ViperEkura
53c804e233
- Engine/Scheduler/TaskManager: merge max_prompt_len into max_seq_len - train.py: replace bare assert with ValueError/FileNotFoundError - server.py: add --max_seq_len CLI option - engine.py: remove dead page_size param
286 lines
9.0 KiB
Python
286 lines
9.0 KiB
Python
import logging
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import threading
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import time
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import uuid
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from collections import deque
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from enum import Enum
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from typing import Any, Callable, Deque, Dict, List, Optional
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from astrai.tokenize.tokenizer import AutoTokenizer
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logger = logging.getLogger(__name__)
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STOP = object()
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class StreamDecoder:
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"""Incremental decoder for byte-level BPE streaming.
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Byte-level BPE may split a single Unicode character (e.g. em-dash,
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smart quotes) across multiple tokens. Decoding such a token in
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isolation produces U+FFFD (replacement char). This decoder
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accumulates token IDs and only emits text once the trailing
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characters are complete, buffering incomplete multi-byte sequences
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until the next token arrives.
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"""
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__slots__ = ("_tokenizer", "_ids", "_emitted")
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def __init__(self, tokenizer: AutoTokenizer):
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self._tokenizer = tokenizer
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self._ids: List[int] = []
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self._emitted: str = ""
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def push(self, token_id: int) -> str:
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"""Append a token ID and return newly completed text.
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Returns "" while a multi-byte character is still incomplete.
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"""
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self._ids.append(token_id)
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full = self._tokenizer.decode(self._ids, skip_special_tokens=True)
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if full.endswith("\ufffd"):
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return ""
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if len(full) > len(self._emitted):
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diff = full[len(self._emitted) :]
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self._emitted = full
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return diff
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return ""
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class TaskStatus(Enum):
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"""Task lifecycle states."""
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PENDING = "pending"
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RUNNING = "running"
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FINISHED = "finished"
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ABORTED = "aborted"
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class Task:
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"""Single generation request: prompt, sampling params, output state."""
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def __init__(
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self,
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task_id: str,
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prompt_ids: List[int],
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max_tokens: Optional[int] = None,
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temperature: float = 1.0,
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top_p: float = 1.0,
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top_k: int = 50,
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frequency_penalty: float = 0.0,
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rep_window: int = 64,
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):
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self.task_id = task_id
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self.prompt_ids = prompt_ids
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self.max_tokens = max_tokens
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self.temperature = temperature
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self.top_p = top_p
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self.top_k = top_k
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self.frequency_penalty = frequency_penalty
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self.rep_window = rep_window
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self.status = TaskStatus.PENDING
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self.output_ids: List[int] = []
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self.output_logprobs: List[float] = []
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self.input_tokens: int = 0
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self.output_tokens: int = 0
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self.arrival_time = time.time()
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self.finish_time: Optional[float] = None
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self._decoder: Optional[StreamDecoder] = None
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def decode_new_token(self, tokenizer: AutoTokenizer) -> str:
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"""Decode the last appended output token, buffering incomplete
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multi-byte sequences across calls.
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Lazily creates a :class:`StreamDecoder` on first use.
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"""
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if self._decoder is None:
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self._decoder = StreamDecoder(tokenizer)
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return self._decoder.push(self.output_ids[-1])
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def flush_remaining(self, tokenizer: AutoTokenizer) -> str:
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"""Emit any text still buffered in the decoder.
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Called when generation terminates (max_tokens reached, stop
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sequence, or external removal) to avoid dropping a final
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incomplete-looking fragment that is actually complete when
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adjacent to the stop token.
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"""
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if self._decoder is None or not self.output_ids:
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return ""
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full = tokenizer.decode(self.output_ids, skip_special_tokens=True)
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if len(full) > len(self._decoder._emitted):
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diff = full[len(self._decoder._emitted) :]
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self._decoder._emitted = full
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return diff
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return ""
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@property
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def next_pos(self) -> int:
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return self.input_tokens + len(self.output_ids)
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def is_finished(self, stop_ids: List[int]) -> bool:
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if self.max_tokens is not None and self.output_tokens >= self.max_tokens:
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return True
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if self.output_ids and self.output_ids[-1] in stop_ids:
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return True
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return False
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class TaskManager:
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"""Thread-safe task queues and lifecycle transitions (no page ops)."""
