def autotune(self): self.tuning_time -= time.time() tunerconfig.applypatch(tunerconfig.patch_pbbenchmark) tunerconfig.applypatch(tunerconfig.patch_n_offset(self.n)) tunerconfig.applypatch(tunerconfig.patch_accuracy_target(self.acc_target)) self.tuned_candidate=sgatuner.autotune(self.benchmark) tunerconfig.applypatch(tunerconfig.patch_reset) self.tuning_time += time.time()
def autotune(self):
self.tuning_time -= time.time()
tunerconfig.applypatch(tunerconfig.patch_pbbenchmark)
tunerconfig.applypatch(tunerconfig.patch_n_offset(self.n))
tunerconfig.applypatch(
tunerconfig.patch_accuracy_target(self.acc_target))
self.tuned_candidate = sgatuner.autotune(self.benchmark)
tunerconfig.applypatch(tunerconfig.patch_reset)
self.tuning_time += time.time()
def main(tester_lambda=None, pop_lambda=None, hlconfig_lambda=None, config_lambda=None):
from optparse import OptionParser
parser = OptionParser(usage="usage: sgatuner.py [options] Benchmark")
parser.add_option("--check",
action="store_true", dest="check", default=False,
help="check for correctness")
parser.add_option("--debug",
action="store_true", dest="debug", default=False,
help="enable debugging options")
parser.add_option("-n", type="int", help="input size to train for")
parser.add_option("--max_time", type="float", action="callback", callback=option_callback)
parser.add_option("--rounds_per_input_size", type="int", action="callback", callback=option_callback)
parser.add_option("--mutations_per_mutator", type="int", action="callback", callback=option_callback)
parser.add_option("--output_dir", type="string", action="callback", callback=option_callback)
parser.add_option("--population_size", type="int", action="callback", callback=option_callback)
parser.add_option("--min_input_size", type="int", action="callback", callback=option_callback)
parser.add_option("--offset", type="int", action="callback", callback=option_callback)
parser.add_option("--threads", type="int", action="callback", callback=option_callback)
parser.add_option("--name", type="string", action="callback", callback=option_callback)
parser.add_option("--abort_on", type="string", action="callback", callback=option_callback)
parser.add_option("--accuracy_target", type="float", action="callback", callback=option_callback)
(options, args) = parser.parse_args()
if len(args)!=1:
parser.print_usage()
sys.exit(1)
if options.check:
tunerconfig.applypatch(tunerconfig.patch_check)
if options.debug:
tunerconfig.applypatch(tunerconfig.patch_debug)
if options.n:
tunerconfig.applypatch(tunerconfig.patch_n(options.n))
config.benchmark=args[0]
if tester_lambda is None and pop_lambda is None and hlconfig_lambda is None:
recompile()
autotune(config.benchmark, None, tester_lambda, pop_lambda, hlconfig_lambda, config_lambda)
def regression_check(benchmark):
tunerconfig.applypatch(tunerconfig.patch_regression)
storagedirs.callWithLogDir(lambda: autotuneInner(benchmark),
config.output_dir,
config.delete_output_dir)
print 'error'
timers.total.stop()
finally:
at = storagedirs.getactivetimers()
if len(at):
storagedirs.openCsvStats("timers", at.keys()).writerow(at.values())
tester.cleanup()
def onlinelearn(benchmark):
storagedirs.callWithLogDir(lambda: onlinelearnInner(benchmark),
config.output_dir,
config.delete_output_dir)
if __name__ == "__main__":
tunerconfig.applypatch(tunerconfig.patch_onlinelearning)
from optparse import OptionParser
parser = OptionParser(usage="usage: onlinelearning.py [options] Benchmark -n N")
parser.add_option("--debug",
action="store_true", dest="debug", default=False,
help="enable debugging options")
parser.add_option("-n", type="int", help="input size to train for")
parser.add_option("--max_time", type="float", action="callback", callback=option_callback)
parser.add_option("--max_gen", type="int", action="callback", callback=option_callback)
parser.add_option("--output_dir", type="string", action="callback", callback=option_callback)
parser.add_option("--seed", type="string", action="callback", callback=option_callback)
parser.add_option("--offset", type="int", action="callback", callback=option_callback)
parser.add_option("--recompile", type="int", action="callback", callback=option_callback)
parser.add_option("--online_baseline", type="int", action="callback", callback=option_callback)
parser.add_option("--fixed_safe_alg", type="int", action="callback", callback=option_callback)
parser.add_option("--race_split_ratio",type="float", action="callback", callback=option_callback)
timers.total.stop()
finally:
at = storagedirs.getactivetimers()
