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Version hash registry

As explained in Designing Deep Learning Systems: A guide for software engineers

An internal registry that maps training-dataset version hashes to their corresponding versioned snapshots.

A version hash registry maps a generated hash for selected dataset commits to an immutable versioned snapshot. The snapshot represents the training files and supports reproducible retrieval after preparation completes. section 2.2.4

A dataset management service uses the registry to:

  • Return an existing snapshot when the same commit-selection hash is requested, avoiding duplicate preparation work. section 2.2.4

Hash-based fetch

A preparation request filters commits, generates a hash from the selected commit IDs, and stores or reuses the corresponding snapshot. A later fetch supplies the dataset ID and hash to retrieve it.

How Designing Deep Learning Systems: A guide for software engineers covers it

How deep it goes
Explains hash creation, snapshot reuse, lookup, and download readiness, but not the registry’s storage schema.
Examples
Uses filtered commit lists, generated version hashes, FetchTrainingDataset requests, and download URLs as concrete artifacts.
What it assumes
Assumes dataset commits, tag filtering, dataset preparation, and fetch-request concepts.
What you can do after
Operate dataset preparation and retrieval through stable hashes while avoiding repeated snapshot construction.
How it connects
Connects dataset versioning with immutable snapshots, reproducibility, caching, commit filtering, and dataset-fetching APIs.
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