Source code for pypose.function.checking
import torch, math
from .. import lietensor
from .. import LieTensor
[docs]def is_lietensor(obj):
r'''
Check whether an instance or object is a LieTensor or not.
Args:
obj (``obj``): a Python object or instantance.
Return:
``bool``: ``True`` if obj is a LieTensor object otherwise ``False``.
'''
return True if isinstance(obj, LieTensor) else False
[docs]def is_SE3(obj):
r'''
Check whether an instance or object is an SE3 Type LieTensor or not.
Args:
obj (``obj``): a Python object or instantance.
Return:
``bool``: ``True`` if obj is a SE3 Type LieTensor object otherwise ``False``.
'''
return True if isinstance(obj.ltype, lietensor.lietensor.SE3Type) else False
[docs]def hasnan(obj:list):
r'''
Checks whether a deep nested list of tensors contains Nan or not.
Args:
obj (``obj``): a Python object that can be a list of nested list.
Return:
``bool``: ``True`` if the list contains a tensor with ``Nan`` otherwise ``False``.
Example:
>>> L1 = [[1, 3], [4, [5, 6]], 7, [8, torch.tensor([0, -1.0999])]]
>>> hasnan(L1)
False
>>> L2 = [[torch.tensor([float('nan'), -1.0999]), 3], [4, [5, 6]], 7, [8, 9]]
>>> hasnan(L2)
True
>>> L3 = [[torch.tensor([1, -1.0999]), 3], [4, [float('nan'), 6]], 7, [8, 9]]
>>> hasnan(L3)
True
'''
if isinstance(obj, list) or isinstance(obj, tuple):
for l in obj:
if hasnan(l):
return True
return False
else:
return torch.isnan(obj).any() if torch.is_tensor(obj) else math.isnan(obj)
