mindspore.ops.bitwise_and

mindspore.ops.bitwise_and(x, y)[source]

Returns bitwise and of two tensors element-wise.

\[out_i = x_{i} \wedge y_{i}\]

Args of x and y comply with the implicit type conversion rules to make the data types consistent. If they have different data types, the lower priority data type will be converted to the relatively highest priority data type.

Parameters

x (Tensor) – The input tensor with int16, int32 or uint16 data type. \((N,*)\) where \(*\) means, any number of additional dimensions.
y (Tensor) – The input tensor with same type as the x.

Returns

Tensor, has the same type as the x.

Raises

TypeError – If x or y is not a Tensor.

Supported Platforms:: Ascend GPU CPU

Examples

>>> x = Tensor(np.array([0, 0, 1, -1, 1, 1, 1]), mindspore.int16)
>>> y = Tensor(np.array([0, 1, 1, -1, -1, 2, 3]), mindspore.int16)
>>> output = ops.bitwise_and(x, y)
>>> print(output)
[ 0  0  1 -1  1  0  1]