mindspore.mint.nn.functional.hardsigmoid

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mindspore.mint.nn.functional.hardsigmoid(input)[source]

Hard Sigmoid activation function. Calculates the output according to the input elements.

Hard Sigmoid is defined as:

\[\begin{split}\text{Hardswish}(input) = \begin{cases} 0, & \text{ if } input \leq -3, \\ 1, & \text{ if } input \geq +3, \\ input/6 + 1/2, & \text{ otherwise } \end{cases}\end{split}\]

HSigmoid Activation Function Graph:

../../_images/HSigmoid.png
Parameters

input (Tensor) – The input Tensor.

Returns

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

Examples

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