def __to_frozen_trial(self, trial):
number = trial["number"]
state = trial["state"]
datetime_start = trial["datetime_start"]
datetime_complete = trial["datetime_complete"]
params = trial["params"]
distributions = {}
for p in params:
distributions[p] = json_to_distribution(trial["distributions"][p])
user_attrs = trial["user_attrs"]
system_attrs = trial["system_attrs"]
trial["intermediate_values"]
intkey_val = {}
for k in trial["intermediate_values"]:
intk = int(k)
intkey_val[k] = trial["intermediate_values"][k]
intermediate_values = intkey_val
trial_id = trial["trial_id"]
value = trial["value"]
ret = structs.FrozenTrial(number=number,
state=structs.TrialState(state),
datetime_start=datetime_start,
datetime_complete=datetime_complete,
params=params,
distributions=distributions,
user_attrs=user_attrs,
system_attrs=system_attrs,
intermediate_values=intermediate_values,
trial_id=trial_id,
value=value)
return ret
def _create_running_trial():
# type: () -> structs.FrozenTrial
return structs.FrozenTrial(
trial_id=-1, # dummy value.
number=-1, # dummy value.
state=structs.TrialState.RUNNING,
params={},
distributions={},
user_attrs={},
system_attrs={},
value=None,
intermediate_values={},
datetime_start=datetime.now(),
datetime_complete=None)
def _trial(self, trial_id):
if trial_id in self.trials:
return self.trials[trial_id]
trial = structs.FrozenTrial(trial_id=trial_id,
state=structs.TrialState.RUNNING,
params={},
user_attrs={},
system_attrs={},
value=None,
intermediate_values={},
params_in_internal_repr={},
datetime_start=None,
datetime_complete=None)
self.trials[trial_id] = trial
return trial
def create_new_trial_id(self, study_id):
# type: (int) -> int
self._check_study_id(study_id)
with self._lock:
trial_id = len(self.trials)
self.trials.append(
structs.FrozenTrial(trial_id=trial_id,
state=structs.TrialState.RUNNING,
params={},
user_attrs={},
system_attrs={},
value=None,
intermediate_values={},
params_in_internal_repr={},
datetime_start=datetime.now(),
datetime_complete=None,
timedelta_sampling_elapsed=None))
return trial_id
def create_new_trial(self, study_id):
# type: (int) -> int
self._check_study_id(study_id)
with self._lock:
trial_id = len(self.trials)
self.trials.append(
structs.FrozenTrial(number=trial_id,
state=structs.TrialState.RUNNING,
params={},
distributions={},
user_attrs={},
system_attrs={'_number': trial_id},
value=None,
intermediate_values={},
datetime_start=datetime.now(),
datetime_complete=None,
trial_id=trial_id))
return trial_id
def _append_trial(
self,
value=None, # type: Optional[float]
params=None, # type: Optional[Dict[str, Any]]
distributions=None, # type: Optional[Dict[str, BaseDistribution]]
user_attrs=None, # type: Optional[Dict[str, Any]]
system_attrs=None, # type: Optional[Dict[str, Any]]
intermediate_values=None, # type: Optional[Dict[int, float]]
state=structs.TrialState.COMPLETE, # type: structs.TrialState
datetime_start=None, # type: Optional[datetime.datetime]
datetime_complete=None, # type: Optional[datetime.datetime]
):
# type: (...) -> None
params = params or {}
distributions = distributions or {}
user_attrs = user_attrs or {}
system_attrs = system_attrs or {}
intermediate_values = intermediate_values or {}
datetime_start = datetime_start or datetime.datetime.now()
if state.is_finished():
datetime_complete = datetime_complete or datetime.datetime.now()
trial = structs.FrozenTrial(
number=-1, # dummy value.
trial_id=-1, # dummy value.
