make sure negative examples are unique

dtree_learner.py

@@ -15,10 +15,11 @@ class DTreeLearner(LearnerBase):
     def __init__(self, state_dim: int, perc_dim: int,
                  timeout: int = 10000) -> None:
         super().__init__()
-
+        self.debug_neg_conc= set()
+        self.debug_neg_perc= set()
         self._state_dim: int = state_dim
         self._perc_dim: int = perc_dim
-
+        self.count_neg_dup =0
         self._s2f_func = lambda x: x
 
         # Given a base or derived feature name,
@@ -127,6 +128,14 @@ class DTreeLearner(LearnerBase):
         self._append_to_data_file(feature_vec_list, "true")
 
     def add_negative_examples(self, *args) -> None:
+        for samp in args:
+            if samp in self.debug_neg_conc:
+                self.count_neg_dup+=1
+                print("repeated negative example: "+ str(samp))
+                #raise ValueError()
+            
+            self.debug_neg_conc.add(samp)
+        print(f"number of negative duplicate {self.count_neg_dup}")
         feature_vec_list = [self._s2f_func(sample) for sample in args]
 
         print("Negative feature vectors:", feature_vec_list)