Add Speaker Diarization and Verification heads
# What does this PR do?

This adds the Audio Frame classification (equivalent of token classification) and X-vector (speaker embedding extraction) heads to `Wav2Vec2` and `UniSpeech-SAT` models. The target tasks for the heads are SUPERB's Speaker Diarization and Speaker Verification respectively. These were mainly motivated by `UniSpeech-SAT`, since the model performs better on those tasks, rather than on ASR.

Sources for the models and weights from the SUPERB's `s3prl` framework:
* `ModelForAudioFrameClassification`: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/diarization/model.py (with `use_rnn=False`)
* `ModelForXVector`: https://github.com/s3prl/s3prl/blob/master/s3prl/downstream/sv_voxceleb1/model.py#L261

The heads for both W2V2 and US-SAT were finetuned from scratch, since the official checkpoints use custom (better) heads that are incompatible with SUPERB's evaluation protocol.

@patrickvonplaten the code is ready for a full review now. I'll post the model links and evaluation results (DER and EER metrics) shortly.<|||||>checking tomorrow after the `-large` checkpoint problem is solved :-)