PyTorch datasets don't support multiprocessing

[jeremyjordan]

PyTorch's Dataloader has an argument for num_workers which can fetch items from your dataset in parallel using multiprocessing, but this requires your dataset to be able to be pickled so Python can distribute it across multiple processes.

Currently, if you try to use multiple workers for a muspy dataset you get the following error:

AttributeError: Can't pickle local object 'Dataset.to_pytorch_dataset.<locals>.TorchRepresentationDataset'

There's more context on the pickle issue in this Stackoverflow thread.

Here's a minimal reproducible example to test it out yourself:

import muspy
import torch

haydn = muspy. HaydnOp20Dataset("data/", download_and_extract=True).convert()
dataset = haydn.to_pytorch_dataset(representation="pianoroll")
dataloader = torch.utils.data.DataLoader(dataset, batch_size=1, num_workers=2)
batch = next(iter(dataloader))

I'm happy to open a PR with a fix for this, it mostly involves moving TorchRepresentationDataset and TorchMusicFactoryDataset to be defined outside of to_pytorch_dataset.