Add collate_fn parameter support to DataLoader#48
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- Add collate_fn parameter to core DataLoader class for custom batch collation - Implement collate_fn support across all backends (JAX, PyTorch, TensorFlow) - JAX backend applies collate_fn to batched data from dataset indexing - PyTorch backend uses custom collate_fn or defaults to _numpy_collate - TensorFlow backend uses tf.data.Dataset.map() for collate_fn application - Add Callable import to typing imports for proper type annotations - Add comprehensive test_collate_fn function in tests.ipynb - Update BaseDataLoader interface to include collate_fn parameter - Add documentation example in core.ipynb demonstrating usage The collate_fn parameter behaves consistently with PyTorch's DataLoader, allowing users to customize how individual samples are combined into batches.
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- Fix test_collate_fn to properly handle PyTorch list format vs JAX batched format - Add support for HuggingFace datasets with PyTorch backend (list of dicts) - Ensure collate_fn works correctly across all backends (JAX, PyTorch, TensorFlow) - All collate_fn tests now pass for available backends
- Add tf_collate_wrapper to handle TensorFlow's argument unpacking behavior - TensorFlow map() calls functions with unpacked args (features, labels) - Wrapper packs them back into tuple format expected by collate_fn - Ensures result is properly unpacked for TensorFlow consumption - Fixes TypeError in CI when TensorFlow is installed
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This fixes #38
Summary
collate_fnparameter toDataLoaderfor custom batch collation functionalityChanges
collate_fnparameter with proper type annotationscollate_fnto batched data from dataset indexingcollate_fnor defaults to_numpy_collatetf.data.Dataset.map()forcollate_fnapplicationCallableimport to typing importstest_collate_fnfunction intests.ipynbwith cross-backend validationcore.ipynbBehavior
The
collate_fnparameter behaves consistently with PyTorch's DataLoader, allowing users to customize how individual samples are combined into batches. Whencollate_fn=None, each backend uses its default collation behavior.Test plan
collate_fnfunctionality with JAX backendcollate_fnfunctionality with PyTorch backendcollate_fnfunctionality with TensorFlow backendcollate_fn=Noneuses default behaviornbdev_testto ensure all tests pass