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mindspore.nn.HSigmoid

class mindspore.nn.HSigmoid

Applies Hard Sigmoid activation function element-wise.

Hard Sigmoid is defined as:

$$\begin{array}{r}\text{HSigmoid}(input)=\{\begin{array}{ll}0,& \text{ if }input\le -3,\\ 1,& \text{ if }input\ge +3,\\ input/6+1/2,& \text{ otherwise }\end{array}\end{array}$$

HSigmoid Activation Function Graph:

Inputs:

• input (Tensor) - The input of HSigmoid.

Outputs:

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

Raises

• TypeError – If input is not a Tensor.

• TypeError – If input is neither int nor float.

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> from mindspore import Tensor, nn
>>> import numpy as np
>>> input = Tensor(np.array([-1, -2, 0, 2, 1]), mindspore.float16)
>>> hsigmoid = nn.HSigmoid()
>>> result = hsigmoid(input)
>>> print(result)
[0.3333 0.1666 0.5    0.8335 0.6665]