aws / aws/sagemaker-python-sdk

@ remote support for multi-instance training job

Chiusa
#4,125 1 commento 0 reazioni 1 assegnatario Rivendicata da @nargokul Vedi su GitHub
component: training remote-function type: feature request
Lingua principale
Python
Stelle
2.3k
Fork
1.3k
Merge medio
1g 22h
PR unite (30g)
35

Descrizione

**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.

Guida per i contributori

Apri la guida per i contributori

Valutazione

Questa issue non è ancora stata valutata.

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.