import pickle import queue import signal import threading import time from multiprocessing.connection import Connection from typing import List, Tuple, Type import psutil import zmq import zmq.asyncio from msgspec import msgpack from vllm.config import CacheConfig, VllmConfig from vllm.logger import init_logger from vllm.transformers_utils.config import ( maybe_register_config_serialize_by_value) from vllm.utils import get_exception_traceback, zmq_socket_ctx from vllm.v1.core.scheduler import Scheduler from vllm.v1.engine import (EngineCoreOutput, EngineCoreOutputs, EngineCoreProfile, EngineCoreRequest, EngineCoreRequestType, EngineCoreRequestUnion) from vllm.v1.engine.mm_input_mapper import MMInputMapperServer from vllm.v1.executor.abstract import Executor from vllm.v1.request import Request, RequestStatus from vllm.v1.serial_utils import PickleEncoder from vllm.version import __version__ as VLLM_VERSION logger = init_logger(__name__) POLLING_TIMEOUT_MS = 5000 POLLING_TIMEOUT_S = POLLING_TIMEOUT_MS // 1000 LOGGING_TIME_S = 5 class EngineCore: """Inner loop of vLLM's Engine.""" def __init__( self, vllm_config: VllmConfig, executor_class: Type[Executor], log_stats: bool = False, ): assert vllm_config.model_config.runner_type != "pooling" self.log_stats = log_stats logger.info("Initializing an LLM engine (v%s) with config: %s", VLLM_VERSION, vllm_config) # Setup Model. self.model_executor = executor_class(vllm_config) # Setup KV Caches and update CacheConfig after profiling. num_gpu_blocks, num_cpu_blocks = self._initialize_kv_caches( vllm_config.cache_config) vllm_config.cache_config.num_gpu_blocks = num_gpu_blocks vllm_config.cache_config.num_cpu_blocks = num_cpu_blocks # Setup scheduler. self.scheduler = Scheduler(vllm_config.scheduler_config, vllm_config.cache_config, vllm_config.lora_config) self._last_logging_time = time.time() self.mm_input_mapper_server = MMInputMapperServer( vllm_config.model_config) def _initialize_kv_caches(self, cache_config: CacheConfig) -> Tuple[int, int]: start = time.time() num_gpu_blocks, _ = self.model_executor.determine_num_available_blocks( ) if cache_config.num_gpu_blocks_override is not None: num_gpu_blocks_override = cache_config.num_gpu_blocks_override logger.info( "Overriding num_gpu_blocks=%d with " "num_gpu_blocks_override=%d", num_gpu_blocks, num_gpu_blocks_override) num_gpu_blocks = num_gpu_blocks_override num_cpu_blocks = 0 self.model_executor.initialize(num_gpu_blocks) elapsed = time.time() - start logger.info(("init engine (profile, create kv cache, " "warmup model) took %.2f seconds"), elapsed) return num_gpu_blocks, num_cpu_blocks def add_request(self, request: EngineCoreRequest): """Add request to the scheduler.""" if request.mm_hashes is not None: # Here, if hash exists for an image, then it will be fetched # from the cache, else it will be added to the cache. # Note that the cache here is mirrored with the client side of the # MM mapper, so anything that has a hash must have a HIT cache # entry here as well. assert request.mm_inputs is not None request.mm_inputs = self.mm_input_mapper_server.process_inputs( request.mm_inputs, request.mm_hashes) req = Request.from_engine_core_request(request) self.scheduler.add_request(req) def abort_requests(self, request_ids: List[str]): """Abort requests from the scheduler.""" # TODO: The scheduler doesn't really need to know the # specific finish reason, TBD whether we propagate that # (i.e. client-aborted vs stop criteria met). self.scheduler.finish_requests(request_ids, RequestStatus.FINISHED_ABORTED) def step(self) -> List[EngineCoreOutput]: """Schedule, execute, and make output.""" if not self.scheduler.has_unfinished_requests(): return [] scheduler_output = self.scheduler.schedule() output = self.model_executor.execute_model(scheduler_output) engine_core_outputs = self.scheduler.update_from_output( scheduler_output, output) return engine_core_outputs def shutdown(self): self.model_executor.shutdown() def profile(self, is_start: bool = True): self.model_executor.profile(is_start) class EngineCoreProc(EngineCore): """ZMQ-wrapper for running EngineCore in background process.""" def __init__( self, input_path: str, output_path: str, ready_pipe: Connection, vllm_config: VllmConfig, executor_class: Type[Executor], log_stats: bool = False, ): super().