[opengm] 149/386: renamed sum_of_experts to lsum_of_experts for consistency
Ghislain Vaillant
ghisvail-guest at moszumanska.debian.org
Wed Aug 31 08:36:43 UTC 2016
This is an automated email from the git hooks/post-receive script.
ghisvail-guest pushed a commit to branch debian/master
in repository opengm.
commit 87c14d06b1192f830e1d358b203a88105a8481b6
Author: mschiegg <martin.schiegg at iwr.uni-heidelberg.de>
Date: Fri Dec 19 10:27:18 2014 +0100
renamed sum_of_experts to lsum_of_experts for consistency
---
.../{sum_of_experts.hxx => lsum_of_experts.hxx} | 58 +++++++++++-----------
include/opengm/learning/dataset/testdatasets.hxx | 6 +--
.../python/opengm/opengmcore/pyFunctionTypes.cxx | 8 +--
src/unittest/learning/test_dataset.cxx | 4 +-
src/unittest/learning/test_dataset_io.cxx | 4 +-
src/unittest/learning/test_gridsearch_learner.cxx | 4 +-
src/unittest/learning/test_learning.cxx | 4 +-
7 files changed, 44 insertions(+), 44 deletions(-)
diff --git a/include/opengm/functions/learnable/sum_of_experts.hxx b/include/opengm/functions/learnable/lsum_of_experts.hxx
similarity index 77%
rename from include/opengm/functions/learnable/sum_of_experts.hxx
rename to include/opengm/functions/learnable/lsum_of_experts.hxx
index 02d06c6..6b0072b 100644
--- a/include/opengm/functions/learnable/sum_of_experts.hxx
+++ b/include/opengm/functions/learnable/lsum_of_experts.hxx
@@ -1,6 +1,6 @@
#pragma once
-#ifndef OPENGM_LEARNABLE_SUM_OF_EXPERTS_FUNCTION_HXX
-#define OPENGM_LEARNABLE_SUM_OF_EXPERTS_FUNCTION_HXX
+#ifndef OPENGM_LEARNABLE_LSUM_OF_EXPERTS_FUNCTION_HXX
+#define OPENGM_LEARNABLE_LSUM_OF_EXPERTS_FUNCTION_HXX
#include <algorithm>
#include <vector>
@@ -25,16 +25,16 @@ namespace learnable {
///
/// \ingroup functions
template<class T, class I = size_t, class L = size_t>
-class SumOfExperts
- : public opengm::FunctionBase<opengm::functions::learnable::SumOfExperts<T, I, L>, T, I, L>
+class LSumOfExperts
+ : public opengm::FunctionBase<opengm::functions::learnable::LSumOfExperts<T, I, L>, T, I, L>
{
public:
typedef T ValueType;
typedef L LabelType;
typedef I IndexType;
- SumOfExperts();
- SumOfExperts(const std::vector<L>& shape,
+ LSumOfExperts();
+ LSumOfExperts(const std::vector<L>& shape,
const opengm::learning::Weights<T>& weights,
const std::vector<size_t>& weightIDs,
const std::vector<marray::Marray<T> >& feat
@@ -61,13 +61,13 @@ protected:
std::vector<size_t> weightIDs_;
std::vector<marray::Marray<T> > feat_;
- friend class opengm::FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >;
+ friend class opengm::FunctionSerialization<opengm::functions::learnable::LSumOfExperts<T, I, L> >;
};
template <class T, class I, class L>
inline
-SumOfExperts<T, I, L>::SumOfExperts
+LSumOfExperts<T, I, L>::LSumOfExperts
(
const std::vector<L>& shape,
const opengm::learning::Weights<T>& weights,
@@ -82,7 +82,7 @@ SumOfExperts<T, I, L>::SumOfExperts
template <class T, class I, class L>
inline
-SumOfExperts<T, I, L>::SumOfExperts()
+LSumOfExperts<T, I, L>::LSumOfExperts()
: shape_(std::vector<L>(0)), weightIDs_(std::vector<size_t>(0)), feat_(std::vector<marray::Marray<T> >(0))
{
;
@@ -92,7 +92,7 @@ SumOfExperts<T, I, L>::SumOfExperts()
template <class T, class I, class L>
template <class ITERATOR>
inline T
-SumOfExperts<T, I, L>::weightGradient
+LSumOfExperts<T, I, L>::weightGradient
(
size_t weightNumber,
ITERATOR begin
@@ -104,7 +104,7 @@ SumOfExperts<T, I, L>::weightGradient
template <class T, class I, class L>
template <class ITERATOR>
inline T
-SumOfExperts<T, I, L>::operator()
+LSumOfExperts<T, I, L>::operator()
(
ITERATOR begin
) const {
@@ -118,7 +118,7 @@ SumOfExperts<T, I, L>::operator()
template <class T, class I, class L>
inline L
-SumOfExperts<T, I, L>::shape
+LSumOfExperts<T, I, L>::shape
(
const size_t i
) const {
@@ -127,13 +127,13 @@ SumOfExperts<T, I, L>::shape
template <class T, class I, class L>
inline size_t
-SumOfExperts<T, I, L>::dimension() const {
+LSumOfExperts<T, I, L>::dimension() const {
