Calling SageMaker Notebook instance function by endpoint

Question

I am a newbie in AWS. Right now I have defined an image segmentation function in SageMaker notebook instance and this will return masks.

I didn't train my models there, what I have done is pip install models packages there, upload pre-trained weights manually. The rest is very similar to working in local machine: I imported package, load the weights, defined a function to take an image as input then outputs masks.

My question is: is there a way to host my function so that I can call it with URL endpoint + one image info, then it returns me masks in response?

Again I am so new to AWS and I begin to doubt SageMaker is not designed for this job... The reason I chose SageMaker is the need of computing capacity, I don't think I can do this job with pure lambda.

Yoav Zimmerman · Accepted Answer · 2020-07-07 15:51:54Z

0

SageMaker inference endpoints currently rely on an interface based on Docker images. At the base level, you can set up a Docker image that runs a web server and responds to the endpoints on the ports that AWS require. This guide will show you how to do it: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-inference-code.html.

This is an annoying amount of work. If you're using a well-known framework they have a container library that contains some boilerplate code you might be able to reuse: https://github.com/aws/sagemaker-containers. You might have to do some customization there.

Or don't use SageMaker inference endpoints at all :) If your model can fit within the size / memory restrictions of AWS Lambda, that is an easier option!

Full disclaimer, I'm working on a platform that competes with SageMaker: Model Zoo

answered Jul 7, 2020 at 15:51

Yoav Zimmerman

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