def _create_experiment(self, parameters, pid, trial, count,
experiment_kwargs):
# type: (Any, Any, Any, Any, Dict[str, Any]) -> BaseExperiment
"""
Instantiates an Experiment, OfflineExperiment, or
callable.
"""
from comet_ml import Experiment, OfflineExperiment
LOGGER.debug("Creating a %r with %r parameters", self.experiment_class,
parameters)
if not experiment_kwargs:
# Fallback on deprecated experiment kwargs given at Optimizer creation
experiment_kwargs = self.experiment_kwargs
# Inject the API Key if not set
if "api_key" not in experiment_kwargs and self.api_key is not None:
experiment_kwargs["api_key"] = self.api_key
if self.experiment_class == "Experiment":
exp = Experiment(**experiment_kwargs) # type: BaseExperiment
elif self.experiment_class == "OfflineExperiment":
exp = OfflineExperiment(**
experiment_kwargs) # type: BaseExperiment
elif callable(self.experiment_class):
exp = self.experiment_class(**experiment_kwargs)
else:
raise OptimizerException("Invalid experiment_class: %s" %
self.experiment_class)
exp._set_optimizer(self, pid, trial, count)
if self.predictor_spec:
LOGGER.debug("Setting predictor in experiment: %s",
self.predictor_spec)
if isinstance(exp, OfflineExperiment):
mode = "local"
else:
# This should be at least global as it is set in Optimizer._fill_defaults_predictor
mode = self.predictor_spec["mode"]
# Old version of the Python SDK used to store predictor_spec with an
# empty optimizer_id, which would leads to TypeError: type object
# got multiple values for keyword argument 'optimizer_id'
# Also pop mode as it is passed explicitely
predictor_spec = self.predictor_spec.copy()
predictor_spec.pop("optimizer_id", None)
predictor_spec.pop("mode", None)
try:
exp.set_predictor(
Predictor(exp,
optimizer_id=self.id,
mode=mode,
**predictor_spec))
except Exception:
LOGGER.warning(
"Failure to create Predictor, experiment will run without Predictor",
exc_info=True,
)
exp.log_parameters(parameters)
# Log optimizer static information:
exp.log_other("optimizer_id", self.id)
exp.log_other("optimizer_pid", pid)
exp.log_other("optimizer_trial", trial)
return exp
