aws / aws/sagemaker-python-sdk

@ remote support for multi-instance training job

已关闭
#4,125 1 条评论 0 个 reaction 已指派 1 人 已被 @nargokul 认领 在 GitHub 查看
component: training remote-function type: feature request
主要语言
Python
星标
2.3k
派生
1.3k
平均合并
1 天 22 小时
30 天内合并 PR
35

描述

**Describe the feature you'd like**
Need the ability to use @ remote to train on a multi-instance node for distributed training.

**How would this feature be used? Please describe.**
Distributed training packages like h2o can be used with @ remote. Currently @ remote restrict the instance count for training job to "One" instance

**Describe alternatives you've considered**
Use sagemaker.estimator.Estimator to configure distributed training job. This requires duplication of code when switching between local mode vs Instance based training.

**Additional context**
We are in the process of switching from SageMaker notebook instance to SageMaker Studio. SageMaker studio does not support local mode at this time. So, in order to test with local mode we are using @ remote. However, to train on large datasets we use distributed training. In Sagemaker Notebook Instance env, sagemaker.estimator.Estimator easily allowed us to switch between local and multi-instance based training. However, not having a SDK function for a comparable local/distributed training option in studio is causing a lot of rework of templates. Enhancing @ remote to train on multi-instance would mitigate the concern.

贡献指南

打开贡献指南

评估

这个 Issue 还没有评估数据。

把新 issue 发到你的邮箱

精选适合新手参与的 GitHub issue 摘要。