in EWC the penalty is 0
🐛 **Describe the bug**
A clear and concise description of what the bug is.
Currently in [EWC ](https://github.com/ContinualAI/avalanche/blob/master/avalanche/training/plugins/ewc.py)plugin the penalty is always 0 
```
n_units = saved_param.shape[0]
cur_param = saved_param[:n_units]
penalty += (imp * (cur_param - saved_param).pow(2)).sum()
```

because `cur_param` is equal to `saved_param` in the penalty from computation `penalty += (imp * (cur_param - saved_param).pow(2)).sum()`

diff --git a/avalanche/benchmarks/classic/cmnist.py b/avalanche/benchmarks/classic/cmnist.py
index 8f2866c4..c36319d8 100644
--- a/avalanche/benchmarks/classic/cmnist.py
+++ b/avalanche/benchmarks/classic/cmnist.py
@@ -250,7 +250,7 @@ def PermutedMNIST(
         n_experiences=len(list_train_dataset),
         task_labels=return_task_id,
         shuffle=False,
-        class_ids_from_zero_in_each_exp=False,
+        class_ids_from_zero_in_each_exp=True,
         one_dataset_per_exp=True,
         train_transform=train_transform,
         eval_transform=eval_transform,
@@ -373,7 +373,7 @@ def RotatedMNIST(
         n_experiences=len(list_train_dataset),
         task_labels=return_task_id,
         shuffle=False,
-        class_ids_from_zero_in_each_exp=False,
+        class_ids_from_zero_in_each_exp=True,
         one_dataset_per_exp=True,
         train_transform=train_transform,
         eval_transform=eval_transform,
diff --git a/avalanche/training/plugins/ewc.py b/avalanche/training/plugins/ewc.py
index 09608b43..b184e56e 100644
--- a/avalanche/training/plugins/ewc.py
+++ b/avalanche/training/plugins/ewc.py
@@ -89,7 +89,7 @@ class EWCPlugin(SupervisedPlugin):
                     # dynamic models may add new units
                     # new units are ignored by the regularization
                     n_units = saved_param.shape[0]
-                    cur_param = saved_param[:n_units]
+                    cur_param = cur_param[:n_units]
                     penalty += (imp * (cur_param - saved_param).pow(2)).sum()
         elif self.mode == "online":
             prev_exp = exp_counter - 1
@@ -101,7 +101,7 @@ class EWCPlugin(SupervisedPlugin):
                 # dynamic models may add new units
                 # new units are ignored by the regularization
                 n_units = saved_param.shape[0]
-                cur_param = saved_param[:n_units]
+                cur_param = cur_param[:n_units]
                 penalty += (imp * (cur_param - saved_param).pow(2)).sum()
         else:
             raise ValueError("Wrong EWC mode.")
['avalanche/benchmarks/classic/cmnist.py', 'avalanche/training/plugins/ewc.py']