code: def loadLabeledPoints(sc, path, minPartitions=None):
          
          minPartitions = minPartitions or min(sc.defaultParallelism, 2)
          return callMLlibFunc("loadLabeledPoints", sc, path, minPartitions)
docs: Load labeled points saved using RDD.saveAsTextFile.
  
          :param sc: Spark context
          :param path: file or directory path in any Hadoop-supported file
                       system URI
          :param minPartitions: min number of partitions
          @return: labeled data stored as an RDD of LabeledPoint
  
          >>> from tempfile import NamedTemporaryFile
          >>> from pyspark.mllib.util import MLUtils
          >>> from pyspark.mllib.regression import LabeledPoint
          >>> examples = [LabeledPoint(1.1, Vectors.sparse(3, [(0, -1.23), (2, 4.56e-7)])),
          ...             LabeledPoint(0.0, Vectors.dense([1.01, 2.02, 3.03]))]
          >>> tempFile = NamedTemporaryFile(delete=True)
          >>> tempFile.close()
          >>> sc.parallelize(examples, 1).saveAsTextFile(tempFile.name)
          >>> MLUtils.loadLabeledPoints(sc, tempFile.name).collect()
          [LabeledPoint(1.1, (3,[0,2],[-1.23,4.56e-07])), LabeledPoint(0.0, [1.01,2.02,3.03])]