LpNormalization - version 1#

This page documents version 1 of operator LpNormalization. See LpNormalization for the latest version (since version 22).

  • Domain: ai.onnx

  • Since version: 1

Given a matrix, apply Lp-normalization along the provided axis. The output is computed as: output = input / Lp_norm(input, axis). When the Lp norm is zero (i.e., all elements along the axis are zero), the output is defined to be zero to avoid division by zero.

Inputs

  • input (T): Input matrix

Outputs

  • output (T): Matrix after normalization

Attributes

  • axis (int): The axis on which to apply normalization, -1 mean last axis.

  • p (int): The order of the normalization, only 1 or 2 are supported.

Type Constraints

  • T: Constrain input and output types to float tensors. Allowed types: tensor(double), tensor(float), tensor(float16).