RuntimeError: DataLoader worker (pid 31433) is killed by signal: Aborted. about vits

[heesuju]

I checked dataloader.py and it seems like function _MultiProcessingDataLoaderIter.del is being called when dataloader iterators are created within a subprocess.
From what I can understand, when a process ends it calls del on the iterator.
If the dataloader iterator is still referenced in a function the dataloader workers are not notified before they're killed, hence causing this error.
Since this problems occurs when memory is being freed after a process ends, it does not seem like it will affect the training process.
I've also checked the result after 3000 epochs, and the model doesn't have any problems during inference so far.
However, this is just a guess based on my experience and surface-level knowledge.
It would be great if anyone could actually confirm this.

[heesuju]

I got the exact same error when training with a batch size of 32 on torch 2.0.1
On other forums, the popular solution was to change the "num_workers" value when initializing the dataloader.
I have a feeling this is not the solution, however, as num_workers is set as 8 by default, and lowering this value will only make the training slower, not to mention the fact that VITS is only using 1% of my shared memory during training.
Does anyone know if this error affects training or why it happens at all?