Use selector.get_support (Documentation).
This will give you a mask of the features that were selected and features that were discarded.
array([False, True, True, False])
And here is how you get your selected features indices
>>> [ i for i, f in enumerate(selector.get_support()) if f ]
I believe you are trying to access "labels_" before fitting the data.
from sklearn.cluster import KMeans
import numpy as np
X = np.array([[1, 2], [1, 4], [1, 0],
[10, 2], [10, 4], [10, 0]])
kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
return [i for i in model.__dict__ ]