aws / aws/sagemaker-python-sdk

@ remote support for multi-instance training job

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#4,125 1 comment 0 reactions 1 assignee Claimed by @nargokul View on GitHub
component: training remote-function type: feature request
Dominant language
Python
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Description

**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.

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