:nosearch:

.. _op_ai_onnx_MeanVarianceNormalization-9:

MeanVarianceNormalization - version 9
=====================================

This page documents version **9** of operator **MeanVarianceNormalization**. See :doc:`MeanVarianceNormalization` for the latest version (since version 13).

- **Domain**: ``ai.onnx``
- **Since version**: 9

A MeanVarianceNormalization Function: Perform mean variance normalization
on the input tensor X using formula: ``(X-EX)/sqrt(E(X-EX)^2)``

**Inputs**

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

**Outputs**

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

**Attributes**

- **axes** (*int[]*): A list of integers, along which to reduce. The default is to calculate along axes [0,2,3] for calculating mean and variance along each channel. Two variables with the same C-coordinate are associated with the same mean and variance.

**Type Constraints**

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