[TTS] GAN-based spectrogram enhancer
# What does this PR do ?

Add a GAN-based spectrogram enhancer to NeMo.

The intended purpose is to add details to blurry spectrograms from TTS models like FastPitch.

**Collection**: TTS

# Changelog 
- Add the spectrogram enhancer NeMo model
- Add example config and training script

# Usage
Given a trained model,
```python
model = SpectrogramEnhancer.restore_from("checkpoint.nemo")
with torch.no_grad():
    # spectrograms :: B x 80 x L
    # lengths  :: B - the usual LongTensor with lengths or every spectrogram in the batch
    enhanced_spectrograms = model.forward(condition=spectrograms, lengths=lengths)
    # enhanced_spectrograms = B x 80 x L
```

# Before your PR is "Ready for review"
**Pre checks**:
- [x] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in the community is free to review the PR once the checks have passed. 
[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Based on https://github.com/lucidrains/stylegan2-pytorch (MIT License)
