Migrating a model from one language or runtime to another is deceptively hard. The maths looks the same, but library defaults, floating-point behavior, and feature preprocessing all drift in subtle ways.
Parity is a deliverable, not a hope
Before changing anything, capture the legacy model behavior as a fixed test set: inputs and outputs. Every step of the migration is then measured against that baseline, so you know exactly when and where behavior diverges.
Migrate incrementally
- Reproduce the legacy pipeline end-to-end before optimizing anything.
- Compare outputs at each stage, not just the final prediction.
- Only refactor once parity is proven — never both at once.
Done this way, a migration becomes a controlled, observable process rather than a leap of faith.