mindspore.ops.LogicalAnd
- class mindspore.ops.LogicalAnd[source]
Computes the "logical AND" of two tensors element-wise.
Refer to
mindspore.ops.logical_and()
for more details.- Inputs:
x (Union[Tensor, bool]) - The first input is a bool or a tensor whose data type can be implicitly converted to bool.
y (Union[Tensor, bool]) - The second input is a bool when the first input is a tensor or a tensor whose data type can be implicitly converted to bool.
- Outputs:
Tensor, the shape is the same as the x and y after broadcasting, and the data type is bool.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> import mindspore >>> import numpy as np >>> from mindspore import Tensor, ops >>> x = Tensor(np.array([True, False, True]), mindspore.bool_) >>> y = Tensor(np.array([True, True, False]), mindspore.bool_) >>> logical_and = ops.LogicalAnd() >>> output = logical_and(x, y) >>> print(output) [ True False False] >>> x = Tensor(1, mindspore.bool_) >>> y = Tensor(0, mindspore.bool_) >>> output = ops.LogicalAnd()(x, y) >>> print(output) False >>> x = True >>> y = Tensor(0, mindspore.bool_) >>> output = ops.LogicalAnd()(x, y) >>> print(output) False >>> x = True >>> y = Tensor(np.array([True, False]), mindspore.bool_) >>> output = ops.LogicalAnd()(x, y) >>> print(output) [True False]