Description
Is your feature request related to a problem? Please describe.
No
Describe the solution you'd like
If you build a custom container for SageMaker, you can use the sagemaker-training-toolkit library to provide script mode execution and be able to load user training module from an Amazon S3 archive, following the same approach of the open source deep learning containers implemented by AWS.
Then, running training with this container with the SM Python SDK would benefit from the ability to instantiate the Framework estimator class, in order to leverage on the SDK functionalities which build the sourcedir.tar.gz and upload it to Amazon S3 before starting the training job.
Describe alternatives you've considered
The alternative solution is extending the Framework class for the specific use case.
Additional context
Examples on how to build custom training containers for Amazon SageMaker using the training toolkit. The last example shows how to extend the Framework estimator class.
https://github.com/awslabs/amazon-sagemaker-examples/tree/master/advanced_functionality/sagemaker-custom-training-containers