How to run a batch transformation with custom inference code in sagemaker pipeline?

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based on the docs here , https://sagemaker-examples.readthedocs.io/en/latest/sagemaker-pipelines/tabular/abalone_build_train_deploy/sagemaker-pipelines-preprocess-train-evaluate-batch-transform.html#Define-a-Transform-Step-to-Perform-Batch-Transformation, after creating a model, the example shows a batch transform job is run. how to include any custom inference script that is required to get an inference from the model.

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The inference code plus model artifacts information is defined with SageMaker Model. In SageMaker Model, you have the option of which model artifact to use plus which inference script to use, usually defined as entry_point in the model object.

To be more specific, after training, you need a step to create/register the model as described here. During this process, you could choose appropriate model artifacts with inference scripts.

Then this model could be defined to be used in a transform job.

AWS
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