mindspore.ops.hardsigmoid

mindspore.ops.hardsigmoid(input)[source]

Hard sigmoid activation function.

Applies hard sigmoid activation element-wise. The input is a Tensor with any valid shape.

Hard sigmoid is defined as:

\[\text{hsigmoid}(x_{i}) = \max(0, \min(1, \frac{x_{i} + 3}{6}))\]

where \(x_i\) is an element of the input Tensor.

HSigmoid Activation Function Graph:

Parameters

input (Tensor) – The input Tensor.

Returns

A Tensor whose dtype and shape are the same as input.

Raises

TypeError – If input is not a Tensor.
TypeError – If dtype of input is not int or float.

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> x = Tensor(np.array([ -3.5,  0,  4.3]), mindspore.float32)
>>> output = ops.hardsigmoid(x)
>>> print(output)
[0.  0.5 1. ]