forked from M-Labs/artiq
482 lines
17 KiB
Python
482 lines
17 KiB
Python
import asyncio
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import logging
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from enum import Enum
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from time import time
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from sipyco.sync_struct import Notifier
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from sipyco.asyncio_tools import TaskObject, Condition
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from artiq.master.worker import Worker, log_worker_exception
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from artiq.tools import asyncio_wait_or_cancel
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logger = logging.getLogger(__name__)
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class RunStatus(Enum):
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pending = 0
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flushing = 1
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preparing = 2
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prepare_done = 3
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running = 4
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run_done = 5
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analyzing = 6
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deleting = 7
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paused = 8
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def _mk_worker_method(name):
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async def worker_method(self, *args, **kwargs):
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if self.worker.closed.is_set():
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return True
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m = getattr(self.worker, name)
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try:
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return await m(*args, **kwargs)
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except Exception as e:
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if isinstance(e, asyncio.CancelledError):
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raise
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if self.worker.closed.is_set():
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logger.debug("suppressing worker exception of terminated run",
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exc_info=True)
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# Return completion on termination
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return True
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else:
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raise
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return worker_method
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class Run:
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def __init__(self, rid, pipeline_name,
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wd, expid, priority, due_date, flush,
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pool, **kwargs):
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# called through pool
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self.rid = rid
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self.pipeline_name = pipeline_name
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self.wd = wd
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self.expid = expid
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self.priority = priority
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self.due_date = due_date
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self.flush = flush
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self.worker = Worker(pool.worker_handlers)
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self.termination_requested = False
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self._status = RunStatus.pending
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notification = {
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"pipeline": self.pipeline_name,
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"expid": self.expid,
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"priority": self.priority,
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"due_date": self.due_date,
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"flush": self.flush,
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"status": self._status.name
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}
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notification.update(kwargs)
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self._notifier = pool.notifier
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self._notifier[self.rid] = notification
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self._state_changed = pool.state_changed
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@property
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def status(self):
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return self._status
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@status.setter
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def status(self, value):
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self._status = value
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if not self.worker.closed.is_set():
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self._notifier[self.rid]["status"] = self._status.name
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self._state_changed.notify()
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def priority_key(self):
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"""Return a comparable value that defines a run priority order.
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Applies only to runs the due date of which has already elapsed.
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"""
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return (self.priority, -(self.due_date or 0), -self.rid)
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async def close(self):
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# called through pool
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await self.worker.close()
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del self._notifier[self.rid]
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_build = _mk_worker_method("build")
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async def build(self):
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await self._build(self.rid, self.pipeline_name,
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self.wd, self.expid,
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self.priority)
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prepare = _mk_worker_method("prepare")
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run = _mk_worker_method("run")
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resume = _mk_worker_method("resume")
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analyze = _mk_worker_method("analyze")
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class RunPool:
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def __init__(self, ridc, worker_handlers, notifier, experiment_db):
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self.runs = dict()
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self.state_changed = Condition()
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self.ridc = ridc
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self.worker_handlers = worker_handlers
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self.notifier = notifier
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self.experiment_db = experiment_db
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def submit(self, expid, priority, due_date, flush, pipeline_name):
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# mutates expid to insert head repository revision if None.
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# called through scheduler.
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rid = self.ridc.get()
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if "repo_rev" in expid:
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if expid["repo_rev"] is None:
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expid["repo_rev"] = self.experiment_db.cur_rev
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wd, repo_msg = self.experiment_db.repo_backend.request_rev(
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expid["repo_rev"])
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else:
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wd, repo_msg = None, None
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run = Run(rid, pipeline_name, wd, expid, priority, due_date, flush,
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self, repo_msg=repo_msg)
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self.runs[rid] = run
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self.state_changed.notify()
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return rid
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async def delete(self, rid):
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# called through deleter
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if rid not in self.runs:
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return
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run = self.runs[rid]
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await run.close()
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if "repo_rev" in run.expid:
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self.experiment_db.repo_backend.release_rev(run.expid["repo_rev"])
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del self.runs[rid]
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class PrepareStage(TaskObject):
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def __init__(self, pool, delete_cb):
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self.pool = pool
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self.delete_cb = delete_cb
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def _get_run(self):
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"""If a run should get prepared now, return it. Otherwise, return a
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float giving the time until the next check, or None if no time-based
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check is required.
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The latter can be the case if there are no due-date runs, or none
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of them are going to become next-in-line before further pool state
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changes (which will also cause a re-evaluation).
