aws / aws/sagemaker-python-sdk

custom_overrides flag in sdk

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component: training type: feature request
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Python
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描述

Describe the feature you'd like
Add a flag that can be passed to the sagemaker-training-toolkit from an estimator that allows a user to provide: custom_override=dict[list,list] (default can be None)

How would this feature be used? Please describe.
This would enable the sagemaker-training-toolkit to have additional functionality where users could override commands and provide their own custom launch scripts. For instance, rather than having to use MPI, I could use torch.distributed.launch, deepspeed, or my fork of any of the above.

Describe alternatives you've considered
You could embed these into hyperparameters but this would be a poor user experience. You could use environment variables, but those don't transfer to local sessions (previously listed as a bug).

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