Made the sequence trainer use the reject_labeling() information from

the feature extractor.  Also added the necessary input validation
to make sure this feature doesn't get misused.

dlib/svm/structural_sequence_labeling_trainer.h

@@ -143,11 +143,14 @@ namespace dlib
         {
 
             // make sure requires clause is not broken
-            DLIB_ASSERT(is_sequence_labeling_problem(x,y) == true,
+            DLIB_ASSERT(is_sequence_labeling_problem(x,y) == true &&
+                        contains_invalid_labeling(get_feature_extractor(), x, y) == false,
                         "\t sequence_labeler structural_sequence_labeling_trainer::train(x,y)"
                         << "\n\t invalid inputs were given to this function"
                         << "\n\t x.size(): " << x.size() 
                         << "\n\t is_sequence_labeling_problem(x,y): " << is_sequence_labeling_problem(x,y)
+                        << "\n\t contains_invalid_labeling(get_feature_extractor(),x,y): " << contains_invalid_labeling(get_feature_extractor(),x,y)
+                        << "\n\t this: " << this
             );
 
 #ifdef ENABLE_ASSERTS

dlib/svm/structural_sequence_labeling_trainer_abstract.h

@@ -197,7 +197,8 @@ namespace dlib
         ) const;
         /*!
             requires
-                - is_sequence_labeling_problem(x, y)
+                - is_sequence_labeling_problem(x, y) == true
+                - contains_invalid_labeling(get_feature_extractor(), x, y) == false
                 - for all valid i and j: y[i][j] < num_labels()
             ensures
                 - Uses the structural_svm_sequence_labeling_problem to train a 

dlib/svm/structural_svm_sequence_labeling_problem.h

@@ -85,11 +85,13 @@ namespace dlib
             fe(fe_)
         {
             // make sure requires clause is not broken
-            DLIB_ASSERT(is_sequence_labeling_problem(samples,labels) == true,
+            DLIB_ASSERT(is_sequence_labeling_problem(samples,labels) == true &&
+                        contains_invalid_labeling(fe, samples, labels) == false,
                         "\t structural_svm_sequence_labeling_problem::structural_svm_sequence_labeling_problem()"
                         << "\n\t invalid inputs were given to this function"
                         << "\n\t samples.size(): " << samples.size() 
                         << "\n\t is_sequence_labeling_problem(samples,labels): " << is_sequence_labeling_problem(samples,labels)
+                        << "\n\t contains_invalid_labeling(fe,samples,labels): " << contains_invalid_labeling(fe,samples,labels)
                         << "\n\t this: " << this
                         );
 
@@ -187,12 +189,8 @@ namespace dlib
                 const matrix_exp<EXP>& node_states
             ) const
             {
-                /* TODO, uncomment this and setup some input validation to catch when rejection 
-                    is used incorrectly. 
                 if (dlib::impl::call_reject_labeling_if_exists(fe, sequence,  node_states, node_id))
                     return -std::numeric_limits<double>::infinity();
-                */
-
 
                 double loss = 0;
                 if (node_states(0) != label[node_id])

dlib/svm/structural_svm_sequence_labeling_problem_abstract.h

@@ -50,7 +50,8 @@ namespace dlib
         );
         /*!
             requires
-                - is_sequence_labeling_problem(samples, labels)
+                - is_sequence_labeling_problem(samples, labels) == true
+                - contains_invalid_labeling(fe, samples, labels) == false
                 - for all valid i and j: labels[i][j] < fe.num_labels()
             ensures
                 - This object attempts to learn a mapping from the given samples to the