“8d253e4965196d7ae535a32d88057383201b40fd”上不存在“paddle/operators/ctc_align_op.h”
名称 最后提交 最后更新
adversarial fix bugs and modify func param name
benchmark Fluid distributed training benchmark (#7410)
cmake Port WarpCTC Operator (#5107)
doc fix op doc
doc_theme mistaken: Folk -> Fork in develop branch
go unify the indentation of license
paddle Enhance print_op.
proto Refine AvgPooling with excludeMode to make it compatible with the raw prototxt
python Merge pull request #7249 from typhoonzero/transpiler_split_tensor
tools/manylinux1 Move content in the buildtools repo into paddle repo (#7326)
v1_api_demo refine README.md for v1_api_demo and v1_api_tutorials
.clang-format Send recv op (#5520)
.clang_format.hook clang format with version check (#3513)
.dockerignore refine docker build
.gitignore Add version api (#2985)
.pre-commit-config.yaml Fix gometalinter versioning (#4832)
.style.yapf change python code style to pep8
.travis.yml Refine CheckStyle Script (#5942)
AUTHORS.md sort the Author.md with Alphabetical order
CMakeLists.txt Add a simple example for fluid to do inference in C++ code.
CONTRIBUTING.md * Add symbolic link from Paddle/CONTRIBUTING.md to doc/howto/dev/contribute_to_paddle_en.md so sphinx can generate the document
Dockerfile Send recv op (#5520)
Dockerfile.android Add ARGS ANDROID_API in Dockerfile.android, to support using toolchain of different api level.
ISSUE_TEMPLATE.md Revise one word in ISSUE_TEMPLATE.md (#371)
LICENSE Change "Baidu, Inc" into "PaddlePaddle Authors"
README.md add a brief introduction of MKL-DNN work in root README.md
RELEASE.cn.md update v0.11.0 release note
RELEASE.md change Fluid description

项目简介

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)

:rocket: Github 镜像仓库 :rocket:

源项目地址 :arrow_down: :arrow_down: :arrow_down:

https://github.com/paddlepaddle/paddle

deep-learningdistributed-trainingefficiencymachine-learningneural-networkpaddlepaddlepythonscalability

发行版本 60

PaddlePaddle 2.5.0 Release Note

全部发行版

贡献者 246

全部贡献者

开发语言

  • C++ 49.8 %
  • Python 41.0 %
  • Cuda 7.0 %
  • CMake 1.1 %
  • Shell 0.6 %
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