state=state,
value=value,
datetime_start=datetime_start,
datetime_complete=datetime_complete,
params=params,
distributions=distributions,
user_attrs=user_attrs,
system_attrs=system_attrs,
intermediate_values=intermediate_values,
)
trial._validate()
self._storage.create_new_trial(self._study_id, template_trial=trial)
def dict_to_trial(d):
params = {}
params_in_internal_repr = {}
for k, v in d['params'].items():
distribution = distributions.json_to_distribution(v['distribution'])
params[k] = distribution.to_external_repr(v['value'])
params_in_internal_repr[k] = v['value']
return structs.FrozenTrial(
trial_id=d['trial_id'],
state=str_to_trial_state(d['state']),
params=params,
user_attrs=d['user_attrs'],
system_attrs=d['system_attrs'],
value=d['value'],
intermediate_values=dict(
(int(k), v) for k, v in d['intermediate_values'].items()),
params_in_internal_repr=params_in_internal_repr,
datetime_start=datetime.fromtimestamp(d['datetime_start']),
datetime_complete=datetime.fromtimestamp(d['datetime_end'])
if d['datetime_end'] else None,
)
def _merge_trials_orm(
self,
trials, # type: List[models.TrialModel]
trial_params, # type: List[models.TrialParamModel]
trial_intermediate_values, # type: List[models.TrialValueModel]
trial_user_attrs, # type: List[models.TrialUserAttributeModel]
trial_system_attrs # type: List[models.TrialSystemAttributeModel]
):
# type: (...) -> List[structs.FrozenTrial]
id_to_trial = {}
for trial in trials:
id_to_trial[trial.trial_id] = trial
id_to_params = defaultdict(
list) # type: Dict[int, List[models.TrialParamModel]]
for param in trial_params:
id_to_params[param.trial_id].append(param)
id_to_values = defaultdict(
list) # type: Dict[int, List[models.TrialValueModel]]
for value in trial_intermediate_values:
id_to_values[value.trial_id].append(value)
id_to_user_attrs = \
defaultdict(list) # type: Dict[int, List[models.TrialUserAttributeModel]]
for user_attr in trial_user_attrs:
id_to_user_attrs[user_attr.trial_id].append(user_attr)
id_to_system_attrs = \
defaultdict(list) # type: Dict[int, List[models.TrialSystemAttributeModel]]
for system_attr in trial_system_attrs:
id_to_system_attrs[system_attr.trial_id].append(system_attr)
result = []
for trial_id, trial in id_to_trial.items():
params = {}
param_distributions = {}
for param in id_to_params[trial_id]:
distribution = distributions.json_to_distribution(
param.distribution_json)
params[param.param_name] = distribution.to_external_repr(
param.param_value)
param_distributions[param.param_name] = distribution
intermediate_values = {}
for value in id_to_values[trial_id]:
intermediate_values[value.step] = value.value
user_attrs = {}
for user_attr in id_to_user_attrs[trial_id]:
user_attrs[user_attr.key] = json.loads(user_attr.value_json)
system_attrs = {}
for system_attr in id_to_system_attrs[trial_id]:
system_attrs[system_attr.key] = json.loads(
system_attr.value_json)
result.append(
structs.FrozenTrial(number=trial.number,
state=trial.state,
params=params,
distributions=param_distributions,
user_attrs=user_attrs,
system_attrs=system_attrs,
value=trial.value,
intermediate_values=intermediate_values,
datetime_start=trial.datetime_start,
datetime_complete=trial.datetime_complete,
trial_id=trial_id))
return result
def _merge_trials_orm(
self,
trials, # type: List[models.TrialModel]
trial_params, # type: List[models.TrialParamModel]
trial_intermediate_values, # type: List[models.TrialValueModel]
trial_user_attrs, # type: List[models.TrialUserAttributeModel]
trial_system_attrs # type: List[models.TrialSystemAttributeModel]
):
# type: (...) -> List[structs.FrozenTrial]
id_to_trial = {}
for trial in trials:
id_to_trial[trial.trial_id] = trial
id_to_params = defaultdict(
list) # type: Dict[int, List[models.TrialParamModel]]
for param in trial_params:
id_to_params[param.trial_id].append(param)
id_to_values = defaultdict(
list) # type: Dict[int, List[models.TrialValueModel]]
for value in trial_intermediate_values:
id_to_values[value.trial_id].append(value)
id_to_user_attrs = \
defaultdict(list) # type: Dict[int, List[models.TrialUserAttributeModel]]
for user_attr in trial_user_attrs:
id_to_user_attrs[user_attr.trial_id].append(user_attr)
id_to_system_attrs = \
defaultdict(list) # type: Dict[int, List[models.TrialSystemAttributeModel]]
for system_attr in trial_system_attrs:
id_to_system_attrs[system_attr.trial_id].append(system_attr)
temp_trials = []
for trial_id, trial in id_to_trial.items():
params = {}
param_distributions = {}
for param in id_to_params[trial_id]:
distribution = distributions.json_to_distribution(
param.distribution_json)
params[param.param_name] = distribution.to_external_repr(
param.param_value)
param_distributions[param.param_name] = distribution
intermediate_values = {}
for value in id_to_values[trial_id]:
intermediate_values[value.step] = value.value
user_attrs = {}
for user_attr in id_to_user_attrs[trial_id]:
user_attrs[user_attr.key] = json.loads(user_attr.value_json)
system_attrs = {}
for system_attr in id_to_system_attrs[trial_id]:
system_attrs[system_attr.key] = json.loads(
system_attr.value_json)
# `-1` is a dummy value.
# It will be replaced by a proper value before returned to the caller.
#
# TODO(ohta): Use trial.number after TrialModel.number is added.
trial_number = -1
temp_trials.append(
structs.FrozenTrial(number=trial_number,
state=trial.state,
params=params,
distributions=param_distributions,
user_attrs=user_attrs,
system_attrs=system_attrs,
value=trial.value,
intermediate_values=intermediate_values,
datetime_start=trial.datetime_start,
datetime_complete=trial.datetime_complete,
trial_id=trial_id))
result = []
for temp_trial in temp_trials:
# [NOTE]
# We set actual trial numbers here to avoid calling `self.get_trial_number_from_id()`
# within the above loop.
#
# This is because `self.get_trial_number_from_id()` may call `session.commit()`
# internally, which causes unintended changes of the states of `trials`.
# (see https://github.com/pfnet/optuna/pull/349#issuecomment-475086642 for details)
trial_number = self.get_trial_number_from_id(temp_trial.trial_id)
result.append(temp_trial._replace(number=trial_number))
return result