mindspore.ops.Select

class mindspore.ops.Select[source]

The conditional tensor determines whether the corresponding element in the output must be selected from x (if True) or y (if False) based on the value of each element.

It can be defined as:

\[\begin{split}out_i = \begin{cases} x_i, & \text{if } cond_i \\ y_i, & \text{otherwise} \end{cases}\end{split}\]

Inputs:

cond (Tensor[bool]): The condition tensor, decides which element is chosen. The shape is \((x_1, x_2, ..., x_N, ..., x_R)\).
x (Tensor): The first Tensor to be selected. The shape is \((x_1, x_2, ..., x_N, ..., x_R)\).
y (Tensor): The second Tensor to be selected. The shape is \((x_1, x_2, ..., x_N, ..., x_R)\).

Outputs:

Tensor, has the same shape as cond.

Raises

TypeError – If x or y is not a Tensor.
ValueError – The shape of inputs are different.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, ops
>>> # Both inputs are Tensor
>>> select = ops.Select()
>>> cond = Tensor([True, False])
>>> x = Tensor([2,3], mindspore.float32)
>>> y = Tensor([1,2], mindspore.float32)
>>> output = select(cond, x, y)
>>> print(output)
[2. 2.]