fix: preprocess yielding whole dataset to each worker (axolotl-ai-cloud#2503) [skip ci]

Author: NanoCode012

src/axolotl/utils/data/sft.py

@@ -332,16 +332,23 @@ def load_tokenized_prepared_datasets(
         if cfg.local_rank == 0 and not cfg.skip_prepare_dataset:
             LOG.info(f"Saving merged prepared dataset to disk... {prepared_ds_path}")
             if isinstance(dataset, IterableDataset):
+                num_workers = cfg.dataset_processes
 
-                def gen_from_iter_ds(_ds, _=None):
-                    yield from _ds
+                def gen_from_iter_ds(_ds, worker_id: List[int], num_workers: List[int]):
+                    """Generator function to correctly splice the dataset for each worker"""
+                    for i, item in enumerate(_ds):
+                        if i % num_workers[0] == worker_id[0]:
+                            yield item
 
                 ds_from_iter = Dataset.from_generator(
                     functools.partial(gen_from_iter_ds, dataset),
                     features=dataset.features,
-                    num_proc=cfg.dataset_processes,
+                    num_proc=num_workers,
                     split=split,
-                    gen_kwargs={"_": list(range(cfg.dataset_processes))},
+                    gen_kwargs={
+                        "worker_id": list(range(num_workers)),
+                        "num_workers": [num_workers] * num_workers,
+                    },
                 )
                 ds_from_iter.save_to_disk(str(prepared_ds_path))
             else: