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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(mat):
 """ Convert a matrix from the new mllib-local representation. This does NOT copy the data; it copies references. :param mat: a :py:class:`pyspark.ml.linalg.Matrix` :return: a :py:class:`pyspark.mllib.linalg.Matrix` .. versionadded:: 2.0.0 """

        if isinstance(mat, newlinalg.DenseMatrix):
            return DenseMatrix(mat.numRows, mat.numCols, mat.values, mat.isTransposed)
        elif isinstance(mat, newlinalg.SparseMatrix):
            return SparseMatrix(mat.numRows, mat.numCols, mat.colPtrs, mat.rowIndices,
                                mat.values, mat.isTransposed)
        else:
            raise TypeError("Unsupported matrix type %s" % type(mat))