Английская Википедия:Apache MXNet

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Apache MXNet is an open-source deep learning software framework that trains and deploys deep neural networks. It is scalable, allows fast model training, and supports a flexible programming model and multiple programming languages (including C++, Python, Java, Julia, MATLAB, JavaScript, Go, R, Scala, Perl, and Wolfram Language). The MXNet library is portable and can scale to multiple GPUs[1] and machines. It was co-developed by Carlos Guestrin at the University of Washington (along with GraphLab).[2]

As of September 2023, it is no longer actively developed.[3]

Features

Apache MXNet is a scalable deep learning framework that supports deep learning models, such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs).

Scalability

MXNet can be distributed on dynamic cloud infrastructure using a distributed parameter server (based on research at Carnegie Mellon University, Baidu, and Google[4]). With multiple GPUs or CPUs, the framework approaches linear scale.

Flexibility

MXNet supports both imperative and symbolic programming. The framework allows developers to track, debug, save checkpoints, modify hyperparameters, and perform early stopping.

Multiple languages

MXNet supports Python, R, Scala, Clojure, Julia, Perl, MATLAB, and JavaScript for front-end development and C++ for back-end optimization.

Portability

Supports deployment of a trained model to low-end devices for inference, such as mobile devices (using Amalgamation[5]), Internet of things devices (using AWS Greengrass), serverless computing (using AWS Lambda), or containers. These low-end environments can have only weaker CPU or limited memory (RAM) and should be able to use the models that were trained on a higher-level environment (GPU-based cluster, for example)

Cloud Support

MXNet is supported by public cloud providers including Amazon Web Services (AWS)[6] and Microsoft Azure.[7] Amazon has chosen MXNet as its deep learning framework of choice at AWS.[8][9] Currently, MXNet is supported by Intel, Baidu, Microsoft, Wolfram Research, and research institutions such as Carnegie Mellon, MIT, the University of Washington, and the Hong Kong University of Science and Technology.[10]

See also

References

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Шаблон:Deep Learning Software Шаблон:Apache Software Foundation