ONNX-Chainer

All code and functionalities of ONNX-Chainer have been merged into Chainer v7rc1 and this repository supports only bug fixes.

This is an add-on package for ONNX support by Chainer.

Tested environment

see Tested environments

Installation

pip install onnx-chainer

Run Test

1. Install test modules

$ pip install onnx-chainer[test-cpu]

Or, on GPU environment

$ pip install cupy  # or cupy-cudaXX is useful
$ pip install onnx-chainer[test-gpu]

2. Run tests

$ pytest -m "not gpu"

Or, on GPU environment

$ pytest

Quick Start

First, install ChainerCV to get the pre-trained models.

import numpy as np

import chainer
import chainercv.links as C
import onnx_chainer

model = C.VGG16(pretrained_model='imagenet')

# Pseudo input
x = np.zeros((1, 3, 224, 224), dtype=np.float32)

onnx_chainer.export(model, x, filename='vgg16.onnx')

Supported Functions

see Supported Functions

Contribution

Any contribution to ONNX-Chainer is welcome!

• Python codes follow Chainer Coding Guidelines