apss

v0.3.0

一种基于神经网络和启发式策略的深度学习模型分布式训练切分(3D parallelism)快速策略搜索算法 For more information about how to use this package see README

Latest version published 1 year ago

License: Unknown

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Package Health Score

33 / 100

security
Security review needed
popularity
Limited
maintenance
Inactive
community
Limited

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Popularity

Limited

GitHub Stars: 0
Forks: 0
Contributors: 4

Direct Usage Popularity

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Security

Security review needed

Security and license risk for latest version

Release Date: Nov 22, 2023
Direct Vulnerabilities: 0
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Indirect Vulnerabilities: 0
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License Risk: 0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

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Security Policy

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Maintenance

Inactive

Commit Frequency

Open Issues: 0
Open PR: 0
Last Release: 1 year ago
Last Commit: 5 months ago

Further analysis of the maintenance status of apss 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 apss 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.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Limited

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 4
Funding: No

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Package

Python Versions Compatibility: >=3.7

Age: 1 year
Latest Release: 1 year ago
Dependencies: 4 Direct / 13 Total
Versions: 3
Maintainers: 1
Wheels: OS Independent

Readme

APSS(for Training): Automatically Distributed Deep Learning Parallelism Strategies Search by Self Play

APSS 是一种基于神经网络和启发式策略的深度学习模型分布式训练切分(3D parallelism)快速策略搜索算法，它结合启发式策略和训练集群环境初步生成候选策略，然后通过深度管道策略网络（DPSN）为每个候选策略提供详细的pipeline划分，采用自我对弈的对比强化学习（CRLSP）进行离线训练，无需实际数据收集和后续应用中的微调。此仓库我们使用Mindspore进行实现。

Context

Installation

Requirements:

Python >= 3.7
Mindspore >= 2.1.1

Method 1: With pip

pip install apss

Method 2: From source

git clone https://github.com/Cheny1m/APSS
cd APSS
pip install -e .

Usage and Examples

一步执行训练

python -m apss.training.apss_run --graph_size 8 --num_split 3 --rebuild_data

graph_size , num_split 分别代表了问题的层数大小和需要执行pipeline划分的数量，两个命令行参数共同描述了所训练问题的大小，可根据需求动态调整。
rebuild_data 表示是否在执行训练前，从Data Synthesizer中生成训练数据，默认建议开启。如果需要从.ckpt中接续训练或无需改变之前生成的训练数据直接禁用--rebuild_data参数即可。训练数据可在/data目录下找到。
已经完成过执行训练后，.ckpt保存在/output文件夹下，日志保存在/log文件夹下，可以通过tensorboard_logger在浏览器中实时查看训练过程及其数据。

How It Works

The pipeline of APSS.

apss dependencies

mindspore numpy tensorboard-logger tqdm

FAQs

What is apss?

一种基于神经网络和启发式策略的深度学习模型分布式训练切分(3D parallelism)快速策略搜索算法. Visit Snyk Advisor to see a full health score report for apss, including popularity, security, maintenance & community analysis.

Is apss popular?

The python package apss receives a total of 71 weekly downloads. As such, apss popularity was classified as limited. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is apss well maintained?

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

Is apss safe to use?

While scanning the latest version of apss, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 25 November-2024, at 18:52 (UTC).

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