Kalyani Nikure

Thank you for reaching out! The latest SageMaker Studio release now offers increased shared memory on instances running Studio Apps. The memory size scales in proportion to the size of...

@Peter-Devine We are closing this issue due to inactivity. Please feel free to reopen the issue if suggested solution doesn't solve the issue for you. Thanks!

We have provided the fix for this dependency issue in sagemaker>=[v2.111.0](https://github.com/aws/sagemaker-python-sdk/releases/tag/v2.111.0). Please feel free to open this issue if there are any concerns.

`The Triton Python backend uses shared memory (SHMEM) to connect your code to Triton. SageMaker Inference provides up to half of the instance memory as SHMEM so you can use...

@jmahlik Kindly take a look at the failing integ-tests.

@Shaked35 Does the suggested resolution works for you? Can you confirm?

> > Looks like the image isn't available yet, per here: > > [aws/deep-learning-containers@`master`/available_images.md](https://github.com/aws/deep-learning-containers/blob/master/available_images.md?rgh-link-date=2023-06-16T19%3A22%3A00Z) > > Do we know if this is being worked on or how I could contribute...

@phall1 Can you check with someone in DLC if transformers 4.29 is supported with PT 2.0. If not, can we close this PR?

@saimidu Can we have the config updated in SDK?

@oleksiishevchuk Please open this issue with DLC who is an upstream dependency to release these images and then we can rework on this PR. Meanwhile I advice you to use...