You can debug your scoring script locally by using the Azure Machine Learning inference HTTP server. The HTTP server is a Python package that exposes your scoring function as an HTTP endpoint and wraps the Flask server code and dependencies into a singular package. It's included in the [prebuilt Docker images for inference](concept-prebuilt-docker-images-inference.md) that are used when deploying a model with Azure Machine Learning. Using the package alone, you can deploy the model locally for production, and you can also easily validate your scoring (entry) script in a local development environment. If there's a problem with the scoring script, the server will return an error and the location where the error occurred.
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