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English | 简体中文
Welcome to the PaddlePaddle GitHub.
PaddlePaddle (PArallel Distributed Deep LEarning) is an easy-to-use,
efficient, flexible and scalable deep learning platform, which is originally
developed by Baidu scientists and engineers for the purpose of applying deep
learning to many products at Baidu.
Our vision is to enable deep learning for everyone via PaddlePaddle.
Please refer to our release announcement to track the latest feature of PaddlePaddle.
# Linux CPU
pip install paddlepaddle
# Linux GPU cuda9cudnn7
pip install paddlepaddle-gpu
# Linux GPU cuda8cudnn7
pip install paddlepaddle-gpu==1.4.1.post87
# Linux GPU cuda8cudnn5
pip install paddlepaddle-gpu==1.4.1.post85
# For installation on other platform, refer to http://paddlepaddle.org/
Flexibility
PaddlePaddle supports a wide range of neural network architectures and
optimization algorithms. It is easy to configure complex models such as
neural machine translation model with attention mechanism or complex memory
connection.
Efficiency
In order to unleash the power of heterogeneous computing resource,
optimization occurs at different levels of PaddlePaddle, including
computing, memory, architecture and communication. The following are some
examples:
Scalability
With PaddlePaddle, it is easy to use many CPUs/GPUs and machines to speed
up your training. PaddlePaddle can achieve high throughput and performance
via optimized communication.
Connected to Products
In addition, PaddlePaddle is also designed to be easily deployable. At Baidu,
PaddlePaddle has been deployed into products and services with a vast number
of users, including ad click-through rate (CTR) prediction, large-scale image
classification, optical character recognition(OCR), search ranking, computer
virus detection, recommendation, etc. It is widely utilized in products at
Baidu and it has achieved a significant impact. We hope you can also explore
the capability of PaddlePaddle to make an impact on your product.
It is recommended to read this doc on our website.
We provide English and
Chinese documentation.
You might want to start from this online interactive book that can run in a Jupyter Notebook.
You can run distributed training jobs on MPI clusters.
Our new API enables much shorter programs.
We appreciate your contributions!
PaddlePaddle is provided under the Apache-2.0 license.
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
https://www.paddlepaddle.org.cn/
C++ Python Cuda Text Shell other
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