mindspore.Tensor.logical_or

Tensor.logical_or(other) → Tensor

Computes the "logical OR" of two tensors element-wise.

\[\begin{split}out_{i} = self_{i} \\vee other_{i}\end{split}\]

Note

  • Inputs of self and other comply with the implicit type conversion rules to make the data types consistent.

  • When the other is bool, it could only be a constant.

Inputs:

  • other (Union[Tensor, bool]) - A bool or a tensor whose data type can be implicitly converted to bool.

Outputs:

Tensor, the shape is the same as that of self and other after broadcasting, and the data type is bool.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor
>>> input = Tensor(np.array([True, False, True]), mindspore.bool_)
>>> other = Tensor(np.array([True, True, False]), mindspore.bool_)
>>> output = input.logical_or(other)
>>> print(output)
[ True  True  True]
>>> input = Tensor(1, mindspore.bool_)
>>> other = Tensor(0, mindspore.bool_)
>>> output = input.logical_or(other)
>>> print(output)
True
>>> input = True
>>> other = Tensor(0, mindspore.bool_)
>>> output = input.logical_or(other)
>>> print(output)
True
>>> input = True
>>> other = Tensor(np.array([True, False]), mindspore.bool_)
>>> output = input.logical_or(other)
>>> print(output)
[True True]