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mindspore.Tensor.select

Tensor.select(condition, y)

The conditional tensor determines whether the corresponding element in the output must be selected from the current Tensor (if true) or $y$ (if false) based on the value of each element.

It can be defined as:

$$\begin{array}{r}ou{t}_i=\{\begin{array}{ll}tenso{r}_i,& \text{if }conditio{n}_i\\ y_i,& \text{otherwise}\end{array}\end{array}$$

Parameters

• condition (Tensor[bool]) – The condition tensor, decides which element is chosen. The shape is the same as the current Tensor.

• y (Union[Tensor, int, float]) – If y is Tensor, the shape is the same as the current Tensor. If y is an int or a float, it will be cast to the type of int32 or float32, and broadcast to the same shape as the Tensor.

Returns

Tensor, has the same shape as the current Tensor.

Raises

• TypeError – If y is not a Tensor, an int or a float.

• ValueError – The shapes of inputs are different.

Supported Platforms:

Ascend GPU CPU

Examples

>>> # 1) y is Tensor
>>>
>>> cond = Tensor([True, False])
>>> x = Tensor([2,3], mindspore.float32)
>>> y = Tensor([1,2], mindspore.float32)
>>> output = x.select(cond, y)
>>> print(output)
[2. 2.]
>>> # 2) y is a float
>>> cond = Tensor([True, False])
>>> x = Tensor([2,3], mindspore.float32)
>>> y = 2.0
>>> output = x.select(cond, y)
>>> print(output)
[2. 2.]