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mindspore.ops.hardsigmoid

mindspore.ops.hardsigmoid(input)

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. ]