.. _op_ai_onnx_HannWindow:

HannWindow
==========

- **Domain**: ``ai.onnx``
- **Since version**: 17

Generates a Hann window as described in the paper https://ieeexplore.ieee.org/document/1455106.

**Inputs**

- **size** (*T1*): A scalar value indicating the length of the window.

**Outputs**

- **output** (*T2*): A Hann window with length: size. The output has the shape: [size].

**Type Constraints**

- **T1**: Constrain the input size to int32_t or int64_t.
  Allowed types: tensor(int32), tensor(int64).
- **T2**: Constrain output types to numeric tensors.
  Allowed types: tensor(bfloat16), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8).

Examples
--------

**test_cc_hannwindow**

.. code-block:: text

    Node:
      HannWindow(x) -> (y)

.. code-block:: text

    Inputs:
      x: shape=(), dtype=int32
        10

    Outputs:
      y: shape=(10,), dtype=float32
        [0.        , 0.09549151, 0.3454915 , 0.6545085 , 0.9045085 , 1.        ,
         0.9045085 , 0.6545085 , 0.3454915 , 0.09549151]

**test_cc_hannwindow_symmetric**

.. code-block:: text

    Node:
      HannWindow(x) -> (y)
      Attributes:
        periodic = 0

.. code-block:: text

    Inputs:
      x: shape=(), dtype=int32
        10

    Outputs:
      y: shape=(10,), dtype=float32
        [0.        , 0.11697778, 0.4131759 , 0.75      , 0.9698463 , 0.9698463 ,
         0.75      , 0.4131759 , 0.11697778, 0.        ]