.. _op_ai_onnx_Swish:

Swish
=====

- **Domain**: ``ai.onnx``
- **Since version**: 24

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

**Inputs**

- **X** (*T*): Input tensor

**Outputs**

- **Y** (*T*): Output tensor

**Attributes**

- **alpha** (*float*): Coefficient to multiply with input before sigmoid.

**Type Constraints**

- **T**: Constrain input and output types to float tensors.
  Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16).

Examples
--------

**test_cc_swish**

.. code-block:: text

    Node:
      Swish(X) -> (Y)

.. code-block:: text

    Inputs:
      X: shape=(2, 3), dtype=float32
        [[-4., -1.,  0.],
         [ 1.,  2.,  4.]]

    Outputs:
      Y: shape=(2, 3), dtype=float32
        [[-0.07194484, -0.26894143,  0.        ],
         [ 0.7310586 ,  1.761594  ,  3.928055  ]]

**test_cc_swish_alpha**

.. code-block:: text

    Node:
      Swish(X) -> (Y)
      Attributes:
        alpha = 2.0

.. code-block:: text

    Inputs:
      X: shape=(2, 3), dtype=float32
        [[-4., -1.,  0.],
         [ 1.,  2.,  4.]]

    Outputs:
      Y: shape=(2, 3), dtype=float32
        [[-1.3414006e-03, -1.1920292e-01,  0.0000000e+00],
         [ 8.8079703e-01,  1.9640275e+00,  3.9986587e+00]]