Mish
Mish#
Versioned name: Mish-1
Category: Activation
Short description: Mish is a Self Regularized Non-Monotonic Neural Activation Function.
OpenVINO description: This OP is as same as OpenVINO OP
Detailed Description
Mish is a self regularized non-monotonic neural activation function proposed in this article.
Mish performs element-wise activation function on a given input tensor, based on the following mathematical formula:
Attributes: Mish operation has no attributes.
Inputs:
1:
input
- multidimensional input tensor. Required.Type: T
Outputs
1:
output
- multidimensional output tensor with shape and type matching the input tensor. Required.Type: T
Types:
T: f32, f16, bf16.
Note: Inputs and outputs have the same data type denoted by T. For example, if input is f32 tensor, then all other tensors have f32 data type.