# optimizer

**Repository Path**: chongyangwang-song/optimizer

## Basic Information

- **Project Name**: optimizer
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-12-12
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ONNX Optimizer

[![PyPI version](https://img.shields.io/pypi/v/onnxoptimizer.svg)](https://pypi.python.org/pypi/onnxoptimizer/)
[![PyPI license](https://img.shields.io/pypi/l/onnxoptimizer.svg)](https://pypi.python.org/pypi/onnxoptimizer/)
[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](https://github.com/onnx/optimizer/pulls)

## Introduction

ONNX provides a C++ library for performing arbitrary optimizations on ONNX models, as well as a growing list of prepackaged optimization passes.

The primary motivation is to share work between the many ONNX backend implementations. Not all possible optimizations can be directly implemented on ONNX graphs - some will need additional backend-specific information - but many can, and our aim is to provide all such passes along with ONNX so that they can be re-used with a single function call.

You may be interested in invoking the provided passes, or in implementing new ones (or both).

## Installation

You can install onnxoptimizer from PyPI:

```bash
pip3 install onnxoptimizer
```

Or build it from source:

```bash
git clone --recursive https://github.com/onnx/optimizer onnxoptimizer
cd onnxoptimizer
pip3 install -e .
```

Note that you need to install protobuf before building from source.

## Roadmap

* Command-line API (e.g. `python3 -m onnxoptimizer model.onnx output.onnx`)
* More built-in pass
* Separate graph rewriting and constant folding (or a pure graph rewriting mode, see [issue #9](https://github.com/onnx/optimizer/issues/9) for the details)

## Relevant tools

* [onnx-simplifier](https://github.com/daquexian/onnx-simplifier): A handy and popular tool based on onnxoptimizer

## Code of Conduct

[ONNX Open Source Code of Conduct](https://onnx.ai/codeofconduct.html)