Unable to load the xgboost model after logging via mlflow. You get a "ModuleNotFoundError: No module named 'ml'" error message.

[Adam_Pavlacka]

When using MLflow to log a model, be aware of warnings like the one below:

WARNING mlflow.utils.requirements_utils: The following packages were not found in the public PyPI package index as of 2022-12-21; if these packages are not present in the public PyPI index, you must install them manually before loading your model: {'spark-xgboost'}

This warning indicates that if certain package artifacts, such as spark-xgboost, are not available in PyPI, they won't be logged in the requirements.txt file. To recreate the model environment, these dependencies must be installed explicitly.

Here's an example:

%sh
git clone https://github.com/sllynn/spark-xgboost.git;
cd spark-xgboost;
pip install -e .