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"""
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pending_runs = list(
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filter(lambda r: r.status == RunStatus.pending,
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self.pool.runs.values()))
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now = time()
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def is_runnable(r):
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return (r.due_date or 0) < now
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prepared_max = max((r.priority_key() for r in self.pool.runs.values()
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if r.status == RunStatus.prepare_done),
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default=None)
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def takes_precedence(r):
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return prepared_max is None or r.priority_key() > prepared_max
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candidate = max(filter(is_runnable, pending_runs),
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key=lambda r: r.priority_key(),
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default=None)
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if candidate is not None and takes_precedence(candidate):
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return candidate
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return min((r.due_date - now for r in pending_runs
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if (not is_runnable(r) and takes_precedence(r))),
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default=None)
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async def _do(self):
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while True:
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run = self._get_run()
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if run is None:
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await self.pool.state_changed.wait()
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elif isinstance(run, float):
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await asyncio_wait_or_cancel([self.pool.state_changed.wait()],
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timeout=run)
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else:
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if run.flush:
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run.status = RunStatus.flushing
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while not all(r.status in (RunStatus.pending,
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RunStatus.deleting)
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or r.priority < run.priority
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or r is run
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for r in self.pool.runs.values()):
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ev = [self.pool.state_changed.wait(),
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run.worker.closed.wait()]
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await asyncio_wait_or_cancel(
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ev, return_when=asyncio.FIRST_COMPLETED)
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if run.worker.closed.is_set():
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break
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if run.worker.closed.is_set():
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continue
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run.status = RunStatus.preparing
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try:
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await run.build()
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await run.prepare()
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except:
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logger.error("got worker exception in prepare stage, "
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"deleting RID %d", run.rid)
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log_worker_exception()
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self.delete_cb(run.rid)
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else:
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run.status = RunStatus.prepare_done
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class RunStage(TaskObject):
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def __init__(self, pool, delete_cb):
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self.pool = pool
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self.delete_cb = delete_cb
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def _get_run(self):
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prepared_runs = filter(lambda r: r.status == RunStatus.prepare_done,
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self.pool.runs.values())
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try:
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r = max(prepared_runs, key=lambda r: r.priority_key())
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except ValueError:
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# prepared_runs is an empty sequence
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r = None
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return r
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async def _do(self):
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stack = []
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while True:
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next_irun = self._get_run()
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if not stack or (
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next_irun is not None and
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next_irun.priority_key() > stack[-1].priority_key()):
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while next_irun is None:
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await self.pool.state_changed.wait()
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next_irun = self._get_run()
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stack.append(next_irun)
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run = stack.pop()
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try:
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if run.status == RunStatus.paused:
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run.status = RunStatus.running
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# clear "termination requested" flag now
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# so that if it is set again during the resume, this
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# results in another exception.
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request_termination = run.termination_requested
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run.termination_requested = False
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completed = await run.resume(request_termination)
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else:
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run.status = RunStatus.running
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completed = await run.run()
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except:
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logger.error("got worker exception in run stage, "
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"deleting RID %d", run.rid)
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log_worker_exception()
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self.delete_cb(run.rid)
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else:
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if completed:
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run.status = RunStatus.run_done
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else:
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run.status = RunStatus.paused
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stack.append(run)
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class AnalyzeStage(TaskObject):
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def __init__(self, pool, delete_cb):
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self.pool = pool
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self.delete_cb = delete_cb
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def _get_run(self):
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run_runs = filter(lambda r: r.status == RunStatus.run_done,
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self.pool.runs.values())
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try:
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r = max(run_runs, key=lambda r: r.priority_key())
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except ValueError:
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# run_runs is an empty sequence
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r = None
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return r
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async def _do(self):
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while True:
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run = self._get_run()
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while run is None:
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await self.pool.state_changed.wait()
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run = self._get_run()
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run.status = RunStatus.analyzing
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try:
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await run.analyze()
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except:
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logger.error("got worker exception in analyze stage of RID %d.",
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run.rid)
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log_worker_exception()
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self.delete_cb(run.rid)
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class Pipeline:
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def __init__(self, ridc, deleter, worker_handlers, notifier, experiment_db):
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self.pool = RunPool(ridc, worker_handlers, notifier, experiment_db)
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self._prepare = PrepareStage(self.pool, deleter.delete)
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self._run = RunStage(self.pool, deleter.delete)
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self._analyze = AnalyzeStage(self.pool, deleter.delete)
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def start(self):
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self._prepare.start()
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self._run.start()
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self._analyze.start()
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async def stop(self):
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# NB: restart of a stopped pipeline is not supported
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await self._analyze.stop()
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await self._run.stop()
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await self._prepare.stop()
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class Deleter(TaskObject):
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"""Provides a synchronous interface for instigating deletion of runs.
