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[RL] Add Pause and Resume Generation for Asynchronous RL Training (#28037)
Signed-off-by: SamitHuang <285365963@qq.com> Signed-off-by: Samit <285365963@qq.com> Signed-off-by: samithuang <285365963@qq.com> Co-authored-by: 22quinn <33176974+22quinn@users.noreply.github.com>
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@ -149,6 +149,33 @@ class EngineClient(ABC):
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"""Load a new LoRA adapter into the engine for future requests."""
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...
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@abstractmethod
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async def pause_generation(
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self,
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*,
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wait_for_inflight_requests: bool = False,
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clear_cache: bool = True,
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) -> None:
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"""Pause new generation/encoding requests.
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Args:
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wait_for_inflight_requests: When ``True`` waits for in-flight requests
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to finish before pausing. When ``False`` (default), aborts in-flight
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requests immediately.
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clear_cache: Whether to clear KV and prefix caches after draining.
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"""
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...
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@abstractmethod
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async def resume_generation(self) -> None:
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"""Resume accepting generation/encoding requests."""
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...
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@abstractmethod
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async def is_paused(self) -> bool:
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"""Return whether the engine is currently paused."""
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...
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async def scale_elastic_ep(
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self, new_data_parallel_size: int, drain_timeout: int = 300
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) -> None:
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@ -394,6 +394,84 @@ async def get_server_load_metrics(request: Request):
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return JSONResponse(content={"server_load": request.app.state.server_load_metrics})
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@router.post("/pause")
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async def pause_generation(
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raw_request: Request,
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wait_for_inflight_requests: bool = Query(False),
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clear_cache: bool = Query(True),
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) -> JSONResponse:
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"""Pause generation requests to allow weight updates.
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Args:
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wait_for_inflight_requests: When ``True`` waits for in-flight
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requests to finish before pausing. When ``False`` (default),
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aborts any in-flight requests immediately.
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clear_cache: Whether to clear KV/prefix caches after draining.
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"""
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engine = engine_client(raw_request)
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try:
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await engine.pause_generation(
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wait_for_inflight_requests=wait_for_inflight_requests,
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clear_cache=clear_cache,
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)
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return JSONResponse(
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content={"status": "paused"},
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status_code=HTTPStatus.OK.value,
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)
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except ValueError as err:
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return JSONResponse(
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content={"error": str(err)},
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status_code=HTTPStatus.BAD_REQUEST.value,
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)
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except Exception as err: # pragma: no cover - defensive
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logger.exception("Failed to pause generation")
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return JSONResponse(
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content={"error": f"Failed to pause generation: {err}"},
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status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value,
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)
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@router.post("/resume")
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async def resume_generation(raw_request: Request) -> JSONResponse:
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"""Resume generation after a pause."""
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engine = engine_client(raw_request)
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try:
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await engine.resume_generation()
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return JSONResponse(
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content={"status": "resumed"},
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status_code=HTTPStatus.OK.value,
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)
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except Exception as err: # pragma: no cover - defensive
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logger.exception("Failed to resume generation")
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return JSONResponse(
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content={"error": f"Failed to resume generation: {err}"},
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status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value,
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)
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@router.get("/is_paused")
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async def is_paused(raw_request: Request) -> JSONResponse:
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"""Return the current pause status."""
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engine = engine_client(raw_request)
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try:
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paused = await engine.is_paused()
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except Exception as err: # pragma: no cover - defensive
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logger.exception("Failed to fetch pause status")
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return JSONResponse(
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content={"error": f"Failed to fetch pause status: {err}"},
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status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value,
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)
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return JSONResponse(content={"is_paused": paused})
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@router.post(
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"/tokenize",
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dependencies=[Depends(validate_json_request)],
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@ -152,6 +152,10 @@ class AsyncLLM(EngineClient):
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)
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self.logger_manager.log_engine_initialized()
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# Pause / resume state for async RL workflows.
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self._pause_cond = asyncio.Condition()
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self._paused = False
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self.output_handler: asyncio.Task | None = None
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try:
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# Start output handler eagerly if we are in the asyncio eventloop.
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@ -404,6 +408,10 @@ class AsyncLLM(EngineClient):
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# to handle startup failure gracefully in the OpenAI server.
