input: Write a function to perform K-means clustering on a given dataset and return the cluster labels for each data point.
  assert perform_kmeans([[1, 2], [1, 4], [1, 0], [10, 2], [10, 4], [10, 0]], 2) == [1, 1, 1, 0, 0, 0]
  assert perform_kmeans([[1, 2], [1, 4], [1, 0], [10, 2], [10, 4], [10, 0]], 3) == [1, 1, 1, 2, 2, 2]
  assert perform_kmeans([[2, 3], [3, 3], [4, 4], [5, 5], [6, 6], [7, 7]], 2) == [0, 0, 0, 1, 1, 1]
output: def perform_kmeans(data, k):
      from sklearn.cluster import KMeans
      kmeans = KMeans(n_clusters=k)
      kmeans.fit(data)
      return kmeans.labels_.tolist()