
 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 https://github.com/PaddlePaddle/Paddle/releases to track the latest feature of PaddlePaddle.
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.
https://github.com/PaddlePaddle/book
You might want to start from this online interactive book that can run in a Jupyter Notebook.
Distributed Training
You can run distributed training jobs on MPI clusters.
Python API
Our new API enables much shorter programs.
How to Contribute
We appreciate your contributions!
You are welcome to submit questions and bug reports as https://github.com/PaddlePaddle/Paddle/issues.
PaddlePaddle is provided under the Apache-2.0 license.






探索更多轩辕镜像的使用方法,找到最适合您系统的配置方式
通过 Docker 登录认证访问私有仓库
无需登录使用专属域名
Kubernetes 集群配置 Containerd
K3s 轻量级 Kubernetes 镜像加速
VS Code Dev Containers 配置
Podman 容器引擎配置
HPC 科学计算容器配置
ghcr、Quay、nvcr 等镜像仓库
Harbor Proxy Repository 对接专属域名
Portainer Registries 加速拉取
Nexus3 Docker Proxy 内网缓存
需要其他帮助?请查看我们的 常见问题Docker 镜像访问常见问题解答 或 提交工单
manifest unknown
no matching manifest(架构)
invalid tar header(解压)
TLS 证书失败
DNS 超时
410 Gone 排查
402 与流量用尽
401 认证失败
429 限流
D-Bus 凭证提示
413 与超大单层
来自真实用户的反馈,见证轩辕镜像的优质服务