## Function Changelog
*This file is automatically generated from the
            [def files](/onnx/defs) via [this script](/onnx/defs/gen_doc.py).
            Do not modify directly and instead edit function definitions.*
# ai.onnx (default)
## Version 9 of domain ai.onnx (default)
### <a name="MeanVarianceNormalization-9"></a>**MeanVarianceNormalization-9**</a>

  A MeanVarianceNormalization Function: Perform mean variance normalization on the input tensor X using formula: <br/> ``` (X-EX)/sqrt(E(X-EX)^2) ``` <br/><br/><b>INPUT: </b>X(float/float16/double) with shape [N,C,W,H] or N-D shape <br/><br/><b>ATTRIBUTE: </b><br/>&nbsp;&nbsp;&nbsp;&nbsp;<tt>axes: </tt>will be passed to ReducedMean Ops. Use [0,2,3] (without C axis for N-D cases) for calculating means and variances along channels. Two variables with the same C-coordinate are associated with the same mean and variance. Use [0,1,2,3] (with C axis) to calculate global mean and global variance with all variables sharing the same mean/variance.<br/>&nbsp;&nbsp;&nbsp;&nbsp;(The KeepDims attribute in ReducedMean is set to true for calculation)<br/><br/><b>OUTPUT: </b>X_MVN(float/float16/double) with the same shape as input X<br/>

#### Version

This version of the function has been available since version 9 of the default ONNX operator set.

#### Inputs

<dl>
<dt>X; </dt>
<br/></dl>

#### Outputs

<dl>
<dt>X_MVN; </dt>
<br/></dl>

#### Attributes

<dl>
<dt>axes;<br/></dt>
</dl>

