[core] add sleep and wake up endpoint and v1 support

tests/basic_correctness/test_cumem.py

@@ -118,14 +118,16 @@ def model(x):
 
 @fork_new_process_for_each_test
 @pytest.mark.parametrize(
-    "model",
+    "model, use_v1",
     [
         # sleep mode with safetensors
-        f"{MODEL_WEIGHTS_S3_BUCKET}/Llama-3.2-1B",
+        (f"{MODEL_WEIGHTS_S3_BUCKET}/Llama-3.2-1B", True),
         # sleep mode with pytorch checkpoint
-        "facebook/opt-125m"
+        ("facebook/opt-125m", False),
     ])
-def test_end_to_end(model):
+def test_end_to_end(model: str, use_v1: bool):
+    import os
+    os.environ["VLLM_USE_V1"] = "1" if use_v1 else "0"
     free, total = torch.cuda.mem_get_info()
     used_bytes_baseline = total - free  # in case other process is running
     load_format = LoadFormat.AUTO
@@ -152,3 +154,5 @@ def test_end_to_end(model):
 
     # cmp output
     assert output[0].outputs[0].text == output2[0].outputs[0].text
+
+    del os.environ["VLLM_USE_V1"]

tests/entrypoints/openai/test_sleep.py

@@ -0,0 +1,32 @@
+# SPDX-License-Identifier: Apache-2.0
+
+import requests
+
+from ...utils import RemoteOpenAIServer
+
+MODEL_NAME = "meta-llama/Llama-3.2-1B"
+
+
+def test_sleep_mode():
+    # dtype, max-len etc set so that this can run in CI
+    args = [
+        "--dtype",
+        "bfloat16",
+        "--max-model-len",
+        "8192",
+        "--max-num-seqs",
+        "128",
+        "--enable-sleep-mode",
+    ]
+
+    with RemoteOpenAIServer(MODEL_NAME,
+                            args,
+                            env_dict={
+                                "VLLM_SERVER_DEV_MODE": "1",
+                                "CUDA_VISIBLE_DEVICES": "0"
+                            }) as remote_server:
+        response = requests.post(remote_server.url_for("/sleep"),
+                                 data={"level": "1"})
+        assert response.status_code == 200
+        response = requests.post(remote_server.url_for("/wake_up"))
+        assert response.status_code == 200

vllm/engine/async_llm_engine.py

@@ -1187,6 +1187,12 @@ async def stop_profile(self) -> None:
     async def reset_prefix_cache(self) -> None:
         self.engine.reset_prefix_cache()
 
+    async def sleep(self, level: int = 1) -> None:
+        self.engine.sleep(level)
+
+    async def wake_up(self) -> None:
+        self.engine.wake_up()
+
     async def add_lora(self, lora_request: LoRARequest) -> None:
         self.engine.add_lora(lora_request)
 

vllm/engine/multiprocessing/__init__.py

@@ -127,6 +127,15 @@ class RPCResetPrefixCacheRequest(Enum):
     RESET_PREFIX_CACHE = 1
 
 
+class RPCSleepRequest(Enum):
+    SLEEP_LEVEL_1 = 1
+    SLEEP_LEVEL_2 = 2
+
+
+class RPCWakeUpRequest(Enum):
+    WAKE_UP = 1
+
+
 @dataclass
 class RPCLoadAdapterRequest:
     lora_request: LoRARequest
@@ -141,7 +150,8 @@ class RPCAdapterLoadedResponse:
 
 RPC_REQUEST_T = Union[RPCProcessRequest, RPCAbortRequest, RPCStartupRequest,
                       RPCUProfileRequest, RPCLoadAdapterRequest,
-                      RPCResetPrefixCacheRequest]
+                      RPCResetPrefixCacheRequest, RPCSleepRequest,
+                      RPCWakeUpRequest]
 
 REQUEST_OUTPUTS_T = Union[List[RequestOutput], RPCAdapterLoadedResponse,
                           RPCError]

vllm/engine/multiprocessing/client.py

@@ -31,8 +31,9 @@
                                          RPCLoadAdapterRequest,
                                          RPCProcessRequest,
                                          RPCResetPrefixCacheRequest,
-                                         RPCStartupRequest, RPCStartupResponse,
-                                         RPCUProfileRequest)
+                                         RPCSleepRequest, RPCStartupRequest,
+                                         RPCStartupResponse,
+                                         RPCUProfileRequest, RPCWakeUpRequest)
 from vllm.engine.protocol import EngineClient
 # yapf: enable
 from vllm.envs import VLLM_RPC_TIMEOUT
@@ -685,6 +686,16 @@ async def reset_prefix_cache(self) -> None:
             request=RPCResetPrefixCacheRequest.RESET_PREFIX_CACHE,
             socket=self.input_socket)
 