return shape_.size();
}
template <class T, class I, class L>
inline size_t
-SumOfExperts<T, I, L>::size() const {
+LSumOfExperts<T, I, L>::size() const {
size_t s = 1;
for(size_t i=0; i<dimension(); ++i)
s *=shape_[i];
@@ -146,20 +146,20 @@ SumOfExperts<T, I, L>::size() const {
/// FunctionSerialization
template<class T, class I, class L>
-class FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> > {
+class FunctionSerialization<opengm::functions::learnable::LSumOfExperts<T, I, L> > {
public:
- typedef typename opengm::functions::learnable::SumOfExperts<T, I, L>::ValueType ValueType;
+ typedef typename opengm::functions::learnable::LSumOfExperts<T, I, L>::ValueType ValueType;
- static size_t indexSequenceSize(const opengm::functions::learnable::SumOfExperts<T, I, L>&);
- static size_t valueSequenceSize(const opengm::functions::learnable::SumOfExperts<T, I, L>&);
+ static size_t indexSequenceSize(const opengm::functions::learnable::LSumOfExperts<T, I, L>&);
+ static size_t valueSequenceSize(const opengm::functions::learnable::LSumOfExperts<T, I, L>&);
template<class INDEX_OUTPUT_ITERATOR, class VALUE_OUTPUT_ITERATOR>
- static void serialize(const opengm::functions::learnable::SumOfExperts<T, I, L>&, INDEX_OUTPUT_ITERATOR, VALUE_OUTPUT_ITERATOR);
+ static void serialize(const opengm::functions::learnable::LSumOfExperts<T, I, L>&, INDEX_OUTPUT_ITERATOR, VALUE_OUTPUT_ITERATOR);
template<class INDEX_INPUT_ITERATOR, class VALUE_INPUT_ITERATOR>
- static void deserialize( INDEX_INPUT_ITERATOR, VALUE_INPUT_ITERATOR, opengm::functions::learnable::SumOfExperts<T, I, L>&);
+ static void deserialize( INDEX_INPUT_ITERATOR, VALUE_INPUT_ITERATOR, opengm::functions::learnable::LSumOfExperts<T, I, L>&);
};
template<class T, class I, class L>
-struct FunctionRegistration<opengm::functions::learnable::SumOfExperts<T, I, L> > {
+struct FunctionRegistration<opengm::functions::learnable::LSumOfExperts<T, I, L> > {
enum ID {
Id = opengm::FUNCTION_TYPE_ID_OFFSET + 100 + 67
};
@@ -167,18 +167,18 @@ struct FunctionRegistration<opengm::functions::learnable::SumOfExperts<T, I, L>
template<class T, class I, class L>
inline size_t
-FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >::indexSequenceSize
+FunctionSerialization<opengm::functions::learnable::LSumOfExperts<T, I, L> >::indexSequenceSize
(
- const opengm::functions::learnable::SumOfExperts<T, I, L> & src
+ const opengm::functions::learnable::LSumOfExperts<T, I, L> & src
) {
return 1+src.shape_.size()+1+src.weightIDs_.size();
}
template<class T, class I, class L>
inline size_t
-FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >::valueSequenceSize
+FunctionSerialization<opengm::functions::learnable::LSumOfExperts<T, I, L> >::valueSequenceSize
(
- const opengm::functions::learnable::SumOfExperts<T, I, L> & src
+ const opengm::functions::learnable::LSumOfExperts<T, I, L> & src
) {
return src.feat_.size()*src.size();
}
@@ -186,9 +186,9 @@ FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >::val
template<class T, class I, class L>
template<class INDEX_OUTPUT_ITERATOR, class VALUE_OUTPUT_ITERATOR >
inline void
-FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >::serialize
+FunctionSerialization<opengm::functions::learnable::LSumOfExperts<T, I, L> >::serialize
(
- const opengm::functions::learnable::SumOfExperts<T, I, L> & src,
+ const opengm::functions::learnable::LSumOfExperts<T, I, L> & src,
INDEX_OUTPUT_ITERATOR indexOutIterator,
VALUE_OUTPUT_ITERATOR valueOutIterator
) {
@@ -221,11 +221,11 @@ FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >::ser
template<class T, class I, class L>
template<class INDEX_INPUT_ITERATOR, class VALUE_INPUT_ITERATOR >
inline void
-FunctionSerialization<opengm::functions::learnable::SumOfExperts<T, I, L> >::deserialize
+FunctionSerialization<opengm::functions::learnable::LSumOfExperts<T, I, L> >::deserialize
(
INDEX_INPUT_ITERATOR indexInIterator,
VALUE_INPUT_ITERATOR valueInIterator,
- opengm::functions::learnable::SumOfExperts<T, I, L> & dst
