Enable faster training by pinning data to memory

[JRMeyer]

>>> btomtom5
[June 21, 2019, 5:55am]

Is there a reason that the DataLoader sets pin_memory=false?

loader = DataLoader(
dataset,
batch_size=c.eval_batch_size if is_val else c.batch_size,
shuffle=False,
collate_fn=dataset.collate_fn,
drop_last=False,
sampler=sampler,
num_workers=c.num_val_loader_workers
if is_val else c.num_loader_workers,
pin_memory=False)
return loader

As I understand it, pin_memory speeds up transfers from host to device.
Perhaps it's because it has been determined that this is not a
bottleneck in the training?

[This is an archived TTS discussion thread from discourse.mozilla.org/t/enable-faster-training-by-pinning-data-to-memory]

[JRMeyer]

>>> erogol
[June 21, 2019, 8:18am]

This is one of the pytorch core developers.

> try to use pin_memory, but if you are seeing system freeze or swap
> being used a lot, disable it.

So this is not the case for my training. But consider it for your own.

[Archived Post]

[JRMeyer]

>>> btomtom5
[June 21, 2019, 4:47pm]

! Makes sense!

[Archived Post]