def load_models(): models = [] nb_models = 5 for run in range(nb_models): print("====== Loading ensemble model: %d ======" % run) m = BaseModel('data/', dense_nodes=4096) model_prefix = "da_r%d_" % run m.model_name = model_prefix + m.model_name print("model path: %s" % m.model_path) m.load_model() models = models + [m] return models
def train_ensemble(): nb_models = 5 # train 5 ensemble models models = [] model_paths = [] for run in range(nb_models): print("====== Ensemble model: %d ======" % run) m = BaseModel('data/', dense_nodes=4096) model_prefix = "da_r%d_" % run m.model_name = model_prefix + m.model_name print("====== training model ======") m.train(nb_epoch=20, use_da=True) # append model models = models + [m] model_paths = model_paths + [m.model_path] return models, model_paths