PLearn 0.1
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This class propagates a (possibly scaled) 'tanh' function. More...
#include <TanhModule.h>
Public Member Functions | |
TanhModule () | |
Default constructor. | |
virtual void | fprop (const Vec &input, Vec &output) const |
given the input, compute the output (possibly resize it appropriately) SOON TO BE DEPRECATED, USE fprop(const TVec<Mat*>& ports_value) | |
virtual void | fprop (const Mat &inputs, Mat &outputs) |
Mini-batch fprop. | |
virtual void | bpropUpdate (const Vec &input, const Vec &output, const Vec &output_gradient) |
SOON TO BE DEPRECATED, USE bpropAccUpdate(const TVec<Mat*>& ports_value, const TVec<Mat*>& ports_gradient) Adapt based on the output gradient: this method should only be called just after a corresponding fprop; it should be called with the same arguments as fprop for the first two arguments (and output should not have been modified since then). | |
virtual void | bpropUpdate (const Mat &inputs, const Mat &outputs, Mat &input_gradients, const Mat &output_gradients, bool accumulate=false) |
SOON TO BE DEPRECATED, USE bpropAccUpdate(const TVec<Mat*>& ports_value, const TVec<Mat*>& ports_gradient) | |
virtual void | bpropUpdate (const Vec &input, const Vec &output, Vec &input_gradient, const Vec &output_gradient, bool accumulate=false) |
SOON TO BE DEPRECATED, USE bpropAccUpdate(const TVec<Mat*>& ports_value, const TVec<Mat*>& ports_gradient) this version allows to obtain the input gradient as well N.B. | |
virtual void | bbpropUpdate (const Vec &input, const Vec &output, const Vec &output_gradient, const Vec &output_diag_hessian) |
Similar to bpropUpdate, but adapt based also on the estimation of the diagonal of the Hessian matrix, and propagates this back. | |
virtual void | bbpropUpdate (const Vec &input, const Vec &output, Vec &input_gradient, const Vec &output_gradient, Vec &input_diag_hessian, const Vec &output_diag_hessian, bool accumulate=false) |
this version allows to obtain the input gradient and diag_hessian The flag indicates whether the input_gradient and input_diag_hessian gets accumulated into or set with the computed derivatives. | |
virtual void | forget () |
reset the parameters to the state they would be BEFORE starting training. | |
virtual string | classname () const |
virtual OptionList & | getOptionList () const |
virtual OptionMap & | getOptionMap () const |
virtual RemoteMethodMap & | getRemoteMethodMap () const |
virtual TanhModule * | deepCopy (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_ () |
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 () |
Public Attributes | |
real | in_scale |
real | ex_scale |
Static Public Attributes | |
static StaticInitializer | _static_initializer_ |
Static Protected Member Functions | |
static void | declareOptions (OptionList &ol) |
Declares the class options. | |
Private Types | |
typedef OnlineLearningModule | inherited |
Private Member Functions | |
void | build_ () |
This does the actual building. |
This class propagates a (possibly scaled) 'tanh' function.
The output is ex_scale( in_scale * input ), for each coordinate. Usually in_scale = ex_scale = 1, but the values in_scale = 2/3 and ex_scale = 1.7159 are also used.
Definition at line 59 of file TanhModule.h.
typedef OnlineLearningModule PLearn::TanhModule::inherited [private] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 61 of file TanhModule.h.
PLearn::TanhModule::TanhModule | ( | ) |
string PLearn::TanhModule::_classname_ | ( | ) | [static] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 55 of file TanhModule.cc.
OptionList & PLearn::TanhModule::_getOptionList_ | ( | ) | [static] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 55 of file TanhModule.cc.
RemoteMethodMap & PLearn::TanhModule::_getRemoteMethodMap_ | ( | ) | [static] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 55 of file TanhModule.cc.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 55 of file TanhModule.cc.
Object * PLearn::TanhModule::_new_instance_for_typemap_ | ( | ) | [static] |
Reimplemented from PLearn::Object.
Definition at line 55 of file TanhModule.cc.
