input: Write a python function to perform KMeans clustering on a set of 3D data points and return the cluster labels.
  assert kmeans_clustering([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) == [0, 1, 2]
  assert kmeans_clustering([[1, 1, 1], [2, 2, 2], [3, 3, 3]]) == [0, 1, 2]
  assert kmeans_clustering([[5, 5, 5], [10, 10, 10], [15, 15, 15]]) == [0, 1, 2]
output: def kmeans_clustering(data):
      from sklearn.cluster import KMeans
      kmeans = KMeans(n_clusters=len(data))
      kmeans.fit(data)
      return kmeans.labels_.tolist()