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doc/fluid/advanced_usage/deploy/index_cn.rst

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预测部署
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########
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- `原生预测引擎 <inference/index_cn.html>`_ :介绍了支持模型部署上线的Fluid C++ API
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- `服务器端部署 <inference/index_cn.html>`_ :介绍了支持模型部署上线的Fluid C++ API
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- `移动端部署 <mobile/index_cn.html>`_:介绍了 PaddlePaddle组织下的嵌入式平台深度学习框架Paddle-Mobile
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doc/fluid/advanced_usage/deploy/inference/index_cn.rst

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############
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原生预测引擎
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服务器端部署
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############
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PaddlePaddle Fluid 提供了 C++ API 来支持模型的部署上线
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.. toctree::
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:titlesonly:
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build_and_install_lib_cn.rst
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native_infer.md

doc/fluid/advanced_usage/deploy/inference/windows_cpp_inference.md

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执行完毕后,build 目录如图所示,打开箭头指向的 solution 文件:
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<p align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image3.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image3.png">
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修改编译属性为 `/MT`
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<p align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image4.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image4.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image5.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image5.png">
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编译生成选项改成 `Release`
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<p align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image6.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image6.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image7.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image7.png">
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将提供的依赖包中,Release下的openblas和模型文件拷贝到编译生成的Release下。
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<p align="center">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image8.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image8.png">
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通过cmd进到Release目录执行:
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`simple_on_word2vec.exe --dirname=.\word2vec.inference.model`
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/user_guides/howto/inference/image/image9.png">
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<img src="https://raw.githubusercontent.com/PaddlePaddle/FluidDoc/develop/doc/fluid/advanced_usage/deploy/inference/image/image9.png">
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doc/fluid/advanced_usage/development/profiling/index_cn.rst

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性能调优
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.. toctree::
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benchmark.rst
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cpu_profiling_cn.md
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gpu_profiling_cn.rst
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host_memory_profiling_cn.md
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timeline_cn.md
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本模块介绍 Fluid 使用过程中的调优方法,包括:
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- `如何进行基准测试 <benchmark.html>`_:介绍如何选择基准模型,从而验证模型的精度和性能
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- `Timeline工具简介 <timeline_cn.html>`_ :介绍如何使用 Timeline 工具进行性能分析和调优
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benchmark.rst
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cpu_profiling_cn.md
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gpu_profiling_cn.rst
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timeline_cn.md
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## High/Low-level API简介
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Paddle目前有2套API接口
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PaddlePaddle Fluid目前有2套API接口
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- Low-level(底层) API:
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- 灵活性强并且已经相对成熟,使用它训练的模型,能直接支持C++预测上线。
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- 提供了大量的模型作为使用示例,包括[Book](https://github.com/PaddlePaddle/book)中的第7和8章,以及[models](https://github.com/PaddlePaddle/models)中的所有章节。
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- 提供了大量的模型作为使用示例,包括[Book](https://github.com/PaddlePaddle/book)中的全部章节,以及[models](https://github.com/PaddlePaddle/models)中的所有章节。
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- 适用人群:对深度学习有一定了解,需要自定义网络进行训练/预测/上线部署的用户。
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- High-level(高层)API:
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- 使用简单,[Book](https://github.com/PaddlePaddle/book)中前六章提供了示例。
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- 使用简单
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- 尚未成熟,接口暂时在[paddle.fluid.contrib](https://github.com/PaddlePaddle/Paddle/tree/develop/python/paddle/fluid/contrib)下面。
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- 适用人群:想通过Book课程进行深度学习基础知识学习的初级用户。

doc/fluid/api/average.rst

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doc/fluid/api/backward.rst

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doc/fluid/api/clip.rst

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doc/fluid/api/data_feeder.rst

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doc/fluid/api/executor.rst

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