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TEE Simple AI (SAI) User Manual

SAI是基于PyTorch/Caffe的卷积神经网络模型训练,转换,部署工具——可训练得到定点化模型(1bit或者3bit),该模型可在TEE.COM的算力棒产品上运行。支持Windows,Linux等主流平台。

TODO list:

  • PyTorch quantization model training for classification & conversion
  • Caffe quantization model training for classification & conversion
  • Windows/Linux classify inference library and c++ examples
  • Python examples
  • ARM-Linux/Android inference library and c++ examples
  • Caffe Faster RCNN model training & conversion & inference library
  • Pytorch Faster RCNN model training & conversion & inference library
  • Model Zoo
  • Benchmark

算力棒运行环境

系统 (Win10/Ubuntu 16.04)

安装算力棒驱动

Windows 10系统无需安装驱动,Linux系统请参考以下命令为算力棒安装驱动

$ sudo cp api/lib/linux/50-emmc.rules /etc/udev/rules.d/

模型训练(SAI_ROOT/train)

针对不同的开发者,我们提供了两种训练框架(Pytorch与Caffe)的模型训练与转换,大家可以根据个人喜好选择使用。

推断部署(SAI_ROOT/api)

得到可以在算力棒上运行的模型后,我们可以通过调用SAI的API,在终端设备上很方便的部署上你的模型。

目前API里包括用于图片分类的TEEClassifier library和用于目标检测的基于Faster RCNN的TEEDetectorFRCNN library,支持windows/linux/arm-linux三个平台,后续会增加android/ios等平台支持。

SAI_ROOT/example下提供了各个平台的c++/python示例工程,展示了API的调用方法。

Issue: Windows版本的library依赖于libeay32.dll,请确定系统路径里存在该dll文件,若没有的话,可直接使用api目录下的libeay32.dll。

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