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:

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

  • condition (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 and the shape is \((x_1, x_2, ..., x_N, ..., x_R)\).

  • y (Tensor) - The second tensor to be selected and the shape is \((x_1, x_2, ..., x_N, ..., x_R)\).

Outputs:

Tensor, has the same shape as condition.

Raises

  • TypeError – If x or y is not a Tensor.

  • ValueError – If shape of the three inputs are different.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, ops
>>> select = ops.Select()
>>> input_cond = Tensor([True, False])
>>> input_x = Tensor([2,3], mindspore.float32)
>>> input_y = Tensor([1,2], mindspore.float32)
>>> output = select(input_cond, input_x, input_y)
>>> print(output)
[2. 2.]