How to use custom functions for a model in a Sagemaker pipeline?

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If I want to use a custom function transformer in preprocessing, how do I ensure that it's detected at both pipeline building and deployment?

I'm building a sklearn pipeline, and in preprocessing I use a custom FunctionTransformer. In Sagemaker, I am able to train, evaluate, and register the model, but get the below error when I try to deploy it: AttributeError: Can't get attribute 'truncate_function' on <module '__main__' from '/miniconda3/bin/gunicorn'>

I've tried putting the functions into a helper.py file, and including it as a dependency during training, but then get the following error when evaluating in a ProcessingStep: "ModuleNotFoundError: No module named 'helper'.

dxu271
asked a year ago106 views
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