def test_vec_to_tril_and_back_exceptions(check_lazy_shapes):
# Check rank checks.
for x in Tensor().forms():
with pytest.raises(ValueError):
B.vec_to_tril(x)
with pytest.raises(ValueError):
B.tril_to_vec(x)
for x in Tensor(3).forms():
with pytest.raises(ValueError):
B.tril_to_vec(x)
# Check square checks.
for x in Tensor(3, 4).forms():
with pytest.raises(ValueError):
B.tril_to_vec(x)
for x in Tensor(3, 4, 5).forms():
with pytest.raises(ValueError):
B.tril_to_vec(x)
def test_vec_to_tril(offset, batch_shape, check_lazy_shapes):
n = B.length(B.tril_to_vec(B.ones(7, 7), offset=offset))
check_function(B.vec_to_tril, (Tensor(*batch_shape, n),), {"offset": Value(offset)})
def test_vec_to_tril_and_back_correctness(offset, batch_shape, check_lazy_shapes):
n = B.length(B.tril_to_vec(B.ones(7, 7), offset=offset))
for vec in Tensor(*batch_shape, n).forms():
mat = B.vec_to_tril(vec, offset=offset)
approx(B.tril_to_vec(mat, offset=offset), vec)
def generate_init(shape, dtype):
mat = B.randn(dtype, *shape)
return transform(B.tril_to_vec(mat, offset=-1))
def inverse_transform(x):
eye = B.eye(x)
skew = B.solve(eye + x, eye - x)
return B.tril_to_vec(skew, offset=-1)
def inverse_transform(x):
return B.tril_to_vec(B.logm(x), offset=-1)
def inverse_transform(x):
chol = B.cholesky(B.reg(x))
return B.concat(B.log(B.diag(chol)), B.tril_to_vec(chol,
offset=-1))
def inverse_transform(x):
return B.tril_to_vec(x)