def psd_solve_with_chol(node):
if node.op == solve:
A, b = node.inputs # result is solution Ax=b
if is_psd(A):
L = cholesky(A) # assume lower triangular factor
x = solve_cholesky(L, b)
return [x]
def test_mat_mat_lower(self):
if not imported_scipy:
raise SkipTest("Scipy needed for the SolveCholesky op.")
f = function([self.L, self.B], solve_cholesky(self.L, self.B))
reference = scipy.linalg.cho_solve((self.L_mat, True), self.B_mat)
result = f(self.L_mat, self.B_mat)
numpy.testing.assert_array_almost_equal(result, reference)
def inv_cholesky_as_solve_cholesky(node):
if not imported_scipy:
return False
if isinstance(node.op, (Dot, Dot22)):
l, r = node.inputs
if l.owner and isinstance(l.owner.op, MatrixInverseCholesky):
return [solve_cholesky(l.owner.inputs[0], r)]
if r.owner and isinstance(r.owner.op, MatrixInverseCholesky):
return [SolveCholesky(lower=False)(r.owner.inputs[0].T, l.T).T]
