minor correction.

pypose/__init__.py

@@ -12,7 +12,8 @@
 from .lietensor import Sim3_type, sim3_type, RxSO3_type, rxso3_type
 from .lietensor import tensor, translation, rotation, scale, matrix, euler
 from .lietensor import mat2SO3, mat2SE3, mat2Sim3, mat2RxSO3, from_matrix, matrix, euler2SO3, vec2skew
-from .func import *
+from .lietensor.lietensor import retain_ltype
+from . import func
 from .function import *
 from .basics import *
 from . import module

pypose/func/jac.py

@@ -1,6 +1,6 @@
 import torch
+from .. import retain_ltype
 from typing import Callable, Union, Tuple, Optional
-from pypose.lietensor.lietensor import retain_ltype
 
 
 def jacrev(func: Callable, argnums: Union[int, Tuple[int]] = 0, *, has_aux=False,
@@ -36,7 +36,7 @@ def jacrev(func: Callable, argnums: Union[int, Tuple[int]] = 0, *, has_aux=False
         instead returns a ``(jacobian, aux)`` tuple where ``jacobian``
         is the Jacobian and ``aux`` is auxiliary objects returned by ``func``.
 
-    A basic usage with our LieTensor type would be the transformation function. 
+    A basic usage with our LieTensor type would be the transformation function.
 
         >>> import pypose as pp
         >>> import torch

pypose/lietensor/lietensor.py

@@ -1,9 +1,9 @@
 import torch
 from torch import nn
-from contextlib import contextmanager
 from .basics import vec2skew
-import collections, numbers, warnings, importlib
+from contextlib import contextmanager
 from .operation import broadcast_inputs
+import collections, numbers, warnings, importlib
 from torch.utils._pytree import tree_map, tree_flatten
 from .operation import SO3_Log, SE3_Log, RxSO3_Log, Sim3_Log
 from .operation import so3_Exp, se3_Exp, rxso3_Exp, sim3_Exp

tests/optim/test_jacobian.py

@@ -4,12 +4,11 @@
 import pypose as pp
 from torch import nn
 from contextlib import contextmanager
+from typing import Collection, Callable
 from torch.utils._pytree import tree_map
 from torch.autograd.functional import jacobian
 from torch.func import functional_call, jacfwd, jacrev
-from typing import Collection, Callable
 
-from pypose.lietensor.lietensor import retain_ltype
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 
@@ -169,7 +168,7 @@ def assert_fn_equal(func1, func2):
         }
 
         with check_fn_equal(TO_BE_CHECKED):
-            with retain_ltype():
+            with pp.retain_ltype():
                 jac_func = jacrev(func)
                 jac = jac_func(pose, points)
                 assert not pp.hasnan(jac)