def simple_experiment_from_json(object_json: Dict[str, Any]) -> SimpleExperiment:
"""Load AE SimpleExperiment from JSON."""
time_created_json = object_json.pop("time_created")
trials_json = object_json.pop("trials")
experiment_type_json = object_json.pop("experiment_type")
data_by_trial_json = object_json.pop("data_by_trial")
description_json = object_json.pop("description")
is_test_json = object_json.pop("is_test")
optimization_config = object_from_json(object_json.pop("optimization_config"))
# not relevant to simple experiment
del object_json["tracking_metrics"]
del object_json["runner"]
kwargs = {k: object_from_json(v) for k, v in object_json.items()}
kwargs["evaluation_function"] = unimplemented_evaluation_function
kwargs["objective_name"] = optimization_config.objective.metric.name
kwargs["minimize"] = optimization_config.objective.minimize
kwargs["outcome_constraints"] = optimization_config.outcome_constraints
experiment = SimpleExperiment(**kwargs)
experiment.description = object_from_json(description_json)
experiment.is_test = object_from_json(is_test_json)
experiment._time_created = object_from_json(time_created_json)
experiment._trials = trials_from_json(experiment, trials_json)
for trial in experiment._trials.values():
for arm in trial.arms:
experiment._arms_by_signature[arm.signature] = arm
if experiment.status_quo is not None:
sq_sig = experiment.status_quo.signature
experiment._arms_by_signature[sq_sig] = experiment.status_quo
experiment._experiment_type = object_from_json(experiment_type_json)
experiment._data_by_trial = data_from_json(data_by_trial_json)
return experiment
def experiment_from_sqa(self, experiment_sqa: SQAExperiment) -> Experiment:
"""Convert SQLAlchemy Experiment to Ax Experiment."""
opt_config, tracking_metrics = self.opt_config_and_tracking_metrics_from_sqa(
metrics_sqa=experiment_sqa.metrics)
search_space = self.search_space_from_sqa(
parameters_sqa=experiment_sqa.parameters,
parameter_constraints_sqa=experiment_sqa.parameter_constraints,
)
if search_space is None:
raise SQADecodeError( # pragma: no cover
"Experiment SearchSpace cannot be None.")
runner = (self.runner_from_sqa(experiment_sqa.runner)
if experiment_sqa.runner else None)
status_quo = (Arm(
parameters=experiment_sqa.status_quo_parameters,
name=experiment_sqa.status_quo_name,
) if experiment_sqa.status_quo_parameters is not None else None)
if (experiment_sqa.properties is not None
and experiment_sqa.properties.get("subclass")
== "SimpleExperiment"):
if opt_config is None:
raise SQADecodeError( # pragma: no cover
"SimpleExperiment must have an optimization config.")
experiment = SimpleExperiment(
name=experiment_sqa.name,
search_space=search_space,
objective_name=opt_config.objective.metric.name,
minimize=opt_config.objective.minimize,
outcome_constraints=opt_config.outcome_constraints,
status_quo=status_quo,
)
experiment.description = experiment_sqa.description
experiment.is_test = experiment_sqa.is_test
else:
experiment = Experiment(
name=experiment_sqa.name,
description=experiment_sqa.description,
search_space=search_space,
optimization_config=opt_config,
tracking_metrics=tracking_metrics,
runner=runner,
status_quo=status_quo,
is_test=experiment_sqa.is_test,
)
trials = [
self.trial_from_sqa(trial_sqa=trial, experiment=experiment)
for trial in experiment_sqa.trials
]
data_by_trial = defaultdict(dict)
for data_sqa in experiment_sqa.data:
trial_index = data_sqa.trial_index
timestamp = data_sqa.time_created
data_by_trial[trial_index][timestamp] = self.data_from_sqa(
data_sqa=data_sqa)
data_by_trial = {
trial_index: OrderedDict(sorted(data_by_timestamp.items()))
for trial_index, data_by_timestamp in data_by_trial.items()
}
experiment._trials = {trial.index: trial for trial in trials}
for trial in trials:
for arm in trial.arms:
experiment._arms_by_signature[arm.signature] = arm
if experiment.status_quo is not None:
sq_sig = experiment.status_quo.signature
experiment._arms_by_signature[sq_sig] = experiment.status_quo
experiment._time_created = experiment_sqa.time_created
experiment._experiment_type = self.get_enum_name(
value=experiment_sqa.experiment_type,
enum=self.config.experiment_type_enum)
experiment._data_by_trial = dict(data_by_trial)
return experiment
