Added a spec for the structural_svm_assignment_problem and added missing asserts.

dlib/svm/structural_svm_assignment_problem.h

@@ -6,7 +6,6 @@
 
 #include "structural_svm_assignment_problem_abstract.h"
 #include "../matrix.h"
-#include "assignment_function.h"
 #include <vector>
 #include "structural_svm_problem_threaded.h"
 
@@ -46,6 +45,31 @@ namespace dlib
             fe(fe_),
             force_assignment(force_assignment_)
         {
+            // make sure requires clause is not broken
+#ifdef ENABLE_ASSERTS
+            if (force_assignment)
+            {
+                DLIB_ASSERT(is_forced_assignment_problem(samples, labels),
+                            "\t structural_svm_assignment_problem::structural_svm_assignment_problem()"
+                            << "\n\t invalid inputs were given to this function"
+                            << "\n\t is_forced_assignment_problem(samples,labels): " << is_forced_assignment_problem(samples,labels)
+                            << "\n\t is_assignment_problem(samples,labels):        " << is_assignment_problem(samples,labels)
+                            << "\n\t is_learning_problem(samples,labels):          " << is_learning_problem(samples,labels)
+                            << "\n\t this: " << this
+                            );
+            }
+            else
+            {
+                DLIB_ASSERT(is_assignment_problem(samples, labels),
+                            "\t structural_svm_assignment_problem::structural_svm_assignment_problem()"
+                            << "\n\t invalid inputs were given to this function"
+                            << "\n\t is_assignment_problem(samples,labels): " << is_assignment_problem(samples,labels)
+                            << "\n\t is_learning_problem(samples,labels):   " << is_learning_problem(samples,labels)
+                            << "\n\t this: " << this
+                            );
+            }
+#endif
+
         }
 
     private:

dlib/svm/structural_svm_assignment_problem_abstract.h

+// Copyright (C) 2011  Davis E. King (davis@dlib.net)
+// License: Boost Software License   See LICENSE.txt for the full license.
+#undef DLIB_STRUCTURAL_SVM_ASSiGNMENT_PROBLEM_ABSTRACT_H__
+#ifdef DLIB_STRUCTURAL_SVM_ASSiGNMENT_PROBLEM_ABSTRACT_H__
+
+
+#include "../matrix.h"
+#include <vector>
+#include "structural_svm_problem_threaded_abstract.h"
+#include "assignment_function_abstract.h"
+
+// ----------------------------------------------------------------------------------------
+
+namespace dlib
+{
+
+    template <
+        typename feature_extractor
+        >
+    class structural_svm_assignment_problem : noncopyable,
+                                              public structural_svm_problem_threaded<matrix<double,0,1>, 
+                                                     typename feature_extractor::feature_vector_type >
+    {
+        /*!
+            REQUIREMENTS ON feature_extractor
+                It must be an object that implements an interface compatible with 
+                the example_feature_extractor defined in dlib/svm/assignment_function_abstract.h.
+
+            WHAT THIS OBJECT REPRESENTS
+                This object is a tool for learning the weight vector needed to use
+                an assignment_function object.  It learns the parameter vector by 
+                formulating the problem as a structural SVM problem.  
+        !*/
+
+    public:
+        typedef matrix<double,0,1> matrix_type;
+        typedef typename feature_extractor::feature_vector_type feature_vector_type;
+        typedef typename feature_extractor::lhs_element lhs_element;
+        typedef typename feature_extractor::rhs_element rhs_element;
+        typedef std::pair<std::vector<lhs_element>, std::vector<rhs_element> > sample_type;
+        typedef std::vector<long> label_type;
+
+        structural_svm_assignment_problem(
+            const std::vector<sample_type>& samples,
+            const std::vector<label_type>& labels,
+            const feature_extractor& fe,
+            bool force_assignment,
+            unsigned long num_threads = 2
+        );
+        /*!
+            requires
+                - is_assignment_problem(samples,labels) == true
+                - if (force_assignment) then
+                    - is_forced_assignment_problem(samples,labels) == true
+            ensures
+                - This object attempts to learn a mapping from the given samples to the 
+                  given labels.  In particular, it attempts to learn to predict labels[i] 
+                  based on samples[i].  Or in other words, this object can be used to learn 
+                  a parameter vector, w, such that an assignment_function declared as:
+                    assignment_function<feature_extractor> assigner(fe,w,force_assignment)
+                  results in an assigner object which attempts to compute the following mapping:
+                    labels[i] == labeler(samples[i])
+                - This object will use num_threads threads during the optimization 
+                  procedure.  You should set this parameter equal to the number of 
+                  available processing cores on your machine.
+        !*/
+
+    };
+
+// ----------------------------------------------------------------------------------------
+
+}
+
+#endif // DLIB_STRUCTURAL_SVM_ASSiGNMENT_PROBLEM_ABSTRACT_H__
+