def import_data(self, data): # for resuming experiment
for trial in data:
param = format_parameters(trial['parameter'], self.space)
loss = trial['value']
if self.optimize_mode is OptimizeMode.Maximize:
loss = -trial['value']
for key, value in param.items():
self._history[key].append(Record(value, loss))
_logger.info(f'Replayed {len(data)} trials')
def import_data(self, data): # for resuming experiment
if isinstance(data, str):
data = nni.load(data)
for trial in data:
if isinstance(trial, str):
trial = nni.load(trial)
param = format_parameters(trial['parameter'], self.space)
loss = trial['value']
if isinstance(loss, dict) and 'default' in loss:
loss = loss['default']
if self.optimize_mode is OptimizeMode.Maximize:
loss = -loss
for key, value in param.items():
self._history[key].append(Record(value, loss))
_logger.info(f'Replayed {len(data)} trials')
def test_resuming():
internal_space = format_search_space(user_space)
assert format_parameters(user_params_1, internal_space) == resume_params_1
assert format_parameters(user_params_2, internal_space) == resume_params_2
assert format_parameters(user_params_3, internal_space) == resume_params_3