openvino/docs/ops/activation/Mish_4.md

Mish

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Versioned name: Mish-4

Category: Activation function

Short description: Mish is a Self Regularized Non-Monotonic Neural Activation Function.

Detailed description

Mish is a self regularized non-monotonic neural activation function proposed in this article <https://arxiv.org/abs/1908.08681v2>__.

Mish performs element-wise activation function on a given input tensor, based on the following mathematical formula:

.. math::

Mish(x) = x\cdot\tanh\big(SoftPlus(x)\big) = x\cdot\tanh\big(\ln(1+e^{x})\big)

Attributes: Mish operation has no attributes.

Inputs:

• 1: A tensor of type T and arbitrary shape. Required.

Outputs:

• 1: The result of element-wise Mish function applied to the input tensor. A tensor of type T and the same shape as input tensor.

Types

• T: arbitrary supported floating-point type.

Example

.. code-block:: cpp

<layer ... type="Mish"> 256 56 256 56

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