How to integrate two models in sequential order in one endpoint?
Question:
Answers:
Pipeline Model (sequential models)
There is a specific mode in SageMaker:
Look at PipelineModel.
You can pass a list of sagemaker.Model objects in the order you want
the inference to happen.
This is an official AWS example to follow:
Train register and deploy a pipeline model
from sagemaker import PipelineModel
pipeline_model = PipelineModel(
models=[model_0, model_1, ...],
role=role,
sagemaker_session=pipeline_session
)
It works like a normal SageMaker Model, in fact you have the normal deployment method.
You can also follow this guide that show how to deploy an Xgboost model binary built for a developer, where a post-processing layer is added through an inference pipeline in sagemaker, deploying an endpoint.
Pipeline Model (sequential models)
There is a specific mode in SageMaker:
Look at PipelineModel.
You can pass a list of sagemaker.Model objects in the order you want
the inference to happen.
This is an official AWS example to follow:
Train register and deploy a pipeline model
from sagemaker import PipelineModel
pipeline_model = PipelineModel(
models=[model_0, model_1, ...],
role=role,
sagemaker_session=pipeline_session
)
It works like a normal SageMaker Model, in fact you have the normal deployment method.
You can also follow this guide that show how to deploy an Xgboost model binary built for a developer, where a post-processing layer is added through an inference pipeline in sagemaker, deploying an endpoint.