vision classification QAT tutorial: fix for DDP (redo)

[vkuzo]

Summary:

Redo of #2191

Makes the classification QAT tutorial not crash when used
with DDP. There were two issues:

1. the model was moved to GPU before the observers were added, and they
   are created on CPU. In the context of this repo, the fix is to finalize
   the model before moving to GPU. We can potentially follow up with a
   better error message in the future, in a separate PR.
2. the QAT conversion was running on the DDP'ed model, which had various
   problems. The fix is to unwrap the model from DDP before cloning it for
   evaluation.

There is still work to do on verifying that BN is working correctly in
QAT + DDP, but saving that for a separate PR.

Test Plan:

python -m torch.distributed.launch --use_env references/classification/train_quantization.py --data-path {path_to_imagenet_1k} --output_dir {output_dir}

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Subscribers:

Tasks:

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[fmassa]

Thanks a lot!