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"],
