✨ feat: add configurable stride and chunk_size for XAttention BSA

- Add sparse_chunk_size config option (default: 16384)
- Pass stride, chunk_size, use_triton through factory function
- Add --sparse-stride CLI option to test_ruler.py

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

tests/test_ruler.py

@@ -274,6 +274,7 @@ def run_ruler_benchmark(
     sparse_threshold: float = 0.9,
     sparse_samples: int = 128,
     sparse_block_size: int = 128,
+    sparse_stride: int = 8,
 ) -> Dict:
     """
     Run RULER benchmark on multiple tasks.
@@ -339,6 +340,7 @@ def run_ruler_benchmark(
         if sparse_policy_type == SparsePolicyType.XATTN_BSA:
             llm_kwargs["sparse_threshold"] = sparse_threshold
             llm_kwargs["sparse_samples_per_chunk"] = sparse_samples
+            llm_kwargs["sparse_stride"] = sparse_stride
 
     # Factory function for fresh_llm mode
     def create_llm():
@@ -485,6 +487,8 @@ if __name__ == "__main__":
                         help="XAttention BSA: samples per chunk for estimation")
     parser.add_argument("--sparse-block-size", type=int, default=128,
                         help="XAttention BSA: block size for estimation")
+    parser.add_argument("--sparse-stride", type=int, default=8,
+                        help="XAttention BSA: stride for Q/K downsampling")
 
     args = parser.parse_args()
 
@@ -521,6 +525,7 @@ if __name__ == "__main__":
         sparse_threshold=args.sparse_threshold,
         sparse_samples=args.sparse_samples,
         sparse_block_size=args.sparse_block_size,
+        sparse_stride=args.sparse_stride,
     )
 
     # Exit code (skip for json output mode)