[opengm] 129/386: use multiple models in test_learning

[Ghislain Vaillant]

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ghisvail-guest pushed a commit to branch debian/master
in repository opengm.

commit 1a1e177afc6676054990c9f2a1d80010665606da
Author: Jan Funke <funke at ini.ch>
Date:   Thu Dec 18 16:16:55 2014 +0100

    use multiple models in test_learning
---
 src/unittest/learning/test_learning.cxx | 35 +++++++++++++++++----------------
 1 file changed, 18 insertions(+), 17 deletions(-)

diff --git a/src/unittest/learning/test_learning.cxx b/src/unittest/learning/test_learning.cxx
index 99b03ee..2eed459 100644
--- a/src/unittest/learning/test_learning.cxx
+++ b/src/unittest/learning/test_learning.cxx
@@ -48,26 +48,26 @@ int main() {
    std::cout << " Includes are fine :-) " << std::endl; 
 
    {
-	  DSS dataset;
+	  DSS dataset(5);
 	  std::cout << "Dataset includes " << dataset.getNumberOfModels() << " instances and has " << dataset.getNumberOfWeights() << " parameters."<<std::endl;
 	  
 	  
-      opengm::learning::StructMaxMargin<DSS>::Parameter para;
-      opengm::learning::StructMaxMargin<DSS> learner(dataset,para);
+	  opengm::learning::StructMaxMargin<DSS>::Parameter para;
+	  opengm::learning::StructMaxMargin<DSS> learner(dataset,para);
 	  
 	  
 	  INF::Parameter infPara;
 	  infPara.integerConstraint_ = true;
 	  learner.learn<INF>(infPara); 
-          const DSS::Weights& weights = learner.getWeights();
-          std::cout <<"Weights: ";
-          for (size_t i=0; i<weights.numberOfWeights(); ++i)
-             std::cout << weights[i] <<" ";
-          std::cout <<std::endl;
+		  const DSS::Weights& weights = learner.getWeights();
+		  std::cout <<"Weights: ";
+		  for (size_t i=0; i<weights.numberOfWeights(); ++i)
+			 std::cout << weights[i] <<" ";
+		  std::cout <<std::endl;
    }
 
    {
-	  DS1 dataset;
+	  DS1 dataset(4);
 	  std::cout << "Dataset includes " << dataset.getNumberOfModels() << " instances and has " << dataset.getNumberOfWeights() << " parameters."<<std::endl;
 	  
 	  
@@ -87,22 +87,23 @@ int main() {
    }
 
    {
-	  DS2 dataset;
+	  DS2 dataset(4);
 	  std::cout << "Dataset includes " << dataset.getNumberOfModels() << " instances and has " << dataset.getNumberOfWeights() << " parameters."<<std::endl;
 	  
 	  
-      opengm::learning::StructMaxMargin<DS2>::Parameter para;
-      opengm::learning::StructMaxMargin<DS2> learner(dataset,para);
+	  opengm::learning::StructMaxMargin<DS2>::Parameter para;
+	  para.optimizerParameter_.lambda = 1000.0;
+	  opengm::learning::StructMaxMargin<DS2> learner(dataset,para);
 	  
 	  
 	  INF::Parameter infPara;
 	  infPara.integerConstraint_ = true;
 	  learner.learn<INF>(infPara);
-          const DS2::Weights& weights = learner.getWeights();
-          std::cout <<"Weights: ";
-          for (size_t i=0; i<weights.numberOfWeights(); ++i)
-             std::cout << weights[i] <<" ";
-          std::cout <<std::endl;
+		  const DS2::Weights& weights = learner.getWeights();
+		  std::cout <<"Weights: ";
+		  for (size_t i=0; i<weights.numberOfWeights(); ++i)
+			 std::cout << weights[i] <<" ";
+		  std::cout <<std::endl;
    }
 
 

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