RadixCache method adjust (#977)

python/sglang/srt/managers/schedule_batch.py

@@ -124,7 +124,7 @@ class Req:
         # For vision input
         self.pixel_values = None
         self.image_size = None
-        self.image_offset = 0
+        self.image_offset = None
         self.pad_value = None
 
         # Prefix info
@@ -162,6 +162,13 @@ class Req:
     def finished(self) -> bool:
         return self.finished_reason is not None
 
+    def adjust_max_prefix_ids(self):
+        max_prefix_ids = self.input_ids
+        if self.return_logprob:
+            max_prefix_ids = self.input_ids[: self.logprob_start_len]
+
+        return max_prefix_ids
+
     # Based on https://github.com/vllm-project/vllm/blob/7a64d24aad69e4d2548aa0bf528d9fe63428ab01/vllm/transformers_utils/detokenizer.py#L194-L313
     def init_incremental_detokenize(self):
         first_iter = self.surr_offset is None or self.read_offset is None
@@ -444,7 +451,8 @@ class ScheduleBatch:
         self.pixel_values = [r.pixel_values for r in reqs]
         self.image_sizes = [r.image_size for r in reqs]
         self.image_offsets = [
-            r.image_offset - p_len for r, p_len in zip(reqs, prefix_lens)
+            (r.image_offset - p_len) if r.image_offset is not None else 0
+            for r, p_len in zip(reqs, prefix_lens)
         ]
         self.prefix_lens = torch.tensor(prefix_lens, dtype=torch.int32, device=device)
         self.extend_num_tokens = extend_num_tokens
@@ -596,15 +604,7 @@ class ScheduleBatch:
                     req.vid += 1
 
                     # insert the old request into tree_cache
-                    self.tree_cache.cache_req(
-                        rid=req.rid,
-                        token_ids=cur_all_ids,
-                        last_uncached_pos=len(req.prefix_indices),
-                        req_pool_idx=req.req_pool_idx,
-                    )
-
-                    # unlock the last node
-                    self.tree_cache.dec_lock_ref(req.last_node)
+                    self.tree_cache.cache_finished_req(req, cur_all_ids)
 
                     # re-applying image padding
                     if req.pixel_values is not None:
@@ -621,8 +621,7 @@ class ScheduleBatch:
                     jump_forward_reqs.append(req)
                     filter_indices.remove(i)
 
-        if len(filter_indices) < len(self.reqs):
-            self.filter_batch(filter_indices)
+        self.filter_batch(filter_indices)
 
         return jump_forward_reqs
 
@@ -644,6 +643,15 @@ class ScheduleBatch:
         ] = self.out_cache_loc
 
     def filter_batch(self, unfinished_indices: List[int]):
+        if unfinished_indices is None or len(unfinished_indices) == 0:
+            # Filter out all requests
+            self.reqs = []
+            return
+
+        if len(unfinished_indices) == len(self.reqs):
+            # No need to filter
+            return
+
         self.reqs = [self.reqs[i] for i in unfinished_indices]
         new_indices = torch.tensor(unfinished_indices, dtype=torch.int32, device="cuda")
         self.seq_lens = self.seq_lens[new_indices]
@@ -711,6 +719,7 @@ class ScheduleBatch:
             self.logit_bias = torch.concat([self.logit_bias, other.logit_bias])
 
     def sample(self, logits: torch.Tensor):
+        # TODO(lsyin): move this into a part of layer and run with CUDA Graph
         # Post process logits
         logits = logits.contiguous()
         logits.div_(self.temperatures)

python/sglang/srt/managers/tp_worker.py

@@ -232,8 +232,6 @@ class ModelTpServer:
         if new_batch is not None:
             # Run a new prefill batch
             self.forward_prefill_batch(new_batch)
-            self.cache_filled_batch(new_batch)
-            self.filter_out_inflight(new_batch)
 
             if not new_batch.is_empty():
                 if self.running_batch is None:
@@ -353,26 +351,20 @@ class ModelTpServer:
         self.waiting_queue.append(req)
 
     def get_new_prefill_batch(self) -> Optional[ScheduleBatch]:
-        # TODO(lsyin): organize this function
         running_bs = (
             len(self.running_batch.reqs) if self.running_batch is not None else 0
         )
         if running_bs >= self.max_running_requests:
-            return
+            return None
 
