Versioned name: SoftPlus-1

Category: Activation

Short description: SoftPlus takes one input tensor and produces output tensor where the SoftPlus function is applied to the tensor elementwise.

Detailed description: For each element from the input tensor calculates corresponding element in the output tensor with the following formula:

\[SoftPlus(x) = 1/beta*ln(e^{beta*x} + 1.0)\]


  • beta

    • Description: beta is value for the Softplus formulation.

    • Range of values: A positive s64 value

    • Type: s64

    • Default value: 1

    • Required: no


  • 1: Multidimensional input tensor of type T. Required.

    • Type: T


  • 1: The resulting tensor of the same shape as input tensor. Required.

    • Type: T


  • 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.