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self._run_output_handler()
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# Wait until generation is resumed if the engine is paused.
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async with self._pause_cond:
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await self._pause_cond.wait_for(lambda: not self._paused)
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if tokenization_kwargs is None:
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tokenization_kwargs = {}
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truncate_prompt_tokens = sampling_params.truncate_prompt_tokens
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@ -551,6 +559,58 @@ class AsyncLLM(EngineClient):
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if self.log_requests:
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logger.info("Aborted request(s) %s.", ",".join(request_ids))
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async def pause_generation(
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self,
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*,
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wait_for_inflight_requests: bool = False,
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clear_cache: bool = True,
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) -> None:
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"""
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Pause generation to allow model weight updates.
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New generation/encoding requests are blocked until resume.
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Args:
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wait_for_inflight_requests: When ``True`` waits for in-flight
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requests to finish before pausing. When ``False`` (default),
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immediately aborts any in-flight requests.
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clear_cache: Whether to clear KV cache and prefix cache after
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draining. Set to ``False`` to preserve cache for faster resume.
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Default is ``True`` (clear caches).
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"""
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async with self._pause_cond:
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if self._paused:
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return
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self._paused = True
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if not wait_for_inflight_requests:
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request_ids = list(self.output_processor.request_states.keys())
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if request_ids:
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await self.abort(request_ids)
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# Wait for running requests to drain before clearing cache.
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if self.output_processor.has_unfinished_requests():
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await self.output_processor.wait_for_requests_to_drain()
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# Clear cache
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if clear_cache:
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await self.reset_prefix_cache()
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await self.reset_mm_cache()
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async def resume_generation(self) -> None:
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"""Resume generation after :meth:`pause_generation`."""
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async with self._pause_cond:
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self._paused = False
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self._pause_cond.notify_all() # Wake up all waiting requests
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async def is_paused(self) -> bool:
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"""Return whether the engine is currently paused."""
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async with self._pause_cond:
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return self._paused
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async def encode(
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self,
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prompt: PromptType,
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@ -582,6 +642,10 @@ class AsyncLLM(EngineClient):
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# to handle startup failure gracefully in the OpenAI server.
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self._run_output_handler()
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# Respect pause state before accepting new requests.
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async with self._pause_cond:
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await self._pause_cond.wait_for(lambda: not self._paused)
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if tokenization_kwargs is None:
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tokenization_kwargs = {}
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_validate_truncation_size(
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@ -350,6 +350,8 @@ class OutputProcessor:
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self.parent_requests: dict[str, ParentRequest] = {}
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self.lora_states = LoRARequestStates(log_stats)
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self.tracer: Tracer | None = None
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self._requests_drained = asyncio.Event()
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self._requests_drained.set()
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def get_num_unfinished_requests(self):
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return len(self.request_states)
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@ -357,6 +359,11 @@ class OutputProcessor:
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def has_unfinished_requests(self) -> bool:
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return len(self.request_states) > 0
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async def wait_for_requests_to_drain(self) -> None:
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if not self.request_states:
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return
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await self._requests_drained.wait()
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def propagate_error(self, e: Exception):
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"""Propagate error to all generate() tasks."""
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@ -396,6 +403,8 @@ class OutputProcessor:
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child_reqs = self.abort_requests(child_reqs)
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request_ids_to_abort.extend(child_reqs)
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self.parent_requests.pop(request_id, None)
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if not self.request_states:
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self._requests_drained.set()
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return request_ids_to_abort
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def add_request(
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@ -420,6 +429,8 @@ class OutputProcessor:
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log_stats=self.log_stats,
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stream_interval=self.stream_interval,
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)
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if self._requests_drained.is_set():
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self._requests_drained.clear()
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self.request_states[request_id] = req_state
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if parent_req:
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self.parent_requests[parent_req.request_id] = parent_req
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@ -511,6 +522,8 @@ class OutputProcessor:
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parent_req = req_state.parent_req
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if parent_req and not parent_req.child_requests:
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self.parent_requests.pop(parent_req.request_id, None)
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if not self.request_states:
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self._requests_drained.set()
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if not engine_core_output.finished:
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# If req not finished in EngineCore, but Detokenizer
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# detected stop string, abort needed in EngineCore.
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