PaddlePaddle (PArallel Distributed Deep LEarning) 是一个简单易用、高效灵活、可扩展的深度学习平台,最初由百度科学家和工程师共同开发,目的是将深度学习技术应用到百度的众多产品中。
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PaddlePaddle-Gardener beb66385d8 !746 Revert "Fix some Bugs of Undefined Variable" 3 days ago
.github !112 graph engine 1 month ago
cmake !702 Check the installed openblas version in cmake 1 week ago
doc add paddlepaddle logo (#25690) 11 months ago
go !278 refator paddle inference c api interface 1 month ago
paddle !744 Fix LayerNorm Problem 4 days ago
patches !414 [Rocm] fix expand as 1 month ago
python !746 Revert "Fix some Bugs of Undefined Variable" 3 days ago
r Upgrade string literals to raw string (#28989) 6 months ago
tools !726 fix the bug that `` cannot get all the public apis 1 week ago
.clang-format fix develop build issue (#10978) 3 years ago
.dockerignore refine docker build 4 years ago
.gitignore don't re-generate header file if content doesn't change (#25130) 1 year ago
.pre-commit-config.yaml remove shellcheck test=develop (#28457) 7 months ago
.style.yapf change python code style to pep8 4 years ago !460 Simple authors change 1 month ago
CMakeLists.txt !613 [ROCM] update paddle inference cmake, test=develop 1 week ago Adding a Code of Conduct for Paddle open source project (#7579) 3 years ago change from Traditional Chinese to Simplified Chinese 3 years ago Update 1 year ago Revise one word in (#371) 4 years ago
LICENSE Fix the grammar in copyright. (#8403) 3 years ago !507 Optimize 102Flowers dataset reading speed 1 month ago !507 Optimize 102Flowers dataset reading speed 1 month ago update_release_1.4 2 years ago

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Welcome to the PaddlePaddle GitHub.

PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open-sourced to professional communities since 2016. It is an industrial platform with advanced technologies and rich features that cover core deep learning frameworks, basic model libraries, end-to-end development kits, tools & components as well as service platforms.
PaddlePaddle is originated from industrial practices with dedication and commitments to industrialization. It has been widely adopted by a wide range of sectors including manufacturing, agriculture, enterprise service, and so on while serving more than 2.3 million developers. With such advantages, PaddlePaddle has helped an increasing number of partners commercialize AI.


Latest PaddlePaddle Release: v2.0

Our vision is to enable deep learning for everyone via PaddlePaddle.
Please refer to our release announcement to track the latest features of PaddlePaddle.

Install Latest Stable Release:

pip install paddlepaddle
pip install paddlepaddle-gpu

More infomation about installation, please view Quick Install

Now our developers can acquire Tesla V100 online computing resources for free. If you create a program by AI Studio, you will obtain 10 hours to train models online per day. Click here to start.


  • Agile Framework for Industrial Development of Deep Neural Networks

    The PaddlePaddle deep learning framework facilitates the development while lowering the technical burden, through leveraging a programmable scheme to architect the neural networks. It supports both declarative programming and imperative programming with both development flexibility and high runtime performance preserved. The neural architectures could be automatically designed by algorithms with better performance than the ones designed by human experts.

  • Support Ultra-Large-Scale Training of Deep Neural Networks

    PaddlePaddle has made breakthroughs in ultra-large-scale deep neural networks training. It launched the world’s first large-scale open-source training platform that supports the training of deep networks with 100 billions of features and trillions of parameters using data sources distributed over hundreds of nodes. PaddlePaddle overcomes the online deep learning challenges for ultra-large-scale deep learning models, and further achieved the real-time model updating with more than 1 trillion parameters.
    Click here to learn more

  • Accelerated High-Performance Inference over Ubiquitous Deployments

    PaddlePaddle is not only compatible with other open-source frameworks for models training, but also works well on the ubiquitous developments, varying from platforms to devices. More specifically, PaddlePaddle accelerates the inference procedure with the fastest speed-up. Note that, a recent breakthrough of inference speed has been made by PaddlePaddle on Huawei’s Kirin NPU, through the hardware/software co-optimization.
    Click here to learn more

  • Industry-Oriented Models and Libraries with Open Source Repositories

    PaddlePaddle includes and maintains more than 100 mainstream models that have been practiced and polished for a long time in the industry. Some of these models have won major prizes from key international competitions. In the meanwhile, PaddlePaddle has further more than 200 pre-training models (some of them with source codes) to facilitate the rapid development of industrial applications.
    Click here to learn more


We provide English and
Chinese documentation.

  • Guides

    You might want to start from how to implement deep learning basics with PaddlePaddle.

  • Practice

    So far you have already been familiar with Fluid. And the next step should be building a more efficient model or inventing your original Operator.

  • API Reference

    Our new API enables much shorter programs.

  • How to Contribute

    We appreciate your contributions!


  • Github Issues: bug reports, feature requests, install issues, usage issues, etc.
  • QQ discussion group: 793866180 (PaddlePaddle).
  • Forums: discuss implementations, research, etc.

PaddlePaddle is provided under the Apache-2.0 license.