[opengm] 145/386: breaks all tests. Revert "changed loss interface"
Ghislain Vaillant
ghisvail-guest at moszumanska.debian.org
Wed Aug 31 08:36:37 UTC 2016
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ghisvail-guest pushed a commit to branch debian/master
in repository opengm.
commit 70431337047c95d92f03fcd7a1cc822fb938639f
Author: mschiegg <martin.schiegg at iwr.uni-heidelberg.de>
Date: Fri Dec 19 10:07:12 2014 +0100
breaks all tests. Revert "changed loss interface"
This reverts commit 9762c5ad12ab680388786a0228d05ab3e8da266a.
---
include/opengm/learning/gridsearch-learning.hxx | 2 +-
include/opengm/learning/loss/generalized-hammingloss.hxx | 10 +++++-----
include/opengm/learning/loss/hammingloss.hxx | 8 ++++----
include/opengm/learning/loss/noloss.hxx | 8 ++++----
src/interfaces/python/opengm/learning/__init__.py | 12 +++++-------
src/interfaces/python/opengm/learning/pyLoss.cxx | 6 +++---
6 files changed, 22 insertions(+), 24 deletions(-)
diff --git a/include/opengm/learning/gridsearch-learning.hxx b/include/opengm/learning/gridsearch-learning.hxx
index 360be57..3650e1e 100644
--- a/include/opengm/learning/gridsearch-learning.hxx
+++ b/include/opengm/learning/gridsearch-learning.hxx
@@ -84,7 +84,7 @@ namespace opengm {
inf.infer();
inf.arg(confs[m]);
const std::vector<typename INF::LabelType>& gt = dataset_.getGT(m);
- loss += lossFunction.loss(dataset_.getModel(m),confs[m].begin(), confs[m].end(), gt.begin(), gt.end());
+ loss += lossFunction.loss(confs[m].begin(), confs[m].end(), gt.begin(), gt.end());
}
// *call visitor*
diff --git a/include/opengm/learning/loss/generalized-hammingloss.hxx b/include/opengm/learning/loss/generalized-hammingloss.hxx
index f7158a3..16ef2ff 100644
--- a/include/opengm/learning/loss/generalized-hammingloss.hxx
+++ b/include/opengm/learning/loss/generalized-hammingloss.hxx
@@ -32,7 +32,7 @@ public:
return nodeLossMultiplier_ < labelLossMultiplier_;
}
bool operator>(const GeneralizedHammingLoss & other) const{
- return nodeLossMultiplier_ > labelLossMultiplier_;
+ nodeLossMultiplier_ > labelLossMultiplier_;
}
/**
@@ -53,8 +53,8 @@ public:
public:
GeneralizedHammingLoss(const Parameter& param = Parameter()) : param_(param){}
- template<class GM, class IT1, class IT2>
- double loss(const GM & gm, IT1 labelBegin, IT1 labelEnd, IT2 GTBegin,IT2 GTEnd) const;
+ template<class IT1, class IT2>
+ double loss(IT1 labelBegin, IT1 labelEnd, IT2 GTBegin,IT2 GTEnd) const;
template<class GM, class IT>
void addLoss(GM& gm, IT GTBegin) const;
@@ -104,8 +104,8 @@ inline void GeneralizedHammingLoss::Parameter::load(const hid_t& groupHandle) {
}
}
-template<class GM, class IT1, class IT2>
-double GeneralizedHammingLoss::loss(const GM & gm, IT1 labelBegin, const IT1 labelEnd, IT2 GTBegin, const IT2 GTEnd) const
+template<class IT1, class IT2>
+double GeneralizedHammingLoss::loss(IT1 labelBegin, const IT1 labelEnd, IT2 GTBegin, const IT2 GTEnd) const
{
double loss = 0.0;
size_t nodeIndex = 0;
diff --git a/include/opengm/learning/loss/hammingloss.hxx b/include/opengm/learning/loss/hammingloss.hxx
index 47e272e..783d615 100644
--- a/include/opengm/learning/loss/hammingloss.hxx
+++ b/include/opengm/learning/loss/hammingloss.hxx
@@ -35,8 +35,8 @@ namespace opengm {
public:
HammingLoss(const Parameter& param = Parameter()) : param_(param){}
- template<class GM, class IT1, class IT2>
- double loss(const GM & gm, IT1 labelBegin, IT1 labelEnd, IT2 GTBegin,IT2 GTEnd) const;
+ template<class IT1, class IT2>
+ double loss(IT1 labelBegin, IT1 labelEnd, IT2 GTBegin,IT2 GTEnd) const;
template<class GM, class IT>
void addLoss(GM& gm, IT GTBegin) const;
@@ -50,8 +50,8 @@ namespace opengm {
marray::hdf5::save(groupHandle,"lossId",name);
}
- template<class GM, class IT1, class IT2>
