split verbosity processing into separate method.

Signed-off-by: GiulioZizzo <[email protected]>

Author: GiulioZizzo

art/estimators/certification/randomized_smoothing/pytorch.py

@@ -164,16 +164,7 @@ class was initialised.
         import torch
         from torch.utils.data import TensorDataset, DataLoader
 
-        if verbose is not None:
-            if isinstance(verbose, int):
-                if verbose == 0:
-                    display_pb = False
-                else:
-                    display_pb = True
-            else:
-                display_pb = verbose
-        else:
-            display_pb = self.verbose
+        display_pb = self.process_verbose(verbose)
 
         # Set model mode
         self._model.train(mode=training_mode)

art/estimators/certification/randomized_smoothing/tensorflow.py

@@ -156,16 +156,7 @@ class was initialised.
         """
         import tensorflow as tf
 
-        if verbose is not None:
-            if isinstance(verbose, int):
-                if verbose == 0:
-                    display_pb = False
-                else:
-                    display_pb = True
-            else:
-                display_pb = verbose
-        else:
-            display_pb = self.verbose
+        display_pb = self.process_verbose(verbose)
 
         if self._train_step is None:  # pragma: no cover
             if self._loss_object is None:  # pragma: no cover