def testExperimentTagTruncation(self):
ray.init()
def train(config, reporter):
reporter(timesteps_total=1)
trial_executor = RayTrialExecutor()
register_trainable("f1", train)
experiments = {
"foo": {
"run": "f1",
"config": {
"a" * 50: lambda spec: 5.0 / 7,
"b" * 50: lambda spec: "long" * 40
},
}
}
for name, spec in experiments.items():
trial_generator = BasicVariantGenerator()
trial_generator.add_configurations({name: spec})
for trial in trial_generator.next_trials():
trial_executor.start_trial(trial)
self.assertLessEqual(len(trial.logdir), 200)
trial_executor.stop_trial(trial)
def _add_trials(self, name, spec):
"""Add trial by invoking TrialRunner."""
resource = {}
resource["trials"] = []
trial_generator = BasicVariantGenerator()
trial_generator.add_configurations({name: spec})
for trial in trial_generator.next_trials():
runner.add_trial(trial)
resource["trials"].append(self._trial_info(trial))
return resource
def _add_trials(self, name, spec):
"""Add trial by invoking TrialRunner."""
resource = {}
resource["trials"] = []
trial_generator = BasicVariantGenerator()
trial_generator.add_configurations({name: spec})
for trial in trial_generator.next_trials():
runner.add_trial(trial)
resource["trials"].append(self._trial_info(trial))
return resource
def execute_command(self, args):
def get_trial():
trial = runner.get_trial(args["trial_id"])
if trial is None:
error = "Trial ({}) not found.".format(args["trial_id"])
raise TuneManagerError(error)
else:
return trial
command = args["command"]
response = {}
try:
if command == TuneClient.GET_LIST:
response["trials"] = [
self.trial_info(t) for t in runner.get_trials()
]
elif command == TuneClient.GET_TRIAL:
trial = get_trial()
response["trial_info"] = self.trial_info(trial)
elif command == TuneClient.STOP:
trial = get_trial()
runner.request_stop_trial(trial)
elif command == TuneClient.ADD:
name = args["name"]
spec = args["spec"]
trial_generator = BasicVariantGenerator()
trial_generator.add_configurations({name: spec})
for trial in trial_generator.next_trials():
runner.add_trial(trial)
else:
raise TuneManagerError("Unknown command.")
status = True
except TuneError as e:
status = False
response["message"] = str(e)
return status, response
def execute_command(self, args):
def get_trial():
trial = runner.get_trial(args["trial_id"])
if trial is None:
error = "Trial ({}) not found.".format(args["trial_id"])
raise TuneManagerError(error)
else:
return trial
command = args["command"]
response = {}
try:
if command == TuneClient.GET_LIST:
response["trials"] = [
self.trial_info(t) for t in runner.get_trials()
]
elif command == TuneClient.GET_TRIAL:
trial = get_trial()
response["trial_info"] = self.trial_info(trial)
elif command == TuneClient.STOP:
trial = get_trial()
runner.request_stop_trial(trial)
elif command == TuneClient.ADD:
name = args["name"]
spec = args["spec"]
trial_generator = BasicVariantGenerator()
trial_generator.add_configurations({name: spec})
for trial in trial_generator.next_trials():
runner.add_trial(trial)
else:
raise TuneManagerError("Unknown command.")
status = True
except TuneError as e:
status = False
response["message"] = str(e)
return status, response
def generate_trials(self, spec, name):
suggester = BasicVariantGenerator()
suggester.add_configurations({name: spec})
return suggester.next_trials()
def generate_trials(self, spec, name):
suggester = BasicVariantGenerator({name: spec})
return suggester.next_trials()
def generate_trials(self, spec, name):
suggester = BasicVariantGenerator()
suggester.add_configurations({name: spec})
return suggester.next_trials()