Skip to main content

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: - mxnet-cu101 with CUDA-10.1 support. - mxnet-cu100 with CUDA-10.0 support. - mxnet-cu100mkl with CUDA-10.0 support and MKLDNN support. - 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-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 of CUDA, check Installing MXNet for instructions on building from source.

Installation

To install:

pip install mxnet-cu101mkl

Release files for mxnet-cu101mkl 1.5.1.post0

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-cu101mkl 1.5.1.post0
File Interpreter ABI Platform
mxnet_cu101mkl-1.5.1.post0-py2.py3-none-manylinux1_x86_64.whl Python 3, Python 2 none Linux glibc 2.5+ x86-64 Details

Release files / mxnet_cu101mkl-1.5.1.post0-py2.py3-none-manylinux1_x86_64.whl

Download URL mxnet_cu101mkl-1.5.1.post0-py2.py3-none-manylinux1_x86_64.whl
Size 587.7 MB
Tags Linux glibc 2.5+ x86-64 Python 2 Python 3
SHA-256 checksum
How to use checksums
bbc53af68b81bba6de5ee9ef1bc7831faa0d3b683adc980311f44bc6f121b3cf
BLAKE2b-256 checksum
How to use checksums
77aa3bab75904a39935cc71b68bec100f51c9ff061d0244bcd68037a6d57aba4
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/1.15.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/36.2.0 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/2.7.6

Release history Release notifications | RSS feed

This release

1.5.1.post0 This release

1 release file

1.5.1

1 release file

1.5.0

2 release files

1.4.1

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