Files
AstrAI/astrai/inference/core/task.py
T
ViperEkura a95794d3db perf: use Rust-native DecodeStream for O(n) streaming decode
- Replace hand-rolled StreamDecoder (O(n^2) full-history re-decode per token) with tokenizers.decoders.DecodeStream
- Keep O(1) bounded token buffer internally via prefix drain instead of accumulating all token IDs
- Simplify flush_remaining to no-op since stream always emits completed text per step
- Benchmark on 8000 tokens: 2305ms -> 3.9ms (~592x speedup)
2026-07-28 14:32:10 +08:00

274 lines
8.5 KiB
Python

import logging
import threading
import time
import uuid
from collections import deque
from enum import Enum
from typing import Any, Callable, Deque, Dict, List, Optional
from tokenizers.decoders import DecodeStream
from astrai.tokenize.tokenizer import AutoTokenizer
logger = logging.getLogger(__name__)
STOP = object()
class StreamDecoder:
"""Incremental decoder backed by the tokenizers library's DecodeStream.
Delegates to the Rust-native streaming decoder which maintains an
O(1) bounded token buffer internally (via prefix drain), avoiding
the O(n²) cost of re-decoding the full history on each step.
Multi-byte UTF-8 sequences split across token boundaries are
buffered until complete; ``push`` returns "" while the trailing
sequence is still incomplete.
"""
__slots__ = ("_stream", "_tok")
def __init__(self, tokenizer: AutoTokenizer):
self._tok = tokenizer._tokenizer
self._stream = DecodeStream(skip_special_tokens=True)
def push(self, token_id: int) -> str:
"""Append a token ID and return newly completed text.
Returns "" while a multi-byte character is still incomplete.
"""
chunk = self._stream.step(self._tok, token_id)
return chunk or ""
class TaskStatus(Enum):
"""Task lifecycle states."""
PENDING = "pending"
RUNNING = "running"
FINISHED = "finished"
ABORTED = "aborted"
class Task:
"""Single generation request: prompt, sampling params, output state."""
def __init__(
self,
task_id: str,
prompt_ids: List[int],
max_tokens: Optional[int] = None,
temperature: float = 1.0,
top_p: float = 1.0,
top_k: int = 50,
frequency_penalty: float = 0.0,
rep_window: int = 64,
):
self.task_id = task_id
self.prompt_ids = prompt_ids
self.max_tokens = max_tokens
self.temperature = temperature
self.top_p = top_p
self.top_k = top_k
self.frequency_penalty = frequency_penalty
self.rep_window = rep_window
self.status = TaskStatus.PENDING
self.output_ids: List[int] = []
self.output_logprobs: List[float] = []
self.input_tokens: int = 0
self.output_tokens: int = 0
self.arrival_time = time.time()
self.finish_time: Optional[float] = None
self._decoder: Optional[StreamDecoder] = None
def decode_new_token(self, tokenizer: AutoTokenizer) -> str:
"""Decode the last appended output token, buffering incomplete
multi-byte sequences across calls.
Lazily creates a :class:`StreamDecoder` on first use.
"""
if self._decoder is None:
self._decoder = StreamDecoder(tokenizer)
return self._decoder.push(self.output_ids[-1])
def flush_remaining(self, tokenizer: AutoTokenizer) -> str:
"""Emit any text still buffered in the decoder.
With the Rust-native DecodeStream, the stream is always in a
correct state — any completed text was already emitted by the
last ``push``. A trailing incomplete multi-byte sequence has no
valid text to emit, so this is a no-op.
