def test_permutation_raises(self):
perm = constant_op.constant(0, dtype=dtypes.int32)
with self.assertRaisesRegex(ValueError, "must have at least 1 dimension"):
permutation.LinearOperatorPermutation(perm)
perm = [0., 1., 2.]
with self.assertRaisesRegex(TypeError, "must be integer dtype"):
permutation.LinearOperatorPermutation(perm)
perm = [-1, 2, 3]
with self.assertRaisesRegex(ValueError,
"must be a vector of unique integers"):
permutation.LinearOperatorPermutation(perm)
def test_to_dense_4x4(self):
perm = [0, 1, 2, 3]
self.assertAllClose(
permutation.LinearOperatorPermutation(perm).to_dense(),
linalg_ops.eye(4))
perm = [1, 0, 3, 2]
self.assertAllClose(
permutation.LinearOperatorPermutation(perm).to_dense(),
[[0., 1, 0, 0], [1., 0, 0, 0], [0., 0, 0, 1], [0., 0, 1, 0]])
perm = [3, 2, 0, 1]
self.assertAllClose(
permutation.LinearOperatorPermutation(perm).to_dense(),
[[0., 0, 0, 1], [0., 0, 1, 0], [1., 0, 0, 0], [0., 1, 0, 0]])
def operator_and_matrix(self,
build_info,
dtype,
use_placeholder,
ensure_self_adjoint_and_pd=False):
shape = list(build_info.shape)
perm = math_ops.range(0, shape[-1])
perm = array_ops.broadcast_to(perm, shape[:-1])
perm = random_ops.random_shuffle(perm)
if use_placeholder:
perm = array_ops.placeholder_with_default(perm, shape=None)
operator = permutation.LinearOperatorPermutation(perm, dtype=dtype)
matrix = math_ops.cast(
math_ops.equal(math_ops.range(0, shape[-1]),
perm[..., array_ops.newaxis]), dtype)
return operator, matrix