProductTransposeVariable::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::BinaryVariable.
Definition at line 58 of file ProductTransposeVariable.cc.
void PLearn::ProductTransposeVariable::fprop | ( | ) | [virtual] |
compute output given input
Implements PLearn::Variable.
Definition at line 95 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::Variable::matValue, and PLearn::productTranspose().
{ // m[i,j] = sum_k input1[i,k] * input2[j,k] productTranspose(matValue, input1->matValue,input2->matValue); }
OptionList & PLearn::ProductTransposeVariable::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ProductTransposeVariable.cc.
OptionMap & PLearn::ProductTransposeVariable::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ProductTransposeVariable.cc.
RemoteMethodMap & PLearn::ProductTransposeVariable::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 58 of file ProductTransposeVariable.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 84 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::Var::length(), PLERROR, and PLearn::Var::width().
{ if (input1 && input2) { if (input1->width() != input2->width()) PLERROR("In ProductVariable: the size of m1 and m2 are not compatible for a matrix product"); l = input1->length(); w = input2->length(); } else l = w = 0; }
void PLearn::ProductTransposeVariable::rfprop | ( | ) | [virtual] |
Reimplemented from PLearn::Variable.
Definition at line 133 of file ProductTransposeVariable.cc.
References PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::TVec< T >::length(), PLearn::Variable::matRValue, PLearn::productTranspose(), PLearn::productTransposeAcc(), PLearn::BinaryVariable::resizeRValue(), and PLearn::Variable::rValue.
{ if (rValue.length()==0) resizeRValue(); productTranspose(matRValue, input1->matRValue,input2->matValue); productTransposeAcc(matRValue, input1->matValue,input2->matRValue); }
void PLearn::ProductTransposeVariable::symbolicBprop | ( | ) | [virtual] |
compute a piece of new Var graph that represents the symbolic derivative of this Var
Reimplemented from PLearn::Variable.
Definition at line 124 of file ProductTransposeVariable.cc.
References PLearn::Variable::g, PLearn::BinaryVariable::input1, PLearn::BinaryVariable::input2, PLearn::product(), and PLearn::transposeProduct().
{ // dC/dinput1[i,k] += sum_j dC/dm[i,j] input2[j,k] input1->accg(product(g, input2)); // dC/dinput2[j,k] += sum_i dC/dm[i,j] itnput1[i,k] input2->accg(transposeProduct(g,input1)); }
Reimplemented from PLearn::BinaryVariable.
Definition at line 62 of file ProductTransposeVariable.h.