cleaned up for submission

unlearning/LinearFiltration.py

@@ -124,7 +124,6 @@ class LinearFiltration(Strategy):
         if self.A is None:
             self._compute_A(
                 model = model,
-                #num_classes = num_classes,
                 loader = forget_loader,
                 device = device
             )
@@ -147,6 +146,9 @@ class LinearFiltration(Strategy):
         A_inv = torch.linalg.pinv(A_t, rcond=1e-2)
         # 11 
         W_temp = B_z @ A_inv @ W 
+        # Linear (Normalisation)filtration is done here, 
+        # next steps are added for safe automated evaluations
+
         # with one class removed, we have a  head W_temp for 19 classes.
         # but we have loaders for 20 classes for evaluation. so ,
         # map K-1  W back to K x K.
@@ -164,6 +166,7 @@ class LinearFiltration(Strategy):
             # neutralise forget bias if exists
             if clf.bias is not None:
                 n_bias = clf.bias.data.clone()
+                # push it down to negative
                 n_bias[forget_index] = -1e9
                 clf.bias.copy_(n_bias)