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:meth:`RunPool.delete` is an async function (it needs to close the worker
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connection, etc.), so we maintain a queue of RIDs to delete on a background task.
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"""
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def __init__(self, pipelines):
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self._pipelines = pipelines
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self._queue = asyncio.Queue()
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def delete(self, rid):
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"""Delete the run with the given RID.
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Multiple calls for the same RID are silently ignored.
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"""
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logger.debug("delete request for RID %d", rid)
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for pipeline in self._pipelines.values():
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if rid in pipeline.pool.runs:
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pipeline.pool.runs[rid].status = RunStatus.deleting
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break
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self._queue.put_nowait(rid)
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async def join(self):
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await self._queue.join()
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async def _delete(self, rid):
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# By looking up the run by RID, we implicitly make sure to delete each run only
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# once.
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for pipeline in self._pipelines.values():
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if rid in pipeline.pool.runs:
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logger.debug("deleting RID %d...", rid)
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await pipeline.pool.delete(rid)
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logger.debug("deletion of RID %d completed", rid)
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break
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async def _gc_pipelines(self):
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pipeline_names = list(self._pipelines.keys())
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for name in pipeline_names:
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if not self._pipelines[name].pool.runs:
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logger.debug("garbage-collecting pipeline '%s'...", name)
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await self._pipelines[name].stop()
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del self._pipelines[name]
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logger.debug("garbage-collection of pipeline '%s' completed",
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name)
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async def _do(self):
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while True:
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rid = await self._queue.get()
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await self._delete(rid)
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await self._gc_pipelines()
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self._queue.task_done()
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class Scheduler:
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def __init__(self, ridc, worker_handlers, experiment_db):
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self.notifier = Notifier(dict())
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self._pipelines = dict()
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self._worker_handlers = worker_handlers
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self._experiment_db = experiment_db
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self._terminated = False
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self._ridc = ridc
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self._deleter = Deleter(self._pipelines)
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def start(self):
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self._deleter.start()
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async def stop(self):
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# NB: restart of a stopped scheduler is not supported
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self._terminated = True # prevent further runs from being created
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for pipeline in self._pipelines.values():
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for rid in pipeline.pool.runs.keys():
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self._deleter.delete(rid)
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await self._deleter.join()
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await self._deleter.stop()
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if self._pipelines:
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logger.warning("some pipelines were not garbage-collected")
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def submit(self, pipeline_name, expid, priority=0, due_date=None, flush=False):
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"""Submits a new run.
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When called through an experiment, the default values of
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``pipeline_name``, ``expid`` and ``priority`` correspond to those of
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the current run."""
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# mutates expid to insert head repository revision if None
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if self._terminated:
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return
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try:
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pipeline = self._pipelines[pipeline_name]
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except KeyError:
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logger.debug("creating pipeline '%s'", pipeline_name)
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pipeline = Pipeline(self._ridc, self._deleter,
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self._worker_handlers, self.notifier,
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self._experiment_db)
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self._pipelines[pipeline_name] = pipeline
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pipeline.start()
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return pipeline.pool.submit(expid, priority, due_date, flush, pipeline_name)
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def delete(self, rid):
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"""Kills the run with the specified RID."""
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self._deleter.delete(rid)
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def request_termination(self, rid):
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"""Requests graceful termination of the run with the specified RID."""
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for pipeline in self._pipelines.values():
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if rid in pipeline.pool.runs:
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run = pipeline.pool.runs[rid]
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if run.status == RunStatus.running or run.status == RunStatus.paused:
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run.termination_requested = True
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else:
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self.delete(rid)
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break
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def get_status(self):
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"""Returns a dictionary containing information about the runs currently
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tracked by the scheduler.
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Must not be modified."""
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return self.notifier.raw_view
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def check_pause(self, rid):
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"""Returns ``True`` if there is a condition that could make ``pause``
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not return immediately (termination requested or higher priority run).
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The typical purpose of this function is to check from a kernel
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whether returning control to the host and pausing would have an effect,
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in order to avoid the cost of switching kernels in the common case
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where ``pause`` does nothing.
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This function does not have side effects, and does not have to be
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followed by a call to ``pause``.
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"""
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for pipeline in self._pipelines.values():
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if rid in pipeline.pool.runs:
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run = pipeline.pool.runs[rid]
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if run.status != RunStatus.running:
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return False
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if run.termination_requested:
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return True
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prepared_runs = filter(lambda r: r.status == RunStatus.prepare_done,
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pipeline.pool.runs.values())
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try:
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r = max(prepared_runs, key=lambda r: r.priority_key())
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except ValueError:
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# prepared_runs is an empty sequence
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return False
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return r.priority_key() > run.priority_key()
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raise KeyError("RID not found")
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