Make sliding window size inclusive in eager attention (#29519)

* Make sliding window size inclusive in eager attention

* Fix tests

src/transformers/modeling_attn_mask_utils.py

@@ -164,10 +164,10 @@ class AttentionMaskConverter:
 
         # add lower triangular sliding window mask if necessary
         if sliding_window is not None:
-            diagonal = past_key_values_length - sliding_window + 1
+            diagonal = past_key_values_length - sliding_window - 1
 
-            context_mask = 1 - torch.triu(torch.ones_like(mask, dtype=torch.int), diagonal=diagonal)
-            mask.masked_fill_(context_mask.bool(), torch.finfo(dtype).min)
+            context_mask = torch.tril(torch.ones_like(mask, dtype=torch.bool), diagonal=diagonal)
+            mask.masked_fill_(context_mask, torch.finfo(dtype).min)
 
         return mask[None, None, :, :].expand(bsz, 1, tgt_len, tgt_len + past_key_values_length)
 

tests/test_modeling_utils.py

@@ -1673,7 +1673,7 @@ class AttentionMaskTester(unittest.TestCase):
     def compute_num_context_mask(self, kv_len, context, q_len):
         # This function computes the # of attention tokens that are added for
         # the sliding window
-        c_mask_len = kv_len - context
+        c_mask_len = kv_len - context - 1
         num_mask_triangle = c_mask_len * (c_mask_len + 1) // 2
         cut_mask_len = max(c_mask_len - q_len, 0)
         num_cut_mask = cut_mask_len * (cut_mask_len + 1) // 2