correctly handle num_past_tokens > sliding_window case

Author: masahi

examples/python/run_llama_batched_vllm.py

@@ -274,17 +274,18 @@ def _prepare_eval_queries(
 
         positions += [num_past_tokens + i for i in range(num_queries)]
 
-        if sliding_window:
-            seq_lens.append(min(num_past_tokens + num_queries, sliding_window))
-            num_past = min(num_past_tokens, sliding_window)
-            past_slot_mapping += all_slot_mappings[request_id][:num_past]
-            slot_mapping += all_slot_mappings[request_id][num_past: num_past + num_queries]
+        if sliding_window and num_past_tokens + num_queries >= sliding_window:
+            seq_lens.append(sliding_window)
+            past_slot_mapping += all_slot_mappings[request_id][
+                num_past_tokens - (sliding_window - num_queries) : num_past_tokens
+            ]
         else:
             seq_lens.append(num_past_tokens + num_queries)
             past_slot_mapping += all_slot_mappings[request_id][:num_past_tokens]
-            slot_mapping += all_slot_mappings[request_id][
-                num_past_tokens : num_past_tokens + num_queries
-            ]
+
+        slot_mapping += all_slot_mappings[request_id][
+            num_past_tokens : num_past_tokens + num_queries
+        ]
 
         permute_map += list(range(past_offset, past_offset + num_past_tokens)) + list(
             range(query_offset, query_offset + num_queries)