"""
return ""
@property
def next_pos(self) -> int:
return self.input_tokens + len(self.output_ids)
def is_finished(self, stop_ids: List[int]) -> bool:
if self.max_tokens is not None and self.output_tokens >= self.max_tokens:
return True
if self.output_ids and self.output_ids[-1] in stop_ids:
return True
return False
class TaskManager:
"""Thread-safe task queues and lifecycle transitions (no page ops)."""
def __init__(
self,
tokenizer: AutoTokenizer,
max_batch_size: int = 16,
max_seq_len: int = 8192,
):
self.tokenizer = tokenizer
self.max_batch_size = max_batch_size
self.max_seq_len = max_seq_len
self.waiting_queue: Deque[Task] = deque()
self.active_tasks: List[Task] = []
self._callbacks: Dict[str, Callable[[str], None]] = {}
self._task_event = threading.Event()
self._lock = threading.Lock()
self._total_tasks = 0
self._total_tokens = 0
def add_task(
self,
prompt: str,
max_tokens: Optional[int] = None,
temperature: float = 1.0,
top_p: float = 1.0,
top_k: int = 50,
frequency_penalty: float = 0.0,
rep_window: int = 64,
stream_callback: Optional[Callable[[str], None]] = None,
) -> str:
task_id = f"task_{int(time.time())}_{uuid.uuid4().hex[:8]}"
prompt_ids = self.tokenizer.encode(prompt)
if len(prompt_ids) > self.max_seq_len:
prompt_ids = prompt_ids[-self.max_seq_len :]
if len(prompt_ids) > self.max_seq_len:
if stream_callback:
stream_callback(STOP)
return task_id
if max_tokens is None:
max_tokens = self.max_seq_len - len(prompt_ids)
else:
max_tokens = min(max_tokens, self.max_seq_len - len(prompt_ids))
task = Task(
task_id=task_id,
prompt_ids=prompt_ids,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
top_k=top_k,
frequency_penalty=frequency_penalty,
rep_window=rep_window,
)
with self._lock:
self.waiting_queue.append(task)
self._total_tasks += 1
if stream_callback:
self._callbacks[task_id] = stream_callback
self._task_event.set()
return task_id
def remove_task(self, task_id: str) -> List[Task]:
with self._lock:
removed_active = [t for t in self.active_tasks if t.task_id == task_id]
self.waiting_queue = deque(
t for t in self.waiting_queue if t.task_id != task_id
)
self.active_tasks = [t for t in self.active_tasks if t.task_id != task_id]
self._callbacks.pop(task_id, None)
return removed_active
def invoke_callback(self, task_id: str, token: str):
cb = self._callbacks.get(task_id)
if cb:
cb(token)
def get_stats(self) -> Dict[str, Any]:
return {
"total_tasks": self._total_tasks,
"total_tokens": self._total_tokens,
"active_tasks": len(self.active_tasks),
"waiting_queue": len(self.waiting_queue),
}
def remove_finished_tasks(self, stop_ids: List[int]) -> List[Task]:
with self._lock:
finished = []
for task in self.active_tasks:
if task.status == TaskStatus.ABORTED:
task.finish_time = time.time()
finished.append(task)
elif task.is_finished(stop_ids):
task.status = TaskStatus.FINISHED
task.finish_time = time.time()
finished.append(task)
self._total_tokens += task.output_tokens
self.active_tasks = [
t
for t in self.active_tasks
if t.status not in (TaskStatus.FINISHED, TaskStatus.ABORTED)
]
return finished
def pull_candidates(self, n: int) -> List[Task]:
to_add: List[Task] = []
with self._lock:
take = min(n, len(self.waiting_queue))
for _ in range(take):
to_add.append(self.waiting_queue.popleft())
return to_add
def activate(self, task: Task):
task.status = TaskStatus.RUNNING
with self._lock:
self.active_tasks.append(task)
def return_to_waiting(self, tasks: List[Task]):
with self._lock:
for task in reversed(tasks):
self.waiting_queue.appendleft(task)
def has_work(self) -> bool:
return bool(self.active_tasks or self.waiting_queue)
def wait_for_tasks(self, timeout: float = 1.0):
with self._lock:
if self.waiting_queue or self.active_tasks:
return
self._task_event.clear()
self._task_event.wait(timeout=timeout)
def get_active_tasks(self) -> List[Task]:
with self._lock:
return list(self.active_tasks)
def get_waiting_tasks(self) -> List[Task]:
with self._lock:
return list(self.waiting_queue)
def clear_queues(self):
with self._lock:
self.waiting_queue.clear()
self.active_tasks.clear()
self._callbacks.clear()
def wake(self):
self._task_event.set()