StaticInitializer TanhModule::_static_initializer_ & PLearn::TanhModule::_static_initialize_ | ( | ) | [static] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 55 of file TanhModule.cc.
void PLearn::TanhModule::bbpropUpdate | ( | const Vec & | input, |
const Vec & | output, | ||
const Vec & | output_gradient, | ||
const Vec & | output_diag_hessian | ||
) | [virtual] |
Similar to bpropUpdate, but adapt based also on the estimation of the diagonal of the Hessian matrix, and propagates this back.
If these methods are defined, you can use them INSTEAD of bpropUpdate(...) THE DEFAULT IMPLEMENTATION PROVIDED HERE JUST CALLS bbpropUpdate(input, output, input_gradient, output_gradient, in_hess, out_hess) AND IGNORES INPUT HESSIAN AND INPUT GRADIENT
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 190 of file TanhModule.cc.
References bpropUpdate(), PLearn::OnlineLearningModule::output_size, PLERROR, and PLearn::TVec< T >::size().
{ int odh_size = output_diag_hessian.size(); if( odh_size != output_size ) { PLERROR("TanhModule::bbpropUpdate : 'output_diag_hessian.size()'\n" " should be equal to 'output_size' (%i != %i)\n", odh_size, output_size); } bpropUpdate( input, output, output_gradient ); }
void PLearn::TanhModule::bbpropUpdate | ( | const Vec & | input, |
const Vec & | output, | ||
Vec & | input_gradient, | ||
const Vec & | output_gradient, | ||
Vec & | input_diag_hessian, | ||
const Vec & | output_diag_hessian, | ||
bool | accumulate = false |
||
) | [virtual] |
this version allows to obtain the input gradient and diag_hessian The flag indicates whether the input_gradient and input_diag_hessian gets accumulated into or set with the computed derivatives.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 207 of file TanhModule.cc.
References bpropUpdate(), PLearn::TVec< T >::clear(), PLearn::OnlineLearningModule::estimate_simpler_diag_hessian, ex_scale, i, in_scale, PLearn::OnlineLearningModule::input_size, PLearn::OnlineLearningModule::output_size, PLASSERT_MSG, PLERROR, PLearn::TVec< T >::resize(), and PLearn::TVec< T >::size().
{ int odh_size = output_diag_hessian.size(); // size check // others size checks will be done in bpropUpdate() if( odh_size != output_size ) { PLERROR("TanhModule::bbpropUpdate : 'output_diag_hessian.size()'\n" " should be equal to 'output_size' (%i != %i)\n", odh_size, output_size); } if( accumulate ) { PLASSERT_MSG( input_diag_hessian.size() == input_size, "Cannot resize input_diag_hessian AND accumulate into it" ); } else { input_diag_hessian.resize( input_size ); input_diag_hessian.clear(); } for( int i=0 ; i<input_size ; i++ ) { real output_i = output[i]; real fprime_i = in_scale * (ex_scale-output_i*output_i / ex_scale); if( estimate_simpler_diag_hessian ) input_diag_hessian[i] += fprime_i*fprime_i*output_diag_hessian[i]; else input_diag_hessian[i] += fprime_i*fprime_i*output_diag_hessian[i] - 2*in_scale/ex_scale*fprime_i*output_i*output_gradient[i]; } bpropUpdate( input, output, input_gradient, output_gradient, accumulate ); }
void PLearn::TanhModule::bpropUpdate | ( | const Mat & | inputs, |
const Mat & | outputs, | ||
Mat & | input_gradients, | ||
const Mat & | output_gradients, | ||
bool | accumulate = false |
||
) | [virtual] |
SOON TO BE DEPRECATED, USE bpropAccUpdate(const TVec<Mat*>& ports_value, const TVec<Mat*>& ports_gradient)
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 96 of file TanhModule.cc.
References bpropUpdate(), i, PLearn::OnlineLearningModule::input_size, PLearn::TMat< T >::length(), PLASSERT, and PLearn::TMat< T >::resize().
{ int mbs=inputs.length(); PLASSERT(mbs==outputs.length() && mbs==output_gradients.length()); input_gradients.resize(mbs,input_size); for (int i=0;i<mbs;i++) { Vec in_i = inputs(i); Vec out_i = outputs(i); Vec gin_i = input_gradients(i); Vec gout_i = output_gradients(i); bpropUpdate(in_i,out_i,gin_i,gout_i, accumulate); } }
void PLearn::TanhModule::bpropUpdate | ( | const Vec & | input, |
const Vec & | output, | ||
Vec & | input_gradient, | ||
const Vec & | output_gradient, | ||
bool | accumulate = false |
||
) | [virtual] |
SOON TO BE DEPRECATED, USE bpropAccUpdate(const TVec<Mat*>& ports_value, const TVec<Mat*>& ports_gradient) this version allows to obtain the input gradient as well N.B.
