mindspore.mint.nn.functional.silu

mindspore.mint.nn.functional.silu(input)

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

\[\text{SiLU}(x) = x * \sigma(x),\]

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

Examples

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