def random_design_matrix(self, X):
        Z = self.s_rng.normal(size=X.shape,
                              avg=X, std=1./T.sqrt(self.beta), dtype=config.floatX)
        return Z
Swap two elements in the heap.
dataset/ETHPy150Open lisa-lab/pylearn2/pylearn2/distributions/mnd.py/AdditiveDiagonalMND.random_design_matrix--crossover with--dataset/ETHPy150Open steveniemitz/scales/scales/loadbalancer/heap.py/Heap.Swap