Remove option for replica seeds to be None in Preprocessing

n3fit/src/n3fit/layers/preprocessing.py

@@ -21,6 +21,8 @@ class Preprocessing(MetaLayer):
 
     Parameters
     ----------
+        replica_seeds: List[int]
+            list of pre replica seeds for the initializer of the random alpha and beta values
         flav_info: list
             list of dicts containing the information about the fitting of the preprocessing factor
             This corresponds to the `fitting::basis` parameter in the nnpdf runcard.
@@ -31,16 +33,14 @@ class Preprocessing(MetaLayer):
                             (defaults to true)
         large_x: bool
             Whether large x preprocessing factor should be active
-        replica_seeds: List[int]
-            list of pre replica seeds for the initializer of the random alpha and beta values
         num_replicas: int (default 1)
             The number of replicas
     """
 
     def __init__(
         self,
+        replica_seeds: Optional[List[int]],
         flav_info: Optional[list] = None,
-        replica_seeds: Optional[List[int]] = None,
         large_x: bool = True,
         num_replicas: int = 1,
         **kwargs,
@@ -50,10 +50,7 @@ def __init__(
                 "Trying to instantiate a preprocessing factor with no basis information"
             )
         self.flav_info = flav_info
-        if replica_seeds is None:
-            self.replica_seeds = [0] * num_replicas  # TODO Aron: figure out if this ever happens
-        else:
-            self.replica_seeds = replica_seeds
+        self.replica_seeds = replica_seeds
         self.large_x = large_x
         self.num_replicas = num_replicas