PySpark createDataFrame on list of LabeledPoints fails (regression)

import numpy as np
from pyspark.mllib.regression import LabeledPoint
from pyspark.mllib.linalg import Vectors

lp1 = LabeledPoint(1.0, Vectors.sparse(5, np.array([0, 1]), np.array([2.0, 21.0])))
lp2 = LabeledPoint(0.0, Vectors.sparse(5, np.array([2, 3]), np.array([2.0, 21.0])))
tmp = [lp1, lp2]
sqlContext.createDataFrame(tmp).show()

ValueError: Unexpected tuple LabeledPoint(1.0, (5,[0,1],[2.0,21.0])) with StructType
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-1-0e7cb8772e10> in <module>()
      6 lp2 = LabeledPoint(0.0, Vectors.sparse(5, np.array([2, 3]), np.array([2.0, 21.0])))
      7 tmp = [lp1, lp2]
----> 8 sqlContext.createDataFrame(tmp).show()

/home/ubuntu/databricks/spark/python/pyspark/sql/context.pyc in createDataFrame(self, data, schema, samplingRatio)
    404             rdd, schema = self._createFromRDD(data, schema, samplingRatio)
    405         else:
--> 406             rdd, schema = self._createFromLocal(data, schema)
    407         jrdd = self._jvm.SerDeUtil.toJavaArray(rdd._to_java_object_rdd())
    408         jdf = self._ssql_ctx.applySchemaToPythonRDD(jrdd.rdd(), schema.json())

/home/ubuntu/databricks/spark/python/pyspark/sql/context.pyc in _createFromLocal(self, data, schema)
    335 
    336         # convert python objects to sql data
--> 337         data = [schema.toInternal(row) for row in data]
    338         return self._sc.parallelize(data), schema
    339 

/home/ubuntu/databricks/spark/python/pyspark/sql/types.pyc in toInternal(self, obj)
    539                 return tuple(f.toInternal(v) for f, v in zip(self.fields, obj))
    540             else:
--> 541                 raise ValueError("Unexpected tuple %r with StructType" % obj)
    542         else:
    543             if isinstance(obj, dict):

ValueError: Unexpected tuple LabeledPoint(1.0, (5,[0,1],[2.0,21.0])) with StructType