         # Compute matched prefix length
         for req in self.waiting_queue:
             req.input_ids = req.origin_input_ids + req.output_ids
-            try_match_ids = req.input_ids
-            if req.return_logprob:
-                try_match_ids = req.input_ids[: req.logprob_start_len]
             # NOTE: the prefix_indices must always be aligned with last_node
-            prefix_indices, last_node = self.tree_cache.match_prefix(
-                rid=req.rid, key=try_match_ids
+            req.prefix_indices, req.last_node = self.tree_cache.match_prefix(
+                rid=req.rid, key=req.adjust_max_prefix_ids()
             )
-            req.extend_input_len = len(req.input_ids) - len(prefix_indices)
-            req.prefix_indices = prefix_indices
-            req.last_node = last_node
+            req.extend_input_len = len(req.input_ids) - len(req.prefix_indices)
 
         # Get priority queue
         self.waiting_queue = self.scheduler.get_priority_queue(self.waiting_queue)
@@ -394,6 +386,24 @@ class ModelTpServer:
             )
 
         for req in self.waiting_queue:
+
+            # FIXME: Move this code into adjust_max_prefix_len
+            if req.return_logprob and req.normalized_prompt_logprob is None:
+                # Need at least two tokens to compute normalized logprob
+                if req.extend_input_len < 2:
+                    delta = 2 - req.extend_input_len
+                    req.extend_input_len += delta
+                    req.prefix_indices = req.prefix_indices[:-delta]
+                    if req.image_offset is not None:
+                        req.image_offset += delta
+
+            if req.extend_input_len == 0 and req.sampling_params.max_new_tokens > 0:
+                # Need at least one token to compute logits
+                req.extend_input_len = 1
+                req.prefix_indices = req.prefix_indices[:-1]
+                if req.image_offset is not None:
+                    req.image_offset += 1
+
             res = adder.add_one_req(req)
             if (
                 not res
@@ -470,10 +480,20 @@ class ModelTpServer:
         pt = 0
         for i, req in enumerate(batch.reqs):
             if req is not self.current_inflight_req:
+                # Inflight reqs' prefill is not finished
                 req.completion_tokens_wo_jump_forward += 1
                 req.output_ids.append(next_token_ids[i])
                 req.check_finished()
 
+            if req.finished():
+                self.tree_cache.cache_finished_req(req)
+            else:
+                self.tree_cache.cache_unfinished_req(req)
+
+            if req is self.current_inflight_req:
+                # Inflight request would get a new req idx
+                self.req_to_token_pool.free(req.req_pool_idx)
+
             if req.return_logprob:
                 self.add_logprob_return_values(i, req, pt, next_token_ids, output)
                 pt += req.extend_input_len
@@ -529,22 +549,6 @@ class ModelTpServer:
                 )
             req.output_top_logprobs.append(output.output_top_logprobs[i])
 
-    def cache_filled_batch(self, batch: ScheduleBatch):
-        for i, req in enumerate(batch.reqs):
-            new_prefix_indices, new_last_node = self.tree_cache.cache_req(
-                rid=req.rid,
-                token_ids=tuple(req.input_ids),
-                last_uncached_pos=len(req.prefix_indices),
-                req_pool_idx=req.req_pool_idx,
-                del_in_memory_pool=False,
-                old_last_node=req.last_node,
-            )
-            req.prefix_indices, req.last_node = new_prefix_indices, new_last_node
-
-            if req is self.current_inflight_req:
-                # inflight request would get a new req idx
-                self.req_to_token_pool.free(req.req_pool_idx)
-
     def forward_decode_batch(self, batch: ScheduleBatch):
         # Check if decode out of memory
         if not batch.check_decode_mem():
@@ -595,6 +599,9 @@ class ModelTpServer:
             req.output_ids.append(next_token_id)
             req.check_finished()
 