__init__(vllm_config, executor_class, log_stats) # Background Threads and Queues for IO. These enable us to # overlap ZMQ socket IO with GPU since they release the GIL, # and to overlap some serialization/deserialization with the # model forward pass. # Threads handle Socket <-> Queues and core_busy_loop uses Queue. self.input_queue: queue.Queue[EngineCoreRequestUnion] = queue.Queue() self.output_queue: queue.Queue[List[EngineCoreOutput]] = queue.Queue() threading.Thread(target=self.process_input_socket, args=(input_path, ), daemon=True).start() threading.Thread(target=self.process_output_socket, args=(output_path, ), daemon=True).start() # Send Readiness signal to EngineClient. ready_pipe.send({"status": "READY"}) @staticmethod def run_engine_core(*args, **kwargs): """Launch EngineCore busy loop in background process.""" # Signal handler used for graceful termination. # SystemExit exception is only raised once to allow this and worker # processes to terminate without error shutdown_requested = False # Ensure we can serialize transformer config after spawning maybe_register_config_serialize_by_value() def signal_handler(signum, frame): nonlocal shutdown_requested if not shutdown_requested: shutdown_requested = True raise SystemExit() # Either SIGTERM or SIGINT will terminate the engine_core signal.signal(signal.SIGTERM, signal_handler) signal.signal(signal.SIGINT, signal_handler) parent_process = psutil.Process().parent() engine_core = None try: engine_core = EngineCoreProc(*args, **kwargs) engine_core.run_busy_loop() except SystemExit: logger.debug("EngineCore interrupted.") except Exception: traceback = get_exception_traceback() logger.error("EngineCore hit an exception: %s", traceback) parent_process.send_signal(signal.SIGQUIT) finally: if engine_core is not None: engine_core.shutdown() engine_core = None def run_busy_loop(self): """Core busy loop of the EngineCore.""" # Loop until process is sent a SIGINT or SIGTERM while True: # 1) Poll the input queue until there is work to do. if not self.scheduler.has_unfinished_requests(): while True: try: req = self.input_queue.get(timeout=POLLING_TIMEOUT_S) self._handle_client_request(req) break except queue.Empty: self._log_stats() logger.debug("EngineCore busy loop waiting.") except BaseException: raise # 2) Handle any new client requests (Abort or Add). while not self.input_queue.empty(): req = self.input_queue.get_nowait() self._handle_client_request(req) # 3) Step the engine core. outputs = self.step() # 4) Put EngineCoreOutputs into the output queue. self.output_queue.put_nowait(outputs) self._log_stats() def _log_stats(self): """Log basic stats every LOGGING_TIME_S""" if not self.log_stats: return now = time.time() if now - self._last_logging_time > LOGGING_TIME_S: logger.info( "RUNNING: %s | WAITING: %s", len(self.scheduler.running), len(self.scheduler.waiting), ) self._last_logging_time = now def _handle_client_request(self, request: EngineCoreRequestUnion) -> None: """Handle EngineCoreRequest or EngineCoreABORT from Client.""" if isinstance(request, EngineCoreRequest): self.add_request(request) elif isinstance(request, EngineCoreProfile): self.model_executor.profile(request.is_start) else: # TODO: make an EngineCoreAbort wrapper assert isinstance(request, list) self.abort_requests(request) def process_input_socket(self, input_path: str): """Input socket IO thread.""" # Msgpack serialization decoding. decoder_add_req = PickleEncoder() decoder_abort_req = PickleEncoder() with zmq_socket_ctx(input_path, zmq.constants.PULL) as socket: while True: # (RequestType, RequestData) type_frame, data_frame = socket.recv_multipart(copy=False) request_type = type_frame.buffer request_data = data_frame.buffer # Deserialize the request data. if request_type == EngineCoreRequestType.ADD.value: request = decoder_add_req.decode(request_data) elif request_type == EngineCoreRequestType.ABORT.value: request = decoder_abort_req.decode(request_data) elif request_type == EngineCoreRequestType.PROFILE.value: request = pickle.loads(request_data) else: raise ValueError(f"Unknown RequestType: {request_type}") # Push to input queue for core busy loop. self.input_queue.put_nowait(request) def process_output_socket(self, output_path: str): """Output socket IO thread.""" # Msgpack serialization encoding. encoder = msgpack.Encoder() # Reuse send buffer. buffer = bytearray() with zmq_socket_ctx(output_path, zmq.constants.PUSH) as socket: while True: engine_core_outputs = self.output_queue.get() outputs = EngineCoreOutputs(outputs=engine_core_outputs) encoder.encode_into(outputs, buffer) socket.send_multipart((buffer, ), copy=False)