Hey everyone, first off thank you for developing this amazing library.
🐛 Describe the bug
So apparently there is a bug, which I am not sure if it is a bug related to avalanche or mps, but if you attempt to run the multihead example without the num_workers parameter set (which I would assume would default to 1), the training loop stops working and a KeyError is raised, with a seemingly random key.
🐜 To Reproduce
In lines 71 and 72 of the multihead.py example just replace with the following lines:
strategy.train(train_task)strategy.eval(test_stream)
🦋 Additional context
The issue only seems to occur when running the script on 'mps' devices, as when running the same piece of code on a server with cuda the issue does not persust
Hey everyone, first off thank you for developing this amazing library.
🐛 Describe the bug So apparently there is a bug, which I am not sure if it is a bug related to avalanche or mps, but if you attempt to run the multihead example without the
num_workersparameter set (which I would assume would default to 1), the training loop stops working and a KeyError is raised, with a seemingly random key.🐜 To Reproduce In lines 71 and 72 of the multihead.py example just replace with the following lines:
strategy.train(train_task)strategy.eval(test_stream)🦋 Additional context The issue only seems to occur when running the script on 'mps' devices, as when running the same piece of code on a server with cuda the issue does not persust