Skip to main content

MXNet is an ultra-scalable deep learning framework. This version uses CUDA-9.2.

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-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-cu90 with CUDA-9.0 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-cu92

Release history Release notifications

Download files

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

Filename, size & hash SHA256 hash help File type Python version Upload date
mxnet_cu92-1.3.1b20181027-py2.py3-none-manylinux1_x86_64.whl (444.6 MB) Copy SHA256 hash SHA256 Wheel py2.py3

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page