logical_and¶

paddle. logical_and ( x, y, out=None, name=None ) [source]

Compute element-wise logical AND on x and y, and return out. out is N-dim boolean Tensor. Each element of out is calculated by

\[out = x \&\& y\]

Note

paddle.logical_and supports broadcasting. If you want know more about broadcasting, please refer to Introduction to Tensor .

Parameters

x (Tensor) – the input tensor, it’s data type should be one of bool, int8, int16, in32, in64, float16, float32, float64, complex64, complex128.
y (Tensor) – the input tensor, it’s data type should be one of bool, int8, int16, in32, in64, float16, float32, float64, complex64, complex128.
out (Tensor, optional) – The Tensor that specifies the output of the operator, which can be any Tensor that has been created in the program. The default value is None, and a new Tensor will be created to save the output.
name (str, optional) – Name for the operation (optional, default is None). For more information, please refer to Name.

Returns

N-D Tensor. A location into which the result is stored. It’s dimension equals with x.

Examples

           >>> import paddle

>>> x = paddle.to_tensor([True])
>>> y = paddle.to_tensor([True, False, True, False])
>>> res = paddle.logical_and(x, y)
>>> print(res)
Tensor(shape=[4], dtype=bool, place=Place(cpu), stop_gradient=True,
[True , False, True , False])

          