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artiq/artiq/master/scheduler.py

482 lines
17 KiB
Python

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