+            if req.finished():
+                self.tree_cache.cache_finished_req(req)
+
             if req.return_logprob:
                 req.output_token_logprobs.append(
                     (next_token_logprobs[i], next_token_id)
@@ -614,12 +621,9 @@ class ModelTpServer:
         output_spaces_between_special_tokens = []
         output_meta_info = []
         output_finished_reason: List[BaseFinishReason] = []
-        finished_indices = []
         unfinished_indices = []
         for i, req in enumerate(batch.reqs):
-            if req.finished():
-                finished_indices.append(i)
-            else:
+            if not req.finished() and req is not self.current_inflight_req:
                 unfinished_indices.append(i)
 
             if req.finished() or (
@@ -683,34 +687,7 @@ class ModelTpServer:
                 )
             )
 
-        # Remove finished reqs
-        if finished_indices:
-            # Update radix cache
-            for i in finished_indices:
-                req = batch.reqs[i]
-                self.tree_cache.cache_req(
-                    rid=req.rid,
-                    token_ids=tuple(req.origin_input_ids + req.output_ids)[:-1],
-                    last_uncached_pos=len(req.prefix_indices),
-                    req_pool_idx=req.req_pool_idx,
-                )
-
-                self.tree_cache.dec_lock_ref(req.last_node)
-
-            # Update batch tensors
-            if unfinished_indices:
-                batch.filter_batch(unfinished_indices)
-            else:
-                batch.reqs = []
-
-    def filter_out_inflight(self, batch: ScheduleBatch):
-        # TODO(lsyin): reduce the overhead, make a special version for this
-        if self.current_inflight_req is None:
-            return
-
-        to_remove = batch.reqs.index(self.current_inflight_req)
-        unfinished_indices = [i for i in range(len(batch.reqs)) if i != to_remove]
-
+        # Remove finished reqs: update batch tensors
         batch.filter_batch(unfinished_indices)
 
     def flush_cache(self):

python/sglang/srt/mem_cache/base_cache.py → python/sglang/srt/mem_cache/base_prefix_cache.py

@@ -17,7 +17,11 @@ class BasePrefixCache(ABC):
         pass
 
     @abstractmethod
-    def cache_req(self, **kwargs):
+    def cache_finished_req(self, **kwargs):
+        pass
+
+    @abstractmethod
+    def cache_unfinished_req(self, **kwargs):
         pass
 
     @abstractmethod

python/sglang/srt/mem_cache/chunk_cache.py

 """Cache for chunked prefill, used when RadixCache is disabled."""
 
-from sglang.srt.mem_cache.base_cache import BasePrefixCache
+from typing import TYPE_CHECKING
+
+from sglang.srt.mem_cache.base_prefix_cache import BasePrefixCache
+
+if TYPE_CHECKING:
+    from sglang.srt.managers.schedule_batch import Req
 
 
 class ChunkCacheEntry:
@@ -27,22 +32,31 @@ class ChunkCache(BasePrefixCache):
         entry = self.entries[rid]
         return entry.value, entry
 
-    def cache_req(
-        self, rid, token_ids, req_pool_idx, del_in_memory_pool=True, **kwargs
-    ):
-        indices = self.req_to_token_pool.req_to_token[req_pool_idx, : len(token_ids)]
-        if del_in_memory_pool:
-            assert rid in self.entries
-            self.req_to_token_pool.free(req_pool_idx)
-            self.token_to_kv_pool.free(indices)
-            return
+    def cache_finished_req(self, req: "Req", token_ids=None):
+        if token_ids is None:
+            token_ids = (req.input_ids + req.output_ids)[:-1]
 
-        if rid not in self.entries:
-            self.entries[rid] = ChunkCacheEntry(rid, indices)
+        kv_indices = self.req_to_token_pool.req_to_token[
+            req.req_pool_idx, : len(token_ids)
+        ]
+        assert req.rid in self.entries
+        self.req_to_token_pool.free(req.req_pool_idx)
+        self.token_to_kv_pool.free(kv_indices)
 
