mxnet

MXNet is an ultra-scalable deep learning framework. This version uses openblas.

Project description

MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix the flavours of deep learning programs together to maximize the efficiency and your productivity.

For feature requests on the PyPI package, suggestions, and issue reports, click here. Prerequisites ———— This package supports Linux, Mac OSX and Windows platforms. If you have GPU, you may want to check: mxnet-cu90, mxnet-cu90mkl, mxnet-cu80 and mxnet-cu80mkl with CUDA-8.0 support, or mxnet-cu75 and mxnet-cu75mkl with CUDA-7.5 support. If you are using Linux without GPU, you may want to check mxnet-mkl with MKL support.

To install for other platforms (e.g. Windows, Raspberry Pi/ARM) or other versions, check Installing MXNet for instructions on building from source.

Installation

To install, use:

pip install mxnet

Project details

Release history Release notifications | RSS feed

2.0.0a0 pre-release

Mar 31, 2021

1.8.0.post0

Mar 30, 2021

1.8.0

Mar 21, 2021

1.7.0.post2

Feb 7, 2021

1.7.0.post1

Aug 28, 2020

1.6.0

Feb 21, 2020

1.5.1.post0

Oct 1, 2019

1.5.1

Sep 30, 2019

1.5.0

Jul 19, 2019

1.4.1

May 14, 2019

1.4.0.post0

Mar 8, 2019

1.4.0

Feb 28, 2019

1.3.1

Nov 27, 2018

1.3.0.post0

Sep 14, 2018

1.3.0

Sep 12, 2018

1.2.1.post1

Jul 31, 2018

1.2.1.post0

Jul 30, 2018

1.2.1

Jul 17, 2018

1.2.0

May 21, 2018

1.1.0.post0

Apr 7, 2018

1.1.0

Feb 20, 2018

1.0.0.post4

Jan 14, 2018

1.0.0.post3

Jan 6, 2018

This version

1.0.0.post2

Dec 23, 2017

1.0.0.post1

Dec 8, 2017

1.0.0.post0

Dec 5, 2017

1.0.0

Dec 4, 2017

0.12.1

Nov 16, 2017

0.12.0

Oct 30, 2017

0.11.0

Aug 20, 2017

0.10.0.post2

Jul 18, 2017

0.10.0

May 26, 2017

0.9.5.post2

May 24, 2017

0.9.5.post1

May 12, 2017

0.9.5

May 2, 2017

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for mxnet, version 1.0.0.post2
Filename, size	File type	Python version	Upload date	Hashes
Filename, size mxnet-1.0.0.post2-cp27-cp27m-macosx_10_10_x86_64.whl (13.9 MB)	File type Wheel	Python version cp27	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp27-cp27m-macosx_10_11_x86_64.whl (12.4 MB)	File type Wheel	Python version cp27	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp27-cp27m-macosx_10_12_x86_64.whl (11.7 MB)	File type Wheel	Python version cp27	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp34-cp34m-macosx_10_10_x86_64.whl (13.9 MB)	File type Wheel	Python version cp34	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp34-cp34m-macosx_10_11_x86_64.whl (12.4 MB)	File type Wheel	Python version cp34	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp34-cp34m-macosx_10_12_x86_64.whl (11.7 MB)	File type Wheel	Python version cp34	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp35-cp35m-macosx_10_10_x86_64.whl (13.9 MB)	File type Wheel	Python version cp35	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp35-cp35m-macosx_10_11_x86_64.whl (12.4 MB)	File type Wheel	Python version cp35	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp35-cp35m-macosx_10_12_x86_64.whl (11.7 MB)	File type Wheel	Python version cp35	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp36-cp36m-macosx_10_10_x86_64.whl (13.9 MB)	File type Wheel	Python version cp36	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp36-cp36m-macosx_10_11_x86_64.whl (12.4 MB)	File type Wheel	Python version cp36	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-cp36-cp36m-macosx_10_12_x86_64.whl (11.7 MB)	File type Wheel	Python version cp36	Upload date Dec 23, 2017	Hashes View
Filename, size mxnet-1.0.0.post2-py2.py3-none-manylinux1_x86_64.whl (27.4 MB)	File type Wheel	Python version py2.py3	Upload date Dec 23, 2017	Hashes View

Hashes for mxnet-1.0.0.post2-cp27-cp27m-macosx_10_10_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp27-cp27m-macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`9b5b6a9295543c1c4f79e64834b74a1576ff8543aad98859cab85bbd9fe8b9f3`
MD5	`f73d363f12e646c57219dc90a13b983d`
BLAKE2-256	`593691f8ef5e1463200ed478764a6ebbe81581ba6911a995154e4ea481785118`

Hashes for mxnet-1.0.0.post2-cp27-cp27m-macosx_10_11_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp27-cp27m-macosx_10_11_x86_64.whl
Algorithm	Hash digest
SHA256	`fe520f132a812ed7fd895e556a739f31b16de909ffa67ee5a0977e2778fa1394`
MD5	`d8839246c02e4e54a6cb0425e0d8ec08`
BLAKE2-256	`0de202f510b1d9b26afffdbd0ef9db3f128c64242f70338c5a5358736938e409`

Hashes for mxnet-1.0.0.post2-cp27-cp27m-macosx_10_12_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp27-cp27m-macosx_10_12_x86_64.whl
Algorithm	Hash digest
SHA256	`5cf26a4dc5c50855f554d5747a452a69f44a67d2819a8e3f1c47adab8dac7ba4`
MD5	`32a46f707e3e075672282ac0f4c77fb4`
BLAKE2-256	`d3e119a817e44e0065a50c5ecf7f52c18fa4ed119d687314bd1e96c012b2fc28`

