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README
Apache-2.0

Paddle2ONNX

简体中文 | English

1 简介

Paddle2ONNX 支持将 PaddlePaddle 模型格式转化到 ONNX 模型格式。通过 ONNX 可以完成将 Paddle 模型到多种推理引擎的部署,包括 TensorRT/OpenVINO/MNN/TNN/NCNN,以及其它对 ONNX 开源格式进行支持的推理引擎或硬件。

感谢EasyEdge团队贡献的Paddle2Caffe, 支持将Paddle模型导出为Caffe格式,安装及使用方式参考Paddle2Caffe

2 环境依赖

  • PaddlePaddle == 2.6.0
  • onnxruntime >= 1.10.0

3 安装

针对PaddlePaddle2.5.2的用户可以直接运行以下命令行代码来安装P2O

pip install paddle2onnx

由于没有自动发包机制,针对PaddlePaddle2.6.0的用户,请按照Github 源码安装方式编译Paddle2ONNX。

4 使用

4.1 获取PaddlePaddle部署模型

Paddle2ONNX 在导出模型时,需要传入部署模型格式,包括两个文件

  • model_name.pdmodel: 表示模型结构
  • model_name.pdiparams: 表示模型参数 [注意] 这里需要注意,两个文件其中参数文件后辍为 .pdiparams,如你的参数文件后辍是 .pdparams ,那说明你的参数是训练过程中保存的,当前还不是部署模型格式。 部署模型的导出可以参照各个模型套件的导出模型文档。

4.2 调整Paddle模型

如果对Paddle模型的输入输出需要做调整,可以前往Paddle 相关工具查看教程。

4.3 命令行转换

使用如下命令将Paddle模型转换为ONNX模型

paddle2onnx --model_dir saved_inference_model \
            --model_filename model.pdmodel \
            --params_filename model.pdiparams \
            --save_file model.onnx

可调整的转换参数如下表:

参数 参数说明
--model_dir 配置包含 Paddle 模型的目录路径
--model_filename [可选] 配置位于 --model_dir 下存储网络结构的文件名
--params_filename [可选] 配置位于 --model_dir 下存储模型参数的文件名称
--save_file 指定转换后的模型保存目录路径
--opset_version [可选] 配置转换为 ONNX 的 OpSet 版本,目前支持 7~16 等多个版本,默认为 9
--enable_onnx_checker [可选] 配置是否检查导出为 ONNX 模型的正确性, 建议打开此开关, 默认为 False
--enable_auto_update_opset [可选] 是否开启 opset version 自动升级功能,当低版本 opset 无法转换时,自动选择更高版本的 opset进行转换, 默认为 True
--deploy_backend [可选] 量化模型部署的推理引擎,支持 onnxruntime、tensorrt 或 others,当选择 others 时,所有的量化信息存储于 max_range.txt 文件中,默认为 onnxruntime
--save_calibration_file [可选] TensorRT 8.X版本部署量化模型需要读取的 cache 文件的保存路径,默认为 calibration.cache
--version [可选] 查看 paddle2onnx 版本
--external_filename [可选] 当导出的 ONNX 模型大于 2G 时,需要设置 external data 的存储路径,推荐设置为:external_data
--export_fp16_model [可选] 是否将导出的 ONNX 的模型转换为 FP16 格式,并用 ONNXRuntime-GPU 加速推理,默认为 False
--custom_ops [可选] 将 Paddle OP 导出为 ONNX 的 Custom OP,例如:--custom_ops '{"paddle_op":"onnx_op"},默认为 {}

4.4 裁剪ONNX

如果你需要调整 ONNX 模型,请参考如下工具:ONNX 相关工具

4.5 优化ONNX

如你对导出的 ONNX 模型有优化的需求,推荐使用 onnx-simplifier,也可使用如下命令对模型进行优化

python -m paddle2onnx.optimize --input_model model.onnx --output_model new_model.onnx

5 License

Provided under the Apache-2.0 license.

6 捐赠

  • 感谢 PaddlePaddle 团队提供服务器支持 Paddle2ONNX 的 CI 建设。
  • 感谢社区用户 chenwhqlluotao1goocodyjeff41404jzhang553ZhengBicheng 于2024年03月28日向 Paddle2ONNX PMC 捐赠共 10000 元人名币用于 Paddle2ONNX 的发展。
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paddle2onnx支持将PaddlePaddle模型格式转化到ONNX模型格式 展开 收起
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