Data

Tools

Indexes

Applications

Experiments

Open Source Science

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

https://github.com/apache/mxnet

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ○
    .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ✓
    Committers with academic emails
    59 of 929 committers (6.4%) from academic institutions
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (12.4%) to scientific vocabulary

Keywords

mxnet

Keywords from Contributors

deep-neural-networks distributed tensor semantic-segmentation pose-estimation autograd gans gluon gbm action-recognition
Last synced: 10 months ago · JSON representation

Repository

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

Basic Info
  • Host: GitHub
  • Owner: apache
  • License: apache-2.0
  • Language: C++
  • Default Branch: master
  • Homepage: https://mxnet.apache.org
  • Size: 96.6 MB
Statistics
  • Stars: 20,824
  • Watchers: 1,065
  • Forks: 6,757
  • Open Issues: 2,009
  • Releases: 34
Archived
Topics
mxnet
Created about 11 years ago · Last pushed over 2 years ago
Metadata Files
Readme License Code of conduct Codeowners Security

README.md


banner

Apache MXNet for Deep Learning

GitHub release (latest SemVer) GitHub stars GitHub forks GitHub contributors GitHub issues good first issue GitHub pull requests by-label GitHub license Twitter Twitter Follow

Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. MXNet is portable and lightweight, scalable to many GPUs and machines.

Apache MXNet is more than a deep learning project. It is a community on a mission of democratizing AI. It is a collection of blue prints and guidelines for building deep learning systems, and interesting insights of DL systems for hackers.

Licensed under an Apache-2.0 license.

| Branch | Build Status | |:-------:|:-------------:| | master | CentOS CPU Build Status CentOS GPU Build Status Clang Build Status
Edge Build Status Miscellaneous Build Status Sanity Build Status
Unix CPU Build Status Unix GPU Build Status Website Build Status
Windows CPU Build Status Windows GPU Build Status Documentation Status | | v1.x | CentOS CPU Build Status CentOS GPU Build Status Clang Build Status
Edge Build Status Miscellaneous Build Status Sanity Build Status
Unix CPU Build Status Unix GPU Build Status Website Build Status
Windows CPU Build Status Windows GPU Build Status Documentation Status |

Features

  • NumPy-like programming interface, and is integrated with the new, easy-to-use Gluon 2.0 interface. NumPy users can easily adopt MXNet and start in deep learning.
  • Automatic hybridization provides imperative programming with the performance of traditional symbolic programming.
  • Lightweight, memory-efficient, and portable to smart devices through native cross-compilation support on ARM, and through ecosystem projects such as TVM, TensorRT, OpenVINO.
  • Scales up to multi GPUs and distributed setting with auto parallelism through ps-lite, Horovod, and BytePS.
  • Extensible backend that supports full customization, allowing integration with custom accelerator libraries and in-house hardware without the need to maintain a fork.
  • Support for Python, Java, C++, R, Scala, Clojure, Go, Javascript, Perl, and Julia.
  • Cloud-friendly and directly compatible with AWS and Azure.

Contents

What's New

Ecosystem News

Stay Connected

| Channel | Purpose | |---|---| | Follow MXNet Development on Github | See what's going on in the MXNet project. | | MXNet Confluence Wiki for Developers | MXNet developer wiki for information related to project development, maintained by contributors and developers. To request write access, send an email to send request to the dev list . | | dev@mxnet.apache.org mailing list | The "dev list". Discussions about the development of MXNet. To subscribe, send an email to dev-subscribe@mxnet.apache.org . | | discuss.mxnet.io | Asking & answering MXNet usage questions. | | Apache Slack #mxnet Channel | Connect with MXNet and other Apache developers. To join the MXNet slack channel send request to the dev list . | | Follow MXNet on Social Media | Get updates about new features and events. |

Social Media

Keep connected with the latest MXNet news and updates.

Apache MXNet on Twitter

Contributor and user blogs about MXNet

reddit Discuss MXNet on r/mxnet

Apache MXNet YouTube channel

Apache MXNet on LinkedIn

History

MXNet emerged from a collaboration by the authors of cxxnet, minerva, and purine2. The project reflects what we have learned from the past projects. MXNet combines aspects of each of these projects to achieve flexibility, speed, and memory efficiency.

