Reproducibility is a spectrum. A good starting point is to snapshot the exact version of the code that produced a model. Even better, you should snapshot the full dependency graph, including transitive dependencies, of all (compiled) libraries, which Metaflow does with @conda. Together with data snapshots, this gives a pretty good foundation for reproducibility.

Depending on the libraries you use, the exact results may or may not be reproducible on other architectures. If cross-platform reproducibility is important to you, you should choose your libraries accordingly. Metaflow provides the tools for choosing the level of reproducibility that your application requires.

Is there any library in the metaflow ecosystem that offers floating point determinism? I would like to read more, can you link somewhere?

Also, what tools does metaflow offers to control the level of reproducibility?