move vit functionality into derandomised smoothing toolset

Signed-off-by: GiulioZizzo <giulio.zizzo@yahoo.co.uk>

art/estimators/certification/derandomized_smoothing/vision_transformers/smooth_vit.py

@@ -25,6 +25,7 @@
 """
 
 from typing import Optional, Tuple
+import random
 
 import torch
 
@@ -101,6 +102,9 @@ def ablate(self, x: torch.Tensor, column_pos: int) -> torch.Tensor:
         :return: The ablated input with 0s where the ablation occurred
         """
         k = self.ablation_size
+        if column_pos is None:
+            column_pos = random.randint(0, x.shape[3])
+
         if column_pos + k > x.shape[-1]:
             x[:, :, :, (column_pos + k) % x.shape[-1] : column_pos] = 0.0
         else: