mindspore.ops.silu

mindspore.ops.silu(input)

Computes Sigmoid Linear Unit of input element-wise, also known as Swish function. The SiLU function is defined as:

$$\text{SiLU}(x)=x\ast \sigma (x),$$

where $x$ is an element of the input, $\sigma (x)$ is Sigmoid function.

$$\text{sigma}(x_i)=\frac{1}{1+\exp (-x_i)},$$

SiLU Function Graph:

Parameters

input (Tensor) – input is $x$ in the preceding formula. Input with the data type float16 or float32.

Returns

Tensor, with the same type and shape as the input.

Raises

TypeError – If dtype of input is neither float16 nor float32.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, ops
>>> import numpy as np
>>> input = Tensor(np.array([-1, 2, -3, 2, -1]), mindspore.float16)
>>> output = ops.silu(input)
>>> print(output)
[-0.269  1.762  -0.1423  1.762  -0.269]