+    async def sleep(self, level: int = 1) -> None:
+        """Sleep the engine for a given level"""
+        return await self._send_one_way_rpc_request(
+            request=RPCSleepRequest(level), socket=self.input_socket)
+
+    async def wake_up(self) -> None:
+        """Wake up the engine"""
+        return await self._send_one_way_rpc_request(
+            request=RPCWakeUpRequest.WAKE_UP, socket=self.input_socket)
+
     async def add_lora(self, lora_request: LoRARequest) -> None:
         """Load a new LoRA adapter into the engine for future requests."""
         # Uses the same I/O as generate requests

vllm/engine/multiprocessing/engine.py

@@ -20,8 +20,9 @@
                                          RPCLoadAdapterRequest,
                                          RPCProcessRequest,
                                          RPCResetPrefixCacheRequest,
-                                         RPCStartupRequest, RPCStartupResponse,
-                                         RPCUProfileRequest)
+                                         RPCSleepRequest, RPCStartupRequest,
+                                         RPCStartupResponse,
+                                         RPCUProfileRequest, RPCWakeUpRequest)
 # yapf: enable
 from vllm.logger import init_logger
 from vllm.outputs import RequestOutput
@@ -242,6 +243,10 @@ def handle_new_input(self):
                     self._handle_load_adapter_request(request)
                 elif isinstance(request, RPCResetPrefixCacheRequest):
                     self.reset_prefix_cache()
+                elif isinstance(request, RPCSleepRequest):
+                    self.sleep(request.value)
+                elif isinstance(request, RPCWakeUpRequest):
+                    self.wake_up()
                 else:
                     raise ValueError("Unknown RPCRequest Type: "
                                      f"{type(request)}")
@@ -369,6 +374,12 @@ def stop_profile(self) -> None:
     def reset_prefix_cache(self) -> bool:
         return self.engine.reset_prefix_cache()
 
+    def sleep(self, level: int = 1) -> None:
+        self.engine.sleep(level)
+
+    def wake_up(self) -> None:
+        self.engine.wake_up()
+
 
 def signal_handler(*_) -> None:
     raise KeyboardInterrupt("MQLLMEngine terminated")

vllm/engine/protocol.py

@@ -278,6 +278,16 @@ async def reset_prefix_cache(self) -> None:
         """Reset the prefix cache"""
         ...
 
+    @abstractmethod
+    async def sleep(self, level: int = 1) -> None:
+        """Sleep the engine"""
+        ...
+
+    @abstractmethod
+    async def wake_up(self) -> None:
+        """Wake up the engine"""
+        ...
+
     @abstractmethod
     async def add_lora(self, lora_request: LoRARequest) -> None:
         """Load a new LoRA adapter into the engine for future requests."""

vllm/entrypoints/openai/api_server.py

@@ -625,6 +625,24 @@ async def reset_prefix_cache(raw_request: Request):
         await engine_client(raw_request).reset_prefix_cache()
         return Response(status_code=200)
 
+    @router.post("/sleep")
+    async def sleep(raw_request: Request):
+        # get POST params
+        level = raw_request.query_params.get("level", "1")
+        logger.info("sleep the engine with level %s", level)
+        await engine_client(raw_request).sleep(int(level))
+        # FIXME: in v0 with frontend multiprocessing, the sleep command
+        # is sent but does not finish yet when we return a response.
+        return Response(status_code=200)
+
+    @router.post("/wake_up")
+    async def wake_up(raw_request: Request):
+        logger.info("wake up the engine")
+        await engine_client(raw_request).wake_up()
+        # FIXME: in v0 with frontend multiprocessing, the wake-up command
+        # is sent but does not finish yet when we return a response.
+        return Response(status_code=200)
+
 
