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【首席架构师推荐】深度学习软件比较

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Wikipedia Comparison of deep-learning software

下表比较了用于深度学习的著名软件框架、库和计算机程序。

Deep-learning software by name

Software

Initial Release

Software license[a]

Open source

Platform

Written in

Interface

OpenMP 

support

OpenCL

 support

CUDA support

Automatic differentiation[1]

Has pretrained models

Recurrent nets

Convolutional nets

RBM/DBNs

Parallel execution (multi node)

Actively Developed
BigDL 2016 Apache 2.0 Yes

Apache

Spark

 Scala

Scala,

Python

     No   Yes Yes Yes      
Caffe 2013 BSD Yes

Linux, 

macOS, 

Windows[2]

 C++

Python, 

MATLAB, 

C++

 Yes

Under

development[3]

 Yes Yes Yes[4] Yes Yes No ?  
Chainer 2015 BSD Yes

Linux, 

macOS

 Python Python No No Yes Yes Yes Yes Yes No Yes Yes
Deeplearning4j 2014 Apache 2.0 Yes

Linux, 

macOS, 

Windows,

 Android 

(Cross-

platform)

C++, 

Java

Java, 

Scala, 

Clojure, 

Python 

(Keras), 

Kotlin

 Yes No[5] Yes[6][7] Computational Graph Yes[8] Yes Yes Yes Yes[9]  
Dlib 2002 Boost Software License Yes

Cross-

Platform

 C++ C++ Yes No Yes Yes Yes No Yes Yes Yes  
Intel Data Analytics Acceleration Library 2015 Apache License 2.0 Yes

Linux, 

macOS, 

Windows 

on Intel 

CPU[10]

C++, 

Python, 

Java

C++, 

Python, 

Java[10]

 Yes No No Yes No   Yes   Yes  
Intel Math Kernel Library   Proprietary No

Linux,

 macOS, 

Windows 

on Intel 

CPU[11]

   C[12] Yes[13] No No Yes No Yes[14] Yes[14]   No  
Keras 2015 MIT license Yes

Linux, 

macOS, 

Windows

 Python

Python, 

R

 Only if using Theano as backend

Can use

Theano,

Tensorflow

or PlaidML

as backends

 Yes Yes Yes[15] Yes Yes No[16] Yes[17] Yes
MATLAB + Deep Learning Toolbox   Proprietary No

Linux,

 macOS, 

Windows

C, 

C++, 

Java, 

MATLAB

 MATLAB No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder[18] No Yes[19][20] Yes[19] Yes[19] No With Parallel Computing Toolbox[21] Yes
Microsoft Cognitive Toolkit (CNTK) 2016 MIT license[22] Yes

Windows, 

Linux[23] 

(macOS 

via Docker

on roadmap)

 C++

Python

(Keras), 

C++,

 Command

line,[24] 

BrainScript[25] 

(.NET on

roadmap[26])

 Yes[27] No Yes Yes Yes[28] Yes[29] Yes[29] No[30] Yes[31] No[32]
Apache MXNet 2015 Apache 2.0 Yes

Linux, 

macOS, 

Windows,[33][34] 

AWS, 

Android,[35] 

iOS, 

JavaScript[36]

Small

 C++ 

core

library

C++, 

Python, 

Julia, 

Matlab, 

JavaScript,

 Go, 

R, 

Scala, 

Perl

 Yes

On

roadmap[37]

 Yes Yes[38] Yes[39] Yes Yes Yes Yes[40] Yes
Neural Designer   Proprietary No

Linux, 

macOS, 

Windows

 C++

Graphical

user

interface

 Yes No No ? ? No No No ?  
OpenNN 2003 GNU LGPL Yes

Cross

-platform

 C++ C++ Yes No Yes ? ? No No No ?  
PlaidML 2017 AGPL Yes

Linux, 

macOS, 

Windows

Python,

 C++, 

OpenCL

Python,

 C++

 ?

Some

OpenCL

ICDs are

not recognized

 No Yes Yes Yes Yes   Yes Yes
PyTorch 2016 BSD Yes

Linux,

 macOS, 

Windows

Python,

 C, 

C++, 

CUDA

Python,

 C++

 Yes

Via separately maintained

package

[41]

[42][42]

 Yes Yes Yes Yes Yes   Yes Yes
Apache SINGA 2015 Apache 2.0 Yes

Linux, 

macOS,

 Windows

 C++

Python, 

C++, 

Java

 No

Supported

in V1.0

 Yes ? Yes Yes Yes Yes Yes  
TensorFlow 2015 Apache 2.0 Yes

Linux, 

macOS, 

Windows,[43] 

Android

C++,

 Python, 

CUDA

Python 

(Keras), 

C/C++, 

Java, Go, 

JavaScript,

 R,[44] 

Julia, 

Swift

 No

On roadmap

[45] but

already with

 SYCL[46] 

support

 Yes Yes[47] Yes[48] Yes Yes Yes Yes Yes
Theano 2007 BSD Yes

Cross

-platform

 Python

Python 

(Keras)

 Yes

Under develo

pment[49]

 Yes Yes[50][51] Through Lasagne's model zoo[52] Yes Yes Yes Yes[53] No
Torch 2002 BSD Yes

Linux, 

macOS, 

Windows,[54] 

Android,[55] 

iOS

 C, Lua

Lua, 

LuaJIT,

[56] C,

utility

library for

 C++/

OpenCL[57]

 Yes

Third

party

implemen

tations[58][59]

 Yes[60][61] Through Twitter's Autograd[62] Yes[63] Yes Yes Yes Yes[54] No
Wolfram Mathematica 1988 Proprietary No

Windows,

 macOS, 

Linux, 

Cloud computing

C++, 

Wolfram

Language, 

CUDA

 Wolfram Language Yes No Yes Yes Yes[64] Yes Yes Yes Yes[65] Yes
  1. ^ Licenses here are a summary, and are not taken to be complete statements of the licenses. Some libraries may use other libraries internally under different licenses

Related software

See also

 

本文：https://pub.intelligentx.net/wikipedia-comparison-deep-learning-software

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本文地址
https://architect.pub/wikipedia-comparison-deep-learning-software
发布日期
星期日, 九月 22, 2019 - 19:26
最后修改
星期三, 九月 6, 2023 - 14:58

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