THE DEFAULT IMPLEMENTATION JUST RAISES A PLERROR. The flag indicates whether the input_gradients gets accumulated into or set with the computed derivatives.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 143 of file TanhModule.cc.
References PLearn::TVec< T >::clear(), ex_scale, i, in_scale, PLearn::OnlineLearningModule::input_size, PLearn::OnlineLearningModule::output_size, PLASSERT_MSG, PLERROR, PLearn::TVec< T >::resize(), and PLearn::TVec< T >::size().
{ int in_size = input.size(); int out_size = output.size(); int og_size = output_gradient.size(); // size check if( in_size != input_size ) { PLERROR("TanhModule::bpropUpdate: 'input.size()' should be equal\n" " to 'input_size' (%i != %i)\n", in_size, input_size); } if( out_size != output_size ) { PLERROR("TanhModule::bpropUpdate: 'output.size()' should be equal\n" " to 'output_size' (%i != %i)\n", out_size, output_size); } if( og_size != output_size ) { PLERROR("TanhModule::bpropUpdate: 'output_gradient.size()' should\n" " be equal to 'output_size' (%i != %i)\n", og_size, output_size); } if( accumulate ) { PLASSERT_MSG( input_gradient.size() == input_size, "Cannot resize input_gradient AND accumulate into it" ); } else { input_gradient.resize( input_size ); input_gradient.clear(); } for( int i=0 ; i<input_size ; i++ ) { real output_i = output[i]; input_gradient[i] += in_scale * (ex_scale - output_i*output_i/ex_scale)*output_gradient[i]; } }
void PLearn::TanhModule::bpropUpdate | ( | const Vec & | input, |
const Vec & | output, | ||
const Vec & | output_gradient | ||
) | [virtual] |
SOON TO BE DEPRECATED, USE bpropAccUpdate(const TVec<Mat*>& ports_value, const TVec<Mat*>& ports_gradient) Adapt based on the output gradient: this method should only be called just after a corresponding fprop; it should be called with the same arguments as fprop for the first two arguments (and output should not have been modified since then).
Since sub-classes are supposed to learn ONLINE, the object is 'ready-to-be-used' just after any bpropUpdate. N.B. The DEFAULT IMPLEMENTATION JUST CALLS bpropUpdate(input, output, input_gradient, output_gradient) AND IGNORES INPUT GRADIENT.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 116 of file TanhModule.cc.
References PLearn::OnlineLearningModule::input_size, PLearn::OnlineLearningModule::output_size, PLERROR, and PLearn::TVec< T >::size().
Referenced by bbpropUpdate(), and bpropUpdate().
{ int in_size = input.size(); int out_size = output.size(); int og_size = output_gradient.size(); // size check if( in_size != input_size ) { PLERROR("TanhModule::bpropUpdate: 'input.size()' should be equal\n" " to 'input_size' (%i != %i)\n", in_size, input_size); } if( out_size != output_size ) { PLERROR("TanhModule::bpropUpdate: 'output.size()' should be equal\n" " to 'output_size' (%i != %i)\n", out_size, output_size); } if( og_size != output_size ) { PLERROR("TanhModule::bpropUpdate: 'output_gradient.size()' should\n" " be equal to 'output_size' (%i != %i)\n", og_size, output_size); } }
void PLearn::TanhModule::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::OnlineLearningModule.
Definition at line 261 of file TanhModule.cc.
References PLearn::OnlineLearningModule::build(), and build_().
{ inherited::build(); build_(); }
void PLearn::TanhModule::build_ | ( | ) | [private] |
This does the actual building.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 290 of file TanhModule.cc.
References PLearn::OnlineLearningModule::input_size, PLearn::OnlineLearningModule::output_size, and PLERROR.
Referenced by build().
