mxnet

v1.9.1

Apache MXNet is an ultra-scalable deep learning framework. This version uses openblas and MKLDNN. For more information about how to use this package see README

Latest version published 2 years ago

License: Apache-2.0

PyPI

GitHub

Package Health Score

55 / 100

security
Security review needed
popularity
Popular
maintenance
Inactive
community
Sustainable

Explore Similar Packages

Popularity

Popular

Total Weekly Downloads (76,187)

GitHub Stars: 20.65K
Forks: 6.89K
Contributors: -

Direct Usage Popularity

The PyPI package mxnet receives a total of 76,187 downloads a week. As such, we scored mxnet popularity level to be Popular.

Based on project statistics from the GitHub repository for the PyPI package mxnet, we found that it has been starred 20,651 times.

The download numbers shown are the average weekly downloads from the last 6 weeks.

Security

Security review needed

Security and license risk for latest version

Release Date: May 17, 2022
Direct Vulnerabilities: 0
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0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
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0
M
3
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License Risk: 0
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1
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0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

Apache-2.0

Security Policy

Yes

A security vulnerability was detected in an indirect dependency that is added to your project when the latest version of mxnet is installed.

We highly advise you to review these security issues.

You can connect your project's repository to Snyk to stay up to date on security alerts and receive automatic fix pull requests.

Fix it in your project with Snyk!

Maintenance

Inactive

archived

Commit Frequency

Open Issues: 1.8K
Open PR: 206
Last Release: 2 years ago
Last Commit: 11 months ago

Further analysis of the maintenance status of mxnet based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Inactive.

An important project maintenance signal to consider for mxnet is that it hasn't seen any new versions released to PyPI in the past 12 months, and could be considered as a discontinued project, or that which receives low attention from its maintainers.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: Yes
Contributors: 0
Funding: No

This project has seen only 10 or less contributors.

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Package

Python Versions Compatibility: ==3.5.*, ==3.6.*, ==3.7.*, ==3.8.*

Age: 7 years
Latest Release: 2 years ago
Dependencies: 3 Direct / 7 Total
Versions: 38
Maintainers: 3
Wheels: Linux, macOS

Not sure how to use mxnet?

To help you get started, we've collected the most common ways that mxnet is being used within popular public projects.

awslabs / autogluon / autogluon / task / object_detection / pipeline.py View on Github

lr_decay_epoch = list(range(args.lr_decay_period, args.epochs, args.lr_decay_period))
    else:
        lr_decay_epoch = [int(i) for i in args.lr_decay_epoch.split(',')]
    lr_decay_epoch = [e - args.warmup_epochs for e in lr_decay_epoch]
    num_batches = args.num_samples // args.batch_size
    lr_scheduler = LRSequential([
        LRScheduler('linear', base_lr=0, target_lr=args.lr,
                    nepochs=args.warmup_epochs, iters_per_epoch=num_batches),
        LRScheduler(args.lr_mode, base_lr=args.lr,
                    nepochs=args.epochs - args.warmup_epochs,
                    iters_per_epoch=num_batches,
                    step_epoch=lr_decay_epoch,
                    step_factor=args.lr_decay, power=2),
    ])

    trainer = gluon.Trainer(
        net.collect_params(), 'sgd',
        {'wd': args.wd, 'momentum': args.momentum, 'lr_scheduler': lr_scheduler},
        kvstore='local')

    # targets
    sigmoid_ce = gluon.loss.SigmoidBinaryCrossEntropyLoss(from_sigmoid=False)
    l1_loss = gluon.loss.L1Loss()

    # metrics
    obj_metrics = mx.metric.Loss('ObjLoss')
    center_metrics = mx.metric.Loss('BoxCenterLoss')
    scale_metrics = mx.metric.Loss('BoxScaleLoss')
    cls_metrics = mx.metric.Loss('ClassLoss')

    # set up logger
    logging.basicConfig()

View more ways to use mxnet

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, Mac OSX, and Windows platforms. You may also want to check:

mxnet-cu112 with CUDA-11.2 support.
mxnet-cu110 with CUDA-11.0 support.
mxnet-cu102 with CUDA-10.2 support.
mxnet-cu101 with CUDA-10.1 support.
mxnet-cu100 with CUDA-10.0 support.
mxnet-native CPU variant without MKLDNN.

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, use:

pip install mxnet

mxnet dependencies

graphviz numpy requests

FAQs

What is mxnet?

Apache MXNet is an ultra-scalable deep learning framework. This version uses openblas and MKLDNN. Visit Snyk Advisor to see a full health score report for mxnet, including popularity, security, maintenance & community analysis.

Is mxnet popular?

The python package mxnet receives a total of 76,187 weekly downloads. As such, mxnet popularity was classified as a popular. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is mxnet well maintained?

We found indications that mxnet is an Inactive project. See the full package health analysis to learn more about the package maintenance status.

Is mxnet safe to use?

While scanning the latest version of mxnet, we found that a security review is needed. A total of 3 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 11 December-2023, at 13:14 (UTC).

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