def generate_parameters(self, parameter_id, **kwargs):
"""
Generate parameters for one trial.
Parameters
----------
parameter_id : int
The id for the generated hyperparameter
**kwargs
Not used
Returns
-------
dict
One configuration from the expanded search space.
Raises
------
NoMoreTrialError
If all the configurations has been sent, raise :class:`~nni.NoMoreTrialError`.
"""
self.count += 1
while self.count <= len(self.expanded_search_space) - 1:
_params_tuple = convert_dict2tuple(
copy.deepcopy(self.expanded_search_space[self.count]))
if _params_tuple in self.supplement_data:
self.count += 1
else:
return self.expanded_search_space[self.count]
raise nni.NoMoreTrialError('no more parameters now.')
def import_data(self, data):
"""Import additional data for tuning
Parameters
----------
data:
a list of dictionarys, each of which has at least two keys, 'parameter' and 'value'
"""
_completed_num = 0
for trial_info in data:
logger.info("Importing data, current processing progress %s / %s" %
(_completed_num, len(data)))
_completed_num += 1
assert "parameter" in trial_info
_params = trial_info["parameter"]
assert "value" in trial_info
_value = trial_info['value']
if not _value:
logger.info(
"Useless trial data, value is %s, skip this trial data." %
_value)
continue
_params_tuple = convert_dict2tuple(_params)
self.supplement_data[_params_tuple] = True
logger.info("Successfully import data to grid search tuner.")
def generate_parameters(self, parameter_id):
self.count += 1
while (self.count <= len(self.expanded_search_space)-1):
_params_tuple = convert_dict2tuple(self.expanded_search_space[self.count])
if _params_tuple in self.supplement_data:
self.count += 1
else:
return self.expanded_search_space[self.count]
raise nni.NoMoreTrialError('no more parameters now.')
