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
