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.

  • RuntimeError – If the data type of x and y conversion of Parameter is required when data type conversion of Parameter is not supported.

Supported Platforms:

Ascend 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]