solver = Solver()
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
if arg[1] == '--train':
print("Training")
# cmd : python main.py --train emb_dim 30 pre/no m1/m2
# 0 1 2 3 4 5
dim = arg[2] if arg[2] else 50
dim = int(dim)
if not os.path.isfile("data/train_data_{}_{}.npy".format(dim, arg[5])):
print("No File . Preprocessing!")
pre = Preprocessing()
dic = json.load(open("dict.json"))
if arg[5] == 'm1':
pre.batch_data(dic,
dim=dim,
modes=['train', 'valid', 'test'],
model=arg[5])
else:
pre.pad_sentences(dic,
dim=dim,
modes=['train', 'valid', 'test'],
model=arg[5])
train_data = np.load("data/train_data_{}_{}.npy".format(dim, arg[5]),
allow_pickle=True)
print(train_data[0].shape)
print(train_data[0][0])
train_label = np.load("data/train_label_{}_{}.npy".format(dim, arg[5]),
allow_pickle=True)
#print(train_label[0].shape)
#print(train_label[0][0])
