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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212
|
第
10
章
个分布式系统就完成了所有复杂工作。实际上，你可以使用此示例脚本，并将
其扩展到使用
CPU
进行预处理和使用
GPU
进行训练的大型集群，并通过修改
缩放配置中的参数和脚本中的类似选项单独地配置部署模块。使用
Ray
大大简
化了工作，对于数据科学家，使用多个框架（例如，一个用于数据加载和处理，
一个用于训练，一个用于服务）更加常见。
你还可以将
Ray AIR
与
RLlib
结合使用，但目前集成度并不高。例
如，要将
RLlib
与
AIR Trainer
集成，你可以使用
RLTrainer
，它支持
传递标准
RLlib
算法的所有参数。训练完成后，你可以像处理其他
AIR Trainer
一样，将最终的
RL
模型存储在
AIR Checkpoint
中。要部
署已训练的
RL
模型，你可以通过同时传递检查点与
RLPredictor
类
来使用
Serve
的
PredictorDeployment
类。
API
可能面临变动，你可以随时在
AIR
文档（
https://oreil.ly/gB-wg
）
中查看示例。
10.3
适合
AIR
的任务
介绍了
AIR
及其基本概念，让我们扩展一下，讨论一下可以用
AIR
执行哪些任
务。在本书中，我们已经处理了所有这些任务，但是系统地回顾一下是很有好
处的。正如其名，
AIR
旨在处理
AI
项目中的常见任务。这些任务可以粗略地分
为以下几类：
无状态计算
例如，对数据进行预处理或计算一批数据上的模型预测等任务是无状态
的
注
4
。无状态任务可以独立并行计算。在第
2
章中我们对
Ray
任务的处理
就属于无状态计算。
AIR
主要使用
Ray ...
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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.