final curiousity experiments

Tune.py

@@ -62,6 +62,7 @@ def prepare_data_and_model_environment():
     # get Cuda or CPU.
     device = get_device()
     dataset_name = Set_Name.CASIAFACES
+    # we are changing this sample size if we use CASIA Set
     if dataset_name == Set_Name.CASIAFACES:
         SAMPLE_SIZE = 400
         TRAINING_SAMPLE = 320
@@ -259,7 +260,7 @@ def run_unlearning_and_strategy_eval(env_dict, forget_class_idx, strategy, evalu
 # entry
 if __name__ == "__main__":
 
-    outer_loop = 20
+    outer_loop = 2
 
     inner_loop = CLASS_SIZE
     
@@ -301,7 +302,7 @@ if __name__ == "__main__":
             # WF-Net
             weight_filtration = WeightFiltration(
                 target_class_index=0,      #arch  ResNet18  GoogLeNet/Inception
-                epochs=6,                       #   
+                epochs=8,                       #   
                 lr=250.0, # ResNet18 = 150      #      150        100
                 gamma=0.001,                    #    0.001      
                 lambda_1=30,                 #       25        100
@@ -319,8 +320,8 @@ if __name__ == "__main__":
 
             strategies = [
                 #retrain,
-                linear_filtration,
-                #weight_filtration,
+                #linear_filtration,
+                weight_filtration,
                 #certified_unlearning,
             ]
             suite_runner = UnlearningAttack(arch=ARCH, class_size=CLASS_SIZE)
@@ -341,7 +342,7 @@ if __name__ == "__main__":
                         # if we are finetuning, no need to evaluate base model. 
                         # or may be never when not either!
                         evaluate = not finetuning,
-                        suite_runner=suite_runner
+                        #suite_runner=suite_runner
                     )