fix sliding window mgr (#3068)

lmdeploy/pytorch/paging/block_manager/window_block_manager.py

@@ -13,13 +13,6 @@ def _div_up(x, n):
     return (x + n - 1) // n
 
 
-def _last_block_size(history_len: int, block_size: int):
-    """last block size."""
-    last = history_len % block_size
-    last = last if last != 0 else block_size
-    return last
-
-
 def _num_blocks_to_drop(seq: SchedulerSequence, window_size: int):
     """num blocks to free."""
     if seq.history_len <= window_size:
@@ -47,30 +40,17 @@ def __init__(self, num_gpu_blocks: int, num_cpu_blocks: int, window_size: int):
                                  f'but get window_size = {window_size}')
         self.window_size = window_size
 
-    @classmethod
-    def num_required_blocks(cls, obj: SchedulerSequence, prealloc_size: int = 0):
+    def num_required_blocks(self, obj: SchedulerSequence, prealloc_size: int = 0):
         """get num required blocks."""
 
-        def __num_req_seq(seq: SchedulerSequence):
-            """get num required seq blocks."""
-            block_size = seq.block_size
-            lb_tokens = cls.last_block_size(seq)
-            lb_remain_tokens = 0
-            if len(seq.logical_blocks) > 0:
-                lb_remain_tokens = block_size - lb_tokens
-            num_input_tokens = seq.num_token_ids + prealloc_size
-            num_req_tokens = max(0, num_input_tokens - lb_remain_tokens)
-            return _div_up(num_req_tokens, block_size)
-
-        return __num_req_seq(obj)
-
-    @classmethod
-    def last_block_size(cls, seq: SchedulerSequence) -> int:
-        """get last block size."""
-        num_blocks = len(seq.logical_blocks)
-        if num_blocks == 0:
-            return 0
-        return _last_block_size(seq.history_len, seq.block_size)
+        # blocks is not enough
+        if obj.num_history_ids < self.window_size:
+            return super().num_required_blocks(obj, prealloc_size)
+
+        # we only keep history less than window_size
+        num_tokens = self.window_size + obj.num_token_ids + prealloc_size
+        num_all_blocks = _div_up(num_tokens, obj.block_size)
+        return max(0, num_all_blocks - len(obj.logical_blocks))
 
     def can_allocate(self, msg: SchedulerSequence, prealloc_size: int = 0):
         """Return if physical block can be allocated for given message."""