def setUp(self):
utils.set_seed(1)
self.optimizer = GDASOptimizer(config)
self.optimizer.adapt_search_space(HierarchicalSearchSpace())
self.optimizer.before_training()
supported_optimizers = {
'bananas': Bananas(config),
'oneshot': OneShotNASOptimizer(config),
'rsws': RandomNASOptimizer(config),
}
supported_search_spaces = {
'nasbench101': NasBench101SearchSpace(),
'nasbench201': NasBench201SearchSpace(),
'darts': DartsSearchSpace()
}
#load_labeled = (True if config.search_space == 'darts' else False)
load_labeled = False
dataset_api = get_dataset_api(config.search_space, config.dataset)
utils.set_seed(config.seed)
search_space = supported_search_spaces[config.search_space]
optimizer = supported_optimizers[config.optimizer]
optimizer.adapt_search_space(search_space, dataset_api=dataset_api)
trainer = Trainer(optimizer, config, lightweight_output=True)
if config.optimizer == 'bananas':
trainer.search(resume_from="")
trainer.evaluate(resume_from="", dataset_api=dataset_api)
elif config.optimizer in ['oneshot', 'rsws']:
predictor = OneShotPredictor(config, trainer, model_path=config.model_path)
predictor_evaluator = PredictorEvaluator(predictor, config=config)
def setUp(self):
utils.set_seed(1)
self.optimizer = DARTSOptimizer(config)
self.optimizer.adapt_search_space(SimpleCellSearchSpace())
self.optimizer.before_training()
