[data][train] Minor rework of get_dataset_shard#55825
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Signed-off-by: Justin Yu <justinvyu@anyscale.com>
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This pull request refactors how dataset shards are provided to workers by introducing a DatasetShardProvider. This is a good abstraction that improves encapsulation. However, I've identified two critical regressions. First, the new implementation no longer evaluates callable datasets, which would break existing user code. Second, the TrainContext no longer correctly handles cases where no datasets are provided, which will lead to a runtime error. I've provided suggestions to fix both of these issues.
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Signed-off-by: Justin Yu <justinvyu@anyscale.com>
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Signed-off-by: Justin Yu <justinvyu@anyscale.com>
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release test to verify no regressions https://buildkite.com/ray-project/release/builds/54747 |
matthewdeng
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Aug 22, 2025
jugalshah291
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Adds a slim wrapper around dataset shard iterators passed to each worker. --------- Signed-off-by: Justin Yu <justinvyu@anyscale.com> Signed-off-by: jugalshah291 <shah.jugal291@gmail.com>
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Adds a slim wrapper around dataset shard iterators passed to each worker. --------- Signed-off-by: Justin Yu <justinvyu@anyscale.com> Signed-off-by: Douglas Strodtman <douglas@anyscale.com>
landscapepainter
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Adds a slim wrapper around dataset shard iterators passed to each worker. --------- Signed-off-by: Justin Yu <justinvyu@anyscale.com>
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Summary
Adds a slim wrapper around dataset shard iterators passed to each worker.
dataset_shardsdictionary access with a provider pattern that encapsulates dataset shard retrieval logicDatasetsSetupCallbackto returnDatasetShardProviderinstances instead of raw dataset shardsTrainContextand related classes to use the new provider patternDatasetShardMetadatawhich can be extended for more flexible dataset sharding configuration in the future.