if len(at):
storagedirs.openCsvStats("timers", at.keys()).writerow(at.values())
tester.cleanup()
def onlinelearn(benchmark):
storagedirs.callWithLogDir(lambda: onlinelearnInner(benchmark),
config.output_dir, config.delete_output_dir)
if __name__ == "__main__":
tunerconfig.applypatch(tunerconfig.patch_onlinelearning)
from optparse import OptionParser
parser = OptionParser(
usage="usage: onlinelearning.py [options] Benchmark -n N")
parser.add_option("--debug",
action="store_true",
dest="debug",
default=False,
help="enable debugging options")
parser.add_option("-n", type="int", help="input size to train for")
parser.add_option("--max_time",
type="float",
action="callback",
callback=option_callback)
parser.add_option("--max_gen",
type="int",
parser.add_option("-n", type="int", help="input size to train for")
parser.add_option("--max_time", type="float", action="callback", callback=option_callback)
parser.add_option("--rounds_per_input_size", type="int", action="callback", callback=option_callback)
parser.add_option("--mutations_per_mutator", type="int", action="callback", callback=option_callback)
parser.add_option("--output_dir", type="string", action="callback", callback=option_callback)
parser.add_option("--population_high_size", type="int", action="callback", callback=option_callback)
parser.add_option("--population_low_size", type="int", action="callback", callback=option_callback)
parser.add_option("--min_input_size", type="int", action="callback", callback=option_callback)
parser.add_option("--offset", type="int", action="callback", callback=option_callback)
parser.add_option("--threads", type="int", action="callback", callback=option_callback)
parser.add_option("--name", type="string", action="callback", callback=option_callback)
parser.add_option("--abort_on", type="string", action="callback", callback=option_callback)
parser.add_option("--accuracy_target", type="float", action="callback", callback=option_callback)
(options, args) = parser.parse_args()
if len(args)!=1:
parser.print_usage()
sys.exit(1)
if options.check:
tunerconfig.applypatch(tunerconfig.patch_check)
if options.debug:
tunerconfig.applypatch(tunerconfig.patch_debug)
if options.n:
tunerconfig.applypatch(tunerconfig.patch_n(options.n))
config.benchmark=args[0]
recompile()
autotune(config.benchmark)
def main(tester_lambda=None,
pop_lambda=None,
hlconfig_lambda=None,
config_lambda=None):
from optparse import OptionParser
parser = OptionParser(usage="usage: sgatuner.py [options] Benchmark")
parser.add_option("--check",
action="store_true",
dest="check",
default=False,
help="check for correctness")
parser.add_option("--debug",
action="store_true",
dest="debug",
default=False,
help="enable debugging options")
parser.add_option("-n", type="int", help="input size to train for")
parser.add_option("--max_time",
type="float",
action="callback",
callback=option_callback)
parser.add_option("--rounds_per_input_size",
type="int",
action="callback",
callback=option_callback)
parser.add_option("--mutations_per_mutator",
type="int",
action="callback",
callback=option_callback)
parser.add_option("--output_dir",
type="string",
action="callback",
callback=option_callback)
parser.add_option("--population_size",
type="int",
action="callback",
callback=option_callback)
parser.add_option("--min_input_size",
type="int",
action="callback",
callback=option_callback)
parser.add_option("--offset",
type="int",
action="callback",
callback=option_callback)
parser.add_option("--threads",
type="int",
action="callback",
callback=option_callback)
parser.add_option("--name",
type="string",
action="callback",
callback=option_callback)
parser.add_option("--abort_on",
type="string",
action="callback",
callback=option_callback)
parser.add_option("--accuracy_target",
type="float",
action="callback",
callback=option_callback)
(options, args) = parser.parse_args()
if len(args) != 1:
parser.print_usage()
sys.exit(1)
if options.check:
tunerconfig.applypatch(tunerconfig.patch_check)
if options.debug:
tunerconfig.applypatch(tunerconfig.patch_debug)
if options.n:
tunerconfig.applypatch(tunerconfig.patch_n(options.n))
config.benchmark = args[0]
if tester_lambda is None and pop_lambda is None and hlconfig_lambda is None:
recompile()
autotune(config.benchmark, None, tester_lambda, pop_lambda,
hlconfig_lambda, config_lambda)
def regression_check(benchmark):
tunerconfig.applypatch(tunerconfig.patch_regression)
storagedirs.callWithLogDir(lambda: autotuneInner(benchmark),
config.output_dir, config.delete_output_dir)