- double HammingLoss::loss(const GM & gm, IT1 labelBegin, const IT1 labelEnd, IT2 GTBegin, const IT2 GTEnd) const
+ template<class IT1, class IT2>
+ double HammingLoss::loss(IT1 labelBegin, const IT1 labelEnd, IT2 GTBegin, const IT2 GTEnd) const
{
double loss = 0.0;
for(; labelBegin!= labelEnd; ++labelBegin, ++GTBegin){
diff --git a/include/opengm/learning/loss/noloss.hxx b/include/opengm/learning/loss/noloss.hxx
index e207433..bce7acc 100644
--- a/include/opengm/learning/loss/noloss.hxx
+++ b/include/opengm/learning/loss/noloss.hxx
@@ -39,8 +39,8 @@ namespace learning {
}
- template<class GM, class IT1, class IT2>
- double loss(const GM & gm, IT1 labelBegin, IT1 labelEnd, IT2 GTBegin,IT2 GTEnd) const;
+ template<class IT1, class IT2>
+ double loss(IT1 labelBegin, IT1 labelEnd, IT2 GTBegin,IT2 GTEnd) const;
template<class GM, class IT>
void addLoss(GM& gm, IT GTBegin) const;
@@ -55,8 +55,8 @@ namespace learning {
marray::hdf5::save(groupHandle,"lossId",name);
}
- template<class GM, class IT1, class IT2>
- double NoLoss::loss(const GM & gm, IT1 labelBegin, const IT1 labelEnd, IT2 GTBegin, const IT2 GTEnd) const
+ template<class IT1, class IT2>
+ double NoLoss::loss(IT1 labelBegin, const IT1 labelEnd, IT2 GTBegin, const IT2 GTEnd) const
{
double loss = 0.0;
return loss;
diff --git a/src/interfaces/python/opengm/learning/__init__.py b/src/interfaces/python/opengm/learning/__init__.py
index da56988..89f639f 100644
--- a/src/interfaces/python/opengm/learning/__init__.py
+++ b/src/interfaces/python/opengm/learning/__init__.py
@@ -111,25 +111,23 @@ def lPottsFunctions(nFunctions, numberOfLabels, features, weightIds):
raise RuntimeError("not yet implemented")
-def lUnaryFunction(weights, numberOfLabels, features, weightIds):
- assert numberOfLabels >= 2
+def lunaryFunction(weights, numberOfLabels, features, weightIds):
features = numpy.require(features, dtype=value_type)
weightIds = numpy.require(weightIds, dtype=index_type)
-
+
assert features.ndim == weightIds.ndim
if features.ndim == 1 or weightIds.ndim == 1:
- assert numberOfLabels == 2
- assert features.shape[0] == weightIds.shape[0]
+ assert numberOfLabels ==2
features = features.reshape(1,-1)
weightIds = weightIds.reshape(1,-1)
assert features.shape[0] in [numberOfLabels, numberOfLabels-1]
assert weightIds.shape[0] in [numberOfLabels, numberOfLabels-1]
- assert features.shape[1] == weightIds.shape[1]
- return LUnaryFunction(weights=weights, numberOfLabels=int(numberOfLabels),
+
+ return LUnaryFunction(weights=weights, numberOfLabels=numberOfLabels,
features=features, weightIds=weightIds)
diff --git a/src/interfaces/python/opengm/learning/pyLoss.cxx b/src/interfaces/python/opengm/learning/pyLoss.cxx
index 72aa8c5..abfde86 100644
--- a/src/interfaces/python/opengm/learning/pyLoss.cxx
+++ b/src/interfaces/python/opengm/learning/pyLoss.cxx
@@ -38,17 +38,17 @@ void export_loss(){
typedef opengm::learning::GeneralizedHammingLoss::Parameter PyGeneralizedHammingLossParameter;
class_<PyHammingLoss >("HammingLoss")
- .def("loss", &PyHammingLoss::loss<const GM &, Literator,Literator>)
+ .def("loss", &PyHammingLoss::loss<Literator,Literator>)
.def("addLoss", &PyHammingLoss::addLoss<GM, Literator>)
;
class_<PyNoLoss >("NoLoss")
- .def("loss", &PyNoLoss::loss<const GM &,Literator,Literator>)
+ .def("loss", &PyNoLoss::loss<Literator,Literator>)
.def("addLoss", &PyNoLoss::addLoss<GM, Literator>)
;
class_<PyGeneralizedHammingLoss >("GeneralizedHammingLoss", init<PyGeneralizedHammingLossParameter>())
- .def("loss", &PyGeneralizedHammingLoss::loss<const GM &,Literator,Literator>)
+ .def("loss", &PyGeneralizedHammingLoss::loss<Literator,Literator>)
.def("addLoss", &PyGeneralizedHammingLoss::addLoss<GM, Literator>)
;
--
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