{ if( input_size < 0 ) PLERROR("TanhModule::build_: 'input_size' (%d) < 0", input_size); output_size = input_size; }
string PLearn::TanhModule::classname | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 55 of file TanhModule.cc.
void PLearn::TanhModule::declareOptions | ( | OptionList & | ol | ) | [static, protected] |
Declares the class options.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 272 of file TanhModule.cc.
References PLearn::OptionBase::buildoption, PLearn::declareOption(), PLearn::OnlineLearningModule::declareOptions(), ex_scale, in_scale, PLearn::OptionBase::learntoption, PLearn::OnlineLearningModule::output_size, and PLearn::redeclareOption().
{ declareOption(ol, "in_scale", &TanhModule::in_scale, OptionBase::buildoption, "Inner scale"); declareOption(ol, "ex_scale", &TanhModule::ex_scale, OptionBase::buildoption, "External scale"); inherited::declareOptions(ol); redeclareOption(ol, "output_size", &TanhModule::output_size, OptionBase::learntoption, "output_size = input_size"); }
static const PPath& PLearn::TanhModule::declaringFile | ( | ) | [inline, static] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 106 of file TanhModule.h.
:
//##### Protected Options ###############################################
TanhModule * PLearn::TanhModule::deepCopy | ( | CopiesMap & | copies | ) | const [virtual] |
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 55 of file TanhModule.cc.
void PLearn::TanhModule::forget | ( | ) | [virtual] |
reset the parameters to the state they would be BEFORE starting training.
Note that this method is necessarily called from build().
Implements PLearn::OnlineLearningModule.
Definition at line 256 of file TanhModule.cc.
{}
Mini-batch fprop.
Default implementation raises an error. SOON TO BE DEPRECATED, USE fprop(const TVec<Mat*>& ports_value)
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 84 of file TanhModule.cc.
References fprop(), i, PLearn::TMat< T >::length(), PLearn::OnlineLearningModule::output_size, and PLearn::TMat< T >::resize().
{ int mbs=inputs.length(); outputs.resize(mbs,output_size); for (int i=0;i<mbs;i++) { Vec in_i = inputs(i); Vec out_i = outputs(i); fprop(in_i,out_i); } }
given the input, compute the output (possibly resize it appropriately) SOON TO BE DEPRECATED, USE fprop(const TVec<Mat*>& ports_value)
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 64 of file TanhModule.cc.
References ex_scale, PLearn::fasttanh(), i, in_scale, PLearn::OnlineLearningModule::input_size, PLearn::OnlineLearningModule::output_size, PLERROR, PLearn::TVec< T >::resize(), PLearn::TVec< T >::size(), PLearn::tanh(), and PLearn::OnlineLearningModule::use_fast_approximations.
Referenced by fprop().
{ int in_size = input.size(); // size check if( in_size != input_size ) { PLERROR("TanhModule::fprop: 'input.size()' should be equal\n" " to 'input_size' (%i != %i)\n", in_size, input_size); } output.resize( output_size ); if (use_fast_approximations) for( int i=0 ; i<output_size ; i++ ) output[i] = ex_scale * fasttanh( in_scale * input[i] ); else for( int i=0 ; i<output_size ; i++ ) output[i] = ex_scale * tanh( in_scale * input[i] ); }
OptionList & PLearn::TanhModule::getOptionList | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 55 of file TanhModule.cc.
OptionMap & PLearn::TanhModule::getOptionMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 55 of file TanhModule.cc.
RemoteMethodMap & PLearn::TanhModule::getRemoteMethodMap | ( | ) | const [virtual] |
Reimplemented from PLearn::Object.
Definition at line 55 of file TanhModule.cc.
void PLearn::TanhModule::makeDeepCopyFromShallowCopy | ( | CopiesMap & | copies | ) | [virtual] |
Transforms a shallow copy into a deep copy.
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 267 of file TanhModule.cc.
References PLearn::OnlineLearningModule::makeDeepCopyFromShallowCopy().
{ inherited::makeDeepCopyFromShallowCopy(copies); }
Reimplemented from PLearn::OnlineLearningModule.
Definition at line 106 of file TanhModule.h.
Definition at line 66 of file TanhModule.h.
Referenced by bbpropUpdate(), bpropUpdate(), declareOptions(), and fprop().
Definition at line 65 of file TanhModule.h.
Referenced by bbpropUpdate(), bpropUpdate(), declareOptions(), and fprop().