forked from M-Labs/artiq
1
0
Fork 0

artiq_run: refactor, support use from within experiments

You can always (under posix) use #!/usr/bin/env artiq_run as
shebang for experiments and make them executable.
Now, you can also do this (portable):

if __name__ == "__main__":
    from artiq.frontend.artiq_run import run
    run()

to make an experiment executable. The CLI options are all inherited.
Also:

* removed --elf: can be inferred from filename
* did some refactoring and cleanup
* use logging for all messages, except the result printing (use -v to get
parameter changes and dummy scheduler actions)
This commit is contained in:
Robert Jördens 2015-04-04 20:42:37 -06:00
parent 43893c6c1d
commit 1a1afd5410
1 changed files with 79 additions and 85 deletions

View File

@ -5,32 +5,36 @@ import sys
import time
from operator import itemgetter
from itertools import chain
import logging
import h5py
from artiq.language.db import *
from artiq.language.experiment import is_experiment
from artiq.language.experiment import is_experiment, Experiment
from artiq.protocols import pyon
from artiq.protocols.file_db import FlatFileDB
from artiq.master.worker_db import DBHub, ResultDB
from artiq.tools import file_import, verbosity_args, init_logger
class ELFRunner(AutoDB):
logger = logging.getLogger(__name__)
class ELFRunner(Experiment, AutoDB):
class DBKeys:
comm = Device()
file = Argument()
def run(self, filename):
with open(filename, "rb") as f:
binary = f.read()
comm.load(binary)
comm.run("run")
comm.serve(dict(), dict())
def run(self):
with open(self.file, "rb") as f:
self.comm.load(f.read())
self.comm.run("run")
self.comm.serve(dict(), dict())
class SimpleParamLogger:
def set(self, timestamp, name, value):
print("Parameter change: {} -> {}".format(name, value))
logger.info("Parameter change: {} = {}".format(name, value))
class DummyWatchdog:
@ -52,26 +56,26 @@ class DummyScheduler:
def run_queued(self, run_params):
rid = self.next_rid
self.next_rid += 1
print("Queuing: {}, RID={}".format(run_params, rid))
logger.info("Queuing: %s, RID=%s", run_params, rid)
return rid
def cancel_queued(self, rid):
print("Cancelling RID {}".format(rid))
logger.info("Cancelling RID %s", rid)
def run_timed(self, run_params, next_run):
trid = self.next_trid
self.next_trid += 1
next_run_s = time.strftime("%m/%d %H:%M:%S", time.localtime(next_run))
print("Timing: {} at {}, TRID={}".format(run_params, next_run_s, trid))
logger.info("Timing: %s at %s, TRID=%s", run_params, next_run_s, trid)
return trid
def cancel_timed(self, trid):
print("Cancelling TRID {}".format(trid))
logger.info("Cancelling TRID %s", trid)
watchdog = DummyWatchdog
def get_argparser():
def get_argparser(with_file):
parser = argparse.ArgumentParser(
description="Local experiment running tool")
@ -81,15 +85,14 @@ def get_argparser():
parser.add_argument("-p", "--pdb", default="pdb.pyon",
help="parameter database file")
parser.add_argument("-E", "--elf", default=False, action="store_true",
help="run ELF binary")
parser.add_argument("-e", "--experiment", default=None,
help="experiment to run")
parser.add_argument("-o", "--hdf5", default=None,
help="write results to specified HDF5 file"
" (default: print them)")
parser.add_argument("file",
help="file containing the experiment to run")
if with_file:
parser.add_argument("file",
help="file containing the experiment to run")
parser.add_argument("arguments", nargs="*",
help="run arguments")
@ -99,86 +102,77 @@ def get_argparser():
def _parse_arguments(arguments):
d = {}
for argument in arguments:
name, value = argument.split("=")
name, eq, value = argument.partition("=")
d[name] = pyon.decode(value)
return d
def main():
args = get_argparser().parse_args()
def _get_experiment(module, experiment=None):
if experiment:
return getattr(module, experiment)
exps = [(k, v) for k, v in module.__dict__.items()
if is_experiment(v)]
if not exps:
logger.error("No experiments in module")
if len(exps) > 1:
logger.warning("Multiple experiments (%s), using first",
", ".join(k for (k, v) in exps))
return exps[0][1]
def _build_experiment(dbh, args):
if hasattr(args, "file"):
if args.file.endswith(".elf"):
if args.arguments:
raise ValueError("arguments not supported for ELF kernels")
if args.experiment:
raise ValueError("experiment-by-name not supported "
"for ELF kernels")
return ELFRunner(dbh, file=args.file)
else:
module = file_import(args.file)
file = args.file
else:
module = sys.modules["__main__"]
file = getattr(module, "__file__")
exp = _get_experiment(module, args.experiment)
arguments = _parse_arguments(args.arguments)
return exp(dbh,
scheduler=DummyScheduler(),
run_params=dict(file=file,
experiment=args.experiment,
arguments=arguments),
**arguments)
def run(with_file=False):
args = get_argparser(with_file).parse_args()
init_logger(args)
ddb = FlatFileDB(args.ddb)
pdb = FlatFileDB(args.pdb)
pdb.hooks.append(SimpleParamLogger())
rdb = ResultDB(lambda description: None, lambda mod: None)
dbh = DBHub(ddb, pdb, rdb)
try:
if args.elf:
if args.arguments:
print("Run arguments are not supported in ELF mode")
sys.exit(1)
exp_inst = ELFRunner(dbh)
rdb.build()
exp_inst.run(args.file)
else:
module = file_import(args.file)
if args.experiment is None:
exps = [(k, v) for k, v in module.__dict__.items()
if is_experiment(v)]
l = len(exps)
if l == 0:
print("No experiments found in module")
sys.exit(1)
elif l > 1:
print("More than one experiment found in module:")
for k, v in sorted(experiments, key=itemgetter(0)):
if v.__doc__ is None:
print(" {}".format(k))
else:
print(" {} ({})".format(
k, v.__doc__.splitlines()[0].strip()))
print("Use -u to specify which experiment to use.")
sys.exit(1)
else:
exp = exps[0][1]
else:
exp = getattr(module, args.experiment)
try:
arguments = _parse_arguments(args.arguments)
except:
print("Failed to parse run arguments")
sys.exit(1)
with DBHub(ddb, pdb, rdb) as dbh:
exp_inst = _build_experiment(dbh, args)
rdb.build()
exp_inst.run()
exp_inst.analyze()
run_params = {
"file": args.file,
"experiment": args.experiment,
"arguments": arguments
}
exp_inst = exp(dbh,
scheduler=DummyScheduler(),
run_params=run_params,
**run_params["arguments"])
rdb.build()
exp_inst.run()
exp_inst.analyze()
if args.hdf5 is not None:
with h5py.File(args.hdf5, "w") as f:
rdb.write_hdf5(f)
elif rdb.data.read or rdb.realtime_data.read:
r = chain(rdb.realtime_data.read.items(), rdb.data.read.items())
for k, v in sorted(r, key=itemgetter(0)):
print("{}: {}".format(k, v))
def main():
return run(with_file=True)
if args.hdf5 is not None:
f = h5py.File(args.hdf5, "w")
try:
rdb.write_hdf5(f)
finally:
f.close()
else:
if rdb.data.read or rdb.realtime_data.read:
print("Results:")
for k, v in sorted(chain(rdb.realtime_data.read.items(),
rdb.data.read.items()),
key=itemgetter(0)):
print("{}: {}".format(k, v))
finally:
dbh.close_devices()
if __name__ == "__main__":
main()