KSAI Lite is a deep learning inference framework of kingsoft, based on tensorflow lite

KSAI Lite

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KSAI Lite是一个轻量级、灵活性强、高性能且易于扩展的深度学习推理框架,底层基于tensorflow lite,定位支持包括移动端、嵌入式以及服务器端在内的多硬件平台。

当前KSAI Lite已经应用在金山office内部业务中,并逐步支持金山企业的生产任务和众多外部用户。

快速入门

使用KSAI Lite,只需几个简单的步骤,就可以把模型部署到多种终端设备中,运行高性能的推理任务,使用流程如下所示:

一. 准备模型

KSAI Lite框架直接支持模型结构为tflite模型。 如果您手中的模型是由诸如Caffe、MXNet、PyTorch等框架产出的,那么您可以使用工具将模型转换为tflite格式。

二. 模型优化

KSAI Lite框架基于底层tensorflow lite的优化方法,拥有优秀的加速、优化策略及实现,包含量化、子图融合、Kernel优选等优化手段。优化后的模型更轻量级,耗费资源更少,并且执行速度也更快。

三. 下载或编译

KSAI Lite提供了多平台的官方Release预测库下载,我们优先推荐您直接下载 KSAI Lite预编译库,包括了Linux-X64, Linux-ARM, Linux-MIPS64以及Windows-X64索引库Windows-X64动态链接库。 您也可以根据目标平台选择对应的源码编译方法。KSAI Lite 提供了源码编译脚本,位于 tools/目录下,只需要按照docs/目录下的准备环境说明文档environment setup.md搭建好环境然后切到tools/目录调用编译脚本两个步骤即可一键编译得到目标平台的KSAI Lite预测库。

四. 预测示例

KSAI Lite提供了C++ API,并且提供了相应API的完整使用示例: 目录为tensorflow/lite/examples/reg_test/reg_test.cc 您可以参考示例快速了解使用方法,并集成到您自己的项目中去,也可以参考KSAI-Toolkits该项目。

主要特性

  • 多硬件支持
    • KSAI Lite架构已经验证和完整支持从 Mobile 到 Server 多种硬件平台,包括 intel X86、ARM、华为 Kunpeng 920、龙芯Loongson-3A R3、兆芯C4600、Phytium FT1500a等,且正在不断增加更多新硬件支持。
  • 轻量级部署
    • KSAI Lite在设计上对图优化模块和执行引擎实现了良好的解耦拆分,移动端可以直接部署执行阶段,无任何第三方依赖。
  • 高性能
    • 极致的 ARM及X86 CPU 性能优化:针对不同微架构特点实现kernel的定制,最大发挥计算性能,在主流模型上展现出领先的速度优势。
  • 多模型多算子
    • KSAI Lite和tensorflow训练框架的OP对齐,提供广泛的模型支持能力。
    • 目前已对视觉类模型做到了较为充分的支持,覆盖分类、检测和识别,包含了特色的OCR模型的支持,并在不断丰富中。
  • 强大的图分析和优化能力
    • 不同于常规的移动端预测引擎基于 Python 脚本工具转化模型, Lite 架构上有完整基于 C++ 开发的 IR 及相应 Pass 集合,以支持操作融合,计算剪枝,存储优化,量化计算等多类计算图优化。

持续集成

System X86 Linux ARM Linux MIPS64 Linux windows
CPU(32bit) Build Status - - Build Status
CPU(64bit) Build Status - - Build Status
高通骁龙845 - Build Status - -
华为kunpeng920 - Build Status - -
龙芯Loongson-3A - - Build Status -
兆芯C4600 - Build Status - -
Phytium FT1500a - Build Status - -

交流与反馈

版权和许可证

KSAI-Lite由Apache-2.0 license提供

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