 @router.post("/invocations", dependencies=[Depends(validate_json_request)])
 async def invocations(raw_request: Request):

vllm/entrypoints/openai/serving_transcription.py

@@ -295,6 +295,7 @@ async def create_transcription(
         # TODO(rob): figure out a way to pipe streaming in.
         # Non-streaming response.
         try:
+            assert result_generator is not None
             async for op in result_generator:
                 result = op
             return TranscriptionResponse(text=result.outputs[0].text)

vllm/v1/engine/async_llm.py

@@ -361,6 +361,12 @@ async def stop_profile(self) -> None:
     async def reset_prefix_cache(self) -> None:
         await self.engine_core.reset_prefix_cache_async()
 
+    async def sleep(self, level: int = 1) -> None:
+        await self.engine_core.sleep_async(level)
+
+    async def wake_up(self) -> None:
+        await self.engine_core.wake_up_async()
+
     async def add_lora(self, lora_request: LoRARequest) -> None:
         """Load a new LoRA adapter into the engine for future requests."""
         await self.engine_core.add_lora_async(lora_request)

vllm/v1/engine/core.py

@@ -213,6 +213,12 @@ def profile(self, is_start: bool = True):
     def reset_prefix_cache(self):
         self.scheduler.reset_prefix_cache()
 
+    def sleep(self, level: int = 1):
+        self.model_executor.sleep(level)
+
+    def wake_up(self):
+        self.model_executor.wake_up()
+
     def add_lora(self, lora_request: LoRARequest) -> None:
         self.model_executor.add_lora(lora_request)
 

vllm/v1/engine/core_client.py

@@ -81,6 +81,12 @@ def profile(self, is_start: bool = True) -> None:
     def reset_prefix_cache(self) -> None:
         raise NotImplementedError
 
+    def sleep(self, level: int = 1) -> None:
+        raise NotImplementedError
+
+    def wake_up(self) -> None:
+        raise NotImplementedError
+
     def abort_requests(self, request_ids: List[str]) -> None:
         raise NotImplementedError
 
@@ -99,6 +105,12 @@ async def profile_async(self, is_start: bool = True) -> None:
     async def reset_prefix_cache_async(self) -> None:
         raise NotImplementedError
 
+    async def sleep_async(self, level: int = 1) -> None:
+        raise NotImplementedError
+
+    async def wake_up_async(self) -> None:
+        raise NotImplementedError
+
     async def abort_requests_async(self, request_ids: List[str]) -> None:
         raise NotImplementedError
 
@@ -138,6 +150,12 @@ def profile(self, is_start: bool = True) -> None:
     def reset_prefix_cache(self) -> None:
         self.engine_core.reset_prefix_cache()
 
+    def sleep(self, level: int = 1) -> None:
+        self.engine_core.sleep(level)
+
+    def wake_up(self) -> None:
+        self.engine_core.wake_up()
+
     def add_lora(self, lora_request: LoRARequest) -> None:
         self.engine_core.add_lora(lora_request)
 
@@ -303,6 +321,12 @@ def reset_prefix_cache(self) -> None:
     def add_lora(self, lora_request: LoRARequest) -> None:
         self._call_utility("add_lora", lora_request)
 
+    def sleep(self, level: int = 1) -> None:
+        self._call_utility("sleep", level)
+
+    def wake_up(self) -> None:
+        self._call_utility("wake_up")
+
 
 class AsyncMPClient(MPClient):
     """Asyncio-compatible client for multi-proc EngineCore."""
@@ -380,5 +404,11 @@ async def profile_async(self, is_start: bool = True) -> None:
     async def reset_prefix_cache_async(self) -> None:
         await self._call_utility_async("reset_prefix_cache")
 
+    async def sleep_async(self, level: int = 1) -> None:
+        await self._call_utility_async("sleep", level)
+
+    async def wake_up_async(self) -> None:
+        await self._call_utility_async("wake_up")
+
     async def add_lora_async(self, lora_request: LoRARequest) -> None:
         await self._call_utility_async("add_lora", lora_request)

vllm/v1/engine/llm_engine.py

@@ -169,6 +169,12 @@ def stop_profile(self):
     def reset_prefix_cache(self):
         self.engine_core.reset_prefix_cache()
 
+    def sleep(self, level: int = 1):
+        self.engine_core.sleep(level)
+
+    def wake_up(self):
+        self.engine_core.wake_up()
+
     def get_tokenizer_group(
         self,
         group_type: Type[_G] = BaseTokenizerGroup,