How to select single components when installing SageMaker ?

[rfarahmand]

I believe the new SageMaker is quite large in size when installed like pip install sagemaker ? Can you confirm how big it has become since SageMaker 2.* ? and is there a way to select different modules (or dependencies ) when installing it? like pip install sagemaker[train] or pip install sagemaker[xgboost] if I only need to train XGboost for example, and do not want all the PyTorch and all other cuda dependencies that makes it quite large for some use cases ( e.g. in a lambda) ? Could you advise and/or help with this regard?

[gbeasleytombola]

I'd also like to understand if there's a good way to deal with this. Sagemaker 2.* could be installed in less than 1GB and easy enough to be part of a lambda or container deployed to lambda. Now it appears to be 8GB minimum which would mean a significant change to how we deploy some services if upgrading to Sagemaker 3.*. A way to install without PyTorch/cuda would be incredibly helpful