Skip to main content

MXNet is an ultra-scalable deep learning framework. This version uses CUDA-9.0.

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 platform only, and requires CUDA-9.0 for GPU acceleration. Also checkout other versions: mxnet-cu90mkl, mxnet-cu91, mxnet-cu91mkl, mxnet-cu80mkl, and mxnet-cu80, mxnet-cu75mkl, and mxnet-cu75.

To download, check CUDA download. For more instructions, check CUDA Toolkit online documentation.

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:

pip install mxnet-cu90

Project details


Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

mxnet_cu90-1.1.0.post0-py2.py3-none-win_amd64.whl (408.3 MB view details)

Uploaded Python 2Python 3Windows x86-64

mxnet_cu90-1.1.0.post0-py2.py3-none-manylinux1_x86_64.whl (327.5 MB view details)

Uploaded Python 2Python 3

File details

Details for the file mxnet_cu90-1.1.0.post0-py2.py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for mxnet_cu90-1.1.0.post0-py2.py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 3f306227b9341d1d7ab3db1cfbbd0476a92084a9067caff9f8ca6ece5a9d938e
MD5 a9eb3f011b7aea14a92d0cd0c9aadfb6
BLAKE2b-256 397d718672fd43a5f18ce7ee80d0e0fec7ea257fbe2b5c06d8b6b67ad57563f6

See more details on using hashes here.

File details

Details for the file mxnet_cu90-1.1.0.post0-py2.py3-none-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mxnet_cu90-1.1.0.post0-py2.py3-none-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 83bafa2a0a2697460638cd1ca16ff565cd3976f41685bbcdc2f1abde65a71343
MD5 c80f7f4e266ffc9eb17608eaa6e49dba
BLAKE2b-256 a0dc3198a0277d2321474ebd0b06dba6baf44484b00c253f4ead98763a21f634

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page