.. _l-onnx-doccom.microsoft.nchwc-GlobalAveragePool:

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com.microsoft.nchwc - GlobalAveragePool
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.. contents::
    :local:


.. _l-onnx-opcom-microsoft-nchwc-globalaveragepool-1:

GlobalAveragePool - 1 (com.microsoft.nchwc)
===========================================

**Version**

* **name**: `GlobalAveragePool (GitHub) <https://github.com/onnx/onnx/blob/main/docs/Operators.md#com.microsoft.nchwc.GlobalAveragePool>`_
* **domain**: **com.microsoft.nchwc**
* **since_version**: **1**
* **function**:
* **support_level**:
* **shape inference**:

This version of the operator has been available
**since version 1 of domain com.microsoft.nchwc**.

**Summary**

For internal use.

**Inputs**

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

**Outputs**

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

**Examples**

**default**

::

    node = onnx.helper.make_node(
        "GlobalAveragePool",
        inputs=["x"],
        outputs=["y"],
    )
    x = np.random.randn(1, 3, 5, 5).astype(np.float32)
    y = np.mean(x, axis=tuple(range(2, np.ndim(x))), keepdims=True)
    expect(node, inputs=[x], outputs=[y], name="test_globalaveragepool")

**_globalaveragepool_precomputed**

::

    node = onnx.helper.make_node(
        "GlobalAveragePool",
        inputs=["x"],
        outputs=["y"],
    )
    x = np.array(
        [
            [
                [
                    [1, 2, 3],
                    [4, 5, 6],
                    [7, 8, 9],
                ]
            ]
        ]
    ).astype(np.float32)
    y = np.array([[[[5]]]]).astype(np.float32)
    expect(node, inputs=[x], outputs=[y], name="test_globalaveragepool_precomputed")