September 2024
Intermediate to advanced
448 pages
13h 5m
Spanish
Content preview from Aprendizaje profundo a escala
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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.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.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.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.
Capítulo 7. Paralelismo de datos
Este trabajo se ha traducido utilizando IA. Agradecemos tus opiniones y comentarios: translation-feedback@oreilly.com
En el Capítulo 6, leíste sobre los fundamentos del entrenamiento distribuido y exploraste varias técnicas de paralelización para escalar tu carga de trabajo de entrenamiento de modelos. Partiendo de los conceptos de los capítulos anteriores, este capítulo profundizará en la técnica de paralelización de datos. El objetivo de este capítulo es proporcionar una comprensión completa de cómo se realiza el entrenamiento paralelo de datos. Para cumplir este objetivo, introducirá técnicas de partición de datos, explorará cómo se implican los trabajadores en la distribución de la carga y discutirá conceptos relacionados a lo largo del camino. El material de este capítulo es práctico, por lo que la mayoría de los escenarios incluirán ejemplos dedicados que recorren los conceptos.
Partición de datos
Como expuso en el capítulo anterior, el paralelismo de datos escala el entrenamiento particionando el corpus de entrenamiento entre los trabajadores del sistema. Crear subconjuntos de igual tamaño de tu corpus de entrenamiento es un ejemplo de estrategia de partición muy simplista. Con este enfoque, si tienes 10 trabajadores y tu corpus de entrenamiento principal tiene 100 registros con ID [0, 1, 2, ... 99], se dividirá (es decir, se fragmentará o subconjuntará) en 10 partes, y cada trabajador recibirá 10 registros únicos compensados, por ejemplo, ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
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.