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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def fromML(vec):
 """ Convert a vector from the new mllib-local representation. This does NOT copy the data; it copies references. :param vec: a :py:class:`pyspark.ml.linalg.Vector` :return: a :py:class:`pyspark.mllib.linalg.Vector` .. versionadded:: 2.0.0 """

        if isinstance(vec, newlinalg.DenseVector):
            return DenseVector(vec.array)
        elif isinstance(vec, newlinalg.SparseVector):
            return SparseVector(vec.size, vec.indices, vec.values)
        else:
            raise TypeError("Unsupported vector type %s" % type(vec))