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For a dataset that is loaded on multiple cpu cores, sometimes the fork method creates problems (with polars for example) and the spawn method is more adapted.
Your contribution
I could do a PR. A fix could be to add one more parameter to Trainer and pass it to the Dataloader down the line.
The text was updated successfully, but these errors were encountered:
Feature request
In Huggingface Trainer, allow to pass the multiprocessing context : https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader
Motivation
For a dataset that is loaded on multiple cpu cores, sometimes the fork method creates problems (with polars for example) and the spawn method is more adapted.
Your contribution
I could do a PR. A fix could be to add one more parameter to Trainer and pass it to the Dataloader down the line.
The text was updated successfully, but these errors were encountered: