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.. _op_ai_onnx_LpNormalization-1:

LpNormalization - version 1
===========================

This page documents version **1** of operator **LpNormalization**. See :doc:`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).