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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 _convert_labeled_point_to_libsvm(p):
 """Converts a LabeledPoint to a string in LIBSVM format."""

        from pyspark.mllib.regression import LabeledPoint
        assert isinstance(p, LabeledPoint)
        items = [str(p.label)]
        v = _convert_to_vector(p.features)
        if isinstance(v, SparseVector):
            nnz = len(v.indices)
            for i in xrange(nnz):
                items.append(str(v.indices[i] + 1) + ":" + str(v.values[i]))
        else:
            for i in xrange(len(v)):
                items.append(str(i + 1) + ":" + str(v[i]))
        return " ".join(items)