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 and Windows platforms. You may also want to check: - mxnet-cu92 with CUDA-9.2 support. - mxnet-cu92mkl with CUDA-9.2 support and MKLDNN support. - mxnet-cu91 with CUDA-9.1 support. - mxnet-cu91mkl with CUDA-9.1 support and MKLDNN support. - mxnet-cu90mkl with CUDA-9.0 support and MKLDNN support. - mxnet-cu80 with CUDA-8.0 support. - mxnet-cu80mkl with CUDA-8.0 support and MKLDNN support. - mxnet-cu75 with CUDA-7.5 support. - mxnet-cu75mkl with CUDA-7.5 support and MKLDNN support. - mxnet-mkl with MKLDNN support. - mxnet.

To download CUDA, 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_cu90-1.2.0-py2.py3-none-win_amd64.whl (457.0 MB view details)

Uploaded Python 2Python 3Windows x86-64

mxnet_cu90-1.2.0-py2.py3-none-manylinux1_x86_64.whl (346.9 MB view details)

Uploaded Python 2Python 3

File details

Details for the file mxnet_cu90-1.2.0-py2.py3-none-win_amd64.whl.

File metadata

File hashes

Hashes for mxnet_cu90-1.2.0-py2.py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 a5eab9801f014a69d46cfcfdb7cdc41fc51618202e1f9d0796347c0b0b48bc37
MD5 602955d4b38c4c6cedb505a88284f899
BLAKE2b-256 72a89226bd6913b7ba4657a218b9a252b60de98938dd41e8517a0b4ab4291203

See more details on using hashes here.

File details

Details for the file mxnet_cu90-1.2.0-py2.py3-none-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for mxnet_cu90-1.2.0-py2.py3-none-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 cb7c6a4518c10c4946a66e7ac2e4b8c23fd7271e73edafad33d58a4fc9e34224
MD5 4c93ccf1e64a6b4802b808c088a8522b
BLAKE2b-256 87654bc06b46aac2451565359415f430154469304a22b5ef8d8e3ed40cfb7df1

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