Tianqi Chen, Mu Li, Yutian Li, Min Lin, Naiyan Wang, Minjie Wang, Tianjun Xiao, Bing Xu, Chiyuan Zhang, and Zheng Zhang. MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems. In Neural Information Processing Systems, Workshop on Machine Learning Systems, 2015

Owner

  • Name: The Apache Software Foundation
  • Login: apache
  • Kind: organization

GitHub Events

Total
  • Watch event: 177
  • Pull request event: 1
  • Fork event: 33
Last Year
  • Watch event: 177
  • Pull request event: 1
  • Fork event: 33

Committers

Last synced: 11 months ago

All Time
  • Total Commits: 10,436
  • Total Committers: 929
  • Avg Commits per committer: 11.234
  • Development Distribution Score (DDS): 0.947
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Chiyuan Zhang p****d@g****m 556
Eric Junyuan Xie p****g 451
tqchen t****n@g****m 437
muli m****i@c****u 432
Bing Xu a****n@g****m 309
Sheng Zha s****a 278
Leonard Lausen l****n@a****m 237
Haibin Lin l****c@g****m 212
Yizhi Liu j****s@g****m 197
Iblis Lin i****s@h****w 163
Pedro Larroy 9****y 162
Valentin Churavy v****y@g****m 159
Hao Jin h****n@g****m 138
Aaron Markham m****a@a****m 134
Xingjian Shi x****b@u****k 127
Przemyslaw Tredak p****x@g****m 107
Yao Wang k****y@g****m 104
Kellen Sunderland k****d@g****m 101
Hu Shiwen y****n@g****m 101
sneakerkg x****7@g****m 96
Lanking l****0@l****m 89
terrytangyuan t****n@g****m 85
Marco de Abreu m****u 82
Chaitanya Prakash Bapat c****t@g****m 82
Yutian Li h****s@g****m 80
Chris Olivier c****1@g****m 79
Anirudh Subramanian a****0@g****m 79
Sandeep Krishnamurthy s****8@g****m 78
reminisce w****u@g****m 77
Jake Lee g****0@g****m 76
and 899 more...
Committer Domains (Top 20 + Academic)
intel.com: 32 qq.com: 28 163.com: 24 126.com: 12 amazon.com: 10 foxmail.com: 6 cs.washington.edu: 4 umich.edu: 3 msn.com: 3 live.cn: 3 nvidia.com: 3 apache.org: 3 dhcp-18-189-99-114.dyn.mit.edu: 2 dhcp-18-189-9-39.dyn.mit.edu: 2 sina.com: 2 fudan.edu.cn: 2 sjtu.edu.cn: 2 connect.ust.hk: 2 osu.edu: 2 dato.com: 2 my.utsa.edu: 1 students.olin.edu: 1 mail.usf.edu: 1 shanghaitech.edu.cn: 1 31-33-245.wireless.csail.mit.edu: 1 dhcp-18-189-47-161.dyn.mit.edu: 1 a3.epfl.ch: 1 cs.ccu.edu.tw: 1 eva.mpg.de: 1 cs.toronto.edu: 1 berkeley.edu: 1 pku.edu.cn: 1 buffalo.edu: 1 nyu.edu: 1 mit.edu: 1 umail.iu.edu: 1 hs.ntnu.edu.tw: 1 cs.cmu.edu: 1 mail.wbs.ac.uk: 1 mail.utoronto.ca: 1 u.northwestern.edu: 1 college.harvard.edu: 1 columbia.edu: 1 tum.de: 1 umn.edu: 1 imperial.ac.uk: 1 rice.edu: 1 stats.ox.ac.uk: 1 umbc.edu: 1 uw.edu: 1 alumni.princeton.edu: 1 bjtu.edu.cn: 1 utexas.edu: 1 vt.edu: 1 epfl.ch: 1 dhcp-18-189-113-186.dyn.mit.edu: 1 indiana.edu: 1 macreg12561.dyn.cs.washington.edu: 1 mail.ustc.edu.cn: 1 u.nus.edu: 1 stu.xmu.edu.cn: 1 e.ntu.edu.sg: 1

Issues and Pull Requests

Last synced: 10 months ago

All Time
  • Total issues: 87
  • Total pull requests: 57
  • Average time to close issues: 9 months
  • Average time to close pull requests: 6 months
  • Total issue authors: 77
  • Total pull request authors: 37
  • Average comments per issue: 5.41
  • Average comments per pull request: 3.84
  • Merged pull requests: 11
  • Bot issues: 0
  • Bot pull requests: 4
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • szha (3)
  • matteosal (3)
  • DNXie (3)
  • marcontk (2)
  • mureva (2)
  • IvyBazan (2)
  • aaronmarkham (2)
  • fhieber (1)
  • lgg (1)
  • mseth10 (1)
  • wangzbo (1)
  • Kaiser-Yang (1)
  • tdomhan (1)
  • Mukulareddy (1)
  • dongjunjundong (1)
Pull Request Authors
  • josephevans (8)
  • rbyche (4)
  • dependabot[bot] (4)
  • Yulv-git (4)
  • CinnamonJui (3)
  • access2rohit (2)
  • mwunderl (2)
  • Zha0q1 (2)
  • waytrue17 (1)
  • specter119 (1)
  • j420247 (1)
  • anko-intel (1)
  • Kh4L (1)
  • TrellixVulnTeam (1)
  • ghost (1)
Top Labels
Issue Labels
Bug (42) needs triage (22) Feature request (14) Doc (8) good first issue (5) RFC (5) Operator (4) Numpy (4) v1.x (3) C++ (3) ONNX (3) Build (2) Gluon (2) pip (2) ARM (2) Unclear Error/Doc (2) Performance (2) Website (1) Perl (1) Example (1) dependencies (1) Pending Requester Info (1) Discussion (1) CMake (1) Docker (1) Windows (1) Installation (1) v2.0 (1) Python (1)
Pull Request Labels
pr-work-in-progress (24) pr-awaiting-testing (16) pr-awaiting-review (11) dependencies (4) ruby (3) Python (1) MKLDNN (1)

