| from __future__ import annotations |
|
|
| import asyncio |
| import copy |
| import sys |
| import time |
| from collections import deque |
| from typing import Any, Deque, Dict, List, Tuple |
|
|
| import fastapi |
| import httpx |
|
|
| from gradio.data_classes import Estimation, PredictBody, Progress, ProgressUnit |
| from gradio.helpers import TrackedIterable |
| from gradio.utils import AsyncRequest, run_coro_in_background, set_task_name |
|
|
|
|
| class Event: |
| def __init__( |
| self, |
| websocket: fastapi.WebSocket, |
| session_hash: str, |
| fn_index: int, |
| ): |
| self.websocket = websocket |
| self.session_hash: str = session_hash |
| self.fn_index: int = fn_index |
| self._id = f"{self.session_hash}_{self.fn_index}" |
| self.data: PredictBody | None = None |
| self.lost_connection_time: float | None = None |
| self.token: str | None = None |
| self.progress: Progress | None = None |
| self.progress_pending: bool = False |
|
|
| async def disconnect(self, code: int = 1000): |
| await self.websocket.close(code=code) |
|
|
|
|
| class Queue: |
| def __init__( |
| self, |
| live_updates: bool, |
| concurrency_count: int, |
| update_intervals: float, |
| max_size: int | None, |
| blocks_dependencies: List, |
| ): |
| self.event_queue: Deque[Event] = deque() |
| self.events_pending_reconnection = [] |
| self.stopped = False |
| self.max_thread_count = concurrency_count |
| self.update_intervals = update_intervals |
| self.active_jobs: List[None | List[Event]] = [None] * concurrency_count |
| self.delete_lock = asyncio.Lock() |
| self.server_path = None |
| self.duration_history_total = 0 |
| self.duration_history_count = 0 |
| self.avg_process_time = 0 |
| self.avg_concurrent_process_time = None |
| self.queue_duration = 1 |
| self.live_updates = live_updates |
| self.sleep_when_free = 0.05 |
| self.progress_update_sleep_when_free = 0.1 |
| self.max_size = max_size |
| self.blocks_dependencies = blocks_dependencies |
| self.access_token = "" |
| self.queue_client = None |
|
|
| async def start(self, progress_tracking=False): |
| |
| self.queue_client = httpx.AsyncClient() |
|
|
| run_coro_in_background(self.start_processing) |
| if progress_tracking: |
| run_coro_in_background(self.start_progress_tracking) |
| if not self.live_updates: |
| run_coro_in_background(self.notify_clients) |
|
|
| def close(self): |
| self.stopped = True |
|
|
| def resume(self): |
| self.stopped = False |
|
|
| def set_url(self, url: str): |
| self.server_path = url |
|
|
| def set_access_token(self, token: str): |
| self.access_token = token |
|
|
| def get_active_worker_count(self) -> int: |
| count = 0 |
| for worker in self.active_jobs: |
| if worker is not None: |
| count += 1 |
| return count |
|
|
| def get_events_in_batch(self) -> Tuple[List[Event] | None, bool]: |
| if not (self.event_queue): |
| return None, False |
|
|
| first_event = self.event_queue.popleft() |
| events = [first_event] |
|
|
| event_fn_index = first_event.fn_index |
| batch = self.blocks_dependencies[event_fn_index]["batch"] |
|
|
| if batch: |
| batch_size = self.blocks_dependencies[event_fn_index]["max_batch_size"] |
| rest_of_batch = [ |
| event for event in self.event_queue if event.fn_index == event_fn_index |
| ][: batch_size - 1] |
| events.extend(rest_of_batch) |
| [self.event_queue.remove(event) for event in rest_of_batch] |
|
|
| return events, batch |
|
|
| async def start_processing(self) -> None: |
| while not self.stopped: |
| if not self.event_queue: |
| await asyncio.sleep(self.sleep_when_free) |
| continue |
|
|
| if not (None in self.active_jobs): |
| await asyncio.sleep(self.sleep_when_free) |
| continue |
| |
| async with self.delete_lock: |
| events, batch = self.get_events_in_batch() |
|
|
| if events: |
| self.active_jobs[self.active_jobs.index(None)] = events |
| task = run_coro_in_background(self.process_events, events, batch) |
| run_coro_in_background(self.broadcast_live_estimations) |
| set_task_name(task, events[0].session_hash, events[0].fn_index, batch) |
|
|
| async def start_progress_tracking(self) -> None: |
| while not self.stopped: |
| if not any(self.active_jobs): |
| await asyncio.sleep(self.progress_update_sleep_when_free) |
| continue |
|
|
| for job in self.active_jobs: |
| if job is None: |
| continue |
| for event in job: |
