Skip to main content

Apache MXNet (Incubating) Python Package

Apache 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, create an issue by clicking here. Prerequisites

This package supports Linux and Windows platforms. You may also want to check:

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

To use this package on Linux you need the libquadmath.so.0 shared library. On Debian based systems, including Ubuntu, run sudo apt install libquadmath0 to install the shared library. On RHEL based systems, including CentOS, run sudo yum install libquadmath to install the shared library. As libquadmath.so.0 is a GPL library and MXNet part of the Apache Software Foundation, MXNet must not redistribute libquadmath.so.0 as part of the Pypi package and users must manually install it.

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-cu111

Release files for mxnet-cu111 1.9.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for mxnet-cu111 1.9.1
File Interpreter ABI Platform
mxnet_cu111-1.9.1-py3-none-manylinux2014_x86_64.whl Python 3 none Linux glibc 2.17+ x86-64 Details

Release files / mxnet_cu111-1.9.1-py3-none-manylinux2014_x86_64.whl

Download URL mxnet_cu111-1.9.1-py3-none-manylinux2014_x86_64.whl
Size 485.2 MB
Tags Linux glibc 2.17+ x86-64 Python 3
SHA-256 checksum
How to use checksums
893a794c63276b6cf0dfb31bf77ad0057723bfca1dfb28c1c86497c4c819414e
BLAKE2b-256 checksum
How to use checksums
03484191e16f915701f960fd285d88795ce5cfc817b94c7156dc097d9ea22e36
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.7.6

Release history Release notifications | RSS feed

This release

1.9.1 This release

1 release file

1.0.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page