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This project forked from microsoft/deepspeed

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DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Home Page: https://www.deepspeed.ai/

License: Apache License 2.0

Shell 0.55% C++ 10.42% Python 78.51% C 0.15% Cuda 10.17% Batchfile 0.01% Dockerfile 0.18%

deepspeed's Introduction

Distributed Machine Learning Common Codebase

Build Status Documentation Status GitHub license

DMLC-Core is the backbone library to support all DMLC projects, offers the bricks to build efficient and scalable distributed machine learning libraries.

Developer Channel Join the chat at https://gitter.im/dmlc/dmlc-core

What's New

Contents

Known Issues

  • RecordIO format is not portable across different processor endians. So it is not possible to save RecordIO file on a x86 machine and then load it on a SPARC machine, because x86 is little endian while SPARC is big endian.

Contributing

Contributing to dmlc-core is welcomed! dmlc-core follows google's C style guide. If you are interested in contributing, take a look at feature wishlist and open a new issue if you like to add something.

  • DMLC-Core uses C++11 standard. Ensure that your C++ compiler supports C++11.
  • Try to introduce minimum dependency when possible

CheckList before submit code

  • Type make lint and fix all the style problems.
  • Type make doc and fix all the warnings.

NOTE

deps:

libcurl4-openssl-dev

deepspeed's People

Contributors

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