# 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)
}


### 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)
}


### 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.