MeanVarianceNormalization - version 9#

This page documents version 9 of operator MeanVarianceNormalization. See 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).