unlearning CR

Tune.py

@@ -13,6 +13,8 @@ from IdentitySubset import IdentitySubset
 from architectures.Model import Model, Architecture
 
 from unlearning.LinearFiltration import LinearFiltration
+
+import Util
 # WeightFiltration, CertifiedRemoval
 
 # numbre of classes 
@@ -134,10 +136,11 @@ for i in range(0,CLASS_SIZE):
     print(f"Total test images for these {CLASS_SIZE} classes: {len(test_data)}")
 
     # Evaluate
-    model.evaluate(
-        loader = test_loader,
-        mode="finetunned"
-        )
+    mode, accuracy, report_dict = model.evaluate(
+                                    loader = test_loader,
+                                    mode="finetunned"
+                                    )
+    Util._log_to_csv(model=reloaded, mode = "finetuned", accuracy=accuracy, report_dict=report_dict, strategy="base")
 
     # test again
     reloaded = Model.create(
@@ -169,7 +172,9 @@ for i in range(0,CLASS_SIZE):
 
     # 4. Final Performance Analysis
     print("\n--- Performance on Retained Classes")
-    reloaded.evaluate(loader=retain_test_loader, mode="retain")
+    mode, accuracy, report_dict = reloaded.evaluate(loader=retain_test_loader, mode="retain")
+    Util._log_to_csv(model=reloaded, mode = "retain", accuracy=accuracy, report_dict=report_dict, strategy="linearFiltration")
 
     print("\n--- Performance on Forgotten Class")
-    reloaded.evaluate(loader=forget_test_loader,mode="forget")
+    mode, accuracy, report_dict = reloaded.evaluate(loader=forget_test_loader,mode="forget")
+    Util._log_to_csv(model=reloaded, mode = "forgotten", accuracy=accuracy, report_dict=report_dict, strategy="linearFiltration")