01Zalando · migration
Upgrading MLflow Pipelines Across a Python Version Boundary
Upgrading machine learning pipelines across a Python version boundary caused legacy MLflow model deserialization errors due to incompatible cloudpickle bytecode. To avoid costly model retraining at scale, the team developed a 'Load and Repack' technique to migrate models to a PythonModel wrapper and updated their architecture to rely on native serialization formats and standard wrappers.
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