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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201
第 10 章
Ray AIR 入门
从第
1
章介绍有关
Ray AIR
的内容再到本章，我们已经学习了很多内容。除了
Ray
集群和
Ray Core API
的基础知识，你已经对
Ray
的所有高级库有了很好的
理解，这些库可用于
AI
任务，包括
Ray RLlib
、
Tune
、
Train
、
Dataset
和
Serve
。
我们之前没有深入讨论
Ray AIR
，主要是因为，如果了解了以上这些
AIR
的构
建模块，就更容易理解
AIR
的概念并计算复杂示例。
在本章中，我们将介绍
Ray AIR
的核心概念以及如何使用它构建和部署常见工
作流。我们将利用
Ray
的数据科学库创建
AIR
应用程序，还将介绍何时以及为
什么使用
AIR
，并简要介绍其技术基础。关于
AIR
与其他系统的关系，如集成
和关键差异，将在第
11
章讨论，第
11
章还将讨论与
AIR
相关的
Ray
生态。
10.1
为什么使用
AIR
过去几年，使用
Ray
运行机器学习任务持续演进。
Ray RLlib
和
Tune
是基于
Ray Core
创建的第一个库。随后不久，出现了
Ray Train
、
Serve
等组件，最近
又新增了
Ray Dataset
。经过与机器学习社区的积极讨论并收集反馈结果，最终
将
Ray AIR
作为所有其他
Ray
机器学习库的总称。作为具有良好
GPU
支持和支
持复杂机器学习任务（
Ray
执行器）的
Python
原生工具，
Ray
自然成为构建类
似
AIR
的运行时的理想选择。
Ray AIR
是一个用于处理机器学习任务的统一工具包，提供了许多第三方集成，
...
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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.