Packages

  • Total packages: 1
  • Total downloads: unknown
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 7
proxy.golang.org: github.com/apache/mxnet
  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 1
Rankings
Forks count: 0.0%
Stargazers count: 0.1%
Average: 3.4%
Dependent repos count: 4.8%
Dependent packages count: 8.5%
Last synced: 10 months ago

Dependencies

.github/workflows/greetings.yml actions
  • actions/first-interaction v1 composite
.github/workflows/license_check.yml actions
  • actions/checkout v2 composite
  • apache/skywalking-eyes main composite
.github/workflows/link_check.yml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
.github/workflows/os_x_mklbuild.yml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
.github/workflows/os_x_staticbuild.yml actions
  • actions/cache v2 composite
  • actions/checkout v2 composite
  • actions/setup-python v2 composite
cd/python/docker/Dockerfile docker
  • ${BASE_IMAGE} latest build
ci/docker/docker-compose.yml docker
  • ${DOCKER_CACHE_REGISTRY}/build.android_armv7 latest
  • ${DOCKER_CACHE_REGISTRY}/build.android_armv8 latest
  • ${DOCKER_CACHE_REGISTRY}/build.armv6 latest
  • ${DOCKER_CACHE_REGISTRY}/build.armv7 latest
  • ${DOCKER_CACHE_REGISTRY}/build.armv8 latest
  • ${DOCKER_CACHE_REGISTRY}/build.centos7_cpu latest
  • ${DOCKER_CACHE_REGISTRY}/build.centos7_gpu_cu101 latest
  • ${DOCKER_CACHE_REGISTRY}/build.centos7_gpu_cu102 latest
  • ${DOCKER_CACHE_REGISTRY}/build.centos7_gpu_cu110 latest
  • ${DOCKER_CACHE_REGISTRY}/build.centos7_gpu_cu112 latest
  • ${DOCKER_CACHE_REGISTRY}/build.jetson latest
  • ${DOCKER_CACHE_REGISTRY}/build.ubuntu_cpu latest
  • ${DOCKER_CACHE_REGISTRY}/build.ubuntu_cpu_jekyll latest
  • ${DOCKER_CACHE_REGISTRY}/build.ubuntu_gpu_cu111 latest
  • ${DOCKER_CACHE_REGISTRY}/build.ubuntu_tensorrt_cu114 latest
  • ${DOCKER_CACHE_REGISTRY}/publish.test.centos7_cpu latest
  • ${DOCKER_CACHE_REGISTRY}/publish.test.centos7_gpu latest
  • ${DOCKER_CACHE_REGISTRY}/test.armv7 latest
  • ${DOCKER_CACHE_REGISTRY}/test.armv8 latest
cd/utils/requirements.txt pypi
  • PyYAML ==5.1
  • boto3 ==1.26.48
ci/requirements.txt pypi
  • docker ==3.5.0
python/mxnet/onnx/setup.py pypi
  • onnx *
docs/static_site/src/Gemfile rubygems
  • jekyll-feed ~> 0.6 development
  • jekyll-seo-tag ~> 2.6.1 development
  • jekyll ~> 4.0
  • tzinfo ~> 1.2
  • tzinfo-data >= 0
docs/static_site/src/Gemfile.lock rubygems
  • addressable 2.7.0
  • colorator 1.1.0
  • concurrent-ruby 1.1.6
  • em-websocket 0.5.1
  • eventmachine 1.2.7
  • ffi 1.12.2
  • forwardable-extended 2.6.0
  • http_parser.rb 0.6.0
  • i18n 1.8.2
  • jekyll 4.0.0
  • jekyll-feed 0.13.0
  • jekyll-sass-converter 2.1.0
  • jekyll-seo-tag 2.6.1
  • jekyll-watch 2.2.1
  • kramdown 2.1.0
  • kramdown-parser-gfm 1.1.0
  • liquid 4.0.3
  • listen 3.2.1
  • mercenary 0.3.6
  • pathutil 0.16.2
  • public_suffix 4.0.3
  • rb-fsevent 0.10.3
  • rb-inotify 0.10.1
  • rouge 3.17.0
  • safe_yaml 1.0.5
  • sassc 2.2.1
  • terminal-table 1.8.0
  • thread_safe 0.3.6
  • tzinfo 1.2.6
  • tzinfo-data 1.2019.3
  • unicode-display_width 1.7.0
  • wdm 0.1.1
docs/python_docs/themes/mx-theme/setup.py pypi
python/setup.py pypi
tools/pip/setup.py pypi