_, loss = model.sess.run([
model.optimizer,
model.loss,
],
feed_dict=feed_dict)
train_loss.append(np.mean(loss))
print("Epoch: {:3d} train_loss: {:.5f}".format(epoch,
np.mean(train_loss)))
if __name__ == '__main__':
os.makedirs(args.output_dir, exist_ok=True)
data = Data.TextData(args.data_dir, args.batch_size)
config = dict()
config.update(vars(args))
config['vocab_size_en'] = data.vocab_size_en
config['vocab_size_cn'] = data.vocab_size_cn
model = NMTM(config=config,
Map_en2cn=data.Map_en2cn,
Map_cn2en=data.Map_cn2en)
train(model, data)
export_beta(model, data)
train_theta_en, train_theta_cn, test_theta_en, test_theta_cn = export_theta(
