You are managing an Azure Machine Learning workspace and have built a custom model that must be logged with MLflow. The model has the following characteristics:

• It is not natively supported by MLflow.
• It cannot be serialized using Pickle format.
• Its source code is complex.
• The associated Python library must be packaged with the model.

You need to create a custom model flavor to enable logging with MLflow.

What should you use?