from utils import Data from CharCNN1 import CharCNN1 from CharCNN2 import CharCNN2 from CharTCN import CharTCN tf.flags.DEFINE_string("m", "CharCNN1", "Select between models CharCNN1, CharCNN2, and CharTCN") FLAGS = tf.flags.FLAGS FLAGS._parse_flags() if __name__ == "__main__": config = json.load(open("config.json")) train_data = Data(path=config["data"]["train_path"], input_size=config["data"]["input_size"], vocab=config["data"]["vocab"], num_classes=config["data"]["num_classes"]) X_train, y_train = train_data.load() dev_data = Data(path=config["data"]["dev_path"], input_size=config["data"]["input_size"], vocab=config["data"]["vocab"], num_classes=config["data"]["num_classes"]) X_dev, y_dev = dev_data.load() if FLAGS.m == "CharCNN1": m = CharCNN1(input_size=config["data"]["input_size"], vocab_size=config["data"]["vocab_size"], embedding_size=config["data"]["embedding_size"], num_classes=config["data"]["num_classes"], conv_layers=config["cnn1"]["conv_layers"], fc_layers=config["cnn1"]["fc_layers"], optim_alg=config["cnn1"]["optim_alg"],