Softplus

Softplus - 22

Version

  • name: Softplus (GitHub)

  • domain: main

  • since_version: 22

  • function: True

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 22.

Summary

Softplus takes one input data (Tensor) and produces one output data (Tensor) where the softplus function, y = ln(exp(x) + 1), is applied to the tensor elementwise.

Function Body

The function definition for this operator.

<
  domain: "",
  opset_import: ["" : 18]
>
Softplus (X) => (Y)
{
   exp_x = Exp (X)
   one = Constant <value: tensor = float {1}> ()
   one_cast = CastLike (one, X)
   exp_x_add_one = Add (exp_x, one_cast)
   Y = Log (exp_x_add_one)
}

Inputs

  • X (heterogeneous) - T:

    1D input tensor

Outputs

  • Y (heterogeneous) - T:

    1D input tensor

Type Constraints

  • T in ( tensor(bfloat16), tensor(double), tensor(float), tensor(float16) ):

    Constrain input and output types to float tensors.

Softplus - 1

Version

  • name: Softplus (GitHub)

  • domain: main

  • since_version: 1

  • function: True

  • support_level: SupportType.COMMON

  • shape inference: True

This version of the operator has been available since version 1.

Summary

Softplus takes one input data (Tensor) and produces one output data (Tensor) where the softplus function, y = ln(exp(x) + 1), is applied to the tensor elementwise.

Function Body

The function definition for this operator.

<
  domain: "",
  opset_import: ["" : 18]
>
Softplus (X) => (Y)
{
   exp_x = Exp (X)
   one = Constant <value: tensor = float {1}> ()
   one_cast = CastLike (one, X)
   exp_x_add_one = Add (exp_x, one_cast)
   Y = Log (exp_x_add_one)
}

Inputs

  • X (heterogeneous) - T:

    1D input tensor

Outputs

  • Y (heterogeneous) - T:

    1D input tensor

Type Constraints

  • T in ( tensor(double), tensor(float), tensor(float16) ):

    Constrain input and output types to float tensors.