(l-onnx-doc-Swish)=

# Swish


(l-onnx-op-swish-24)=

## Swish - 24

### Version

- **name**: [Swish (GitHub)](https://github.com/onnx/onnx/blob/main/docs/Operators.md#Swish)
- **domain**: `main`
- **since_version**: `24`
- **function**: `True`
- **support_level**: `SupportType.COMMON`
- **shape inference**: `True`

This version of the operator has been available
**since version 24**.

### Summary

Swish function takes one input data (Tensor<T>) and produces one output data (Tensor<T>) of the same shape,
where $Swish(x) = x * sigmoid(alpha * x)$.

#### Function Body

The function definition for this operator.

```
<
  domain: "",
  opset_import: ["" : 24]
>
Swish <alpha>(X) => (Y)
{
   Alpha = Constant <value_float: float = @alpha> ()
   AlphaCast = CastLike (Alpha, X)
   AlphaMulX = Mul (AlphaCast, X)
   SigmoidAlphaMulX = Sigmoid (AlphaMulX)
   Y = Mul (X, SigmoidAlphaMulX)
}
```

### Attributes

* **alpha - FLOAT** (default is `'1.0'`):

  Coefficient to multiply with input before sigmoid.

### Inputs

- **X** (heterogeneous) - **T**:

  Input tensor

### Outputs

- **Y** (heterogeneous) - **T**:

  Output tensor

### Type Constraints

* **T** in ( `tensor(bfloat16)`, `tensor(double)`, `tensor(float)`, `tensor(float16)` ):

  Constrain input and output types to float tensors.