Hashes for mxnet-1.0.0.post2-cp34-cp34m-macosx_10_10_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp34-cp34m-macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`8057f12112cd40d522bd910b34a9045af16c72cc2e23e2fe8ae0cd2f795ef044`
MD5	`49ccb914c2161189297c275bf82b3c6c`
BLAKE2-256	`6453ed1b587ee5ec2a010abd5688da9a12da9be0e9eda5516bd92ed04f900fce`

Hashes for mxnet-1.0.0.post2-cp34-cp34m-macosx_10_11_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp34-cp34m-macosx_10_11_x86_64.whl
Algorithm	Hash digest
SHA256	`b10a478a39b25101f51f9fb53eadaa88b48e6f3e35a4ecb4bc4b9b396e42d4ed`
MD5	`ba2888742edb9cef4f9a1bb8cd5069bd`
BLAKE2-256	`f61be0904cdb6bec6a547f30153c969283fbecb83e5767ab9b4eeffdfffabf44`

Hashes for mxnet-1.0.0.post2-cp34-cp34m-macosx_10_12_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp34-cp34m-macosx_10_12_x86_64.whl
Algorithm	Hash digest
SHA256	`7e5ce86ba232e39882f62278696cf0889027d75b8b9a08eadf61e1810ea7c430`
MD5	`5865e1b5a2b059e5ae41f1ce6fe3c394`
BLAKE2-256	`61174b45920045469637ebfbd1bcc84e5e1eeac42c8248f92371343283dd8a62`

Hashes for mxnet-1.0.0.post2-cp35-cp35m-macosx_10_10_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp35-cp35m-macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`99dcfa54d94e279a7138445d72e7eb8294d3b4454927220f51d5e0ba2a8f3205`
MD5	`17b44ebf02cf5693ece0a67aec28e80d`
BLAKE2-256	`87b3029e530c0bf8cb87018bfd83de194e62187026917c20ec07c8aa25def9d0`

Hashes for mxnet-1.0.0.post2-cp35-cp35m-macosx_10_11_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp35-cp35m-macosx_10_11_x86_64.whl
Algorithm	Hash digest
SHA256	`c3c23f3de2dffdad60c80884ca64880ec4be9b745615b62c86d89f49e3d7916e`
MD5	`c0c781454147eed40745bab37e5950df`
BLAKE2-256	`f58e2f0c174a944ac4760fc5a831cf541b0148ab41d9cdb591b14b162abf3ff6`

Hashes for mxnet-1.0.0.post2-cp35-cp35m-macosx_10_12_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp35-cp35m-macosx_10_12_x86_64.whl
Algorithm	Hash digest
SHA256	`740b891053643dc7858bc3361912da8729fec1c3b6c2801daa0c76b7fe812c89`
MD5	`6aac6da10aed0de144bee9967c8cc482`
BLAKE2-256	`0737c380ce76f2554ca1f75318143e45b4f4f47c2bd1bbf25e883dc9ca6e60b7`

Hashes for mxnet-1.0.0.post2-cp36-cp36m-macosx_10_10_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp36-cp36m-macosx_10_10_x86_64.whl
Algorithm	Hash digest
SHA256	`d6f2756b0c76fcf3ac23df63f3d8d46f2af92f4d19fccc95457b846b32623f9a`
MD5	`85359b25c43d5e5fcaace4ab128c605f`
BLAKE2-256	`0b646f42e5039df3ac3e66afa6267d5ffcb42d55f9ec37fea9a4fc3fc700e53b`

Hashes for mxnet-1.0.0.post2-cp36-cp36m-macosx_10_11_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp36-cp36m-macosx_10_11_x86_64.whl
Algorithm	Hash digest
SHA256	`184ea0ec539b6bc6c38e3576d8cfaa1aefb3c5429ac5ab842aa5c896a95a6ca0`
MD5	`0e32786d0fb5139a9a145872ce919d22`
BLAKE2-256	`b645610df6c71d9eaa6bdbfc862a38f98bbd90fccc1c080c72b5d1a45a12d95f`

Hashes for mxnet-1.0.0.post2-cp36-cp36m-macosx_10_12_x86_64.whl

Hashes for mxnet-1.0.0.post2-cp36-cp36m-macosx_10_12_x86_64.whl
Algorithm	Hash digest
SHA256	`4cad73ffbb22187ff74f12a67e13eca2ffe76cbaf0200a6638932bc49952fbdd`
MD5	`d78ca4d67ba03a078bf989b8e4fde767`
BLAKE2-256	`1d5436cc67ec9f8f3d5cc6a240d2e4479619edac06b092e6a2de791dedea4fb3`

Hashes for mxnet-1.0.0.post2-py2.py3-none-manylinux1_x86_64.whl

Hashes for mxnet-1.0.0.post2-py2.py3-none-manylinux1_x86_64.whl
Algorithm	Hash digest
SHA256	`dedf0bea157712e44e16a2d95a8a1560e5ac24d7cbc52b72322f8415b90629af`
MD5	`6d741af971ad4703da0c8eefd2954d96`
BLAKE2-256	`a42c8587e51185a1116fde1791df38ed4d810754a3d82fa5705ad1e333c7717f`