| if event.progress_pending and event.progress: |
| event.progress_pending = False |
| client_awake = await self.send_message( |
| event, event.progress.dict() |
| ) |
| if not client_awake: |
| await self.clean_event(event) |
|
|
| await asyncio.sleep(self.progress_update_sleep_when_free) |
|
|
| def set_progress( |
| self, |
| event_id: str, |
| iterables: List[TrackedIterable] | None, |
| ): |
| if iterables is None: |
| return |
| for job in self.active_jobs: |
| if job is None: |
| continue |
| for evt in job: |
| if evt._id == event_id: |
| progress_data: List[ProgressUnit] = [] |
| for iterable in iterables: |
| progress_unit = ProgressUnit( |
| index=iterable.index, |
| length=iterable.length, |
| unit=iterable.unit, |
| progress=iterable.progress, |
| desc=iterable.desc, |
| ) |
| progress_data.append(progress_unit) |
| evt.progress = Progress(progress_data=progress_data) |
| evt.progress_pending = True |
|
|
| def push(self, event: Event) -> int | None: |
| """ |
| Add event to queue, or return None if Queue is full |
| Parameters: |
| event: Event to add to Queue |
| Returns: |
| rank of submitted Event |
| """ |
| queue_len = len(self.event_queue) |
| if self.max_size is not None and queue_len >= self.max_size: |
| return None |
| self.event_queue.append(event) |
| return queue_len |
|
|
| async def clean_event(self, event: Event) -> None: |
| if event in self.event_queue: |
| async with self.delete_lock: |
| self.event_queue.remove(event) |
|
|
| async def broadcast_live_estimations(self) -> None: |
| """ |
| Runs 2 functions sequentially instead of concurrently. Otherwise dced clients are tried to get deleted twice. |
| """ |
| if self.live_updates: |
| await self.broadcast_estimations() |
|
|
| async def gather_event_data(self, event: Event) -> bool: |
| """ |
| Gather data for the event |
| |
| Parameters: |
| event: |
| """ |
| if not event.data: |
| client_awake = await self.send_message(event, {"msg": "send_data"}) |
| if not client_awake: |
| return False |
| event.data = await self.get_message(event) |
| return True |
|
|
| async def notify_clients(self) -> None: |
| """ |
| Notify clients about events statuses in the queue periodically. |
| """ |
| while not self.stopped: |
| await asyncio.sleep(self.update_intervals) |
| if self.event_queue: |
| await self.broadcast_estimations() |
|
|
| async def broadcast_estimations(self) -> None: |
| estimation = self.get_estimation() |
| |
| await asyncio.gather( |
| *[ |
| self.send_estimation(event, estimation, rank) |
| for rank, event in enumerate(self.event_queue) |
| ] |
| ) |
|
|
| async def send_estimation( |
| self, event: Event, estimation: Estimation, rank: int |
| ) -> Estimation: |
| """ |
| Send estimation about ETA to the client. |
| |
| Parameters: |
| event: |
| estimation: |
| rank: |
| """ |
| estimation.rank = rank |
|
|
| if self.avg_concurrent_process_time is not None: |
| estimation.rank_eta = ( |
| estimation.rank * self.avg_concurrent_process_time |
| + self.avg_process_time |
| ) |
| if None not in self.active_jobs: |
| |
| estimation.rank_eta += self.avg_concurrent_process_time |
| client_awake = await self.send_message(event, estimation.dict()) |
| if not client_awake: |
| await self.clean_event(event) |
| return estimation |
|
|
| def update_estimation(self, duration: float) -> None: |
| """ |
| Update estimation by last x element's average duration. |
| |
| Parameters: |
| duration: |
| """ |
| self.duration_history_total += duration |
| self.duration_history_count += 1 |
| self.avg_process_time = ( |
| self.duration_history_total / self.duration_history_count |
| ) |
| self.avg_concurrent_process_time = self.avg_process_time / min( |
| self.max_thread_count, self.duration_history_count |
| ) |
| self.queue_duration = self.avg_concurrent_process_time * len(self.event_queue) |
|
|
| def get_estimation(self) -> Estimation: |
| return Estimation( |
| queue_size=len(self.event_queue), |
| avg_event_process_time=self.avg_process_time, |
| avg_event_concurrent_process_time=self.avg_concurrent_process_time, |
| queue_eta=self.queue_duration, |
| ) |
|
|
| def get_request_params(self, websocket: fastapi.WebSocket) -> Dict[str, Any]: |
| return { |
| "url": str(websocket.url), |
| "headers": dict(websocket.headers), |
