reshard-c4-data

To split large datasets into size-limited and count-limited shards, you reorganize files into a multi-level directory structure that respects maximum file sizes and items per folder while generating metadata for reconstruction.

Data resharding is the process of reorganizing files into compliant partitions. It is needed when preparing large datasets like C4 for distributed training, ensuring directories adhere to specific size and count constraints.

To verify data integrity after reorganizing files into shards, use generated reconstruction metadata that links original files to their new locations and includes checksums for validation.

Directory hierarchy levels for partitioned files are determined through recursive constraint calculation, ensuring the generated folder layout satisfies both per-directory item count and file size limits.

Yes, you can use this resharding approach for large image collections. It applies to any scenario requiring size-limited and count-limited data partitions across a hierarchical directory structure.

Yes, resharding a dataset generates reconstruction metadata that maps original files to their shard locations and includes checksums, allowing you to verify integrity and restore the original layout.