How to access deployed container and edit score script
I used Azure ML studio to set up a custom environment (base image using mcr.microsoft.com/azureml/openmpi4.1.0-cuda11.6-cudnn8-ubuntu20.04) and an online endpoint using that env.
The endpoint managed to deploy successfully using a Standard_NC4as_T4_v3 SKU. I would like to:
- Access the container to check if torch is accessing the GPU using terminal
- Edit the score script
I am able to do so locally but how do I do so after deploying online?
@He Cheng Hui Here is the Doc to update the deployed online endpoint using the SDK.
And if you are simply trying to debug and redeploy, doing so locally Please follow the below doc. https://learn.microsoft.com/en-us/azure/machine-learning/how-to-troubleshoot-deployment#debug-locally
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Thank you. I have tried following the Doc to update the online deployment but I got the following error:
I have tried doing locally first but i wasn't able to get the container to use my GPU (window host, linux container using this).