DataLoaderPrefetcher for quicker starts of training loops
It causes a segmentation fault in GPU tests (but works fine in casual settings -- probably too many daemonic threads spawned in tests when enabled by default, or otherwise some global state conflict). Maybe I'll revisit this later but don't want to invest more time into it right now: closing.
# What does this PR do ?

Removes/reduces the waiting on step 0 of a training loop for dataloading worker initialization. The waiting duration is specific to a given training setup and can range from a few seconds to a minute or two. An obvious factor is faster/slower disk/network, but also some settings e.g. using larger bucketing or shuffling buffers requires more time to pre-load data into memory. 

The main point is to trigger the actual initialization (which happens on `DataLoader.__iter__()`) at the time the dataloader is constructed, without blocking. Then it can pre-load the data concurrently to other stuff being initialized in training script and ideally it's ready to yield a mini-batch by the time the training loop starts.

**Collection**: ASR

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