I need to deploy a custom object detection model using tensorflow AWS API following this tutoriel : https://github.com/aws-samples/amazon-sagemaker-tensorflow-object-detection-api I'm getting this error whenever I try to deploy using this code :

predictor = model_endpoint.deploy(initial_instance_count=1, instance_type='ml.m5.large')

The problem:

update_endpoint is a no-op in sagemaker>=2.

Can you help me to solve this please ? Or can you tell me how to deploy a custom detection model on sagemaker ?

CodePudding user response：

Can you try using model_endpoint.update_endpoint(...)? Alternatively, you can find examples here for deploying a Tensorflow model - https://github.com/RamVegiraju/SageMaker-Deployment/tree/master/RealTime/Script-Mode/TensorFlow.

CodePudding user response：

According to the documentation:

The update_endpoint argument in deploy() methods for estimators and models is now a no-op. Please use sagemaker.predictor.Predictor.update_endpoint() instead.

However, I recently successfully deployed a TensorFlow 2.7.0 model with SageMaker 2.70.0, as far as I know this is a warning not a breaking-change error.

The errors that you have will have to do with other problems, not this one (bear in mind that it is a warning, not a breaking change, as of the time of this comment versions of the dependencies).