def main():
parser = argparse.ArgumentParser(description="-----[IMDB-classifier]-----")
parser.add_argument("--sample",
default=False,
action='store_true',
help="flag whether use sample dataset")
parser.add_argument(
"--mode",
default="train",
help="train: train (with test) a model / test: test saved models")
parser.add_argument("--model",
default="simple-gru",
help="available models: simple-gru, ...")
parser.add_argument("--epoch",
default=10,
type=int,
help="number of max epoch")
parser.add_argument("--learning_rate",
default=0.001,
type=float,
help="learning rate")
parser.add_argument("--batch_size",
default=32,
type=int,
help="batch size")
options = parser.parse_args()
params = {
'sample': options.sample,
'model': options.model,
'mode': options.mode,
'batch_size': options.batch_size,
'epoch': options.epoch,
'learning_rate': options.learning_rate
}
modelRunner = ModelRunner(params)
if options.mode == 'train':
print("=" * 20 + "TRAINING STARTED" + "=" * 20)
modelRunner.train()
elif options.mode == 'test':
print("=" * 20 + "TESTING STARTED" + "=" * 20)
modelRunner.load_model()
modelRunner.test()
from model_runner import ModelRunner runner = ModelRunner() runner.train_and_save() runner.load_model() runner.test()