[opengm] 01/386: prototype for learnable functions with features

[Ghislain Vaillant]

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

commit c37e05fec44abfa6552aa28d3ec21683fc7ef1aa
Author: joergkappes <kappes at math.uni-heidelberg.de>
Date:   Thu May 15 15:33:24 2014 +0200

    prototype for learnable functions with features
---
 include/opengm/functions/learnablefunction.hxx | 138 +++++++++++++++++++++++++
 1 file changed, 138 insertions(+)

diff --git a/include/opengm/functions/learnablefunction.hxx b/include/opengm/functions/learnablefunction.hxx
new file mode 100644
index 0000000..85d9011
--- /dev/null
+++ b/include/opengm/functions/learnablefunction.hxx
@@ -0,0 +1,138 @@
+#pragma once
+#ifndef OPENGM_LEARNABLE_FEATURE_FUNCTION_HXX
+#define OPENGM_LEARNABLE_FEATURE_FUNCTION_HXX
+
+#include <algorithm>
+#include <vector>
+#include <cmath>
+
+#include "opengm/opengm.hxx"
+#include "opengm/functions/function_registration.hxx"
+#include "opengm/functions/function_properties_base.hxx"
+
+namespace opengm {
+
+/// Learnable feature function for two variables
+///
+/// f(x) = w * A(x) * feat
+///  - w    = parameter vector
+///  - feat = feature vector
+///  - A    = assignment matrix variant to the labeling x
+///
+/// derive from this class and implement the function
+///   paramaterGradient(i,x)= A(x)_{i,*}*feat
+///  
+/// \ingroup functions
+template<class T, class I = size_t, class L = size_t>
+class LearnableFeatureFunction
+: public FunctionBase<LearnableFeatureFunction<T, I, L>, T, I, L>
+{
+public:
+   typedef T ValueType;
+   typedef L LabelType;
+   typedef I IndexType;
+
+   LearnableFeatureFunction(
+      const Parameters<ValueType,IndexType>& parameters,
+      const std::vector<LabelType>& shape,
+      const std::vector<size_t>& parameterIDs,
+      const std::vector<ValueType>& feat
+      );
+   LabelType shape(const size_t) const;
+   size_t size() const;
+   size_t dimension() const;
+   template<class ITERATOR> ValueType operator()(ITERATOR) const;
+ 
+   // parameters
+   size_t numberOfParameters()const
+      {return parameterIDs_.size();}
+   IndexType parameterIndex(const size_t paramNumber)const
+      {return parameterIDs_[i]} //dummy
+   template<class ITERATOR> 
+   ValueType paramaterGradient(size_t,ITERATOR) const;
+
+private:
+   const Parameters<ValueType,IndexType> * parameters_;
+   const std::vector<LabelType> shape_;
+   const std::vector<ValueType> parameterIDs_;
+   const std::vector<ValueType> feat_;
+
+
+friend class FunctionSerialization<LearnableFeatureFunction<T, I, L> > ;
+};
+
+
+template<class T, class I, class L>
+struct FunctionRegistration<LearnableFeatureFunction<T, I, L> > {
+   enum ID {
+      Id = opengm::FUNCTION_TYPE_ID_OFFSET + 100 + 64
+   };
+};
+
+template <class T, class I, class L>
+inline
+LearnableFeatureFunction<T, I, L>::LearnableFeatureFunction
+( 
+   const Parameters<ValueType,IndexType>& parameters,
+   const std::vector<LabelType>& shape,
+   const std::vector<size_t>& parameterIDs,
+   const std::vector<ValueType>& feat
+   )
+   :  parameters_(&parameters), shape_(shape), parameterIDs_(parameterIDs),feat_(feat)
+{}
+
+template <class T, class I, class L>
+template <class ITERATOR>
+inline T
+LearnableFeatureFunction<T, I, L>: paramaterGradient
+(
+   size_t parameterNumber,
+   ITERATOR begin
+) const {
+   OPENGM_ASSERT(parameterNumber< numberOfParameters());
+   return 0; // need to be implemented
+}
+
+
+template <class T, class I, class L>
+template <class ITERATOR>
+inline T
+LearnableFeatureFunction<T, I, L>::operator()
+(
+   ITERATOR begin
+) const {
+   ValueType val = 0;
+   for(size_t i=0;i<param_.size();++i){
+      val += parameters__->getParameter(i) * paramaterGradient(i,begin);
+   }
+}
+
+
+template <class T, class I, class L>
+inline L
+LearnableFeatureFunction<T, I, L>::shape
+(
+   const size_t i
+) const {
+   return shape_[i];
+}
+
+template <class T, class I, class L>
+inline size_t
+LearnableFeatureFunction<T, I, L>::dimension() const {
+   return shape_.size();
+}
+
+template <class T, class I, class L>
+inline size_t
+LearnableFeatureFunction<T, I, L>::size() const {
+   size_t s = 1;
+   for(size_t i=0;i<dimension(); ++i)
+      s *= shape(i);
+   return s;
+}
+
+
+} // namespace opengm
+
+#endif // #ifndef OPENGM_LEARNABLE_FUNCTION_HXX

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