+ opengm::functions::learnable::LSumOfExperts<T, I, L> & dst
) {
//read shape
size_t dim = *indexInIterator;
diff --git a/include/opengm/learning/dataset/testdatasets.hxx b/include/opengm/learning/dataset/testdatasets.hxx
index 2753695..7208fda 100644
--- a/include/opengm/learning/dataset/testdatasets.hxx
+++ b/include/opengm/learning/dataset/testdatasets.hxx
@@ -7,7 +7,7 @@
#include <opengm/learning/dataset/dataset.hxx>
#include <opengm/functions/learnable/lpotts.hxx>
-#include <opengm/functions/learnable/sum_of_experts.hxx>
+#include <opengm/functions/learnable/lsum_of_experts.hxx>
namespace opengm {
namespace datasets{
@@ -215,7 +215,7 @@ namespace opengm {
feat[1](1) = std::fabs(val1-1);
std::vector<size_t> wID(2);
wID[0]=1; wID[1]=2;
- opengm::functions::learnable::SumOfExperts<ValueType,IndexType,LabelType> f(shape,this->weights_, wID, feat);
+ opengm::functions::learnable::LSumOfExperts<ValueType,IndexType,LabelType> f(shape,this->weights_, wID, feat);
typename GM::FunctionIdentifier fid = this->gms_[m].addFunction(f);
// factor
@@ -277,7 +277,7 @@ namespace opengm {
feat[1](1) = val1-1;
std::vector<size_t> wID(2);
wID[0]=0; wID[1]=1;
- opengm::functions::learnable::SumOfExperts<ValueType,IndexType,LabelType> f(shape,this->weights_, wID, feat);
+ opengm::functions::learnable::LSumOfExperts<ValueType,IndexType,LabelType> f(shape,this->weights_, wID, feat);
typename GM::FunctionIdentifier fid = this->gms_[m].addFunction(f);
// factor
diff --git a/src/interfaces/python/opengm/opengmcore/pyFunctionTypes.cxx b/src/interfaces/python/opengm/opengmcore/pyFunctionTypes.cxx
index 3615564..70827a0 100644
--- a/src/interfaces/python/opengm/opengmcore/pyFunctionTypes.cxx
+++ b/src/interfaces/python/opengm/opengmcore/pyFunctionTypes.cxx
@@ -28,7 +28,7 @@
#include "opengm/functions/learnable/lpotts.hxx"
#include "opengm/functions/learnable/lunary.hxx"
-#include "opengm/functions/learnable/sum_of_experts.hxx"
+#include "opengm/functions/learnable/lsum_of_experts.hxx"
using namespace boost::python;
@@ -478,7 +478,7 @@ void export_functiontypes(){
typedef opengm::python::PythonFunction <ValueType,IndexType,LabelType> PyPythonFunction;
typedef opengm::functions::learnable::LPotts <ValueType,IndexType,LabelType> PyLPottsFunction;
typedef opengm::functions::learnable::LUnary <ValueType,IndexType,LabelType> PyLUnaryFunction;
- typedef opengm::functions::learnable::SumOfExperts <ValueType,IndexType,LabelType> PySumOfExpertsFunction;
+ typedef opengm::functions::learnable::LSumOfExperts <ValueType,IndexType,LabelType> PyLSumOfExpertsFunction;
// vector exporters
export_function_type_vector<PyExplicitFunction>("ExplicitFunctionVector");
@@ -779,8 +779,8 @@ void export_functiontypes(){
)
;
- FUNCTION_TYPE_EXPORTER_HELPER(PySumOfExpertsFunction,"SumOfExpertsFunction")
- .def("__init__", make_constructor(&pyfunction::sumOfExpertsConstructor<PySumOfExpertsFunction> ,default_call_policies(),
+ FUNCTION_TYPE_EXPORTER_HELPER(PyLSumOfExpertsFunction,"SumOfExpertsFunction")
+ .def("__init__", make_constructor(&pyfunction::sumOfExpertsConstructor<PyLSumOfExpertsFunction> ,default_call_policies(),
(
boost::python::arg("shape"),
boost::python::arg("weight"),
diff --git a/src/unittest/learning/test_dataset.cxx b/src/unittest/learning/test_dataset.cxx
index b00f9d4..f4d5367 100644
--- a/src/unittest/learning/test_dataset.cxx
+++ b/src/unittest/learning/test_dataset.cxx
@@ -9,7 +9,7 @@
#include <opengm/utilities/metaprogramming.hxx>
#include <opengm/functions/learnable/lpotts.hxx>
-#include <opengm/functions/learnable/sum_of_experts.hxx>
+#include <opengm/functions/learnable/lsum_of_experts.hxx>
//#include <opengm/learning/dataset/testdataset.hxx>
//#include <opengm/learning/dataset/testdataset2.hxx>
#include <opengm/learning/dataset/dataset_io.hxx>
@@ -23,7 +23,7 @@
typedef double ValueType;
typedef size_t IndexType;
typedef size_t LabelType;
-typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::SumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
+typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::LSumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
typedef opengm::GraphicalModel<ValueType,opengm::Adder, FunctionListType, opengm::DiscreteSpace<IndexType,LabelType> > GM;
//typedef opengm::datasets::TestDataset<GM> DS1;
//typedef opengm::datasets::Dataset<GM> DS;
diff --git a/src/unittest/learning/test_dataset_io.cxx b/src/unittest/learning/test_dataset_io.cxx
index 53b77b7..aa2a2a5 100644
--- a/src/unittest/learning/test_dataset_io.cxx
+++ b/src/unittest/learning/test_dataset_io.cxx
@@ -9,7 +9,7 @@
#include <opengm/utilities/metaprogramming.hxx>
#include <opengm/functions/learnable/lpotts.hxx>
-#include <opengm/functions/learnable/sum_of_experts.hxx>
+#include <opengm/functions/learnable/lsum_of_experts.hxx>
//#include <opengm/learning/dataset/testdataset.hxx>
//#include <opengm/learning/dataset/testdataset2.hxx>
#include <opengm/learning/dataset/dataset_io.hxx>
@@ -24,7 +24,7 @@
typedef double ValueType;
typedef size_t IndexType;
typedef size_t LabelType;
-typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::SumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
+typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::LSumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
typedef opengm::GraphicalModel<ValueType,opengm::Adder, FunctionListType, opengm::DiscreteSpace<IndexType,LabelType> > GM;
typedef opengm::learning::NoLoss LOSS1;
typedef opengm::learning::HammingLoss LOSS2;
diff --git a/src/unittest/learning/test_gridsearch_learner.cxx b/src/unittest/learning/test_gridsearch_learner.cxx
index f18b7e6..cef54d8 100644
--- a/src/unittest/learning/test_gridsearch_learner.cxx
+++ b/src/unittest/learning/test_gridsearch_learner.cxx
@@ -9,7 +9,7 @@
#include <opengm/utilities/metaprogramming.hxx>
#include <opengm/functions/learnable/lpotts.hxx>
-#include <opengm/functions/learnable/sum_of_experts.hxx>
+#include <opengm/functions/learnable/lsum_of_experts.hxx>
#include <opengm/learning/gridsearch-learning.hxx>
#include <opengm/learning/loss/hammingloss.hxx>
//#include <opengm/learning/dataset/testdataset.hxx>
@@ -21,7 +21,7 @@
typedef double ValueType;
typedef size_t IndexType;
typedef size_t LabelType;
-typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::SumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
+typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::LSumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
typedef opengm::GraphicalModel<ValueType,opengm::Adder, FunctionListType, opengm::DiscreteSpace<IndexType,LabelType> > GM;
//typedef opengm::datasets::TestDataset<GM> DS;
//typedef opengm::datasets::TestDataset2<GM> DS2;
diff --git a/src/unittest/learning/test_learning.cxx b/src/unittest/learning/test_learning.cxx
index 2eed459..0514124 100644
--- a/src/unittest/learning/test_learning.cxx
+++ b/src/unittest/learning/test_learning.cxx
@@ -16,7 +16,7 @@
#include <opengm/functions/learnable/lpotts.hxx>
-#include <opengm/functions/learnable/sum_of_experts.hxx>
+#include <opengm/functions/learnable/lsum_of_experts.hxx>
#include <opengm/learning/struct-max-margin.hxx>
#include <opengm/learning/loss/hammingloss.hxx>
//#include <opengm/learning/dataset/testdataset.hxx>
@@ -28,7 +28,7 @@
typedef double ValueType;
typedef size_t IndexType;
typedef size_t LabelType;
-typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::SumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
+typedef opengm::meta::TypeListGenerator<opengm::ExplicitFunction<ValueType,IndexType,LabelType>, opengm::functions::learnable::LPotts<ValueType,IndexType,LabelType>, opengm::functions::learnable::LSumOfExperts<ValueType,IndexType,LabelType> >::type FunctionListType;
typedef opengm::GraphicalModel<ValueType,opengm::Adder, FunctionListType, opengm::DiscreteSpace<IndexType,LabelType> > GM;
typedef opengm::learning::HammingLoss LOSS;
--
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