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def __init__(
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self,
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tokenizer: AutoTokenizer,
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max_batch_size: int = 16,
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max_seq_len: int = 8192,
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):
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self.tokenizer = tokenizer
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self.max_batch_size = max_batch_size
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self.max_seq_len = max_seq_len
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self.waiting_queue: Deque[Task] = deque()
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self.active_tasks: List[Task] = []
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self._callbacks: Dict[str, Callable[[str], None]] = {}
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self._task_event = threading.Event()
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self._lock = threading.Lock()
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self._total_tasks = 0
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self._total_tokens = 0
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def add_task(
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self,
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prompt: str,
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max_tokens: Optional[int] = None,
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temperature: float = 1.0,
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top_p: float = 1.0,
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top_k: int = 50,
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frequency_penalty: float = 0.0,
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rep_window: int = 64,
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stream_callback: Optional[Callable[[str], None]] = None,
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) -> str:
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task_id = f"task_{int(time.time())}_{uuid.uuid4().hex[:8]}"
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prompt_ids = self.tokenizer.encode(prompt)
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if len(prompt_ids) > self.max_seq_len:
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prompt_ids = prompt_ids[-self.max_seq_len :]
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if len(prompt_ids) > self.max_seq_len:
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if stream_callback:
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stream_callback(STOP)
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return task_id
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if max_tokens is None:
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max_tokens = self.max_seq_len - len(prompt_ids)
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else:
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max_tokens = min(max_tokens, self.max_seq_len - len(prompt_ids))
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task = Task(
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task_id=task_id,
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prompt_ids=prompt_ids,
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max_tokens=max_tokens,
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temperature=temperature,
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top_p=top_p,
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top_k=top_k,
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frequency_penalty=frequency_penalty,
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rep_window=rep_window,
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)
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with self._lock:
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self.waiting_queue.append(task)
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self._total_tasks += 1
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if stream_callback:
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self._callbacks[task_id] = stream_callback
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self._task_event.set()
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return task_id
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def remove_task(self, task_id: str) -> List[Task]:
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with self._lock:
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removed_active = [t for t in self.active_tasks if t.task_id == task_id]
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self.waiting_queue = deque(
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t for t in self.waiting_queue if t.task_id != task_id
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)
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self.active_tasks = [t for t in self.active_tasks if t.task_id != task_id]
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self._callbacks.pop(task_id, None)
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return removed_active
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def invoke_callback(self, task_id: str, token: str):
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cb = self._callbacks.get(task_id)
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if cb:
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cb(token)
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def get_stats(self) -> Dict[str, Any]:
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return {
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"total_tasks": self._total_tasks,
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"total_tokens": self._total_tokens,
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"active_tasks": len(self.active_tasks),
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"waiting_queue": len(self.waiting_queue),
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}
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def remove_finished_tasks(self, stop_ids: List[int]) -> List[Task]:
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with self._lock:
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finished = []
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for task in self.active_tasks:
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if task.status == TaskStatus.ABORTED:
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task.finish_time = time.time()
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finished.append(task)
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elif task.is_finished(stop_ids):
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task.status = TaskStatus.FINISHED
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task.finish_time = time.time()
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finished.append(task)
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self._total_tokens += task.output_tokens
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self.active_tasks = [
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t
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for t in self.active_tasks
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if t.status not in (TaskStatus.FINISHED, TaskStatus.ABORTED)
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]
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return finished
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def pull_candidates(self, n: int) -> List[Task]:
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to_add: List[Task] = []
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with self._lock:
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take = min(n, len(self.waiting_queue))
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for _ in range(take):
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to_add.append(self.waiting_queue.popleft())
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return to_add
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def activate(self, task: Task):
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task.status = TaskStatus.RUNNING
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with self._lock:
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self.active_tasks.append(task)
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def return_to_waiting(self, tasks: List[Task]):
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with self._lock:
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for task in reversed(tasks):
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self.waiting_queue.appendleft(task)
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def has_work(self) -> bool:
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return bool(self.active_tasks or self.waiting_queue)
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def wait_for_tasks(self, timeout: float = 1.0):
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with self._lock:
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if self.waiting_queue or self.active_tasks:
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return
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self._task_event.clear()
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self._task_event.wait(timeout=timeout)
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def get_active_tasks(self) -> List[Task]:
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with self._lock:
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return list(self.active_tasks)
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def get_waiting_tasks(self) -> List[Task]:
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with self._lock:
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return list(self.waiting_queue)
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def clear_queues(self):
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with self._lock:
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self.waiting_queue.clear()
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self.active_tasks.clear()
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self._callbacks.clear()
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def wake(self):
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self._task_event.set()
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