isinf¶
Documentation¶
-
treetensor.torch.
isinf
(input)[source]¶ In
treetensor
, you can test if each element ofinput
is infinite (positive or negative infinity) or not.Examples:
>>> import torch >>> import treetensor.torch as ttorch >>> ttorch.isinf(torch.tensor([1, float('inf'), 2, float('-inf'), float('nan')])) tensor([False, True, False, True, False]) >>> ttorch.isinf(ttorch.tensor({ ... 'a': [1, float('inf'), 2, float('-inf'), float('nan')], ... 'b': {'x': [[1, float('inf'), -2], [float('-inf'), 3, float('nan')]]} ... })) <Tensor 0x7fb782a29b80> ├── a --> tensor([False, True, False, True, False]) └── b --> <Tensor 0x7fb782a2d1f0> └── x --> tensor([[False, True, False], [ True, False, False]])
Torch Version Related
This documentation is based on torch.isinf in torch v1.10.0+cu102. Its arguments’ arrangements depend on the version of pytorch you installed.
If some arguments listed here are not working properly, please check your pytorch’s version with the following command and find its documentation.
1 | python -c 'import torch;print(torch.__version__)' |
The arguments and keyword arguments supported in torch v1.10.0+cu102 is listed below.
Description From Torch v1.10.0+cu102¶
-
torch.
isinf
(input) → Tensor¶ Tests if each element of
input
is infinite (positive or negative infinity) or not.Note
Complex values are infinite when their real or imaginary part is infinite.
- Args:
input (Tensor): the input tensor.
- Returns:
A boolean tensor that is True where
input
is infinite and False elsewhere
Example:
>>> torch.isinf(torch.tensor([1, float('inf'), 2, float('-inf'), float('nan')])) tensor([False, True, False, True, False])