from utils import USE_GPU, init_experiment
from pytorch_lightning import Trainer
from test_tube import Experiment, HyperOptArgumentParser
from models.baseline import CNN as Network

config = {
    'epochs':1
}

def epochs_500():
    global config
    config['epochs'] = 500

def run(hparams):
    init_experiment(comment=hparams.experiment_name)
    from utils import CURR_RUN_PATH, logger # import these after init_experiment
    logger.info(CURR_RUN_PATH)
    logger.info(f"tensorboard --logdir={CURR_RUN_PATH}")
    exp = Experiment(save_dir=CURR_RUN_PATH)

    def setup_config():
        conf = hparams.config
        conf_func = globals()[conf]
        try:
            conf_func()
        except:
            logger.error(f"Config {conf} not defined")

    setup_config()
    global config
    # parameters used in the baseline (read from main.py and solver.py)
    # n_epochs = 500
    # lr = 1e-4
    # num_class = 56
    # batch_size = 32

    if USE_GPU:
        trainer = Trainer(gpus=[0], distributed_backend='ddp',
                          experiment=exp, max_nb_epochs=config['epochs'], train_percent_check=hparams.train_percent,
                          fast_dev_run=False)
    else:
        trainer = Trainer(experiment=exp, max_nb_epochs=1, train_percent_check=0.01,
                          fast_dev_run=True)

    model = Network(num_class=56)  # TODO num_class

    print(model)

    trainer.fit(model)
    trainer.test()


if __name__=='__main__':
    parent_parser = HyperOptArgumentParser(strategy='grid_search', add_help=False)
    parent_parser.add_argument('--experiment_name', type=str,
                               default='pt_lightning_exp_a', help='test tube exp name')
    parent_parser.add_argument('--config', type=str, help='config function to run')
    #TODO : multiple arguments for --config using nargs='+' is not working with the test_tube
    # implementation of argument parser
    parent_parser.add_argument('--train_percent', type=float,
                               default=1.0, help='how much train data to use')
    parser = Network.add_model_specific_args(parent_parser)
    hyperparams = parser.parse_args()
    run(hyperparams)