May 2024
Intermediate
252 pages
5h 31m
Chinese
Content preview from Ray 分布式机器学习：利用Ray 进行大模型的数据处理、训练、推理和部署
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3
前言
分布式计算是当下非常热门的技术。回顾计算的发展历程，不禁让人感叹越来
越多的公司将工作负载
编辑注
分布在计算机集群上。人们开发出了高效的计算方法
来做到这一点，与此同时，扩展计算也变得越来越必要。这是因为虽然单台计算
机的速度不断提高，但人们对大规模计算的需求仍然超出了单台机器的算力。
扩展计算不仅是必要的，而且极具挑战性，而
Ray
的出现大大简化了开发工
作量。
Ray
使普通开发者也能轻松进行分布式计算，并且可以毫不费力地将
Python
脚本扩展到多个节点。
Ray
擅长处理数据密集型和计算密集型的计算
任务（如数据预处理和模型训练），非常适合需要扩展的机器学习（
Machine
Learning
，
ML
）计算任务。虽然在当前的技术环境下不借助
Ray
也可以扩展这
两种类型的任务，但开发者可能需要为每种类型的任务使用不同的
API
和分布
式系统。而且，管理多个分布式系统可能会导致混乱和低效。
1
Ray 2.0
于
2022
年
8
月发布，新增了
Ray AI Runtime
（
AIR
）功能，进一步提升
了
Ray
在复杂机器学习计算任务上的能力。
AIR
是由库和工具组成的集合，可
在单个分布式系统中轻松构建和部署端到端的机器学习应用程序。借助
AIR
，
即使处理最复杂的工作流，也可以将其表示为单个
Python
脚本。这意味着用户
可以预先在本地运行程序，从而大大提升调试和开发的效率。
因为可以使用持续增强的
Ray
机器学习库和第三方集成，所以数据科学家从
Ray
受益良多。
Ray AIR
能帮助用户快速实现想法原型，并更从容地从开发过渡
到生产环境 ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.