Files
AstrAI/astrai/inference/core/task.py
T
ViperEkura 95c43368ae refactor: unify rollout onto inference engine KV-cache path
- RolloutGenerator now delegates prefill/decode to InferenceScheduler.run_batch (sync API, no background thread), sharing one KV-cache code path with the inference server and eliminating O(n^2) recompute in rollout
- Add sample(return_logprobs=) and Executor.execute_decode(return_logprobs=) to expose behaviour-policy log-probs through the engine; Task gains output_logprobs
- RolloutResult now subclasses RawRollout (adds rewards only), removing duplicated fields
- RolloutRunner.__call__ returns (result, is_fresh) instead of relying on object identity, removing the fragile refresh-detection contract
- Remove O(n^2) generate_responses helper and dead code (_tokenize_prompts, unused old_model arg)
- train_context.py wires InferenceScheduler directly instead of hand-rolling SamplingPipeline
- Tests: +11 covering return_logprobs, run_batch, and KV-cache-backed rollout semantics; 404 pass
2026-07-20 12:52:20 +08:00

288 lines
9.1 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 astrai.tokenize.tokenizer import AutoTokenizer
logger = logging.getLogger(__name__)
STOP = object()
class StreamDecoder:
"""Incremental decoder for byte-level BPE streaming.
Byte-level BPE may split a single Unicode character (e.g. em-dash,
smart quotes) across multiple tokens. Decoding such a token in
isolation produces U+FFFD (replacement char). This decoder
accumulates token IDs and only emits text once the trailing
characters are complete, buffering incomplete multi-byte sequences
until the next token arrives.
"""
__slots__ = ("_tokenizer", "_ids", "_emitted")
def __init__(self, tokenizer: AutoTokenizer):
self._tokenizer = tokenizer
self._ids: List[int] = []
self._emitted: str = ""
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.
"""
self._ids.append(token_id)
full = self._tokenizer.decode(self._ids, skip_special_tokens=True)
if full.endswith("\ufffd"):
return ""
if len(full) > len(self._emitted):
diff = full[len(self._emitted) :]
self._emitted = full
return diff
return ""
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.
Called when generation terminates (max_tokens reached, stop
sequence, or external removal) to avoid dropping a final
incomplete-looking fragment that is actually complete when
adjacent to the stop token.
"""
if self._decoder is None or not self.output_ids:
return ""
full = tokenizer.decode(self.output_ids, skip_special_tokens=True)
if len(full) > len(self._decoder._emitted):
diff = full[len(self._decoder._emitted) :]
self._decoder._emitted = full
return diff
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,
max_prompt_len: int = 512,
):
self.tokenizer = tokenizer
self.max_batch_size = max_batch_size
self.max_seq_len = max_seq_len
self.max_prompt_len = max_prompt_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_prompt_len:
prompt_ids = prompt_ids[-self.max_prompt_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()