def check_instantiation(self):
"""
Runs a series of checks to ensure that the user has not supplied
contradictory arguments which will result in undefined behavior
with multiple hyperparameters.
:return:
"""
if self.logger_name is None:
if self.output is None:
self.logger_name = self.name + "GaussianProcess"
set_logger(
self.logger_name,
stream=True,
fileout_name=None,
verbose=self.verbose,
)
else:
self.logger_name = self.output.basename + "log"
logger = logging.getLogger(self.logger_name)
# check whether it's be loaded before
loaded = False
if self.name + "_0" in _global_training_labels:
if (_global_training_labels.get(self.name + "_0", None)
is not self.training_labels_np):
loaded = True
if self.name + "_0" in _global_energy_labels:
if (_global_energy_labels.get(self.name + "_0", None)
is not self.energy_labels_np):
loaded = True
if loaded:
base = f"{self.name}"
count = 2
while self.name + "_0" in _global_training_labels and count < 100:
time.sleep(random())
self.name = f"{base}_{count}"
logger.debug("Specified GP name is present in global memory; "
"Attempting to rename the "
f"GP instance to {self.name}")
count += 1
if self.name + "_0" in _global_training_labels:
milliseconds = int(round(time.time() * 1000) % 10000000)
self.name = f"{base}_{milliseconds}"
logger.debug(
"Specified GP name still present in global memory: "
f"renaming the gp instance to {self.name}")
logger.debug(f"Final name of the gp instance is {self.name}")
self.sync_data()
self.hyps_mask = Parameters.check_instantiation(
self.hyps, self.cutoffs, self.kernels, self.hyps_mask)
def check_instantiation(self):
"""
Runs a series of checks to ensure that the user has not supplied
contradictory arguments which will result in undefined behavior
with multiple hyperparameters.
:return:
"""
logger = logging.getLogger(self.logger_name)
# check whether it's be loaded before
loaded = False
if self.name in _global_training_labels:
if _global_training_labels.get(self.name,
None) is not self.training_labels_np:
loaded = True
if self.name in _global_energy_labels:
if _global_energy_labels.get(self.name,
None) is not self.energy_labels_np:
loaded = True
if loaded:
base = f'{self.name}'
count = 2
while self.name in _global_training_labels and count < 100:
time.sleep(random())
self.name = f'{base}_{count}'
logger.debug("Specified GP name is present in global memory; "
"Attempting to rename the "
f"GP instance to {self.name}")
count += 1
if self.name in _global_training_labels:
milliseconds = int(round(time.time() * 1000) % 10000000)
self.name = f"{base}_{milliseconds}"
logger.debug(
"Specified GP name still present in global memory: "
f"renaming the gp instance to {self.name}")
logger.debug(f"Final name of the gp instance is {self.name}")
self.sync_data()
self.hyps_mask = Parameters.check_instantiation(
hyps=self.hyps, cutoffs=self.cutoffs, kernels=self.kernels,
param_dict=self.hyps_mask)
self.bounds = deepcopy(self.hyps_mask.get('bounds', None))