d6a2e55cea7640cf6ab1250bbaba66dd79a7ee85,pymc3/theanof.py,BatchedDiag,perform,#BatchedDiag#Any#Any#Any#Any#,475

Before Change

            np.arange(0, C.size, C.shape[1]).reshape((-1, 1)),
            C.shape[1], 1
        )
        index[index.nonzero()] += inc.flatten()
        z[0] = C1[index]

    def grad(self, inputs, gout):
        (gz,) = gout

After Change

        bc = C.shape[0]
        dim = C.shape[-1]
        Cd = np.zeros((bc, dim, dim), C.dtype)
        bidx = np.repeat(np.arange(bc), dim)
        didx = np.tile(np.arange(dim), bc)
        Cd[bidx, didx, didx] = C.flatten()
        z[0] = Cd

    def grad(self, inputs, gout):

Instances