| "query_params": dict(websocket.query_params), |
| "path_params": dict(websocket.path_params), |
| "client": dict(host=websocket.client.host, port=websocket.client.port), |
| } |
|
|
| async def call_prediction(self, events: List[Event], batch: bool): |
| data = events[0].data |
| assert data is not None, "No event data" |
| token = events[0].token |
| data.event_id = events[0]._id if not batch else None |
| try: |
| data.request = self.get_request_params(events[0].websocket) |
| except ValueError: |
| pass |
|
|
| if batch: |
| data.data = list(zip(*[event.data.data for event in events if event.data])) |
| data.request = [ |
| self.get_request_params(event.websocket) |
| for event in events |
| if event.data |
| ] |
| data.batched = True |
| response = await AsyncRequest( |
| method=AsyncRequest.Method.POST, |
| url=f"{self.server_path}api/predict", |
| json=dict(data), |
| headers={"Authorization": f"Bearer {self.access_token}"}, |
| cookies={"access-token": token} if token is not None else None, |
| client=self.queue_client, |
| ) |
| return response |
|
|
| async def process_events(self, events: List[Event], batch: bool) -> None: |
| awake_events: List[Event] = [] |
| try: |
| for event in events: |
| client_awake = await self.gather_event_data(event) |
| if client_awake: |
| client_awake = await self.send_message( |
| event, {"msg": "process_starts"} |
| ) |
| if client_awake: |
| awake_events.append(event) |
| if not awake_events: |
| return |
| begin_time = time.time() |
| response = await self.call_prediction(awake_events, batch) |
| if response.has_exception: |
| for event in awake_events: |
| await self.send_message( |
| event, |
| { |
| "msg": "process_completed", |
| "output": {"error": str(response.exception)}, |
| "success": False, |
| }, |
| ) |
| elif response.json.get("is_generating", False): |
| old_response = response |
| while response.json.get("is_generating", False): |
| |
| |
| |
| if sys.version_info < (3, 8): |
| is_alive = await self.send_message(event, {"msg": "alive?"}) |
| if not is_alive: |
| return |
| old_response = response |
| open_ws = [] |
| for event in awake_events: |
| open = await self.send_message( |
| event, |
| { |
| "msg": "process_generating", |
| "output": old_response.json, |
| "success": old_response.status == 200, |
| }, |
| ) |
| open_ws.append(open) |
| awake_events = [ |
| e for e, is_open in zip(awake_events, open_ws) if is_open |
| ] |
| if not awake_events: |
| return |
| response = await self.call_prediction(awake_events, batch) |
| for event in awake_events: |
| if response.status != 200: |
| relevant_response = response |
| else: |
| relevant_response = old_response |
|
|
| await self.send_message( |
| event, |
| { |
| "msg": "process_completed", |
| "output": relevant_response.json, |
| "success": relevant_response.status == 200, |
| }, |
| ) |
| else: |
| output = copy.deepcopy(response.json) |
| for e, event in enumerate(awake_events): |
| if batch and "data" in output: |
| output["data"] = list(zip(*response.json.get("data")))[e] |
| await self.send_message( |
| event, |
| { |
| "msg": "process_completed", |
| "output": output, |
| "success": response.status == 200, |
| }, |
| ) |
| end_time = time.time() |
| if response.status == 200: |
| self.update_estimation(end_time - begin_time) |
| finally: |
| for event in awake_events: |
| try: |
| await event.disconnect() |
| except Exception: |
| pass |
| self.active_jobs[self.active_jobs.index(events)] = None |
| for event in awake_events: |
| await self.clean_event(event) |
| |
| |
| |
| |
| await self.reset_iterators(event.session_hash, event.fn_index) |
|
|
| async def send_message(self, event, data: Dict) -> bool: |
| try: |
| await event.websocket.send_json(data=data) |
| return True |
| except: |
| await self.clean_event(event) |
| return False |
|
|
| async def get_message(self, event) -> PredictBody | None: |
| try: |
| data = await event.websocket.receive_json() |
| return PredictBody(**data) |
| except: |
| await self.clean_event(event) |
| return None |
|
|
| async def reset_iterators(self, session_hash: str, fn_index: int): |
| await AsyncRequest( |
| method=AsyncRequest.Method.POST, |
| url=f"{self.server_path}reset", |
| json={ |
| "session_hash": session_hash, |
| "fn_index": fn_index, |
| }, |
| client=self.queue_client, |
| ) |
|
|