feat: use async dataset for index training #3669
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chebbyChefNEQ
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Apr 11, 2025
| filter=filt, | ||
| ) | ||
| ) as torch_ds: | ||
| loader = torch.utils.data.DataLoader( |
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every thing below here are just indentation change
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we previously disabled async dataset for index training because it required setting global multiprocess context to
spawnThis PR makes the async dataset class have an internal mp context what is always spawn. Also enable async dataloading for vector index training
Async dataset move heavy compute to a subprocess, therefore reducing the time, for which we need to wait when loading batches for the GPU