How do I get the original indices of the data when using train_test_split()?

What I have is the following

from sklearn.cross_validation import train_test_split

import numpy as np

data = np.reshape(np.randn(20),(10,2)) # 10 training examples

labels = np.random.randint(2, size=10) # 10 labels

x1, x2, y1, y2 = train_test_split(data, labels, size=0.2)

But this does not give the indices of the original data. One workaround is to add the indices to data (e.g.** data = [(i, d) for i, d in enumerate(data)]**) and then pass them inside **train_test_split** and then expand again. Are there any cleaner solutions?