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()