-        entry = self.entries[rid]
-        entry.value = indices
-        return indices, entry
+    def cache_unfinished_req(self, req: "Req", token_ids=None):
+        if token_ids is None:
+            token_ids = req.input_ids
+
+        kv_indices = self.req_to_token_pool.req_to_token[
+            req.req_pool_idx, : len(token_ids)
+        ]
+
+        if req.rid not in self.entries:
+            self.entries[req.rid] = ChunkCacheEntry(req.rid, kv_indices)
+
+        entry = self.entries[req.rid]
+        entry.value = kv_indices
+        return kv_indices, entry
 
     def insert(self):
         raise NotImplementedError

python/sglang/srt/mem_cache/radix_cache.py

@@ -20,10 +20,14 @@ The radix tree data structure for managing the KV cache.
 import heapq
 import time
 from collections import defaultdict
+from typing import TYPE_CHECKING
 
 import torch
 
-from sglang.srt.mem_cache.base_cache import BasePrefixCache
+from sglang.srt.mem_cache.base_prefix_cache import BasePrefixCache
+
+if TYPE_CHECKING:
+    from sglang.srt.managers.schedule_batch import Req
 
 
 class TreeNode:
@@ -85,40 +89,54 @@ class RadixCache(BasePrefixCache):
             value = [x for x in key]
         return self._insert_helper(self.root_node, key, value)
 
-    def cache_req(
-        self,
-        token_ids,
-        last_uncached_pos,
-        req_pool_idx,
-        del_in_memory_pool=True,
-        old_last_node=None,
-        **kwargs,
-    ):
-        # Insert the request into radix cache
-        indices = self.req_to_token_pool.req_to_token[req_pool_idx, : len(token_ids)]
-        new_prefix_len = self.insert(token_ids, indices.clone())
+    def cache_finished_req(self, req: "Req", token_ids=None):
+        """Cache request when it finishes."""
+        if token_ids is None:
+            token_ids = (req.input_ids + req.output_ids)[:-1]
+        kv_indices = self.req_to_token_pool.req_to_token[
+            req.req_pool_idx, : len(token_ids)
+        ]
 
         if self.disable:
-            if del_in_memory_pool:
-                self.token_to_kv_pool.free(indices)
-            else:
-                return torch.tensor([], dtype=torch.int32), self.root_node
+            self.token_to_kv_pool.free(kv_indices)
+            self.req_to_token_pool.free(req.req_pool_idx)
+            return
 
         # Radix Cache takes one ref in memory pool
-        self.token_to_kv_pool.free(indices[last_uncached_pos:new_prefix_len])
+        new_prefix_len = self.insert(token_ids, kv_indices.clone())
+        self.token_to_kv_pool.free(kv_indices[len(req.prefix_indices) : new_prefix_len])
 
-        if del_in_memory_pool:
-            self.req_to_token_pool.free(req_pool_idx)
-        else:
-            cached_indices, new_last_node = self.match_prefix(token_ids)
-            assert len(cached_indices) == len(token_ids)
-
-            self.req_to_token_pool.req_to_token[
-                req_pool_idx, last_uncached_pos : len(cached_indices)
-            ] = cached_indices[last_uncached_pos:]
-            self.dec_lock_ref(old_last_node)
-            self.inc_lock_ref(new_last_node)
-            return cached_indices, new_last_node
+        # Remove req slot release the cache lock
+        self.req_to_token_pool.free(req.req_pool_idx)
+        self.dec_lock_ref(req.last_node)
+
+    def cache_unfinished_req(self, req: "Req", token_ids=None):
+        """Cache request when it is unfinished."""
+        if self.disable:
+            return
+
+        if token_ids is None:
+            token_ids = req.input_ids
+
+        kv_indices = self.req_to_token_pool.req_to_token[
+            req.req_pool_idx, : len(token_ids)
+        ]
+
+        # Radix Cache takes one ref in memory pool
+        new_prefix_len = self.insert(token_ids, kv_indices.clone())
+        self.token_to_kv_pool.free(kv_indices[len(req.prefix_indices) : new_prefix_len])
+
+        # The prefix indices could be updated, reuse it
+        new_indices, new_last_node = self.match_prefix(token_ids)
+        assert len(new_indices) == len(token_ids)
+        self.req_to_token_pool.req_to_token[
+            req.req_pool_idx, len(req.prefix_indices) : len(new_indices)
+        ] = new_indices[len(req.prefix_indices) :]
+
+        self.dec_lock_ref(req.last_node)
+        self.inc_lock_ref(new_last_node)
+        req.prefix_indices = new_indices
+        req.last_node = new_last_node
 
     def pretty_print(self):
         self._print_helper(self.root_node, 0)