[D] A worker instance holds down other workers when processing load is unevenly distributed

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I'm using Pytorch and I have an iterable dataset, let’s say I create 2 workers: worker 0 generates an audio clip and combines it with other pre-generated audio clips to create a data point, and workers 1 only combines pre-generated audio clips to create a data point. Naturally, worker 0 takes more time then worker 1 (audio clip generation and saving to the disk takes ≈ 0.8s while loading 12 audio clips takes 0.18s).