mirror of https://github.com/hpcaitech/ColossalAI
aibig-modeldata-parallelismdeep-learningdistributed-computingfoundation-modelsheterogeneous-traininghpcinferencelarge-scalemodel-parallelismpipeline-parallelism
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133 lines
4.5 KiB
133 lines
4.5 KiB
1 year ago
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import asyncio
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from colossalai.inference.dynamic_batching.ray_dist_init import Driver
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from .dynamic_batching.io_struct import RequestOutput
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from .dynamic_batching.sampling_params import SamplingParams
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class RequestTracker:
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"""
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A class for trace down all the requests, abstraction for async
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"""
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def __init__(self) -> None:
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self._requests: asyncio.Queue[str] = asyncio.Queue()
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self._finished_requests: asyncio.Queue[RequestOutput] = asyncio.Queue()
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self.new_requests_event = None
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def __contains__(self, item):
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return item in self._requests
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def init_event(self):
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self.new_requests_event = asyncio.Event()
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def add_request(self, request_id: str):
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"""Add a request to be sent to the engine on the next background
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loop iteration."""
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self._requests.put_nowait(request_id)
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self.new_requests_event.set() # NOTE: we may find a better way to clear this event
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def add_stop(self):
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"""
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Add a StopIteration flag to stop async generator.
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"""
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self._finished_requests.put_nowait(StopIteration)
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self.new_requests_event.clear()
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def process_request_output(self, request_output: RequestOutput) -> None:
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"""Process a request output from the engine."""
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self._finished_requests.put_nowait(request_output)
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async def wait_for_new_requests(self):
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await self.new_requests_event.wait()
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def __aiter__(self):
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return self
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async def __anext__(self) -> RequestOutput:
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result = await self._finished_requests.get()
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# print("result of ", result)
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if result is StopIteration:
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raise StopAsyncIteration
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return result
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class Async_Engine:
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"""
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Use an engine to launch RAY Driver --> RAY Worker --> Async_Manager
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Background loop: inference reqs in waiting list (Listen)
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Request Tracker: manage incoming requests and restore finished ones
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Generate: exposed func for add new input and return finished ones
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"""
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def __init__(
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self,
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router_config,
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engine_config,
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start_engine_loop: bool = True,
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) -> None:
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self.driver = Driver(router_config=router_config, engine_config=engine_config)
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self.background_loop = None
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self.start_engine_loop = start_engine_loop
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self._request_tracker = RequestTracker()
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def _step(self):
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"""
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Logic for handling requests
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"""
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request_outputs = self.driver.step()
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if request_outputs is not None:
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for request_output in request_outputs:
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self._request_tracker.process_request_output(request_output)
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self._request_tracker.add_stop()
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def abort_request(self, request_id: str):
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self.driver.abort(request_id)
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def _has_requests_in_progress(self):
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return self.driver.is_running()
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async def run_loop_fwd(self):
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has_requests_in_progress = self._has_requests_in_progress()
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while True:
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if not has_requests_in_progress:
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await self._request_tracker.wait_for_new_requests()
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self._step()
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await asyncio.sleep(0)
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@property
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def is_running(self):
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return self.background_loop is not None and not self.background_loop.done()
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def start_background_loop(self):
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if self.is_running:
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raise RuntimeError("Background loop is already running.")
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self._request_tracker.init_event()
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self.background_loop_unshielded = asyncio.get_event_loop().create_task(self.run_loop_fwd())
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self.background_loop = asyncio.shield(self.background_loop_unshielded)
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async def add_request(self, request_id: str, prompt: str, sampling_params: SamplingParams):
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self.driver.add_input(request_id, prompt, sampling_params)
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self._request_tracker.add_request(request_id)
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async def generate(self, request_id: str, prompt: str, sampling_params: SamplingParams):
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"""
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The only exposed func, adding new request and return a async generator that yields the existing results.
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"""
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try:
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if not self.is_running:
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self.start_background_loop()
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await self.add_request(request_id, prompt, sampling_params)
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async for request_output in self._request_tracker:
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yield request_output
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except (Exception, asyncio.CancelledError) as e:
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# If there is an exception or coroutine is cancelled, abort the request.
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self.abort_request(request_id)
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raise e
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